427 results for "fc26 pc Besuche die Website Buyfc26coins.com. Schnelle Lieferung, guter Support..i0HF"

in 81.79 milliseconds.

• Colon Cancer Family Registry (Colon CFR)

  The Colon Cancer Family Registry Cohort (CCFRC www.coloncfr.org) is a cohort of families recruited through six study sites located in the USA, Canada, Australia, and New Zealand. The CCFRC was formed as a resource to support studies on the etiology, prevention, and clinical management of colorectal cancer. Recruitment protocols fall broadly into two main categories: population-based and clinic-based ascertainment. Between 1998 and 2013, the CCFR recruited and interviewed probands who were either recently diagnosed with colorectal cancer that was reported to state or regional population cancer registries in the United States (Washington, California, Arizona, Minnesota, Colorado, New Hampshire, North Carolina, and Hawaii), Australia (Victoria), and Canada (Ontario) or were from multiple-case families referred to family-cancer clinics in the United States (Mayo Clinic in Rochester, Minnesota, and Cleveland Clinic in Cleveland, Ohio), Australia (Melbourne, Adelaide, Perth, Brisbane, and Sydney), New Zealand (Auckland), and Canada. Cases with known familial adenomatous polyposis were excluded. Once recruited, probands were asked for permission to contact their relatives for recruitment. Collectively, we have enrolled 42,49874 participants in 15,048 families who participated in standardized protocols used to collect information regarding family cancer history and colorectal cancer risk factors and biospecimens. All participants of population-based case families (excluding control-families) and clinic-based families are asked to provide updates on their personal and family history of cancer as well as their history of surgery, cancer screening, and some risk factors every 4-5 years either by telephone interview or by self-completed questionnaire via mail or online (PMID: 17982118).

  Study phs002733

• Target sequencing of 27 cancer-predisposing genes in Japanese colorectal cancer patients

  Background: National Comprehensive Cancer Network (NCCN) recently recommended germline genetic testing for all pancreatic cancer patients. However, the genes targeted by genetic testing and the feasibility of selecting patients likely to carry pathogenic variants have not been sufficiently verified. The purpose of this study was to genetically characterize Japanese patients and examine whether the current guideline is applicable in this population. Methods: Using targeted sequencing, we analyzed the coding regions of 27 cancer-predisposing genes in 1,005 pancreatic cancer patients and 23,705 controls in Japan. We compared the pathogenic variant frequency between cases and controls and documented the demographic and clinical characteristics of carrier patients. We then examined if it was possible to use machine learning to predict carrier status based on those characteristics. Findings: We identified 205 pathogenic variants across the 27 genes. Pathogenic variants in BRCA2, ATM, and BRCA1 were significantly associated with pancreatic cancer. Characteristics associated with carrier status were inconsistent with previous investigations. Machine learning classifiers had a low performance in determining the carrier status of pancreatic cancer patients, while the same classifiers, when applied to breast cancer data as a positive control, had a higher performance that was comparable to that of the NCCN guideline. Interpretation: Our findings support the clinical significance of multigene panel testing for pancreatic cancer and indicate that at least 3.4% of Japanese patients may respond to poly (ADP ribose) polymerase inhibitor treatments. The difficulty in predicting carrier status suggests that offering germline genetic testing for all pancreatic cancer patients is reasonable.

  Study JGAS000346

• Target sequencing of 27 cancer-predisposing genes in Japanese pancreatic cancer patients

  Background: National Comprehensive Cancer Network (NCCN) recently recommended germline genetic testing for all pancreatic cancer patients. However, the genes targeted by genetic testing and the feasibility of selecting patients likely to carry pathogenic variants have not been sufficiently verified. The purpose of this study was to genetically characterize Japanese patients and examine whether the current guideline is applicable in this population. Methods: Using targeted sequencing, we analyzed the coding regions of 27 cancer-predisposing genes in 1,005 pancreatic cancer patients and 23,705 controls in Japan. We compared the pathogenic variant frequency between cases and controls and documented the demographic and clinical characteristics of carrier patients. We then examined if it was possible to use machine learning to predict carrier status based on those characteristics. Findings: We identified 205 pathogenic variants across the 27 genes. Pathogenic variants in BRCA2, ATM, and BRCA1 were significantly associated with pancreatic cancer. Characteristics associated with carrier status were inconsistent with previous investigations. Machine learning classifiers had a low performance in determining the carrier status of pancreatic cancer patients, while the same classifiers, when applied to breast cancer data as a positive control, had a higher performance that was comparable to that of the NCCN guideline. Interpretation: Our findings support the clinical significance of multigene panel testing for pancreatic cancer and indicate that at least 3.4% of Japanese patients may respond to poly (ADP ribose) polymerase inhibitor treatments. The difficulty in predicting carrier status suggests that offering germline genetic testing for all pancreatic cancer patients is reasonable.

  Study JGAS000327

• A Single Complex Agpat2 Allele In A Patient With Partial Lipodystrophy

  Genetic lipodystrophies are a group of rare syndromes associated with major metabolic complications - including severe insulin resistance, type 2 diabetes mellitus, and hypertriglyceridemia - which are classified according to the distribution of adipose tissue. Lipodystrophies can be present at birth or develop during life and can range from local to partial and general. With at least 18 different genes implicated so far, definite diagnosis can be challenging due to clinical and genetic heterogeneity. In an adult female patient with clinical and metabolic features of partial lipodystrophy we identified via whole genome sequencing a single complex AGPAT2 allele [V67M;V167A], functionally equivalent to heterozygosity. AGPAT2 encodes for an acyltransferase implicated in the biosynthesis of triacylglycerol and glycerophospholipids. So far homozygous and compound heterozygous mutations in AGPAT2 have only been associated with generalized lipodystrophy. A SNP risk score analysis indicated that the index patient is not predisposed to lipodystrophy based on her genetic background. The partial phenotype in our patient is therefore more likely associated to the genetic variants in AGPAT2. To test whether the resulting double-mutant AGPAT2 protein is functional we analysed its in vitro enzymatic activity via mass spectrometry. The resulting AGPAT2 double mutant is enzymatically inactive. Our data support the view that the current classification of lipodystrophies as strictly local, partial or generalized may have to be re-evaluated and viewed more as a continuum, both in terms of clinical presentation and underlying genetic causes. Better molecular understanding of lipodystrophies may lead to new therapies to treat adipose tissue dysfunction in common and rare diseases.

  Study EGAS00001003177

• Comparison of the diagnostic yield of aCGH and NGS across different neurodevelopmental disorders

  Current recommendations for the genetic diagnosis of neurodevelopmental disorders (NDDs) do not include the use of next generation sequencing (NGS) and are still based on chromosomal microarrays, such as comparative genomic hybridization array (aCGH). The present study compares the diagnostic yield obtained by aCGH and clinical exome sequencing in NDD globally and its spectrum of disorders. To that end, 1412 patients clinically diagnosed with NDDs and studied with aCGH were classified into phenotype categories: Global developmental delay/intellectual disability (GDD/ID); autism spectrum disorder (ASD); and Other NDDs. These categories were further subclassified into subcategories, based on the most frequent accompanying signs and symptoms: isolated forms, forms with epilepsy; forms with micro or macrocephaly and syndromic forms. A subset of 245 patients of the 1412 were subjected to clinical exome sequencing. Diagnostic yield of aCGH and clinical exome sequencing, expressed as the number of solved cases, was compared for each phenotype category and subcategory. Clinical exome sequencing was superior than aCGH for all cases except for isolated ASD, with no cases solved by NGS. Globally, clinical exome sequencing solved 20% of cases (versus 5.7% by aCGH) and the diagnostic yield was highest for all forms of GDD/ID and lowest for Other NDDs (7.1% versus 1.4% by aCGH) and ASD (6.1% versus 3% by aCGH). In the majority of cases, diagnostic yield was higher in the phenotype subcategories than in the mother category. These results support the use of NGS as the first-tier test in the diagnostic algorithm of all NDDs followed by aCGH when necessary.

  Study EGAS00001004949

• Sudden Cardiac Death in Heart Failure Trial (SCD-HeFT-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives The Sudden Cardiac Death in Heart Failure Trial (SCD-HeFT) was designed to evaluate the hypothesis that amiodarone or a conservatively programmed shock-only, single-lead implantable cardioverter defibrillator (ICD) would decrease the risk of death from any cause in a broad population of patients with mild-to-moderate heart failure. Background Patients with congestive heart failure (CHF) can die suddenly and unpredictably from arrhythmia despite the use of proven medical therapies, such as beta-blockade. Two approaches have been developed to prevent sudden death among patients with CHF: therapy with amiodarone and therapy with an ICD. However, most of the mortality data on amiodarone and ICD therapy at the time of the study had been obtained in clinical trials performed after myocardial infarction in patients without CHF or those with ventricular arrhythmias. Thus, more data was needed to guide these therapies in patients who did not meet these criteria. Participants There were a total of 2521 participants. 847 were randomly assigned to placebo, 845 to amiodarone, and 829 to ICD therapy. Design Before randomization, participants underwent electrocardiography, a 6-minute walk test, 24-hour ambulatory electrocardiography, liver and thyroid function studies, and chest radiography. Participants were required, if clinically reasonable, to receive treatment with a beta-blocker and an angiotensin-converting-enzyme inhibitor, as well as an aldosterone antagonist, aspirin, and statins, when appropriate. Participants were randomly assigned in equal proportions to receive placebo, amiodarone, or a single-chamber ICD programmed to shock-only mode. Participants assigned to amiodarone or matching placebo began therapy as outpatients immediately after randomization. Placebo and amiodarone were administered as a loading dose of 800 mg/day for one week, 400 mg/day for three weeks, and then as a daily maintenance dosage according to weight and bradycardia status. Participants assigned to ICD therapy received their device a median of three days after randomization. The goal of ICD therapy was to treat only rapid, sustained ventricular tachycardia or ventricular fibrillation. Dual-chamber or biventricular devices, or antitachycardia or rate-response pacing therapies were not permitted. The ICD was uniformly programmed to have a detection rate of 187 beats per minute or more. Antibradycardia pacing was initiated only if the intrinsic rate decreased to less than 34 beats per minute. Median follow-up was 45.5 months. The primary end point was death from any cause. Secondary outcome measures included cardiac mortality, arrhythmic mortality, morbidity, quality of life, and incremental cost-effectiveness of the interventions. Each active treatment arm was compared to the placebo drug arm. Conclusions In participants with NYHA class II or III CHF and LVEF of 35% or less, amiodarone had no favorable effect on survival, whereas single-lead, shock-only ICD therapy reduced overall mortality by 23%.

  Study phs003654

• Resuscitation Outcomes Consortium (ROC) Trauma Epidemiologic Registry (Trauma Epistry) (ROC-Trauma Epistry-BioLINCC)

  Data Access NOTE: Please refer to the "Authorized Access" section below for information about how access to the data from this accession differs from many other dbGaP accessions.Available Data: This dataset only includes traumatic injury participants. For ROC cardiac arrest Epistry data please see: ROC-Cardiac Epistry 1 and 2 and ROC-Cardiac Epistry 3.Objectives: To build a prospective population-based registry of participants with out-of-hospital traumatic injury responded to by Emergency Medical Services (EMS). Specific aims included: to establish whether the results of Resuscitation Outcomes Consortium (ROC) trials can be generalized to the larger population of people that experience traumatic injury; to more fully establish the burden of traumatic injury; and to examine the relationships between variation in EMS structure and process, regional and periodic factors, and participant outcomes.Background: Traumatic injury is a major public health problem generating substantial morbidity, mortality, and economic burden on society. The majority of seriously injured persons are initially evaluated and cared for by prehospital providers, however the effect of EMS systems, EMS clinical care, and EMS interventions on trauma patient outcomes is largely unknown. EMS factors such as service level, number of responding providers, use of procedures or drugs in the field, training, quality assurance/feedback, and response time intervals also vary significantly by region.The Resuscitation Outcomes Consortium (ROC) was established in 2004 to conduct clinical research in the areas of cardiopulmonary arrest and life-threatening traumatic injury with the overall goal of improving resuscitation outcomes. Previous trauma registries have generally focused primarily on hospitalized patients with limited prehospital information. Registries may also exclude trauma cases at far ends of the spectrum, such as those who die in the field or in a non-trauma center and/or patients that are treated and released. These limitations do not allow for detailed, outcome-based assessments of EMS system factors necessary to define prehospital resuscitation best practices. Therefore there was a need for standardized data collection of out-of-hospital traumatic injuries matched to hospital-based outcomes in diverse geographic locations in order to identify the independent effects of prognostic or treatment factors accounting for variations in survival. Participants: The registry included 13,830 traumatic events from 264 EMS agencies transporting to 287 acute care hospitals from the following regional centers: Birmingham, Alabama; Dallas, Texas; Iowa City, Iowa; Milwaukee, Wisconsin; Pittsburgh, Pennsylvania; Portland, Oregon; San Diego, California; Seattle/King County, Washington; Ottawa, Ontario; Toronto, Ontario; and Vancouver, British Columbia.Design: ROC Epistry collected standardized data regarding episode-specific factors, participant demographics, clinical information, pre-hospital interventions and disposition, hospital information, and participant outcome for all out-of-hospital traumatic injuries in the ROC regions. Cases were identified through review of emergency response system records including dispatch centers, EMS ground agencies, and air medical services. Out-of-hospital data were extracted from existing databases whenever possible and augmented with targeted review of EMS reports. Hospital data were abstracted directly from the hospital file in most cases. Sites submitted data using a web-based interface or batch uploads (Newgard, et al., 2008, PMID: 18482792).

  Study phs003809

• Elevated somatic mutation burdens in normal human cells due to defective DNA polymerases

  Mutation accumulation over time in normal somatic cells contributes to cancer development and is proposed as a cause of ageing. DNA polymerases POLE and POLD1 replicate DNA with high fidelity during normal cell divisions. However, in some cancers defective proofreading due to acquired mutations in the exonuclease domains of POLE or POLD1 causes markedly elevated somatic mutation burdens with distinctive mutational signatures. POLE and POLD1 exonuclease domain mutations also cause familial cancer predisposition when inherited through the germline. Here, we sequenced normal tissue DNA from individuals with germline POLE or POLD1 exonuclease domain mutations. Increased mutation burdens with characteristic mutational signatures were found to varying extents in all normal adult somatic cell types examined, during early embryogenesis and in sperm. Mutation burdens were further markedly elevated in neoplasms from these individuals. Thus human physiology is able to tolerate ubiquitously elevated mutation burdens. Indeed, with the exception of early onset cancer, individuals with germline POLE and POLD1 exonuclease domain mutations are not reported to show abnormal phenotypic features, including those of premature ageing. The results, therefore, do not support a simple model in which all features of ageing are attributable to widespread cell malfunction directly resulting from somatic mutation burdens accrued during life.

  Dataset EGAD00001006212

• Ecological Stressors, PTSD, and Drug Use in Detroit: The Detroit Neighborhood Health Study (DNHS)

  The Detroit Neighborhood Health Study (DNHS) is a prospective, representative longitudinal cohort study of predominantly African American adults living in Detroit, Michigan. The overall goal of the DNHS is to identify how genetic variation, lifetime experience of stressful and traumatic events, and features of the neighborhood environment predict psychopathology and behavior. Cohort participants were selected with a dual-frame probability design, using telephone numbers obtained from the U.S. Postal Service Delivery Sequence Files as well as a listed-assisted random-digit-dial frame. Individuals without listed landlines or telephones and individuals with only a cell phone listed were invited to participate through a postal mail effort. Participants completed a 40 minute, structured telephone interview annually between 2008-2012 to assess perceptions of participants' neighborhoods, mental and physical health status, social support, exposure to traumatic events, and alcohol and tobacco use; each participant was compensated $25USD. All survey participants were offered the opportunity to provide a specimen (venipuncture, blood spot, or saliva) for immune and inflammatory marker testing as well as genetic testing of DNA. Participants received an additional $25USD if they elected to give a sample. Informed consent was obtained at the beginning of each interview and again at specimen collection. The Institutional Review Board of the University of Michigan reviewed and approved the study protocol. The DNHS submission to dbGaP includes phenotype data from all five survey waves (n=856), all available GWAS data for participants who completed wave 4 (n=507), and methylation data for wave 1, wave 2, wave 4, and wave 5 participants (n = 456).

  Study phs000560

• Epigenetics of Cocaine and Nicotine Addiction

  This project characterizes DNA methylation and gene expression changes that occur in the human brain, specifically in neurons from the rostral striatum. Major advances from NIDA funded initiatives for noninvasive neuroimaging studies have made it possible to study neuroanatomical, neurochemical and functional changes in the human brain that contribute to the vulnerability to abuse drugs, together with the neurotoxic consequences of years of drug misuse. Animal models have been developed to explain the fundamental behavioral and biological mechanisms of addiction, including reward, tolerance and dependence. From these studies, we learned that cocaine abuse not only alters the epigenetic status of genes, but also induces particular epigenetic modifications depending on the frequency of the drug's administration. Certain genes are switched on by infrequent (short-term exposure) administration, while others are switched on only after chronic administration (addiction/dependence). Animal studies have also suggested that cocaine-seeking habits modeling chronic cocaine addiction in humans depend upon dopamine-dependent serial connectivity linking the ventral (nucleus accumbens) with the dorsal striatum (caudate nucleus). The primary goal of this study is to identify DNA methylation and gene expression changes that occur in the transition from recreational cocaine use to cocaine addiction. High throughput sequencing studies were designed to investigate unique postmortem human brain specimens from individuals that met criteria for cocaine dependence, as compared to unaffected age-matched controls. Brain biospecimens were available from the University of Miami Brain Endowment BankTM, from a collection of phenotypically well-characterized postmortem tissues sampled from chronic cocaine abusers that came to autopsy. This biobank of postmortem brain specimens and annotated genomic data serve as a research resource to support NIDA's scientific mission.

  Study phs001377

• Genomic Studies in Charcot-Marie-Tooth Disease

  The various forms of Charcot-Marie-Tooth disease (CMT) comprise a genetically heterogeneous set of peripheral neuropathies. Currently, >90 different CMT genes have been identified; yet, for the axonal CMT2 subtype these genes explain only 30-40% of the genetic effect. In particular, the application of exome sequencing has led to an unprecedented pace in identifying about half of those genes in the past five years. We have been at the forefront of this development with 22+ published new gene identifications in the past seven years. This success was only possible through broad national and international collaborations, data sharing, and the development of advanced analysis tools and methods. We also learned that despite an accumulation of exome sequencing data, over 50% of axonal CMT patients remain undiagnosed, suggesting even more genes are involved; additionally, our preliminary data also support the existence of non-coding variations as Mendelian allele contributors. In this study, we will continue our highly impactful work in CMT family recruitment, exome sequencing and traditional gene identification. In addition, we will expand the genetic studies to whole genome sequencing with a focus on families already explored unsuccessfully in whole exome studies. We further plan to perform the first large rare variant burden analysis in the rare disorder CMT2. This is only possible through the exceptional clinical resources we have built over the past decade. Finally, with many CMT genes available, we will perform statistical network analyses on a CMT-ome to identify gene modules and pathways that will be the starting point of polypharmacology, and provide insight into pathophysiology of peripheral nerve degeneration. All data will be available in real-time to an existing network of CMT investigators worldwide, and deposited in dbGaP annually.

  Study phs003389

• Sudden Death in the Young Case Registry

  Knowledge gaps persist about the incidence of and risk factors for sudden death in the young (SDY). The SDY Case Registry is a collaborative effort between the National Institutes of Health, the Centers for Disease Control and Prevention, and the Michigan Public Health Institute. Its goals are to: (1) describe the incidence of SDY in the United States by using population-based surveillance: (2) compile data from SDY cases to create a resource of information and DNA samples for research; (3) encourage standardized approaches to investigation, autopsy, and categorization of SDY cases; (4) develop partnerships between local, state, and federal stakeholders toward a common goal of understanding and preventing SDY; and (5) support families who have lost loved ones to SDY by providing resources on bereavement and medical evaluation of surviving family members. Built on existing Child Death Review programs and as an expansion of the Sudden Unexpected Infant Death Case Registry, the SDY Case Registry achieves its goals by identifying SDY cases, providing guidance to medical examiners/coroners in conducting comprehensive autopsies, evaluating cases through child death review and an advanced review by clinical specialists, and classifying cases according to a standardized algorithm. The SDY Case Registry also includes a process to obtain informed consent from next-of-kin to save DNA for research, banking, and, in some cases, diagnostic genetic testing. The SDY Case Registry will provide valuable incidence data and will enhance understanding of the characteristics of SDY cases to inform the development of targeted prevention efforts. For cases where informed consent has been obtained for research genomic sequencing has been performed. On these cases genomic data, phenotype information and on a limited number of cases redacted autopsy reports will be available through dbGaP.

  Study phs003221

• Hispanic Community Health Study /Study of Latinos (HCHS/SOL)

  The Hispanic Community Health Study / Study of Latinos (HCHS/SOL) is a multi-center epidemiologic study in Hispanic/Latino populations to determine the role of acculturation in the prevalence and development of disease, and to identify risk factors playing a protective or harmful role in Hispanics/Latinos. The study is sponsored by the National Heart, Lung, and Blood Institute (NHLBI) and six other institutes, centers, and offices of the National Institutes of Health (NIH). The goals of the HCHS/SOL include studying the prevalence and development of disease in Hispanics/Latinos, including the role of acculturation, and identifying disease risk factors that play protective or harmful roles in Hispanics/Latinos. A total of 16,415 persons of Cuban, Dominican, Mexican, Puerto Rican, Central American, and South American backgrounds were recruited through four Field Centers affiliated with San Diego State University, Northwestern University in Chicago, Albert Einstein College of Medicine in the Bronx area of New York, and the University of Miami. Seven additional academic centers serve as scientific and logistical support centers. Study participants aged 18-74 years took part in an extensive clinic exam and assessments to ascertain socio-demographic, cultural, environmental and biomedical characteristics. Annual follow-up interviews are conducted to determine a range of health outcomes. The HCHS SOL Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" section of this top-level study page phs000810 HCHS SOL Cohort. phs000555 PAGE CALiCo SOL phs000880 HCHS/SOL Omics in Latinos (Ola)

  Study phs000810

• Genetic Neuroscience: How Human Genes and Alleles Shape Neuronal Phenotypes

  The goal of this collaborative, interdisciplinary project is to develop powerful, generalizable approaches for discovering how risk variants for psychiatric disorders shape neurobiological processes at multiple levels of analysis, and to identify the processes whose dysregulation underlies disease.Induced pluripotent stem cells (iPSCs) were used towards the development of these new experimental and inferential systems bridging gaps between human genetics and experimental biology. The largest publicly available collection of iPSCs (2607 lines) has been generated from 2184 donors by the California Institute for Regenerative Medicine (CIRM). To expand our donor collection, an additional 44 iPSC donors from the McLean_Levy cohort were identified. We wish to share the available SNP data for 2167 CIRM lines and whole genome sequence data generated at the Broad Institute for 473 of the CIRM and 44 McLean_Levy iPSC donors. These data can be used to identify (for experiments) lines with specific genotypes of interest and lines from donors with high or low polygenic risk scores for phenotypes of interest. The data can also be used to identify acquired mutations in the iPSC lines. The CIRM iPSC lines are available through Fujifilm Cellular Dynamics iPSC Repository (https://www.fujifilmcdi.com/cirm-ipsc-products/). The McLean_Levy lines are available through the NIMH Repository & Genomics Resource (https://www.nimhgenetics.org/).Additional project data registered with the study includes data from an iPSC line derived from an SMA patient (n=1), as well as single-cell RNA sequence data and supplemental processed genomic datasets in support of project publications.Molecular DatasetsSingle-cell RNA-seq: 10X Genomics, Illumina NovaSeqSupplemental "cell village" pooled genomic sequence data: Illumina NextSeqWhole Genome Genotyping: Infinium Global Screening Array-24 Kit, Illumina HumanCore chipWhole Genome Sequencing: Illumina NovaSeq

  Study phs002032

• Blood Transcriptome Profiling Following Seizures

  The retrospective diagnosis or confirmation of a seizure, after the event, is very challenging. Many times clinicians can only use a patient's self-reported history. To further complicate the diagnosis, it is known that 20-30% of patients reporting a seizure actually suffer from psychogenic non-epileptic seizure (PNES). The patient has the behavior of a seizure, but does not suffer from brain seizure activity. Considerable time and resources are used to monitor PNES, and many patients undergo unnecessary therapy with anti-epileptic drugs. These resources could be more effectively used if we could confirm a seizure after the event (retrospective diagnosis). Here we propose a novel approach to distinguish seizures from PNES after the seizure event has happened.We have developed an accurate blood biomarker technology to diagnose acute brain injury, and assess chronic progression following brain injury. Previous studies support the premise that seizures affect blood RNA expression; here we assess temporal RNA expression pattern changes following seizure. We present preliminary preclinical data showing the discrimination of electric-stimulation evoked animal seizures. Here, we validate this maturing technology to assist with the discrimination of epileptic seizures from psychogenic non-epileptic seizures. We will analyze blood samples from patients undergoing video EEG monitoring in an epilepsy monitoring unit (Emory University Hospital, Atlanta GA). We expect 20% of these patients will have PNES. Once a patient has an EEG verified seizure, we will collect blood at various time points and identify biomarker RNA molecules in the blood. Blood samples will be collected from patients with non-verified seizures as control. These RNA expression values will be used to develop a predictive test for the occurrence of seizures. A biomarker gene panel will be developed from this exploratory project for validation in a larger patient population.

  Study phs003460

• High Frequency Ventilation in Premature Infants (HIFI-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: To evaluate the hypothesis that high frequency oscillatory ventilation in preterm infants would reduce the incidence of mortality and pulmonary complications compared to conventional mechanical ventilation.Background: With the introduction of mechanical ventilation in preterm infants, mortality and morbidity significantly improved but remained high. The improvement in survival that accompanied the use of mechanical ventilation also brought about an increase in the incidence of pulmonary complications. The principal complication occurs in the form of bronchopulmonary dysplasia. Barotrauma and oxygen toxicity are considered to be in the pathogenesis for this disorder. Considerable interest in high frequency ventilation for preterm infants was generated when animal studies indicated high frequency ventilation to be effective in promoting gas exchange without apparent adverse effects. High Frequency Ventilation (HFV) delivers small tidal volumes at high frequencies of 4 to 15 Hz, and animal studies had indicated that HFV was associated with effective gas exchange, less barotrauma, and lower mean airway pressure. However, the efficacy and safety of HFV in preterm infants had not been studied. The HIFI Planning Phase was initiated in August 1984, and recruitment and intervention began in February, 1986. Follow-up studies continued thru September, 1988.Participants: A total of 673 infants were enrolled.Conclusions: Bronchopulmonary dysplasia incidence was similar in the two groups as was mortality and the need for ventilatory support during the first 28 days. There was a significantly greater rate of pneumoperitoneum of pulmonary origin in the high frequency group as was a greater incidence rate of intracranial hemorrhage. (HIFI Study Group, 1989, PMID: 2643039)

  Study phs004032

• Convergent evolution towards CD38 biallelic loss is a recurrent mechanism of resistance to anti-CD38 antibodies in multiple myeloma.

  Monoclonal antibodies directed against CD38 are a therapeutic mainstay in multiple myeloma (MM). While they have contributed to improved outcomes, most patients will still experience disease relapse. Despite their ubiquity, little is known about tumor-intrinsic mechanisms of resistance to these drugs. Antigen escape, whereby tumor cells alter expression of cell surface immunotherapy targets, has been proposed as a potential avenue, and has been seen with other immunotherapies in MM. Yet, it is unknown whether MM cells can develop permanent resistance to anti-CD38 antibodies by acquiring genomic events leading to biallelic disruption of the CD38 gene locus. Here, by using whole genome and whole exome sequencing data from 701 newly diagnosed patients, 72 patients at relapse with naivety to anti-CD38 antibodies, and 52 patients collected at relapse following anti-CD38 antibodies, we report biallelic inactivation of CD38 as a recurrent mechanism of resistance in 6% of patients, often via convergent evolution where distinct subclones are advantaged towards the same selective endpoint within the same patient. Monoallelic loss of the CD38 locus was seen in another 14% post-CD38-directed therapy. Three of the cases with biallelic events on CD38 presented with missense mutations and retained CD38 expression. Functional work demonstrated that two of these mutations decreased binding affinity and antibody-dependent cellular cytotoxicity of commercial antibodies Daratumumab and Isatuximab. However, the third mutation (R140G) provided relative resistance only towards one commercial product. Given that patients are often rechallenged with CD38 antibodies following disease progression, these data support the need for next generation sequencing to guide treatment selection.

  Study EGAS50000000709

• RNAseq: Acquired non-permissive bone marrow microenvironment impairs hematopoietic stem cell proliferation and maintenance and B-cell development post-HSCT

  Defects in B-cell reconstitution upon hematopoietic stem-cell (HSC) transplantation (HSCT) are a common observation, yet the mechanism remains unexplained. The bone marrow (BM) stroma, including mesenchymal stromal cells (MSCs), guides HSC maintenance and B-lymphopoiesis by secreting crucial cytokines. We report acquired, permanent, selective and complete B-cell deficiency in the context of full donor-chimerism in a patient with X-linked lymphoproliferative disease and aimed to identify the contribution of the BM-microenvironment in disrupted B-cell reconstitution post-HSCT. We studied longitudinal BM samples from the patient and his identical twin, both of whom underwent HSCT with the same donor with opposite outcomes in B-cell reconstitution. In the index patient BM, we observed progressive loss of proliferation of HSCs and a selective block at the pre-BI cell stage. In vitro modeling studies showed limited survival of patient-HSCs and a relative accumulation of pre-B cells. Patient-derived MSCs failed to support survival and proliferation of HSCs and B-cell development of healthy-HSCs which was correlated with reduced CXCL12 levels. Using bulk RNA-sequencing of MSCs and in vitro functional studies, we showed global changes in the patients’ MSCs and a progressive loss of CXCL12 expression. Indeed, survival of patients HSCs improved supplementing in vitro development culture with CXCL12, suggesting a contribution of defective CXCL12 signaling to the phenotype. In summary, our data show that an acquired defect in the BM-stromal microenvironment and exhaustion of HSCs and committed progenitors may cause a permanent non-permissive state for normal B-cell development.

  Study EGAS50000001437

• ATAC-seq: Acquired non-permissive bone marrow microenvironment impairs hematopoietic stem cell proliferation and maintenance and B-cell development post-HSCT

  Defects in B-cell reconstitution upon hematopoietic stem-cell (HSC) transplantation (HSCT) are a common observation, yet the mechanism remains unexplained. The bone marrow (BM) stroma, including mesenchymal stromal cells (MSCs), guides HSC maintenance and B-lymphopoiesis by secreting crucial cytokines. We report acquired, permanent, selective and complete B-cell deficiency in the context of full donor-chimerism in a patient with X-linked lymphoproliferative disease and aimed to identify the contribution of the BM-microenvironment in disrupted B-cell reconstitution post-HSCT. We studied longitudinal BM samples from the patient and his identical twin, both of whom underwent HSCT with the same donor with opposite outcomes in B-cell reconstitution. In the index patient BM, we observed progressive loss of proliferation of HSCs and a selective block at the pre-BI cell stage. In vitro modeling studies showed limited survival of patient-HSCs and a relative accumulation of pre-B cells. Patient-derived MSCs failed to support survival and proliferation of HSCs and B-cell development of healthy-HSCs which was correlated with reduced CXCL12 levels. Using bulk RNA-sequencing of MSCs and in vitro functional studies, we showed global changes in the patients’ MSCs and a progressive loss of CXCL12 expression. Indeed, survival of patients HSCs improved supplementing in vitro development culture with CXCL12, suggesting a contribution of defective CXCL12 signaling to the phenotype. In summary, our data show that an acquired defect in the BM-stromal microenvironment and exhaustion of HSCs and committed progenitors may cause a permanent non-permissive state for normal B-cell development.

  Study EGAS50000001438

• Repotrectinib in NTRK fusion–positive advanced solid tumors: a phase 1/2 trial

  Early-generation TRK tyrosine kinase inhibitors (TKIs) approved for treating NTRK fusion–positive (NTRK+) solid tumors provide clinical benefit; however, resistance emerges. Repotrectinib is a next-generation ROS1/TRK TKI with a compact macrocyclic structure designed to improve durability of response. TRIDENT-1 is a registrational phase 1/2 trial assessing repotrectinib, a next-generation ROS1/TRK TKI, in adults with advanced solid tumors, including NTRK+ disease. The primary endpoint was confirmed objective response; secondary endpoints included duration of response (DOR), progression-free survival (PFS), overall survival and safety. Median follow-up ranged between 21.3 months and 25.7 months. In the TKI-naive cohort (n = 51; 95% confidence interval (CI)), the response rate was 59% (44–72); the median DOR was not estimable (NE); and the median PFS was 30.3 months (9.0–NE). In the TKI-pretreated cohort (n = 69; 95% CI), the response rate was 48% (36–60); the median DOR was 9.8 months (7.4–13.0); and the median PFS was 7.4 months (3.9–9.7). Of 30 TKI-pretreated patients with NTRK solvent front mutations, 16 had a response (53%; 95% CI: 34–72). Intracranial responses were observed in two of three TKI-naive patients and in four of six TKI-pretreated patients with measurable intracranial disease at baseline. Among all treated patients (n = 565), the most common any-grade treatment-related adverse event (TRAE) was dizziness (57%); most TRAEs were low grade; and 4% discontinued repotrectinib due to a TRAE. Overall, repotrectinib demonstrated durable systemic and intracranial responses with generally low-grade adverse events in patients with NTRK+ solid tumors, including those with previous TRK TKI treatment and solvent front mutations. These results support the use repotrectinib to treat patients with NTRK+ solid tumors. ClinicalTrials.gov identifier: NCT03093116 .

  Study EGAS50000001572

• Multi-site tumor sampling highlights molecular intra-tumor heterogeneity in malignant pleural mesothelioma

  Background:Malignant pleural mesothelioma (MPM) is a heterogeneous cancer. Better knowledge of molecular and cellular intra-tumor heterogeneity throughout the thoracic cavity is required to develop efficient therapies. This study focuses on molecular intra-tumor heterogeneity using the largest series to date in MPM and is the first to report on the multi-omics profiling of a substantial series of multi-site tumor samples. Methods:Intra-tumor heterogeneity was investigated in 16 patients from whom biopsies were taken at distinct anatomical sites. The paired biopsies collected from apex, side wall, costo-diaphragmatic or highest metabolic sites as well as 5 derived cell lines were screened using targeted sequencing. Whole exome sequencing, RNA sequencing, and DNA methylation were performed on a subset of the cohort for deep characterization. Molecular classification, recently defined histo-molecular gradients, and cell populations of the tumor microenvironment were assessed. Results:Sequencing analysis identified heterogeneous variants notably in NF2, a key tumor suppressor gene of mesothelial carcinogenesis. Subclonal tumor populations were shared among paired biopsies, suggesting a polyclonal dissemination of the tumor. Transcriptome analysis highlighted dysregulation of cell adhesion and extracellular matrix pathways, linked to changes in histo-molecular gradient proportions between anatomic sites. Methylome analysis revealed contribution of epigenetic mechanisms in two patients. Finally, significant changes in the expression of immune mediators and genes related to immunological synapse, as well as differential infiltration of immune populations in the tumor environment were observed and led to a switch from a hot to a cold immune profile in three patients. Conclusions:This comprehensive analysis reveals patient-dependent spatial intra-tumor heterogeneity at the genetic, transcriptomic and epigenetic levels and in the immune landscape of the tumor microenvironment. Results support

  Study EGAS00001005328

• Altered oligodendrocyte heterogeneity in Multiple sclerosis revealed by single nuclei RNA sequencing

  This study is currently hosted by the European Nucleotide Archive. To access the data contained within the Study please follow the link below: https://www.ebi.ac.uk/ena/browser/view/PRJEB39323 Oligodendrocyte (OL) pathology is increasingly implicated in neurodegenerative diseases, as they are involved in metabolic support of axons and functional cross-talk with other brain cells. Rodent OLs are heterogeneous, with developmental and biological differences, but the extent of heterogeneity in the normal human brain and its contribution to any changes to disease remains unknown. Here we performed single nuclei RNA-sequencing (snRNA-seq) from white matter (WM) areas of post mortem human brain both in control (Ctr) and multiple sclerosis (MS) patients. We identified several sub-clusters of oligodendroglia in the Ctr human WM, some similar to those in mouse, and defined new markers for these cell states. Strikingly, some of these sub-clusters were under-represented in MS tissue, while others were more prevalent than in controls. We found a lack of OL precursor cells (OPCs) and an OL subcluster in an intermediate stage of differentiation in MS lesions and in normal appearing white matter (NAWM), suggesting either depletion by the disease or by a regenerative response. The differences in mature OL sub-clusters indicate different functional states of OLs in MS tissue and, as this is similar in NAWM to lesions, that MS is a more diffuse brain disease than the focal demyelinating lesions suggest. We were also able to identify new putative markers of different MS lesion subtypes. Our findings of an altered heterogeneity of oligodendroglia in MS may have an important contribution to our understanding of disease progression and may alter therapeutic approaches to MS.

  Study EGAS00001003412

• Targeting FGFR1 for treatment of soft-tissue sarcoma (H021)

  Purpose: Altered FGFR1 signaling has emerged as therapeutic target in various epithelial malignancies. In contrast, the role of FGFR1 in soft-tissue sarcoma (STS) has not been established. Prompted by the detection and subsequent therapeutic inhibition of amplified FGFR1 in a patient with metastatic leiomyosarcoma, we investigated the oncogenic properties and potential as drug target of FGFR1 in STS.Experimental Design: The frequency of FGFR1 amplification and overexpression, as assessed by fluorescence in situ hybridization, microarray-based comparative genomic hybridization and mRNA expression profiling, SNP array profiling, and RNA sequencing, was determined in three independent patient cohorts. The sensitivity of STS cell lines with or without FGFR1 alterations to genetic and pharmacologic FGFR1 inhibition and the signaling pathways engaged by FGFR1 were investigated using short-term viability assays, long-term colony formation assays, and biochemical analysis.Results: Increased FGFR1 copy number was detected in 74 of 190 (38.9%; Cohort 1), 13 of 79 (16.5%; Cohort 2), and 80 of 254 (31.5%; Cohort 3) patients. FGFR1 overexpression occurred in 16 of 79 (20.2%, Cohort 2) and 39 of 254 (15.4%; Cohort 3) patients. Targeting of FGFR1 by short hairpin RNA-mediated knockdown and different small-molecule inhibitors (PD173074, AZD4547, BGJ398) revealed that the requirement for FGFR1 signaling in STS cells is primarily dictated by FGFR1 expression levels, and identified the MAPK-ERK1/2 axis as critical FGFR1 effector pathway.Conclusion: These data identify FGFR1 as driver gene in multiple STS subtypes and support FGFR1 inhibition, guided by patient selection according to FGFR1 expression and monitoring of MAPK-ERK1/2 signaling, as therapeutic option in this challenging group of diseases.H021

  Study EGAS00001001844

• Genetics and therapeutic responses to TIL therapy of pancreatic cancer PDX models

  Pancreatic cancer is the 7th leading cause of cancer-related deaths worldwide. Checkpoint immunotherapy has not yet showed encouraging results in pancreatic cancer possibly owing to a poor immunogenicity and/or an immune suppressive microenvironment. The aim of this study was to develop patient-derived xenografts (PDX) models and to assess if autologous tumor-infiltrating lymphocytes (TILs) would have anti-tumoral activity in pancreatic cancer. Tumor biopsies from 29 patients were subcutaneously transplanted into NOG mice. Tumor growths were confirmed in 11 out of 29 transplantations. The PDX tumors histologically resembled their original biopsies, but since stromal cells in the PDX model tumors were from mouse, their gene expression differed from the original biopsies. Immune checkpoint ligands other than PD-L1 were expressed in pancreatic cancers but PD-L1 was rarely expressed. One of the three tumors that did express PD-L1 was an adenosquamous cancer and another had a mismatch repair deficiency. TILs were expanded from six tumors and were injected into NOG or human interleukin-2 transgenic-NOG (hIL2-NOG) mice carrying PDX tumors. Regression of tumors could be verified in hIL2-NOG mice in 3 of the 6 PDX models treated with autologous TILs, including the adenosquamous PDX model. In conclusion, PDX models of pancreatic cancer can be used to learn more about tumor characteristics and biomarkers, and to evaluate responses to ACT and combination therapies. The major benefit of the model is that modifications of T cells can be tested in an autologous humanized mouse model to gain preclinical data to support the initiation of a clinical trial.

  Study EGAS00001005596

• Monocyte and macrophage lipid accumulation results in downregulated type-I interferon responses

  Macrophages are critical components of atherosclerotic lesions and their pro- and anti-inflammatory responses influence atherogenesis. Type-I interferons (IFNs) are cytokines that play an essential role in antiviral responses and inflammatory activation and have been shown to promote atherosclerosis. Although the impact of type-I IFNs on macrophage foam cell formation is well-documented, the effect of lipid accumulation in monocytes and macrophages on type-I IFN responses remains unknown. Here we examined IFN stimulated (ISG) and non-ISG inflammatory gene expression in mouse and human macrophages that were loaded with acetylated LDL (acLDL), as a model for foam cell formation. We found that acLDL loading in mouse and human macrophages specifically suppressed expression of ISGs and IFN-β secretion, but not other pro-inflammatory genes. The downregulation of ISGs could be rescued by exogenous IFN-β supplementation. Activation of the cholesterol-sensing nuclear liver X receptor (LXR) recapitulated the cholesterol-initiated type-I IFN suppression. Additional analyses of murine in vitro and in vivo generated foam cells confirmed the suppressed IFN signalling pathways and suggest that this phenotype is mediated via downregulation of interferon regulatory factor binding at gene promoters. Finally, RNA-seq analysis of monocytes of familial hypercholesterolemia (FH) patients also showed type-I IFN suppression which was restored by lipid-lowering therapy and not present in monocytes of healthy donors. Taken together, we define type-I IFN suppression as an athero-protective characteristic of foamy macrophages. These data provide new insights into the mechanisms that control inflammatory responses in hyperlipidaemic settings and can support future therapeutic approaches focusing on reprogramming of macrophages to reduce atherosclerotic plaque progression and improve stability.

  Study EGAS00001005955

• Germline variants in patients with rare cancers and their implications for precision cancer medicine: experiences from the Multicenter MASTER Trial by the German Cancer Consortium (HIPO_021)

  The era of precision oncology entails an increasing amount of molecular data from tumor sequencing in research and diagnostics. In this setting, germline variant analysis may add clinical benefits for patients and family members. In this study, we evaluated germline variants from genome/exome matched tumor-blood sequencing in 1.485 advanced cancer patients within a prospective observational study carried out by the German Cancer Consortium. Included patients had cancers of rare entities (79.2%) or were under the age of 51 at first diagnosis (76.6%). Ten percent of the patients harbored pathogenic germline variants in 35 tumor predisposition genes with autosomal-dominant inheritance such as BRCA1, BRCA2, TP53, RB1, CHEK2, ATM, PALB2, SDHB etc., while 4.6% of the patients were carriers of pathogenic germline variants in 18 genes with autosomal-recessive inheritance of tumor predisposition. Based on pathogenic germline variants, 14% of the patients received genetic counselling recommendations in the molecular tumor board report. Forty five percent of pathogenic germline variants supported a molecular treatment recommendation, which was implemented for 28 patients. Furthermore, we compared our approach and results to previous studies, broadening the insight into pan cancer germline findings but also revealing differences between studies on various levels, such as cohort demographics, tumor entities, gene nominations, variant detection and variant interpretation. Our data support the importance of germline variant interpretation in precision oncology studies for patients and their families, if applicable. However, guidelines for evaluation and reporting of germline variants in the context of genetic tumor profiling need to be established and further research on the relevance of germline mutations as biomarkers for treatment recommendations is needed.

  Study EGAS00001005537

• Genetic heritage of the Baphuthi highlights an over-ethnicised notion of 'Bushman' in the Maloti-Drakensberg, southern Africa

  Using contemporary people as proxies for ancient communities is a contentious but necessary practice in anthropology. In southern Africa, the distinction between the Cape KhoeSan and eastern KhoeSan remains unclear as ethnicity labels have been changed through time and most communities were decimated if not extirpated. The eastern KhoeSan may have had genetic distinctions from neighbouring communities who speak Bantu languages and KhoeSan further away, alternatively the identity may not have been tied to any notion of biology, instead denoting communities with a nomadic 'lifeway' distinct from African agro-pastoralism. The Baphuthi of the 1800s in the Maloti-Drakensberg, southern Africa had a substantial KhoeSan constituency and a lifeway of nomadism, cattle raiding, and horticulture. Baphuthi heritage could provide insights into the history of the eastern KhoeSan. We examine genetic affinities of 23 Baphuthi to discern whether the narrative of KhoeSan descent reflects distinct genetic ancestry. Genome-wide SNP data (Illumina GSA) were merged with 52 global populations, for 160K SNPs. Genetic analyses show no support for a unique eastern KhoeSan ancestry distinct from other KhoeSan or southern Bantu-speakers. The Baphuthi have strong affinities with early-arriving southern Bantu-speaking (Nguni) communities, as the later-arriving non-Nguni show strong evidence of recent African admixture possibly related to Late-Iron Age migrations. The references to communities as 'San',and 'Bushman' in historic literature has often been misconstrued as notions of ethnic/biological distinctions. The terms may have reflected ambiguous references to non-sedentary polities instead, as seems to be the case for the eastern ‘Bushman’ heritage of the Baphuthi.

  Study EGAS00001007080

• IL7-receptor expression is frequent in T-cell acute lymphoblastic leukemia and predicts sensitivity to JAK-inhibition

  T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematological malignancy with a dismal prognosis related to refractory/relapsing diseases, raising the need for new targeted-therapies. Activating mutations of the IL7-receptor pathway genes (IL7Rp) play a proven leukemia-supportive role in T-ALL. JAK-inhibitors such as ruxolitinib have recently demonstrated preclinical efficacy. However, prediction markers for sensitivity to JAK-inhibitors are still lacking. Herein, we show that IL7R (CD127) expression is more frequent (~70%) than IL7Rp-mutations in T-ALL (~30%). We compared the so-called non-expressers (no IL7R-expression/IL7Rp-mutation), expressers (IL7R-expression without IL7Rp-mutation) and mutants (IL7Rp-mutations). Integrative multi-omics analysis outlined IL7R-deregulation in virtually all T-ALL subtypes, at the epigenetic-level in non-expressers, genetic-level in mutants, and post-transcriptional level in expressers. Ex-vivo data using primary-derived xenografts support that IL7Rp is functional whenever the IL7R is expressed, regardless of the IL7Rp mutational status. Consequently, ruxolitinib impaired T-ALL survival in both expressers and mutants. Interestingly, we show that expressers displayed ectopic IL7R-expression and IL7Rp-addiction conferring a deeper sensitivity to ruxolitinib. Conversely, mutants were more sensitive to venetoclax than expressers. Overall, combination of ruxolitinib and venetoclax resulted in synergistic effects in both groups. We illustrate the clinical relevance of this association by reporting achievement of complete remission in two patients with refractory/relapsed-T-ALL. This provides proof of concept for translation of this strategy into clinics as bridge to transplant. Altogether, IL7R-expression can be used as a biomarker for sensitivity to JAK-inhibition, thereby expanding the fraction of T-ALL patients eligible to ruxolitinib up to nearly ~70% of T-ALL.

  Study EGAS00001007144

• Genome-Wide Association Studies of Prematurity and Its Complications

  Preterm labor resulting in the delivery of a premature child is a complex problem with an enormous impact on individuals, families and society. An estimated 500,000 children are born prematurely in the U.S. each year, and 5 million worldwide die annually of prematurity and its complications. Prematurity is also the single largest contributor to disability-adjusted life years, a measure of the lifetime impact of a disease. Despite the importance of the problem and its disproportionate occurrence in poor and minority populations, its underlying etiology (or etiologies) remains unknown; the single best predictor for preterm delivery is a previous preterm birth. The largest single cause of prematurity is spontaneous preterm labor, and suspected triggers for this include infection, stress, poor nutrition and genetic factors. Family and twin studies provide strong evidence that genetic factors underlie about 40% of the risk for prematurity. A major challenge in studying genetic factors in prematurity is maternal/uterine factors, fetal/placental factors, or both may influence risk. Thus, any approach to studying preterm birth should account for both infant and maternal risk, environmental covariates and interactions. The Danish National Birth Cohort (DNBC) is a well-established, prospective cohort that enrolled women early in pregnancy, prior to any adverse pregnancy outcomes, to minimize bias in data collection and sampling. See details at: http://www.ssi.dk/English. The DNBC followed over 100,000 pregnancies beginning in the first trimester and has extensive biological material and epidemiologic data on health outcomes in both mother and child. The current study posted on dbGaP contains data from a genome-wide case/control study using approximately 1,000 preterm mother-child pairs from the DNBC most with spontaneous onset of labor or preterm premature rupture of membranes (PPROM), along with 1,000 control pairs where the child was born at ~40 weeks' gestation. After data cleaning some small changes in case/control status and other variables resulted in minor changes in numbers of cases or controls in certain categories. Environmental variables are being used as covariates in the analysis. To replicate positive findings, we are using additional mother-child pairs from the DNBC and from the general Danish population, as well as 2200 samples coming primarily from an African-American population known to have high rates of preterm labor and delivery. This group includes over 1000 mostly very low birthweight infants, over 500 infant term controls, 326 term mother/baby pairs and 180 preterm mother/baby pairs. The data from these additional cohorts will be available in separate dbGaP postings. The study is expected to yield a better understanding of the biology of parturition, identify common genetic factors that play a role in preterm birth and its complications and suggest environmental modifications that can prolong gestation, with the goal of improving both neonatal and adult outcomes. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to prematurity and its complications through large-scale genome-wide association studies of a well-characterized cohort of Danish mothers and babies. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000103

• Trial of Late Surfactant for Prevention of Bronchopulmonary Dysplasia: A Study in Ventilated Preterm Infants Receiving Inhaled Nitric Oxide (TOLSURF-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions.Objectives: To assess whether late surfactant treatment in extremely low gestational age newborn (ELGAN, ≤28 week gestation) infants requiring ventilation at 7-14 days safely improves survival without bronchopulmonary dysplasia.Background: Bronchopulmonary dysplasia (BPD) is the most common form of chronic lung disease in children with an estimated 15,000 new cases annually in the United States. BPD affects infants born prematurely, is a major contributor to the cost of prematurity each year, and is associated with long-term pulmonary disability, neurodevelopmental abnormalities and death.Increases in the survival of ELGAN infants have resulted in another form of BPD, which is characterized by impaired alveolar and microvascular development with excess tone and reactivity of airway smooth muscle. Despite treatments to enhance lung maturation, premature infants often need prolonged intubation and mechanical ventilation and/or oxygen support. When mechanical ventilation is required longer than 7 days, BPD results in 70% of surviving ELGAN infants. Most of these infants experience clinical episodes of increased requirement for ventilatory support that are associated with dysfunctional surfactant, which is primarily due to low surfactant protein B (SP-B). In pilot studies of late surfactant treatment in premature infants, there was short-term improvement in SP-B content. These prior studies provided the rationale for a larger clinical trial for later doses of surfactant treatment to prevent episodes of respiratory decompensation and BPD. Participants: 511 infants were eligible for randomization of the 2693 infants screened. Of the 511 infants eligible for randomization, there were 252 infants allocated to the treatment arm and 259 infants allocated to the placebo arm.Design: The study was designed to assess the effect of late doses of surfactant on survival without BPD at 36 weeks post menstrual age (PMA) in ELGAN infants who required intubation and mechanical ventilation between 7 and 14 days of age and were receiving Inhaled nitric oxide (iNO). Infants were stratified within clinical centers and gestational age groups and randomized to treatment with calfactant, a natural surfactant extracted from bovine lung lavage fluid, or a sham procedure.All infants received iNO according to the protocol used in the Nitric Oxide Chronic Lung Disease (NOCLD) trial. A masked syringe containing either a standard dose of calfactant for the treatment group, or air for the placebo group, was administered to the infant behind a screen by staff not involved in providing the infant's clinical care. Monitor and ventilator alarms were turned off during dosing to avoid unblinding of clinical staff. To accommodate research staff availability and infant instability, the dosing interval was not strictly set but could be repeated every 24 – 72 hours up to 5 doses if the infant still required intubation. Dosing could be discontinued by physician request or parental withdrawal from the study. Due to parental preference, the first infant in a multiple birth was randomized according to the randomization schedule and subsequent infants were assigned to the same treatment group. Follow-up to assess pulmonary and neurologic development continued until 2 years of age, with treatment group blinding maintained. The primary outcome was survival without BPD at 36 weeks PMA. Secondary outcomes included BPD at 40 weeks PMA, pulmonary outcome at 12–24 months of age, and neurodevelopmental outcome at 2 years of age. Conclusions: There were no significant differences observed between the treatment group and the control group for survival without BPD at 36 weeks or 40 weeks.

  Study phs003899

• Genomics Define Malignant Transformation in Myeloma Precursor Conditions

  Multiple myeloma (MM) is consistently preceded by monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM). While these precursor conditions are asymptomatic, they are not entirely benign and carry a lifelong risk of progression to MM. Unlike other cancers defined by pathology, malignant transformation from MGUS or SMM to MM has so far relied on demonstration of clinical end-organ damage as morphology and cytogenetics cannot reliably distinguish them. In this study, using genomic data from 374 patients with MGUS or SMM (277 training, 97 validation), to our knowledge, we demonstrate for the first time the ability to identify malignant transformation in MGUS and SMM. We introduce the concept of genomic MM and genomic MGUS to differentiate the subsets of MGUS and SMM that are biologically malignant with genomic features indistinguishable from MM from the subset that is premalignant and unlikely to progress to malignancy. Importantly, we find that most SMM has biological features of malignant transformation indistinguishable from MM. As expected, this subset that we consider having genomic MM is associated with a high risk of progression to MM although some patients remained progression-free beyond 5 years. Conversely, 60% of MGUS and 10% of SMM have no evidence of malignant transformation (genomic MGUS), with no progression during follow-up. Integration of genomic features with the 2/20/20 International Myeloma Working Group model significantly improved the prediction of progression among genomic MM. These findings support the use of genomic criteria to refine the classification and the risk stratification in myeloma precursor conditions.

  Dataset EGAD00001015768

• Genome-Wide Association Study of HIV-1 Host Genetics Among Injection Drug Users

  The overarching goal of this project is to identify and characterize genetic determinants of HIV 1 susceptibility and resistance in samples of African American (AA) and European American (EA) injection drug users (IDUs) by conducting (1) a case/control genome-wide association (GWA) study of HIV 1 infection (positive/negative); (2) a case-only GWA study of viral load among HIV+ IDUs. The study uses existing samples and data from Urban Health Study (UHS) (PI: Alex Kral), which was the longest-running study of street-recruited IDUs in North America, from 1986-2005. UHS was a serial, cross-sectional sero-epidemiological study. Data were collected every 6 months in communities with a high prevalence of injection drug use in the San Francisco Bay Area. It used targeted sampling in neighborhoods at easily accessible community field sites, such as churches, single room occupancy hotels, and community centers. Eligibility criteria for initial entry to the study were (1) injection drug use in past 30 days; (2) ability to provide informed consent; and (3) age 18 or older. The UHS cohort includes over 9,000 African American and European American IDUs whose serum samples have been stored and data are available on HIV antibody status, HIV risk behaviors, drug abuse and demographics. The current study includes 985 HIV+ cases and 5,222 HIV- controls. Approximately six HIV- controls per case were frequency matched on: (1) self-reported ancestry; (2) sex; (3) age; (4) year of ascertainment; and (5) HIV risk class. This GWAS (DA026141) was funded by the National Institute on Drug Abuse (NIDA; PI: Eric O. Johnson). Funding support for genotyping, which was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR), was provided by NIDA and the NIH contract "High throughput genotyping for studying the genetic contributions to human disease"(HHSN268200782096C).

  Study phs000454

• Phenotypic and Genotypic Study of Keratoconus

  Keratoconus, a disease in which the cornea is abnormally steep and thin, affects approximately 1 in 2000 individuals and usually begins in the second decade of life. Keratoconus is a progressive disorder that results in loss of vision that cannot be alleviated by contact lenses or glasses alone and is a leading indication for corneal transplantation in developed countries (Udar et al., 2006, PMID: 16877401). Keratoconus has a strong genetic component, and while several causative genes are clearly suspected, the underlying pathogenic processes have not yet been identified. The goal of our research is to identify genes that harbor mutations contributing to keratoconus and underlying biochemical processes relevant to keratoconus pathogenesis and to develop a better understanding of the etiology of keratoconus, leading to improved detection, treatment, and management. We will enroll isolated keratoconus along with familial cases and unaffected relatives when available. The subject population will consist of individuals diagnosed with keratoconus and unaffected relatives in families. Individuals/families will be ascertained through support groups and clinical collaborators. The identities of the study participants will be known only to Dr. Chakravarti, the study coordinator, physicians in the team and the post-doctoral fellow(s) working directly on the project. DNA, lymphocytes, and lymphoblastoid cell lines may be prepared from the blood samples for future use. Molecular analyses using markers and sequencing and statistical analyses of these data will be used to identify regions of human chromosomes where putative keratoconus disease genes reside. Analyses of coding DNA sequences within genes from keratoconus subjects will be compared to published control sequences to identify disease specific variants. Additionally, to understand disease pathogenesis, subsets of patients may be asked to provide tear samples. Study subjects will not directly benefit from participation and results will not be disclosed to participants nor their health care providers, unless medically relevant.

  Study phs003168

• Integrative analysis reveals a macrophage-predominant, immunosuppressive immune microenvironment and subtype-specific therapeutic vulnerabilities in advanced salivary gland cancer

  Background Salivary gland cancers (SGC) are rare and heterogeneous malignant tumors. Advanced SGC lack established treatment options and show poor response to immunotherapy. Here, an integrative multi-omics analysis in a large cohort of advanced SGC revealed insights into the tumor immune microenvironment (TIM) and distinct mechanisms of immune evasion. Methods A total of 104 patients with recurrent/metastatic SGC from the DKTK MASTER program were included in this study. Whole-exome or whole-genome sequencing and RNA-sequencing was performed on fresh frozen tumor tissue. The tumor immune microenvironment was analyzed using CIBERSORT deconvolution analysis and immune gene expression scores in bulk RNA-sequencing data. Single-nuclei sequencing and immunohistochemistry analyses were performed in selected samples. Results were validated in bulk RNA-sequencing data of a previously published independent dataset. Results Bulk transcriptome analysis revealed an immune-deserted TIM in the majority of advanced SGC samples. Immune exclusion was most prominent in adenoid cystic carcinoma (ACC) subgroup 1 exhibiting a downregulation of the antigen processing machinery. Only a small subset of advanced SGC, including few adenoid cystic carcinoma, exhibited T-cell inflammation, which was correlated with tumor mutational burden in Non-ACC samples. Subtype specific expression of immune checkpoints as well as cancer testis antigens were identified with prominent expression of VTCN1 in luminal cells within ACC. Single-cell RNA-sequencing and bulk RNA-seq deconvolution analysis validated immune cell exclusion and revealed a TIM that was dominated by M2 macrophages across SGC subtypes. Among evaluable patients treated with immune checkpoint inhibitors, a high T-cell to macrophage ratio was associated with clinical benefit. Conclusions These data support biomarker-based development of immune-checkpoint inhibition and the development of novel immune-checkpoint inhibitors and cellular therapies in SGC.

  Study EGAS50000000809

• Single-Gene vs. Panel Sequencing in Advanced HR+/HER2− Breast Cancer

  Background: Hormone receptor-positive (HR+)/HER2-negative (HER2−) breast cancer is the most common subtype of breast cancer, with biomarker-driven therapies improving outcomes. Liquid biopsies, which analyze circulating tumor DNA (ctDNA), are increasingly essential in clinical management, offering a minimally invasive approach to assess somatic alterations and guide therapy decisions. However, the choice of assay directly affects clinical utility and global access to validated testing platforms remains inconsistent. To address these challenges, this study aimed to compare the performance of single-gene and panel-based sequencing for detecting PIK3CA mutations in HR+/HER2− breast cancer and evaluate the added value of broader genomic profiling in guiding treatment decisions. Patients and methods: We conducted a prospective, multicenter study comparing our previously established SiMSen-Seq (SSS) assay, a single-gene method targeting PIK3CA hotspot mutations, with the AVENIO ctDNA Expanded assay, enriching for 77 clinically relevant cancer genes. Additionally, tumor fractions were estimated with mFAST-SeqS by assessing chromosomal aneuploidy. We analyzed 161 plasma samples collected from 146 patients with HR+/HER2− advanced breast cancer before starting a new line of palliative therapy. Results: High concordance (92.6%) was observed between SSS and AVENIO for PIK3CA mutation detection, with accurate variant allele frequency (VAF) quantification confirmed by Bland-Altman analysis and linear mixed-effects modeling. AVENIO identified additional PIK3CA mutations in 19% of samples as well as other actionable alterations, including ESR1 mutations (17.5%) and PI3K pathway alterations (40.6%). Panel sequencing improved the interpretation of negative liquid biopsy results by integrating tumor fraction and VAF metrics. Conclusions: Panel sequencing assays such as AVENIO provide broader genomic coverage, enhance the detection of actionable mutations and refine the interpretation of negative liquid biopsy findings. These findings support the integration of comprehensive ctDNA profiling into routine clinical practice for HR+/HER2− advanced breast cancer while highlighting the need for improved assay accessibility and expanded genomic targets.

  Study EGAS00001008200

• Probabilistic modeling of personalized drug combinations from integrated chemical screen and molecular data in sarcoma

  Background: Cancer patients with advanced disease exhaust available clinical regimens and lack actionable genomic medicine results, leaving a large patient population without effective treatments options when their disease inevitably progresses. To address the unmet clinical need for evidence-based therapy assignment when standard clinical approaches have failed, we have developed a probabilistic computational modeling approach which integrates sequencing data with functional assay data to develop patient-specific combination cancer treatments. Methods: Tissue taken from a murine model of alveolar rhabdomyosarcoma was used to perform single agent drug screening and DNA/RNA sequencing experiments; results integrated via our computational modeling approach identified a synergistic personalized two-drug combination. Cells derived from the tumor were allografted into mouse models and used to validate the personalized two-drug combination. Computational modeling of single agent drug screening and RNA sequencing of multiple heterogenous sites from a single patient’s epithelioid sarcoma identified a personalized two-drug combination effective across all tumor regions. The heterogeneity-consensus combination was validated in a xenograft model derived from the patient’s primary tumor. Cell cultures derived from human and canine undifferentiated pleomorphic sarcoma were assayed by drug screen; computational modeling identified a resistance-abrogating two-drug combination common to both cell cultures. This combination was validated in vitro via a cell regrowth assay. Results Our computational modeling approach addresses three major challenges in personalized cancer therapy: synergistic drug combination predictions (validated in vitro and in vivo in a genetically engineered murine cancer model), identification of unifying therapeutic targets to overcome intra-tumor heterogeneity (validated in vivo in a human cancer xenograft), and mitigation of cancer cell resistance and rewiring mechanisms (validated in vitro in a human and canine cancer model). Conclusions These proof-of-concept studies support the use of an integrative functional approach to personalized combination therapy prediction for the population of high-risk cancer patients lacking viable clinical options and without actionable DNA sequencing-based therapy.

  Study EGAS00001003564

• Bulk-RNA Sequencing of high-grade pancreatic and non-pancreatic Neuroendocrine Neoplasms

  Therapeutic decisions in oncology depend on a precise pathological classification of individual neoplasms. Recent years have seen an intensification of research activities aimed at the extraction of clinically relevant information from patient-derived 'omics' data based on Machine-Learning models. However, a comprehensive training of Machine-Learning models requires sufficiently large numbers of training samples, which are usually not available for rare cancer types. The problem is worsened when individual tissues segregate into different cancer subtypes, as their discrimination would require even more training samples. Methods: Here, we report on a new data-augmentation technique to support the training of Machine-Learning models on ‘omics’ data from pancreatic neuroendocrine neoplasms (panNEN). PanNENs display all properties described above: Only about 2-3% of all pancreatic neoplasms are neuroendocrine and they fall into different subtypes with distinctly different prognosis, which makes the precise classification of such samples both difficult and important for therapy decisions. The approach reconstructs a given transcriptome based on healthy pancreatic cell type signatures and creates a Machine-Learning model that integrates the observed reconstruction error and predicted cell type proportions as features. Results: A benchmark of the deconvolution model predictions with the ground-truth found that the model could efficiently predict the sample grading, disease-related patient survival time, and differentiate between different subtypes in four panNEN and one mixed panNEN and non-pancreatic NENs dataset. We compared the predictive performance of the deconvolution-trained model to that of a model trained directly on the transcriptomic data, under inclusion of the Ki-67 classification gold standard biomarker, and found the performances to be comparable. Conclusion: Our approach serves as a data-augmentation technique to facilitate the training of Machine Learning models for rare cancer types via utilization of data from healthy origin. Additionally, the deconvolution results were clinically interpretable and further research can render the deconvolution approach an effective complementary asset for the clinical classification of neoplasms.

  Study EGAS00001004861

• Separation of chronic myeloid leukemia stem cells from normal hematopoietic stem cells at single-cell resolution

  Chronic myeloid leukemia (CML) is a clonal disease, initiated and sustained by a subpopulation of CML stem cells (CML-SC) containing the BCR::ABL1 oncogene. Genetic markers that enrich for CML-SC have been identified, including CD26 being most specific. Genome sequencing analysis remain yet to be performed at single cell level in order to determine differences and heterogeneity in the genetic profile of CML-SC versus normal hematopoietic stem cells (HSC). Here we show that CD26 and CD33 separate CML-SC from normal HSC in freshly isolated bone marrow samples from newly diagnosed CML patients. DNA sequencing confirms that single CML-SC derived colonies are positive for BCR::ABL1 and harbor a recurrent set of patient-specific clonal somatic mutations across different CML-SC derived colonies. In contrast, marker-negative (CD26-CD33-) HSC from the same patients are negative for the BCR::ABL1 oncogene and do not carry recurrent, clonal mutation across different colonies. These results support the concept that CD26/CD33 expression separates genetically defined, clonal mutant CML-SC from normal HSC that carry individual sets of random mutations in CML patients. We provide whole exome DNA sequencing data for 23 clinical samples of CML-SC plus two buccal swipes derived normal samples. CML samples are comprised of 4 to 8 replicates from two patients, at diagnosis and after treatment. Single CML stem cells before treatment and single non-transformed HSC at remission were selected from bone marrow samples by FACS, according to genetic markers CD33+CD26+ at diagnosis and CD33+CD26-/CD33-CD26- at remission. WES libraries of colony forming assays derived CML-SC and HSC populations were prepared using Agilent SureSelect Human All Exon V6 kit and sequenced running 150 cycles (2x 75bp paired-end) on an Illumina NextSeq 500 platform. Following GATK best practices for somatic mutation calling, novel CML variants and random mutation events during remission phase were obtained.

  Study EGAS00001006904

• Angelman, Rett, Prader-Willi Syndrome Consortium (ARP) Rett Syndrome Natural History Protocol

  This observational study will involve the comprehensive assessment of the clinical features of Rett syndrome with this Rare Diseases Clinical Research Network. A clinical database of 1350 individuals with Rett syndrome including MECP2 mutation status for the purpose of elaborating phenotype-genotype correlations will be established. Eligible participants will be enrolled in the natural history study for 11 years from the 4 clinic sites currently involved with Rett syndrome (BCM, GGC, and UAB, CHB) as well as from the several thousand registrants in the International Rett Syndrome Foundation registry who will be invited to the nearest consortium site involved in Rett syndrome. Potential participants are expected to have had determination of their MECP2 mutation status, but will not be excluded should no mutation be present. All individuals who meet criteria and are currently receiving care from study sites will be invited to participate (N>600). Additional participants will be invited through the assistance of the International Rett Syndrome Foundation (IRSF). All individuals with RS registered with IRSF will be invited to participate in this study via the IRSF website and the IRSF newsletter. Potential participants will be apprised of the participating study sites and invited to contact one of the sites based on feasibility of travel. Inasmuch as the enrollment goal of 1350 participants is 40% of the current IRSF registry, we believe this will be a representative sampling. Bias can certainly occur based on travel requirements, level of interest, and other factors. However, inclusion of such a large sample should minimize sampling bias. No travel expenses will be covered, so it is likely that participants will be those with geographic proximity to Houston, Greenwood, Birmingham, or Boston. From the sample pool described above, the aim is to conduct the observational longitudinal (natural history) study on up to 1350 participants with classic Rett syndrome and variant forms of Rett syndrome, that is, participants who fully meet the established clinical criteria for Rett syndrome and those who meet some but not all of these criteria. All participants expressing MECP2 mutations irrespective of phenotype will be eligible for enrollment. For each of the eight common genetic mutations as well as those with large scale deletions, the prevalence of the following RS characteristics will be estimated for each age category and overall: seizure presence and frequency, ambulation status, scoliosis, ECG abnormality, breathing irregularities while awake, feeding difficulties, growth as measured in percentiles from NCHS standards curves, the presence of osteopenia as evidenced by bone fracture, and the presence of gallbladder disease. Both incidence and prevalence estimates will be made using a combination of data obtained at the regularly scheduled clinical visits and that obtained from the medical history. Incidence estimates will be calculated using time-to-event analyses (e.g., Kaplan-Meier survival curves) with appropriate calculations of standard errors and 95% confidence intervals. Cox proportional hazard regression models will be used to allow control for other factors, and t-tests will be calculated on the coefficients themselves. Appropriate transformations on explanatory variables will be used as deemed necessary in Cox models. Prevalence estimates will be calculated from estimates of proportions with exact confidence intervals. For a sample size of 275, the standard error of the estimate will not exceed 0.03 (3%) and for a sample size of 60, the standard error of the estimate will not exceed 0.06 (6%).

  Study phs000574

• Add Health: Longitudinal Study of a Nationally Representative Sample of Adolescents in Grades 7-12 in the United States during the 1994-95 School Year, Followed into Adulthood with Five Interviews/Surveys in 1995, 1996, 2001-02, 2008, and 2016-18

  The National Longitudinal Study of Adolescent to Adult Health [Add Health] is an ongoing longitudinal study of a nationally representative U.S. cohort of more than 20,000 adolescents in grades 7-12 (aged 12-19 years) in 1994 followed into adulthood with five interviews/surveys in 1995, 1996, 2001-02, 2008, and 2016-18. Add Health was designed to understand how social environments and behaviors in adolescence are linked to health and achievement outcomes in young adulthood. Add Health contains unprecedented environmental, behavioral, psychosocial, biological, and genetic data from early adolescence and into adulthood on a large, nationally representative cohort with unprecedented racial, ethnic, socioeconomic, and geographic diversity. Add Health has a large, multidisciplinary user base of over 50,000 researchers around the world who have published over 3,400 research articles. Add Health is housed at the Carolina Population Center of the University of North Carolina at Chapel Hill. Add Health datasets are distributed according to a tiered data disclosure plan designed to protect the data from the risk of direct and indirect disclosure of respondent identity. Add Health's large sample size, population diversity and rich longitudinal database of psychosocial, physical, and contextual data will permit investigation of an exceptionally broad range of phenotypes with known genetic variation. Prospective longitudinal measures are available to document change over time in each of these phenotypes, as well as change in the social environment and life experiences, making the Add Health sample ideal for understanding genetic linkages with health and behavior across the life course. The original design of Add Health included important features for understanding biological processes in health and developmental trajectories across the life course of young people, including an embedded genetic sample with more than 3,000 pairs of adolescents with varying biological resemblance (e.g., twins, full sibs, half sibs, and adolescents who grew up in the same household but have no biological relationship), testing of saliva and urine for sexually transmitted infections and HIV, and biomarkers of cardiovascular health, metabolic processes, immune function, renal function, and inflammation. Add Health therefore has critical objective indicators of health status and disease markers in young adulthood, well before chronic illness or its complications emerge in later adulthood. Because DNA has been collected on the full sample at Wave IV, it is possible to link genetic profiles with social, behavioral, and biological measures over time from adolescence into adulthood. Add Health sampled the multiple environments in which young people live their lives, including the family, peers, school, neighborhood, community, and relationship dyads, and provides independent and direct measurement of these environments over time. Add Health contains extensive longitudinal information on health-related behavior, including life histories of physical activity, involvement in risk behavior, substance use, sexual behavior, civic engagement, education, and multiple indicators of health status based on self-report (e.g., general health, chronic illness), direct measurement (e.g., overweight status and obesity), and biomarkers. No other data resource with this expanse of genotype and phenotype data on a large nationally representative longitudinal sample with race, ethnic, socioeconomic, and geographic diversity exists. A complete reference guide on study design and accomplishments can be found on the Add Health website: https://cdr.lib.unc.edu/concern/articles/6t053j27s.

  Study phs001367

• Procardis study on novel susceptibility genes for coronary artery disease (CAD)

  An increased level of Lp(a) lipoprotein has been identified as a risk factor for coronary artery disease that is highly heritable. The genetic determinants of the Lp(a) lipoprotein level and their relevance for the risk of coronary disease are incompletely understood. METHODS: We used a novel gene chip containing 48,742 single-nucleotide polymorphisms (SNPs) in 2100 candidate genes to test for associations in 3145 case subjects with coronary disease and 3352 control subjects. Replication was tested in three independent populations involving 4846 additional case subjects with coronary disease and 4594 control subjects. RESULTS: Three chromosomal regions (6q26-27, 9p21, and 1p13) were strongly associated with the risk of coronary disease. The LPA locus on 6q26-27 encoding Lp(a) lipoprotein had the strongest association. We identified a common variant (rs10455872) at the LPA locus with an odds ratio for coronary disease of 1.70 (95% confidence interval [CI], 1.49 to 1.95) and another independent variant (rs3798220) with an odds ratio of 1.92 (95% CI, 1.48 to 2.49). Both variants were strongly associated with an increased level of Lp(a) lipoprotein, a reduced copy number in LPA (which determines the number of kringle IV-type 2 repeats), and a small Lp(a) lipoprotein size. Replication studies confirmed the effects of both variants on the Lp(a) lipoprotein level and the risk of coronary disease. A meta-analysis showed that with a genotype score involving both LPA SNPs, the odds ratios for coronary disease were 1.51 (95% CI, 1.38 to 1.66) for one variant and 2.57 (95% CI, 1.80 to 3.67) for two or more variants. After adjustment for the Lp(a) lipoprotein level, the association between the LPA genotype score and the risk of coronary disease was abolished. CONCLUSIONS: We identified two LPA variants that were strongly associated with both an increased level of Lp(a) lipoprotein and an increased risk of coronary disease. Our findings provide support for a causal role of Lp(a) lipoprotein in coronary disease.

  Study EGAS00000000055

• Exome Sequencing of Statin-Induced Myopathy Cases

  Severe myopathic events occur in 0.1-0.5% of patients taking statins. Although genetic association studies have identified some possibly associated gene loci, these have not been reproducible in additional studies with independent patient cohorts. A more reasonable explanation for susceptibility to statin-induced myopathy is the presence of rare pathogenic variants in genes important for skeletal muscle structure and function. In support of this, we have previously reported an increased incidence of pathogenic variants in genes causing metabolic myopathies in patients with statin-induced myopathy (Vladutiu et al.,2006). We also reported a patient with statin myopathy who had an RYR1 variant known to be causative of malignant hyperthermia susceptibility (MHS) (Vladutiu et al., 2011). There are a number of genes associated with metabolic myopathies triggered by various factors such as extreme exercise, fasting, extremes in temperature, viral infection and exposure to volatile anesthetics. In addition, many of the genes causing congenital myopathies, myofibrillar myopathies and muscular dystrophies have overlapping phenotypes with these genes. We propose that statins act as an additional trigger inducing myopathic symptoms and many patients with severe statin-induced myopathy have causative genetic variants within similar genes associated with MHS and congenital myopathy. We have analyzed the resultant data using a disease model in which rare pathogenic variants, possibly within multiple genes, are causative of statin-induced myopathy. In this study, we have identified potentially causative genetic variants in greater than 50% of the statin-induced myopathy cases and in particular, rare and possibly pathogenic in the RYR1 and CACNA1S genes were present in 25% of the patient samples studied. Vladutiu, G. D., Simmons, Z., Isackson, P.J., Tarnopolsky, M., Peltier, W.L., Barboi, A.C., Sripathi, N., Wortmann, R.L., Phillips, P.S., (2006). "Genetic risk factors associated with lipid-lowering drug-induced myopathies." Muscle Nerve 34: 153-162. Vladutiu, G. D., Isackson, P.J., Kaufman, K., Harley, J.B., Cobb, B., Christopher-Stine, L., Wortmann, R.L, (2011). "Genetic risk for malignant hyperthermia in non-anesthesia-induced myopathies." Mol Genet Metab 104: 167-173.

  Study phs001342

• Exploring the Genetic Variants Associated with Brain Growth in Children

  Understanding the genetic factors that control brain growth during childhood and adolescence is a priority for neuroscience. Its importance lies partly in the finding that disturbances in the course of brain development characterizes many common childhood behavioral problems. Recent advances in neuroimaging such as the use of non-invasive magnetic resonance imaging have provided a chance to define these trajectories in the living child. The intramural programs of the NIMH and NHGRI have conducted repeated neuroanatomic imaging on children along with the banking of DNA, providing a cohort which is studied for defining developmental trajectories of the brain. A central goal of this cohort is to define the disturbances in brain development that are linked with common behavioral problems, such as excessive impulsivity, hyperactivity and inattention. Studies have demonstrated that problems in these domains are distributed across the entire population and that children with Attention Deficit Hyperactivity Disorder (ADHD) lie at the extreme end of these behavioral dimensions. We found a similar dimensionality in the development of brain regions that are associated with these behavioral problems. Specifically, we showed that the rate of change in both the lateral prefrontal cortex and interconnected striatum during childhood and adolescence was linked to the severity of symptoms of hyperactivity and impulsivity. As symptoms increased, the rate of growth of both structures decreased. The lateral prefrontal cortex and striatum are core components of richly interconnected 'loops' that support a host of cognitive processes, including attention, cognitive control and motor planning. Anomalies in these structures and their connections have been implicated in many childhood behavioral problems, including ADHD. In summary, we aim to identify the common and rare genetic variants that are associated with the developmental trajectories of the lateral-prefrontal cortex and striatum. Identifying genetic variants influencing the growth of these structures may reveal the biological mechanisms underlying dysregulated control of attention, impulse and activity level, which in the extreme constitute ADHD. The study thus could inform our understanding of neurobiology underpinning one of the most common neuropsychiatric disorders of childhood.

  Study phs000962

• NSIGHT North Carolina Newborn Exome Sequencing for Universal Screening (NC NEXUS)

  Since newborn screening (NBS) began in the 1960s, technological advances have resulted in its use in an increasing number of disorders. Recent developments in whole-genome sequencing and its simpler corollary, whole-exome sequencing (WES), now afford the opportunity to comprehensively define the variation within an individual's genome in a rapid and affordable manner. Many challenges arise with the clinical application of genome-scale sequencing and in deriving practical benefits to infants and children. Its utility in NBS has yet to be demonstrated and its application in the pediatric population requires special examination, not only for potential clinical benefits but also for the unique ethical challenges it presents. In this proposal, we outline a highly interdisciplinary approach to identify, confront, and overcome the major challenges that must be met in order to implement deep sequencing technology to enhance current newborn screening in a diverse pediatric population. Overarching Aim 1 will evaluate the utility of WES as a diagnostic tool to extend the utility of current NBS. Using diverse cohorts of infants and young children with known conditions identified through NBS, we will examine the sensitivity and specificity of WES. We will also utilize WES in cohorts of children with known conditions not currently screened as potential candidates for NBS in the future. Overarching Aim 2 will develop and assess a framework for analyzing WES in a clinically oriented framework based on principles of ethics and evidence-based medicine. We will develop strategies to guide clinicians, clinical laboratories, and patients/families in their decisions regarding the inevitable incidental findings that will be detected, in ways that respect the child and protect his/her future autonomy, while also respecting parental interests and rights. Overarching Aim 3 will explore ethical, legal, and social issues (ELSI) involved in informed decision making and develop best practices regarding the return of results after testing. We will develop novel decision support tools and evaluate their usefulness in parental decision making, and examine the burdens placed on clinicians as this new technology is deployed in the vulnerable and special population that are newborns and their families.

  Study phs002095

• NRG-GY017: Atezolizumab before and/or with Chemoradiotherapy in Immune System Activation in Patients with Node Positive Stage IB2, II, IIIB, or IVA Cervical Cancer

  Locally advanced cervical cancer remains an area of high therapeutic unmet need, with ~50% of patients developing disease recurrence despite treatment with chemotherapy combined with radiation. Combination of immune checkpoint blockade with chemoradiation has been explored in this setting, but optimal sequencing of these modalities is unknown. To address this question, we developed and conducted the NCI sponsored trial “Anti PD-L1 (Atezolizumab) as an Immune Primer and Concurrently with Extended Field Chemoradiotherapy for Node Positive Locally Advanced Cervical Cancer”, randomizing patients to atezolizumab administration prior to and concurrent with chemoradiation therapy (CRT) vs. concurrent with CRT (NRG-GY017; N=40, ClinicalTrials.gov Identifier: NCT03738228). Patients were randomized to atezolizumab neoadjuvant and concurrent (Arm A) or concurrent with CRT (Arm B). The study closed to successful accrual of 36 evaluable patients in June 2020. Out of 40 patients consented patients, 4 were never treated. The reasons for that are: 2 were screen failures, 1 withdrew consent, and 1 was not treated due to physician preference. The study incorporated comprehensive collection of pre- and on-treatment tumor biopsies as well as multitime point blood collections. T cell receptor (TCR) sequencing was performed on the tumors as well as pre- and on-treatment peripheral blood, and the data are included with dbGaP submission. Among the 36 eligible and treated patients, there were 30 (17 on Arm A and 13 on Arm B) with pre- and on-treatment peripheral TCR sequencing data. Twenty-five patients (14 in Arm A and 11 in Arm B) had additional tumor TCR sequencing data available, which enabled tracking of tumor-associated TCR clones in peripheral blood. We demonstrate that neoadjuvant atezolizumab administration results in peripheral expansion of higher proportion of tumor-associated TCR clones in Arm A than in Arm B and is associated with favorable 2-year disease-free survival (DFS). No new safety signals were identified. These findings support further evaluation of the neoadjuvant IO and CRT sequencing strategy in locally advanced cervical cancer.

  Study phs003833

• Clinical and Genetic Evaluation of Individuals with Undiagnosed Disorders through the Undiagnosed Diseases Network (UDN)

  The National Human Genome Research Institute and the NIH Clinical Center established the intramural Undiagnosed Diseases Program (UDP) in 2008 to make progress in uncovering, understanding, and treating rare disorders. Based on the success of the UDP, the NIH Common Fund established the Undiagnosed Diseases Network (UDN) in FY 2013 (Phase I, 9/16/2015-8/31/2018) to achieve this type of cross-disciplinary approach to disease diagnosis in academic medical centers around the United States. The NIH Common Fund expanded the network in 2018 (Phase II, 9/1/2018-6/20/2023) to increase the availability of diagnostic services, foster opportunities for collaboration between laboratory and clinical investigators, provide resulting data and protocols to the broader community, and assess development of a sustainable national resource after Common Fund support ends. The UDN transitioned from Common Fund in 2023. The National Institute of Neurological Disorders and Stroke (NINDS) will oversee the Network in Phase III, which launched in July 2023, with help from 17 different NIH Institutes and Centers along with the NIH Office of the Director. With help from patients, family members, patient advocacy groups, a Data Management and Coordinating Center (DMCC), several Clinical Sites, and other stakeholders, the NIH envisions the UDN evolving into a larger, diverse, and self-sustained network that fosters scientific discovery and provides expert diagnostic services for undiagnosed patients across the nation. The overarching goals of the UDN in Phase III include: Continuing the proven success of the UDN in improving the clinical evaluation of difficult-to-diagnose patients using a collaborative team approach and investigating and validating promising new diagnostic technologies. Facilitating research into the etiology of undiagnosed diseases by collecting and sharing standardized, high-quality clinical and laboratory data including genotyping, phenotyping, and documentation of environmental exposures. Promoting a broader integrated and collaborative community across multiple Clinical Sites and among laboratory and clinical investigators prepared to investigate the genetic, pathophysiologic, cell biologic, and molecular mechanisms underpinning these difficult-to-diagnose conditions.

  Study phs001232

• Profiling Genome-Wide Circulating ncRNAs for the Early Detection of Lung Cancer

  Lung cancer remains the leading cause of cancer-related mortality worldwide, with non-small cell lung cancer (NSCLC) accounting for approximately 85% of all cases. Although imaging techniques such as low-dose computed tomography (LDCT), combined with tissue biopsies, have improved early detection rates, current diagnostic approaches are often limited by high false-positive rates, invasiveness, and radiation exposure, which lead to misdiagnosis and increased patient burden. Therefore, there is an urgent need for minimally invasive, accurate, and safe diagnostic biomarkers, particularly those derived from liquid biopsies such as blood-based exosomal RNA.This dataset specifically focuses on plasma-derived exosomal small non-coding RNAs (sncRNAs).A total of 233 de-identified plasma samples were obtained from Rush University Medical Center, including 116 NSCLC patients and 117 non-cancer controls. Exosomes were isolated from plasma, RNA was extracted, and small RNA sequencing was performed using the Illumina NextSeq 500 platform. Data available through dbGaP include individual-level raw sequencing files (FASTQ) and basic phenotype annotations of the plasma cohort.A diagnostic model was initially developed using small RNA-seq data from 1,446 tissue samples obtained from TCGA and GEO, identifying a robust sncRNA signature that distinguished NSCLC from non-cancer samples with an AUC of 0.90 in hold-out tissue validation. This signature was subsequently validated in the plasma exosome cohort, achieving an AUC of 0.84 in independent validation. The model demonstrated consistent diagnostic performance across subgroups stratified by age, sex, smoking history, cancer stage, and NSCLC subtype. Survival and functional analyses further supported the clinical and biological relevance of the identified sncRNAs. It is hoped that this resource will contribute to a better understanding of the sncRNA expression landscape in NSCLC and promote the development of non-invasive biomarkers for early cancer detection. These data may be applied to the investigation of transcriptomic and other risk factors, provide insight into cancer screening, tumor progression mechanisms, and prognosis prediction, and ultimately support precision medicine for NSCLC.

  Study phs004166

• Acute Respiratory Distress Syndrome Clinical Network: Fluid and Catheter Treatment Trial (ARDSNet FACTT-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions.Biospecimens: Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from ARDSNet-FACTT include plasma, DNA, and serum. Please note that use of biospecimens in genetic research is subject to a tiered consent. Objectives: This study evaluated the benefits and risks of Pulmonary Artery Catheters (PACs) in patients with established acute lung injury in a trial comparing hemodynamic management guided by a PAC with hemodynamic management guided by a central venous catheter (CVC) using an explicit management protocol.Background: Optimal fluid management in patients with acute lung injury is unknown. Diuresis or fluid restriction may improve lung function but could jeopardize extrapulmonary organ perfusion.Participants: This randomized study compared a conservative and a liberal strategy of fluid management using explicit protocols applied for seven days in 1000 patients with acute lung injury. The primary end point was death at 60 days. Secondary end points included the number of ventilator-free days and organ-failure-free days and measures of lung physiology. Design: Participants were randomly assigned to a strategy involving either conservative or liberal use of fluids with concealed allocation in permuted blocks of eight with the use of an automated system. Participants were simultaneously and randomly assigned to receive either a pulmonary-artery catheter or a central venous catheter in a two-by-two factorial design.Conclusions: There was no significant difference in the primary outcome of 60-day mortality; however, the conservative strategy of fluid management was associated with improved lung function and shortened the duration of mechanical ventilation and intensive care without increasing non-pulmonary organ failures. These results support the use of a conservative strategy of fluid management in patients with acute lung injury. (NEJM June 15, 2006; Vol 354, No. 24, pp 2564-75; NEJM May 25, 2006; Vol 354, No. 21, pp 2213-24)

  Study phs004165

• Research of factors related to diagnosis, progression, prognosis and treatment of hepato-biliary-pancreatic malignancies

  Advanced cancers with metastasis and/or recurrence are usually resistant and refractory to treatment. In our studies, whole exome sequencing analysis, comprehensive epigenetic analysis and genome-wide expression analysis were performed using cancerous and non-cancerous tissues derived from multicentric cohort study of hepatocellular carcinoma (HCC). The aim of the studies is identification of the refractoriness-related deriver genes for application to novel molecular targeted therapy and preventive medicine. The studies are intended for refractory HCC. High frequency of the tumor recurrence even after curative resection is one of the major difficulties in the treatment of HCC. According to our previous studies, not the recurrence itself, but the recurrence pattern has critical effects on prognosis of the patient with HCC. Then, we analyzed the cancerous and non-cancerous tissues of primary HCC on the point of the recurrence patterns in accordance with or without Milan criteria. The materials were obtained from thirty three patients underwent curative hepatectomy for HCC at Department of Hepato-Biliary-Pancreatic Surgery, Tokyo Medical and Dental University Hospital. Written informed consent from these patients, as well as the institutional review board approved was obtained. The determination of the refractory HCC group (16 cases) was based on the point of the recurrence patterns in accordance with Milan criteria for the recurrent tumor (solitary <5cm, or up to 3 nodules <3 cm, without major vascular invasion or distant metastasis) that has been proposed as the useful criteria of the liver transplantation for HCC. The cellular DNA was extracted from the cancerous and non-cancerous tissues of primary HCC by the phenol-chloroform method. After SNP certification using Genome-Wide Human SNP Array 6.0 (Affymetrix), whole exome sequencing was performed at the Cancer Institute of JFCR, as the support infrastructure. Exome sequencing was performed using HiSeq 2000 (Illumina), and the obtained reads were mapped to the human reference genome (hg19) using BWA software. GATK software was used for local realignment base call recalibration. Single nucleotide variants (SNVs) and indels were analyzed by MuTect and SomaticIndelDetector, as well as visual confirmation by IGV software.

  Study JGAS000052

• Implementation, Adoption, and Utility of Family History in Diverse Care Settings

  The purpose of this study is to address the key question of whether and how family health history (FHH) is adopted as a tool to more efficiently manage patients at risk for breast, colon, ovarian, and hereditary cancer syndromes as well as thrombophilia and coronary heart disease (CHD) and to provide evidence supporting clinical utility -- improved health behaviors in patients and physician screening recommendations. Five health care delivery organizations will participate in this demonstration project: Duke University, the Medical College of Wisconsin, the Air Force, Essentia Health, University of North Texas. Duke will serve as a coordinating center for this project (Pro00043372) as well as a site. Healthcare Effectiveness Data and Information Set (HEDIS) measures as intermediate clinical effectiveness measures for Coronary Heart Disease (CHD) and selected cancers as well as survey/formative data and electronic medical record (EMR) data will be used as outcomes measures. The research model is purposely designed to mimic clinical delivery as an important step toward widespread implementation and sustainability. In addition, a cost-effectiveness analysis comparing usual care to the FHH guided preventive health model will be used. The completion of this project will result in an optimal strategy for integration of FHH data collection and clinical decision support (CDS) tools into an EMR and demonstrate the utility of the FHH intervention among diverse primary care patients, their settings, their providers, and the health systems that deliver their care. Specific Aim 1: To optimize the collection of patient entered FHH in diverse clinical environments for coronary heart disease, thrombosis, and selected cancers Specific Aim 2: To export FHH data to an open clinical decision support (open CDS) platform and return CDS results to providers and patients (and to EMRs where relevant). To explore the integration of genetic risk and FHH data at selected sites. Specific Aim 3: To assess the clinical and personal utility of FHH using a pragmatic observational study design to assess reach, adoption, integrity, exposure, and sustainability, and to capture, analyze, and report effectiveness outcomes at each stakeholder level: patient, provider, and clinic/system. Specific Aim 4: To take a leadership role in the dissemination of guidelines for a FHH intervention across in diverse practice settings. AAA Hypertension Lupus Multiple sclerosis Obesity Osteoporosis Thyroid disease Rheumatoid arthritis Blood clotting (6): Blood Clot (high risk features) Factor V PT mutation AT III deficiency Protein S deficiency Protein C deficiency Brain Disorders (5): Dementia Hemorrhagic stroke Ischemic stroke Macrocephaly Seizure Cancer/Adenomas (32): Bone cancer Brain cancer Breast cancer Colon cancer Adrenal cortex tumor Neuroendocrine tumor Paraganglioma Pheochromoctyoma Pituitary adenoma Medullary thyroid cancer Non-medullary (follicular or papillary) thyroid cancer Don&#39;t know type of thyroid cancer Thyroid nodule Other type of endocrine cancer Esophageal cancer Kidney cancer Leukemia Lipoma Liver cancer Muscle cancer Ovarian cancer Pancreatic cancer Prostate cancer Rectal cancer Retinoblastoma Melanoma Non-melanoma skin cancer Do not know type of skin cancer Small bowel cancer Stomach cancer Uterine cancer Other type of cancer Cardiovascular/heart/artery disease (5): Atrial fibrillation Carotid stenosis Heart attack/coronary artery disease Peripheral arterial disease Other heart disease Diabetes (3): Gestational diabetes Diabetes type I Diabetes type 2 Digestive Disorders (5): Colon polyp Crohn&#39;s disease Irritable bowel syndrome Ulcerative colitis Other digestive disorder Eye Disorder (3): Blindness Glaucoma Macular degeneration Hereditary Cancer Syndromes (22): Birt-Hogg-Dube syndrome Cowden syndrome Familial adenomatous polyposis Hereditary breast and ovarian cancer syndrome Hereditary diffuse gastric cancer Hereditary leiomyomatosis and renal cell carcinoma syndrome Hereditary melenoma Hereditary papillary renal cancer syndrome Hereditary paraganglioma-pheochromocytoma syndrome Hereditary retinoblastoma Juvenile polyposis Li-Fraumeni syndrome Lynch syndrome Mutyh-associated polyposis Malignant hyperthermia susceptibility Multiple endocrine neoplasia type 1 Multiple endocrine neoplasia type 2 Nevoid basal cell carcinoma syndrome Peutz-Jeghers syndrome Tuberous Sclerosis complex Von-Hippel Lindau syndrome Other hereditary cancer Hereditary Cardiovascular syndromes (10): Long qt Brugada Catecholaminergic polymorphic ventricular tachycardia Hypertrophic cardiomyopathy Dilated cardiomyopathy Left ventricular non-compaction syndrome Arrhythmogenic right ventricular dysplasia Ehlers-Danlos syndrome Marfan syndrome Other hereditary cardiovascular syndrome High cholesterol (2): Hyperlipidemia Familial hypercholesterolemia Kidney Disease (6): Cystic kidney disease Diabetic kidney disease Kidney nephrosis Nephritis Nephrotic syndrome Other kidney disease Liver Disease (6): Alpha 1 antitrypsinase deficiency Auto-immune hepatitis Hereditary hemochromatosis Primary biliary cirrhosis Sclerosing cholangitis Wilson&#39;s disease Lung Disease (3): Asthma COPD/chronic bronchitis/emphysema Other lung disease Psychological disorder (14): Addiction ADHD Autism Bipolar Depression Eating disorder Intellectual disability Obsessive compulsive disorder Panic disorder Personality disorder PTSD Schizophrenia Social phobia Sickle cell/thalassemia (3): Sickle cell disease Sickle cell trait Thalassemia

  Study phs001641

• Multiple Myeloma Genomic Study (MMGS)

  Multiple Myeloma (MM) is a plasma cell dyscrasia characterized by bone marrow (BM) infiltration and lytic bone lesions. Recent studies of massive parallel sequencing of tumor cells obtained from the BM of patients with MM have demonstrated significant clonal heterogeneity in MM. Despite this remarkable clonal heterogeneity, it could be envisioned that such clonal diversity may be even higher since single BM samples only represent a small fraction of the whole BM compartment, and the pattern of BM infiltration in MM is typically patchy. In addition, BM biopsies are painful and cannot be repeated multiple times during the course of therapy, indicating a need for less invasive methods to molecularly characterize MM patients and monitor disease progression during the therapy. Thus, optimal characterization of circulating tumor cells (CTCs) may represent a non-invasive method to capture relevant mutations present in PC clones. In addition, MM almost always progresses from precursor states of monoclonal gammopathy of undetermined significance (MGUS)/smoldering multiple myeloma (SMM) to overt MM. However, some patients rapidly progress from MGUS/SMM to overt MM (progressors) with a rate of progression of up to 70% over 5 years, while others remain indolent with minimal progression over the same time period (non-progressors). Although many patients are diagnosed with earlier phases of disease, most patients do not receive treatment until their disease progresses, at which time they have overt end-organ damage. This concept of initiating therapy at the time of symptomatic disease is analogous to initiating therapy in patients with solid tumors only after the development of measurable metastatic disease. It is therefore not surprising that cure is not achieved for most patients with MM. Interestingly, studies have demonstrated that MGUS/SMM clones may already harbor chromosomal alterations (Ig loci or hyperdiploidy) and that progression to MM is mainly due to expansion of clones that were already present in the early stages of MGUS/SMM. However, the biological factors that discriminate progressors from non-progressors in MGUS/SMM are not well known. Therefore, our overarching hypothesis is that an effective therapeutic intervention will result from defining genomic and transcriptomic markers that are associated with disease progression. We believe, therefore, that focused research studies that define molecular mechanisms of clonal evolution in MGUS/SMM/MM will identify novel biomarkers of disease progression and help develop therapeutic agents that prevent or delay progression from MGUS to overt MM. Indeed, by eradicating the disease at the precursor stages, MM may become a preventable disease. Recently, a new term called Clonal Hematopoiesis of Indeterminate Potential (CHIP) has been proposed to describe asymptomatic individuals with hematologic malignancy-associated somatic mutations. Those individuals do not fulfill any diagnostic criteria for any hematological malignancy yet they have a tendency to progress into myelodysplastic syndrome (MDS) or myeloid or lymphoid neoplasia at a rate of around 0.5-1% per year, similar to MGUS. The frequency of CHIP and role of HSCs mutations in enhancing acquisition of somatic mutations in MM plasma cells, allowing progression following treatment, has not been studied. Investigating the dysregulated pathways in early progenitor cells would allow us to understand the reasons of progression and establish novel therapeutic and potentially preventive strategies. This study dissects genomic and transcriptomic characteristics of clonal evolution from MGUS/SMM to MM as well as the characteristics of the tumor microenvironment/immune cells/peripheral blood. Our hypothesis is that molecular biomarkers will be strong predictors of progression from MGUS/SMM to MM and will allow for the development of novel therapeutic agents that prevent or delay this progression. We aim to define genomic and transcriptomic markers that lead to progression from MGUS/SMM to MM in tumor cells, blood biopsies (cell free DNA and circulating tumor cells), and the tumor microenvironment.

  Study phs001323

• Genetic Testing to Understand and Address Renal Disease Disparities

  People of African ancestry (Blacks) have increased risk of kidney failure due to numerous socioeconomic, environmental, and clinical factors. Two variants in the APOL1 gene (GeneID: 8542) are now thought to account for much of the racial disparity associated with hypertensive kidney failure in Blacks. One in 7 AAs carry this risk allele, but it is nearly absent in other populations; the variants protect against infection with African trypanosomiasis which is endemic to Africa. However, this knowledge has not been translated into clinical care to help improve patient outcomes and address disparities. It is unknown whether patient or clinician knowledge of genetic risk impacts patient care (i.e., renal surveillance, BP medication use/intensification) or outcomes such as BP control and CKD. GUARDD is a randomized trial to evaluate the effects and challenges of incorporating genetic risk information into primary care. Hypertensive, nondiabetic, adults with self-reported African ancestry, without kidney dysfunction, are recruited from diverse clinical settings and randomized to undergo APOL1 genetic testing at baseline (intervention) or at one year (waitlist control). Prior to enrolling their patients, providers are educated about genomics and APOL1. Guided by a genetic counselor, trained staff return APOL1 results to patients and provide low-literacy educational materials. Real-time clinical decision support tools alert clinicians of their patients&#39; APOL1 results and associated risk status at the point of care. Our academic - community clinical partnership designed a study to generate information about the impact of genetic risk information on our primary outcome - patient care (renal surveillance by clinicians, of serum creatinine and/or urine albumin tests. with a sub-aim of reduction of systolic blood pressure). Secondary outcomes include impact on primary outcomes at 12 months, psycho-behavioral differences of patients between groups and over time, clinician knowledge, attitudes and beliefs at baseline and 12 months, and differences in outcomes between those tested and not tested. GUARDD will help establish the effective implementation of APOL1 risk informed management of hypertensive patients at high risk of CKD, and will provide a robust framework for future endeavors to implement genomic medicine in diverse clinical practices. It will also add to the important dialog about factors that contribute to and may help eliminate racial disparities in kidney disease.

  Study phs001620

• Circulating Genomic Determinants of Treatment Failure in Hodgkin Lymphoma

  In this study, we show that the plasma representation of mutations exceeds the bulk tumor representation in most cases, making classic Hodgkin Lymphoma (cHL) particularly amenable to noninvasive profiling. Leveraging single-cell transcriptional profiles of cHL tumors, we demonstrate hazard ratios (HRs) circulating tumor DNA (ctDNA) shedding to be shaped by DNASE1L3, whose increased tumor microenvironment-derived expression drives high ctDNA concentrations. Using this insight, we comprehensively profile 366 patients, revealing two distinct cHL genomic subtypes with characteristic clinical and prognostic correlates, as well as distinct transcriptional and immunological profiles. Furthermore, we identify a novel class of truncating IL4R-mutations that are dependent on IL13 signaling and therapeutically targetable with IL4R blocking antibodies. Finally, we demonstrate the clinical value of pre- and on-treatment ctDNA levels for longitudinally refining cHL risk prediction, and for detection of radiographically occult minimal residual disease. Collectively, these results support the utility of noninvasive strategies for genotyping and dynamic monitoring of cHL as well as capturing molecularly distinct subtypes with diagnostic, prognostic, and therapeutic potential.Methods utilized include a) targeted genotyping of baseline plasma samples, b) whole exome sequencing (WES) of baseline plasma samples, c) epigenetic expression inference from cell-free DNA-sequencing (EPIC-Seq) to infer gene expression from cell-free DNA (cfDNA) fragmentation profiles, d) ctDNA tracking in on-treatment samples, e) RNA-Sequencing, and f) Phased variant Enrichment and Detection Sequencing (PhasED-Seq).All patients were treated at cancer centers across Europe and North America between 2011 and 2020. The following 3 cancer centers, Stanford (CA, USA), Bellinzona [Confoederatio Helvetica (CH) or Switzerland], and Leuven (Belgium), were included. The 6 clinical trial collectives included in this study are the Phase III trial AHOD1331 trial (NCT02166463) and the Phase II cHOD17 study (NCT03755804) for enrolled pediatric patients, the Phase III AHL2011 (NCT01358747), the Phase II BREACH trial (NCT02292979), a pilot study evaluating concurrent Pembrolizumab with AVD (Doxorubicin, also known as Adriamycin, Vinblastine, and Dacarbazine; NCT03331341), and a Phase II study evaluating PVAB (Prednisone, Vinblastine, Doxorubicin and Bendamustine; NCT02414568) in older patients (61 years and older). In addition, lymph node specimens from a biorepository at St. Jude Children's Research Hospital (TN, USA) were included.

  Study phs003435

• University of Michigan Clinical Sequencing Exploratory Research (CSER)

  Overview. The personalization of therapy for cancer will require molecular characterization of unique and shared genetic aberrations. In particular, patients who have a sarcoma or other rare cancers and are candidates for clinical trials could potentially benefit by identifying eligibility for "targeted" drugs based on the "actionable" genes in their specific tumor. Growing technological advances in genomic sequencing has now made it possible to consider the use of sequence data in a clinical setting. For instance, comprehensive testing that includes whole exome and transcriptome sequencing may identify biomarkers for predictive or prognostic purposes and thereby inform treatment choices and prevention strategies. Thus, the translation of high throughput next generation sequencing would support a "personalized" strategy for cancer. However, the translation of clinical sequencing bears unique challenges including identifying patients who could benefit, developing informed consent and human subjects protections, outlining measurable outcomes, interpreting what results should be reported and validated, and how results should be reported. In addition, we know very little about how patients and clinicians will respond to the potentially confusing and overwhelming amount of information generated by genomic sequencing, and we lack model processes for clinically evaluating and presenting these data. For the promise of our innovative biotechnologies to be realized, "translational genomics" research that evaluates genomic applications within real-world clinical settings will be required. This proposal brings together expertise at the University of Michigan including clinical oncology, cancer genetics, genomic science/bioinformatics, clinical pathology, social and behavioral sciences, and bioethics in order to implement this clinical cancer sequencing project. Three integrated Projects have the following themes: Project 1) "Clinical Genomic Study" will identify patients with a rare cancer (i.e., 15 out of 100,000 individuals per year) who are eligible for clinical trials, consent them to the study, obtain biospecimens (tumor tissue, germline tissue), store clinical data, and assemble a multi-disciplinary Sequencing Tumor Board to deliberate on return of actionable or incidental genomic results; Project 2) "Sequencing &#38; Analysis" will process biospecimens and perform comprehensive sequencing and analysis of tumors to identify point mutations, copy number changes, rearrangements/gene fusions, and aberrant gene expression; Project 3) "Ethics &#38; Psychosocial Analysis" will observe the expert review process for evaluating sequence results and will examine the clinician and patient response to the informed consent process, delivery of genomic sequence results, and use of genomic results.

  Study phs000673

• National Cancer Institute (NCI) TARGET: Therapeutically Applicable Research to Generate Effective Treatments

  The Therapeutically Applicable Research to Generate Effective Treatments (TARGET) Initiative seeks to accelerate research in novel marker and drug development, along with understanding the molecular basis of pediatric malignancy, through identification of genomic changes associated with the following childhood cancers: Acute Lymphoblastic Leukemia (ALL) - A fast-growing type of blood cancer in which too many immature white blood cells are found in the blood and bone marrow. Acute Myeloid Leukemia (AML), including AML Induction Failure cases (AML-IF) - Another type of blood cancer marked by too many myeloblasts, an alternate type of immature white blood cell, are found in the blood and bone marrow. Upon diagnosis, AML patients without high-risk genetic markers undergo standard chemotherapy regimen, called the primary induction phase, to eliminate most cancer cells and induce a remission state. Clear Cell Sarcoma of the Kidney (CCSK) - A rare type of kidney cancer, in which the inside of the cells looks clear when viewed under a microscope. Clear cell sarcoma can spread from the kidney to other organs, most commonly the bone, but also including the lungs, brain, and soft tissues of the body. Neuroblastoma (NBL) - Cancer of cells of the sympathetic nervous system. Cancer Model Systems (MDLS), including PPTP - MDLS includes acute leukemia cell lines and xenografts with matched primary and/or relapsed tumor information, NBL cell lines and xenografts with matched controls, kidney tumor cell lines, normal brain tissues, and embryonic stem cell lines that were sequenced for some TARGET disease projects. Osteosarcoma (OS) - A cancer of the bone that primarily affects children and adolescents. Rhabdoid Tumor (RT) - A rare, fast-growing cancer that usually forms in the kidney or central nervous system (the brain and spinal cord) but can also form in soft tissues in other areas of the body. Rhabdoid tumors tend to spread quickly, are hard to treat, and have a poor prognosis. Wilms' Tumor (WT) - A cancer of cells in the kidney that can spread to the liver, lung and lymph nodes. More information can be found about each TARGET subproject by following the links on the top of this page. Together these cancers account for the majority of the more than 10,000 childhood cancer cases diagnosed in the United States each year. TARGET has employed a set of advanced and complementary genome analysis technologies, including large scale 2nd and 3rd generation genome sequencing, to strategically characterize alterations in both gene expression and in genomic structure (such as deletions and amplification) that are involved in childhood cancers. The goal of this coordinated effort has been to create a comprehensive genomic and transcriptomic profile of each cancer. Integrated analysis of the TARGET data has identified those genes that are either altered in their expression level or mapped to the chromosome regions of deletion/amplification/translocation, as these genes represent strong candidates for therapeutic targeting. To learn more about the TARGET project, which is now completed, visit the website at https://www.cancer.gov/ccg/research/genome-sequencing/target. TARGET data is accessible at the NCI's Genomic Data Commons (GDC) via the GDC's Data Portal and from each of the TARGET Publication Pages at the GDC (Please see the "Supplemental Links" section of any TARGET publication's "Publication Information and Associated Data Files page" at the GDC.). Available datasets include raw sequencing data, datasets generated by the original TARGET research teams (fully annotated clinical information and higher-level/analyzed molecular characterization data - gene expression, copy number variation, epigenetics, targeted sequencing), as well as higher level data generated by the GDC. Please see the TARGET Use and Publication Guidelines for updated details on the sharing of any TARGET substudy data, including how to cite TARGET.

  Study phs000218

• The UCSD / O'Connor "TSP" (Twin/Sibling/Pedigree) Resource in Hypertension

  Study Design: The UCSD / O'Connor "TSP" (Twin/Sibling/Pedigree) Resource in Hypertension contains N=797 participants. At the time of recruitment individuals ranged from 15-84 years of age and had varying ethnic backgrounds (Whites, African-Americans and Hispanics). The cohort was developed to study the genetic basis of autonomic dysfunction in human essential hypertension (reviewed in Zhang et al. Curr Hypertens Rep. 2011 13: 36-45. PMID: 21104344) and contains cross-sectionally collected phenotypes related to blood pressure regulation.&nbsp; Phenotypes: Phenotype data specifically focuses on the sympathetic branch of the autonomic system, which is a key regulator of blood pressure. Data includes circulating concentrations of the secretory "quantum" (catecholamines, neuropeptides, chromogranins) which influence vascular responses to sympatho-adrenal activation resulting in blood pressure. Other measures on the twins and a subset of family members include a standard urine panel with absolute concentrations of potassium, sodium, uric acid, phosphorous; DynaPulse acquired heart rate and blood pressure measures including systolic and diastolic blood pressure, mean arterial pressure, heart rate, Left Ventricular (LV) ejection time, LV contractility, cardiac output, stroke volume data including; and absolute concentrations of plasma aldosterone, endothelin, leptin, and insulin. Phenotype data is included for the 697 individuals sequenced here and 100 family members.&nbsp; Whole Genome Sequence Data Generation: Whole genome sequencing (20X coverage) was conducted on plasma-derived DNA. The WGS was generated using the Illumina HiSeq X Ten sequencing platform with variants called by Human Longevity, Inc (HLI; Ref 1). Preparation of sample libraries was conducted by mechanical shearing of gDNA (100-800 bp), isolation of DNA fragments 300-500bp in size, followed by library PCR amplification employing high-fidelity, low-bias PCR to amplify library fragments consisting of appropriate adapter sequences on both ends. BAM files were created by alignment of sequence reads to the reference genome (GRCh38) using iSAAC-01.14.02.06 (Python2.7). Note: The user may want to realign the sequence data and recall variants. In total, the WGS dataset contains 30 monozygotic twin pairs represented by one member of the twin pair, 133 monozygotic twin pairs with both individuals sequenced, 7 dizygotic twin pairs represented by one member of the twin pair, 67 dizygotic twin pairs with both individuals sequenced, 8 twin pairs with undetermined zygosity (both individuals sequenced) and 1 triplet with mother (all individuals sequenced). The dataset also contains sequences of 260 family members of twins including their mother, father, non-twin sibling, and offspring. Table 1 describes the composition of families ("sibling" refers to a non-twin sibling in the cohort). Note: We suggest users check gender and family relatedness. Table 1: Description of the families with sequence data &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;Units with:Twin PairsTwin (no pairs)No twinSibshipsMother and Father511Mother only1222Father only113One or more siblings22133Mother and siblings132Father and siblings(s)211Offspring of twins11Non twin siblings2Sib with unknown relative1Only one member of8The UCSD/O'Connor "TSP" (Twin/Sibling/Pedigree) Resource in Hypertension is now being managed at the UCSD School of Medicine's Institute for Genomic Medicine (IGM). The TSP Resource has collected a wide range of information (phenotypic, genotypic, demographic, metabolomic) and reagents (blood, plasma, urine, DNA, human induced pluripotent stem cells). For additional information about the resource, including other data types available as well as references and links to data from studies with previous collaborators, please go to the resource website at IGM [http://igm.ucsd.edu/research/twins-resource.shtml] or contact Dr. Brinda Rana at UCSD [bkrana@ucsd.edu].&nbsp;

  Study phs002230

• How to use EGA Webin?

  EGA Webin EGA Webin serves as a platform for registering metadata for array based submissions, large scale sequence submission as well as for legacy EGA submission accounts (ega-box-XXXX). For large scale submitters of sequence data you have also the option to submit metadata via XMLS programmatic submission, while new submitters are advised to utilise the Submitter Portal for their submissions. You can request a legacy EGA submission account (ega-box-XXXX) by populating this form. Please, allow two business days for our Helpdesk team to contact you after populating this form. WEBIN actions: Register metadata for a sequence submission Register study, samples, experiments, runs, DAC, policy and dataset/s after file upload. Register components for your array-based metadata submission Register study, samples, DAC or policy before uploading files. Edit existing submission metadata Change or update previously submitted metadata. Register metadata for a sequence submission Ensure that all sequence files have been encrypted before uploading them to your submission account using the EgaCryptor. Go to the EGA Webin and log in using your submission account name (ega-box-XXX) and password. Register components of your metadata submission Study Samples Data Access Committee (DAC) Data access policy Dataset For array-base submissions: Study, Samples, Data Access Committee (DAC) and Data access policy may all be registered BEFORE file upload and dataset registration through the array-base template. Register your Study Go to the “Studies (Projects)” box Click on “Register Study” and fill in the information related to your study. Click on “Submit”, this will save the information and generate an EGA study ID. To use the study accession number in a publication, the study has to be previously released on the EGA website, we suggest the following format: "Sequence data has been deposited at the European Genome-phenome Archive (EGA), which is hosted by the EBI and the CRG, under accession number EGASXXXXXXXXXXX.Further information about EGA can be found on https://ega-archive.org and “The European Genome-phenome Archive in 202 "(10.1093/nar/gkab1059)" Register your Samples Go to the “Samples” box Click on “Register Samples” Select “Download spreadsheet to register samples” and customise your template, there is a default EGA template (EGA default checklist) but more attributes can be added if required. For the EGA default checklist, there are mandatory,recommended and optional attributes. As well custom fields which can be added if required. Mandatory attributes Field Name Description tax_id Taxonomy ID of the organism as in the NCBI Taxonomy database. Entries in the NCBI Taxonomy database have integer taxon IDs. See our tips for sample taxonomy here scientific_name Scientific name of the organism as in the NCBI Taxonomy database. Scientific names typically follow the binomial nomenclature. For example, the scientific name for humans is Homo sapiens. sample_alias Unique name of the sample. If not selected system will auto generate an unique alias sample_title Title of the sample sample_description Description of the sample phenotype *** Where possible, please use the Experimental Factor Ontology (EFO) to describe your phenotypes. Recommended attributes Field Name Description subject_id Identifier for the subject where the sample has been derived from gender * Sex Optional attributes Field Name Description sex sex of the organism from which the sample was obtained disease_site Affected organ sample type Affected organ donor_id ** Identifier of the donor where the sample has been derived from *Gender should be described as 'male', 'female' or 'unknown'. If 'unknown' due to a known sex chromosome aneuploidy, please create a user defined attribute called 'Sex chromosome karyotype' and add the appropriate value, for example, 'XXY'. **Donor id (Subject id) should be a de-identified subject handle. If unknown, please add 'unknown' to the field. ***Phenotypes should, where possible, be an Experimental Factor Ontology accession. If a term cannot be found to describe your phenotype please use free text. All sample phenotypes considered important for further analysis of the data should be provided (for example, tumour type), additional phenotype attributes can be created by defining your own attributes; use the notion 'phenotype2', 'phenotype3', etc. After you have customised the fields for the sample submission, download the template and fill in the information. Example of the sample template: Finally upload the sample template to get the EGA accession IDs for the samples. Register your Data Access Committee (DAC) Further information on the role of your DAC Go to the “Data Access” box Click on “Register Dacs” Input the information about the DAC and register at least one main DAC contact. Register your Data Access Policy Your Data Access Policy provides the terms and conditions of data use, this is also referred to as the Data Access Agreement (DAA). Completion of a DAA by the applicant/s should form part of the application process to the Data Access Committee (DAC). Go to the “Data Access” box Click on “Register Policies” Select the DAC to which this policy will be linked to and fill in the policy information. Submitting your Runs and Analyses This section is only for sequence data submission, for array-based submission it can be skipped. Please refer to our Submitting array based metadata Runs Registration Go to the “Raw Reads (Experiments and Runs)” box Click on “Submit Reads” Select “Download spreadsheet template for Read submission” Select the template corresponding to your submission type For the templates you have the option to customise the optional fields. To check their description click on “Show Description “ Download the template and fill in the required information. Example of the runs template: We recommend that Fastq, BAM, and CRAM read files are submitted using Webin-CLI When using this interface instead of Webin-CLI, raw sequences must be uploaded in one of the supported data formats before they can be submitted. The files can be uploaded using FTP or Aspera. The study and the sequenced samples must be pre-registered before the raw reads are submitted. Please note that each individual study and sample should be registered only once. You will be asked to provide information about the sequencing libraries and instruments. Submitting your Dataset This section is only for sequence data submissions, for array based submissions it can be skipped. Please refer to our Submitting array based metadata The dataset describes the data files, defined by the run (EGARXXXXXXXXXXX) and analysis (EGAZXXXXXXXXXXX) accessions that make up the dataset and links the collection of data files to a specified Data Access Committee and Data Access Policy. As a result, you must have registered your Reads and experiments, Data Access Committee (DAC) and Data access policy before submitting your Dataset. Please consider the number of datasets that your submission consists of, for example, a case control study is likely to consist of at least two datasets. In addition, we suggest that multiple datasets should be described for studies using the same samples but different sequence technologies. Please contact EGA Helpdesk for further assistance. Go to the “Data Access” box Click on “Register Dataset” Select the Data Access Committee (DAC) and Data access policy Register your dataset After submitting your dataset you should contact the EGA Helpdesk to provide a release date for your dataset. Datasets are automatically held (i.e. not released) unless they are affiliated to a study that has already been released. Edit/update existing submission metadata Go to the “Report” section of the object you would like to edit. Locate the object and click on the arrow under action. An option menu will be displayed. Objects can be edited through their XML or with the WEBIN menu. After an object has been edited, changes would be available on the website until the submission is released again. Please contact the EGA Helpdesk if you require further assistance.

  Documentation submission/metadata/submission/EGA_webin

• Reference exome data for Australian Aboriginal populations to support health-based research

  Whole exome sequencing (WES) is a popular and successful technology which is widely used in both research and clinical settings. However, there is a paucity of reference data for Aboriginal Australians to underpin the translation of health-based genomic research. Here we provide a catalogue of variants called after sequencing the exomes of 50 Aboriginal individuals from the Northern Territory (NT) of Australia and compare these to 72 previously published exomes from a Western Australian (WA) population of Martu origin. Sequence data for both NT and WA samples were processed using an ‘intersect-then-combine’ (ITC) approach, using GATK and SAMtools to call variants. A total of 289,829 variants were identified in at least one individual in the NT cohort and 248,374 variants in at least one individual in the WA cohort. Of these, 166,719 variants were present in both cohorts, whilst 123,110 variants were private to the NT cohort and 81,655 were private to the WA cohort. Our data set provides a useful reference point for genomic studies on Aboriginal Australians.

  Study EGAS00001003745

• Infiltrative and drug-resistant slow-cycling cells support metabolic heterogeneity in glioblastoma

  Metabolic reprogramming has been described in rapidly growing tumors, which are thought to mostly contain fast-cycling cells (FCCs) that have impaired mitochondrial function and rely on aerobic glycolysis. Here, we characterize the metabolic landscape of glioblastoma (GBM) and explore metabolic specificities as targetable vulnerabilities. Our studies highlight the metabolic heterogeneity in GBM, in which FCCs harness aerobic glycolysis, and slow-cycling cells (SCCs) preferentially utilize mitochondrial oxidative phosphorylation for their functions. SCCs display enhanced invasion and chemoresistance, suggesting their important role in tumor recurrence. SCCs also demonstrate increased lipid contents that are specifically metabolized under glucose-deprived conditions. Increased fatty acid transport in SCCs is targetable by pharmacological inhibition or genomic deletion of FABP7, both of which sensitize SCCs to metabolic stress. Furthermore, FABP7 inhibition, whether alone or in combination with glycolysis inhibition, leads to overall increased survival. Our studies reveal the existence of GBM cell subpopulations with distinct metabolic requirements and suggest that FABP7 is central to lipid metabolism in SCCs and that targeting FABP7-related metabolic pathways is a viable therapeutic strategy.

  Study EGAS00001003251

• Introducing Federated EGA Affiliates: a newly defined tier in the Federated EGA Network

  We're happy to announce that we are now accepting Affiliates in the Federated EGA Network! Federated EGA is a global network of repositories enabling secure discovery and access to sensitive human data. Currently, Federated EGA consists of Central EGA (CEGA), which serves the global community, and nine national Nodes that serve respective jurisdictions. Did you know that the Federated EGA (FEGA) has always envisioned a third tier within the network? This brings us to FEGA Affiliates, recently defined in the newly approved "Federated EGA Structure and Organisation" document. This new tier broadens the range of institutions or organisations that can become part of FEGA. Thus begins a new era for the network. What is a FEGA Affiliate? A FEGA Affiliate archives and serves controlled-access data within its own governance scope, while still participating in federated discovery through the EGA catalogue. Affiliates can be individual organisations or institutions, healthcare genomics initiatives, consortia of institutions, as well as project-specific consortia (national or international). In practical terms, a FEGA Affiliate: Hosts and safeguards the data it archives. Submits non-personal metadata to CEGA so studies are discoverable and can receive EGA accessions. Manages permissions and data access workflows for its datasets. Provides data access and/or distribution, along with support, to authorised users. Key takeaways about FEGA Affiliates FEGA is now organised into three tiers: CEGA, FEGA Nodes, and FEGA Affiliates. Affiliates archive data from their own organisation and/or selected partner institutions (for example, an international consortium). Affiliates make studies discoverable through the EGA catalogue by submitting non-personal metadata for accessioning. Access decisions and conditions are managed locally by the Affiliate (e.g. distribution or access in a trusted research environment). Are you considering whether your institution or project might be a good fit as a FEGA Affiliate? Would you like to learn more about this tier? We have published a blog post that addresses potential common questions, providing answers on this topic. You can read it here.

  Blog fega-affiliates

• National Eye Institute Glaucoma Human Genetics Collaboration (NEIGHBOR) Consortium Glaucoma Genome-Wide Association Study

  This is a case-control study of primary open angle glaucoma (POAG). POAG is an intraocular pressure (IOP) related progressive optic neuropathy that ultimately leads to blindness. For this study we have formed a collaborative consortium contributing 2170 POAG cases and 2347 controls with a unified definition of POAG (the NEIGHBOR consortium: NEI Glaucoma Human genetic collaBORation). The case definition has also been harmonized with an additional 976 cases and 1140 controls from the NHGRI supported GENEVA (gene-environment) study of glaucoma (GLAUGEN) (NIH/NHGRI U01HG004728, Pasquale PI). Cases and controls were recruited from ophthalmology clinics and were examined by ophthalmologists. For cases, the clinical exam included intraocular pressure measurements, optic nerve assessment and visual field evaluation. Controls had no family history of glaucoma, normal intraocular pressure and normal optic nerves. Cases and controls were also drawn from two clinical trial populations: Advanced Glaucoma Intervention Study (AGIS, NEI U10EY006827, D. Gaasterland PI) and Collaborative Initial Glaucoma Treatment Study (CIGTS, NEI U10 EY009149, P. Lichter PI). The NEIGHBOR consortium has two Co-Principal Investigators: J. Wiggs (Harvard, MEEI), and M. Hauser (Duke). The consortium includes eleven different centers where data collection and analysis take place. The eleven sites and investigators are: Harvard Medical School (Massachusetts Eye and Ear Infirmary) (J. Wiggs, L. Pasquale); Duke University Medical Center (M. Hauser, E. Hauser, R. Allingham, S. Schmidt); University of Michigan (J. Richards, S. Moroi, P. Lichter); University of Miami (M. Pericak-Vance, R. Lee, D. Budenz); Vanderbilt University (J. Haines); University of California San Diego (K. Zhang, R. Weinreb; T. Gaasterland); University of Pittsburgh (J. Schuman, G. Wollstein); University of West Virginia (A. Realini, J. Charlton, S. Zareparsi); Johns Hopkins University (D. Friedman, D. Zack); Stanford University (D. Vollrath, K. Singh), Eye Doctors of Washington (D. Gaasterland). Hemin Chin serves as the NEI Staff Collaborator. This national collaborative study is supported by multiple NIH grants: NEI R01 EY015543 (Allingham); NEI U10 EY006827 (D. Gaasterland); NHLBI R01 HL073389 (E. Hauser); NEI R01 EY13315 (M. Hauser); NEI U10 EY009149 (Lichter); NEI R01 EY015473 (Pasquale); NEI U10 EY012118 (Pericak-Vance); NEI R03 EY015682 (Realini); NEI R01 EY011671 (Richards); NEI R01 EY09580 (Richards); NEI R01 EY013178 (Schuman); NEI R01 EY015872 (Wiggs); NEI R01 EY009847 (Wiggs); NEI R01 EY010886 (Wiggs); NEI R01 EY144428 (Zhang); NEI R01 EY144448 (Zhang); NEI R01 EY18660 (Zhang). Funding support for genotyping, which was performed at the Johns Hopkins University Center for Inherited Disease Research, was provided by the National Eye Institute (X01HG005259).

  Study phs000238

• North American Mitochondrial Disease Consortium Patient Registry and Biorepository

  Mitochondrial diseases are caused by dysfunction of the mitochondria, which are specialized compartments that are present in every cell of the body except red blood cells. Mitochondria generate more than 90% of the energy that the body needs to sustain life and support growth. When they fail, less and less energy is generated within the cell. This injures the cell and can cause its death. If this process is repeated throughout the body, whole organ systems begin to fail, and the life of the person in whom this is happening is severely compromised. Mitochondrial diseases primarily affect children, but adult onset is becoming more and more common. Mitochondrial diseases are probably the most diverse human disorders at every level: clinical, biochemical, and genetic. Some affect only the nervous system but most affect many body systems, including the brain, heart, liver, skeletal muscles, kidney, and the endocrine and respiratory systems. Although mitochondrial disorders vary in severity, they are usually progressive, and often crippling. They can cause paralysis, seizures, mental retardation, dementia, hearing loss, blindness, weakness and premature death. Because of the range of symptoms and the frequent involvement of multiple body systems, mitochondrial diseases can be a great challenge to diagnose. Even when accurately diagnosed, they pose an even more formidable challenge to treat, as there are very few therapies and most are only partially effective. About this Study The first objective of this study is to establish a clinical registry of patients with suspected or confirmed mitochondrial diseases. We are collecting medical and family history, diagnostic test results, and prospective medical information for these patients and, using agreed procedures developed by the leading research clinicians in the field, providing, for the first time, standardized diagnoses of these complex disorders for the patients. The clinical information we collect from the participants will be used to learn about the spectrum of mitochondrial disorders and their prevalence. We will also develop studies which allow us to better understand how these diseases progress, which we do not understand well enough. When we begin clinical trials for mitochondrial diseases, patients enrolled in the registry who are identified as potentially eligible will be offered enrollment. Patients will only be included in studies if they give their consent in advance. The second objective of this study is to establish a biorepository for specimens and DNA from patients with mitochondrial diseases, in order to make materials easily available to consortium researchers.

  Study phs001538

• Germline and Somatic Genetic Landscape of Pediatric Rhabdomyosarcoma

  Dynamic approaches that integrate population-based research and molecular biology are needed to explain the mechanisms underlying pediatric rhabdomyosarcoma (RMS) and to determine novel prevention strategies. RMS, the most common soft-tissue sarcoma in children and adolescents, has one of the poorest 5-year survival rates among all pediatric cancers (less than 65%). One of the strongest risk factors for RMS is having a cancer predisposition syndrome. The syndromes that are most commonly seen among those with RMS are Li-Fraumeni, neurofibromatosis type 1, Costello, Noonan, and DICER1. Based on smaller clinic-based studies, only about 7% of RMS cases are thought to be associated with the genes responsible for these syndromes. However, there have been no population-based assessments to support this estimate. Even in the most recent large-scale evaluations of germline mutations in predisposition genes among children with cancer, very few RMS cases were included (43 cases). Furthermore, no distinctions were made between the major histologic subtypes of RMS: embryonal (eRMS) and alveolar (aRMS), which display differences in terms of age distribution, incidence, and cytogenetics. For instance, nearly 80% of alveolar cases are driven by a chromosomal translocation between either PAX3 or PAX7 and FOXO1, whereas these fusions are not seen in embryonal cases. In fact, RMS research is shifting from categorization based on histology to fusion status (eRMS is overwhelmingly fusion-negative). Another limitation in previous studies has been the inability to evaluate the frequency of de novo germline mutations (DNMs) in cancer predisposition genes due to the absence of any well-characterized cohorts of RMS case-parent trios. Therefore, a major gap in our understanding of the role of cancer predisposition in pediatric RMS that limit translational impact is there have been no population-based assessments to determine the true impact of these mutations on pediatric RMS, which limits clinical sequencing guidelines and surveillance protocols in these children.Overall Project Strategy: The objective of this project is to advance our understanding of the relationship between cancer predisposition genes and pediatric RMS. Our central hypotheses are: 1) mutations in cancer predisposition genes are more common than expected in children with RMS; and 2) children with fusion-negative tumors have a higher burden of germline mutations than those with fusion-positive tumors. The framework for this study relies on &gt;600 well annotated samples collected from newly diagnosed RMS patients and stored in the Children&#8217;s Oncology Group (COG) Biopathology Center.

  Study phs002304

• Randomized Evaluation of Sedation Titration for Respiratory Failure (RESTORE-BioLINCC)

  Data Access NOTE Please refer to the "Authorized Access" section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives The primary aim of the RESTORE clinical trial was to determine whether critically ill children managed with a nurse-implemented, goal-directed sedation protocol would experience fewer days of mechanical ventilation than participants receiving usual care. Background Ensuring the safety and comfort of critically ill infants and children supported by mechanical ventilation is integral to the practice of pediatric critical care. Although sedation therapy benefits young participants who cannot understand the imperative nature of invasive life-sustaining therapies, sedative use is also associated with untoward adverse effects. Specifically, opioids and benzodiazepines commonly used for pediatric sedation may impair bedside neurological assessment, depress spontaneous ventilation, and prolong mechanical ventilation. Over time, drug tolerance develops, which may precipitate iatrogenic withdrawal syndrome when sedation therapy is no longer necessary.Numerous studies in adult critical care support a minimal yet effective approach to sedation management. Sedation goals for mechanically ventilated adults have shifted from an unresponsive state to a calm, easily aroused, readily evaluated participant. Studies in adult participants evaluating targeted sedation, daily interruption and/or titration of sedation, pairing of spontaneous awakening with breathing, and no sedation have reported improved clinical outcomes, including decreased length of mechanical ventilation when compared with usual care. In contrast, few data inform sedation practices in pediatric critical care, and international studies describe significant practice variation. Given unique biobehavioral differences, knowledge generated in adult critical care may not translate to the care of critically ill children. The RESTORE study was conducted to test the effect of a nurse-implemented, goal-directed sedation protocol on clinical outcomes in pediatric participants with acute respiratory failure. Participants There was a total of 2,449 participants (mean age: 4.7 years; range: 2 weeks to 17 years). Design The RESTORE study was a cluster randomized clinical trial conducted in 31 US PICUs. Intervention PICUs (17 sites; 1,225 participants) used a protocol that included targeted sedation, arousal assessments, extubation readiness testing, sedation adjustment every 8 hours, and sedation weaning. Control PICUs (14 sites; 1,224 participants) managed sedation per usual care. The primary outcome variable was duration of mechanical ventilation. Conclusions Among children undergoing mechanical ventilation for acute respiratory failure, the use of a sedation protocol compared with usual care did not reduce the duration of mechanical ventilation. Exploratory analyses of secondary outcomes suggest a complex relationship among wakefulness, pain, and agitation (JAMA 2015; 313(4):379-89).

  Study phs003783

• DNA methylomes of monozygotic twins clinically discordant for multiple sclerosis

  Multiple sclerosis (MS) is an inflammatory demyelinating disease of the central nervous system. Although genetic susceptibility is important, a modest concordance rate for MS in monozygotic (MZ) twins suggests that interaction with other risk factors is required to develop clinical symptoms. In this study, we examined whether DNA methylation differences contribute to the discordant clinical manifestation of MS in MZ twins, and studied the impact of MS treatments on the DNA methylome. Genome-wide DNA methylation profiles of peripheral blood mononuclear cells (PBMCs) of 45 MZ twins clinically discordant for MS were generated using the Illumina HumanMethylationEPIC array. Repetitive element methylation and selected differentially methylated positions (DMPs) were validated using targeted deep bisulfite sequencing (TDBS). In addition, we performed whole genome bisulfite sequencing (WGBS) to profile CD4+ memory T-cells of a subset of four MS discordant MZ twins. Our results show that interferon treatment causes robust DNA methylation changes and several epigenetic biomarkers for interferon treatment response were identified. However, overall the PBMC-based methylomes of the MS discordant MZ twins were highly similar, since large systematic methylation differences (&gt;5%) were absent in the data. This suggests that previously reported large methylation changes are probably caused by genetic rather than epigenetic differences. In addition, our data does not support the hypothesis that the observed maternal parent-of-origin effect in MS is due to genomic imprinting errors, and no evidence was found that copy number variations explain the discordant phenotype in these MZ twins. Although not genome-wide significant, a couple of DMPs associated with the MS phenotype were identified and successfully technically replicated using TDBS, including a differentially methylated region (DMR) in the promoter of the transmembrane protein encoding gene TMEM232. Another MS-associated DMP, located in an enhancer in the gene body of the transcription factor ZBTB16, was also associated with medium-term glucocorticoid treatment history. WGBS analysis confirmed this DMP as a promising epigenetic biomarker for glucocorticoid treatment. In conclusion, this epigenome-wide association study (EWAS) in genetically identical twins identified a DMR in the TMEM232 promoter as a candidate loci associated with the clinical manifestation of MS. In addition, epigenetic biomarkers for MS treatments were identified, revealing that not only short-term, but also medium-term treatment effects are detectable in immune cells, which should be taken into account in future EWAS designs.

  Study EGAS00001003147

• The EGA Helpdesk team: 2025 in review and what we are building next

  Behind every dataset submitted, every access request processed, and every technical question answered, there is a team working quietly to keep things moving: the Helpdesk (HD). With the onset of 2026, this feels like the right moment to look back on what 2025 has been like for the HD team: the challenges we faced, how we adapted, and where we're heading next. Why the Helpdesk matters to EGA The EGA Helpdesk is more than a support channel. It plays a key role in maintaining trust in the EGA ecosystem. By supporting data submitters, researchers, Data Access Committees (DACs), and institutional partners, the HD helps ensure that data can flow securely, efficiently, and reliably. When issues arise, the Helpdesk is often the first place where their impact is felt and addressed. In that sense, the HD sits at the intersection of technology, policy, and people. One Helpdesk, two locations, one shared mission The EGA Helpdesk is a joint, distributed team working closely across two locations: CRG (Barcelona, Spain) and EMBL-EBI (Cambridge, UK). Although we are based in different institutions, we operate as a single Helpdesk, with shared workflows, priorities, and responsibility towards users. At CRG, the HD team is formed by: Andrea Max Àlex and me At EMBL-EBI, we work closely with: Silvia Coline Aravind What defines us as a team is simple: we work user-first, even under pressure. In a highly technical environment, clarity, empathy, and consistency matter just as much as tools and processes. A close collaboration across sites is essential to making that happen. What does the EGA Helpdesk do? The HD supports users across the full lifecycle of data in EGA. This includes: Data submissions, uploads, and encryption workflows. Data access requests and permissions. Questions around policies, consent, and data usage. Technical and system-related issues. Coordination between users, internal teams, and external partners. 2025: growth, change, and recalibration 2025 was a year of growth, but not always a predictable one. Early in the year, several technical and system-related challenges required us to adjust our original plans. Priorities shifted, timelines changed, and some improvements had to be rethought. For the HD team, this is often the hardest part of the job: we see delays through the eyes of users and understand the real impact they can have on ongoing research. One of the key lessons from 2025 was that stability is not only a technical challenge, but also an organisational one. Teamwork proved to be essential: anticipating peak periods, sharing context early, and coordinating closely across teams made a tangible difference. When things became complex, working together across roles and locations was what allowed us to keep moving forward. In 2025, the Helpdesk received 5.313 tickets and resolved 5.511 requests, reflecting both increased adoption of EGA and the team’s ability to absorb higher demand. At the same time, demand continued to grow. Compared to 2024, ticket creation increased by over 6%, while resolution capacity grew by more than 11%. The team not only kept up with incoming requests but also resolved part of the accumulated backlog, finishing the year having solved more tickets than were created. The real challenge of 2025 was not overall performance, but how the workload was concentrated during peak months. Seasonality and demand spikes placed pressure on the system, even while overall efficiency remained strong. On a team level, 2025 was also a year of transition. I joined the HD leadership role in January 2025, stepping into a period of change and rapid learning. Later in the year, in October, we said goodbye to Raül, and in January 2026, we welcomed Àlex, strengthening the team for the next phase. What users needed most in 2025 While requests vary widely, some themes stood out throughout the year: Support with data submissions and uploads Data access requests and permissions Technical and system-related issues As EGA matures, day-to-day operations have become more complex. Many long-running tickets are not delayed due to a lack of follow-up, but because they depend on external approvals, cross-institutional coordination, or multi-step processes. Understanding these patterns helps us focus not just on resolving tickets, but on improving how work flows through the system. Looking ahead to 2026 With a reinforced team and clearer insights from 2025, our focus for 2026 shifts from throughput to flow. Key priorities include: Strengthening our web content and documentation Reducing structural backlog Improving cross-team and cross-system coordination Anticipating peak demand earlier and planning capacity accordingly Challenges will continue to arise in 2026, as they always do. However, 2025 reinforced something important: a stable, empathetic, and well-aligned Helpdesk team is essential to supporting EGA's mission at scale. Supporting users well means supporting research, and that remains at the core of what we do.

  Blog ega-helpdesk-team-2025-in-review-and-upcoming-improvements

• National Cancer Institute Cancer Genome Characterization Initiative (CGCI)

  The Office of Cancer Genomics at the National Cancer Institute sponsored a series of studies as part of the Cancer Genome Characterization Initiative (CGCI) to assess novel emerging sequencing technologies in cancer. The CGCI program included comprehensive characterization of the genetic aberrations found in different pediatric and/or adult tumors. CGCI characterized a number of B-cell non-Hodgkin lymphomas (including diffuse large B-cell lymphoma (DLBCL) from patients with and without HIV+ infection, follicular lymphoma (FL), as well as adult and pediatric Burkitt lymphomas), and additional HIV-associated tumors (including DLBCL, lung, and cervical cancers). All data from these projects is available at the NCI Genomic Data Commons. Individual project descriptions are available by disease on the substudy pages (links are included at the top of this page). Brief summaries are as follows: Non-Hodgkin Lymphoma (NHL) - CGCI investigators probed genomic alterations more deeply than had previously been possible by using state-of-the-art RNA sequencing (mRNA-seq) and whole genome shotgun sequencing (WGS) coupled with leading edge bioinformatics, data management and analysis approaches. The project sequenced tumor DNA and/or RNA from 117 NHL tumor samples and 10 cell lines. This included the genomes or exomes of 1 Follicular Lymphoma (FL) and 13 diffuse large B-cell lymphoma (DLBCL) cases, all with matched constitutional DNA sequenced to comparable depths, RNA-sequencing (mRNA-seq) of 92 DLBCL, 12 FL and 8 B-cell NHL cases with other histologies and 10 DLBCL-derived cell lines. The DLBCL cases and cell-lines are from the two major subtypes of DLBCL: germinal center B-cell (GCB) and activated B-cell (ABC). HIV+ Tumor Molecular Characterization Project (HTMCP) - This project was a joint effort of the Office of Cancer Genomics (OCG) and the Office of HIV and AIDS Malignancy (OHAM). Its goals were to characterize HIV-associated cancers (obtained from HIV-infected patients) and compare them to the same types of cancers from patients without HIV infection. Investigators performed 30X genome sequencing of 100 cases of paired tumor and germline DNA, along with transcriptome sequencing in each of 3 types of HIV+ tumors (DLBCL, lung and cervical cancers). These platforms allow discovery of mutations both in coding and non-coding genomic regions, gene expression and genomic alterations (including translocations, insertions and deletions). Comparing tumors of cancer patients both with and without HIV-infection provides insight into the potential function of this virus in certain cancers. Burkitt Lymphoma Genome Sequencing Project (BLGSP) - This project was a collaborative effort between the National Cancer Institute and the Foundation for Burkitt Lymphoma Research to develop a databank of the many alterations found in Burkitt lymphoma (BL), an uncommon type of Non-Hodgkin lymphoma that occurs most often in children and young adults. The goal of the BLGSP was to explore potential genetic changes in patients with BL that could lead to better prevention, detection and treatment of the cancer. The project characterized the alterations of the tumors' genomes (with matched normal as control) and transcriptomes by sequencing the DNA and RNA of each case. Using the data generated, the ultimate goals of the project was to discover the molecular changes that are present in BL patients and then determine how those changes correlate with treatment regimen and outcome. CGCI data is accessible at the NCI's Genomic Data Commons (GDC) via the GDC's Data Portal and from each of the CGCI Publication Pages at the GDC (Please see the "Supplemental Links" section of any CGCI publication's "Publication Information and Associated Data Files page" at the GDC.). Available datasets include raw sequencing data, datasets generated by the original CGCI research teams (fully annotated clinical information and higher-level/analyzed molecular characterization data), as well as higher level data generated by the GDC. Please see the CGCI Use and Publication Guidelines for updated details on the sharing of any CGCI substudy data, including how to cite CGCI.To learn more about the CGCI studies, please visit the CGCI Program website.

  Study phs000235

• CSER: Genomic Sequencing to Aid Diagnosis in Pediatric and Prenatal Practice: Examining Clinical Utility, Ethical Implications, Payer Coverage, and Data Integration in a Diverse Population

  Congenital abnormalities and developmental disorders affect 3-5% of live born infants and children. Despite advances in both pre- and post-natal treatment, the utility of genetic testing in diagnosing the etiology underlying such conditions in order to guide management has been frustratingly limited. Traditional genetic testing with specific gene tests, or even gene panels, is diagnostic in only a small percentage of cases. Recent technological advances in next generation sequencing (NGS) have led to the ability to sequence and interpret the entire exome relatively quickly, allowing a diagnosis in 25-30% or more of cases of developmental disorders when other genetic tests have not yielded a result. Although whole exome sequencing (WES) holds great promise for improved diagnosis leading to better clinical outcomes, challenges remain in determining how best to apply and utilize sequence data. Fulfilling the promise of WES also requires investigation of ELSI (ethical, legal, social) concerns, given skepticism in some communities that research will benefit them; economic considerations that ultimately determine access to and equitable use of WES; and a need to share clinical genetic results with families and across health care systems to enable better prognostication and management of rare conditions in community settings. We propose a Program in Prenatal and Pediatric Genomic Sequencing (P3EGS) at UCSF to examine the diagnostic and clinical utility of WES. P3EGS will recruit and study affected individuals and their parents, including pregnancies in which the fetus has a confirmed structural anomaly and children with previously undiagnosed developmental disorders that are likely of genetic etiology. Following consent and collection of standardized phenotypic data, the families will undergo WES as part of clinical care. To achieve diversity, patient ascertainment and recruitment will occur at four UCSF sites that serve a broad range of underrepresented minorities (target of 75%) and span the full socio-economic spectrum, including the underserved. Our specific aims will: 1) examine the clinical utility of WES, including assessment of a variety of health-related and reproductive outcomes, in undiagnosed individuals; 2) address ethical, social and economic issues in the delivery of genomic sequencing results to ancestrally and economically diverse populations through (2.1) a mixed methods, longitudinal empirical study of clinical interactions and experiences, (2.2) an economic analysis of insurance coverage, price and reimbursement of multigene tests, and (2.3) creation of an Ethics Advisory Board to respond to emerging issues and establishment of authentic stakeholder engagement; and 3) pilot a user-friendly web-based patient/provider application integrating genomic and clinical data as a shared evidence base to support result communication, interpretation and clinical decision making; the application will be based on the &#8220;Bioscreen&#8221; model created and successfully implemented at UCSF.

  Study phs002324

• Cryptococcosis in Previously Healthy Adults

  Cryptococcus is a fungus that causes infections most commonly in immunocompromised patients, such as those with AIDS and solid organ transplant recipients and is currently responsible for an estimated 15% of all AIDS-related deaths globally. However, in developed countries, approximately one-third of cases fall outside these groups such that cryptococcal meningoencephalitis (CM) has become the most common cause of non-viral meningitis in the U.S. Within the U.S., approximately 15-20% have no readily identifiable immune defect and cryptococcal infection in these hosts has a mortality rate of 30-50% despite optimal antifungal therapy. NIH Clinical Study Protocol 93-I-0106 (NCT00001352). The objectives of this protocol can be broadly categorized as: 1) Characterize the immunologic and genetic mechanisms predisposing to disease acquisition; 2) Understand the post-infectious inflammatory response and distinguish its consequences from those directly due to fungal growth; and 3) Management of post-infectious neuro-inflammatory syndromes associated with cryptococcal meningitis (CM). This protocol recruits patients who have microbiological evidence of cryptococcal neurologic or non-CNS disease (typically pulmonary or bone). Cerebrospinal fluid (CSF) and blood samples collected during clinical care are used to measure serum and CNS cellular and soluble cytokines as well as to perform in-situ immunohistochemistry. CSF and blood samples are also collected to measure transcriptional (gene expression), proteomic (protein), and lipidomic (lipids) changes that occur throughout disease and treatment. Observational data detailing audiological, ophthalmological and neurocognitive deficits in these patients is also recorded. We have recently described a post-infectious inflammatory syndrome (PIIRS) associated with cryptococcal meningoencephalitis (CM) which can be best described as a neuro-inflammatory state during which CM patients present with altered mental status (Montreal Cognitive Assessment Score As part of the protocol, we treat patients for either microbiological failure or neuroinflammatory sequelae by conventional therapies utilizing FDA-approved pharmaceuticals at FDA-approved doses. To understand and identify the predominant biological pathways responsible for PIIRS neuroinflammation, we examined patient CSF at baseline (at time of PIIRS diagnosis) and post-treatment with different FDA-approved pharmaceuticals at FDA-approved doses compared to CSF from non-PIIRS donors. Upstream pathway analysis of differentially expressed genes in the CSF of PIIRS patients revealed a prominent role for the JAK/STAT pathway in the pathogenesis of PIIRS and support the use of the JAK inhibitor, ruxolinib, as a pathway-instructed therapy to treat PIIRS patients. Data available through dbGaP: single cell RNA sequencing (scRNA-seq) data from CSF cells of a patient with PIIRS at the time of diagnosis and following treatment with steroids (1g solumedrol/day) and NanoString transcriptional data from CSF cells of patients with PIIRS at the time of diagnosis compared to CSF cells from non-PIIRS donors.

  Study phs003871

• Security Overview

  Security Overview The European Genome-phenome Archive (EGA) houses consented human data under controlled access. Access decisions are handled by the relevant Data Access Committee (DAC), which autonomously manages requests through the DAC Portal. This document provides an overview of EGA’s practices in ensuring the security of data stored at EGA. As security is a prime concern of the EGA, the EGA is a member of the Global Alliance for Genomics and Health (GA4GH) Data Security work stream. The EGA contributes and helps develop the recommendations outlined the GA4GH Security Technology Infrastructure document, which defines guidelines, best practices, and standards for building and operating an infrastructure that promotes responsible data sharing in accordance with the GA4GH Privacy and Security Policy. Explore the EGA dataflow to gain deeper insights! Accessing data in the EGA involves several steps. First, users need to create an EGA account. Once logged in, they can request access to data controlled by a DAC through the EGA website (see documentation). The DAC oversees these requests through the DAC Portal, and if approved, grants the necessary permissions to the user's EGA account, allowing them to access and download all relevant data and metadata for the requested dataset(s). The key points of EGA security strategy are: 1 Regular Risk Assessment The EGA regularly identifies and assesses risk related to the following: Breach of confidentiality,Breach of privacy or autonomy,Malicious or accidental corruption or destruction of data archived at EGA,Disruption of services provided by the EGA. 2 Risk mitigation The EGA implements and maintains safeguards to minimise the risks identified above in accordance with the 6 control objectives listed in Appendix 1 and outlined in the GA4GH Security and Infrastructure document.If a breach is discovered, the EGA applies a defined protocol to minimise damage. 3 Identity and authorisation management The EGA authenticates the identity of individuals or software accessing controlled access data held at the EGA.The EGA ensures an appropriate level of assurance (LoA) is applied to the identity consistent with the risk associated with that individual, such as multi-factor authentication for DACs.The EGA provides the minimum access rights and privileges consistent with the user’s identity, allowing access consistent with the GA4GH Privacy and Security Policy, as determined by the appropriate DAC. 4 Audit Logs The EGA maintains a set of logs recording: Changes to user access rights,Data access requests,Resource usage. 5 Cryptography, communication security, and data integrity The EGA ensures data transmission integrity using a hash function.All data transmitted to or from the EGA is end-to-end encrypted.All data at EGA is stored using strong encryption.Encryption keys are not stored in the same system as the encrypted data.All data archived at EGA must be accompanied by a signed submission statement ensuring appropriate consent or ethical approval has been obtained, and is in accordance with all applicable laws and regulations. The EGA has a defined protocol defining the response in the event of a security breach, and is continuing to work with the GA4GH Data Security Work Stream to help define best practice and associated standards for breach responses. Appendix 1 GA4GH Control Objectives Control Objective 1: Implement technology safeguards to minimise the risk of unauthorised access, use, or disclosure of confidential and private data.Control Objective 2: Implement technology safeguards to minimise the risk of discovery, access, and use of individuals’ clinical and genomic data, and individual identities, other than as authorised by applicable jurisdictional law, institutional policy, and individual consents.Control Objective 3: Implement technology safeguards to minimise the risk of accidental or malicious corruption or destruction of data.Control Objective 4: Implement technology safeguards to minimise the risk of disruption, degradation, and interruption of services enabling access to data.Control Objective 5: Implement technology safeguards to minimise the risk of potential security attacks and misuse of authorised accesses and privileges.Control Objective 6: Implement technology safeguards to promptly detect the failure to attain the above control objectives and to respond with proper countermeasures.Appendix 2Refer to the document below to learn more about EGA long-term data preservation policy and procedures at EMBL-EBI.Long-term data preservation

  Documentation about/security

• Demographically Diverse Substance Use Disorder Cohorts of Dr. Stanley H. Weiss

  The Demographically Diverse Substance Use Disorder Cohorts of Dr. Stanley H. Weiss, which constitute the Epidemiology of the Weiss Cohort Projects, consist of a series of inter-connected projects, building upon a set of cohort projects of various groups, mainly drug users from medication-assisted treatment programs, that Dr. Stanley H. Weiss first developed in the 1980&#8217;s plus several newer initiatives, each with an array of collaborators. Beginning in the 1980&#8217;s, Dr. Stanley H. Weiss started several long-term studies of persons who inject drugs (PWID) across the United States, ultimately enrolling over 10,000 participants through the early 1990&#8217;s with an average age then in their 30&#8217;s. About a quarter were enrolled from sites in New Jersey (NJ). These studies included the first testing of PWID for the human immunodeficiency virus (HIV) and the human T-cell lymphotropic viruses (HTLV I and HTLV II). Cumulative past support (initiation thru ~ 1999) for these cohort studies included ~ $20 million from intramural resources from the National Cancer Institute (NCI) and the National Institute on Drug Abuse (NIDA), plus multiple grants and in-kind support from the New Jersey Department of Health (NJDOH) totaling ~ $1 million. The Weiss Cohort Projects include the first large AIDS-era cohorts to include women at high risk for HIV. A high percentage of subjects in these studies are black or Latino. Thus, this is an ethnically diverse US cohort, with a high proportion of women included. These subjects are at high risk of parenteral and sexual infection from both drug use and sexual practices. Samples from other studies conducted by Dr. Weiss, in which detailed interviews were conducted, are included as controls (persons documented by us not to have a history of opioid drug use). As one of our groups of subjects have many persons of Haitian ancestry, we specifically included some Haitians who had never used opioids as controls. Our documentation includes such ancestry. These cohorts demonstrated high rates of HIV and HTLV-II infection in PWIDs, including one study initiated in 1981 with confirmation in the later cohorts. In the first two decades of these studies, among numerous publications was the first study showing a very high rate of hepatitis C infection among PWIDs. An example of how the studies&#8217; long-time horizon proved essential was that it first became possible to test whether a person had ever been infected with hepatitis C virus (HCV), as well as how much HCV was in each person&#8217;s blood, many years after the specimens were collected. This allowed HCV amounts in blood to be compared for subjects who had died of liver disease early in the study versus those who survived. Then a sequence of published papers culminated in demonstrating, using a nested case-control design, that a high baseline HCV titer was predictive of early progression to death from end-stage liver failure. Outcomes related to HCV (end stage liver disease and hepatocellular carcinoma) remain under study. In the original cohort studies, the mean age at enrollment was ~ 33 years old, so that those still alive in 2022 are mainly now ~ 60 - 75 years old. Many participants have already died. The tincture of time has led to subjects reaching ages when many more are dying from a wide array of outcomes, including from many chronic diseases (including cancer) as well as from infectious agents (especially HIV, HCV) or drug overdose. Renewed collaboration with local drug treatment programs has led to new field-based studies, including examination of some currently evolving problems among drug users. Dr. Weiss joined the National Institute on Drug Abuse (NIDA) Genetics Consortium (NGC) in 2017, and through the NIDA project officer has had access to NGC contract resources (see below). NIH Certificate of Confidentiality, CC-DA-16-214 (attached) protects these studies. Past arrangements related to data on our subjects leads to restrictions on the use of data emanating from our study, such as potential commercialization and restrictions on whom may access and use these data. NIDA Genetics Consortium (NGC) resources further support these endeavors and will be used as part of the NGC analyses studying the genetics of substance use. Study participants signed informed consent for the information collected from them to be used with no time limit and for biologic specimens collected from them to be used without restriction in future research. Serum samples were collected from participants, and from many also plasma, white blood cells and/or urine samples. About 100,000 vials were stored. All specimens have been continuously preserved at sufficiently cold temperatures to prevent deterioration, and many subjects separated white blood cells were processed and frozen in such a way as to maintain viability. Detailed data from the participants has been accumulated over time, and in general, linkage has been retained in each sub-study in accordance with the consent forms and protocols. For some participants, specimens were collected at multiple times (that is, sequential specimens). Multiple specimens from a single person exist in this database, and efforts at de-duplication remain ongoing. Dr. Weiss should be contacted if an investigator requires unique individuals since: &#8226; Multiple phases of enrollment occurred, and as our prospective follow-up continues; Dr. Weiss may identify new instances of multiple enrollment. &#8226; Some persons are related to each other. &#8226; In general, in this dataset for dbGaP, only a single specimen/record form a given person is included. Advances in laboratory testing techniques now permit innovative new uses for our linked research biospecimen repository. The ongoing focus of an interdisciplinary research program based on these cohorts relates subjects&#8217; diseases, behaviors, medical history, and outcomes with biological and exposure markers. Participants&#8217; use of various substances was ascertained on study enrollments, many serially over time. Quantitative frequency of use data, also sometimes sequential over time, were ascertained. Active ascertainment of outcomes is being conducted, including matching to mortality and cancer databases. Investigators interested in collaborations on specific outcomes (which is not part of this dbGaP dataset) or in the use of our stored specimens are encouraged to contact the principal investigator, Dr. Weiss. The processing of the genomic data was done in conjunction with NIDA, and in accordance with some longstanding data cleaning steps used by NIDA in the NIDA Genetics Consortium (NGC), a group to which we shall be contributing these data for collaborative analyses. Since there is the potential for these steps to introduce certain types of potential biases, we summarize these here. Under contract from NIDA, cryopreserved sera or plasma (-80 C) or cells (in liquid nitrogen) were used, with most stored having been stored for 30 to 40 years in our biorepository. In the case of serum or plasma, in which only (largely) cell-free DNA fragments were available, DNA was extracted and restored prior to amplification. Industry standard DNA amplification techniques were done on all samples prior to genotyping in accord with established protocols of the NIDA Genetics Consortium. Our genotype data were run and processed on the Illumina Infinium OmniExpress_v_1.3 array. This array has 714,238 SNPs, and was designed many years ago. There were 628 SNPs on the array that do not correspond to any chromosome position, and these were removed. Genotype data were submitted by NIDA&#8217;s contracted genotyping laboratory in six batches over time to NIDA&#8217;s contracted dbGaP data management group, which conducted quality control (QC) analyses. QC analysis included an assessment of batch effects on for five of the six batches. (One of the batches, with only 12 samples, was too small for QC analysis of batch effects.) Standard NIDA Genetic Consortium cleaning was performed. Samples with a call rate &lt;.85 were removed. Only one sample per person was retained. When more than one specimen was genotyped from one subject, only the sample with the higher call rate was retained (provided, of course, that that call rate was &#8805; 0.85). We have retained some people we know are related, including some found to have been related through genotyping; the pedigree file describes those relationships. In summary, key cleaning steps include: 1. Using PLINK to check gender discrepancy. 2. Using PREST-PLUS and KING (Kinship-based Inference for GWAS) to check relatedness. 3. Using PEDCHECK and PLINK to check/zero-out Mendelian error. 4. Using PLINK to perform sample QC, SNP QC, along with KING to perform chromosome X and chromosome Y QC. 5. SNP-QC: Batch-effect: 5 Batches were compared (one batch, with few samples, was not). These five batches were compared to each other in all ten possible pairs, one batch vs. another batch, examining SNP allele frequency discrepancies by population (from GRAF), Fisher Exact Allelic test, with the criterion of p&lt;5e-8 for removal. 6. SNP-QC: discordant SNPs in QC duplicates. Compared 25 QC duplicated samples with call rate &gt; 0.95, removed SNPs with 3+ discordance. 7. There were 1,056 SNPs that were monomorphic; these have been retained so they can be included in analyses in which our dbGaP data are combined with those from other cohorts (in the latter of which those SNPs may not be monomorphic). The final cleaned dataset submitted has 8,898 samples and 606,793 SNPs.

  Study phs002140

• National Eye Institute Glaucoma Human Genetics Collaboration (NEIGHBOR) Consortium Glaucoma Genome-Wide Association Study: Whole Exome Resequencing in Glaucoma

  This is a study of primary open angle glaucoma (POAG) conducted through exome sequencing of cases and comparison of variant frequencies with general population frequencies available in dbGAP and controlled for sequencing platform artifact to minimize false positives. POAG is an intraocular pressure (IOP) related progressive optic neuropathy that ultimately leads to blindness. This study builds upon the efforts of an on-going collaborative consortium that studied 2,170 POAG cases and 2,347 controls with a unified definition of POAG (the NEIGHBOR consortium: NEI Glaucoma Human genetic collaBORation). The case definition for NEIGHBOR was harmonized with an additional 976 cases and 1140 controls from the NHGRI supported GENEVA (gene-environment) study of glaucoma (GLAUGEN) (NIH/NHGRI U01HG004728, Pasquale PI). In NEIGHBOR, cases and controls were recruited from ophthalmology clinics and were examined by ophthalmologists. For cases, the clinical exam included intraocular pressure measurements, optic nerve assessment and visual field evaluation. Controls had no family history of glaucoma, normal intraocular pressure and normal optic nerves. Cases and controls were also drawn from two clinical trial populations: Advanced Glaucoma Intervention Study (AGIS, NEI U10EY006827, D. Gaasterland PI) and Collaborative Initial Glaucoma Treatment Study (CIGTS, NEI U10 EY009149, P. Lichter PI). The Glaucoma Exome Sequencing study has one Principal Investigator: Theresa Gaasterland (UCSD) and two Co-Investigators: Robert Weinreb, MD, and Kang Zhang, MD, PhD, all of whom are part of the NEIGHBOR, subsequently NEIGHBORHOOD, consortium, which in turn has two Co-Principal Investigators: J. Wiggs (Harvard, MEEI), and M. Hauser (Duke). NEIGHBOR collaborators who contributed samples and/or expertise to the Glaucoma Exome Sequencing study included the following: Harvard Medical School (Massachusetts Eye and Ear Infirmary) (J. Wiggs, L. Pasquale); Duke University Medical Center (M. Hauser, E. Hauser, R. Allingham, S. Schmidt); University of Michigan (J. Richards, S. Moroi, P. Lichter); University of Miami (M. Pericak-Vance, R. Lee, D. Budenz); Vanderbilt University (J. Haines); University of California San Diego (K. Zhang, R. Weinreb; T. Gaasterland); University of Pittsburgh (J. Schuman, G. Wollenstein); University of West Virginia (A. Realini, J. Charlton, S. Zareparsi); Johns Hopkins University (D. Friedman); Stanford University (D. Vollrath, K. Singh), Eye Doctors of Washington (D. Gaasterland), Marshfield Clinic (Cathy McCarty). Hemin Chin serves as the NEI Staff Collaborator. This national collaborative study is supported by multiple NIH grants: NEI R01 EY015543 (Allingham); NEI U10 EY006827 (D. Gaasterland); NHLBI R01 HL073389 (E. Hauser); NEI R01 EY13315 (M. Hauser); NEI U10 EY009149 (Lichter); NEI R01 EY015473 (Pasquale); NEI U10 EY012118 (Pericak-Vance); NEI R03 EY015682 (Realini); NEI R01 EY011671 (Richards); NEI R01 EY09580 (Richards); NEI R01 EY013178 (Schuman); NEI R01 EY015872 (Wiggs); NEI R01 EY009847 (Wiggs); NEI R01 EY010886 (Wiggs); NEI R01 EY144428 (Zhang); NEI R01 EY144448 (Zhang); NEI R01 EY18660 (Zhang). Funding support for genotyping through exome sequencing, which was performed at the University of California, San Diego, was provided by the National Eye Institute (RC2 EY020678-01).

  Study phs000558

• Population Architecture using Genomics and Epidemiology (PAGE)

  PAGE II (2013-2017) seeks to expand understanding gained during PAGE I and similar studies of how ancestry-specific differences in allele frequencies and LD may explain differences in risks of common traits and conditions. Recent studies have identified rare genetic variants that are likely to contribute to common diseases and traits and observed that rare variants likely to be functional, such as those in coding and regulatory regions, tend to be population-specific. PAGE II has genotyped over 50,000 samples using MEGA, an Illumina high density custom exomechip array. The MEGA data is being imputed in PAGE to the 1000 Genomes panel. PAGE also sequenced 1,000 samples representative of 21 populations from the Americas. PAGE has harmonized phenotype data for ~300 trait variables. These datasets will be analyzed to continue emphasis on characterizing population-level disease risks in non-European-descent individuals. Cohorts in PAGE II are: CALiCo (Causal Variants Across the Life Course, a consortium of ARIC, CARDIA, HCHS/SOL, Strong Heart Studies), ISMMS (Mount Sinai BioMe Biobank), MEC (Multiethnic Cohort), WHI (Women&#39;s Health Initiative), and Stanford University (PAGE Global Reference Panel). Genotyping services were provided by the Center for Inherited Disease Research (CIDR) and sequence data were provided by the McDonnell Genome Institute at Washington University School of Medicine. PAGE I (2008-2013): The first phase of PAGE examined putative causal genetic variants across approximately 100,000 African Americans, Asian Americans, American Indians, European Americans, Hispanic Americans, and Native Hawaiians from four groups representing nine large U.S.-based cohorts. Two genotyping approaches were employed - targeted genotyping of selected SNPs identified in genome-wide association studies of common disease, and a large-scale effort focused on the Metabochip array, which facilitated trans-ethnic fine mapping of several diseases of public health importance. Cohorts in PAGE I were: CALiCo (Causal Variants Across the Life Course, a consortium of ARIC, CARDIA, CHS, HCHS/SOL, Strong Heart Cohort Study, Strong Heart Family Study), EAGLE (Epidemiologic Architecture for Genes Linked to Environment, based on 3 National Health and Nutrition Examination Surveys (NHANES)), MEC (Multiethnic Cohort) and WHI (Women&#39;s Health Initiative). Logistical and scientific support is provided by the PAGE Coordinating Center and the NHGRI Division of Genomic Medicine. PAGE II is funded by the NHGRI and the NIMHD. To access PAGE studies currently available in dbGaP, please click on the links below.Please note that some PAGE studies belong to larger cohorts and have been included as PAGE substudies. For those studies, there is an additional link to the parent study. phs000223 PAGE-ARIC and phs000280 ARIC Cohort phs000236 PAGE-CARDIA and phs000285 CARDIA Cohort phs000301 PAGE-CHS and phs000287 CHS Cohort phs000559 PAGE-EAGLE-BioVu phs000208 PAGE-EAGLE-NHANES phs000555 PAGE-HCHS/SOL and phs000810 HCHS/SOL Cohort phs000220 PAGE-MEC phs000580 PAGE-SHS and SHFS phs001033 PAGE Global Reference Panel phs000227 PAGE-WHI and phs000200 WHI Cohort

  Study phs000356

• Understanding the genetic risk underlying racial disparities in uterine fibroids

  Fibroids affect 77% of women by onset of menopause in the U.S. and account for $2.1 billion in healthcare costs each year. Fibroids negatively impact reproductive health causing heavy and painful menses, pelvic pain and pressure, pregnancy complications, and interventions including myomectomy and hysterectomy. Until recently, tumor tissue and cell culture studies investigating fibroid growth have been the primary sources for understanding fibroid pathophysiology. Genetic analysis can provide a powerful and cost effective tool to identify etiological and causal factors, especially since a genetic predisposition to fibroids has already been documented from twin studies. As much as 69% of risk is explained by genetic factors. Racial disparities also support a role for genetics with fibroid risk. African American women have earlier age of onset, more numerous and larger fibroids with a greater lifetime incidence compared to Caucasians. We propose to identify genetic markers for risk of fibroids through a genome-wide association study (GWAS) of African American and Caucasian participants, leveraging ancestral differences to narrow down genomic regions for targeted follow- up analyses. To accomplish this we will take advantage of a unique Vanderbilt resource, the BioVU DNA databank. BioVU currently has over 122,470 adults linked to electronic medical records. From BioVU we have already identified 2,902 African American and Caucasian subjects who meet our stringent inclusion criteria to conduct a GWAS of fibroids, including pelvic imaging. Available imaging is critical, because many women with fibroids are asymptomatic and without imaging, studies may misclassify as many as 51% of women. We have also defined definitive controls who reached menopause without fibroids. We have a strong group of nationally known fibroid researchers who will provide over 10,000 samples for replication. Our first Specific Aim is to conduct a GWAS for association between common single nucleotide polymorphisms (SNPs) and fibroid risk. Using a case-control design we will perform a GWAS in 2,902 (1,451 fibroid cases and 1,451 controls) women from BioVU stratified by African American and Caucasian race. Secondary admixture mapping (AM) analyses will also be performed to identify chromosomal regions of interest to prioritize for replication. Our second Aim is to resequence chromosome regions identified from GWAS and AM to discover rare variants. Finally, in Aim 3 we will replicate SNPs selected from Aim 1 and 2 in independent samples of at least 3,230 fibroid cases and 7,097 controls. We propose an efficient and cost-effective approach to identify genetic risk factors for fibroids, by taking advantage of imaging information and DNA available through BioVU. This study represents the largest GWAS of uterine fibroids and the first among African Americans leveraging emerging technologies and new statistical approaches to conduct this study. Our proposed study will fundamentally change knowledge about fibroids and lay the ground work for breakthroughs in understanding mechanisms of fibroid formation and in identifying novel therapeutic approaches.

  Study phs001409

• Coagulation and Fibrinolysis in a Pediatric Insulin Titration Trial

  Summary of the Design and Aims: The Coagulation and Fibrinolysis in a Pediatric Insulin Titration Trial (CAF-PINT) is an ancillary study to the HALF PINT (NCT01565941) randomized, controlled trial that was originally designed to study changes in inflammatory and thrombosis pathways in the setting of an interventional trial. The parent HALF PINT study was designed to study the impact of tight glycemic control (TGC) using an explicit insulin titration algorithm to safely achieve a normal glucose in target range of 80-110 mg/dL versus 150-180mg/dL on clinical outcomes among critically ill hyperglycemic children with Heart and Lung Failure. The CAF PINT study collected blood samples pre randomization and at 2 and 4 days after randomization. Blood samples collected in EDTA tubes were centrifuged at local sites to separate the plasma from cell pellets and frozen prior to shipment. In addition, 0.5 mL of whole blood collected in PAXgene tubes modified for use in pediatrics frozen 24 hours after collection prior to shipment.Population Information: Setting: Twenty-one academic children's hospitals (HALF-PINT) and 1 academic children's hospital (IIT-SBPP). Participants: Critically ill hyperglycemic children requiring mechanical ventilation/vasoactive support (n=293).Interventions and Exposures: Patients in HALF PINT were randomized to achieve a low target glucose (80-110 mg/dL) vs. a higher target (150-180 mg/dL). The primary trial was stopped early due to low likelihood of achieving a statistically significant difference in the primary outcomes. Molecular Technologies Employed: Plasma biomarkers were assayed on thawed plasma using a Luminex panel. RNA was extracted from PAXgene Blood RNA Kits modified for pediatric use. Extracted RNA was sequenced with the Novaseq S4 system (Illumina) to generate 2 x 150 base paired end reads to a target depth of 50 million read-pairs per sample.Principal Findings of the Study: We tested for heterogeneity of treatment effects according to baseline blood inflammatory proteins using logistic regression with individual biomarkers as interaction terms and Cox regression analysis using biomarker-derived latent classes. Children with higher inflammatory proteins including TNFR-1, IL-6, IL-8, and IL-10 had lower mortality when treated with insulin to a target glucose of 80-110 mg/dL as compared to 150-180 mg/dL (interaction p&lt;0.05). Causal forest estimates ranged from a 40% mortality reduction to a 15% mortality increase with TGC, depending on each patient&#8217;s individual biomarker profile. Latent class categorization strongly interacted with TGC with respect to mortality (Cox regression interaction p=0.005). Specifically, patients with higher inflammation benefited from TGC (6% mortality with TGC vs. 48% mortality, p=0.004) whereas hypoinflamed patients showed a trend towards harm (14% mortality with TGC vs. 7% mortality, p=0.055).Data available through dbGaP: Transcriptomic (Gene Counts) and phenotype data

  Study phs003016

• Jackson Heart Study (JHS-BioLINCC)

  Accessing Data: Please refer to &#8220;Authorized Access&#8221; below regarding accessing data through the BioData Catalyst ecosystem. The data from this accession is not available for download through dbGaP.Related Studies: Other Jackson Heart Study data available include: Imaging studies (JHS-Imaging), Genetics and genomics (The Jackson Heart Study, phs000286.v7.p2), and Collaborative Cohort of Cohorts for COVID-19 Research (C4R-JHS, phs002907.v1.p1): Jackson Heart Study (phs002907.v1.p1).Available Data: Data available for request include Jackson Heart Study visit 1-3 examination cycles, collated annual follow-up communication data through 2016, and follow-up for mortality, heart disease, and stroke events through 2014.Objectives: The objectives of the Jackson Heart Study are to: 1) investigate the associations of biological, psychosocial, and behavioral factors with the incidence atherosclerotic events and health outcomes in an African American cohort; and 2) increase access to and the participation of African American populations and scientists in biomedical research and professions.Background: It has long been recognized that African Americans share a disproportionate burden of deleterious health outcomes including diabetes, hypertension, kidney disease and early onset of cardiovascular disease. The Jackson Heart Study was initiated in 2000 to explore potential mechanisms and mediators of health outcomes in a large African American cohort. In addition, the JHS conducts a variety of community education and outreach activities to promote healthy lifestyles to reduce disease risk burden and student training programs to promote and support public health research.Participants: African American men and women, age 35-84 at entry. Of the 5306 cohort members enrolled in the study, the data repository contains data from 3,883 that provided informed consent to share their data with investigators not affiliated with the study.Design: Participants were enrolled in the study from 2000-2004 from urban and rural areas of three counties (Hinds, Madison and Rankin) in the Jackson, MS metropolitan statistical area. Participants were enrolled from each of 4 recruitment pools: a random sample component (17%), volunteer component (30%), currently enrolled in the Atherosclerosis Risk in Communities (ARIC) Study (31%), and secondary family members (22%). Recruitment was limited to non-institutionalized adult African Americans age 35-84 years, except in the family cohort where those age &#8805;21 years were eligible. The final cohort of 5,306 participants includes 6.59% of all African American residents aged 35-84 (N=76,426, US Census 2000). Data collection at the baseline exam included a medical history, physical examination, blood/urine analytes and interview questions on areas such as: physical activity; stress, coping and spirituality; racism and discrimination; socioeconomic status; and health care access.The current release of the Jackson Heart Study includes data collected at baseline, exam 2 (2005-2008), and exam 3 (2009-2013). Annual follow-up and surveillance of clinical cardiovascular events is ongoing.

  Study phs003740

• Providing access to COVID-19 data: one year later

  response efforts On 11 March 2020 the World Health Organization declared the novel coronavirus outbreak a global pandemic. Four months later, the European Genome-phenome Archive (EGA) released its first COVID-19 dataset. This dataset – single cell RNA and VDJ sequencing of B cells from 60 COVID-19 patients – showed that neutralizing antibodies could be identified by high-throughput sequencing in response to SARS-CoV-2 infection. That was one year ago. Today, the EGA provides access to fifteen COVID-19 datasets from researchers across seven countries in Asia, Europe, and North America. These studies represent almost 17,000 individuals and have resulted in at least sixteen publications and preprints. Researchers deposit controlled access COVID-19 data at EGA The global research community has come together rapidly to investigate the SARS-CoV-2 coronavirus and better understand the related disease, COVID-19. These research efforts generate valuable genetic and phenotypic data from patients and research participants that can be shared with approved researchers. The EGA enables sharing of this research data by providing a service for archiving and controlled distribution of sensitive data. Over the past year, the EGA has worked with researchers to archive and distribute COVID-19 data from high-throughput sequencing experiments, genotyping studies, and phenotypic information. These datasets investigate the immune system, blood, and cells and tissues of the lung, which are relevant for studying a contagious respiratory illness caused by a viral infection. *Study Spotlight. In January 2021, Ancestry.com demonstrated the utility of deep phenotyping based on self-reported outcomes from a large population of mild and asymptomatic COVID-19 cases. They identified genetic associations with eight COVID-19 phenotypes and showed distinct patterns of association, most notably related to the chr3/SLC6A20/LZTFL1 and chr9/ABO regions. The supporting data is available at the EGA to approved researchers and includes both genotype and phenotype data for 15,000 individuals. EGA collaborates with global COVID-19 community Since the coronavirus outbreak, the EGA has collaborated with other life science resources to support discovery and access to COVID-19 datasets. COVID-19 Host Genetics Initiative. With the NHGRI’s Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL) platform, the EGA enables sharing of individual-level genetic and phenotypic data from the COVID-19 Host Genetics Initiative (HGI). This initiative aims to generate, share, and analyze data from COVID-19 host genetics research projects to better understand the genetic determinants of COVID-19 susceptibility, severity, and outcomes. In response to COVID-19, the EGA actively supports COVID-19 data submissions and integration of data access and flow into the COVID-19-HGI analysis platform. *Study Spotlight. The COVID-19 HGI has combined individual-level data for 13,868 COVID-19 positive patients (N=7,167 hospitalized) from 17 cohorts in nine countries. The data were used to assess the association of the major common COVID-19 genetic risk factor (chromosome 3 locus tagged by rs10490770) with mortality, COVID-19-related complications, and laboratory values. The genotype and phenotype data for 10 of these cohorts is available at the EGA to approved researchers under accession EGAS00001005304. Fig 1: EGA COVID-19 studies are searchable in the European COVID-19 Data Portal alongside other COVID-19 and SARS-CoV-2 public datasets. European COVID-19 Data Portal. EGA-archived COVID-19 data are discoverable via the European COVID-19 Data Portal (Fig. 1), which brings together public and controlled access data to accelerate coronavirus research for the international community. By indexing all COVID-19-related data in one place, researchers can more easily discover relevant datasets of interest, thus increasing the “FAIRness” (Findability, Accessibility, Interoperability, Reusability) of this valuable data. Fig 2: SARS-CoV-2 viral sequences are imported from ENA and analysed in Galaxy to detect variants. Results are accessible to researchers through the COVID-19 Viral Beacon. COVID-19 Viral Beacon. The COVID-19 Viral Beacon tool was developed in collaboration with the European Nucleotide Archive and Galaxy to enable near real-time browsing of SARS-CoV-2 variability at genomic, amino acid, and motif levels (Fig. 2). The COVID-19 Viral Beacon allows researchers to (i) perform detailed searches about genomic variants, (ii) filter queries and find unique cases, (iii) filter data based on strain-specific variants, and (iv) explore associated metadata. It uses the Global Alliance for Genomics and Health (GA4GH) Beacon standard including new Beacon v2 features. With this tool, researchers can study intra-host mutations on genomic regions of interest, or trace any variant frequency over time using raw read data. More than 200,000 SARS-CoV-2 analysed genomic data files are now available to researchers for further exploration. Ongoing COVID-19 efforts at EGA Addressing the COVID-19 pandemic is a global effort. Federated resources are necessary to support transnational deposition, access, and analysis of sensitive COVID-19 host genetics and other related data. At the same time, many countries now have emerging personalized medicine programmes which are generating data from national or regional healthcare initiatives. These data are subject to more stringent information governance than research data and often must comply with national data protection legislation. To address this need, the Federated EGA was established to serve as the primary global resource for discovery and access of sensitive human omics and associated data consented for secondary use. The Federated EGA will comprise a network of national human data repositories and will implement community standards and common interfaces. Launching Federated EGA promises to accelerate not only global research efforts to understand, diagnose, and treat COVID-19, but also to foster data reuse, enable reproducibility, and accelerate biomedical and disease research to ultimately improve human health.

  Blog providing-access-to-covid-19

• The BC Cancer Agency's Personalized Onco-Genomics Project

  The BC Cancer Agency's Personalized Onco-Genomics (POG) Project involves molecular and clinical characterization of individual cancer patients to guide their treatment. The project aims to use whole genome and transcriptome data together with patient information to match treatments to cancer driver alterations and support clinical decision-making. Incorporating genomic data into decision-making should enable more rational development of treatment plans, facilitate enrollment into appropriate clinical trials and potentially identify less toxic and more effective therapeutic options.

  Study EGAS00001001159

• Resource for Genetic Epidemiology Research on Adult Health and Aging (GERA)

  The Resource for Genetic Epidemiology Research on Aging (GERA) Cohort was created by a RC2 "Grand Opportunity" grant that was awarded to the Kaiser Permanente Research Program on Genes, Environment, and Health (RPGEH) and the UCSF Institute for Human Genetics (AG036607; Schaefer/Risch, PIs). The RC2 project enabled genome-wide SNP genotyping (GWAS) to be conducted on a cohort of over 100,000 adults who are members of the Kaiser Permanente Medical Care Plan, Northern California Region (KPNC), and participating in its RPGEH. The purpose of the RPGEH is to facilitate research on the genetic and environmental factors that affect health and disease by linking together clinical data from electronic health records, survey data on demographic and behavioral factors, and environmental data from various sources, with genetic data derived from biospecimens collected from participants. At the time of the award of the RC2 project in late 2009, the RPGEH had established a cohort of about 140,000 individuals who had answered a detailed survey, provided saliva samples for extraction of DNA, and given broad consent for the use of their data in studies of health and disease. To maximize the diversity of the resulting sample, the GERA cohort was formed by including all racial and ethnic minority participants with saliva samples (N = 20,925; 19%); the remaining participants were drawn sequentially and randomly from white non-Hispanic participants (89,341; 81%). A total of 110,266 participant samples were included to ensure that at least 100,000 were successfully assayed. The resulting GERA cohort is 42% male, 58% female, and ranges in age from 18 to over 100 years old with an average age of 63 years at the time of the RPGEH survey (2007). The sample is ethnically diverse, generally well-educated with above average income. Approximately 69% of the participants are married or living with a partner. Length of membership in KPNC averages 23.5 years. UCSF and RPGEH investigators worked with the genomics company Affymetrix to design four custom microarrays for genotyping each of the four major race-ethnicity groups included in the GERA Cohort, described in detail in Hoffmann et al., 2011a and 2011b. Following genotyping and quality control procedures, and after removal of invalid, discordant, or withdrawn samples, about 103,000 participants were successfully genotyped. The resulting genotypic data were linked to survey data and data abstracted from the electronic medical records. As described below, all RPGEH participants were mailed new consent forms with explicit discussion of the placement of data in the NIH-maintained dbGaP. About 77% of participants returned completed consent forms, resulting in a final sample size of 78,486 participants in the GERA Cohort with data for deposit into dbGaP. Origins of the RPGEH GERA Cohort The goal in creating the RPGEH GERA cohort was to create a large, multiethnic, and comprehensive population-based resource for research into the genetic and environmental basis of common age-related diseases and their treatment, and factors influencing healthy aging and longevity. The GERA Cohort consists of a diverse cohort of more than 100,000 adults who are members of the Kaiser Permanente Medical Care Plan, Northern California Region (KPNC), and participating in its Research Program on Genes, Environment and Health (RPGEH). KPNC is an integrated health care delivery system with a population of about 3.3 million people in northern California. The membership of KPNC is representative of the general population in the 14 county area in which facilities are located, although the membership is underrepresented for the extremes of income at both ends of the spectrum. The RPGEH utilizes the longitudinal electronic health records (EHR) of KPNC to obtain clinical, laboratory, imaging and pharmacy information on all cohort members, to which personal demographic, behavioral and health characteristics have been added through member surveys. The GERA Cohort comprises a subsample of the RPGEH participant cohort, and was created through the RC2 award from the NIA, NIMH, and NIH Common Fund as described above. GERA Study Design The GERA Cohort is a subsample, as described above, of the longitudinal cohort enrolled in the Kaiser Permanente RPGEH. The RPGEH cohort includes about 400,000 survey participants of whom about 200,000 have provided broad consent and a sample of saliva or blood for use in studies of genetic and environmental factors in health and disease. The GERA Cohort was developed from a mailed survey sent to all adult members of KPNC who had been members for two years or more in 2007. All survey respondents were contacted and asked to complete a consent form; those who completed consent forms were asked to provide a saliva sample. Additional male participants were added to the RPGEH through inclusion of the Northern California sample of the California Men&#39;s Health Study (CMHS) cohort of about 40,000 men from KPNC, ages 45-69 years old at the time of the CMHS survey in 2002-2003. The CMHS participants contributed about 15,400 saliva samples to the RPGEH and were eligible for inclusion in the GERA Cohort. CMHS participants were included according to the same sampling design as for the RPGEH cohort as a whole. Specifically, all minority participants were selected for inclusion in order to maximize representation of minorities in the GERA Cohort, and Non-Hispanic White participants were selected at random to complete the sample of 110,266 GERA Cohort participants. GERA Genotypic Data High-density genotyping was conducted at UCSF using custom designed Affymetrix Axiom arrays, as described in Hoffmann et al. (2011a; 2011b). To maximize genome-wide coverage of common and less common variants, four specific arrays were designed for individuals of Non-Hispanic White (EUR), East Asian (EAS), African-American (AFR), and Latino (LAT) race/ethnicity. There was broad overlap among the SNPs on the arrays, which were designed using a hybrid greedy imputation algorithm (Hoffmann et al., 2011b) applied to genotype information validated by Affymetrix from the 1000 Genomes Project. However, in order to capture low frequency variants specific to particular race-ethnicity groups, SNP content varies between arrays. A more detailed description of the process of genotyping and results is included in Genotyping of DNA Samples. Description of the analyses of population structure and development of principal components for adjustment of population structure is included in Population Structure Analysis. GERA Phenotypic Data RPGEH and CMHS Survey Data. The sources of data on demographic and behavioral factors deposited in dbGaP for the GERA Cohort are the RPGEH and CMHS surveys. Data on common demographic factors such as gender, race/ethnicity, marital status, and education and on behavioral factors such as smoking, alcohol consumption, and body mass index, have been cleaned, edited, reconciled between the two surveys, and compiled into summary indices, where appropriate, for deposition into dbGaP. A more complete description of the survey variables is included in Survey Variables Documentation. Please note that the terms of use of the GERA Cohort Data, as specified in the Data Use Certification (DUC), prohibit the use of survey variables as outcomes in analyses. For example, a genome-wide association study (GWAS) of education or smoking is not permitted as specified by the DUC. Only health conditions can be used as outcome variables in analyses. Health Conditions derived from Kaiser Permanente Electronic Medical Records. Data on the occurrence of health conditions in participants in the GERA Cohort have been derived from summarizing ICD-9 coded diagnoses in Kaiser Permanente&#39;s electronic medical records. An algorithm that aggregates specific ICD-9 codes into appropriate diagnostic groups for selected conditions is applied to outpatient and inpatient databases; see Disease and Conditions Definitions Documentation for details. The criterion for including a condition as "present" for a participant is the occurrence of two or more diagnoses within a diagnostic category occurring on separate days. Two or more is used as the criterion in order to reduce false positives due to mistakes or rule-out diagnoses. When compared with validated disease registries, the criterion of 2+ diagnoses yields high specificity and good sensitivity. ICD-9 codes in the electronic records are specified in several ways. For outpatient visits occurring during the period 1995 to 2006, diagnoses were assigned by the treating physician who endorsed specific diagnoses on an optically scanned list that varied by specialty. Beginning in 2006 with the advent of an integrated, fully electronic medical record, outpatient diagnoses are made by physicians/ providers using a pull down menu. Discharge diagnoses from inpatient stays are specified by physicians and coded by specially trained coders. Databases of ICD-9 codes for diagnoses assigned at outpatient visits, or as one of the discharge diagnoses following inpatient stays, are complete and available for all KPNC members dating back to 1995. Although the average length of KPNC membership among GERA cohort members is 23.5 years in 2007, not all have been members since 1995, so the history for some conditions, such as those that are not chronic or recurrent, may not be complete for all cohort members. The year of first membership in KPNC is included as a variable in the list of survey variables, enabling investigators to estimate the number of years of observation of each Cohort member. RPGEH Access and Collaborations Website and Procedures The RPGEH maintains a web portal for inquiries and applications for collaboration and access to data. The url is: https://rpgehportal.kaiser.org/. RPGEH has an application process and an Access Review Committee that reviews applications for collaboration and use. For more details, please contact RPGEH through the website.

  Study phs000674

• Genome-wide analysis of genetic risk factors for rheumatic heart disease in Aboriginal Australians provides support for pathogenic molecular mimicry

  Background. Rheumatic heart disease (RHD) following Group A Streptococcus (GAS) infections is heritable and prevalent in Indigenous populations. Molecular mimicry between human and GAS proteins triggers pro-inflammatory cardiac valve-reactive T-cells. Methods. Genome-wide genetic analysis was undertaken in 1263 Aboriginal Australians (398 RHD cases; 865 controls). Single nucleotide polymorphisms (SNPs) were genotyped using Illumina HumanCoreExome BeadChips. Direct typing and imputation was used to fine-map the human leukocyte antigen (HLA) region. Epitope binding affinities were mapped for human cross-reactive GAS proteins, including M5 and M6. Results. The strongest genetic association was intronic to HLA-DQA1 (rs9272622; P=1.86x10-7). Conditional analyses showed rs9272622 and/or DQA1*AA16 account for the HLA signal. HLA-DQA1*0101_DQB1*0503 (OR 1.44, 95%CI 1.09-1.90, P=9.56x10-3) and HLA-DQA1*0103_DQB1*0601 (OR 1.27, 95%CI 1.07-1.52, P=7.15x10-3) were risk haplotypes; HLA_DQA1*0301-DQB1*0402 (OR 0.30, 95%CI 0.14-0.65, P=2.36x10-3) was protective. Human myosin cross-reactive N-terminal and B repeat epitopes of GAS M5/M6 bind with higher affinity to DQA1/DQB1 alpha/beta dimers for the two risk haplotypes than the protective haplotype. Conclusions. Variation at HLA_DQA1-DQB1 is the major genetic risk factor for RHD in Aboriginal Australians studied here. Cross-reactive epitopes bind with higher affinity to alpha/beta dimers formed by risk haplotypes, supporting molecular mimicry as the key mechanism of RHD pathogenesis.

  Study EGAS00001002678

• First datasets available in the Federated EGA Network

  In February 2024, a great milestone was reached for the human omics data community: the first datasets are now available in the Federated European Genome-phenome Archive (FEGA). These datasets - hosted by national nodes in Poland, Norway, and Sweden - are discoverable in the EGA portal and accessible according to national laws. These datasets include: From FEGA Poland - The Genomic Map Of Poland From FEGA Norway - CRCbiome: Gut metagenome of Norwegian screening participants using FIT sampling Also from FEGA Norway - Single cell transcriptomics in expanded Tregs of APS-1 patients From FEGA Sweden - A Combined Omics and Tissue Biobank for Paediatric Cancers The establishment of these datasets represents a significant step towards achieving the broader objectives of the FEGA; to facilitate the sharing of high-quality human genomic and phenotypic data across borders. “The value for users is twofold: it becomes easier to make data available securely compared to storing data locally, and data becomes easier to find for other researchers. The possibility of reuse improves the chances of both verifying scientific discoveries and reaching groundbreaking conclusions, of benefit to the research community and later also patients,” said Anna Hagwall, project manager and head of human data at FEGA Sweden, NBIS. About Federated EGA FEGA was launched in 2022 as a network to store and lawfully share sensitive human omics data safely. It relies on the technology originally developed by the EGA and support from ongoing collaborations with ELIXIR - a European life sciences infrastructure. FEGA has contributed to and benefitted from the implementation of community standards for sensitive data management including those developed by the Global Alliance for Genomics and Health (GA4GH). “The FEGA concept and the development of the Nordic FEGA nodes have been made possible thanks to several projects coordinated by NeIC,” said Kjell Petersen, FEGA Norway technical lead. Managing human omics data is challenging due to its sheer size and privacy concerns, often resulting in restrictions on how and where sensitive data can be shared. The FEGA network follows a federated data access model whereby sensitive data is stored securely within a local or national jurisdiction, while discovery across the network for data of interest is enabled via a central portal. As of February 2024, the FEGA network comprises seven European national nodes with tens of additional national partners working towards establishing a FEGA node. As the FEGA network continues to onboard nodes from around the world, populated with more and more data, we move closer to a vision of a truly global resource for discovery of and access to sensitive human omics data to accelerate disease research and improve human health. "The Federated EGA network is entering a key phase where the first research datasets are now available across the network. In coming years, we look forward to expanding these datasets to cover key areas such as cancer and rare diseases for the benefit of patients" said Thomas Keane, Group Leader at EMBL-EBI.

  Blog first-datasets-available-in-Federated-EGA

• Women's Health Initiative Clinical Trial and Observational Study

  The Women&#39;s Health Initiative (WHI) is a long-term national health study that has focused on strategies for preventing heart disease, breast and colorectal cancer, and osteoporotic fractures in postmenopausal women. The original WHI study included 161,808 postmenopausal women enrolled between 1993 and 1998. The Fred Hutchinson Cancer Research Center in Seattle, WA serves as the WHI Clinical Coordinating Center for data collection, management, and analysis of the WHI. The WHI has two major parts: a partial factorial randomized Clinical Trial (CT) and an Observational Study (OS); both were conducted at 40 Clinical Centers nationwide. The CT enrolled 68,132 postmenopausal women between the ages of 50-79 into trials testing three prevention strategies. If eligible, women could choose to enroll in one, two, or all three of the trial components. The components are: Hormone Therapy Trials (HT): This double-blind component examined the effects of combined hormones or estrogen alone on the prevention of coronary heart disease and osteoporotic fractures, and associated risk for breast cancer. Women participating in this component with an intact uterus were randomized to estrogen plus progestin (conjugated equine estrogens [CEE], 0.625 mg/d plus medroxyprogesterone acetate [MPA] 2.5 mg/d] or a matching placebo. Women with prior hysterectomy were randomized to CEE or placebo. Both trials were stopped early, in July 2002 and March 2004, respectively, based on adverse effects. All HT participants continued to be followed without intervention until close-out. Dietary Modification Trial (DM): The Dietary Modification component evaluated the effect of a low-fat and high fruit, vegetable and grain diet on the prevention of breast and colorectal cancers and coronary heart disease. Study participants were randomized to either their usual eating pattern or a low-fat dietary pattern. Calcium/Vitamin D Trial (CaD): This double-blind component began 1 to 2 years after a woman joined one or both of the other clinical trial components. It evaluated the effect of calcium and vitamin D supplementation on the prevention of osteoporotic fractures and colorectal cancer. Women in this component were randomized to calcium (1000 mg/d) and vitamin D (400 IU/d) supplements or a matching placebo. The Observational Study (OS) examines the relationship between lifestyle, environmental, medical and molecular risk factors and specific measures of health or disease outcomes. This component involves tracking the medical history and health habits of 93,676 women not participating in the CT. Recruitment for the observational study was completed in 1998 and participants were followed annually for 8 to 12 years. Extension Studies: The original protocol allowed for follow-up until March 2005, after which participants were invited to enroll in the first WHI Extension Study for follow-up through 2010. Participants were invited again to participate in the second WHI Extension Study with continued follow up from 2010 to at least 2015. As of March 31, 2011 there were 93,122 women enrolled in the second extension. In Extension Study 2, the overall WHI study population was divided into two new subsamples, the Medical Records Cohort (MRC) and the Self-Report Cohort (SRC). The MRC consists of all former hormone trial participants and all African American and Hispanic participants from all study components. The SRC consists of the remaining participants. The extent of outcome information collected differs between the two cohorts, with more extensive outcomes information collection on the MRC. As part of Extension Study 2, selected older WHI participants were invited to participate in an In Person Visit (a.k.a., Long Life Study) at their homes during which additional blood samples were collected and various measurements were taken (such as blood pressure, height, weight, waist circumference, grip strength, etc.). In October 2015, Extension Study 2 was renewed with continued follow-up planned through October 2020, pending annual contract review and renewal. Additional Information: The WHI website, https://www.whi.org/about/SitePages/About%20WHI.aspx has much more information about the study. For WHI data collection forms used over the years, please see https://www.whi.org/researchers/studydoc/SitePages/Forms.aspx. For additional dataset documentation, see https://www.whi.org/researchers/data/Pages/Available%20Data.aspx. For data preparation and use, please refer to &#39;WHI dbGaP Cohort Data Release Data Preparation Guide May 2018&#39; for additional details about the WHI data. The WHI Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the "Substudies" box located on the right hand side of this top-level study page phs000200 WHI Cohort. phs000386 WHI SHARe phs000281 GO-ESP WHISP phs000315 WHI GARNET phs000503 WHISE phs000227 PAGE WHI phs000675 WHIMS+ phs000746 WHI Harmonized and Imputed GWAS phs001334 WHI Metabolomics of CHD phs001335 WHI BA23 phs001614 WHI LLS Phase III GWAS

  Study phs000200

• Health and Retirement Study (HRS)

  Introduction to V2: This data release comprises data from the V1 release combined with approximately 3,000 additional samples, collected during the HRS 2010 field period. The 2010 data include samples from a random half of the new cohort enrolled in 2010 along with a significant expansion of the minority sample. Description: The University of Michigan Health and Retirement Study (HRS) is a longitudinal panel study that surveys a representative sample of approximately 20,000 people in America over the age of 50 every two years. Supported by the National Institute on Aging (NIA U01AG009740) and the Social Security Administration, the HRS explores the changes in labor force participation and the health transitions that individuals undergo toward the end of their work lives and in the years that follow. The study collects information about income, work, assets, pension plans, health insurance, disability, physical health and functioning, cognitive functioning, and health care expenditures. Through its unique and in-depth interviews, the HRS provides an invaluable and growing body of multidisciplinary data that researchers can use to address important questions about the challenges and opportunities of aging. Because of its innovation and importance, the HRS has become the model and hub for a growing network of harmonized longitudinal aging studies around the world. Origins of the HRS. As the population ages it is increasingly important to obtain reliable data about aging and topics that are relevant to a range of policy issues in aging. To address this need, the National Institutes on Aging (NIA) established a cooperative agreement with the University of Michigan Institute for Social Research to collect such data. The HRS launched data collection in 1992 and has re-interviewed the original sample of respondents every two years since then. By adding new cohorts and refreshing the sample, the HRS has grown to become the largest, most representative longitudinal panel study of Americans 50 years and older. HRS Study Design. The target population for the original HRS cohort includes all adults in the contiguous United States born during the years 1931-1941 who reside in households, with a 2:1 oversample of African-American and Hispanic populations. The original sample is refreshed with new birth cohorts (51-56 years of age) every six years. The sample has been expanded over the years to include a broader range of birth cohorts as well. The target population for the AHEAD survey consists of United States household residents who were born in 1923 or earlier. Children of the Depression (CODA) recruits households born 1924-1930, War Babies 1942-47, Early Boomers 1948-53, and Mid-Boomers 1954-59. Data collection includes a mixed mode design combining in-person, telephone, mail, and Internet. For consenting respondents, HRS data are linked at the individual level to administrative records from Social Security and Medicare claims. Genetic Research in the HRS. The HRS has genotyped 2.5 million single nucleotide polymorphisms (SNPs) on respondents using Illumina&#39;s Human Omni2.5-Quad (Omni2.5) BeadChip. The genotyping was performed by the NIH Center for Inherited Disease Research (CIDR). Saliva was collected on half of the HRS sample each wave starting in 2006. In 2006, saliva was collected using a mouthwash collection method. From 2008 onward, the data collection method switched to the Oragene kit. Saliva completion rates were 83% in 2006, 84% in 2008, and 80% in 2010 among new cohort enrollees. HRS Phenotypic data. Phenotypic data are available on a variety of dimensions. Health measures include physical/psychological self-report, various health conditions, disabilities, cognitive performance, health behaviors (smoking, drinking, exercise), physical performance and anthropomorphic measures, and biomarkers (HbA1c, Total Cholesterol, HDL, CRP, Cystatin-C). Data are also available on health services including utilization, insurance and out-of-pocket spending with linkage to Medicare records. Economic measures include employment status/history, earnings, disability, retirement, type of work, income by source, wealth by asset type, capital gains/debt, consumption, linkage to pensions, Social Security earnings/benefit histories. There is also extensive information on family structure, proximity, transfers to/from of money, time, social and psychological characteristics, as well as a wide range of demographics. Performance on a cognitive test combining immediate and delayed word recall was selected as an example trait for the dbGaP data release. In the immediate word recall task the interviewer reads a list of 10 nouns to the respondent and asks the respondent to recall as many words as possible from the list in any order. After approximately five minutes of asking other survey questions, the respondent is asked to recall the nouns previously presented as part of the immediate recall task. The total recall score is the sum of the correct answers to these two tasks, with a range of 0 to 20. Researchers who wish to link to other HRS measures not in dbGaP will be able to apply for access from HRS. A separate Data Use Agreement (DUA) will be required for linkage to the HRS data. See the HRS website (http://hrsonline.isr.umich.edu/gwas) for details.

  Study phs000428

• A Genomic Approach to Warfarin Dose Prescription in Admixed Caribbean Hispanics

  Warfarin is an oral anticoagulant and one of the most used drugs in the world accounting for up to 1.5% of prescriptions globally. Warfarin inhibits vitamin K epoxide reductase complex 1 (VKORC1), an enzyme responsible for the vitamin K recycling that is required for the activation of clotting factors. Warfarin is prescribed at an average dose of 5 mg/day for most of the indications but significant inter-patient variability has been observed. Single nucleotide variations at the VKORC1 (GeneID: 79001) and CYP2C9 (GeneID: 1559) genes alone explain from 28 to 35% of variability in warfarin dose requirements and up to 56% when clinical factors (age, gender, body surface area, diabetes and heart valve) are incorporated into regression analysis. However, genetic-guided dosing algorithms are mostly derived from studies in Europeans. The objective of the present study was to identify genetic polymorphisms that can explain variability in warfarin dose requirements among Caribbean Hispanics of Puerto Rico. VKORC1 (GeneID: 79001) and CYP2C9 (GeneID: 1559), the most important genetic predictors of warfarin response, were sequenced using Next Generation sequencing. Other candidate genes in DMET Plus Assay were assessed to identify genetic variants with relevance in warfarin dose requirements among Puerto Ricans. Our study used the Extreme Discordant Phenotype approach to perform a case-control association analysis that were confirmed with univariate and conditioned regressions. Accordingly, patients were stratified based on stable warfarin doses as sensitive (&#60;4 mg/day), control (4-6 mg/day) and resistant (&#62;6 mg/day). Genetic variants associated with warfarin response among the study cohort were used to perform a multivariate regression analyses to develop a genetic-guided dosing algorithm tailored for Puerto Ricans. The CYP2C9rs2860905 SNP was found to be strongly associated with warfarin dose requirements in Puerto Ricans. The CYP2C9 rs2860905 SNP tags four haplotypes that represent the trihybrid admixture of Puerto Ricans. Therefore, haplotypes harboring the rs2860905 variant are more informative in predicting warfarin dose among Puerto Ricans than the common single segregating SNPs (i.e., CYP2C9*2 and CYP2C9*3) relevant to Europeans. DMET Plus array confirmed the strong association of VKORC1 (GeneID: 79001) and CYP2C9 (GeneID: 1559) with warfarin dose requirements, but also identified other polymorphisms in CES2 (GeneID: 8824) and ABCB1 (GeneID: 5243) associated with warfarin resistance (&#62;6 mg/day). Ancestry analysis showed that Puerto Ricans from Veteran Affairs Caribbean Healthcare System (VACHS) using warfarin had higher Native American proportions than Puerto Ricans from the 1000 Genomes project; however, this difference was not significant. Incorporation of rs2860905 in a regression model (R2=0.60 MSE=0.38) that also included additional genetic predictors (i.e., VKORC1-1639G&#62;A; CYP2C9 rs1856908; ABCB1 rs10276036; CES2 rs4783745) and non-genetic factors (i.e., hypertension, diabetes and age) showed better prediction of warfarin dose requirements than CYP2C9*2 and CYP2C9*3 combined (partial R2=0.132 versus 0.023 and 0.007, respectively, p&#60;0.001). Interestingly, deep vein thrombosis and diabetes were found associated with high warfarin dose requirements among Puerto Ricans. Our results support the use of CYP2C9 rs2860905 along with other genetic markers [e.g., VKORC1(GeneID: 79001 )] and clinical covariates to predict warfarin dose in Puerto Ricans. Although our findings need further replication, this study contributes to the field of Pharmacogenetics and to improve anticoagulation therapy among Puerto Ricans.

  Study phs001496

• Adipose Tissue Omics In Obesity

  This project used a multi-omics approach to study the adipose tissue transcriptome in humans with and without obesity. Our human cohort included males and females between the ages of 18-80 who underwent elective abdominal surgery at the University of Michigan and the Ann Arbor Veterans Affairs Healthcare System.Patients with advanced cancer or immuncompromised status were excluded. Visceral adipose tissue (VAT/omental) and subcutaneous adipose tissue (SAT/abdominal wall) were collected from subjects with obesity (BMI>=35) at the beginning of elective surgical procedures, placed on ice, and transported back to the laboratory for immediate processing. For adipose tissue stromal cells (ASC) isolation, adipose tissue was digested with Type II collagenase (2 mg/mL in PBS/2% BSA) at 37oC, 60min, centrifuged at 250 rcf, and the stromal-vascular cell pellet was retrieved, plated overnight, and the adherent cells passaged three times to enrich for ASC, which were then frozen in DMEM/F12, 15% fetal calf serum, and 10% DMSO in liquid nitrogen until use. Single nuclear sequencing was performed on preparations from intact adipose tissue. Bulk RNA sequencing and single cell sequencing were performed on ASC isolated from intact adipose tissue and cultured in 2D and 3D culture systems. We currently apply bulk, single cell, and single nuclear sequencing analyses to these tissues. One component of this project studies single nuclear sequencing in nuclei isolated from intact adipose tissues from human subjects with obesity, focusing on depot comparisons (VAT vs. SAT). This cohort also permits comparisons of adipose tissue transcriptomes between male and female subjects, controlling for age and BMI. Primary findings to date include identification of multiple ASC, adipocyte, and endothelial cell (EC) subpopulations, T-cell, and macrophage (MAC) populations that are in concordance with and expand upon other published datasets. Of two dominant ASC subpopulations, one (inflammatory-mesothelial, IM- ASC) is present in VAT, but absent in SAT, while the other (fibroadipogenic, FA-ASC) is present in both VAT and SAT. We identified multiple EC subtypes with features of lymphatic, venous, and arterial EC, and a PRDM16 expressing population with features of an EC progenitor. Immune cell populations match recent experimental validation of lipid-activated macrophage (LAM) phenotypes, TIM4 macrophages, and a prominent population of MRC1/CD206+ resident AT macrophages with expression signatures related to glucocorticoid activation. These data support depot-specific differences in ASC subpopulations and previously unrecognized EC heterogeneity within human AT, with the potential to shed light on functional differences in AT depot and disease state. Planned future studies include ATAC-Seq and other omics analyses. Another component of this project studies transcriptional responses of ASC in vitro to various stimuli, including different matrix environments. Current data includes bulk RNA Sequencing of human ASC from VAT and SAT differentiated into mature adipocytes in hydrogels of differing stiffness (3%, 5%, 10%) to define transcriptional responses to matrix environments of different stiffness. Primary findings to date include enrichment of adipogenesis and lipid and oxidative metabolic gene pathways in adipocytes in 5% relative to 3% hydrogels, while fibrotic gene pathways have been enriched in 3% hydrogels. These data demonstrate that intermediate density matrix promotes a more adipogenic, less fibrotic adipocyte phenotype geared towards increased lipid and aerobic metabolism. Planned future studies include expansion of intact tissues from our cohort studied with single nuclear sequencing, as well as further study of ASC responses in vitro to different biologic stimuli, including different matrix environments.

  Study phs003390

• Acute Respiratory Distress Network (ARDSNet) Studies 01 and 03 Lower Versus Higher Tidal Volume, Ketoconazole Treatment and Lisofylline Treatment (ARMA/KARMA/LARMA) (ARDSNet-ARMA/KARMA/LARMA-BioLINCC)

  Data Access NOTE: Please refer to the &#8220;Authorized Access&#8221; section below for information about how access to the data from this accession differs from many other dbGaP accessions. Biospecimens Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from ARDSNet-ARMA/KARMA/LARMA include plasma, serum and urine. Please note that use of biospecimens in genetic research is subject to a tiered consent. Objectives The ARDS Network is a consortium of clinical centers and a coordinating center to design and test novel therapies for the treatment of Acute Lung Injury (ALI) and Acute Respiratory Distress Syndrome (ARDS). The primary objective of the KARMA trial was to investigate the efficacy and safety of Ketoconazole and Respiratory Management in the treatment of ALI and ARDS. The Ketoconazole arm of the study was later stopped due to an inability to show efficacy. Participants continued to be randomized to the respiratory management arms of the study (ARMA), which compared two ventilator strategies: a tidal volume of 6 mL/kg versus 12 mL/kg. The LARMA phase of the study investigated the efficacy of Lisofylline and Respiratory Management. Background Participants suffering from ARDS are extremely ill, require mechanical ventilation and, despite improvements in medical care and technology, had a mortality rate as high as 50 percent. An excessive inflammatory response is characteristic of ALI of which ARDS represents the most severe end of the pathophysiologic spectrum. The inflammatory response includes increased numbers of neutrophils activated to produce cytokines, proteases, and reactive oxygen intermediates. Pulmonary injury may also be enhanced by alveolar and tissue macrophages as a producer of vasoactive substances, neutrophil chemoattractants, and procoagulant substances. Ketoconazole, a synthetic antifungal imidazole, also has anti-inflammatory activities and may inhibit neutrophil recruitment via several different pathways known to be involved in the development of ALI and ARDS. Lisofylline causes a marked decrease in the circulating levels of the major oxidizable species of free fatty acids and also inhibits proinflammatory intracellular signaling. Mechanical ventilation in participants with ALI and ARDS have traditionally used tidal volumes of 10 to 15 ml per kilogram of body weight. These large tidal volumes are often necessary to achieve normal partial pressure of arterial carbon dioxide and pH, but may induce inflammatory responses through disruption of pulmonary epithelium and endothelium. Mechanical ventilation at lower tidal volumes may reduce injurious lung stretch and decrease the inflammatory response. Participants The Ketoconazole and Lisofylline trials were designed as 2 x 2 factorials and included 220 participants in each trial. A total of 860 participants were randomized into the ventilator management trial. Participants enrolled in the Lisofylline or Ketoconozole studies had to be concurrently enrolled in the ventilator management study and were first randomized into a ventilator strategy and then to drug or placebo. Conclusions Ketoconazole was found to be safe but did not reduce mortality, duration of mechanical ventilation, or improve lung function. Lisofylline was also found to be safe and to have no beneficial effect for participants with ALI or ARDS. Ventilation at lower tidal volumes resulted in reduced mortality and an increase in the number of days without ventilator support. (PMIDs: 10789668, 11902249, 10793162).

  Study phs003734

• Targeted_sequencing_of_genes_recurrently_mutated_in_AML

  Background Massively parallel sequencing technology has transformed cancer genomics. It is now feasible, in a clinically relevant time-frame, for a clinically manageable cost, to screen DNA from patient tumours for mutations essentially genome-wide. The challenge for personalised medicine will be to increase the sample size to thousands or tens of thousands of well-characterised cases in order to attain sufficient statistical power to stratify patients accurately across the complexity and genomic heterogeneity expected for most of the common tumour types. Currently, whole genome sequencing on this scale is not feasible, and targeted sequencing of relevant portions of the genome will be required. Pilot data We have developed protocols for large-scale, multiplexed sequencing of 100-200 genes in thousands of samples. Essentially, using robotic technology, genomic DNA from the cancer specimen is processed into sequencing libraries with unique DNA barcodes, thereby allowing sequencing reads to be attributed to the sample they derive from. Currently, these sequencing libraries can be generated in a 96-well format using fully automated protocols, and we are exploring methods to expand this to a 384-well format. The sequencing libraries are pooled and hybridized to custom sets of RNA baits representing the genomic regions of interest. Sequencing of the pulled-down libraries is done in pools of 48-96 samples per lane of an Illumina Hi-Seq. This protocol is already implemented at the Sanger Institute. We have published proof that somatic mutations in novel cancer genes can be identified from exome-wide sequencing. In unpublished pilot data, we have established the feasibility of robotic library production, custom pull-down, and multiplexed sequencing of barcoded libraries for 100 known myeloid cancer genes across 760 myelodysplasia samples. Highlights of the data thus far analysed reveal that the coverage is remarkably even between samples; when 96 samples are run, average coverage per lane of sequencing is ~250, with 90-95% of targeted exons covered by &gt;25 reads; known mutations can be discovered in the data set; and the protocol is amenable to whole genome amplified DNA. The bioinformatic algorithms for identification of substitutions and indels in pull-down data are well-established; we have pilot data proving that copy number changes, LOH and genomic rearrangements in specific regions of interest can also be identified by tiling of baits across the relevant loci. Proposal We propose to apply this methodology to 10000 samples from patients with AML enrolled in clinical trials over the last 10-20 years. Oncogenic point mutations and potentially genomic rearrangements will be identified, and linked to clinical outcome data, with a view to undertaking the following sorts of analyses: • Identification of co-occurrence, mutual exclusivity and clusters of driver mutations. • Correlation of prognosis with driver mutations and potentially gene-gene interactions • Exploration of genomic markers of drug response Ultimately, we would like to be in a position to release the mutation data together with matched clinical outcome data to genuine medical researchers via a controlled access approach, possibly within the COSMIC framework (www.sanger.ac.uk/genetics/CGP/cosmic/). The vision here is to generate a portal whereby a clinician faced with an AML patient and his / her mutational profile can obtain a ‘personalised’ prediction of outcome, together with a fair assessment of the uncertainty of the estimate. With a sufficient sample size, there would also be the potential to develop decision support algorithms for therapeutic choices based on such data.

  Study EGAS00001000408

• Better Outcomes for Children: GWAS from Cincinnati Children's Hospital Medical Center (CCHMC) - eMERGE Phase II data - (dbGaP Deposit 1)

  This submission includes genotyping data from 6 separate cohorts (named A-E here), each is described in separate paragraphs below. Cohort A) Autism is a neurodevelopmental disorder that affects 1.5 million people in the United States, at an estimated lifetime cost of $4 million. It is part of Pervasive Developmental Disorder characterized by impairments in communication, language and reciprocal social interaction, and by unusual patterns of restricted and repetitive interests or behaviors. Autism, or autistic disorder, is the most severe form of the disease which has a wide range of symptom severity encompassed by the more inclusive term, Autism Spectrum Disorder (ASD). The prevalence of Autistic Disorder is currently estimated to be 4 per 1000, affecting 4 times more boys than girls. Susceptibility to autism is clearly attributable to genetic factors but the extensive clinical and genetic heterogeneity within the disorder have hindered efforts at genetic dissection. Identifying the genetic variants that contribute to this highly heritable disease is crucial to advancing research on autism. Reported concordance rates among monozygotic twins range from 60% &#8722; 90% and heritability of autism has been estimated to be 90% or greater. Identifying genetic variants that contribute to this highly heritable disease is crucial to advancing research on autism. Cohort B) The long-term objective of this research is to determine the molecular genetic basis of Cardiovascular (CV) disease in the young; this study seeks to identify gene mutations that cause "structural heart defects". Every year in the USA, 32,000 individuals are born with CV malformations; approximately 20% die during the first year of life. Another 30,000 young people develop a disturbance of cardiac rhythm or conduction. In addition, the life expectancy of another 40,000 young people is shortened by other forms of CV disease. It is becoming more apparent that in spite of the success in diagnosis and treatment, very little is known about the causes of CV disease in the young; understanding the causes will permit insight into the pathophysiologic basis of disease and allow definition of disease risk - two critical elements for disease prevention. Disease prevention and/or risk modification promises to be the new frontier in the management of CV disease in the young. Cohort C) Eosinophilic Esophagitis (EE) is one of the manifestations of eosinophilic gastrointestinal inflammation which have profound effects on a patient&#39;s health and development. Results of epidemiologic studies performed through our center demonstrate that eosinophil-associated gastrointestinal disease is not an uncommon entity. While the epidemiology of eosinophilic esophagitis has not been thoroughly studied until recently, there appears to be a significant increase in the diagnosis of EE in the last decade. Based on our research, this mainly reflects increased disease recognition, but there is also a bona-fide increase in disease incidence which coincides with the increasing incidence of asthma and allergic diseases in the industrialized world. In addition, many patients with intractable symptoms thought in the past to represent atypical GERD or other disorders are now being recognized as having EE. Diagnosis of EE requires endoscopy and biopsies to document the characteristic histologic findings of esophageal eosinophilia. In general, this study proposed to elucidate the mechanisms underlying eosinophil growth, survival, migration, and function, and to investigate and further characterize the pathophysiology of, clinical manifestations of, and spectrum of disease severity of eosinophilic esophagitis in humans. Cohort D) Juvenile idiopathic arthritis (JIA) is a debilitating complex genetic disorder characterized by inflammation of the joints and other tissues and shares histopathological features with other autoimmune diseases. It is considered a complex genetic disorder. There are more than 50,000 children with JIA in the USA, approximately 1 per 1000 births, which is about the same incidence as juvenile diabetes. It is believed that genes in the major histocompatibility complex (MHC) play a role in defining genetic risk, and it can be hypothesized that loci in other chromosomal regions are involved in conferring risk in JIA. These candidate chromosomal regions can be identified using genome wide association analyses. The long-term goal is a comprehensive understanding of the genetic basis of these disabling arthropathies for which the molecular basis is not presently understood. The results of recent GWAS for Caucasian JIA were recently published in Arthritis Rheum. 2012 Feb 21 (Published online, PMID=22354554). Cohort E) Childhood Absence Epilepsy (CAE) is characterized by very frequent (several to many per day) absence seizures in an otherwise normal child with an EEG usually demonstrating 3 Hz bilateral, synchronous, symmetrical spikewaves pattern with normal background activity. CAE occurs in 10% to 15% of all children with epilepsy with an annual incidence of 6.3 to 8/100,000 in children &lt;15 years of age. Females are more affected than males. Epilepsy onset is typically between the ages of 4 to 8 years with a peak incidence of 6 to 7 years. CAE does not start after age 13 years. The primary objective of this study is: To identify the optimal anticonvulsant (i.e. the antiepileptic drug (AED) with highest rate of seizure control and lowest incidence of treatment limiting toxicity) used for the initial treatment of children with Childhood Absence Epilepsy (CAE). The secondary objectives are: To determine the pharmacogenetic and other non-heritable factors underlying the interindividual variation in anticonvulsant response efficacy and toxicity. To define and contrast the effects of ethosuximide, lamotrigine, and valproic acid monotherapy on cognition (attention), behavior and quality of life in children with Childhood Absence Epilepsy. Cohort F) Cincinnati Controls. These are local healthy children selected to be representative of the population of Cincinnati with respect to gender and ancestry. Cohort G) Cytogenetics cases are ascertained by the clinical request to obtain cytogenetic analysis. The platform used included genotyping data which are then available for genome wide association analysis

  Study phs000494

• PCPT and SELECT Cohorts: Core Infrastructure Support for Cancer Research

  SELECT study: SELECT was a phase III, double-blind, placebo-controlled 4-arm study of selenium, vitamin E, selenium and vitamin E together, and placebo designed to assess the effect of these supplements on the incidence of prostate cancer. Funded by the National Cancer Institute and conducted by SWOG, the study opened in August 2001 and quickly exceeded its accrual goal of 35,533 men.In the fall of 2008, the trial's Data Safety and Monitoring Committee recommended that participants discontinue taking study supplements due to convincing evidence (planned interim futility analysis) that neither vitamin E nor selenium supplements were associated with the prevention of prostate cancer. A subsequent analysis in 2011 showed a significant 17% increase in prostate cancer incidence in participants who were on the vitamin E only arm. Approximately 17,000 participants from the original trial recently completed an additional four years of centralized follow-up. This follow-up ended on May 31, 2014 and SELECT is now closed. PCPT study: The Prostate Cancer Prevention Trial (PCPT) was a SWOG Cancer Research Network-coordinated study designed to test whether the drug finasteride (Proscar&#174;) would prevent prostate cancer in men ages 55 and older. This study was closed on June 24, 2003 because the study objective had been reached. The results of the study, which did find a preventive benefit for the drug, were published as "The Influence of Finasteride on the Development of Prostate Cancer," in the New England Journal of Medicine on July 17, 2003.

  Study phs003382

• CINECA_synthetic_cohort_EUROPE_UK1 referencing fake samples

  Please note: This synthetic data set (with cohort “participants” / ”subjects” marked with FAKE) has no identifiable data and cannot be used to make any inference about cohort data or results. The purpose of this dataset is to aid development of technical implementations for cohort data discovery, harmonization, access, and federated analysis. In support of FAIRness in data sharing, this dataset is made freely available under the Creative Commons Licence (CC-BY). Please ensure this preamble is included with this dataset and that the CINECA project (funding: EC H2020 grant 825775) is acknowledged. For any questions please contact isuru@ebi.ac.uk or cthomas@ebi.ac.uk This dataset (CINECA_synthetic_cohort_EUROPE_UK1) consists of 2521 samples which have genetic data based on 1000 Genomes data (https://www.nature.com/articles/nature15393), and synthetic subject attributes and phenotypic data derived from UKBiobank (https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001779). These data were initially derived using the TOFU tool (https://github.com/spiros/tofu), which generates randomly generated values based on the UKBiobank data dictionary. Categorical values were randomly generated based on the data dictionary, continuous variables generated based on the distribution of values reported by the UK Biobank showcase, and date / time values were random. Additionally we split the phenotypes and attributes into 4 main classes - general, cancer, diabetes mellitus, and cardiac. We assigned the general attributes to all the samples, and the cardiac / diabetes mellitus / cancer attributes to a proportion of the total samples. Once the initial set of phenotypes and attributes were generated, the data data was checked for consistency and where possible dependent attributes were calculated from the independent variables generated by TOFU. For example, BMI was calculated from height and weight data, and age at death generated by date of death and date of birth. These data were then loaded to the development instance of Biosamples (https://www.ebi.ac.uk/biosamples/) which accessioned each of the samples. The genetic data are derived from the 1000 Genomes Phase 3 release (https://www.internationalgenome.org/category/phase-3/). The genotype data consists of a single joint call vcf files with call genotypes for all 2504 samples, plus bed, bim, fam, and nosex files generated via plink for these samples and genotypes. The genotype data has had a variety of errors introduced to mimic real data and as a test for quality control pipelines. These include gender mismatches, ethnic background mislabelling and low call rates for a randomly chosen subset of sample data as well as deviations from Hardy Weinberg equilibrium and low call rates for a random selection of variants. Additionally 40 samples have raw genetic data available in the form of both bam and cram files, including unmapped data. The gender of the samples in the 1000 genomes data has been matched to the synthetic phenotypic data generated for these samples. The genetic data was then linked to the synthetic data in BioSamples, and submitted to EGA.

  Dataset EGAD00001006673

• All you need to know about our new DAC Portal v2

  An updated version to boost the management of DACs (Data Access Committees), policies, and data access requests. In September of 2023, we launched new services for all EGA users, including a DAC Portal. Since then, our team has been working to refine it and improve the user experience. The version 2 of our DAC Portal is now ready, with a range of new features aimed at streamlining your workflow and boosting productivity. If you are interested in learning more about the latest version of our DAC Portal, then you are in the right place! In this post, you will find information about the implemented features and more. The full documentation is available on our website. Moreover, we highly recommend exploring the DAC Portal through the Take the Tour. This said, let's get cracking! Customise your data access requests table This table offers the possibility to tailor information about the data access requests by making visible or hiding different columns regarding the Dataset Persistent Identifier, the Organisation or the requestor's name s, among others. You can choose which columns to see, depending on your needs and interests. Additionally, we have implemented two new features columns with two new functionalities, DAC Comment and Expiration Date. You can find more details in the following sections! In this table, all data access requests are displayed by default. With the latest version of the Portal, you can now apply filters, combine them, and save them for future use. Leave internal comments on pending requests and visible to all the DAC Members We understand that many Data Access Committees (DACs) cannot instantly approve or deny data access requests. Often, there's an intermediary phase where discussions and the signing of legal documents are necessary. To facilitate this process, we've introduced the DAC comment feature! When you navigate to the DAC column, you'll find two tabs: "User" and "DAC". Under "User", you'll see the message provided by the requester at the time of requesting access to the data. As a DAC member/admin, you can then add an internal comment in the "DAC" tab. These comments are visible only to DAC members/admins, ensuring confidentiality. Requesters won't have access to DAC comments. By adding a DAC comment to a pending request, we'll know that you've begun reviewing it. This allows you to filter pending requests without DAC comments to focus on genuinely new requests, and it prevents you from receiving email notifications about ongoing data requests. Set expiration dates for permissions and revoke them automatically The latest update to the DAC Portal introduces a new feature allowing you to set expiration dates for new access requests. For instance, if you anticipate approving a data access request but only wish to grant access for a limited time, you can now specify an expiration date for the granted permissions. Once this date is reached, the permissions will automatically be revoked. By default, permissions are granted indefinitely without an expiration date. However, if you ever need to revoke permissions, you can easily do so from the History page. Audit your metadata objects Managing and auditing your metadata objects will be easier from now on as the new DAC Portal enhances and facilitates your role as a Data Controller. This is possible thanks to the tables available in each of the primary tabs visible on the homepage: DACs, Policies and Datasets. Starting with DACs, this section allows to check the policies linked to a specific DAC. In Policies, you can obtain a list of the datasets connected to a particular policy. In the Dataset tab, it is possible to group datasets by either DAC or Policy, as well as the release status. Now you have the option of deprecating metadata objects that you don’t want to use anymore, or that were created by mistake. You will find the deprecate button on the EDIT page of the DAC, as well as for registered policies. You can find more information here. What's neat about this feature is that once a DAC or policy is deprecated, it becomes hidden within the DAC Portal. This ensures that you only see information that is consistently up to date! Define your preferences regarding email notifications For pending requests, you will be able to decide how often you want to get the notifications: daily, weekly or fortnightly. Remember, you will not receive email notifications for pending requests with a DAC comment! Furthermore, you have the flexibility to decide which notifications you wish to receive, such as invitations to join a new DAC or notifications regarding DAC acceptance by the Helpdesk, among other options. Check the User preference to see the complete list of available notification settings! What’s next: incoming DAC Portal API In addition to the new DAC Portal, we are excited to announce the release of the DAC API! This enables users to programmatically manage permissions. If you are interested in learning more about the technical specifications, you can consult the DAC API specification. This post was written by Aina Jené and Ana T. Alonso.

  Blog new-dac-portal-v2

• Submission FAQ

  Submission FAQ Before Submission Is the EGA the right archive for my data? TThe most suitable archive for your data is dependent on the type of data you are wishing to submit and whether the data require public or controlled access. Public access is defined as complete and open access to all submitted data. On the contrary, controlled access, exerted by the EGA, requires formal applications to be made to access the submitted data files and metadata. EGA only accepts human-derived data subject to controlled access. If your submission contains other types of data, please choose the appropriate repository for it (see image below): ENA, EVA, ArrayExpress, BioSD and GWAS catalog.  Should your submission be subjected to controlled access? Data access conditions are normally defined in the original informed consent agreements signed by the participants involved in your study. All data submitted to the EGA is subject to controlled access. These consents prevent the derived data files, potentially identifiable, from being dispersed by open and public access. Controlled access data often refers to human data derived from medical research and consortium projects. If in doubt, consult the informed consent agreements that apply to your study The EGA enables you to hold a submission before publication. What data types can be submitted to the EGA? Data types accepted by the EGA can be split into three categories: Sequences: both in generic and platform-specific formats. Array-based: from raw signal files to processed matrices. Phenotypes: all possible phenotype formats are accepted. All manufacturer-specific raw data formats derived from major next generation sequencing platforms are accepted. Also generic sequence formats: flat reads in a FASTQ file, aligned sequences (BAM or CRAM files) as well as sequence variation files in VCF format. All array-based technologies are accepted, including raw data, intensity and analysis files, without any restriction on data formats accepted. We also accept and distribute phenotype data (associated to the samples) in almost any format: from an image to a README file. How long does a submission take? Submissions to EGA come in a variety of formats and sizes, thus it is difficult for us to exactly predict how long a submission will take. We, therefore, advise all of our submitters to allow as much time as possible to make a submission. Based on previous records, we anticipate that the submission process may take at least one month. The submitter’s familiarity with the procedures, possible technical issues that may arise during submission and the amount of data that is being submitted are the main factors that will affect the length of the submission process. However, each step of a regular submission should be considered when estimating the time it would take: Encryption of the files Upload of the files Metadata submission Archival of the files Release of the study and datasets to EGA webpage For example, the upload of the files depends on the submission size, while metadata submission mainly relies on each submitter’s expertise. Further, some steps (e.g. answering to inquiries) depend on the EGA Helpdesk team, which may take some days to be processed during busy times Is data deposited in the EGA secure? The EGA set-up consists of a secure computing facility for data processing, a shared EBI set-up for data submissions and distribution of data via data requests made through the EGA website. Data is also copied in the Barcelona Supercomputing Center (BSC) infrastructure, where all stored and distributed data is encrypted Data is encrypted along the submission process and stored securely, granting its access to authorised users exclusively. During the download process, through our Python Client or Aspera, all requested data is downloaded over secure https connections. All data at the EGA is encrypted, and only accessible (for log-in and download) through secure protocols. For further information please, visit our security overview. What documentation do I need to provide? All submissions require policy’s documentation: 'Data Access Agreement (DAA)', 'Data Processing Agreement (DPA)' and 'Authorized Submitters Formulary'. The data processors (EGA) and the data owners will also sign the DPA. Will all metadata be public? Among the submitted metadata we need to make the distinction between identifiable and unidentifiable metadata: (1) the former may allow the identification of the human the sample derived from (e.g. detailed geographical providence, personal name, family ancestry…); (2) while the latter can be used to interpret the data without compromising the anonymity of the patients. The majority of the metadata submitted to the EGA corresponds to the unidentifiable category (e.g. sequencer's model). This type of metadata is publicly available on the EGA website and other EBI resources/partners’ websites. On the other hand, some parts samples’ metadata are subject to being identifiable, and thus only accessible by authorized data requesters, with the exception of: 5 submitter-defined attributes of the sample: alias, title, subject_id, gender and phenotype. It is the submitter’s responsibility not to submit sensitive metadata in these public fields. 3 anonymised fields that pinpoint the sample record in archivals: sample’s EGA stable ID (EGAN…), BioSample ID (SAMEA…) and submitter’s center name. During Submission Are there any sample specific requirements for EGA? All samples submitted to the EGA must include the attributes of biological sex, subject ID (anonymised individual identifier) and phenotype information. These are critical for data findability and its analysis, and we highly recommend using controlled ontology terms where applicable. For example: defining tumour and non-tumour samples and/or defining disease state. The EGA recommends using the Experimental Factor Ontology Database to find ontologized terms that describe your sample phenotypes. How do I get an accession number to use in my publication? You will receive your study accession number (EGAS…) upon complete your submission, either: Programmatically. As soon as the metadata is submitted and validated your study will be assigned an accession number that will be given in the submission’s response. Manually registering your study and relevant metadata using the online metadata submission tool: the EGA submitter Portal. How are files uploaded to the EGA? Data files are uploaded into private submission drop boxes (i.e. environments to which you are granted access and where you can transfer your files) using INBOX or FTP. These spaces are provided as part of the submission procedure. Before uploading any file, you must encrypt your files, . Only encrypted files shall be uploaded to the drop boxes. Why does data need to to encrypted for my submitted files? It is one of the security steps the EGA has implemented. In case of a security breach, people without the proper encryption key will not be able to read or use the information that could have been leaked. This measure is essential when working with sensitive data, such as controlled access human data. All submitters must use crypt4gh to create EGA compliant files prior to uploading them. This encryption is GPG-based, using EGA’s public key. Why are my files not available if I see them in the INBOX? There exists a time window between the data upload and the availability of such files via the Submitter Portal. For this reason, some metadata (run and analysis objects) cannot be registered until at least 24 hours after the files have been uploaded to your box. Why are MD5 sum values generated for my submitted files? We require pre- and post- encryption MD5 (message-digest) checksum values to be provided for all submitted files. These 128-bit values are computed using the content of each file, creating unique sequences that allow us to ensure that file integrity has been maintained during the transfer process. In other words, if the MD5 checksums we generate and those you generated match, we infer that the content of the transferred files is correct (i.e. files are not corrupted or truncated). MD5 checksums are computed automatically using the crypt4gh tool provided. Your submission will not be accepted and may be significantly delayed if you do not provide MD5 checksum values for all data files in the required format. How can I check if my files are correctly uploaded to the inbox? It is important to check the status pf your file so you know whether your files are in the inbox, being processed, or if there is any issue with one of them. In order to check this, you should: Look for the file locally. Drag and drop it to the file table. Then bars will appear on the table, which means that we are processing it. Green: The files checksum are correct and your file will move to “ingested files”. No further actions are needed from your end.. Red: The files checksum does not match and your file needs to be re-uploaded. Please re-upload relevant files to your inbox using the same path. After Submission How do I use my accession number in my publication? We suggest the use of the below template, using your study accession ID (EGAS…) : Data has been deposited at the European Genome-phenome Archive (EGA), which is hosted by the EBI and the CRG, under accession number EGASXXXXXXXXXXX. Further information about EGA can be found at https://ega-archive.org and "The European Genome-phenome Archive of human data consented for biomedical research" Your study ID will be the one that groups your whole submission, and thus its usage is recommended as such. Nevertheless, all metadata submitted to EGA hold a unique and persistent identifier (starting with EGA…) that can be used to identify specific records. For example, you could reference a specific dataset (EGAD…) or sample (EGAN…) in your publications (see full list of identifiers). How do I make my data searchable? Once you have finalized your submission, you can schedule the data release. Please take into account that the release process needs time for the files to be archived in our system, and for the Helpdesk team to validate your submission. Can I withdraw (meta)data from the EGA? We have methods in place for the secure removal of deposited (meta)data. Contact EGA-helpdesk for further details. EGA complies with FAIRness of (meta)data, and thus, even when the data is removed we keep an entry for their identifiers in our system. In other words, we execute a soft delete on canceled objects (e.g. a study): metadata is still stored in our systems, but it loses all links, cannot be queried and data files cannot be retrieved anymore. The reason behind this behaviour is so that queries using withdrawn data properly respond back (see example of a canceled study). What happens to the data once it has been submitted to the EGA? When the data is submitted, the submitter can choose either keep their data private or schedule the release of their data.

  Documentation submission/metadata/submission/FAQ

• Targeted sequencing of genes recurrently mutated in AML

  Background Massively parallel sequencing technology has transformed cancer genomics. It is now feasible, in a clinically relevant time-frame, for a clinically manageable cost, to screen DNA from patient tumours for mutations essentially genome-wide. The challenge for personalised medicine will be to increase the sample size to thousands or tens of thousands of well-characterised cases in order to attain sufficient statistical power to stratify patients accurately across the complexity and genomic heterogeneity expected for most of the common tumour types. Currently, whole genome sequencing on this scale is not feasible, and targeted sequencing of relevant portions of the genome will be required. Pilot data We have developed protocols for large-scale, multiplexed sequencing of 100-200 genes in thousands of samples. Essentially, using robotic technology, genomic DNA from the cancer specimen is processed into sequencing libraries with unique DNA barcodes, thereby allowing sequencing reads to be attributed to the sample they derive from. Currently, these sequencing libraries can be generated in a 96-well format using fully automated protocols, and we are exploring methods to expand this to a 384-well format. The sequencing libraries are pooled and hybridized to custom sets of RNA baits representing the genomic regions of interest. Sequencing of the pulled-down libraries is done in pools of 48-96 samples per lane of an Illumina Hi-Seq. This protocol is already implemented at the Sanger Institute. We have published proof that somatic mutations in novel cancer genes can be identified from exome-wide sequencing. In unpublished pilot data, we have established the feasibility of robotic library production, custom pull-down, and multiplexed sequencing of barcoded libraries for 100 known myeloid cancer genes across 760 myelodysplasia samples. Highlights of the data thus far analysed reveal that the coverage is remarkably even between samples; when 96 samples are run, average coverage per lane of sequencing is ~250, with 90-95% of targeted exons covered by &gt;25 reads; known mutations can be discovered in the data set; and the protocol is amenable to whole genome amplified DNA. The bioinformatic algorithms for identification of substitutions and indels in pull-down data are well-established; we have pilot data proving that copy number changes, LOH and genomic rearrangements in specific regions of interest can also be identified by tiling of baits across the relevant loci. Proposal We propose to apply this methodology to 10000 samples from patients with AML enrolled in clinical trials over the last 10-20 years. Oncogenic point mutations and potentially genomic rearrangements will be identified, and linked to clinical outcome data, with a view to undertaking the following sorts of analyses: ? Identification of co-occurrence, mutual exclusivity and clusters of driver mutations. ? Correlation of prognosis with driver mutations and potentially gene-gene interactions ? Exploration of genomic markers of drug response Ultimately, we would like to be in a position to release the mutation data together with matched clinical outcome data to genuine medical researchers via a controlled access approach, possibly within the COSMIC framework (www.sanger.ac.uk/genetics/CGP/cosmic/). The vision here is to generate a portal whereby a clinician faced with an AML patient and his / her mutational profile can obtain a ?personalised? prediction of outcome, together with a fair assessment of the uncertainty of the estimate. With a sufficient sample size, there would also be the potential to develop decision support algorithms for therapeutic choices based on such data.

  Dataset EGAD00001000606

• Molecular Genetic Studies of Developmental Brain Disorders

  Study 1 2R01-NS050375 (PI: DOBYNS, William B.) The genetic basis of mid-hindbrain malformations Our general goal for this project is to advance our understanding of human developmental disorders that involve the brainstem and cerebellum - brain structures derived from the embryonic midbrain and hindbrain - that affect a minimum of 2.4 per 1000 resident births based on data from the CDC. Importantly, this large class of disorders co-occurs with more common developmental disorders such as autism, mental retardation and some forms of infantile epilepsy, and shares some of the same causes. With this renewal, we propose to expand the scope of our work beyond single phenotypes and genes to focus on delineating the critical phenotype spectra to which the most common MHM belong, and defining the underlying biological networks that are disrupted. To pursue these goals, we will use our large and growing cohort of human subjects to map additional MHM loci using SNP microarrays that provide both high-resolution autozygosity and linkage data in informative families as well as detect critical copy number variants in sporadic subjects. The causative genes will be identified using traditional Sanger or new high-throughput sequencing methods as appropriate abased on size of the critical region. We will use these and other known MHM causative genes to construct and revise model biological networks of genes and proteins, and test these genes and networks in additional patients as a candidate gene or more accurately a candidate network approach. These approaches need to be supported by ongoing active subject recruitment, as studies of comparable disorders such as mental retardation and autism have benefited from even larger numbers of subjects that we have so far collected. We need to use new high-throughput sequencing methods to more efficiently test larger critical regions, and to test entire gene networks rather than individual genes in matched cohorts of subjects. At every step; phenotype analysis, CNV analysis, model network construction and high-throughput sequencing, we will need expanded bioinformatics capabilities. Finally, we need to test the biological function of new genes and networks to support our gene identification studies. We expect that these studies will contribute immediately to more accurate diagnosis and counseling, and over time will lead to development of specific treatments for a subset of these disorders. We further expect that studies of mid-hindbrain development will have broad significance for human developmental disorders generally, providing compelling evidence for a connection between cerebellar development and other classes of developmental disorders such as autism, mental retardation and epilepsy. Study 2 R01-NS058721 (PI: DOBYNS, William B.) De novo copy number variation and gene discovery in human brain malformations Project Summary/Abstract The number of recognized brain malformations and syndromes has grown rapidly during the past several decades, yet relatively few causative genes have been identified, especially for three common malformations that have been associated with numerous cytogenetically visible chromosome deletions and duplications, and that often occur together: agenesis of the corpus callosum (ACC), cerebellar vermis hypoplasia (CVH) including Dandy-Walker malformation (DWM), and polymicrogyria (PMG). We propose to perform high-resolution array comparative genome hybridization (aCGH), emerging technology able to detect small copy number variants (CNV), in 700 probands with one or more of these three malformations. Our central hypothesis states that more than 10% of patients with ACC, CVH or PMG will have de novo CNV below the resolution of routine cytogenetic analysis, but detectable by current array platforms. We therefore expect to identify 70-100 patients with small CNV. We will distinguish CNV found in normal individuals from potentially disease-associated changes, and will confirm CNV using fluorescence in situ hybridization (FISH) and microsatellite (STRP) analysis. We will give highest priority to CNV that are de novo and involve 2 or more BACs, and secondary priority to familial and smaller CNV excluding known polymorphisms. After that, we will evaluate and rank candidate genes in the critical regions using information from public databases and our own expression studies, and perform mutation analysis of the best candidate genes from well-defined critical regions by sequencing in a large panel of subjects with phenotypes that match the phenotypes of the patients whose CNV define the critical regions. Here, we will use more refined criteria to supplement our clinical classification, such as the developmental level and presence of epilepsy or other birth defects. Any abnormalities found will be analyzed using existing data regarding polymorphisms (i.e. dbSNP), cross-species comparisons, and functional assays appropriate for the specific sequence change. Study 2A In 1995, we described a novel multiple congenital anomaly syndrome associated with facial dysmorphism (congenital ptosis, high arched eyebrows, shallow orbits, trigonocephaly), colobomas of the eyes, neuronal migration malformation (frontal predominant lissencephaly) and variable hearing loss. We hypothesized from de novo mutations and used trio-based exome sequencing to identify de novo mutations in the ACTB and ACTG1 genes. Study 2B In 1997 and 2004, we and others defined two novel developmental syndromes associated with markedly enlarged brain size, or megalencephaly, and other highly recognizable features. The megalencephaly-capillary malformation syndrome (MCAP) consists of megalencephaly and associated growth dysregulation with variable asymmetry, developmental vascular anomalies, distal limb malformations, variable cortical malformation, and a mild connective tissue dysplasia. The megalencephaly-polymicrogyria-polydactyly-hydrocephalus syndrome (MPPH) resembles MCAP but lacks vascular malformations and syndactyly. We hypothesized that MCAP and MPPH result from mutations - including postzygotic events - in the same pathway, and studied them together. Using a combination of exome sequencing, Sanger sequencing, restriction-enzyme assays, and targeted ultra-deep sequencing in 50 families with MCAP or MPPH, we identified de novo germline or postzygotic mutations in three core components of the phosphatidylinositol-3-kinase/AKT pathway. These include two mutations in AKT3, a recurrent mutation in PIK3R2, and multiple mostly postzygotic mutations in PIK3CA (Rivi&#232;re JB, Mirzaa GM, O&#39;Roak BJ, Beddaoui M, Alcantara D, Conway RL, St-Onge J, Schwartzentruber JA, Gripp KW, Nikkel SM, Worthylake T, Sullivan CT, Ward TR, Butler HE, Kramer NA, Albrecht B, Armour CM, Armstrong L, Caluseriu O, Cytrynbaum C, Drolet BA, Innes AM, Lauzon JL, Lin AE, Mancini GMS, Meschino WS, Reggin JD, Saggar AK, Lerman-Sagie T, Uyanik G, Weksberg R, Zirn B, Beaulieu CL, FORGE Canada Consortium, Majewski J, Bulman DE, O&#39;Driscoll M, Shendure J, Graham Jr. JM, Boycott KM, Dobyns WB. De novo germline and postzygotic mutations in AKT3, PIK3R2 and PIK3CA cause a spectrum of related megalencephaly syndromes. Nat. Genet. In press). Study 3 2R01-NS046616 (PI: GOLDEN, Jeffrey A) The role of ARX in normal and abnormal brain development This subcontract from the Children&#39;s Hospital of Philadelphia to the University of Chicago (UC) is intended to support research studies of the ARX and functionally related genes in human subjects with any one of several specific developmental disorders. The Co-investigator at UC (W.B. Dobyns) will identify a series of patients with mental retardation and severe infantile epilepsy, some of whom will have specific brain malformations and others who will have normal brain structure by brain imaging studies, and collect research samples from these subjects with informed consent. The studies to be performed will include mutation analysis of ARX, mutation analysis of specific downstream target genes, X inactivation studies in humans and X inactivation studies in mutant mice. The results will be analyzed to determine the significance of any changes found in the gene.

  Study phs000455

• How to request data

  Request Data Access If you're looking to access data from the EGA for your research, you are in the right documentation page! In this page you will find a step by step guide on how to request data archived at the EGA, as well as some frequently asked questions you might find useful. When requesting data, you'll need to provide information about your research project and intended use of the data. Keep in mind that your data access request may require additional approvals or agreements depending on the datasets and data providers involved. Step by step guide Register yourself as an EGA user. Validate your account. A validation link will be sent to your email to activate your EGA user account. Log into the EGA page. Search the dataset of interest from the dataset catalogue or search bar. Click on “Request access” Add a comment requesting these files and send your request Your request is successfully registered, and the DAC will receive a notification about your request In addition to submitting your request, you should also contact the DAC directly via e-mail. You can access the DAC's contact information from the relevant dataset page. Frequently Asked Questions (FAQ) Which is the role of the EGA in the data access process? The European Genome-phenome Archive (EGA) facilitates the secure distribution under controlled access of personally identifiable genetic and phenotypic data. Data Access Committee (DAC) is a body of one or more individuals who are responsible for data release to external requestors, based on participant consent and/or National Research Ethics terms. How do I request access to multiple datasets? To request access for multiple datasets managed by the same Data Access Committee (DAC), please start by visiting the DAC catalogue to locate the DAC of your choice. Once you've found the relevant DAC, proceed to its dedicated page where you'll find a "Request access" button. After logging in to the EGA website, you'll be presented with a comprehensive list of datasets under the chosen DAC. Select the datasets you're interested in, and then compose a message indicating your access request. Click the "Send" button to submit your request, which will include the chosen datasets. Please be sure to review the data usage policies for the requested datasets, as policies can vary among datasets managed by the same DAC. I am a co-applicant. Will I be given a joint access account? Each applicant needs to create an EGA account themselves, with unique login details. User log-in details are for individual use only and should never be shared, under any circumstances. EGA services are only provided to EGA account holders. Therefore, the co-applicant will send a formal request to the DAC. What happens if a co-applicant leaves or a new member needs to be added to an existing DAC application? The appropriate Data Access Committee (DAC) should be contacted and informed about the required changes so that the application can be updated. I have changed my place of work since my EGA account was created. Can I still have access to data? You must contact the relevant Data Access Committee (DAC). The DAC did not reply to my data access request. How should I proceed? There is no estimated time for DAC response. Please allow up to four weeks for a response. In the meantime, please send them a weekly reminder of the status of your request by emailing them directly.If the DAC becomes unresponsive, meaning that they fail to communicate with a requestor within the specified time frame, please contact the EGA Helpdesk team. I have an account with the EGA and would like access to further datasets. How should I proceed? You need to reapply to the relevant Data Access Committee (DAC). Once the DAC has approved your application your account will be updated and an email will be sent to notify you of a change made to your account. How do I download files of the datasets I have been granted access to? The preferred method for data download and decryption is the EGA Secure Download Client. Please carefully review the provided documentation. How do I download metadata? Metadata is retrieved from the EGA webpage; you will not need to use any download client. Be informed that you will only be able to download metadata of your approved datasets. For such download, you should first log in the EGA webpage with your credentials. Then browse the metadata's dataset you have gained access and you will find a metadata download button. You may also want to have a look our metadata schema. I have forgotten or misplaced my user account password; how do I get a new one? Click on “Log in”, located in the top right corner of the EGA homepage. Then click “Forgot password”, type in your registered institutional email address, and instructions for resetting your password will be sent to you. Please check both regular and junk/spam folders. I was sent a link to set a password for my download account, but it seems like the link has expired. What should I do? The procedure is the same as the one for a forgotten password, explained in the previous question.

  Documentation access/request-data/how-to-request-data

• OncoArray: Prostate Cancer

  Original description of the study: From ELLIPSE (linked to the PRACTICAL consortium), we contributed ~78,000 SNPs to the OncoArray. A large fraction of the content was derived from the GWAS meta-analyses in European ancestry populations (overall and aggressive disease; ~27K SNPs). We also selected just over 10,000 SNPs from the meta-analyses in the non-European populations, with a majority of these SNPs coming from the analysis of overall prostate cancer in African ancestry populations as well as from the multiethnic meta-analysis. A substantial fraction of SNPs (~28,000) were also selected for fine-mapping of 53 loci not included in the common fine-mapping regions (tagging at r2&#62;0.9 across &#177;500kb regions). We also selected a few thousand SNPs related with PSA levels and/or disease survival as well as SNPs from candidate lists provided by study collaborators, as well as from meta-analyses of exome SNP chip data from the Multiethnic Cohort and UK studies. The Contributing Studies: Aarhus: Hospital-based, Retrospective, Observational. Source of cases: Patients treated for prostate adenocarcinoma at Department of Urology, Aarhus University Hospital, Skejby (Aarhus, Denmark). Source of controls: Age-matched males treated for myocardial infarction or undergoing coronary angioplasty, but with no prostate cancer diagnosis based on information retrieved from the Danish Cancer Register and the Danish Cause of Death Register. AHS: Nested case-control study within prospective cohort. Source of cases: linkage to cancer registries in study states. Source of controls: matched controls from cohort ATBC: Prospective, nested case-control. Source of cases: Finnish male smokers aged 50-69 years at baseline. Source of controls: Finnish male smokers aged 50-69 years at baseline BioVu: Cases identified in a biobank linked to electronic health records. Source of cases: A total of 214 cases were identified in the VUMC de-identified electronic health records database (the Synthetic Derivative) and shipped to USC for genotyping in April 2014. The following criteria were used to identify cases: Age 18 or greater; male; African Americans (Black) only. Note that African ancestry is not self-identified, it is administratively or third-party assigned (which has been shown to be highly correlated with genetic ancestry for African Americans in BioVU; see references). Source of controls: Controls were identified in the de-identified electronic health record. Unfortunately, they were not age matched to the cases, and therefore cannot be used for this study. Canary PASS: Prospective, Multi-site, Observational Active Surveillance Study. Source of cases: clinic based from Beth Israel Deaconness Medical Center, Eastern Virginia Medical School, University of California at San Francisco, University of Texas Health Sciences Center San Antonio, University of Washington, VA Puget Sound. Source of controls: N/A CCI: Case series, Hospital-based. Source of cases: Cases identified through clinics at the Cross Cancer Institute. Source of controls: N/A CerePP French Prostate Cancer Case-Control Study (ProGene): Case-Control, Prospective, Observational, Hospital-based. Source of cases: Patients, treated in French departments of Urology, who had histologically confirmed prostate cancer. Source of controls: Controls were recruited as participating in a systematic health screening program and found unaffected (normal digital rectal examination and total PSA &#60; 4 ng/ml, or negative biopsy if PSA &#62; 4 ng/ml). COH: hospital-based cases and controls from outside. Source of cases: Consented prostate cancer cases at City of Hope. Source of controls: Consented unaffected males that were part of other studies where they consented to have their DNA used for other research studies. COSM: Population-based cohort. Source of cases: General population. Source of controls: General population CPCS1: Case-control - Denmark. Source of cases: Hospital referrals. Source of controls: Copenhagen General Population Study CPCS2: Source of cases: Hospital referrals. Source of controls: Copenhagen General Population Study CPDR: Retrospective cohort. Source of cases: Walter Reed National Military Medical Center. Source of controls: Walter Reed National Military Medical Center ACS_CPS-II: Nested case-control derived from a prospective cohort study. Source of cases: Identified through self-report on follow-up questionnaires and verified through medical records or cancer registries, identified through cancer registries or the National Death Index (with prostate cancer as the primary cause of death). Source of controls: Cohort participants who were cancer-free at the time of diagnosis of the matched case, also matched on age (&#177;6 mo) and date of biospecimen donation (&#177;6 mo). EPIC: Case-control - Germany, Greece, Italy, Netherlands, Spain, Sweden, UK. Source of cases: Identified through record linkage with population-based cancer registries in Italy, the Netherlands, Spain, Sweden and UK. In Germany and Greece, follow-up is active and achieved through checks of insurance records and cancer and pathology registries as well as via self-reported questionnaires; self-reported incident cancers are verified through medical records. Source of controls: Cohort participants without a diagnosis of cancer EPICAP: Case-control, Population-based, ages less than 75 years at diagnosis, H&#233;rault, France. Source of cases: Prostate cancer cases in all public hospitals and private urology clinics of d&#233;partement of H&#233;rault in France. Cases validation by the H&#233;rault Cancer Registry. Source of controls: Population-based controls, frequency age matched (5-year groups). Quotas by socio-economic status (SES) in order to obtain a distribution by SES among controls identical to the SES distribution among general population men, conditionally to age. ERSPC: Population-based randomized trial. Source of cases: Men with PrCa from screening arm ERSPC Rotterdam. Source of controls: Men without PrCa from screening arm ERSPC Rotterdam ESTHER: Case-control, Prospective, Observational, Population-based. Source of cases: Prostate cancer cases in all hospitals in the state of Saarland, from 2001-2003. Source of controls: Random sample of participants from routine health check-up in Saarland, in 2000-2002 FHCRC: Population-based, case-control, ages 35-74 years at diagnosis, King County, WA, USA. Source of cases: Identified through the Seattle-Puget Sound SEER cancer registry. Source of controls: Randomly selected, age-frequency matched residents from the same county as cases Gene-PARE: Hospital-based. Source of cases: Patients that received radiotherapy for treatment of prostate cancer. Source of controls: n/a Hamburg-Zagreb: Hospital-based, Prospective. Source of cases: Prostate cancer cases seen at the Department of Oncology, University Hospital Center Zagreb, Croatia. Source of controls: Population-based (Croatia), healthy men, older than 50, with no medical record of cancer, and no family history of cancer (1st &#38; 2nd degree relatives) HPFS: Nested case-control. Source of cases: Participants of the HPFS cohort. Source of controls: Participants of the HPFS cohort IMPACT: Observational. Source of cases: Carriers and non-carriers (with a known mutation in the family) of the BRCA1 and BRCA2 genes, aged between 40 and 69, who are undergoing prostate screening with annual PSA testing. This cohort has been diagnosed with prostate cancer during the study. Source of controls: Carriers and non-carriers (with a known mutation in the family) of the BRCA1 and BRCA2 genes, aged between 40 and 69, who are undergoing prostate screening with annual PSA testing. This cohort has not been diagnosed with prostate cancer during the study. IPO-Porto: Hospital-based. Source of cases: Early onset and/or familial prostate cancer. Source of controls: Blood donors Karuprostate: Case-control, Retrospective, Population-based. Source of cases: From FWI (Guadeloupe): 237 consecutive incident patients with histologically confirmed prostate cancer attending public and private urology clinics; From Democratic Republic of Congo: 148 consecutive incident patients with histologically confirmed prostate cancer attending the University Clinic of Kinshasa. Source of controls: From FWI (Guadeloupe): 277 controls recruited from men participating in a free systematic health screening program open to the general population; From Democratic Republic of Congo: 134 controls recruited from subjects attending the University Clinic of Kinshasa KULEUVEN: Hospital-based, Prospective, Observational. Source of cases: Prostate cancer cases recruited at the University Hospital Leuven. Source of controls: Healthy males with no history of prostate cancer recruited at the University Hospitals, Leuven. LAAPC: Subjects were participants in a population-based case-control study of aggressive prostate cancer conducted in Los Angeles County. Cases were identified through the Los Angeles County Cancer Surveillance Program rapid case ascertainment system. Eligible cases included African American, Hispanic, and non-Hispanic White men diagnosed with a first primary prostate cancer between January 1, 1999 and December 31, 2003. Eligible cases also had (a) prostatectomy with documented tumor extension outside the prostate, (b) metastatic prostate cancer in sites other than prostate, (c) needle biopsy of the prostate with Gleason grade &#8805;8, or (d) needle biopsy with Gleason grade 7 and tumor in more than two thirds of the biopsy cores. Eligible controls were men never diagnosed with prostate cancer, living in the same neighborhood as a case, and were frequency matched to cases on age (&#177; 5 y) and race/ethnicity. Controls were identified by a neighborhood walk algorithm, which proceeds through an obligatory sequence of adjacent houses or residential units beginning at a specific residence that has a specific geographic relationship to the residence where the case lived at diagnosis. Malaysia: Case-control. Source of cases: Patients attended the outpatient urology or uro-onco clinic at University Malaya Medical Center. Source of controls: Population-based, age matched (5-year groups), ascertained through electoral register, Subang Jaya, Selangor, Malaysia MCC-Spain: Case-control. Source of cases: Identified through the urology departments of the participating hospitals. Source of controls: Population-based, frequency age and region matched, ascertained through the rosters of the primary health care centers MCCS: Nested case-control, Melbourne, Victoria. Source of cases: Identified by linkage to the Victorian Cancer Registry. Source of controls: Cohort participants without a diagnosis of cancer MD Anderson: Participants in this study were identified from epidemiological prostate cancer studies conducted at the University of Texas MD Anderson Cancer Center in the Houston Metropolitan area. Cases were accrued in the Houston Medical Center and were not restricted with respect to Gleason score, stage or PSA. Controls were identified via random-digit-dialing or among hospital visitors and they were frequency matched to cases on age and race. Lifestyle, demographic, and family history data were collected using a standardized questionnaire. MDACC_AS: A prospective cohort study. Source of cases: Men with clinically organ-confined prostate cancer meeting eligibility criteria for a prospective cohort study of active surveillance at MD Anderson Cancer Center. Source of controls: N/A MEC: The Multiethnic Cohort (MEC) is comprised of over 215,000 men and women recruited from Hawaii and the Los Angeles area between 1993 and 1996. Between 1995 and 2006, over 65,000 blood samples were collected from participants for genetic analyses. To identify incident cancer cases, the MEC was cross-linked with the population-based Surveillance, Epidemiology and End Results (SEER) registries in California and Hawaii, and unaffected cohort participants with blood samples were selected as controls MIAMI (WFPCS): Prostate cancer cases and controls were recruited from the Departments of Urology and Internal Medicine of the Wake Forest University School of Medicine using sequential patient populations as described previously (PMID:15342424). All study subjects received a detailed description of the study protocol and signed their informed consent, as approved by the medical center&#39;s Institutional Review Board. The general eligibility criteria were (i) able to comprehend informed consent and (ii) without previously diagnosed cancer. The exclusion criteria were (i) clinical diagnosis of autoimmune diseases; (ii) chronic inflammatory conditions; and (iii) infections within the past 6 weeks. Blood samples were collected from all subjects. MOFFITT: Hospital-based. Source of cases: clinic based from Moffitt Cancer Center. Source of controls: Moffitt Cancer Center affiliated Lifetime cancer screening center NMHS: Case-control, clinic based, Nashville TN. Source of cases: All urology clinics in Nashville, TN. Source of controls: Men without prostate cancer at prostate biopsy. PCaP: The North Carolina-Louisiana Prostate Cancer Project (PCaP) is a multidisciplinary population-based case-only study designed to address racial differences in prostate cancer through a comprehensive evaluation of social, individual and tumor level influences on prostate cancer aggressiveness. PCaP enrolled approximately equal numbers of African Americans and Caucasian Americans with newly-diagnosed prostate cancer from North Carolina (42 counties) and Louisiana (30 parishes) identified through state tumor registries. African American PCaP subjects with DNA, who agreed to future use of specimens for research, participated in OncoArray analysis. PCMUS: Case-control - Sofia, Bulgaria. Source of cases: Patients of Clinic of Urology, Alexandrovska University Hospital, Sofia, Bulgaria, PrCa histopathologically confirmed. Source of controls: 72 patients with verified BPH and PSA&#60;3,5; 78 healthy controls from the MMC Biobank, no history of PrCa PHS: Nested case-control. Source of cases: Participants of the PHS1 trial/cohort. Source of controls: Participants of the PHS1 trial/cohort PLCO: Nested case-control. Source of cases: Men with a confirmed diagnosis of prostate cancer from the PLCO Cancer Screening Trial. Source of controls: Controls were men enrolled in the PLCO Cancer Screening Trial without a diagnosis of cancer at the time of case ascertainment. Poland: Case-control. Source of cases: men with unselected prostate cancer, diagnosed in north-western Poland at the University Hospital in Szczecin. Source of controls: cancer-free men from the same population, taken from the healthy adult patients of family doctors in the Szczecin region PROCAP: Population-based, Retrospective, Observational. Source of cases: Cases were ascertained from the National Prostate Cancer Register of Sweden Follow-Up Study, a retrospective nationwide cohort study of patients with localized prostate cancer. Source of controls: Controls were selected among men referred for PSA testing in laboratories in Stockholm County, Sweden, between 2010 and 2012. PROGReSS: Hospital-based, Prospective, Observational. Source of cases: Prostate cancer cases from the Hospital Cl&#237;nico Universitario de Santiago de Compostela, Galicia, Spain. Source of controls: Cancer-free men from the same population ProMPT: A study to collect samples and data from subjects with and without prostate cancer. Retrospective, Experimental. Source of cases: Subjects attending outpatient clinics in hospitals. Source of controls: Subjects attending outpatient clinics in hospitals ProtecT: Trial of treatment. Samples taken from subjects invited for PSA testing from the community at nine centers across United Kingdom. Source of cases: Subjects who have a proven diagnosis of prostate cancer following testing. Source of controls: Identified through invitation of subjects in the community. PROtEuS: Case-control, population-based. Source of cases: All new histologically-confirmed cases, aged less or equal to 75 years, diagnosed between 2005 and 2009, actively ascertained across Montreal French hospitals. Source of controls: Randomly selected from the Provincial electoral list of French-speaking men between 2005 and 2009, from the same area of residence as cases and frequency-matched on age. QLD: Case-control. Source of cases: A longitudinal cohort study (Prostate Cancer Supportive Care and Patient Outcomes Project: ProsCan) conducted in Queensland, through which men newly diagnosed with prostate cancer from 26 private practices and 10 public hospitals were directly referred to ProsCan at the time of diagnosis by their treating clinician (age range 43-88 years). All cases had histopathologically confirmed prostate cancer, following presentation with an abnormal serum PSA and/or lower urinary tract symptoms. Source of controls: Controls comprised healthy male blood donors with no personal history of prostate cancer, recruited through (i) the Australian Red Cross Blood Services in Brisbane (age range 19-76 years) and (ii) the Australian Electoral Commission (AEC) (age and post-code/ area matched to ProsCan, age range 54-90 years). RAPPER: Multi-centre, hospital based blood sample collection study in patients enrolled in clinical trials with prospective collection of radiotherapy toxicity data. Source of cases: Prostate cancer patients enrolled in radiotherapy trials: CHHiP, RT01, Dose Escalation, RADICALS, Pelvic IMRT, PIVOTAL. Source of controls: N/A SABOR: Prostate Cancer Screening Cohort. Source of cases: Men &#62;45 yrs of age participating in annual PSA screening. Source of controls: Males participating in annual PSA prostate cancer risk evaluations (funded by NCI biomarkers discovery and validation grant), recruited through University of Texas Health Science Center at San Antonio and affiliated sites or through study advertisements, enrolment open to the community SCCS: Case-control in cohort, Southeastern USA. Prospective, Observational, Population-based. Source of cases: SCCS entry population. Source of controls: SCCS entry population SCPCS: Population-based, Retrospective, Observational. Source of cases: South Carolina Central Cancer Registry. Source of controls: Health Care Financing Administration beneficiary file SEARCH: Case-control - East Anglia, UK. Source of cases: Men &#60; 70 years of age registered with prostate cancer at the population-based cancer registry, Eastern Cancer Registration and Information Centre, East Anglia, UK. Source of controls: Men attending general practice in East Anglia with no known prostate cancer diagnosis, frequency matched to cases by age and geographic region SNP_Prostate_Ghent: Hospital-based, Retrospective, Observational. Source of cases: Men treated with IMRT as primary or postoperative treatment for prostate cancer at the Ghent University Hospital between 2000 and 2010. Source of controls: Employees of the University hospital and members of social activity clubs, without a history of any cancer. SPAG: Hospital-based, Retrospective, Observational. Source of cases: Guernsey. Source of controls: Guernsey STHM2: Population-based, Retrospective, Observational. Source of cases: Cases were selected among men referred for PSA testing in laboratories in Stockholm County, Sweden, between 2010 and 2012. Source of controls: Controls were selected among men referred for PSA testing in laboratories in Stockholm County, Sweden, between 2010 and 2012. PCPT: Case-control from a randomized clinical trial. Source of cases: Randomized clinical trial. Source of controls: Randomized clinical trial SELECT: Case-cohort from a randomized clinical trial. Source of cases: Randomized clinical trial. Source of controls: Randomized clinical trial TAMPERE: Case-control - Finland, Retrospective, Observational, Population-based. Source of cases: Identified through linkage to the Finnish Cancer Registry and patient records; and the Finnish arm of the ERSPC study. Source of controls: Cohort participants without a diagnosis of cancer UGANDA: Uganda Prostate Cancer Study: Uganda is a case-control study of prostate cancer in Kampala Uganda that was initiated in 2011. Men with prostate cancer were enrolled from the Urology unit at Mulago Hospital and men without prostate cancer (i.e. controls) were enrolled from other clinics (i.e. surgery) at the hospital. UKGPCS: ICR, UK. Source of cases: Cases identified through clinics at the Royal Marsden hospital and nationwide NCRN hospitals. Source of controls: Ken Muir&#39;s control- 2000 ULM: Case-control - Germany. Source of cases: familial cases (n=162): identified through questionnaires for family history by collaborating urologists all over Germany; sporadic cases (n=308): prostatectomy series performed in the Clinic of Urology Ulm between 2012 and 2014. Source of controls: age-matched controls (n=188): age-matched men without prostate cancer and negative family history collected in hospitals of Ulm WUGS/WUPCS: Cases Series, USA. Source of cases: Identified through clinics at Washington University in St. Louis. Source of controls: Men diagnosed and managed with prostate cancer in University based clinic. Acknowledgement Statements: Aarhus: This study was supported by the Danish Strategic Research Council (now Innovation Fund Denmark) and the Danish Cancer Society. The Danish Cancer Biobank (DCB) is acknowledged for biological material. AHS: This work was supported by the Intramural Research Program of the NIH, National Cancer Institute, Division of Cancer Epidemiology and Genetics (Z01CP010119). ATBC: This research was supported in part by the Intramural Research Program of the NIH and the National Cancer Institute. Additionally, this research was supported by U.S. Public Health Service contracts N01-CN-45165, N01-RC-45035, N01-RC-37004, HHSN261201000006C, and HHSN261201500005C from the National Cancer Institute, Department of Health and Human Services. BioVu: The dataset(s) used for the analyses described were obtained from Vanderbilt University Medical Center&#39;s BioVU which is supported by institutional funding and by the National Center for Research Resources, Grant UL1 RR024975-01 (which is now at the National Center for Advancing Translational Sciences, Grant 2 UL1 TR000445-06). Canary PASS: PASS was supported by Canary Foundation and the National Cancer Institute&#39;s Early Detection Research Network (U01 CA086402) CCI: This work was awarded by Prostate Cancer Canada and is proudly funded by the Movember Foundation - Grant # D2013-36.The CCI group would like to thank David Murray, Razmik Mirzayans, and April Scott for their contribution to this work. CerePP French Prostate Cancer Case-Control Study (ProGene): None reported COH: SLN is partially supported by the Morris and Horowitz Families Endowed Professorship COSM: The Swedish Research Council, the Swedish Cancer Foundation CPCS1 &#38; CPCS2: Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev Ringvej 75, DK-2730 Herlev, DenmarkCPCS1 would like to thank the participants and staff of the Copenhagen General Population Study for their important contributions. CPDR: Uniformed Services University for the Health Sciences HU0001-10-2-0002 (PI: David G. McLeod, MD) CPS-II: The American Cancer Society funds the creation, maintenance, and updating of the Cancer Prevention Study II cohort. CPS-II thanks the participants and Study Management Group for their invaluable contributions to this research. We would also like to acknowledge the contribution to this study from central cancer registries supported through the Centers for Disease Control and Prevention National Program of Cancer Registries, and cancer registries supported by the National Cancer Institute Surveillance Epidemiology and End Results program. EPIC: The coordination of EPIC is financially supported by the European Commission (DG-SANCO) and the International Agency for Research on Cancer. The national cohorts are supported by the Danish Cancer Society (Denmark); the Deutsche Krebshilfe, Deutsches Krebsforschungszentrum and Federal Ministry of Education and Research (Germany); the Hellenic Health Foundation, Greek Ministry of Health; Greek Ministry of Education (Greece); the Italian Association for Research on Cancer (AIRC) and National Research Council (Italy); the Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF); the Statistics Netherlands (The Netherlands); the Health Research Fund (FIS), Regional Governments of Andaluc&#237;a, Asturias, Basque Country, Murcia and Navarra, Spanish Ministry of Health ISCIII RETIC (RD06/0020), Red de Centros RCESP, C03/09 (Spain); the Swedish Cancer Society, Swedish Scientific Council and Regional Government of Sk&#229;ne and V&#228;sterbotten, Fundacion Federico SA (Sweden); the Cancer Research UK, Medical Research Council (United Kingdom). EPICAP: The EPICAP study was supported by grants from Ligue Nationale Contre le Cancer, Ligue d&#233;partementale du Val de Marne; Fondation de France; Agence Nationale de s&#233;curit&#233; sanitaire de l&#39;alimentation, de l&#39;environnement et du travail (ANSES). The EPICAP study group would like to thank all urologists, Antoinette Anger and Hasina Randrianasolo (study monitors), Anne-Laure Astolfi, Coline Bernard, Oriane Noyer, Marie-H&#233;l&#232;ne De Campo, Sandrine Margaroline, Louise N&#39;Diaye, and Sabine Perrier-Bonnet (Clinical Research nurses). ERSPC: This study was supported by the DutchCancerSociety (KWF94-869,98-1657,2002-277,2006-3518, 2010-4800), The Netherlands Organisation for Health Research and Development (ZonMW-002822820, 22000106, 50-50110-98-311, 62300035), The Dutch Cancer Research Foundation (SWOP), and an unconditional grant from Beckman-Coulter-HybritechInc. ESTHER: The ESTHER study was supported by a grant from the Baden W&#252;rttemberg Ministry of Science, Research and Arts. The ESTHER group would like to thank Hartwig Ziegler, Sonja Wolf, Volker Hermann, Heiko M&#252;ller, Karina Dieffenbach, Katja Butterbach for valuable contributions to the study. FHCRC: The FHCRC studies were supported by grants R01-CA056678, R01-CA082664, and R01-CA092579 from the US National Cancer Institute, National Institutes of Health, with additional support from the Fred Hutchinson Cancer Research Center. FHCRC would like to thank all the men who participated in these studies. Gene-PARE: The Gene-PARE study was supported by grants 1R01CA134444 from the U.S. National Institutes of Health, PC074201 and W81XWH-15-1-0680 from the Prostate Cancer Research Program of the Department of Defense and RSGT-05-200-01-CCE from the American Cancer Society. Hamburg-Zagreb: None reported HPFS: The Health Professionals Follow-up Study was supported by grants UM1CA167552, CA133891, CA141298, and P01CA055075. HPFS are grateful to the participants and staff of the Physicians&#39; Health Study and Health Professionals Follow-Up Study for their valuable contributions, as well as the following state cancer registries for their help: AL, AZ, AR, CA, CO, CT, DE, FL, GA, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, and WY. IMPACT: The IMPACT study was funded by The Ronald and Rita McAulay Foundation, CR-UK Project grant (C5047/A1232), Cancer Australia, AICR Netherlands A10-0227, Cancer Australia and Cancer Council Tasmania, NIHR, EU Framework 6, Cancer Councils of Victoria and South Australia, and Philanthropic donation to Northshore University Health System. We acknowledge support from the National Institute for Health Research (NIHR) to the Biomedical Research Centre at The Institute of Cancer Research and Royal Marsden Foundation NHS Trust. IMPACT acknowledges the IMPACT study steering committee, collaborating centres, and participants. IPO-Porto: The IPO-Porto study was funded by Funda&#231;&#228;o para a Ci&#234;ncia e a Tecnologia (FCT; UID/DTP/00776/2013 and PTDC/DTP-PIC/1308/2014) and by IPO-Porto Research Center (CI-IPOP-16-2012 and CI-IPOP-24-2015). MC and MPS are research fellows from Liga Portuguesa Contra o Cancro, N&#250;cleo Regional do Norte. SM is a research fellow from FCT (SFRH/BD/71397/2010). IPO-Porto would like to express our gratitude to all patients and families who have participated in this study. Karuprostate: The Karuprostate study was supported by the the Frech National Health Directorate and by the Association pour la Recherche sur les Tumeurs de la ProstateKarusprostate thanks S&#233;verine Ferdinand. KULEUVEN: F.C. and S.J. are holders of grants from FWO Vlaanderen (G.0684.12N and G.0830.13N), the Belgian federal government (National Cancer Plan KPC_29_023), and a Concerted Research Action of the KU Leuven (GOA/15/017). TVDB is holder of a doctoral fellowship of the FWO. LAAPC: This study was funded by grant R01CA84979 (to S.A. Ingles) from the National Cancer Institute, National Institutes of Health. Malaysia: The study was funded by the University Malaya High Impact Research Grant (HIR/MOHE/MED/35). Malaysia thanks all associates in the Urology Unit, University of Malaya, Cancer Research Initiatives Foundation (CARIF) and the Malaysian Men&#39;s Health Initiative (MMHI). MCCS: MCCS cohort recruitment was funded by VicHealth and Cancer Council Victoria. The MCCS was further supported by Australian NHMRC grants 209057, 251553, and 504711, and by infrastructure provided by Cancer Council Victoria. Cases and their vital status were ascertained through the Victorian Cancer Registry (VCR) and the Australian Institute of Health and Welfare (AIHW), including the National Death Index and the Australian Cancer Database. MCC-Spain: The study was partially funded by the Accion Transversal del Cancer, approved on the Spanish Ministry Council on the 11th October 2007, by the Instituto de Salud Carlos III-FEDER (PI08/1770, PI09/00773-Cantabria, PI11/01889-FEDER, PI12/00265, PI12/01270, and PI12/00715), by the Fundaci&#243;n Marqu&#233;s de Valdecilla (API 10/09), by the Spanish Association Against Cancer (AECC) Scientific Foundation and by the Catalan Government DURSI grant 2009SGR1489. Samples: Biological samples were stored at the Parc de Salut MAR Biobank (MARBiobanc; Barcelona) which is supported by Instituto de Salud Carlos III FEDER (RD09/0076/00036). Also sample collection was supported by the Xarxa de Bancs de Tumors de Catalunya sponsored by Pla Director d&#39;Oncologia de Catalunya (XBTC). MCC-Spain acknowledges the contribution from Esther Gracia-Lavedan in preparing the data. We thank all the subjects who participated in the study and all MCC-Spain collaborators. MD Anderson: Prostate Cancer Case-Control Studies at MD Anderson (MDA) supported by grants CA68578, ES007784, DAMD W81XWH-07-1-0645, and CA140388. MDACC_AS: None reported MEC: Funding provided by NIH grant U19CA148537 and grant U01CA164973. MIAMI (WFPCS): ACS MOFFITT: The Moffitt group was supported by the US National Cancer Institute (R01CA128813, PI: J.Y. Park). NMHS: Funding for the Nashville Men&#39;s Health Study (NMHS) was provided by the National Institutes of Health Grant numbers: RO1CA121060. PCaP only data: The North Carolina - Louisiana Prostate Cancer Project (PCaP) is carried out as a collaborative study supported by the Department of Defense contract DAMD 17-03-2-0052. For HCaP-NC follow-up data: The Health Care Access and Prostate Cancer Treatment in North Carolina (HCaP-NC) study is carried out as a collaborative study supported by the American Cancer Society award RSGT-08-008-01-CPHPS. For studies using both PCaP and HCaP-NC follow-up data please use: The North Carolina - Louisiana Prostate Cancer Project (PCaP) and the Health Care Access and Prostate Cancer Treatment in North Carolina (HCaP-NC) study are carried out as collaborative studies supported by the Department of Defense contract DAMD 17-03-2-0052 and the American Cancer Society award RSGT-08-008-01-CPHPS, respectively. For any PCaP data, please include: The authors thank the staff, advisory committees and research subjects participating in the PCaP study for their important contributions. For studies using PCaP DNA/genotyping data, please include: We would like to acknowledge the UNC BioSpecimen Facility and LSUHSC Pathology Lab for our DNA extractions, blood processing, storage and sample disbursement (https://genome.unc.edu/bsp). For studies using PCaP tissue, please include: We would like to acknowledge the RPCI Department of Urology Tissue Microarray and Immunoanalysis Core for our tissue processing, storage and sample disbursement. For studies using HCaP-NC follow-up data, please use: The Health Care Access and Prostate Cancer Treatment in North Carolina (HCaP-NC) study is carried out as a collaborative study supported by the American Cancer Society award RSGT-08-008-01-CPHPS. The authors thank the staff, advisory committees and research subjects participating in the HCaP-NC study for their important contributions. For studies that use both PCaP and HCaP-NC, please use: The authors thank the staff, advisory committees and research subjects participating in the PCaP and HCaP-NC studies for their important contributions. PCMUS: The PCMUS study was supported by the Bulgarian National Science Fund, Ministry of Education and Science (contract DOO-119/2009; DUNK01/2-2009; DFNI-B01/28/2012) with additional support from the Science Fund of Medical University - Sofia (contract 51/2009; 8I/2009; 28/2010). PHS: The Physicians&#39; Health Study was supported by grants CA34944, CA40360, CA097193, HL26490, and HL34595. PHS members are grateful to the participants and staff of the Physicians&#39; Health Study and Health Professionals Follow-Up Study for their valuable contributions, as well as the following state cancer registries for their help: AL, AZ, AR, CA, CO, CT, DE, FL, GA, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, and WY. PLCO: This PLCO study was supported by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHPLCO thanks Drs. Christine Berg and Philip Prorok, Division of Cancer Prevention at the National Cancer Institute, the screening center investigators and staff of the PLCO Cancer Screening Trial for their contributions to the PLCO Cancer Screening Trial. We thank Mr. Thomas Riley, Mr. Craig Williams, Mr. Matthew Moore, and Ms. Shannon Merkle at Information Management Services, Inc., for their management of the data and Ms. Barbara O&#39;Brien and staff at Westat, Inc. for their contributions to the PLCO Cancer Screening Trial. We also thank the PLCO study participants for their contributions to making this study possible. Poland: None reported PROCAP: PROCAP was supported by the Swedish Cancer Foundation (08-708, 09-0677). PROCAP thanks and acknowledges all of the participants in the PROCAP study. We thank Carin Cavalli-Bj&#246;rkman and Ami R&#246;nnberg Karlsson for their dedicated work in the collection of data. Michael Broms is acknowledged for his skilful work with the databases. KI Biobank is acknowledged for handling the samples and for DNA extraction. We acknowledge The NPCR steering group: P&#228;r Stattin (chair), Anders Widmark, Stefan Karlsson, Magnus T&#246;rnblom, Jan Adolfsson, Anna Bill-Axelson, Ove Andr&#233;n, David Robinson, Bill Pettersson, Jonas Hugosson, Jan-Erik Damber, Ola Bratt, G&#246;ran Ahlgren, Lars Egevad, and Roy Ehrnstr&#246;m. PROGReSS: The PROGReSS study is founded by grants from the Spanish Ministry of Health (INT15/00070; INT16/00154; FIS PI10/00164, FIS PI13/02030; FIS PI16/00046); the Spanish Ministry of Economy and Competitiveness (PTA2014-10228-I), and Fondo Europeo de Desarrollo Regional (FEDER 2007-2013). ProMPT: Founded by CRUK, NIHR, MRC, Cambride Biomedical Research Centre ProtecT: Founded by NIHR. ProtecT and ProMPT would like to acknowledge the support of The University of Cambridge, Cancer Research UK. Cancer Research UK grants (C8197/A10123) and (C8197/A10865) supported the genotyping team. We would also like to acknowledge the support of the National Institute for Health Research which funds the Cambridge Bio-medical Research Centre, Cambridge, UK. We would also like to acknowledge the support of the National Cancer Research Prostate Cancer: Mechanisms of Progression and Treatment (PROMPT) collaborative (grant code G0500966/75466) which has funded tissue and urine collections in Cambridge. We are grateful to staff at the Welcome Trust Clinical Research Facility, Addenbrooke&#39;s Clinical Research Centre, Cambridge, UK for their help in conducting the ProtecT study. We also acknowledge the support of the NIHR Cambridge Biomedical Research Centre, the DOH HTA (ProtecT grant), and the NCRI/MRC (ProMPT grant) for help with the bio-repository. The UK Department of Health funded the ProtecT study through the NIHR Health Technology Assessment Programme (projects 96/20/06, 96/20/99). The ProtecT trial and its linked ProMPT and CAP (Comparison Arm for ProtecT) studies are supported by Department of Health, England; Cancer Research UK grant number C522/A8649, Medical Research Council of England grant number G0500966, ID 75466, and The NCRI, UK. The epidemiological data for ProtecT were generated though funding from the Southwest National Health Service Research and Development. DNA extraction in ProtecT was supported by USA Dept of Defense award W81XWH-04-1-0280, Yorkshire Cancer Research and Cancer Research UK. The authors would like to acknowledge the contribution of all members of the ProtecT study research group. The views and opinions expressed therein are those of the authors and do not necessarily reflect those of the Department of Health of England. The bio-repository from ProtecT is supported by the NCRI (ProMPT) Prostate Cancer Collaborative and the Cambridge BMRC grant from NIHR. We thank the National Institute for Health Research, Hutchison Whampoa Limited, the Human Research Tissue Bank (Addenbrooke&#39;s Hospital), and Cancer Research UK. PROtEuS: PROtEuS was supported financially through grants from the Canadian Cancer Society (13149, 19500, 19864, 19865) and the Cancer Research Society, in partnership with the Minist&#232;re de l&#39;enseignement sup&#233;rieur, de la recherche, de la science et de la technologie du Qu&#233;bec, and the Fonds de la recherche du Qu&#233;bec - Sant&#233;.PROtEuS would like to thank its collaborators and research personnel, and the urologists involved in subjects recruitment. We also wish to acknowledge the special contribution made by Ann Hsing and Anand Chokkalingam to the conception of the genetic component of PROtEuS. QLD: The QLD research is supported by The National Health and Medical Research Council (NHMRC) Australia Project Grants (390130, 1009458) and NHMRC Career Development Fellowship and Cancer Australia PdCCRS funding to J Batra. The QLD team would like to acknowledge and sincerely thank the urologists, pathologists, data managers and patient participants who have generously and altruistically supported the QLD cohort. RAPPER: RAPPER is funded by Cancer Research UK (C1094/A11728; C1094/A18504) and Experimental Cancer Medicine Centre funding (C1467/A7286). The RAPPER group thank Rebecca Elliott for project management. SABOR: The SABOR research is supported by NIH/NCI Early Detection Research Network, grant U01 CA0866402-12. Also supported by the Cancer Center Support Grant to the Cancer Therapy and Research Center from the National Cancer Institute (US) P30 CA054174. SCCS: SCCS is funded by NIH grant R01 CA092447, and SCCS sample preparation was conducted at the Epidemiology Biospecimen Core Lab that is supported in part by the Vanderbilt-Ingram Cancer Center (P30 CA68485). Data on SCCS cancer cases used in this publication were provided by the Alabama Statewide Cancer Registry; Kentucky Cancer Registry, Lexington, KY; Tennessee Department of Health, Office of Cancer Surveillance; Florida Cancer Data System; North Carolina Central Cancer Registry, North Carolina Division of Public Health; Georgia Comprehensive Cancer Registry; Louisiana Tumor Registry; Mississippi Cancer Registry; South Carolina Central Cancer Registry; Virginia Department of Health, Virginia Cancer Registry; Arkansas Department of Health, Cancer Registry, 4815 W. Markham, Little Rock, AR 72205. The Arkansas Central Cancer Registry is fully funded by a grant from National Program of Cancer Registries, Centers for Disease Control and Prevention (CDC). Data on SCCS cancer cases from Mississippi were collected by the Mississippi Cancer Registry which participates in the National Program of Cancer Registries (NPCR) of the Centers for Disease Control and Prevention (CDC). The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the CDC or the Mississippi Cancer Registry. SCPCS: SCPCS is funded by CDC grant S1135-19/19, and SCPCS sample preparation was conducted at the Epidemiology Biospecimen Core Lab that is supported in part by the Vanderbilt-Ingram Cancer Center (P30 CA68485). SEARCH: SEARCH is funded by a program grant from Cancer Research UK (C490/A10124) and supported by the UK National Institute for Health Research Biomedical Research Centre at the University of Cambridge. SNP_Prostate_Ghent: The study was supported by the National Cancer Plan, financed by the Federal Office of Health and Social Affairs, Belgium. SPAG: Wessex Medical ResearchHope for Guernsey, MUG, HSSD, MSG, Roger Allsopp STHM2: STHM2 was supported by grants from The Strategic Research Programme on Cancer (StratCan), Karolinska Institutet; the Linn&#233; Centre for Breast and Prostate Cancer (CRISP, number 70867901), Karolinska Institutet; The Swedish Research Council (number K2010-70X-20430-04-3) and The Swedish Cancer Society (numbers 11-0287 and 11-0624); Stiftelsen Johanna Hagstrand och Sigfrid Linn&#233;rs minne; Swedish Council for Working Life and Social Research (FAS), number 2012-0073STHM2 acknowledges the Karolinska University Laboratory, Aleris Medilab, Unilabs and the Regional Prostate Cancer Registry for performing analyses and help to retrieve data. Carin Cavalli-Bj&#246;rkman and Britt-Marie Hune for their enthusiastic work as research nurses. Astrid Bj&#246;rklund for skilful data management. We wish to thank the BBMRI.se biobank facility at Karolinska Institutet for biobank services. PCPT &#38; SELECT are funded by Public Health Service grants U10CA37429 and 5UM1CA182883 from the National Cancer Institute. SWOG and SELECT thank the site investigators and staff and, most importantly, the participants who donated their time to this trial. TAMPERE: The Tampere (Finland) study was supported by the Academy of Finland (251074), The Finnish Cancer Organisations, Sigrid Juselius Foundation, and the Competitive Research Funding of the Tampere University Hospital (X51003). The PSA screening samples were collected by the Finnish part of ERSPC (European Study of Screening for Prostate Cancer). TAMPERE would like to thank Riina Liikanen, Liisa Maeaettaenen and Kirsi Talala for their work on samples and databases. UGANDA: None reported UKGPCS: UKGPCS would also like to thank the following for funding support: The Institute of Cancer Research and The Everyman Campaign, The Prostate Cancer Research Foundation, Prostate Research Campaign UK (now Prostate Action), The Orchid Cancer Appeal, The National Cancer Research Network UK, The National Cancer Research Institute (NCRI) UK. We are grateful for support of NIHR funding to the NIHR Biomedical Research Centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust. UKGPCS should also like to acknowledge the NCRN nurses, data managers, and consultants for their work in the UKGPCS study. UKGPCS would like to thank all urologists and other persons involved in the planning, coordination, and data collection of the study. ULM: The Ulm group received funds from the German Cancer Aid (Deutsche Krebshilfe). WUGS/WUPCS: WUGS would like to thank the following for funding support: The Anthony DeNovi Fund, the Donald C. McGraw Foundation, and the St. Louis Men&#39;s Group Against Cancer.

  Study phs001391

• CIDR: Collaborative Study on the Genetics of Alcoholism Case Control Study

  This is a case-control study of alcoholism, in which the subjects have been drawn from the Collaborative Study on the Genetics of Alcoholism (COGA), a large, ongoing family-based study that includes subjects from seven sites around the US. COGA has gathered detailed, standardized data on study participants, including diagnostic and neurophysiological assessments. This sample has already proved successful in identifying several genes that influence the risk for alcoholism and neurophysiological endophenotypes, which have been independently replicated. COGA data were included as part of two Genetic Analysis Workshops, and the phenotypes are familiar to the genetics community. Alcoholic probands were recruited from treatment facilities, assessed by personal interview, and after securing permission, other family members were also assessed. A set of comparison families was drawn from the same communities as the families recruited through an alcoholic proband. Assessment involved a detailed personal interview developed for this project, the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA), which gathers detailed information on alcoholism related symptoms along with other drugs and psychiatric symptoms. Many participants also came to the laboratories for electroencephalographic studies. Neurophysiological features that have been shown to be useful endophenotypes for which we have linkage and in some cases association results are included on a subset of the case-control sample: the beta power of the resting electroencephalogram (EEG), the P3(00) amplitude of the visual event-related potential (ERP), and the theta and delta event-related oscillations (EROs) underlying the P3 (See Porjesz et al., 2005; Porjesz and Rangaswamy, 2007 for reviews). A brief description of COGA is in Edenberg, H. J. (2002) The Collaborative Study on the Genetics of Alcoholism: an update. Alcohol Res Health 26, 214-218., Bierut, LJ, NL Saccone, JP Rice, A Goate, T Foroud, HJ Edenberg, L Almasy, PM Conneally, R Crowe, V Hesselbrock, T-K Li, JI Nurnberger, Jr, B Porjesz, MA Schuckit, J Tischfield, H Begleiter, and T Reich (2002) Defining alcohol-related phenotypes in humans: The Collaborative Study on the Genetics of Alcoholism. Alcohol Res Health 26, 208-213. Edenberg HJ and Foroud T (2006) The genetics of alcoholism: identifying specific genes through family studies. Addiction Biology 11, 386-396. This case-control sample of biologically unrelated individuals was drawn from COGA subjects. All cases meet DSM-IV criteria for alcohol dependence. Controls are individuals who have consumed alcohol, but did not meet any definition of alcohol dependence or alcohol abuse, nor did they meet any DSM-IIIR or DSM-IV definition of abuse or dependence for other drugs (except nicotine). All cases and controls have undergone identical clinical assessments. Many individuals in this case-control sample have not previously been genotyped. The Collaborative Study on the Genetics of Alcoholism (COGA) has four Co-Principal Investigators: B. Porjesz, V. Hesselbrock, H. Edenberg, L. Bierut. COGA includes nine different centers where data collection, analysis, and storage take place. The nine sites and Principal Investigators and Co-Investigators are: University of Connecticut (V. Hesselbrock); Indiana University (H.J. Edenberg, J. Nurnberger Jr., T. Foroud); University of Iowa (S. Kuperman); SUNY Downstate (B. Porjesz); Washington University in St. Louis (L. Bierut, A. Goate, J. Rice); University of California at San Diego (M. Schuckit); Howard University (R. Taylor); Rutgers University (J. Tischfield); Southwest Foundation (L. Almasy). Q. Max Guo serves as the NIAAA Staff Collaborator. This national collaborative study is supported by the NIH Grant U10AA008401 from the National Institute on Alcohol Abuse and Alcoholism (NIAAA) and the National Institute on Drug Abuse (NIDA). Funding support for genotyping, which was performed at the Johns Hopkins University Center for Inherited Disease Research, was provided by the National Institute on Alcohol Abuse and Alcoholism, the NIH GEI (U01HG004438),and the NIH contract "High throughput genotyping for studying the genetic contributions to human disease" (HHSN268200782096C). COGA has over 250 publications listed at www.niaaagenetics.org

  Study phs000125

• T2D-GENES Project 2: San Antonio Mexican American Family Studies

  The Type 2 Diabetes (T2D) Genetic Exploration by Next-generation sequencing in Ethnic Samples (T2D-GENES) Consortium is a collaborative international effort to identify genes influencing susceptibility to T2D in multiple ethnic groups using next generation sequencing. T2D-GENES Project 2 is a complex pedigree-based study designed to identify low frequency or rare variants influencing susceptibility to T2D, using whole genome sequence (WGS) information from 1,043 individuals in 20 Mexican American T2D-enriched pedigrees from San Antonio, Texas. The major objectives of this study are to identify low frequency or rare variants in and around known common variant signals for T2D, as well as to find novel low frequency or rare variants influencing susceptibility to T2D. The sampled individuals are obtained from two studies: the San Antonio Family Heart Study (SAFHS) and the San Antonio Family Diabetes/Gallbladder Study (SAFDGS), collectively referred to as the San Antonio Mexican American Family Studies (SAMAFS). The strategy is to sequence approximately 600 individuals at an average of 50x coverage across the entire genome, then impute genome wide genotypes for about 440 additional family members. The 600 sequenced individuals are specifically chosen for their value in imputing sequence information into other family members. By studying large pedigrees, we expect to find multiple individuals carrying each genetic variant, even if this variant is very rare in the population at large. Thus, a pedigree-based approach provides an excellent opportunity for identifying rare novel variants influencing risk of T2D and quantitative variation in T2D-related phenotypes. The whole genome sequencing has been done commercially by Complete Genomics, Inc. (CGI). The final data set includes whole genome sequence data for 607 individuals. After quality control, 585 sequenced individuals provide data for family based imputation, using Merlin linkage analysis software, into approximately 440 additional family members for whom chip based genotypes are available to indicate which parental haplotype is transmitted. Extensive phenotype data is provided for 1048 individuals. These include 5 sequenced individuals who do not belong to any of the 20 large pedigrees. Phenotype information was collected between 1991 and 2011 in the two contributing longitudinal studies. SAFHS participants may have information from up to 5 visits, and SAFDGS participants may have up to 4 visits. The clinical variables reported are coordinated with T2D-GENES Project 1 (multi-ethnic exome sequencing) and include T2D status and age at diagnosis, glycemic traits (fasting and 2 hour glucose and insulin), blood pressure, blood lipids (total cholesterol, HDL cholesterol, calculated LDL cholesterol and triglycerides), clinical chemistry (cystatin c, glutamic acid decarboxylase antibody titer (GadAb), creatinine, adiponectin and leptin). Glycated hemoglobin (HbA1c) was not measured for these individuals and insulin C-peptide is not included in this data set. Additional phenotype data include the medication status at each visit, classified in four categories as any current use of diabetes, hypertension or lipid-lowering medications, and, for females, current use of female hormones. Anthropometric measurements include age, sex, height, weight, hip circumference, waist circumference and derived ratios. Each phenotype variable has an initial summary column containing the most recent non-missing measurement for each individual, followed by the five potential time points for each individual, the number of non-missing measurements, and the age and year for the most recent non-missing measurement. For historical reasons, the order in which variables are presented on the dbGaP web site differs from their order in the data download file. When reading the comment fields for each variable, please note that commas are omitted to support data exchange in .csv format.

  Study phs000462

• Natural Killer Cell Therapies for Hematologic Malignancies

  The "Natural Killer Cell Therapies for Hematologic Malignancies" study is an umbrella repository for data pertaining to multiple related clinical trials that aim to assess NK cell therapies as part of treatment strategies for a range of hematologic malignancies. Here, data from two trials, NCT03068819 and NCT02782546, are presented.Cytokine Induced Memory-like NK Cell Adoptive Therapy for Relapsed AML after Allogeneic Hematopoietic Cell Transplant in Children and Adults (NCT03068819)Pediatric and young adult (YA) patients with acute myeloid leukemia (AML) who relapse after allogeneic hematopoietic cell transplantation (HCT) have extremely poor prognosis. Standard salvage chemotherapy and donor lymphocyte infusions (DLI) have little curative potential. Previous studies showed that natural killer (NK) cells can be stimulated ex vivo with interleukin-12 (IL-12), IL-15, and IL-18 to generate memory-like (ML) NK cells with enhanced anti-leukemia responses. We treated nine pediatric/YA patients with post-HCT relapsed AML with donor ML NK cells on a phase I trial. Patients received fludarabine, cytarabine, and filgrastim followed two weeks later by infusion of DLI and ML NK cells from the original HCT donor. ML NK cells were successfully generated from haploidentical, matched-related and matched-unrelated donors. Following infusion, donor-derived ML NK cells expanded and maintained ML multidimensional mass cytometry phenotype for over 3 months. Furthermore, ML NK cells exhibited persistent functional responses as evidenced by leukemia-triggered IFN-gamma production. Following DLI and ML NK cell adoptive transfer, 4 of 8 evaluable patients achieved complete remission at day 28. Two patients maintained a durable remission for over 3 months with one patient in remission for greater than two years. No significant toxicity was experienced. This study demonstrates that in a compatible immune environment post-HCT, donor ML NK cells robustly expand and persist with potent anti-leukemic activity in the absence of exogenous cytokines. ML NK cells in combination with DLI present a novel immunotherapy platform for AML that has relapsed after allogeneic HCT. This trial was registered at https://www.clinicaltrials.gov/study/NCT03068819.A Phase II Study of Cytokine Induced Memory-like NK Cell Adoptive Therapy after Haploidentical Donor Hematopoietic Cell Transplantation (NCT02782546)Natural killer (NK) cells are innate lymphoid cells that eliminate cancer cells, produce cytokines, and are being investigated as a nascent cellular immunotherapy. Impaired NK cell function, expansion, and persistence remain key challenges for optimal clinical translation. One promising strategy to overcome these challenges is cytokine-induced memory-like (ML) differentiation, whereby NK cells acquire enhanced anti-tumor function following stimulation with IL-12, IL-15, and IL-18. Here, reduced-intensity conditioning (RIC) for HLA-haploidentical hematopoietic cell transplantation (HCT) was augmented with same-donor ML NK cells on Day 7 and 3 weeks of N-803 (IL-15 superagonist) to treat patients with relapsed/refractory acute myeloid leukemia (AML) in the clinical trial (NCT02782546). In 15 patients, donor ML NK cells were well-tolerated and 87% of patients achieved a composite complete response at Day 28, which corresponded with clearing high-risk mutations, including TP53 variants. NK cells were the major blood lymphocytes for two months post-HCT with prolific expansion (1104-fold) over 1-2 weeks. Multidimensional mass cytometry and CITE-seq identified donor ML NK cells as distinct from conventional NK cells and persisting for over two months. ML NK cells expressed CD16, CD57, and high granzyme B and perforin, along with a unique transcription factor profile. ML NK cells differentiated in patients had enhanced ex vivo function compared to conventional NK cells from both patient and healthy donors. Overall, same-donor ML NK cell therapy with 3 weeks of N-803 support safely augmented RIC haplo-HCT for AML, with ML NK cells demonstrating enhanced in vivo persistence and functionality, overcoming barriers in the field.

  Study phs002681

• Resuscitation Outcomes Consortium (ROC) Amiodarone, Lidocaine or Neither for Out-Of-Hospital Cardiac Arrest Due to Ventricular Fibrillation or Ventricular Tachycardia (ALPS)(ROC-ALPS-BioLINCC)

  Accessing Data Please refer to &#8220;Authorized Access&#8221; below regarding accessing data through the BioData Catalyst ecosystem. The data from this accession is not available for download through dbGaP. Objective To compare the effects of amiodarone, lidocaine, and placebo on survival to hospital discharge after out-of-hospital cardiac arrest due to shock-refractory ventricular fibrillation or pulseless ventricular tachycardia. Background Ventricular fibrillation (VF) or pulseless ventricular tachycardia (VT) are common causes of out-of-hospital cardiac arrest, but are considered the most responsive to shock and therefore the most treatable. Nonetheless, most defibrillation attempts do not result in sustained return of spontaneous circulation, and VF or VT may persist or recur after shock. There is also evidence that longer durations of VF or VT are associated with decreases in the likelihood of resuscitation. Amiodarone and lidocaine are commonly used to promote successful defibrillation of shock-refractory VF or VT and prevent recurrences. Previous trials have shown amiodarone to be more effective than placebo or lidocaine for return of spontaneous circulation and survival at hospital admittance. This study sought to further extend the research and examine whether amiodarone would improve survival to hospital discharge and neurologic outcomes, as compared to placebo or lidocaine. Participants 3,026 eligible participants were enrolled, with 974 assigned to amiodarone, 993 assigned to lidocaine, and 1,059 assigned to placebo. An additional 1,627 participants that received a study intervention, but did not meet eligibility criteria, were included in analysis of the intention-to-treat population. Design The study interventions (amiodarone, lidocaine, and saline) were packaged in indistinguishable sealed kits and randomly distributed in to Emergency Medical Services (EMS) providers in a 1:1:1 ratio, stratified by participating site and agency. Each kit contained three syringes, and each syringe held 3 ml of colorless fluid containing 150 mg of amiodarone, 60 mg of lidocaine, or normal saline. Participants with out-of-hospital cardiac arrest were treated in accordance with local EMS protocols, in compliance with American Heart Association (AHA) guidelines. If VF or VT persisted or recurred after one or more shocks, eligible participants received a vasopressor and the masked kit containing amiodarone, lidocaine, or placebo. Approximating current clinical practice, the initial dose consisted of two syringes administered by rapid bolus. If the estimated body weight of the patient was less than 100 lbs., then one syringe was used. If VF or VT persisted, standard resuscitation measures, additional shocks, and an additional syringe of the study drug were administered. At that point the trial interventions were completed and standard interventions for advanced life support were employed. Upon arrival at the hospital, providers were notified of the patient's enrollment in the trial and encouraged to provide usual care in accordance with AHA guidelines, including open-label amiodarone or lidocaine if necessary. Components of hospital care were monitored but not standardized by the trial protocol. Participants, providers, and trial personnel were blinded to the trial drug assignments, with the exception of treating physicians if emergency un-blinding was required for care. Data from pre-hospital patient care records, CPR process measures, and hospital medical records were collected. The primary outcome of the trial was survival to hospital discharge, and the secondary outcome was survival with favorable neurologic status at discharge, defined as a score on the modified Rankin scale of 3 or less. Conclusions Neither amiodarone nor lidocaine resulted in a significantly higher rate of survival to hospital discharge or favorable neurologic outcome, as compared to placebo, among participants with out-of-hospital cardiac arrest due to initial shock-refractory ventricular fibrillation or pulseless ventricular tachycardia.

  Study phs003784