Search Results - EGA European Genome-Phenome Archive

NHLBI TOPMed: The Genetic Epidemiology of Asthma in Costa Rica

This administrative supplement to the project, "The Genetic Epidemiology of Asthma in Costa Rica" (R37 HL066289) is in response to NOT-HL-14-029 to perform whole genome sequencing (WGS) on existing NHLBI populations. We focus on asthma because of its public health significance. Asthma affects 26 million U.S. children and adults, remains a major cause of morbidity (one-half million hospitalizations a year) and is the most common cause of school and work days lost. Asthma-related costs are estimated to be over $12.7 billion annually. The Asthma Probands for both the extended pedigrees and the trios utilized in this study were selected on the basis of a physician diagnosis of asthma; a history of recurrent asthma attacks or at least 2 respiratory symptoms; and either airway hyperresponsiveness to methacholine or significant response to bronchodilator (Albuterol) administration. These criteria are identical to the criteria used in the Childhood Asthma Management Program (CAMP). The three primary goals of this project are to: (1) identify common and rare genetic variants that determine asthma and its associated phenotypes (height, weight, IgE level, lung function, bronchodilator response, steroid treatment response) through whole genome sequencing (WGS); (2) perform novel family based association analysis of our WGS data to identify novel genes for asthma; and (3) integrate epigenomic and transcriptomic data with our WGS data and determine the epistatic interactions present using systems genomics approaches. Identification of the molecular determinants of asthma remains an important priority in translational science. Genome-wide association studies (GWAS) have been successful in this regard, identifying at least 10 novel susceptibility genes for asthma. However, as with most complex traits, the variants identified by GWAS explain only a fraction of the estimated heritability of this disorder. Herein, we propose a novel family-based study design and state-of-the-art genome sequencing techniques to map a set of sequence variants for asthma and its associated phenotypes and assess the interrelationships of the identified genes and variants using systems genomics methods. We have assembled a team of investigators highly-skilled and expert in whole genome sequencing (Drs. Michael Cho and Benjamin Raby), genetic association analysis (Drs. Scott T. Weiss, Jessica Lasky-Su and Christoph Lange), integrative genomics (Drs. Raby, Kelan Tantisira, Augusto Litonjua and Dawn DeMeo), and systems genomics (Drs. Weiss, Amitabh Sharma, Lange and Raby) to address this important problem with both a novel study design and data set.

Study phs000988

NSIGHT BabySeq Project

The Genomic Sequencing for Childhood Risk and Newborn Illness (BabySeq Project) is a research study exploring the use of genomic sequencing in newborns. The National Institutes of Health is funding this study. Investigators enrolled 240 healthy infants and their parents from the Brigham and Women's Hospital (BWH) Well Newborn Nursery and 240 sick infants and their parents at Boston Children's Hospital (BCH) or the BWH Neonatal Intensive Care Unit (NICU). A small blood sample was taken from each infant and genome sequencing may have been performed. Whole-exome (WES) was performed at the Broad Institute. Six weeks later, the results were returned and explained. Over 12 months, the investigators studied the experiences of parents and pediatricians of infants who receive sequencing to help understand how best to use genomics in pediatric care. Parents were surveyed at four points over the 12 months after enrollment: baseline, immediately post-disclosure (approximately 6 weeks after enrollment), 3 months post-disclosure, and at 10 months post-disclosure. Primary outcome measures included: (1) downstream health care costs attributable to BabySeq Project disclosure measured as days of inpatient care; (2) Parents' distress using validated scales and a novel item assessing blame; (3) parent-child relationship using validated scales; (4) Parents' relationship using validated and novel measures of marital satisfaction; (5-9) downstream health care utilization attributable to BabySeq project disclosure measured as the number of health care provider visits, per-patient counts for number of medications at 10 months, number of emergency room visits, number of outpatient lab tests, and per-patient means for healthcare costs in U.S. dollars. A secondary outcome was whether there was a change in perceived utility toward genomic sequencing. Findings of BabySeq include: (1) interest in newborn genomic testing is high among parents of healthy children and the majority of couples had similar levels of interest; (2) parents reported several motivations to receive and reasons to decline adult-onset only results from newborn sequencing; (3) 88% of newborns had at least one recessive carrier variant that could be relevant to their parents' future reproductive planning; (4) 5% of babies had an atypical pharmacogenomic variant related to how they might process medications used in childhood; (5) parent surveys using validated measures showed no evidence that newborn genomic sequencing caused increased psychological distress, even if the baby had a disease risk identified; and (6) 11% of newborn babies in the study had unanticipated monogenic disease risks.

Study phs002093

Dynamics of genome architecture and chromatin function during human B cell differentiation and neoplastic transformation

Despite recent advances, the dynamics of genome architecture and chromatin function during human cell differentiation and its potential reorganization upon neoplastic transformation remains poorly characterized. Here, we integrate in situ Hi-C and nine additional omic layers to define and biologically characterize the dynamic changes in three-dimensional (3D) genome architecture across normal B cell differentiation and in neoplastic cells from different subtypes of chronic lymphocytic leukemia (CLL) and mantle cell lymphoma (MCL) patients. Beyond conventional active (A) and inactive (B) compartments, an integrative analysis of Hi-C data uncovers a highly-dynamic intermediate compartment enriched in poised and polycomb-repressed chromatin. During B cell development, we detect that 28% of the compartments change at defined maturation stages and mostly involve the intermediate compartment. The transition from naive to germinal center B cells is associated with widespread chromatin activation, which mostly reverts into the naive state upon further maturation of germinal center cells into memory B cells. The analysis of CLL and MCL neoplastic cells points both to entity and subtype-specific alterations in chromosome organization. Remarkably, we observe that large chromatin blocks containing key disease-specific genes alter their 3D genome organization. These include the inactivation of a 2Mb region containing the EBF1 gene in CLL and the activation of a 6.1Mb region containing the SOX11 gene in clinically aggressive MCL. This study indicates that 3D genome interactions are extensively modulated during normal B cell differentiation and that the genome of B cell neoplasias acquires a tumor-specific 3D genome architecture.

Study EGAS00001004763

Histological Transformation and Progression in Follicular Lymphoma: a Clonal Evolution Study

Background: Follicular lymphoma (FL) is an indolent, yet incurable B-cell malignancy. A subset of patients experience increased mortality rate driven by two distinct clinical end points: histological transformation and early progression after immuno-chemotherapy. The nature of tumor clonal dynamics leading to these clinical endpoints is poorly understood and previously determined genetic alterations do not explain the majority of transformed cases or accurately predict early progressive disease. We contend that detailed knowledge of the expansion patterns of specific cell populations plus their associated mutations would provide insight into therapeutic strategies and disease biology over the timecourse of FL clinical histories. Methods and Findings: Using a combination of whole genome sequencing, targeted deep sequencing and digital droplet PCR on matched diagnostic and relapse specimens, we deciphered the constituent clonal populations in n=15 transformation patients and n=6 progressors, and measured their change in abundance over time. We observed widely divergent patterns of clonal dynamics in transformed cases relative to progressed cases. Transformation specimens were generally composed of clones that were rare or absent in diagnostic specimens, consistent with dramatic clonal expansions that came to dominate the transformation specimen. This pattern was independent of time to transformation and treatment modality. By contrast, progression specimens were composed of clones that were already present in the diagnostic specimens and exhibited only moderate clonal dynamics, even in the presence of immuno-chemotherapy. Analysis of somatic mutations impacting 94 genes was undertaken in a validation cohort consisting of 395 samples from 277 patients in order to decipher disrupted biology in the two clinical endpoints. We found 12 genes were more commonly mutated in transformed samples than in preceding FL, including TP53, B2M, CCND3, GNA13, S1PR2 and P2RY8. Moreover, 10 genes were more commonly mutated in diagnostic specimens of early progressors including TP53, BTG1, MKI67 and XBP1. Conclusions: Our results illuminate contrasting modes of evolution shaping the clinical histories of transformation and progression. They have implication for interpretation of evolutionary dynamics in the context of treatment-induced selective pressures, and indicate that transformation and progression will require different clinical management strategies.

Study EGAS00001001709

FEGA FAQs: a summary of the Q+A session from the FEGA workshop at ELIXIR AHM 2024

The ELIXIR All Hands Meeting (AHM) was held in Uppsala, Sweden this June. We at EGA always look forward to this meeting as a chance to see many of our partners and colleagues face-to-face. The Federated EGA (FEGA) is one initiative that always benefits from the AHM, and this year FEGA was in the spotlight, with several questions related to the advances we've made recently. We held this year's FEGA workshop a little differently, with most time for discussions on various “hot topics”. Organised in different breakouts, over 2 rounds, participants could choose which session they wanted to attend. One breakout was a general Q+A about FEGA and the path to join. We had a diverse range of participants, including experts from Central EGA (CEGA) and FEGA inaugural nodes, people from up and coming nodes at various stages of readiness, as well as participants not directly a part of FEGA but curious to learn more. It made for a great discussion! In this blog post, we highlight some of the questions for those who didn’t have a chance to be there. What is the FEGA Collaboration Agreement? It is a legal agreement between the node and Central EGA (CEGA) where both parties agree to certain responsibilities, like what services will be provided, sharing of public metadata with CEGA, interoperable technologies and more. The agreement is for 4 years, with the expectation of long-term sustainability. If a node is made up of multiple institutes, one institute must be the signatory. This could require a legal agreement within the node. CEGA is composed of CRG and EMBL-EBI (EGA itself has its own legal agreement between these institutes) Check the FEGA Collaboration Agreement What about purely medical data? Is this accepted in FEGA? CEGA only accepts data approved for secondary research use. We do accept medical data collected in this context, as do some nodes. Nodes are able to accept any data they like, as long as it is sensitive, thus in need of controlled access. What about other data types other than genomics? Like proteomics or images? They can be accepted, although CEGA is currently not designed with those formats in mind, so they might not fit with precision in the data model. The FEGA nodes are welcome to accept any data they want. Proteomic studies generating sensitive data are increasing, and specific work will likely be developed in the near future to adress this need. Does CEGA require a certain amount or type of data to be shared by the node? No, we do not and it's up to each node to decide what specific data types they accept and in what format. Nonetheless, a FEGA node has the duty to be open to data submission from any institution of their country, and can't be limited by design to a single or limited data source. Does CEGA and FEGA require a certain amount or type of details and description on the data to be submitted to the node? Data description (technical and biological), usually called metadata in this field, is crucial for the findability of the submitted data. Thus, we highly recommend including as much information as available to maximise the discoverability of the data. Specifical minimal metadata is defined in the submission schema, and thresholds are specified by the nodes. We are currently working towards a unified FEGA metadata model. What are the geographical borders of FEGA? FEGA should make the E for Everyone, because any institute worldwide could join and we indeed do have countries and use-cases worldwide. Some of them are very close to officially joining the federation. What are the main differences between FEGA and GDI? The two networks have a lot in common and also some critical differences. You can read all about this in one of our latest blog post. If you have more questions, please consider having a look at the FEGA onboarding webpage and, of course, don't miss our workshop at the ELIXIR AHM next year!

Blog fega-faqs-elixir-ahm-2024

Prevention and Early Treatment of Acute Lung Injury Network - Vitamin D to Improve Outcomes by Leveraging Early Treatment (PETAL VIOLET-BioLINCC)

Data Access NOTE: Please refer to the "Authorized Access" section below regarding accessing data through the BioData Catalyst ecosystem. The data from this accession is not available for download through dbGaP. Biospecimens: Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from PETAL VIOLET include Plasma and Whole Blood. Please note that use of biospecimens in genetic research is subject to a tiered consent. Specimens may not be used to produce commercial products.Objectives: To evaluate the effect of short-term vitamin D supplementation on mortality among critically ill patients with a vitamin D deficiency.Background: Observational data indicate that vitamin D deficiency is common among critically ill patients and constitutes a potentially modifiable risk factor associated with longer lengths of stay in the hospital and intensive care unit (ICU), lung and other organ injury, prolonged mechanical ventilation, and death. In a previous phase 2 trial, vitamin D supplementation administered to vitamin D-deficient, critically ill patients was associated with lower observed mortality than placebo at 28 days and at 6 months. Because of the need for a larger, phase 3 trial, the PETAL-VIOLET study was initiated to determine if early administration of high-dose vitamin D3 would reduce all-cause mortality among critically ill patients with a vitamin D deficiency.Participants: 1360 patients underwent randomization, 690 were assigned to the vitamin D group and 668 were assigned to the placebo group. Of the 1078 patients confirmed to have a vitamin D deficiency by liquid chromatography-tandem mass spectrometry (LC-MS-MS), 538 had been assigned to the vitamin D group and 540 had been assigned to the placebo group.Design: PETAL-VIOLET was a multicenter, double-blind, placebo-controlled, phase 3 trial. Patients were enrolled within 12 hours after the clinician's decision to admit the patient to the ICU from the emergency department, hospital ward, operating room, or outside facility. Patients were tested for vitamin D deficiency, with a threshold of plasma 25-hydroxyvitamin D level of less than 20 ng per milliliter. Patients were randomly assigned in a 1:1 ratio, stratified according to site, to receive either a single enteral (administered orally or through a nasogastric or orogastric tube) dose of 540,000 IU of vitamin D3 or matched placebo, in liquid form, administered within 2 hours after randomization.Conclusions: After the first interim analysis, the data and safety monitoring board recommended that the trial be stopped for futility.A single 540,000 IU enteral dose of vitamin D3 administered early during critical illness rapidly corrected vitamin D deficiency but did not provide an advantage over placebo with respect to mortality or other clinically important end points.

Study phs003879

eMERGE Network's Multi-Center Pilot of Pharmacogenetic Sequencing in Clinical Practice

eMERGE-PGx is a multi-site test of the concept that sequence information can be coupled to electronic medical records (EMRs) for use in healthcare. The promise of personalized medicine - health care guided by each individual's biological characteristics - is being fostered by increasingly powerful and economical methods to acquire clinically relevant biomarkers from large numbers of people. One therapeutic area that seems especially ripe for an early test of the personalized medicine concept is pharmacogenomics (PGx) - the idea that individual variation in drug response includes a genomic component. Drug response variation is an accepted feature of virtually all drug treatments, and contemporary molecular biologic tools continue to identify key genes mediating drug metabolism, transport, and targets. Importantly, common variation in these genes is an increasingly well-recognized contributor, sometimes with large effects, to variation in drug responses. As a result, recommendations for genotype-guided therapy are increasing. These evidence-based recommendations, if implemented in health care practice, could reduce adverse drug events and improve time to therapeutic response. Through eMERGE-PGx, we are developing strategies for the optimal implementation of genetic sequence data into the clinical environment with the ultimate goal of improving patient care. Site and participants include: Children's Hospital of Pennsylvania (CHOP): The Center for Applied Genomics (CAG) at the Children's Hospital of Philadelphia (CHOP) is a high-throughput, highly automated genotyping and sequencing facility equipped with state-of-the-art genotyping and sequencing platforms. Children who are treated at the Children's Hospital Healthcare Network and their parents may be eligible to take part in a major initiative to collect more than 100,000 blood samples, covering a wide range of pediatric diseases. The PGx population selected for sequencing with the PGRNseq panel at CHOP is 1,650 children from CAG's biorepository with well-documented drug-related severe adverse events (SAEs) or EHR-based drug response profiles. SAEs were extracted from EPIC records and from CHOP's Adverse Event (AE) database, which documents every AE at CHOP. These AEs are classified by a medical review panel according to the causal relationship with the suspected drug into 'doubtful', 'possible', and 'probable'. Individuals with events classified as probable, severe and objective, were selected for sequencing. The drugs more frequently associated with adverse events are antibiotics, antineoplastics, immunosuppressants and psychotropic drugs. This cohort constitutes 50% of the target population. The remaining subjects were selected using EHR-based algorithms that we have developed and validated at CAG for identifying patients not responding to ADHD medication (primarily atomoxetine) and patients refractory to antiepileptic treatment from responders. Cincinnati Children's Hospital Medical Center/Boston's Children's Hospital (CCHMC/BCH): 811 CCHMC samples were obtained from children, adolescents or young adults exposed to medication or at risk for needing medication of study interest. 55% of participants were exposed to one or more opioids and their DNA source was a CCHMC study-specific biobank; while 27% of participants were at risk for needing an opioid for surgical pain management and were newly recruited. The remainder of the cohort was exposed to methylphenidate and their DNA samples were obtained from a CCHMC study-specific biobank. The focus of Boston Children's Hospital eMERGE PGx project is on individuals with epilepsy. Samples were taken from a current pharmacogenomics study already in place through which DMET analysis was run and used as confirmation for PGRN-Seq results. A total of 109 samples were sent for PGRN-Seq analysis at University of Washington. The remaining 141 epilepsy samples were from Children's Hospital of Philadelphia and underwent testing with PGRN-Seq at CHOP. Geisinger Health System: A research cohort of adult Geisinger Clinic patients was enrolled from community-based primary care clinics of the Geisinger Health System. Patients were eligible for enrollment if they were a primary care patient of a Geisinger Clinic physician and were scheduled for a non-emergent clinic visit. All data are from Geisinger patients who consent to participate in the MyCode project. MyCode participants agree to provide biological samples for broad research use, including genomic analysis, and for linking of sample data to information in the participant's Geisinger health record. The consent also permits sharing of de-identified data for research purposes. Group Health(GH)/University of Washington (UW): Potential GH participants for the PGx project were enrolled in the eMERGE Network through the Northwest Institute of Genetic Medicine (NWIGM) biorepository, and provided the appropriate consent to receive clinically relevant genetic results (N~6300). Participants were eligible if aged 50 - 65 years old at the time of their enrollment into the NWIGM repository, living, enrolled in GH's integrated group practice, and had completed an online Health Risk Appraisal. The selection algorithm was based on several data sources from the EHR at Group Health: 1. Demographics - participants with self-reported race as Asian or African ancestry were prioritized and selected to enrich for non-European ancestry; 2. Diagnosis and procedure codes - participants were selected if found to have a history of hypertension, atrial fibrillation (AF,) or congestive heart failure (CHF). Participants with a history of arrhythmia were added if the entire selection algorithm did not generate 900 individuals. We also enriched for participants with EHR evidence of actionable indications related to PGRNSeq genes. Participants were selected if found to have an ICD9 code for malignant hyperthermia, hypertension, atrial fibrillation, congestive heart failure or long QT syndrome (LQTS); 3. Laboratory values - if a participant had any laboratory event of creatine kinase (CK) > 1000, and were dispensed statins within 6 months of the event, then they were selected; and 4. Medications - participants were excluded if ever on carbamazepine or had a current regimen of warfarin. Essentia Institute of Rural Health, Marshfield Clinic, Pennsylvania State University (Marshfield): For this study, 750 subjects were selected and enrolled into PGx based on Vanderbilt's algorithm designed to enrich for patients who are most likely to receive one of three common drugs (Clopidogrel, Warfarin or Simvastatin) in the next 2-3 years. These patients were sent a letter of invitation and description of the PGx project. Follow-up phone calls were made, and interested subjects came in for a one time meeting to discuss the project and go through the informed consent with the research coordinator. If they were interested they signed the consent and HIPAA forms and gave blood. Subjects were chosen and enrolled into PGx independently of previous biobank participation. Mayo Clinic: The Right Drug, Right Dose, Right Time - Using Genomic Data to Individualize Treatment (The RIGHT Protocol) enrolled 1013 patients to test the hypothesis that prescribers could deliver genome-guided drug therapy at the point-of-care by using pharmacogenomic data preemptively integrated in the electronic medical record. Complete details regarding the study population have been previously described (Bielinski et al., 2014). Icahn School of Medicine at Mount Sinai School (Mt Sinai): Our study site is the Primary Care Associates (PCA) practice group of the Mount Sinai Faculty Practice Associates (FPA) of the Mount Sinai Medical Center in New York City. This practice has 12 physician providers. All patient encounters are documented and managed with EpicCare ambulatory electronic medical record. Active PCA Patients eligible for enrollment fulfilled the following criteria: a) age 50 or older receiving clinical care at Mount Sinai FPA PCA practice with at least one practice encounter within 18 months prior to commencement of enrollment; b) no history or current use of clopidogrel, warfarin, or simvastatin. Eligible patients were invited to participate through de novo recruitment by letter sent by their provider. Interested patients were screened for eligibility and enrolled to participate in the eMERGE PGX study on site by a dedicated research coordinator. In addition to de novo enrollment from clinical practice, patients of FPA PCA who had previously enrolled in Mount Sinai's BioMe Biobank program AND fulfilled eligibility criteria as stated under a) and b) were identified by chart review and samples sequenced at CIDR using PGRNseq platform (N=300). PGRNseq data from 291 samples passed stringent quality control and are included in the current data set. Furthermore, 56 of these patients carrying known and validated 'actionable' variants affecting prescribing of clopidogrel, warfarin, and/or simvastatin were enrolled in the eMERGE PGX study following invitation through recontacting by the Principal Investigator of the BioMe Program. Northwestern University: Participants for this study were recruited from the General Internal Medicine (GIM) clinic at Northwestern Medical Group (NMG). Patients were selected for invitation to participate if they had been seen a minimum of two times over the last four years, having a high likelihood to receive a prescription for warfarin, Plavix, or a statin, and are seeing a physician who has agreed to allow their patients to be contacted for the study. We utilized an algorithm developed at Vanderbilt and tailored to our population which uses our EHR to estimate the probability that individuals will receive a prescription for warfarin, Plavix, or a statin in the next three years. Participants were sent a letter explaining the study prior to their GIM appointment and offered participation at the time of their visit. Participants were consented on-site and blood drawn after consent was obtained. The GIM clinic consists of 39 primary care physicians who provide approximately 80,000 patient encounters per year. As with any large primary care clinic, a significant proportion of patients in GIM clinic suffer from a variety of chronic health conditions, such as diabetes, hypertension, and coronary artery disease. Over 50,000 individuals have been seen by GIM doctors in the past 5 years; 11,562 of these patients have evidence of a statin prescription in the EHR, 3,436 have evidence of a warfarin prescription, and 1,872 have evidence of a Plavix prescription. Vanderbilt University: The more than 1000 participants enrolled into Vanderbilt's eMERGE PGx study were newly recruited from the Cardiology and Internal Medicine Clinics and the Hillsboro Medical Group within Vanderbilt University Medical Center (VUMC). Patients were selected based on a predictive algorithm estimating the patient's likelihood of receiving Clopidogrel, Warfarin, and/or Simvastatin. The algorithm identifies primarily older middle-aged patients, and the mean age of the study group is 74. The cohort is approximately 45% female with 75% of subjects self-identified as EA and 24% as AA. Subjects were consented in person by study personnel following a routine clinic visit and an introduction to the study staff by their doctor. VUMC is a comprehensive health care facility dedicated to patient care, research, and the education of health care professionals. Translational research into the causes and treatment of disease as well as studying fundamental biological properties is the primary focus of discovery at Vanderbilt. Clinical research is conducted in Vanderbilt University Hospital, the Nashville Veterans Administration Hospital, Meharry General Hospital and in their associated outpatient clinics. These hospitals and clinics, all associated with the Vanderbilt system, each have full time Vanderbilt faculty and medical housestaff and provide clinical care and participate in research programs. The Vanderbilt Clinic is comprised of more than 95 adult outpatient specialty practices and received over 1.5 million ambulatory visits in 2012-13. The Vanderbilt Heart and Vascular Institute offers a comprehensive heart program offering diagnosis, medical treatment, minimally invasive therapies, surgical intervention and disease management, tailored to each individual's unique needs. All programs within the Vanderbilt Clinic have survival figures that surpass the national average.

Study phs000906

The Environmental Determinants of Diabetes in the Young Study (TEDDY)

The Environmental Determinants of Diabetes in the Young (TEDDY) Study investigates genetic and genetic-environmental interactions, including gestational infection or other gestational events, childhood infections and other environmental factors after birth, in relation to the development of pre-diabetic islet autoimmunity and type 1 diabetes (T1D). Beginning in 2002, a consortium of six centers assembled to participate in the development and implementation of studies to identify environmental factors that trigger the development of islet autoimmunity and T1D in genetically susceptible individuals. The TEDDY study screened around 400,000 newborns and recruited 7,749 neonates from the general population with a pre-determined T1D risk of 3% and 919 neonates with first degree relatives who have T1D and who have a pre-determined T1D risk of 10%. Thus, TEDDY proposes to follow over 8,000 participants across six clinical centers worldwide (Finland, Germany, Sweden and three in the United States) until the age of 15. Participants are followed every three months for islet autoantibody measurements with blood sampling until four years of age and then at least every six months until the age of 15. After the age of four, autoantibody positive subjects continue to be followed at 3 month intervals and autoantibody negative subjects are followed at six month intervals. In addition to the analysis of autoantibodies, additional data and sample collection is performed at each visit. The parents collect monthly stool samples in early childhood. The parents also fill out questionnaires at regular intervals in connection with study visits and record information about diet and health status in the child's TEDDY Book between visits. Continued long-term follow-up of the currently active TEDDY participants will provide important scientific information on early childhood diet, reported and measured infections, vaccinations, and psychosocial stressors that may contribute to the development of type 1 diabetes and islet autoimmunity. DNA extracted from the 9-month TEDDY blood sample was used for SNP genotyping. Samples were available for 7,082 participants. SNPs were genotyped by the Center for Public Health Genomics at the University of Virginia, using the Illumina ImmunoChip SNP microarray of around 196,000 SNPs selected from 186 regions associated with 12 autoimmune diseases (including T1D) (Hadley et al., 2015). "Data quality control (QC) steps included eliminating subjects with a low call rate (> 5% SNPs missing) and discrepancies between reported gender and prior genotyping at the HLA laboratory. Secondly, SNPs were removed from analysis due to low call rate, Hardy-Weinberg equilibrium P value < 10-6, except for chromosome 6 due to HLA eligibility requirements)" (Törn et al., 2015). QC resulted in a total of 7,023 subjects with data on 176,586 SNPs. Additional information on the TEDDY study are available in the following articles: The Environmental Determinants of Diabetes in the Young (TEDDY) Study. TEDDY Study Group. Annals of the New York Academy of Science, 2008 and TEDDY - The Environmental Determinants of Diabetes in the Young - An Observational Clinical Trial. Annals of the New York Academy of Science, 2006 Details of the TEDDY protocol can be found in The Environmental Determinants of Diabetes in the Young (TEDDY): Genetic Criteria and International Diabetes Risk Screening of 421,000 infants. Pediatric Diabetes, 2011

Study phs001037

STAMPEED: Northern Finland Birth Cohort 1966 (NFBC1966)

The Northern Finland Birth Cohorts program (NFBC) was initiated in the 1960s in the two northernmost provinces of Finland to study risk factors involved in pre-term birth and intrauterine growth retardation, and the consequences of these early adverse events on subsequent morbidity and mortality. The uniqueness of NBFCs is that the data of the cohorts were obtained from early fetal life (including maternal health during pregnancy) to adulthood. The NFBC1966 includes 12,058 live births to mothers in the two northern-most provinces of Finland. Two decades later, a second cohort of 9432 births was obtained (NFBC1986). In NFBC1966 pregnancies were followed prospectively from the first antenatal contact (10-16th week). After birth, the offspring were examined and then again underwent clinical evaluation at ages 1y, 7y, 14-16y and 31y. At each visit, a wide range of phenotypic, lifestyle and demographic data were gathered by questionnaires and clinical examinations. For the most part, NFBC1986 has undergone similar evaluations to NFBC1966. Linkage to national registries includes hospitalization, deaths, education, medication, pensions, and provides up-to-date demographic and clinical information for members of both cohorts. DNA samples were obtained from 5,923 subjects from NFBC1966 and 6688 subjects from NFBC1986. Data coverage, 96% of all births in 1966 and 99% in 1986, is highly representative for the whole population. The NFBC program comprises more than 20 different projects coordinated by the Center of Lifecourse Disease studies in Northern Finland (COLD) at Oulu University. The prospective data collected from the NFBCs form a unique resource, allowing the study of disease emergence, and of the importance of genetic, biological, social and behavioral risk factors. The genome-wide association (GWA) study sponsored through the STAMPEED program of NHLBI employed genomic DNA samples previously collected by the NFBC1966 study and stored in the DNA repository of the National Institute for Health and Welfare, Finland. This NHLBI sponsored RO1 project aimed to identify genetic variants contributing to metabolic and cardiovascular diseases (CVD). In addition to de-identified genome wide genotypic data, a selected list of phenotypic data related to CVD including weight, height, BMI, HDL, LDL, total cholesterol, triglyceride, glucose, insulin and fasting status, are also available in dbGaP. A summary of the GWAS for the NFBC1966 cardiovascular risk traits can be found in Sabatti et al., Nature Genetics 41: 35-46, 2009, PMID: 19060910. The version 2 release of this study contains sequence data from seventeen loci associated with levels of triglyceride, HDL-C, LDL-C, total cholesterol, fasting plasma glucose, and fasting plasma insulin (Kathiresan et al. 2008, Willer et al. 2008, Sabatti et al. 2009, Dupuis et al. 2010, Teslovich et al. 2010). At each locus, protein-coding regions and 5' and 3' untranslated regions of genes nearest to single nucleotide polymorphisms showing genome-wide significant association with metabolic syndrome-related traits, were sequenced. Targeted Illumina sequencing of 78 genes (~270kb) using 150bp probes was performed on 4943 subjects of the Northern Finland Birth Cohort 1966 (NFBC1966). Whole exome sequencing on the Illumina platform was carried out on 586 of those participants. The sequencing study is part of a larger project that is funded by the National Human Genome Research Institute's Allelic Spectrum in Common Disease Initiative, and comprises sequence data from more than 7000 individuals in two Finnish cohorts: NFBC1966 and the Finland-United States Investigation of NIDDM Genetics (FUSION) study.

Study phs000276

Prevention and Early Treatment of Acute Lung Injury (PETAL) Network - Functional, Imaging, and Respiratory Evaluation in CORAL (PETAL FIRE CORAL-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 PETAL FIRE CORAL include plasma and whole blood. Please note that use of biospecimens in genetic research is subject to a tiered consent and biospecimens may not be used to produce commercial products.Objectives: To examine the recovery from COVID-19 disease following acute hospitalization with an emphasis on functional, imaging, and respiratory evaluation, and assess the feasibility of conducting a larger study to evaluate variables associated with differential recovery.Background: The BLUE CORAL study, dbGaP phs003419, was intended to address the knowledge gaps and provide critical data to help guide clinical care, public health, and scientific efforts regarding SARS-CoV-2 (COVID-19) recovery. The understanding and treatment of long-term sequelae of COVID-19, referred to variously as post-acute sequelae of COVID-19 (PASC), post-acute COVID, long COVID, or long-haul COVID, is fundamental to patient recovery. These long-term consequences are common and increasingly recognized, although heterogeneous in manifestation, and can result in a failure to return to baseline level of health. At the time of the FIRE CORAL study, there were limited studies that collected objective assessments following hospital discharge for a wide spectrum of patients surviving COVID-19.Participants: FIRE CORAL enrolled adult participants as a subset of those enrolled in the BLUE CORAL study with a recent COVID-19 hospitalization and that completed the 1- or 3-month post-hospital telephone long-term outcomes assessment. The target enrollment for this pilot study cohort was 80 participants.Design: FIRE CORAL was a multicenter prospective cohort study of participants recovering from COVID-19 disease with in-person follow-up, as an extension of the BLUE CORAL study. The study consisted of a battery of assessments objectively measuring pulmonary function, abnormalities on lung imaging, and functional status. Participants were to attend and perform initial in-person testing at 3 to 9 months after hospital discharge. Participants with abnormal findings on pulmonary function testing or chest imaging during their initial assessment or those with persistent respiratory symptoms were eligible to repeat study procedures 3 months later with a subsequent visit at 12 months. All participants were invited to return for in-person follow up at 12 months after hospital discharge. Assessments included high-resolution chest CT scan without contrast, spirometry, lung volume assessment, diffusing capacity measured by single breath measurement, Six Minute Walk Test, Short Physical Performance Battery, St. George's Respiratory Questionnaire, and Functional Assessment of Chronic Illness Therapy-Fatigue scale. Demographic and hospitalization data are available as part of the BLUE CORAL study.The primary aim of the FIRE CORAL study was to examine the feasibility of conducting rigorous in-person follow-up testing of participants discharged from the hospital following COVID-19 illness to assist with planning for a larger study to evaluate variables associated with differential recovery. The secondary aim was to describe the pulmonary, imaging, and functional recovery following COVID-19 hospitalization in a diverse population of patients.

Study phs004130

Jackson Heart Study (JHS) Cohort

The Jackson Heart Study (JHS) is a large, community-based, observational study whose participants were recruited from urban and rural areas of the three counties (Hinds, Madison and Rankin) that make up the Jackson, MS metropolitan statistical area (MSA). Participants were enrolled from each of 4 recruitment pools: (1) random, 17%, (2) volunteer, 30%, (3) currently enrolled in the Atherosclerosis Risk in Communities (ARIC) Study, 31%, and (4) secondary family members, 22%. The final cohort of 5,306 participants included 6.59% of all African American Jackson MSA residents, aged 35-84, during the baseline exam (N-76,426, US Census 2000). Among these, approximately 3,600 gave consent that allows genetic research and deposition of data into dbGaP. Major components of three clinic examinations (see study history) include medical history, physical examination, blood/urine analytes, and interview questions on areas such as physical activity, stress, coping and spirituality, racism and discrimination, socioeconomic position, and access to health care. Extensive clinical phenotyping includes anthropometrics, electrocardiography, carotid ultrasound, ankle-brachial blood pressure index, echocardiography, CT chest and abdomen for coronary and aortic calcification, liver fat, and subcutaneous and visceral fat measurements, and cardiac MRI. At 12-month intervals after the baseline clinic visit (Exam 1), participants have been contacted by telephone to update information, confirm vital statistics, document interim medical events, hospitalizations and functional status, and obtain additional sociocultural information. Questions about medical events, symptoms of cardiovascular disease and functional status are repeated annually. Ongoing cohort surveillance includes abstraction of medical records and death certificates for relevant International Classification of Diseases (ICD) codes and adjudication of nonfatal events and deaths. CMS data are currently being incorporated into the dataset. Note: Regarding date variables warehoused in the Jackson Heart Study (JHS) Cohort on dbGaP, the coordinating center has developed an algorithm that will systematically review and de-identify any of the (nearly 100) date-related variable types stored in the data package. To simultaneously minimize (i) de-identifiability of the data and (ii) impact on analyses utilizing sensitive data elements, a participant-level random number was generated to avoid the necessity of sharing any potentially sensitive data. The coordinating center maintains an archived linkage of these data in their raw form and regularly reviews ad hoc requests to utilize the raw data on a project-by-project basis. The JHS Cohort is utilized in the following dbGaP substudies. To view genotypes, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the "Substudies" section of this top-level study page phs000286 JHS Cohort. phs000402 ESP Heart GO JHS phs000498 JHS Allelic Spectrum Seq phs000499 JHS CARephs001069 MI Gen JHS phs001098 T2D GENES Exome Seq phs001356 Exome Chip phs002256 Cardiometabolic Renal Proteomics phs002369 Metabolomics Insulin Resistance

Study phs000286

Single cell RNAseq of stenotic, inflamed and non-inflamed transmural lesions from patients with Crohn's disease

This dataset contains a gene-cell matrix derived from single-cell RNA sequencing (scRNA-seq) data of ileal tissue from Crohn's disease (CD) patients and colorectal cancer (CRC) patients. It includes: Crohn's Disease Patients: A trio of transmural lesions (stenotic, inflamed, and non-inflamed) from each patient. Colorectal Cancer Patients: Unaffected ileal tissue used as external non-inflamed control. Cell Level Metadata: The dataset includes relevant cell-level metadata such as cell type annotations used in the study. Experimental Details: Platform: 10x Genomics Chromium Single Cell 3' GEX Sequencing: Illumina NovaSeq Processing: Data processed with Cell Ranger software. Resulting count matrices were merged for downstream analysis, including integration and dimensionality reduction. Dataset Composition: Crohn's Disease Patients: 10 patients with 3 samples each (non-inflamed, inflamed, stenotic), totaling 30 samples. Colorectal Cancer Patients: 5 patients with 1 sample each of unaffected tissue, totaling 5 samples. Data Provided: Merged Raw Count Matrix: The final merged raw count matrix used for downstream analysis. Cell Metadata File: Contains details of sample, tissue, and patient for each cell in the count matrix. Barcodes File: Indicate each cell barcode which also encodes the sample, tissue, and patient details for each cell. CD.S_Inf: Stenotic Corhn's disease inflamed samples CD.S_Sten: Stenotic CD patient stenosis sample CD.S_Prox: Stenotic CD Patient - proximal non-inflamed sample CC.C_Prox: CRC Patient proximal unaffected sample eg: A barcode 'CC.C_1_Prox_AAGTCGTAGACCCTTA' indicates CRC Patient unaffected proximal sampe from CRC Patient no.1 and the nucleic acid sequence indicate a unique cell from this sample. Total Samples: Crohn's Disease (CD) Patients: 30 samples Colorectal Cancer (CRC) Patients: 5 samples Patient_no Sample Sample_type 1 CC.C_1 CC.C_1_Prox CC.C_Prox 2 CD.S_1 CD.S_1_Prox CD.S_Prox 3 CD.S_1 CD.S_1_Infl CD.S_Infl 4 CD.S_1 CD.S_1_Sten CD.S_Sten 5 CC.C_2 CC.C_2_Prox CC.C_Prox 6 CD.S_2 CD.S_2_Prox CD.S_Prox 7 CD.S_2 CD.S_2_Infl CD.S_Infl 8 CD.S_2 CD.S_2_Sten CD.S_Sten 9 CC.C_3 CC.C_3_Prox CC.C_Prox 10 CC.C_4 CC.C_4_Prox CC.C_Prox 11 CD.S_3 CD.S_3_Prox CD.S_Prox 12 CD.S_3 CD.S_3_Infl CD.S_Infl 13 CD.S_3 CD.S_3_Sten CD.S_Sten 14 CD.S_4 CD.S_4_Prox CD.S_Prox 15 CD.S_4 CD.S_4_Infl CD.S_Infl 16 CD.S_4 CD.S_4_Sten CD.S_Sten 17 CC.C_5 CC.C_5_Prox CC.C_Prox 18 CD.S_5 CD.S_5_Prox CD.S_Prox 19 CD.S_5 CD.S_5_Infl CD.S_Infl 20 CD.S_5 CD.S_5_Sten CD.S_Sten 21 CD.S_6 CD.S_6_Prox CD.S_Prox 22 CD.S_6 CD.S_6_Infl CD.S_Infl 23 CD.S_6 CD.S_6_Sten CD.S_Sten 24 CD.S_7 CD.S_7_Prox CD.S_Prox 25 CD.S_7 CD.S_7_Infl CD.S_Infl 26 CD.S_7 CD.S_7_Sten CD.S_Sten 27 CD.S_8 CD.S_8_Prox CD.S_Prox 28 CD.S_8 CD.S_8_Infl CD.S_Infl 29 CD.S_8 CD.S_8_Sten CD.S_Sten 30 CD.S_9 CD.S_9_Prox CD.S_Prox 31 CD.S_9 CD.S_9_Infl CD.S_Infl 32 CD.S_9 CD.S_9_Sten CD.S_Sten 33 CD.S_10 CD.S_10_Prox CD.S_Prox 34 CD.S_10 CD.S_10_Infl CD.S_Infl 35 CD.S_10 CD.S_10_Sten CD.S_Sten

Dataset EGAD50000000559

Mult-omics Palbociclib Resistance Study in HR+/HER2– Metastatic Breast Cancer

This study is multi-omics study of a Asian longitudinal metastatic breast cancer (MBC) cohort treated with palbociclib plus endocrine therapy. It contains NGS of baseline (BL) and progressive disease (PD) from 70 patients, consisting of 79 tumor/normal matched whole exome sequencing (WES) from 62 patients and 90 tumor whole transcriptome sequecing samples (WTS) from 70 patients. There were 56 BL biopsies profiled by WES and 64 by WTS; 23 PD biopsies were profiled by WES and 26 by WTS. Twenty and 23 patients had paired BL and PD biopsies profiled by WES and WTS, respectively.

Dataset EGAD00001008314

Heart Failure Network: Entresto(TM) in Advanced Heart Failure (HFN-LIFE-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 compare treatment with sacubitril/valsartan versus valsartan alone in patients with advanced heart failure with a reduced ejection fraction and recent New York Heart Association class IV symptoms.Background: Treatment with evidence-based medical therapies improves survival, reduces heart failure hospitalizations, and improves quality of life in patients with chronic heart failure with a reduced ejection fraction. However, evidence supporting the use of medical therapies among patients with advanced heart failure is limited. Patients with New York Heart Association (NYHA) class IV heart failure are not often enrolled in clinical trials.A previous trial reported that, compared with the angiotensin-converting enzyme inhibitor enalapril, sacubitril/valsartan, an angiotensin receptor-neprilysin inhibitor, reduced the relative risk of cardiovascular mortality and heart failure hospitalizations by 20% in ambulatory patients with heart failure with a reduced ejection fraction. Although patients with NYHA class IV heart failure were eligible to enroll, this population was underrepresented. The HFN-LIFE trial was initiated to provide additional information about the tolerability, safety, and potential efficacy of sacubitril/valsartan in patients with advanced heart failure.Participants: Of the eligible patients that enrolled, a total of 335 patients tolerated the run-in phase and were randomized to a treatment group. 167 patients were randomly assigned to receive sacubitril/valsartan and 168 patients were randomly assigned to receive valsartan alone.Design: The HFN-LIFE trial was a prospective, multicenter, randomized, double-blind phase 4 clinical trial. Trial enrollment was suspended early, due to the high risk for adverse outcomes associated with COVID-19 infection.Eligible patients were enrolled and began an unblinded run-in period of 3 to 7 days with sacubitril/valsartan, 24/26 mg (50-mg fixed dose), administered orally twice daily. Participants tolerating the run-in phase were randomized in a 1:1 fashion to receive sacubitril/valsartan (target dose, 200 mg twice daily) or valsartan (target dose, 160 mg twice daily). The initial doses were selected based on guidelines with dose adjustments being made every 2 weeks.The primary efficacy outcome was the area under the curve of NT-proBNP levels at 2, 4, 8, 12, and 24 weeks compared with the level of NT-proBNP at randomization. The secondary efficacy end point was the number of days the patient was alive, out of the hospital, and free from any of the following outcomes: listing for cardiac transplant, cardiac transplant, implantation of a left ventricular assist device, receipt of continuous inotropic therapy for 7 or more days, or hospitalization for heart failure on 2 or more occasions other than the index admission.Conclusions: In patients with chronic advanced heart failure with a reduced ejection fraction, there was no statistically significant difference between sacubitril/valsartan and valsartan alone with respect to reducing NT-proBNP levels.

Study phs004171

Low mutation burden and frequent loss of CDKN2A/B and SMARCA2, but not PRC2, define pre-malignant neurofibromatosis type 1-associated atypical neurofibromas

Neurofibromatosis type 1 (NF1) is a tumor-predisposition disorder caused by germline mutations in NF1. NF1 patients have an 8-16% lifetime risk of developing a malignant peripheral nerve sheath tumor (MPNST), a highly aggressive soft-tissue sarcoma, often arising from pre-existing benign plexiform neurofibromas (PN) and atypical neurofibromas (ANF). ANF are distinct from both PN and MPNST, representing an intermediate step in malignant transformation. In the first comprehensive genomic analysis of ANF, we performed tumor/normal exome sequencing (ES) of 16 ANFs. In addition, we conducted ES of three MPNSTs, copy-number meta-analysis of 26 ANF and 28 MPNST, and whole transcriptome RNA-seq analysis of five ANF and five MPNST. We identified low mutation burden (median 1, range 0-5) in the exomes of ANF (only NF1 somatic mutations were recurrent), and frequent deletions of CDKN2A/CDKN2B (69%) and SMARCA2(42%) loci. We determined that polycomb repressor complex 2 (PRC2) genes EED or SUZ12 were frequently mutated, deleted or downregulated in MPNST but not in ANF. Our gene expression study revealed upregulated NRAS, MDM2, CCND1/CCND2/CCND3 and CDK4/CDK6 in both ANF and MPNST, and overexpression of EZH2 in MPNST only. We conclude that the PN-ANF transition is primarily driven by the deletion of CDKN2A/CDKN2B in addition to already present inactivated NF1. Further progression from ANF to MPNST likely involves broad chromosomal rearrangements and frequent inactivation of the PRC2 genes, loss of the DNA repair genes, and copy-number increase of signal transduction, cell cycle and pluripotency self-renewal genes.

Study phs001993

Genetic characterization of B-cell prolymphocytic leukemia: a hierarchical prognostic model involving MYC and TP53 abnormalities - WXS

B-PLL is a rare disease, whose molecular pathology is largely unknown. We report here the cytogenetic and molecular findings in a large series of 34 B-PLL. Karyotype (K) was complex (≥3 abnormalities) in 73%, and highly complex (HCK≥5) in 45%. The most frequent chromosomal aberrations were: translocation targeting the MYC gene [t(MYC)] (62%), 17p deletion including TP53 gene (38%), trisomy 18/18q (30%), 13q14 deletion (29%), trisomy 3 (24%), trisomy 12 (24%) and 8p deletion (23%). Whole-Exome Sequencing performed in 16 patients revealed recurrent mutations in TP53 (6/16, 38%), MYD88 (n=4), BCOR (n=4), MYC (n=3), SF3B1 (n=3), FAT1 (n=3), SETD2 (n=2), CHD2 (n=2), CXCR4 (n=2) and BCLAF1 (n=2). The main group of patients (21/34, 62%) had a t(MYC) associated with a higher percentage of prolymphocytes (p=0.03), CD38 expression (p<0.001), lower K complexity (p=0.0004), mutations in MYC and in genes involved in RNA metabolism and chromatin remodeling. Principal component analysis of gene expression data showed that patients with t(MYC) clustered together. A second group with MYC gain (5/34, 15%), was associated with HCK≥5 (p=0,01) and trisomy 3 (p=0,008). Altogether, 26/34 patients (76%) had a MYC activation, translocation or gain, that were mutually exclusive. We identified 3 distinct cytogenetic prognostic groups (p=0.0006): lower risk: absence of MYC activation (median not reached); intermediate risk: MYC activation without del17p (125 months); high risk: MYC activation + del17p (11 months). Our results show that cytogenetic analysis is a useful diagnostic tool in B-PLL that improves prognostic stratification.

Study EGAS00001003275

Genetic characterization of B-cell prolymphocytic leukemia: a hierarchical prognostic model involving MYC and TP53 abnormalities - RNA-seq

B-cell prolymphocytic leukemia (B-PLL) is a rare disease, whose molecular pathology is largely unknown. We report here the cytogenetic and molecular findings in a large series of 34 B-PLL. Karyotype (K) was complex (≥3 abnormalities) in 73%, and highly complex (HCK≥5) in 45%. The most frequent chromosomal aberrations were: translocation targeting the MYC gene [t(MYC)] (62%), 17p deletion including TP53 gene (38%), trisomy 18/18q (30%), 13q14 deletion (29%), trisomy 3 (24%), trisomy 12 (24%) and 8p deletion (23%). Whole-Exome Sequencing performed in 16 patients revealed recurrent mutations in TP53 (6/16, 38%), MYD88 (n=4), BCOR (n=4), MYC (n=3), SF3B1 (n=3), FAT1 (n=3), SETD2 (n=2), CHD2 (n=2), CXCR4 (n=2) and BCLAF1 (n=2). The main group of patients (21/34, 62%) had a t(MYC) associated with a higher percentage of prolymphocytes (p=0.03), CD38 expression (p<0.001), lower K complexity (p=0.0004), mutations in MYC and in genes involved in RNA metabolism and chromatin remodeling. Principal component analysis of gene expression data showed that patients with t(MYC) clustered together. A second group with MYC gain (5/34, 15%), was associated with HCK≥5 (p=0,01) and trisomy 3 (p=0,008). Altogether, 26/34 patients (76%) had a MYC activation, translocation or gain, that were mutually exclusive. We identified 3 distinct cytogenetic prognostic groups (p=0.0006): lower risk: absence of MYC activation (median not reached); intermediate risk: MYC activation without del17p (125 months); high risk: MYC activation + del17p (11 months). Our results show that cytogenetic analysis is a useful diagnostic tool in B-PLL that improves prognostic stratification.

Study EGAS00001003274

FIGHT-207: Anonymized Genomic Alterations and Clinical Responses

Background: FIGHT-207 was a phase 2 study of the FGFR1-FGFR3 inhibitor pemigatinib in patients with previously treated, locally advanced/metastatic or unresectable solid tumor malignancies harboring activating fibroblast growth factor receptor (FGFR) gene alterations. Population information: 107 patients were divided into 3 cohorts: FGFR1–FGFR3 fusions/rearrangements; n=49 Activating FGFR1–FGFR3 non-kinase domain single nucleotide variants (SNVs); n=32 FGFR1–FGFR3 kinase domain mutations or variants of unknown significance (VUS) with potential pathogenicity; n=26 Participants on study had tumors that were grouped into the following histologies based on ≥ 5 patients: Cholangiocarcinoma, gynecologic cancers (cervical, endometrial, uterine), central nervous system (glioblastoma, low-grade pediatric glioma, astrocytoma), pancreatic cancer, breast cancer, urothelial tract/bladder cancer, non-small cell lung cancer, and other (adrenal cancer, anal cancer, cancer of unknown primary origin, colorectal cancer, gastric/gastroesophageal cancer, gallbladder cancer, giant cell bone tumor, head and neck cancer, lung neuroendocrine cancer, nasopharyngeal cancer, ovarian cancer, prostate cancer, renal cell cancer, sarcoma, solitary fibrous tumor). Among the efficacy-evaluable participants, 99 had both independent review committee (IRC) central best overall response (BOR) and tissue NGS- data; 2 additional patients had Not Evaluable (NE) as central BOR Baseline tissue targeted NGS data (F1CDx, Foundation Medicine Inc.) of genomic alterations are reported for N=101 participants Baseline plasma targeted NGS analysis (PredicineCare, Predicine Inc.) of genomic data are reported for N=83 participants; data at disease-progression are reported for N=78 participants. Principal Findings: The FIGHT-207 study provided evidence of clinical benefit of pemigatinib in multiple histologies, explored the clinical actionability of various FGFR1-FGFR3 gene alterations, and leveraged the depth of translational data from targeted NGS analysis of baseline samples and plasma samples obtained at baseline and end of treatment to provide key insights into the biology of FGFR inhibition and the clinical utility of FGFR inhibitors. The FIGHT-207 article (pending in Nat.Med. NMED-A128973B) reports evidence suggesting clinical acquired resistance to FGFR inhibition via secondary FGFR mutations as well as emerging co-mutations in other oncogenic and tumor suppressor pathways. This study also provides evidence of acquired resistance to FGFR inhibition in multiple histologies beyond cholangiocarcinoma and urothelial cancers in a systemic correlative analysis of post-progression ctDNA in a trial. Data available through dbGaP: Anonymized information for 101 participants with both IRC central BOR evaluation (including 2 patients with NE as BOR) and tissue NGS data, including tumor histology, enrollable FGFR alteration, and outcome. Genomic alterations determined by baseline tissue NGS (F1CDx, Foundation Medicine Inc.) Genomic alterations determined by plasma NGS analysis (PredicineCare, Predicine Inc.) of ctDNA analysis at baseline (n=83) and at end of treatment/ disease progression (n=78) including genomic alterations that were not assessed to be Germline SNPs.

Study phs003590

Heart Failure: A Controlled Trial Investigating Outcomes of Exercise Training (HF-ACTION-BioLINCC)

Accessing Data Please refer to “Authorized Access” below regarding accessing data through the BioData Catalyst ecosystem. The data from this accession is not available for download through dbGaP.ObjectivesThe HF-ACTION study examined whether exercise training reduces a composite endpoint of all-cause mortality or all-cause hospitalization for patients with left ventricular systolic dysfunction and heart failure symptoms. Background Heart failure (HF) is a major and growing cardiovascular syndrome that is the end result of many cardiovascular disorders. Although evidence-based drug and device therapies decrease mortality, hospitalizations, and HF symptoms and improve quality of life, many patients treated with these regimens often remain burdened by dyspnea and fatigue, diminished exercise tolerance, reduced quality of life, recurrent hospitalizations, and early mortality. Whereas rest was traditionally recommended for HF patients, there has been evidence that physical deconditioning may play a key role in the progression of symptoms and poor outcomes. Previous studies have shown positive effects of exercise training on exercise capacity, quality of life, and biomarkers and suggest that exercise training might improve survival and decrease HF hospitalizations. Nonetheless, there remains a safety concern regarding exercise training in HF and a large scale, multicenter, controlled clinical trial was needed to provide definitive clinical outcome data. Participants A total of 2,331 participants were randomized. 2,130 consented to share data with non-commercial entities, and 1,753 consented to share for commercial purposes. Design All participants underwent baseline cardiopulmonary exercise testing. Test results were reviewed by investigators to identify significant arrhythmias or ischemia that would prevent safe exercise training, to determine appropriate levels of exercise training, and to establish training heart rate ranges. Demographics, socioeconomic status, past medical history, current medications, physical exam, and the most recent laboratory tests were obtained prior to randomization. All participants received detailed self-management educational materials which included information on medications, fluid management, symptom exacerbation, sodium intake, and physical activity. Participants randomized to the exercise training arm first participated in a structured, group-based, supervised exercise program, with a goal of 3 sessions per week for a total of 36 sessions in 3 months. The primary exercises were walking, treadmill, or stationary cycling. Exercise was initiated at 15 to 30 minutes per session at a heart rate corresponding to 60% of heart rate reserve, and was increased after 6 sessions to 30 to 35 minutes duration and 70% of heart rate reserve. Participants began home-based exercise after completing 18 supervised sessions and were to fully transition to home exercise after 36 supervised sessions. The target training regimen for home exercise was 5 times per week for 40 minutes at a heart rate of 60% to 70% of heart rate reserve. Participants randomized to the usual care group were not provided with a formal exercise prescription. To provide comparable levels of attention from study personnel, all participants were called every 2 weeks for the first 9 months, monthly until 24 months of follow-up, and quarterly thereafter. Participants returned for clinic visits every 3 months for the first 2 years of participation and yearly thereafter for up to 4 years. Follow-up assessments included cardiopulmonary exercise testing, a 6-minute walk test, and a physical activity questionnaire. The primary end point was a composite of all-cause mortality or all-cause hospitalization. Secondary end points included all-cause mortality, the composite of cardiovascular mortality or cardiovascular hospitalization, and the composite of cardiovascular mortality or HF hospitalization. Conclusions After adjustment for highly prognostic predictors of the primary end point, exercise training was associated with modestly significant reductions for both all-cause mortality or hospitalization and cardiovascular mortality or heart failure hospitalization.

Study phs003599

Single Cell Analysis Program - Transcriptome (SCAP-T)

This initiative is part of the Single Cell Analysis Program (SCAP) and is funded through the NIH Common Fund (See http://nihroadmap.nih.gov/), which supports cross-cutting programs that are expected to have exceptionally high impact. Common Fund initiatives address key roadblocks in biomedical research that impede basic scientific discovery and its translation into improved human health. In addition, these programs capitalize on emerging opportunities to catalyze progress across multiple biomedical fields. Single cell analysis has recently emerged as an important field of research because technologies have improved in sensitivity and throughput sufficiently to begin measuring and understanding heterogeneity in complex biological systems and correlating it with changes in biological function and disease processes. By profiling individual cells it is possible to resolve rare cells, transient cell states, and the influence of organization and environment on such cells and states, which cannot be described by ensemble measurements. The long-term goal of the SCAP is to accelerate this move towards personalizing health to the cellular level by understanding the link between cell heterogeneity, tissue function and emergence of disease through the discovery, development and translation of innovative approaches which will dramatically change the way cells are characterized. The SCAP will focus on research, which will systematically measure, analyze and model cell-to-cell variation, and identify crucial differences and rare biological states, which may have important functional consequences. Under SCAP, there are three studies to evaluate the cellular heterogeneity using transcriptional profiling of single cells (U01): University of Pennsylvania: Role of single cell mRNA variation in systems associated electrically excitable cells University of Southern California: Evaluation of cellular heterogeneity using patchclamp and RNA-seq of single cells University of California at San Diego: Single cell sequencing and in situ mapping of RNA transcripts in human brains The SCAP has been designed as a five-year program with several components: (1) the collection, analysis and sharing of comprehensive expression datasets to understand the role of heterogeneity in tissues and systemically and identify critical parameters and states; (2) the discovery of new, innovative tools for spatiotemporal imaging, manipulation, analysis and modeling of a biologically relevant population of cells with minimal perturbation; (3) milestone-driven validation and translation of technologies for characterizing single cells in situ meeting the needs of end-users; and (4) development and coordination of a multidisciplinary research community through workshops and other collective endeavors. Further details about the NIH SCAP-T program can be found here http://commonfund.nih.gov/singlecell/. The SCAP-T data sets include the detailed phenotype information, experimental protocols, QC information, RNA-sequencing data and NGS results from human heart and human brain cells. The first data release includes 697 single cells from human brain and heart. The second data release includes an additional 978 single cells from human brain and heart. The third data release includes an additional 1631 single cells from human brain and heart. The fourth data release is a correction to this study, but adds no new cells. The fifth data release includes an additional 2984 single cells from human brain and heart. The sixth data release includes an additional 944 single cells from human brain and heart. The seventh data release includes an additional 1977 single cells from human brain and heart. The SCAP-T data portal provides a customized interface for users to quickly identify and retrieve files by phenotypes, and data properties such as sequencing facility or coverage for all of these 9231 single cells. For more information about the SCAP-T study and the data portal, please visit http://www.scap-t.org.

Study phs000833

Title: Divergent levels of CD112 and INKA1 define a distinct subset of human long-term hematopoietic stem cells

The data provided here was critical in establishing that human long-term hematopoietic stem cells (LT-HSC), previously described as the most primitive HSC population, is actually composed of distinct subsets that can be prospectively isolated. Via mechanistic studies centering around the Rho-GTPase effector kinase PAK4 and its inhibitor INKA1, we identified the immune checkpoint ligand CD112 as a marker for hematopoietic stem and progenitor cells, that is highest expressed on LT-HSC. More importantly, CD112 can be used to stratify functionally distinct subsets within LT-HSC: In response to regeneration-mediated stress, the CD112low subset exhibits a transient restraint (termed latency) before contributing to hematopoietic reconstitution, while the CD112high subset is primed to respond rapidly. High resolution RNA-seq of the CD112 surface expression spectrum within rare LT-HSC subsets (human umbilical cord blood) demonstrated that more genes are differentially upregulated in the deeper quiescent and less metabolic active subset. Genes enriched in this subset centre around cell adhesion and Rho-GTPase signaling. This is in agreement with the scRNAseq data from human G-CSF mobilized peripheral blood (mPB) generated here that was used as an model of in vivo activation/priming revealing via RNA-velocity and pseudo-time analysis that INKA1high versus PAK4high, CDK6high and CD112high enrichment are either detected early or late in diffusion pseudotime indicative of quiescent versus primed cell status, respectively. RNAseq following INKA1 overexpression in LT-HSC and ST-HSC revealed by GSEA an overall stemness preserving phenotype and particularly in LT-HSC, but not in short-term HSC (ST-HSC), suppression of transcriptional programs linked to activation. Collectively, our data decipher the molecular intricacies underlying HSC heterogeneity and self-renewal regulation and point to latency as an orchestrated physiological response that integrates quiescence control with HSC fate choices to preserve a stem cell reservoir.

Dataset EGAD00001006541

Single cell eQTL map of T cell activation

We isolated naive and memory CD4+ T cells from 119 healthy individuals and stimulated the cells using anti-CD3/anti-CD28 coated beads. We profiled gene expression using single cell RNA-seq (10X-Genomics 3’ v2 kit) at resting state and three time points of activation (16h, 40h and 5 days post stimulation) and mapped expression quantitative trait loci.

Dataset EGAD00001008197

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 Finland-United States Investigation of NIDDM Genetics (FUSION) Tissue Biopsy Study

The Finland-United States Investigation of NIDDM Genetics (FUSION) study is a long-term effort to identify genetic variants that predispose to type 2 diabetes (T2D) or that impact the variability of T2D-related quantitative traits (QTs). Most of the variants associated with T2D and related traits (glucose and insulin, anthropometrics, lipids) through genome-wide association studies (GWAS) occur in non-coding regions, suggesting a strong regulatory component to disease susceptibility. Regulatory element activity is often tissue-specific, which further complicates discovery of the causal/functional variation. Therefore, there is a critical need to identify the appropriate cell type, regulatory elements, target genes, and causal variants(s) in T2D-relevant tissues. We hypothesize that a subset of T2D and related variants alter gene expression regulation in skeletal muscle and adipose tissue - two major insulin target tissues and play key roles in insulin resistance. To that end, our study contains a comprehensive survey of genomics, epigenomics and transcriptomics in skeletal muscle and adipose tissue from individuals with glucose tolerance categories ranging from normal to T2D.For this FUSION Tissue Biopsy Study, we obtained RNA-Seq, microRNA (miRNA)-Seq, and DNA methylation (methyl)-Seq data on biopsy samples from 331 individuals from across the range of glucose tolerance: 124 normal glucose tolerance (NGT), 77 impaired glucose tolerance (IGT), 44 impaired fasting glucose (IFG), and 86 newly-diagnosed T2Ds. Participants completed two study visits, two weeks apart. First visits comprised most of the clinical phenotyping, including four-point OGTT (fasting, and 30, 60, and 120 minute post-load); BMI, WHR; lipids; blood pressure; and many other variables. Participants also completed FUSION health history, medication, and lifestyle questionnaires. On the second visit, we obtained ~250mg vastus lateralis skeletal muscle, ~750mg abdominal subcutaneous adipose, and a ~5x15mm section of abdominal skin. Visits were completed in March 2013. RNA isolation is ongoing in the Collins laboratory at the NIH, RNA and miRNA sequencing at the NIH Intramural Sequencing Center (NISC), and genotyping at the Center for Inherited Disease Research (CIDR). Individual-level data is available here for the 306 individuals who consented to data deposit. To focus on evaluation of gene expression and its regulation in skeletal muscle, we analyzed mRNA extracted from vastus lateralis skeletal muscle obtained from 271 of the 331 individual subjects from Finland, along with genome-wide genotypes. Individual-level data is available here for the 250 subjects who consented to the use of their data.Release phs001048.v2.p1 adds muscle data for an additional 42 subjects and data from adipose tissue for 276 subjects. Total RNA was isolated using Trizol extraction in the Collins laboratory at the NIH. The mRNA was poly-A selected, 24-plex libraries were generated using the Illumina TruSeq directional mRNA-seq library protocol and RNA sequencing was performed on HiSeq2000 sequencers using 101bp paired-end reads at NISC. miRNA libraries were prepared from total RNA from 296 muscle and 270 adipose samples, pooled and sequenced 50bp single-end reads on Illumina HiSeq2500. Data for 272 muscle and 251 adipose samples are available here for individuals with consent for data deposit. DNA was extracted from blood in the Collins laboratory, and genotyping on the Illumina Omni2.5M array was performed at CIDR. Genotypes were imputed using the HRC 2016 reference panel. In order to assess regions of open chromatin in skeletal muscle, we obtained muscle tissue from a commercial provider to perform ATAC-seq; these samples were sequenced at the University of Michigan DNA Sequencing Core.Release phs001048.v3.p1 adds single-nucleus (sn) RNA-seq and ATAC-seq data in 287 skeletal muscle samples out of the original 331 individuals. Individual-level data is available here for the 265 subjects who consented to the use of their data. The frozen tissue biopsy samples were processed in ten batches, each consisting of 40-41 samples. These batches were organized using a randomized block design to protect against experimental contrasts of interest including cohort, age, sex, BMI among others. Samples in each batch were pulverized, pooled together followed by nuclei isolation. The nuclei were processed on the 10X Genomics Chromium platform separately for snATAC-seq and snRNA-seq (v. 3.1 chemistry for snRNA-seq).Release phs001048.v4.p1 adds additional phenotypes and provides some corrections to several previous phenotypes.

Study phs001048

CNS Embryonal tumors

The dataset represents a total of 58 DNA samples from 16 male and 12 female pediatric patients affected with embryonal central nervous system tumors. The samples were subject to whole genome sequencing, WGS, [48 samples, (representing 12 male and 11 female individuals)] and whole exome sequencing, WES, [10 samples, (representing 4 male and 1 female individuals)]. One tumor tissue sample and one peripheral blood sample were analyzed from each of 26 patients, whereas two tumor tissue samples and one peripheral blood sample were analyzed from two patients. The WGS samples were sequenced 2x150 bp paired-end on an Illumina HiSeqX v2.5 instrument, and the WES samples were sequenced 2x100 bp paired-end on an Illumina HiSeq 2500 instrument. The FASTQ files generated were aligned to the human reference genome sequence GRCh38/hg38 using bwa-mem, with the ALT-aware option turned on. Sorting of reads and marking of PCR duplicates was performed with GATK. Base quality score recalibration and joint realignment of reads around insertions and deletions (indels) were conducted using GATK tools. The dataset consists of 58 files in the CRAM format (lossless compression) with a total file size of ~8,8 TB. All CRAM files but one, are derived from one sequence run and one sample. P4551_227N_P4552_112N is a CRAM file where 2 sequence runs (P4551_227N and P4552_112N) from peripheral blood samples from the same individual, P019, were aligned into one single CRAM file. Additional genomic and molecular data (FASTQ, BAM, IDAT, and VCF files) and limited clinical data can be requested by ethically approved projects conducting research in the field of pediatric cancer.

Dataset EGAD50000000298

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