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• H3Africa - Genomic Characterization and Surveillance of Microbial Threats in West Africa

  Viral diseases are remarkably heterogeneous in their presentation and clinical course. Although diseases such as Lassa Fever and Ebola Virus Disease are thought to be severe and rapidly fatal, they can often present with mild symptoms or remain asymptomatic. Host genetic variability is likely an important mediator of this heterogeneity. Complete characterization of the clinical, laboratory, and host genetic features of these illnesses is not only imperative to rapid diagnosis and effective clinical care, but also important for further scientific study. In this project, we propose to address this need through deep characterization of the clinical and laboratory features of viral disease and through study of genetic mediators of resistance to Lassa Fever and Ebola Virus Disease. Will carry out deep clinical characterization and laboratory assessment of viral febrile cases at two West African Collaborative Centers, and will use this data to develop prognostic models using cutting-edge tools in exploratory data visualization and machine learning. Investigate host genetic factors of Lassa Fever and Ebola Virus Disease through genome-wide association studies. We will then develop field-deployable genotyping assays for the top-associated variants, and apply them in new cohorts to replicate our findings and investigate patterns of genetic resistance in clinical subgroups. This project can shed light on the clinical manifestations of viral illness and their host genetic mediators, leading to potential new insights in disease biology and pathophysiology. We will also create a rich resource of clinical, laboratory, and genetic data for these illnesses in two countries in West Africa, which will serve as a foundation for advancing the clinical care and scientific study of viral disease in the region.

  Study EGAS00001007250

• eMERGE Network Imputed GWAS for 41 Phenotypes

  The electronic Medical Records and Genomics (eMERGE) Network is a consortium of ten participating sites (Cincinnati Children's Hospital Medical Center/Boston Children's Hospital, Children's Hospital of Philadelphia, Essentia Institute of Rural Health, Marshfield Clinic Research Foundation and Pennsylvania State University, Geisinger Clinic, Group Health Cooperative/University of Washington, Mayo Clinic, Icahn School of Medicine at Mount Sinai, Northwestern University, Vanderbilt University Medical Center) funded by the NHGRI to investigate the use of electronic medical record (EMR) systems for genomic research. The goal of eMERGE is to conduct genome-wide association studies in approximately 55,000 individuals using EMR-derived phenotypes and DNA from linked Biorepositories. Using electronic phenotyping methods, the consortium used DNA samples from all participating sites to explore the genetic determinants of over forty phenotypes, including Abdominal aortic aneurysm; Ace-Inhibitor/Cough; Attention Deficit Hyperactivity Disorder; Age-related macular disease; Appendicitis; Asthma; Atopic Dermatitis; Autism; Benign Prostatic Hyperplasia; Carotid artery disease as a Quantitative Measure; caMRSA; Cataract; Clostridium difficile colitis; Extreme Obesity; Chronic Kidney Disease; Chronic Kidney Disease and Type 2 Diabetes; Chronic Kidney Disease, Type 2 Diabetes and Hypertension; Colon Polyps; Cardiorespiratory Fitness; Dementia; Diverticulosis; Diabetic retinopathy; Gastroesophageal Reflux Disease; Glaucoma; Height; Heart failure; Hypothyroidism; Lipids; Ocular hypertension; Peripheral Arterial Disease; QRS duration; Red blood cell indices; Remission of Diabetes after ROUX-EN-Y gastric bypass surgery; Resistant hypertension; MACE while on Statins; Type 2 Diabetes; Venous Thromboembolism; White blood cell indices; and Zoster virus infection, as well as using the phenome-wide association study (PheWAS) paradigm to replicate and discover relationships between targeted genotypes with multiple phenotypes. Sites 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. A large majority of participants consenting to prospective genomic analyses also consent to analysis of their de-identified electronic medical records (EMRs). EMRs are longitudinal, with a mean duration of 6.5 years. Cincinnati Children's Hospital Medical Center/Boston's Children's Hospital (CCHMC/BCH): Cincinnati Children's Hospital Medical Center (CCHMC) and Boston Children's Hospital (BCH) are pediatric institutions dedicated to improving health and welfare of children and to the shared purpose of discovery and practical application of new genomic information to the ordinary care of children. The CCHMC/BCH site has been built on a five-year history of collaboration, particularly in patient electronic record (ERM)-related informatics, the basis of much of eMERGE II. CCHMC and BCH together bring an extraordinary faculty to eMERGE II who are committed to diseases that afflict children, specifically phenotypes that focus upon diseases of children in ways that will leverage the available eMERGE adult GWAS and EMRs to discover meaningful use results. CCHMC/BCH plans to demonstrate real-time execution of phenotypic selection across their two distinct pediatric institutions as a model for ensuring phenotypic standardization and for national scalability. They will also look carefully at parents' responses to results and use of their children's research results and better understand the factors that influence their decisions about learning incidental findings. In addition to patient and parent perceptions CCHMC/BCH will also explore clinician perceptions of pharmacogenetic research results after EMR integration. 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 participants provided written informed consent and HIPAA authorization. Consenting patients agreed to provide blood samples for broad biomedical research use, and permission to access data in their Geisinger electronic medical record for research. The enrollment rate was 90% of patients approached. The demographics of the cohort approximate those of the Geisinger Clinic outpatient population. Research blood samples were collected during an outpatient clinical phlebotomy encounter. Research blood samples are coded and stored in a central biorepository. Samples are linkable to clinical data in a de-identified manner for research via an IRB-approved data broker process. For genomic analysis, DNA is extracted from EDTA-anticoagulated whole blood. Group Health(GH)/University of Washington (UW): 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 participants 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): The Marshfield Clinic Personalized Medicine Research Project is a population-based biobank in central Wisconsin with more than 20,000 adult subjects who provided written, informed consent to access their medical records and provided a blood sample from which DNA was extracted and plasma and serum stored. In addition to an average of 30 years of medical history data, a questionnaire about environmental exposures, including a detailed food frequency questionnaire, is available to facilitate gene/environment studies. Mayo Clinic: The Mayo biobank is a disease-specific biobank for vascular diseases including peripheral arterial disease (PAD). PAD patients were identified from individuals referred to the non-invasive vascular laboratory for lower extremity arterial evaluation. Since 1997, laboratory findings have been recorded into an electronic database employing an in-house software package for data archiving and retrieval; this data becomes part of the Mayo EMR. Patients referred to the center with suspected PAD undergo a comprehensive non-invasive evaluation including the ankle-brachial index (ABI) - the ratio of blood pressure measured in the upper arms divided by blood pressure measured at the ankles. Controls subjects are identified from patients referred to the Cardiovascular Health Clinic for stress ECG. The prevalence of PAD in patients with normal exercise capacity who do not have inducible ischemia on the stress ECG , was <1%. Data regarding risk factors for atherosclerosis such as diabetes, dyslipidemia, hypertension, and smoking are ascertained from the EMR. Icahn School of Medicine at Mount Sinai School (Mt. Sinai): The Institute for Personalized Medicine (IPM) Biobank Project is a consented, EMR-linked medical care setting biorepository of the Mount Sinai Medical Center (MSMC) drawing from a population of over 70,000 inpatients and 800,000 outpatient visits annually. MSMC serves diverse local communities of upper Manhattan, including Central Harlem (86% African American), East Harlem (88% Hispanic Latino), and Upper East Side (88% Caucasian/white) with broad health disparities. IPM Biobank populations include 28% African American (AA), 38% Hispanic Latino (HL) predominantly of Caribbean origin, 23% Caucasian/White (CW). IPM Biobank disease burden is reflective of health disparities with broad public health impact: average body mass index of 28.9 and frequencies of hypertension (55%), hypercholesterolemia (32%), diabetes (30%), coronary artery disease (25%), chronic kidney disease (23%), among others. Biobank operations are fully integrated in clinical care processes, including direct recruitment from clinical sites, waiting areas and phlebotomy stations by dedicated Biobank recruiters independent of clinical care providers, prior to or following a clinician standard of care visit. Recruitment currently occurs at a broad spectrum of over 30 clinical care sites. Northwestern University: The NUgene Project is a repository with longitudinal medical information from participating patients at affiliated hospitals and outpatient clinics from the Northwestern University Medical Center. Participants' DNA samples are coupled with data from a self-reported questionnaire and continuously updated data from our Electronic Medical Record (EMR) representing actual clinical care events. Northwestern has a state-of-the art, comprehensive inpatient and outpatient EMR system of over 2 million patients. NUgene has broad access to participant data for all outpatient visits as well as inpatient data via a consolidated data warehouse. NUgene participants consent to distribution and use of their coded DNA samples and data for a broad range of genetic research by third-party investigators. Vanderbilt University: BioVU, Vanderbilt's DNA databank, is an enabling resource for exploration of the relationships among genetic variation, disease susceptibility, and variable drug responses, and represents a key first step in moving the emerging sciences of genomics and pharmacogenomics from research tools to clinical practice. BioVU acquires DNA from discarded blood samples collected from routine patient care. The biobank is linked to de-identified clinical data extracted from Vanderbilt's EMR, which forms the basis for phenotype definitions used in genotype-phenotype correlations.

  Study phs000888

• Whole genome sequencing in myasthenia gravis

  This dataset contains whole genome sequencing data on 25 individuals with myasthenia gravis. The data was generated using Illumina sequencing technology and is presented as BAM files for each sample.

  Dataset EGAD00001005262

• RNA-Seq data of de novo assembly individual EGYPT

  This is the blood RNA-Seq read data used for expression analysis such as haplotypic expression (mapped against GRCh38).

  Dataset EGAD00001006036

• Genomic analysis of primary plasma cell leukemia reveals complex structural alterations and high risk mutational patterns

  Primary plasma cell leukemia (pPCL) is a rare and aggressive form of multiple myeloma (MM) that is characterized by poor overall survival despite advances in anti-MM therapy. The disease biology as well as molecular mechanisms that distinguish pPCL from non-pPCL MM remain poorly understood. In an attempt to identify key biological mechanisms that result in the aggressive pPCL phenotype we performed whole exome sequencing in 23 patients with newly diagnosed pPCL. The results reveal an enrichment of complex structural changes and high risk mutational patterns in pPCL that explain, at least in part, the aggressive nature of the disease. In particular pPCL patients with traditional low risk features such as translocation t(11;14) or hyperdiploidy accumulated adverse risk genetic events that could account for the poor outcome in this group.

  Study phs002022

• From matrimonial practices to genetic diversity in Southeast Asian populations: the signature of the matrilineal puzzle

  This project aims at revisiting the "matrilineal puzzle" from a population genetics' point of view. The dataset consists of 719 individuals from 12 populations sampled in continental Southeast Asia and genotyped at 598764 loci. This dataset can only be accessed and used for non-commercial research purposes with a finality complying with the informed consent provided by donors. For accessing the data, please provide: 1. An explicit title for the project you wish to use the data for. 2. A detailed institutional affiliation of all recipients and users of the data. 3. A summary (500 words) of the research project, with emphasis on its scientific and societal finality, and predicted outputs. If access is granted by the DAC, data cannot be shared with a third party not initially involved in the project, without the third party officially applying for accessing the data.

  Study EGAS00001003727

• Childhood Cancer Data Initiative (CCDI): Genomic Analysis in Pediatric Malignancies

  Pediatric solid tumors are highly heterogeneous, encompassing a large number of histotypes. The genomic landscape of these diseases is characterized by few single-nucleotide variants (SNVs) compared to adult cancers. In contrast, many exhibit a high prevalence of structural or epigenetic changes that alter gene expression, underlining the need for comprehensive genomic approaches such as whole-genome sequencing (WGS). Several studies have specifically addressed the clinical utility of genomic analysis in the pediatric and AYA cancer setting. Review of these studies point to key challenges that must be addressed in order to advance the routine use of genomics in this population. We have established a large collection of solid tumor tissue samples through our biobanking efforts. Where possible, we obtain longitudinal samples from the same patient. These primary patient samples and their corresponding germline have been analyzed using whole genome and whole transcriptome sequencing methods and have been linked to clinical metadata using both manual curation and robust methods for automatic extraction from the electronic health record (EHR). Importantly, research-grade genomic analysis is performed in parallel to our CLIA-grade sequencing (“UCSF500”) efforts for some of the patients in this study cohort and have been submitted as part of the American Association for Cancer Research's project GENIE and/or the National Childhood Cancer Registry. For our sequenced tumor samples, we have retrospective clinical data and ongoing efforts to prospectively record key events throughout the patient's cancer journey. In our solid tumor program, we have developed many patient-derived xenograft models and a number of PDX-derived cell lines. These unique models have been evaluated using genomic and functional approaches including (in some cases) treatment with conventional chemotherapy or investigational agents. Lastly, these samples were collected from a population that is among the most diverse in the nation and includes significant numbers of Asian, Latino, Indigenous and African-American patients, groups that are traditionally underrepresented in many banking efforts.

  Study phs002430

• Exome and RNA sequencing of relapsed TCF3-PBX1 t(1;19) acute lymphoblastic leukemia

  TCF3-PBX1 (E2A-PBX1) is a recurrent gene fusion in B-cell precursor lymphoblastic leukemia (BCP-ALL), which is caused by the translocation t(1;19)(q23;p13). TCF3-PBX1 BCP-ALL patients typically benefit from chemotherapy; however, many relapse and subsequently develop resistant disease with few effective treatment options. Mechanisms driving disease progression and therapy resistance have not been studied in TCF3-PBX1 BCP-ALL. Here, we aimed to identify novel treatment options for TCF3-PBX1 BCP-ALL by profiling leukemia cells from a relapsed patient, and determine molecular mechanisms underlying disease pathogenesis and progression. By drug sensitivity testing of leukemic blasts from the index patient, control samples and TCF3-PBX1 positive and negative BCP-ALL cell lines, we identified the phosphatidylinositide 3-kinase delta (p110δ) inhibitor idelalisib as an effective treatment for TCF3-PBX1 BCP-ALL. This was further supported by evidence showing TCF3-PBX1 directly regulates expression of PIK3CD, the gene encoding p110δ. Other somatic mutations to TP53 and MTOR, as well as aberrant expression of CXCR4, may influence additional drug sensitivities specific to the index patient and accompanied progression of the disease. Our results suggest that idelalisib is a promising treatment option for patients with TCF3-PBX1 BCP-ALL while other drugs could be useful depending on the genetic context of individual patients.

  Study EGAS00001001876

• Benchmarking dataset for ProSolo, a probabilistic single nucleotide caller for single cell DNA sequencing data

  This is the dataset used in the benchmarking of ProSolo, a new probabilistic single nucleotide variant caller for single cell DNA sequencing data that provides control over the false discovery rate of different single cell events at genomic sites (e.g. alternative allele presence or allele dropout). It provides the whole exome sequencing data used in assessing ProSolo's performance that is not available elsewhere, namely bulk whole exome sequencing data of a patient with a constitutional mismatch repair defect (MSH6-) and their parents and siblings, a bulk whole exome sample of granulocytes from that patient and 5 single granulocytes whole exome sequenced after whole genome amplification.

  Dataset EGAD00001005929

• Genome‐wide postnatal changes in immunity following fetal inflammatory response

  The fetal inflammatory response (FIR) increases the risk of perinatal brain injury, particularly in extremely low gestational age newborns (ELGANs, < 28 weeks of gestation). One of the mechanisms contributing to such a risk is a postnatal intermittent or sustained systemic inflammation (ISSI) following FIR. The link between prenatal and postnatal systemic inflammation is supported by the presence of well‐established inflammatory biomarkers in the umbilical cord and peripheral blood. However, the extent of molecular changes contributing to this association is unknown. Using RNA sequencing and mass spectrometry proteomics, we profiled the transcriptome and proteome of archived neonatal dried blood spot (DBS) specimens from 21 ELGANs. Comparing FIR‐affected and unaffected ELGANs, we identified 782 gene and 27 protein expression changes of 50% magnitude or more, and an experiment‐wide significance level below 5% false discovery rate. These expression changes confirm the robust postnatal activation of the innate immune system in FIR‐affected ELGANs and reveal for the first time an impairment of their adaptive immunity. In turn, the altered pathways provide clues about the molecular mechanisms triggering ISSI after FIR, and the onset of perinatal brain injury.

  Study EGAS00001003635

• NHLBI TOPMed: San Antonio Family Heart Study (SAFHS)

  The San Antonio Family Heart Study (SAFHS) is a complex pedigree-based mixed longitudinal study designed to identify low frequency or rare variants influencing susceptibility to cardiovascular disease, using whole genome sequence (WGS) information from 2,590 individuals in large Mexican American 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 CVD, as well as to find novel low frequency or rare variants influencing susceptibility to CVD. WGS of the SAFHS cohort has been obtained through three efforts. Approximately 540 WGS were performed commercially at 50X by Complete Genomics, Inc (CGI) as part of the large T2D-GENES Project. The phenotype and genotype data for this group is available at dbGaP under accession number phs000462. An additional ~900 WGS at 30X were obtained through Illumina as part of the R01HL113322 "Whole Genome Sequencing to Identify Causal Genetic Variants Influencing CVD Risk" project. Finally, ~1,150 WGS at 30X WGS were obtained through Illumina funded by a supplement as part of the NHLBI's TOPMed program. Extensive phenotype data are provided for sequenced individuals primarily obtained from the P01HL45522 "Genetics of Atherosclerosis in Mexican Americans" for adults and R01HD049051 for children in these same families. Phenotype information was collected between 1991 and 2016. For this dataset, the SAFHS appellation represents an amalgamation of the original SAFHS participants and an expansion that reexamined families previously recruited for the San Antonio Family Diabetes Study (R01DK042273) and the San Antonio Family Gall Bladder Study (R01DK053889). Due to this substantial examination history, participants may have information from up to five visits. The clinical variables reported are coordinated with TOPMed and include major adverse cardiac events (MACE), T2D status and age at diagnosis, glycemic traits (fasting glucose and insulin), blood pressure, blood lipids (total cholesterol, HDL cholesterol, calculated LDL cholesterol and triglycerides). 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. PBMC derived gene expression assays for a subset of ~1,060 individuals obtained using the Illumina Sentrix-6 chip is also available from the baseline examination. The WGS data have been jointly called and are available in the current TOPMed accession (phs001215).

  Study phs001215

• Pilot_experiment_on_functional_genomics_in_osteoarthritis_RNA

  The aim of this work is to apply an integrated systems approach to understand the biological underpinnings of large joint (hip and knee) osteoarthritis which culminates in the need for total joint replacement (TJR). In this pilot we will assess the feasibility of the approach in the relevant tissue. We will obtain diseased and non-diseased tissue (cartilage and endochondral bone) following TJR, coupled with a blood sample, from 12 patients. We will characterise the 12 pairs of diseased and non-diseased tissue samples in terms of transcription (RNASeq) The pilot will help assess the feasibility of isolating sufficient levels of starting material for the different approaches, and will instigate the development of analytical approaches to synthesising the resulting data.

  Study EGAS00001001203

• Paraganglioma Smart-Seq2 Single Nuclei Sequencing Data

  Paraganglioma is a rare neuroendocrine tumor that originates from chromaffin cells of the adrenal medulla or extra-adrenal paraganglia. This study aims to investigate the heterogeneity of this tumor and to identify potential biomarkers associated with its malignancy. To achieve this, we performed single-nucleus RNA sequencing of human paraganglioma samples using the SMART-Seq2 protocol.

  Study EGAS50000001184

• Pipeline Olympics: Continuous benchmarking of computational workflows for DNA methylation sequencing data

  DNA methylation is a widely studied epigenetic mark and a powerful biomarker of cell type, age, environmental exposure, and disease. Genome-wide DNA methylation profiling is usually performed using whole-genome sequencing following selective conversion of unmethylated cytosines into thymines via bisulfite treatment or enzymatic methods. Numerous software tools facilitate processing of raw sequencing data for DNA methylation profiling, but a comprehensive benchmarking has been lacking. In this study, we systematically compared methods and tools for processing DNA methylation sequencing data. We established a dedicated benchmarking dataset comprising genome-wide DNA methylation profiling data for four reference samples using five experimental protocols each. The results of data processing were compared to highly quantitative locus-specific DNA methylation measurements available for 46 genomic loci. Based on this gold-standard reference dataset, we identified workflows that consistently demonstrated high performance. We present our results in an interactive application that provides a “living benchmark” ready for continuous updating as new workflows are proposed and require benchmarking against existing methods. In summary, our study provides guidance for any laboratory studying DNA methylation on a genome-wide scale.

  Study EGAS50000000541

• Inhibiton of the GABPB1L-containing GABP tetramer is sufficient to reverse replicative immortality in TERT promoter mutant glioblastoma cells.

  Over 50 types of cancer acquire TERT promoter mutations. These single point mutations reactivate telomerase, allowing for indefinite maintenance of telomere length and enabling cellular immortalization. The transcription factor binding site created by the point mutations specifically recruit the ETS factor GABP, a multimeric transcription factor composed of the GABPα and GABPβ subunits. GABP can form two functionally independent transcription factor species – a dimer or a tetramer – depending on which of the structurally distinct GABPβ isoforms is incorporated into the complex. In this study, we show that genetic disruption of GABPβ1L, a tetramer forming isoform of GABPβ that is dispensable in normal development, results in TERT silencing in a TERT promoter mutation dependent manner. Failure to activate TERT expression by GABPβ1L culminates in telomere dysfunction, DNA damage, and mitotic cell death exclusively in TERT promoter mutant cells. Furthermore, exogenous expression of TERT is sufficient to prevent telomere degradation and loss of cell viability in GABPβ1L-reduced lines bearing the mutant TERT promoter. Orthotopic injection of tetramer-deficient mutant TERT promoter GBM cells rendered lower tumor burden and prolonged the overall survival of the tumor-bearing mice. These results highlight the potentially widespread role of GABPB1L in enabling replicative immortality of TERT promoter cancers.

  Study EGAS00001002582

• Investigating the genetics of immunity against Salmonella in humans (2019-09-05)

  This study entails whole genome sequencing of an interleukin (IL)-12 b-1 receptor-deficient individual who presented with a chronic systemic Salmonella Enteritidis infection that did not resolve with standard IFNg and antibiotic treatment. Whole genome sequencing of the patient's parents are also included. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2019-09-05.

  Dataset EGAD00001005311

• The clinical utility of genomics in childhood cancer extends beyond targetable mutations - Cancer Panel data

  We deeply sequenced 864 cancer-associated genes and the complete genomes and transcriptomes for 300 pediatric and adolescent/young adult (AYA) patients with poor prognosis or rare tumors. Using integrative somatic-germline analyses, we assessed the clinical utility of cancer genomics in this population. Clinically actionable variants were identified in 56% of patients. Improved diagnostic accuracy led to modified management in a subset. Therapeutically targetable variants, found in 54% of patients, were of unanticipated timing and type, with over 20% of these derived from the germline. Enrichment in corroborating mutational signature 3 (‘BRCAness’) in patients with germline homologous recombination defects suggests they are drivers of pediatric cancers and potential targets for PARP inhibition. Comprehensive somatic-germline cancer genomic profiling is useful at multiple points in the care trajectory for pediatric/AYA patients, supporting its integration into early clinical management. Re-biopsy at the time of relapse should be considered, and specific attention to the mutational burden is indicated. Defective DNA repair genes in the germline may represent important targetable drivers.

  Study EGAS00001006642

• NHLBI TOPMed: Outcome Modifying Genes in Sickle Cell Disease (OMG)

  Sickle cell disease (SCD) is caused by homozygosity for a single mutation of the beta hemoglobin gene. Despite the constancy of this genetic abnormality, the clinical course of patients with SCD is remarkably variable. SCD can affect the function and cause the failure of multiple organ systems through the pathophysiologic processes of vaso-occlusion and hemolysis. These pathophysiological processes are complex and expected to impact multiple organ systems in a variety of ways. This study, therefore, was designed to identify genetic factors that predispose SCD patients to develop specific end-organ complications and to experience more or less severe clinical courses. We enrolled > 700 patients with Hb SS, Hb S-beta0 thalassemia and HbSC being followed primarily at three southeastern U.S. regional institutions (Duke University Medical Center, University of North Carolina Medical Center, and Emory University Medical Center). Medical information obtained included the presence or absence of specific targeted outcomes (overall disease severity as well as specific types of end organ damage). Clinical data include medical status (history, physical, examination, and laboratory results) and information regarding potentially confounding environmental factors. Limited plasma samples are available for correlative studies (e.g. of cytokine levels, coagulation activation). Targeted SNP for candidate gene analysis as well as GWAS has been performed on most samples. Whole genome sequencing has been conducted through the TOPMed Consortium. The subjects in this analysis were collected as part of a larger study, "Outcome Modifying Genes in Sickle Cell Disease" (OMG-SCD) aimed at identifying genetic modifiers for sickle cell disease. More information about the study can be found in Elmariah et al. (2014), PMID: 24478166. Clinical and genetic data have been used to identify genetic characteristics predisposing patients with SCD to a more or less severe overall clinical course as well as to individual organ-specific complications. It is anticipated that identification of such genetic factors will reveal new therapeutic targets individualized to specific complications of SCD, leading to improved outcomes and increased life expectancy for patients with SCD.

  Study phs001608

• NHLBI TOPMed - NHGRI CCDG: The Johns Hopkins University School of Medicine Atrial Fibrillation Genetics Study

  Atrial fibrillation (AF), the most common sustained cardiac arrhythmia, is the primary cause of many hospital admissions, and is associated with significant secondary morbidity by increasing the risk of stroke, heart failure, and all-cause mortality. The incidence of AF is on the rise, and it is projected that by the year 2050 more than 10 million patients will be affected by AF in the United States alone. Anti-arrhythmic medications have limited success in maintaining sinus rhythm, are associated with side effects, and appear ineffective at reducing mortality compared to a strategy of rate control and anticoagulation. Given the significant morbidity associated with this common arrhythmia, surgical and catheter ablation techniques have been developed to treat AF. However, despite the incorporation of various strategies for ablation, long-term recurrence rates of AF remain higher than 25 percent after ablation. Current techniques for catheter ablation of AF include pulmonary vein isolation and complex fractionated atrial electrogram (CFAE) ablation. However, the contribution of each strategy to long-term procedural success and the relative importance of each strategy for different patients remain unknown. Recent advances in cardiac imaging have allowed detailed analysis of left atrial myocardial anatomy. Parallel advances in molecular genetics have identified several candidate genes involved in familial and non-familial AF. However, the pathophysiology of AF generation and maintenance, and the potential contribution of such genetic or anatomic substrates for patient selection, and for target identification during catheter ablation have not yet been examined. Advances in molecular genetics and imaging, coupled with techniques for endocardial and epicardial mapping in the electrophysiology laboratory present an opportunity to significantly improve our understanding of (1) The relation of paroxysmal versus persistent AF with (a) structural left atrial changes (left/right atrial scar, wall thinning, pulmonary vein anomalies, and coronary sinus dilation) and with (b) candidate genetic variants. (2) The relation of candidate genetic variants with (a) structural left atrial changes and with (b) electrophysiologic properties (atrial effective refractory period (AERP) inhomogeneity, voltage abnormalities, trigger burden and location, C FAE extent and location), (3) The relation of structural left atrial changes with (a) CFAE location as targets for catheter ablation and with (b) reversible conduction block/myocardial injury after pulmonary vein isolation, and (4) Individualized endocardial targets for AF ablation based on candidate genes and anatomic substrates. The proposed study will improve our understanding of the underlying pathophysiology of AF, and may improve current techniques for treatment of this important arrhythmia.

  Study phs001598

• NSCLC PC9 erlotinib RAF1 study

  This Data Access Committee (DAC) oversees the controlled access to genomic sequencing data generated by Prof. Hoon Kim's laboratory at Sungkyunkwan University. The DAC is responsible for reviewing data access requests related to cancer genomics research, including the study on RAF1 ecDNA-mediated erlotinib resistance in NSCLC models.

  Dac EGAC50000001001

• TCS validation of 11 lung adenos

  This is the targeted capture deep sequencing (TCS) data for validation of the mutations discovered in the WES step. There are 58 bam files of TCS data including 48 tumor samples and 10 peripheral blood WBC samples.

  Dataset EGAD00001000985

• The Gene Partnership (TGP) - eMERGE Data

  The Gene Partnership (TGP) is a prospective longitudinal registry at Boston Children's Hospital (BCH) to study the genetic and environmental contributions to childhood health and disease, collect genetic information on a large number of children who have been phenotyped, and implement the Informed Cohort and the Informed Cohort Oversight Board (ICOB). The term "The Gene Partnership" reflects a partnership between researchers and participants. Children seen at BCH are offered enrollment, as are their parents and siblings. DNA is collected on all enrollees. BCH has a comprehensive EMR system, and virtually all inpatient and outpatient data are captured electronically. Clinical data in the BCH EMR is loaded in the i2b2 data warehouse which is available to investigators. Cases, phenotypes, and covariates are ascertained using the i2b2 database. Participants at BCH in TGP have consented to receive any research result and/or incidental finding that arises from studies using TGP that is approved by the Informed Cohort Oversight Board (ICOB) and is in accordance with the participants' preferences; results are returned through the Personally Controlled Health Record (PCHR). BCH and Cincinnati Children's Hospital Medical Center (CCHMC) have partnered as the Pediatric Alliance for Genomic and Electronic Medical Record (EMR) Research (PAGER) site for the eMERGE Phase II network for pediatric institutions, and the cohort for eMERGE at BCH is TGP.

  Study phs000495

• Exome sequencing of early and late passage Patient Derived Xenogratf Tumoroids with matched Patient Derived Xenogratfs and matched normal liver

  The breadth and depth at which cancer models are interrogated contribute to successful translation of drug discovery efforts to the clinic. In colorectal cancer (CRC), model availability is limited by a dearth of large-scale collections of patient-derived xenografts (PDXs) and paired tumoroids from metastatic disease, the setting where experimental therapies are typically tested. XENTURION is a unique open-science resource that combines a platform of 129 PDX models and a sister platform of 129 matched PDX-derived tumoroids (PDXTs) from patients with metastatic CRC, with accompanying multidimensional molecular and therapeutic characterization. This specific dataset is focused on a comparison of early and late passage tumoroids transcriptomes. In this study we focused our attention on early (passage 3) and late (passage 8-12) PDXTs with their matched PDXs and normal liver

  Study EGAS50000000185

• Whole genome sequencing data of paediatric KMT2A-rearranged acute lymphoblastic leukemia

  Pediatric KMT2A-rearranged leukemia is an aggressive subtype of leukemia commonly seen in infants (less tha 1 year old) and young children. It involves rearrangements of the KMT2A gene (formerly MLL) on chromosome 11q23, resulting in fusion genes that drive uncontrolled cell growth. This subtype is most often found in acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) and is associated with a poor prognosis. In infants, the 5-year event-free and overall survival rates are around 35–40%. Despite intensive chemotherapy, outcomes remain challenging, prompting ongoing research into targeted therapies and novel treatment strategies.

  Study EGAS50000001079

• RNA sequencing data of pediatric KMT2A-rearranged acute lymphoblastic leukemia

  Pediatric KMT2A-rearranged leukemia is an aggressive subtype of leukemia commonly seen in infants (less tha 1 year old) and young children. It involves rearrangements of the KMT2A gene (formerly MLL) on chromosome 11q23, resulting in fusion genes that drive uncontrolled cell growth. This subtype is most often found in acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) and is associated with a poor prognosis. In infants, the 5-year event-free and overall survival rates are around 35–40%. Despite intensive chemotherapy, outcomes remain challenging, prompting ongoing research into targeted therapies and novel treatment strategies.

  Study EGAS50000001799

• Sensitive detection of tumor mutations from blood and its application to immunotherapy prognosis

  Cell-free DNA (cfDNA) is attractive for many applications, including cancer detection, locating, and monitoring. A fundamental task underlying these applications is the SNV calling from cfDNA, which, however, faces a new challenge, namely, the generally very low tumor content in cfDNA. Thus all existing callers fail to achieve satisfactory performance. Here we present cfSNV, a method incorporating multi-layer error suppression and hierarchical mutation calling, to address this important challenge. Furthermore, by leveraging cfDNA’s comprehensive coverage of clonal landscape, for the first time cfSNV can profile mutations even in subclones. In both simulated and real patient data, cfSNV vastly outperforms existing tools, showing tens of times increase in sensitivity in detecting mutations with low allele frequency while maintaining high precision. cfSNV can enhance the clinical utilities of cfDNA by dramatically reducing the required sequencing depth and therefore reduce the cost by magnitudes, and further make the Whole-Exome-Sequencing of cfDNA a viable option. As an example, we demonstrate that cfDNA-WES allows a new biomarker to effectively select patients for immunotherapy.

  Study EGAS00001004373

• CIDR: NCI Genome Wide Predictors of Survival in Colorectal Cancer

  CIDR/Molecular Correlates: This study genotyped archived blood samples from colorectal cancer cases participating in clinical trials. The goals of this project were to identify genetic variants associated with survival outcomes treatment and treatment-related severe adverse events among patients with colorectal cancer. Another goal was to examine the impact of adding information on germline genetic loci to existing prognostic models. MOSAIC: Multicenter International Study of Oxaliplatin/ 5FU-LV in the Adjuvant Treatment of Colon Cancer (MOSAIC). A randomized, open label efficacy trial to evaluate the FOLFOX regimen versus LV5FU2 in the adjuvant treatment of stage II and III colon cancer. The primary end point was disease-free survival. CPT.ES1.604: Randomized phase 3 study of weekly irinotecan plus high-dose 5-fluorouracil (FUIRI) versus biweekly irinotecan plus 5-fluorouracil/leucovorin (FOLFIRI) as first-line chemotherapy for patients with metastatic CRC. The aim of this study was to demonstrate that a regimen without leucovorin (LV) (FUIRI) is not inferior to the standard FOLFIRI (response rate). 03-TTD-01: The purpose of this phase III, multicenter, randomized, open-label study is to evaluate the safety and efficacy of combination therapy with capecitabine and oxaliplatin (XELOX) vs. oxaliplatin and 5-fluorouracil in continous infusion (5-FU CI) as first line treatment in advanced or metastatic colorectal cancer. The primary outcome measure is time to disease progression. Secondary outcome measures are to determine safety of combination, objective response rate, time to onset of response, duration of response, time to treatment failure, one year survival time, and overall survival time. 03-TTD-01: The purpose of this phase III, multicenter, randomized, open-label study is to evaluate the safety and efficacy of combination therapy with capecitabine and oxaliplatin (XELOX) vs. oxaliplatin and 5-fluorouracil in continous infusion (5-FU CI) as first line treatment in advanced or metastatic colorectal cancer. The primary outcome measure is time to disease progression. Secondary outcome measures are to determine safety of combination, objective response rate, time to onset of response, duration of response, time to treatment failure, one year survival time, and overall survival time. N0147: Randomized phase III clinical trial for adjuvant therapy in stage III colon cancer patients enrolled at institutions across North America. Originally designed to compare three different chemotherapy regimens, and then later expanded to evaluate adding cetuximab to each original arm (leading to six total arms). Further modification later added pre-screening for KRAS mutation status, with the resulting goal to assess the potential benefit of cetuximab added to the modified sixth version of the FOLFOX regimen (mFOLFOX6) in patients with resected stage III wild-type KRAS colon cancer. Main outcome of interest is disease-free survival in patients with wild-type KRAS, while secondary end points included overall survival and toxicity. N9741: Randomized phase III trial to compare the effectiveness of various combination chemotherapy regimens in treating patients who have advanced, recurrent, or metastatic colorectal cancer that cannot be treated with surgery or radiation therapy. C-08: A Phase III Clinical Trial Comparing Infusional 5-Fluorouracil (5-FU), Leucovorin, and Oxaliplatin (mFOLFOX6) Every Two Weeks With Bevacizumab to the Same Regimen Without Bevacizumab For the Treatment of Patients With Resected Stages II and III Carcinoma of the Colon. The primary aim of the trial was to compare the relative efficacy of mFOLFOX6 + bevacizumab with that of mFOLFOX6 alone in prolonging disease-free survival and the secondary aim was to compare the relative efficacy of mFOLFOX6 + bevacizumab with that of mFOLFOX6 alone in prolonging survival.

  Study phs001290

• Tumour evolvability metrics predict recurrence in advanced localised prostate cancer (tumour data)

  There is a need for quantitative measurements of evolutionary metrics in controlled clinical trials with long term follow-up information. This is particularly true in advanced localised prostate cancer, which can recur more than a decade after diagnosis. Here we mapped genomic intra-tumour heterogeneity in 642 tumour samples from 114 patients who took part in the IMRT and DELINEATE clinical trials, for which full clinical information and 12y median follow-up was available. We concomitantly assessed phenotypic (morphological) heterogeneity using Deep Learning in 1,923 histological sections from 250 IMRT patients (fully overlapping with the genetic set). This study shows that combining genomics with AI-aided histopathology in clinical trials leads to novel clinical biomarkers. This EGA repository contains data produced from tumour samples using low coverage whole genome sequencing and a prostate cancer specific gene panel data following compression of unique molecular identifiers.

  Dataset EGAD00001010274

• Tumour evolvability metrics predict recurrence in advanced localised prostate cancer (normal data)

  There is a need for quantitative measurements of evolutionary metrics in controlled clinical trials with long term follow-up information. This is particularly true in advanced localised prostate cancer, which can recur more than a decade after diagnosis. Here we mapped genomic intra-tumour heterogeneity in 642 tumour samples from 114 patients who took part in the IMRT and DELINEATE clinical trials, for which full clinical information and 12y median follow-up was available. We concomitantly assessed phenotypic (morphological) heterogeneity using Deep Learning in 1,923 histological sections from 250 IMRT patients (fully overlapping with the genetic set). This study shows that combining genomics with AI-aided histopathology in clinical trials leads to novel clinical biomarkers. This EGA repository contains data produced from tumour samples using low coverage whole genome sequencing and a prostate cancer specific gene panel data following compression of unique molecular identifiers.

  Dataset EGAD00001010295

• Breast Cancer Genome Guided Therapy Study (BEAUTY)

  The Breast Cancer Genome Guided Therapy Study (BEAUTY) is a prospective neoadjuvant clinical study enrolling 140 women with Stage I-III breast cancer. The goals of this study were to 1) perform comprehensive sequencing of germline and tumor tissues (exome and RNA seq), 2) identify genomic alterations and perturbed pathways associated with response/resistance to standard chemotherapy, and 3) develop patient-derived xenograft (PDX) for testing of therapeutic regimens chosen on the basis of alterations identified by genetic sequencing.

  Study phs001050

• Single Suture Craniosynostosis: Gene and Pathway Discovery

  Craniosynostosis is the premature fusion of one or more of the calvarial sutures. In this work, we used genomics and network modeling to reveal genetic and developmental pathways which, when disrupted, result in premature calvarial fusion. Calvarial bone explants were obtained from children undergoing surgery for single suture craniosynostosis. Primary osteoblast cell lines were established from calvarial explants and used as an RNA source.  The data available includes subject sex, affected suture, RNA sequence variants and counts.

  Study phs002684

• Aneurysmal Subarachnoid Hemorrhage patients with or without vasospasm

  Cerebellar vasospasm is a severe complication of aneurysmal subarachnoid hemorrhage (aSAH) occurring for 30% of aSAH patients. To date, no biomarker of vasospasm occurrence exists and thus all aSAH patients undergo a preventive and dangerous treatment. In this study, we explored the miRNome of aSAH patients to detect potential expression differences between the patients developing a vasospasm (VSP+) or not (VSP-). The shared data include raw and normalized count miRNA data in aneurysmal subarachnoid hemorrhage patients with or without vasospasm.

  Study EGAS00001003092

• Investigating_the_genetics_of_immunity_against_Salmonella_in_humans

  This study entails whole genome sequencing of an interleukin (IL)-12 b-1 receptor-deficient individual who presented with a chronic systemic Salmonella Enteritidis infection that did not resolve with standard IFNg and antibiotic treatment. Whole genome sequencing of the patient’s parents are also included.This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001001664

• Transcriptome of human trophoblast stem cells derived from normal and HDP placentas

  Hypertensive disorders of pregnancy (HDP) is a disease driven by abnormal placenta formation, which is a leading cause of maternal and fetal death. For investigation of genetic and epigenetic regulation of human trophoblast differentiation, we have previously established human trophoblast stem cells (hTSCs) from first-trimester placentas. Those hTSCs were able to differentiate into extravillous trophoblasts (EVTs) and syncytiotrophoblasts (STs), and their transcriptome was similar to that of cytotrophoblasts in human placenta. However, since HDP happens in the second half of pregnancy, the conventional hTSC derivation method was not enough to investigate the nature of HDP trophoblasts. In this analysis, we improved the derivation method and successfully established the hTSCs from normal and HDP term placentas after delivery. We performed RNA-seq of normal and HDP hTSCs, and HDP hTSCs recapitulated abnormalities in gene expression reported in HDP placentas.

  Study JGAS000660

• Pseudodiastrophic dysplasia expands the known phenotypic spectrum of defects in proteoglycan biosynthesis

  Pseudodiastrophic dysplasia (PDD) is a severe skeletal dysplasia associated with prenatal manifestation and early lethality. Clinically, PDD is classified as a ‘dysplasia with multiple joint dislocations’ however, the molecular aetiology of the disorder is currently unknown. In order to identify the genetic defects underlying PDD, we performed whole exome sequencing (WES) on 3 patients from 2 unrelated families, clinically diagnosed with PDD. WES resulted in the identification of bi-allelic variants in the established skeletal dysplasia genes, B3GAT3 (Family 1) and CANT1 (Family 2). Mutations in these genes have previously been reported to cause ‘multiple joint dislocations, short stature, and craniofacial dysmorphism with or without congenital heart defects’ (B3GAT3) and Desbuquois dysplasia 1 (CANT1); disorders in the same nosological group as PDD. Follow-up of the B3GAT3 variants demonstrated significantly reduced B3GAT3/GlcAT-I expression. Downstream in vitro functional analysis revealed abolished biosynthesis of glycosaminoglycan side chains on proteoglycans. Functional evaluation of the CANT1 variant showed impaired nucleotidase activity, which results in inhibition of glycosaminoglycan synthesis through accumulation of uridine diphosphate. For the families described in this study, the PDD phenotype was caused by mutations in the known skeletal dysplasia genes B3GAT3 and CANT1, demonstrating the advantage of genomic analyses in delineating the molecular diagnosis of skeletal dysplasias. This finding expands the phenotypic spectrum of B3GAT3- and CANT1- related skeletal dysplasias to include PDD, and highlights the significant phenotypic overlap of conditions within the proteoglycan biosynthesis pathway.

  Study EGAS00001004145

• DCIS fresh frozen fragmentomics dataset

  Ductal carcinoma in situ (DCIS) is a non-obligate precursor lesion of breast cancer (BC). Often detected by mammography, most cases are managed through surgical and/or radiotherapy approaches. Today, it is not possible to predict which patients will progress to invasive disease. Here, we evaluated high-depth whole-genome sequenced (WGS) DCIS, enriched for highgrade clinical lesions, to understand whether deep WGS could reveal biological insights and/or personalized therapeutic vulnerabilities that may be targetable. We find genomic locations that are likely susceptible to producing the initiating lesion for structural variations (SVs) prone to subsequent evolution, termed SHOREs (Susceptibility HOtspots for Rearrangements and ongoing Evolution). We additionally highlight individualized therapeutic potential that would otherwise not be appreciable without WGS. We posit that holistic WGS profiling could offer a more precise stratification approach, discerning higher-risk cases for prospective clinical studies on personalized therapies, from truly low-risk cases suitable for active monitoring. To substantiate our WGS findings, we also performed RNAseq on the same samples, this EGA study contains the RNAseq data.

  Study EGAS50000001475

• Coding and non-coding drivers of mantle cell lymphoma identified through exome and genome sequencing

  Mantle cell lymphoma (MCL) is an uncommon B-cell non-Hodgkin lymphoma (NHL) that is incurable with standard therapies. The genetic drivers of this cancer have not been firmly established and the features that contribute to differences in clinical course remain limited. To extend our understanding of the biological pathways involved in this malignancy, we performed a large-scale genomic analysis of MCL using data from 51 exomes and 34 genomes alongside previously published exome cohorts. To confirm our findings, we re-sequenced the genes identified in the exome cohort in 191 MCL tumors, each having clinical follow-up data. We confirmed the prognostic association of TP53 and NOTCH1 mutations. Our sequencing revealed novel recurrent non-coding mutations surrounding a single exon of the HNRNPH1 gene. In RNA-seq data from 103 of these cases, MCL tumors with these mutations had a distinct imbalance of HNRNPH1 isoforms. This altered splicing of HNRNPH1 was associated with inferior outcomes in MCL and showed a significant increase in protein expression by immunohistochemistry. We describe a functional role for these recurrent non-coding mutations in disrupting an auto-regulatory feedback mechanism, thereby deregulating HNRNPH1 protein expression. Taken together, these data strongly implicate a role for aberrant regulation of mRNA processing in MCL pathobiology.

  Study EGAS00001004289

• HeartShare - Extant Datasets - Harmonized Clinical Trials Collection

  Heart failure with preserved ejection fraction (HFpEF) prevalence is rising with an aging population and contributing comorbidities, such as obesity and diabetes. The Get With The Guidelines - Heart Failure (GWTG-HF) study showed that the proportion of hospitalized HFpEF patients rose from 2005 to 2010, and this trajectory continued to increase through 2020. HFpEF patients have a poor 5-year outcome with a 75% mortality rate. Taken together, these data suggest that HFpEF may be the dominant HF subtype in the future, affecting approximately 1 in 10 adults during their lifetime.In addition to its increasing prevalence, HFpEF is a heterogeneous syndrome with multiple pathophysiological processes and varied clinical presentations. There is an urgent need to improve understanding of different HFpEF phenotypes to match patients with interventions based on their unique subtype. Phenomapping studies have identified between two and six HFpEF clusters/phenogroups with shared features. Of these, three overlapping phenotypes repeatedly arise: an 'older, vascular aging' phenotype, 'metabolic, obese' phenotype, and 'relatively younger, natriuretic peptide (NP) deficiency' phenotype. Continued refinement of these HFpEF subtypes is needed to identify distinct characteristics and underlying biologic and molecular mechanisms towards therapeutic development and future precision trials with improved diagnostic criteria and treatment including prevention.The HeartShare extant datasets collection consists of selected completed trials on HFpEF which have been harmonized for the purpose identifying and defining subtypes. The goal is to identify HFpEF subtypes that have a common pathophysiology. Through the HeartShare extant datasets collection, users can request access to both the harmonized data and the individual trial datasets.To request access to this study collection, select phs003989 in the dbGaP when submitting a data access request. The following clinical trials and harmonized data is available through this collection:Study NameHandleAccessionConsent GroupsSurgical Treatment for Ischemic Heart FailureBioLINCC_STICHphs003493.v1.p1GRUHeart Failure Network Aldosterone Targeted Neurohormonal Combined with Natriuresis TherapyBioLINCC_HFN_ATHENAphs003506.v1.p1GRUHeart Failure Network - Effectiveness of Ultrafiltration in Treating People With Acute Decompensated Heart Failure and Cardiorenal SyndromeBioLINCC_HFN_CARRESSphs003510.v1.p1GRUHeart Failure Network: Diuretic Optimization Strategies Evaluation in Acute Heart FailureBioLINCC_HFN_DOSEphs003524.v1.p1GRUHeart Failure Network - Xanthine Oxidase Inhibition for Hyperuricemic Heart Failure PatientsBioLINCC_EXACT_HFphs003533.v1.p1GRUHeart Failure Network: Functional Impact of GLP-1 for Heart Failure TreatmentBioLINCC_HFN_FIGHTphs003542.v1.p1GRUHeart Failure Network - Nitrate's Effect on Activity Tolerance in Heart Failure with Preserved Ejection FractionBioLINCC_HFN_NEATphs003548.v1.p1GRUHeart Failure Network - Phosphodiesterase-5 Inhibition to Improve Clinical Status and Exercise Capacity in Diastolic Heart FailureBioLINCC_HFN_RELAXphs003565.v1.p1GRUHeart Failure Network - Renal Optimization Strategies Evaluation in Acute Heart Failure and Reliable Evaluation of DyspneaBioLINCC_HFN_ROSEphs003589.v1.p1GRUHeart Failure: A Controlled Trial Investigating Outcomes of Exercise TrainingBioLINCC_HF_ACTIONphs003599.v1.p1HMBHeart Failure: A Controlled Trial Investigating Outcomes of Exercise TrainingBioLINCC_HF_ACTIONphs003599.v1.p1HMB-NPUGuiding Evidence Based Therapy Using Biomarker Intensified Treatment in Heart FailureBioLINCC_GUIDE_ITphs003621.v1.p1GRUSudden Cardiac Death in Heart Failure TrialBioLINCC_SCD_HeFTphs003654.v1.p1GRUTreatment of Preserved Cardiac Function Heart Failure With an Aldosterone AntagonistBioLINCC_TOPCATphs003665.v1.p1HMB-MDSHeart Failure Network - Inorganic Nitrite Delivery to Improve Exercise Capacity in HFpEFBioLINCC_HFN_INDIEphs003667.v1.p1GRUStudies of Left Ventricular DysfunctionBioLINCC_SOLVDphs003668.v1.p1GRUEvaluation Study of Congestive Heart Failure and Pulmonary Artery Catheterization EffectivenessBioLINCC_ESCAPEphs003782.v1.p1GRU

  Study phs003989

• A small cell lung cancer genome reports complex tobacco exposure signatures

  Cancer is driven by mutation. Worldwide, tobacco smoking is the major lifestyle exposure that causes cancer, exerting carcinogenicity through 60 chemicals that bind and mutate DNA. Using massively parallel sequencing technology, we sequenced a small cell lung cancer cell line, NCI-H209, to explore the mutational burden associated with tobacco smoking. 22,910 somatic substitutions were identified, including 132 in coding exons. Multiple mutation signatures testify to the cocktail of carcinogens in tobacco smoke and their proclivities for particular bases and surrounding sequence context. Effects of transcription-coupled repair and a second, more general expression-linked repair pathway were evident. We identified a tandem duplication that duplicates exons 3-8 of CHD7 in-frame, and another two lines carrying PVT1-CHD7 fusion genes, suggesting that CHD7 may be recurrently rearranged in this disease. These findings illustrate the potential for next-generation sequencing to provide unprecedented insights into mutational processes, cellular repair pathways and gene networks associated with cancer.

  Study EGAS00000000051

• InterPregGen-GWAS-UZB-1

  GWAS genotype data for maternal and fetal (baby) cases of preeclampsia and controls from Uzbekistan. This dataset is a component of the InterPregGen FP7 project. DNA samples for this component were collected by InterPregGen Consortium members in Tashkent, Uzbekistan at the Institute of Immunology, Uzbek Academy of Sciences and at the Republic Specialized Scientific Practical Medical Centre of Obstetrics and Gynecology

  Dataset EGAD00010001918

• Whole-Genome Sequencing (WGS) of a Malignant Granular Cell Tumor (GCT) with Metabolic Response to Pazopanib

  We report one case study of a malignant granular cell tumor patient with metabolic response to pazopanib. In this study, we used whole-genome sequencing of the tumor with the matched blood to characterize the somatic mutation profile in this tumor. This is the first reported whole-genome sequencing study of the rare malignant granular cell tumor.

  Study phs000978

• The clinical utility of genomics in childhood cancer extends beyond targetable mutations - WGS data

  We deeply sequenced 864 cancer-associated genes and the complete genomes and transcriptomes for 300 pediatric and adolescent/young adult (AYA) patients with poor prognosis or rare tumors. Using integrative somatic-germline analyses, we assessed the clinical utility of cancer genomics in this population. Clinically actionable variants were identified in 56% of patients. Improved diagnostic accuracy led to modified management in a subset. Therapeutically targetable variants, found in 54% of patients, were of unanticipated timing and type, with over 20% of these derived from the germline. Enrichment in corroborating mutational signature 3 (‘BRCAness’) in patients with germline homologous recombination defects suggests they are drivers of pediatric cancers and potential targets for PARP inhibition. Comprehensive somatic-germline cancer genomic profiling is useful at multiple points in the care trajectory for pediatric/AYA patients, supporting its integration into early clinical management. Re-biopsy at the time of relapse should be considered, and specific attention to mutational burden is indicated. Defective DNA repair genes in the germline may represent important targetable drivers.

  Study EGAS00001006610

• High MAPK Activity Leading to Reduced WNT Signaling Drives Metastasis in Colorectal Cancer

  Colorectal cancer, a leading cause of cancer-related mortality due to distant metastases, is driven by activating mutations in the Wnt and MAPK pathways. Understanding the interplay between these crucial pathways during metastatic progression is essential for developing effective treatments. Here we developed an immunocompetent mouse model of metastatic colorectal cancer using in vivo orthotopic passaging. We demonstrate that highly metastatic tumor cells exhibit chromosomal amplifications in MAPK pathway genes, leading to increased MAPK activity, which in turn suppresses Wnt-associated transcriptional programs, including stem cell-associated genes. Inhibiting mutant KrasG12D effectively reversed this metastatic transcriptional state, reducing MAPK-driven gene expression and restoring Wnt activity. Notably, this treatment significantly curtailed lung metastases and reduced liver metastases during early seeding stages. Analysis of CRC patient data revealed that high MAPK activity and the associated metastatic gene signature correlated with poorer survival outcomes. These findings underscore that the plasticity of metastasis-initiating cells in CRC arises from the opposing roles of MAPK and Wnt signaling, despite their synergistic importance in colon tumor initiation.

  Study EGAS50000001231

• ENU_HT_29_BRAF_Triple_Therapy_Clones

  KRAS mutant CRC is currently in clinical trial with a combination of a MEK and Akt inhibitor. These patients will likely develop resistance to this combination. We aim to identify the mechanisms of resistance via ENU mutagenesis, with a view to identifying additional therapeutics which have the ability to overcome this resistance.

  Study EGAS00001001778

• Single_Cell_Targeted_Sequence_Capture

  This study is to ascertain whether it is feasible to extract single cell from a tumour, perform amplification, generate a library and sequence a targeted pulldown.

  Study EGAS00001000435

• South Asia Rheumatic Heart Disease Genetics Network

  Rheumatic heart disease (RHD) is a major cause of cardiovascular death and disability amongst young adults. Building on a sample collection established for and genotyped in several earlier successful candidate gene studies, this case-control study investigated host genetic susceptibility to RHD using a genome-wide approach. The current dataset comprises over 850 individuals recruited in Uttar Pradesh, India, including cases of RHD based on echocardiographic diagnosis and controls recruited on the basis of normal echocardiograms. For this analysis all available samples were genotyped using the Illumina HumanCore-24 BeadChip platform. Efforts are now underway to establish new sample collections in other areas of India as well as Pakistan and later other neighbouring countries.

  Study EGAS00001003565

• Genotyping of GM samples

  This dataset contains a vcf file for 99 GM individuals genotyped on the Illumina HumanOmni2.5 array . The vcf file is originated after imputation (IMPUTE2) and filtering for minor allele frequency MAF≥0.05, imputation confidence score INFO of >0.4 and Hardy-Weinberg Equilibrium (HWE) p>1e-06, yielding ~6.3 million variants.

  Dataset EGAD00001010255

• using-ega-account

  Using your EGA account The purpose of this page is to help you access and download the data you have been granted permission to view through your EGA account. To obtain an EGA account please register here. Once your account is created, you can find details on how to manage your EGA account here. EGA access policy (New account holders please read) Access to EGA services are only provided to EGA account holders. EGA accounts are created, updated and closed upon direct instruction from the relevant DAC contact, using the EGA account management tools or through EGA Helpdesk. As part of the EGA account creation process, the EGA account holder must reset their password when instructed. Password resets are checked and verified usually within 24 business hours, during which time the EGA account is inaccessible. EGA accounts are assigned on an individual basis for the exclusive use of the registered EGA account holder; log-in details must remain private and only be used by the EGA account holder. Controlled access data files are only provided, in accordance to the permissions set by the DAC, to EGA account holders. EGA controlled access data files are encrypted prior to download and must be decrypted on the EGA account holders side. EGA account holders are provided access to the EGA download streamer to download access approved datasets and files therein. The EGA download streamer represents the primary means for the EGA account holder to download access approved datasets and files therein. EGA account holders may be provided with an EGA download account for accessing approved datasets and files therein, using FTP or Aspera in response to clearly defined technical reasons, which may restrict the use of the EGA download streamer. It is the sole responsibility of the EGA account holder to ensure full compliance to all terms and conditions of the Data Access Agreement are met once data is downloaded from the EGA. Should you move institute you must contact all Data Access Committee's contacts to update your details and, if necessary, re-apply for data access. The Data Access Agreement (DAA) is a contract made between the DAC and the EGA account holder; the EGA is not responsible for enforcing the DAA. EGA reserves the right to place EGA accounts 'onhold', pending DAC approval to re-activate, should EGA account 'misuse' be suspected. Further information Introduction to the EGA Frequently Asked Questions Subscribe to the EGA mailing list

  Documentation using-ega-account

• Using your EGA account

  Using your EGA account The purpose of this page is to help you access and download the data you have been granted permission to view through your EGA account. To obtain an EGA account please register here. Once your account is created, you can find details on how to manage your EGA account here. EGA access policy (New account holders please read) Access to EGA services are only provided to EGA account holders. EGA accounts are created, updated and closed upon direct instruction from the relevant DAC contact, using the EGA account management tools or through EGA Helpdesk. As part of the EGA account creation process, the EGA account holder must reset their password when instructed. Password resets are checked and verified usually within 24 business hours, during which time the EGA account is inaccessible. EGA accounts are assigned on an individual basis for the exclusive use of the registered EGA account holder; log-in details must remain private and only be used by the EGA account holder. Controlled access data files are only provided, in accordance to the permissions set by the DAC, to EGA account holders. EGA controlled access data files are encrypted prior to download and must be decrypted on the EGA account holders side. EGA account holders are provided access to the EGA download streamer to download access approved datasets and files therein. The EGA download streamer represents the primary means for the EGA account holder to download access approved datasets and files therein. EGA account holders may be provided with an EGA download account for accessing approved datasets and files therein, using FTP or Aspera in response to clearly defined technical reasons, which may restrict the use of the EGA download streamer. It is the sole responsibility of the EGA account holder to ensure full compliance to all terms and conditions of the Data Access Agreement are met once data is downloaded from the EGA. Should you move institute you must contact all Data Access Committee's contacts to update your details and, if necessary, re-apply for data access. The Data Access Agreement (DAA) is a contract made between the DAC and the EGA account holder; the EGA is not responsible for enforcing the DAA. EGA reserves the right to place EGA accounts 'onhold', pending DAC approval to re-activate, should EGA account 'misuse' be suspected. Further information Introduction to the EGA Frequently Asked Questions Subscribe to the EGA mailing list

  Documentation download/using_ega_account

• GCAT | Genomes for life

  The GCAT project is a prospective cohort study that was designed to recruit the general population of Catalonia, the north-east region of Spain. This study is a long-term genomic, environmental and lifestyle cohort project that aims to evaluate and track multiple pathologies as well as biologically related traits. By the end of 2017, the GCAT Study had recruited a total of 20 000 participants aged 40–65 years. Participants who agreed to take part in the study completed a self-administered computer-driven questionnaire, and underwent blood pressure, cardiac frequency and anthropometry measurements. For each participant, blood plasma, blood serum and white blood cells are collected at baseline. The GCAT Study has access to the electronic health records of the Catalan Public Healthcare System. Participants are followed biannually for/during, at least, 20 years after recruitment. Therefore, the GCAT Study offers a unique opportunity to integrate diverse data to allow the identification of novel relations among different biomarkers and conditions. Results may lead to the development of new genetic, genomic, epigenomic and proteomic diagnoses and screening tests, as well as new public health recommendations. The only currently available population-based prospective cohort study in Spain to the date, including more than 4899 genotyped participants and 800 whole genome sequences is now stored in the EGA archive under accession id EGAS00001003018.

  Blog gcat-genomes-for-life

• MethCORR: DNA Methylation-based Characterization, Classification and Prognostication of Colorectal Cancer using Archival Formalin-fixed, Paraffin-embedded Tissue

  Transcriptional characterization and classification has potential to resolve the inter-tumor heterogeneity of colorectal cancer (CRC) and improve patient management. Yet, robust transcriptional profiling is difficult using formalin-fixed, paraffin-embedded (FFPE) samples, which complicates testing in clinical and archival material. We present MethCORR, an approach that allows uniform molecular characterization and classification of fresh-frozen and FFPE samples. MethCORR identifies genome-wide correlations between RNA expression and DNA methylation in fresh-frozen samples. This information is used to infer gene expression information in FFPE samples from their DNA methylation profiles. MethCORR was applied to methylation profiles from 877 fresh-frozen and FFPE samples and comparative analysis identified the same two major subtypes in four independent cohorts. Furthermore, subtype-specific prognostic biomarkers that better predicted relapse-free survival (HR=2.66, 95% CI [1.67-4.22], P<0.001) than TNM staging and MSI status were identified and validated using DNA methylation-specific PCR assays. The MethCORR approach is general, and may be similarly successful for other cancer types.

  Study EGAS00001004293

• BIONi010-C-8 / SAMEA4454011 WGS data

  The iPSC line BIONi010-C-8 / SAMEA4454011 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-8 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001028

• SIGi001-A-13 / SAMEA104386250 WGS data

  The iPSC line SIGi001-A-13 / SAMEA104386250 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-13 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001031

• BIONi010-C-3 / SAMEA4342740 WGS data

  The iPSC line BIONi010-C-3 / SAMEA4342740 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-3 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001034

• BIONi010-C-7 / SAMEA4454010 WGS data

  The iPSC line BIONi010-C-7 / SAMEA4454010 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-7 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001035

• BIONi010-C-6 / SAMEA4454009 WGS data

  The iPSC line BIONi010-C-6 / SAMEA4454009 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-6 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001037

• BIONi010-C-9 / SAMEA4454012 WGS data

  The iPSC line BIONi010-C-9 / SAMEA4454012 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-9 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001040

• SIGi001-A-3 / SAMEA4448571 WGS data

  The iPSC line SIGi001-A-3 / SAMEA4448571 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-3 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001041

• BIONi010-C-4 / SAMEA4452060 WGS data

  The iPSC line BIONi010-C-4 / SAMEA4452060 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-4 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001043

• EDi014-A / SAMEA4459369 WGS data

  The iPSC line EDi014-A / SAMEA4459369 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi014-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001051

• EDi014-B / SAMEA4459371 WGS data

  The iPSC line EDi014-B / SAMEA4459371 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi014-B is available for research use at www.EBiSC.org.

  Dataset EGAD50000001053

• SIGi001-A-9 / SAMEA4447499 WGS data

  The iPSC line SIGi001-A-9 / SAMEA4447499 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-9 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001095

• SIGi001-A-8 / SAMEA4448777 WGS data

  The iPSC line SIGi001-A-8 / SAMEA4448777 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-8 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001093

• SIGi001-A-5 / SAMEA4448708 WGS data

  The iPSC line SIGi001-A-5 / SAMEA4448708 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-5 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001092

• SIGi001-A-4 / SAMEA4448632 WGS data

  The iPSC line SIGi001-A-4 / SAMEA4448632 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-4 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001088

• SIGi001-A-6 / SAMEA4447426 WGS data

  The iPSC line SIGi001-A-6 / SAMEA4447426 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-6 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001078

• SIGi001-A-2 / SAMEA4451116 WGS data

  The iPSC line SIGi001-A-2 / SAMEA4451116 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-2 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001077

• SIGi001-A-12 / SAMEA104237570 WGS data

  The iPSC line SIGi001-A-12 / SAMEA104237570 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-12 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001076

• SIGi001-A-11 / SAMEA4451118 WGS data

  The iPSC line SIGi001-A-11 / SAMEA4451118 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-11 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001075

• SIGi001-A-10 / SAMEA4451117 WGS data

  The iPSC line SIGi001-A-10 / SAMEA4451117 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-10 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001074

• SIGi001-A-1 / SAMEA4451096 WGS data

  The iPSC line SIGi001-A-1 / SAMEA4451096 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-1 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001073

• BIONi010-C-2 / SAMEA4342705 WGS data

  The iPSC line BIONi010-C-2 / SAMEA4342705 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-2 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001068

• BIONi010-C-5 / SAMEA4452061 WGS data

  The iPSC line BIONi010-C-5 / SAMEA4452061 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-5 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001062

• SIGi001-A-7 / SAMEA4448730 WGS data

  The iPSC line SIGi001-A-7 / SAMEA4448730 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-7 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001060

• Genomic and transcriptomic analysis on hepatocarcinogenesis after HCV eradication

  Little is known about the genomic and transcriptomic features of hepatocellular carcinoma developing after HCV eradication (SVR-HCC). In this study, we aimed to unveil the genomic and transcriptomic basis of hepatocarcinogenesis after SVR.

  Study JGAS000234

• Variant calling from CC220-MM-001 cohorts A,B,D

  These are genomic and transcriptomic high risk molecular segments for 167 samples collected at baseline from deidentified patients enrolled in cohorts A,B or D in the CC-220-MM-001 clinical study. Data are provided in a patient call table in csv format. Calls are generated from WGS data with mutations called by mutect2 best practices pipeline, CNV calls from Battenberg; and RNA-seq aligned with star aligner and quantified by Salmon.

  Dataset EGAD50000000388

• Whole exome sequencing of an invasive diffuse intrinsic pontine glioma sampled from different sites

  The lateral ventricle subventricular zone (SVZ) is a frequent site of high-grade glioma (HGG) spread and tumor invasion of the SVZ is a predictor of a worse clinical prognosis. A range of HGG types invade the stem cell niche of the SVZ, including both adult glioblastoma and pediatric high-grade gliomas such as diffuse intrinsic pontine glioma (DIPG). The cellular and molecular mechanisms mediating this frequent invasion of the SVZ are poorly understood. Here we demonstrate that neural precursor cell (NPC):glioma cell communication underpins the propensity of glioma to colonize the SVZ. SVZ NPCs secrete chemoattractant signals toward which glioma cells home. Biochemical and proteomic analyses of factors secreted by SVZ NPCs revealed a discrete list of candidate proteins. Necessity and sufficiency testing implicated the neurite outgrowth-promoting factor pleiotrophin, along with three required binding partners (secreted protein acidic and rich in cysteine (SPARC), SPARC-like protein 1, and heat shock protein 90B), as key mediators of this chemoattractant effect. Pleiotrophin protein expression is strongly enriched in the SVZ, and knockdown of pleiotrophin expression starkly reduced glioma invasion of the SVZ in the adult murine brain. Pleiotrophin, in complex with the three binding partners, activated the Rho/ROCK pathway in DIPG cells, and inhibition of ROCK resulted in decreased DIPG invasion toward SVZ neural precursor cell-secreted factors. These findings demonstrate a pathogenic role for neural precursor cell – glioma interactions and potential therapeutic targets to limit glioma invasion.

  Study EGAS00001002326

• Establishment of an iPSC Repository Derived from Healthy Volunteers

  Understanding the interaction between genetic variation and epigenetic variation remains a challenge due to the confounding role of environmental factors. We propose that human induced pluripotent stem cells (iPSCs) are an excellent model to study the relationship between genetic variation and epigenetic variation while controlling for consistent environmental factors. In this study, we have created a comprehensive resource of high-quality genomic, epigenomic, and transcriptomic data of six iPSC lines and three iPS-derived cell types (NSC, Motor Neuron, Monocyte) from three healthy donors. We found that epigenetic variation is most strongly associated with genetic variation at the iPSC stage, and that relationship weakens as epigenetic variation increases in the differentiated cells. Additionally, cell-type is a stronger source of epigenetic variation than genetic variation, highlighting that humans are far more similar than they are different, regardless of genetic background. Further, we have elucidated a utility of studying epigenetic variation in iPSCs and their derivatives for identifying important loci for GWAS studies and the cell-types in which they may be acting.

  Study phs003649

• Whole_Exome_Sequencing_for_Characterization_of_Disease_Causing_Mutations_in_two_Pakistani_Families_Suffering_from_Autosomal_Recessive_Ocular_Disorders_

  We propose to use whole exome Agilent solutionprobes and paired end Illumina sequencing to sequence 4 individualsfrom two families suffering from novel autosomal recessive disease[microphthalmia, MOP (OMIM %251600) and non-syndromic persistenthyperplastic primary vitreous, PHPV (OMIM %611311)]. Selectedcandidate variants will subsequently be genotyped in the remainingfamily members in Pakistan with the aim of identifying the rarehomozygous recessive mutations responsible for the disease phenotype. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001000026

• STAMPEED: Myocardial Infarction Genetics Consortium (MIGen)

  Myocardial infarction (MI) is a common complex disease and the leading cause of death and disability worldwide. The genetic basis of this disease is largely unknown. It has been thought that early-onset MI events would have a substantially greater heritability, thus making DNA collections with younger individuals desirable. More recently, genome-wide association studies have become feasible through the development of whole genome arrays and a large catalogue of common variants reported in the International HapMap database. This study aims to use Affymetrix genotyping platform to do a whole genome scan in 3000 early-onset MI cases and 3000 matched controls from 6 study collection sites.

  Study phs000294

• Immuno-genomic landscape of osteosarcoma

  Osteosarcoma is an orphan disease affecting children and young adults that has seen little to no progress in survival outcomes for >30 years. Despite having heavily rearranged genomes, to date, clinical trials with immunotherapy have shown no benefit for patients with osteosarcoma. In this study, we conducted the first multi-platform immune profiling (whole genome, transcriptome, T-cell receptor sequencing, immunohistochemistry and reverse phase protein array) on every available pediatric and adult osteosarcoma patients from our institution (N = 48) with the goal of describing immune features that may contribute to immunotherapy resistance.

  Study EGAS00001004197

• Immuno-genomic landscape of osteosarcoma

  Osteosarcoma is an orphan disease affecting children and young adults that has seen little to no progress in survival outcomes for >30 years. Despite having heavily rearranged genomes, to date, clinical trials with immunotherapy have shown no benefit for patients with osteosarcoma. In this study, we conducted the first multi-platform immune profiling (whole genome, transcriptome, T-cell receptor sequencing, immunohistochemistry and reverse phase protein array) on every available pediatric and adult osteosarcoma patients from our institution (N = 48) with the goal of describing immune features that may contribute to immunotherapy resistance.

  Study EGAS00001003887

• Discovering the Genetic Basis of Human Neuroblastoma: A Gabriella Miller Kids First Pediatric Research Program (Kids First) Project

  The Gabriella Miller Kids First Pediatric Research Program (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in pediatric cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource). All of the WGS and phenotypic data from this study are accessible through dbGaP and kidsfirstdrc.org, where other Kids First datasets can also be accessed. Children with disseminated neuroblastoma have a very high risk of treatment failure and death despite receiving intensified chemotherapy, radiation therapy and immunotherapy. The long-term goal of our research program is to ultimately improve neuroblastoma cure rates by first comprehensively defining the genetic basis of the disease. The central hypothesis to be tested here is that neuroblastoma arises largely due to the epistatic interaction of common and rare heritable DNA variation. Here we will perform a comprehensive whole genome sequencing of 563 quartets of neuroblastoma patient germline and diagnostic tumor DNAs and germline DNAs from both parents. The case series was recently collected through a Children's Oncology Group epidemiology clinical trial and is robustly annotated with complete demographic (age, sex, race, ethnicity), clinical (e.g. age at diagnosis, stage, risk group), epidemiologic (parental dietary and exposure questionnaire) and biological (e.g. tumor MYCN status and multiple other tumor genomic measures) co-variates. Subjects were consented for genetic research and DNA is immediately available for shipment for sequencing. We propose Illumina-based whole genome sequencing in the 593 "trio" germline samples (Aim 1; due to missing parent: 487 full neuroblastoma triads, 106 child-single parent dyads = 1673 whole genome sequences) and matched diagnostic tumor DNA (Aim 2; N=366) at 30x sequencing depth (N=2039 whole genome sequences). Also in Aim 2 we will perform whole exome (100x) and RNA sequencing on the 366 tumor DNA and 228 tumor RNA samples from this cohort. Finally, we propose a pilot study of structural variation using long-range sequencing in 10 non-overlapping tumor samples chosen based on potentially relevant chromosomal alterations discovered with conventional NGS. Thus, a total of 2277 individual samples and 2655 sequences will be generated. We will use our established analytic pipeline that is currently being used to study the germline genomes of all cases sequenced through the NCI supported Therapeutically Applicable Research to Generate Effective Treatments program. We plan a three-stage analytic approach, first focusing on classic de novo and inherited Mendelian damaging alterations. We will next integrate our extensive epigenomic data from human neuroblastoma cell lines and genome-wide association study data (N=5,703 neuroblastoma cases to date) to guide a comprehensive assessment of noncoding variants that influence tumor initiation with a recently established analytic pipeline. Finally, we will utilize the tumor DNA analyses to inform relevance via somatic gain or loss of function effects at the sequence and/or copy number levels. All data generated in this project will be immediately placed into the Genomic Data Commons (GDC) and we will compute within this environment by importing our analytic pipelines into the GDC. These data will be fully integrated into the Kids First Data Resource and freely shared with all academically qualified petitioners. This comprehensive data set derived from a large and richly phenotyped series of neuroblastoma DNA quartets will be integrated with existing germline and/or tumor genomic data from over 6,000 neuroblastoma subjects (but none with matched patient-parent germline sequencing data) to provide an unparalleled opportunity to comprehensively discover the genetic basis of neuroblastoma.

  Study phs001436

• Studying the single cell characteristics of pancreatic cancer

  Pancreatic cancer is a dangerous malignancy in the pancreas. In this study we use single-cell RNA sequencing technique to help understand the transcriptome characteristics of pancreatic tumor cells. This study help understands the complex microenvironment of pancreatic tumors and will likely to benefit clinical research of pancreatic cancer treatments.

  Study EGAS00001003889

• Spatial_transcriptome_analysis_of_Paediatric_Thymus

  Cell atlas of Paediatric Thymus Cell atlas of Paediatric Thymus - The Human Cell Atlas initiative is an ambitious global research effort which aims to describe every cell in the human body across all developmental stages to generate a reference map to accelerate progress in science and medicine particularly relating to human development and disease. The initiative is led by investigators based at the Wellcome Sanger Institute and the Broad Institute of MIT and Harvard and funding support from the Wellcome and NIH. We aim to interrogate the cellular composition and molecular regulators underpinning a cells identity through; genetic and genomic analysis, expression analysis, non-identifiable video imaging and cell line and organoid production, as well as, computational algorithms to predict cellular developmental trajectories and cell-cell interactions. We will subsequently validate these findings in situ using spatial genomic and imaging technologies e.g. immunohistochemistry, RNAscope, in situ sequencing and spatial transcriptomic analyses. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001004281

• Genomic landscape of poorly differentiated thyroid carcinoma

  Poorly differentiated thyroid carcinoma (PDTC) is a rare and aggressive subtype of thyroid cancer with limited molecular characterization. This study aims to define the somatic mutational landscape of PDTC using whole-genome sequencing. Paired tumour and matched normal blood samples were collected from six patients undergoing surgery. The overarching goal is to identify recurrent mutations, structural variants, and other genomic alterations associated with tumour aggressiveness and poor clinical outcomes.

  Study EGAS50000001134

• GAW16 Framingham and Simulated Data

  Important links to apply for individual-level data Genetic Analysis Workshop Instructions to Request Authorized Access Data Use Certification Requirements (DUC) Apply here for controlled access to individual level data Research Use Statement Questions regarding GAW16 should be directed to Vanessa Olmo at vanessa@business-endeavors.com. Problem 2: Description of the Framingham Heart Study In GAW16, we use data drawn from the Framingham Heart Study. The Framingham Heart Study — under the direction of National Heart, Lung, and Blood Institute; NHLBI — began in 1948 with the recruitment of adults from the town of Framingham, Massachusetts. At the time, little was known about the general causes of heart disease and stroke, but the death rates for cardiovascular disease (CVD) had been increasing steadily since the beginning of the 20th century and had become an American epidemic. The Framingham Heart Study is now conducted in collaboration with Boston University. The objective of the Framingham Heart Study was to identify the common factors or characteristics that contribute to CVD by following its development over a long period of time in a large group of participants who had not yet developed overt symptoms of CVD or suffered a heart attack or stroke. Between 1948 and 1953 the researchers recruited 5,209 subjects (2,336 men and 2,873 women) between the ages of 29 and 62 from the town of Framingham, Massachusetts and began the first round of extensive physical examinations and lifestyle interviews that they would later analyze for common patterns related to CVD development. Subjects were recruited from lists of addresses recorded for the town. Two out of every three households were approached for participation in the study. While there was no intention to recruit families for family studies, the plan was to recruit all household members in the ages 30-60 within each house that was selected for study. Hence, many biologically related individuals were recruited, including 1644 spouse pairs. Since 1948, these participants have returned to the study every two years for a detailed medical history, physical examination, and laboratory tests. Now in 2008 at 60 years of follow up, there remain about 500 participants from this cohort. Between 1971 and 1975 the study enrolled a second-generation group — 5,124 of the original participants' children and the spouses of these children — to participate in similar examinations. 2,616 subjects are offspring of the original spouse pairs and 34 are stepchildren. A total of 898 offspring are children of cohort members where only one parent was a study participant and 1,576 are spouses of the offspring. The Offspring Cohort has been followed every four years through 2001 (except between Exams 1 and 2 with an intervening 8 years) using protocols similar to those used for study of the Original Cohort. Between 2002 and 2005 the study enrolled the third generation (Gen3) of the Framingham Heart Study - 4095 offspring of the second generation. None of their spouses were recruited. An additional 103 parents of this third generation, who were not recruited between 1971 and 1975, were also recruited at this time. The latter group is not included in the GAW16 data. With the recruitment of this third generation, the study has increasingly focused on genetic factors associated with the development of cardiovascular disease and its associated risk factors. To date, there is only one examination of this generation of participants. A description of the recruitment of this third generation and comparison with the earlier generations at their initial recruitment is presented in Splansky GL et al., 2007. Further information on the Study can be found at http://www.nhlbi.nih.gov/about/framingham/index.html. Genome-wide Dense SNP Scan in Framingham Heart Study Genetic studies did not begin in the FHS until the 1990s. In the late 1980s and through the 1990s DNA was extracted from blood samples of surviving FHS participants. In 2007, the FHS entered a new phase with the conduct of genotyping for the FHS SHARe (SNP Health Association Resource) project, for which dense SNP genotyping was performed using approximately 550,000 SNPs (GeneChip® Human Mapping 500K Array Set and the 50K Human Gene Focused Panel) in 10,775 samples (some duplicates) from the three generations of subjects (including over 900 pedigrees). Affymetrix conducted all genotyping for the FHS SHARe project, using the 250K Sty, 250K Nsp, and the supplemental 50K platforms. Eighty-nine percent of the DNA samples were collected during the 1990s. To maximize the power of the study, we also extracted DNA from 1133 blood samples, drawn from subjects who had no DNA, to include in the SHARe project. These samples had been sitting in our refrigerators for some time, a few as far back as the 1970s. We refer to these DNA samples as the legacy samples. These samples had a higher failure rate in the genotyping process (40%) than the other eighty-nine percent (3%). Affymetrix invoked its own criteria for a sample to succeed in genotyping. All non-legacy samples must succeed on all three platforms, while legacy samples needed to pass on at least one platform. When a sample failed, additional attempts were made. Samples that repeatedly failed 2-4 times were called failures. Other samples failed due to issues of genotyped sex identification not matching our records or low SNP concordance among SNPs common across arrays or contamination. Eighty-nine percent of the legacy samples for which genotyping results are available passed all three platforms. The genotyping data from the 10,043 samples from 9354 subjects that passed the Affymetrix criteria were additionally checked for gender consistency and consistency with family structure, resulting in genotyping data for 9,274 participants in FHS SHARe. Genotype calls were made with the BRLMM algorithm. The SHARe database is housed at the National Center for Biotechnology Information database of genotypes and phenotypes (NCBI dbGaP) and contains all ~550,000 SNPs. This genome-wide dense SNP scan and a subset of phenotypes from the Framingham Heart Study are the focus of the Genetic Analysis Workshop 16. Further information on the specific variables in the Problem 2 dataset can be found by clicking on the Documents tab at the top of the page. Problem 3: Description of the Simulated Data Set The focus of this simulation is gene discovery in genome-wide association scans (GWAS). The Framingham Heart Study data set (distributed as "Problem 2") is the basis for the FHS* simulated data. The pedigree structures are derived from the data distributed for Problem 2, and we distribute an accompanying triplet file (triplet_sim) containing person ID, father ID, mother ID, to ensure the identical subjects, pedigrees, and singletons are used in the simulated data analysis. Consistent with standard practice, founders and singletons are designated as subjects with both fshare and mshare equal to zero (missing). The simulated data includes a total of 6,479 subjects with both phenotype and genotype data, in 942 pedigrees distributed among 3 generations and 188 singletons. Data inclusion is consistent with the subjects' consent for use by both for-profit and not-for-profit researchers. The genotypes for all Problem 3 replicates are fixed as measured and distributed for Problem 2 for both the genomewide scan and the additional candidate gene SNPs, for a total of approximately 550,000 SNPs (GeneChip® Human Mapping 500K Array Set and the 50K Human Gene Focused Panel). Thus, to analyze the Problem 3 simulated data you also will need to download the Problem 2 genotypes. Note that there are slight discrepancies in counts between Problems 2 and 3 due to a change in consents between the two datasets. Several phenotypes that contribute to coronary heart disease (CHD) were simulated for all individuals with genotypes across three different time points, 10 years apart. All genotyped individuals have complete data; the effects of missing values can be investigated by user-specified missing value patterns. There are 200 longitudinal datasets created, based on the generating model, and each replication is found in a separate dataset. We suggest that if only one replication is to be analyzed, that it be replication 1 to enable more precise comparisons among analytical approaches. The 'shareid' will allow you to merge the simulated phenotype data with the Problem 2 genotype data, and reconstruction of the pedigrees using the distributed 'triplet_sim' file or for larger families' relationships with the triplet distributed with the Problem 2. The simulated data problem is further described in the associated readme file, and a data dictionary is provided defining all the variables. For disclosure of the generating model for these data, please contact Jean MacCluer at jean@sfbrgenetics.org.

  Study phs000128

• NOTCH1 fusion genes in pediatric T-cell lymphoblastic lymphoma hallmark a common high-risk subgroup with blood TARC levels as possible biomarker

  T-cell lymphoblastic lymphoma (T-LBL) is a common pediatric malignancy accounting for approximately 20% of the non-Hodgkin lymphomas during childhood. Survival rates of T-LBL are ~80%, but outcome after relapse is dismal, with salvage rates reaching only ~15. Considering the extremely poor prognosis after relapse and absence of clinically relevant high-risk genetics, there is an urgent need for the identification of molecular risk factors and new prognostic biomarkers in T-LBL, as well as identification of new therapeutic strategies. In this study we present a novel entity of high-risk pediatric T-LBL patients characterized by previously unknown NOTCH1 gene fusions and highly elevated blood TARC levels

  Dataset EGAD00001015255

• SNP array analysis of spondylocostal dysostosis patient iPSCs and gene edited isogenic controls

  This study, "SNP Array Analysis of Gene Edited SDV Patient iPSCs" is part of a larger study where we applied our recently established experimental in vitro model system of the human segmentation clock, for the analysis of human segmentation defects of the vertebrae (SDV) including spondylocostal dysostosis (SCD). To this end we generated patient-derived iPSC lines, identified putative disease-causing mutations and corrected these mutations using CRISPR/Cas9-based genome editing technology. We identified in the patient-sample originally obtained from the NIGMS Human Genetic Cell Repository at the Coriell Institute for Medical Research (#: GM13539) heterozygous compound mutations in MESP2. These mutations were corrected accordingly and the resulting clones were genotyped by SNP array analysis.

  Study phs001975

• Profiling the Microbiome of Pediatric Gut with Metagenomic Short-Read Sequencing

  This dataset contains short-read metagenomic sequencing of stool, as well as intestinal tissue and tissue washes, from preterm infants. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001016052

• Genetics of diffuse large B-cell lymphoma in Japan

  Diffuse large B-cell lymphoma (DLBCL) is a common hematological malignancy. Treatment with standard chemotherapy results in long-term remission in approximately 60% of patients. Whole-exome sequencing studies of large DLBCL cohorts revealed the biological diversity of tumors and facilitated the identification of genetic subtypes based on genetic alterations. Despite the progress facilitated by NGS, genetic classification is difficult to apply in clinical practice because of the complexity of the clustering algorithm. Furthermore, only a few reports included large Asian cohorts. Thus, a genetic overview of Japanese patients with DLBCL is still needed. Thus, in this study, we aimed to establish the clinical application of our simplified genetic classification algorithm in Japanese DLBCL.

  Study JGAS000307

• Identification of genetic polymorphism on aggressive periodontitis

  Periodontitis is an inflammatory disease with loss of gingival tissue and alveolar bone. Aggressive periodontitis is rapidly progressive form of periodontitis in young people. It has been demonstrated that the susceptibility to AgP is influenced by genetic risk factors. However few were established as a risk factor for aggressive periodontitis. To identify genetic risk factors for aggressive periodontitis in Japanese population, we conducted the exome sequence of unrelated patients.

  Study JGAS000040

• Identification of genetic polymorphism on aggressive periodontitis

  Periodontitis is an inflammatory disease with loss of gingival tissue and alveolar bone. Aggressive periodontitis is rapidly progressive form of periodontitis in young people. It has been demonstrated that the susceptibility to AgP is influenced by genetic risk factors. However few were established as a risk factor for aggressive periodontitis. To identify genetic risk factors for aggressive periodontitis in Japanese population, we conducted the exome sequence of unrelated patients.

  Study JGAS000024

• Whole genome shotgun sequencing and somatic mutations data in Hepatocellular carcinoma

  Hepatocellular carcinoma (HCC) is the most common malignancy of the liver. Genomic analysis is conducted to identify genetic alterations in driver genes which are all druggable targets for cancer therapy.

  Study EGAS00001002578

• Alzheimer's Disease Sequencing Project (ADSP)

  NOTICE OF CHANGE IN LOCATION FOR ALZHEIMER'S DISEASE SEQUENCING PROJECT (ADSP) GENETIC AND PHENOTYPIC DATA: ADSP whole exome and whole genome sequence data that are shared through dbGaP were mapped to the Genome Reference Consortium human genome GRCh37 (build 37). These data are from the Discovery Phase of the project (described below) and will continue to be available at this site. Please see the ADSP Design page for the complete study description. All data that are mapped to GRCh38 (hg38) are being shared through the NIA Genetics of Alzheimer's Disease Data Storage Site (NIAGADS) Data Sharing Service (DSS). For instructions on how access the ADSP Build 38 data that are shared through NIAGADS DSS, visit the Application Instructions page. STUDY DESCRIPTION FOR dbGaP BUILD 37 ADSP DATA: The overarching goals of the Alzheimer's Disease Sequencing Project (ADSP) are to: (1) identify new genomic variants contributing to increased risk of developing Alzheimer's Disease (AD), (2) identify new genomic variants contributing to protection against developing AD, and (3) provide insight as to why individuals with known risk factor variants escape from developing AD. These factors will be studied in multi-ethnic populations in order to identify new pathways for disease prevention. Such a study of human genomic variation and its relationship to health and disease requires examination of a large number of study participants and needs to capture information about common and rare variants (both single nucleotide and copy number) in well phenotyped individuals. Using existing samples from NIH funded and other studies, three NHGRI funded Large Scale Sequencing and Analysis Centers (LSAC) - Broad, Baylor, and Washington University - produced the DNA sequence data. Variant call data are being made available to the scientific community through NIH-approved data repositories. Statistical analysis of the sequence data is anticipated to identify new genetic risk and protective factors. The ADSP will conduct and facilitate analysis of sequence data to extend previous discoveries that may ultimately result in new directions for AD therapeutics. Analysis of ADSP data will be done in two phases. The Discovery Phase analysis (2014-2018) is funded under PAR-12-183. The entire Discovery dataset contains whole-genome sequencing data on 584 subjects from 113 families, and pedigree data for > 4000 subjects; whole exome sequencing data on 5096 cases 4965 controls; and whole exome sequence data on an additional 853 (682 Cases [510 Non-Hispanic, 172 Hispanic]), and 171 Hispanic Control subjects from families that are multiply affected with AD. The Replication Phase (2016-2021) analysis will be funded under RFA-AG-16-001 and RFA-AG-16-002 and is expected to include a combination of genotyping and sequencing approaches on at least 30,000 subjects. Targeted sequencing will be done by the LSACs. GRCh37 Data Releases The first ADSP data release occurred on November 25, 2013. It included the whole-genome sequencing data in BAM file format on 410 individuals. The second ADSP data release occurred on March 31, 2014, and included the whole-genome sequencing data in BAM file format for an additional 168 individuals. The third ADSP data release occurred on November 03, 2014 and included whole-exome sequencing data in BAM file format for 10,939 individuals. The fourth ADSP data release occurred on February 13, 2015 and included revised ethnic data for subjects with whole-exome sequencing data. The fifth ADSP data release occurred on July 13, 2015 and included whole-genome genotypes and updated phenotypes as well as changes to pedigree structures and sample IDs. The sixth ADSP data release occurred on December 8, 2015, and included whole-exome genotypes and updated phenotypes as well as changes to subject IDs. This seventh ADSP data release on April 12, 2016 includes: (1) WES and WGS SNV VCF files (2) WES and WGS Indel PLINK files ADSP Data Available through dbGaP: ADSP - Whole Genome Sequencing ADSP - Whole Exome Sequencing Comments DNA-Seq (BAM) n=578 n=10913 Sequence data available (plus n=38 replications w/out genotype data) Concordant SNV Genotypes (PLINK format) N/A n=10913 QC'ed genotypes that are concordant between the Atlas (Baylor's) and GATK (Broad's) calling pipelines (a subset of the consensus genotype set) Consensus Genotypes (PLINK and VCF format) n=578 n=10913 QC'ed genotypes that are concordant between Atlas and GATK pipelines as well as those that that were called uniquely by Atlas or GATK Concordant Indel Genotypes (PLINK format) n=578 n=10913 QC'ed genotypes that are concordant between the Atlas and GATK calling pipelines Phenotype Data n=4735 n=10913 Data of n=53 phenotype variables available (plus administrative data), including APOE genotype. WGS phenotypes include data of connecting family members. Please use the release notes provided by dbGaP to obtain detailed information about study release updates. The ADSP data portal provides a customized interface for users to quickly identify and retrieve files by covariates, phenotypes, and data properties such as sequencing facility or coverage. For more information about the ADSP study and the data portal, please visit https://www.niagads.org/adsp/.

  Study phs000572

• PGRN/PAT: The genomic basis for susceptibility to drug-induced long QT syndrome (diLQTS)

  The goal of this study was to search for genetic variants that could be responsible for modifying the risk of drug-induced long QT syndrome (diLQTS). diLQTS is a relatively common adverse drug event and has been a leading cause for drug relabeling and withdrawal from the market. Our hypothesis, that variants in genes which regulate electrical properties in the heart modify the risk of diLQTS, was tested by sequencing approximately 225 patients of European descent using next-generation targeted captured or whole exome sequencing. Data from cases and controls (1:2) were analyzed to identify both rare and common genetic variation.

  Study phs000808

• Vanderbilt Genome-Electronic Records (VGER) Project: QRS Duration

  An important potential enabling resource for Personalized Medicine is the combination of a DNA repository with Electronic Medical Record (EMR) systems sufficiently robust to provide excellence in clinical care and to serve as resources for analysis of disease susceptibility and therapeutic outcomes across patient populations. The Vanderbilt EMR is a state of the art clinical and research tool (that includes >1.7 million records), and is associated with a DNA repository which has been in development for over 3 years; these are the key components of VGER, the Vanderbilt Genome-Electronic Records project, a part of NHGRI's eMERGE network. The VGER model acquires DNA from discarded blood samples collected from routine patient care, and can link these to de-identified data extracted and readily updated from the EMR. The phenotype we analyze here is the QRS duration on the electrocardiogram, since slow conduction (indicated by longer QRS duration) is a marker of arrhythmia susceptibility.

  Study phs000188

• Coronary Artery Risk Development in Young Adults (CARDIA) Study - Gene Environment Association Studies Initiative (GENEVA)

  For the GENEVA CARDIA project, three genotype call sets were generated from a single set of array scans as a consequence of DNA sample quality problems. These call sets are designated "Birdsuite-1", "Birdsuite-2" and "Beaglecall". ("Beaglecall" used both Birdseed and BEAGLECALL calling algorithms.) An analysis-ready genotypic data set is provided in PLINK format for the "Beaglecall" set only, because it performs very well in QC analyses. Only raw CHP and ALLELE_SUMMARY files are provided for the two Birdsuite call sets because they have significant quality issues. Use of the Beaglecall set is highly recommended. Users of the other two call sets should proceed with caution. More details are given in the genotypic QC report. The CARDIA study, sponsored by the National Heart, Lung and Blood Institute (NHLBI), is a prospective, multi-center investigation of the natural history and etiology of cardiovascular disease in African-Americans and Whites 18-30 years of age at the time of initial examination. The initial examination included 5,115 participants selectively recruited to represent proportionate racial, gender, age, and education groups from 4 communities: Birmingham, AL; Chicago, IL; Minneapolis, MN; and Oakland, CA. Participants from the Birmingham, Chicago, and Minneapolis centers were recruited from the total community or from selected census tracts. Participants from the Oakland center were randomly recruited from the Kaiser-Permanente health plan membership. From the time of initiation of the study in 1985-1986, five follow-up examinations have been conducted at years 2, 5, 7, 10, 15, and 20. The Year 25 examination is scheduled to begin in 2010. 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 associated with variation in longitudinal blood pressure profiles during the critical transition period from young adulthood to early middle-age; and to characterize their interactions with relevant environmental factors, such as body weight profiles. Genotyping was performed at the Broad Institute of MIT and Harvard, a GENEVA genotyping center. Data cleaning and harmonization were performed at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000309

• Female Infertility: Primary Ovarian Insufficiency

  Premature ovarian failure, or primary ovarian insufficiency (POI) is a phenotype of diminished or absent ovarian function occurring in 1-2% of reproductive aged women. Most cases occur spontaneously. Evaluation of the gametes in women with POI is difficult and invasive. Practitioners must often rely on indirect biomarkers of ovarian function and oocyte health, making it difficult to identify patients who may benefit from therapies allowing them to achieve pregnancy utilizing their own oocytes. This study will generate exome sequences from POI patients in an effort to elucidate the causes of unexplained POI and to better understand the normal processes of ovarian aging. A better understanding of the genetics of ovarian function may lead to new non-invasive tools for managing women's reproductive health, and direct better use of existing biomarkers in diagnosis, screening and predicting clinical outcomes.

  Study phs001174

• Chromatin immunoprecipitation linked to next-generation whole genome sequencing (ChIP-Seq) for H3K36me3 in paediatric high grade glioma cell lines KKNS4 and SF188 with and without a G34V mutation in H3F3A

  Glioblastomas of children and young adults have a median survival of only 12-15months and are clinically and biologically distinct from histologically similar cancers in older adults1. They are defined by highly specific mutations in the gene encoding the histone H3.3 variant H3F3A2, occurring either at or close to key residues marked by methylation for regulation of transcription – K27 and G34. We performed chromatin immunoprecipitation linked to next-generation whole genome sequencing (ChIP-Seq) for H3K36me3 in order to test the hypothesis that, rather than total H3K36me3, the G34V mutation may instead result in differential binding of the trimethyl mark throughout the genome. Compared with H3F3A wild-type SF188 paediatric GBM cells, H3K36me3 was found to be significantly differentially bound in KNS42 cells at 5130 distinct regions of the genome corresponding to 156 genes. Concurrent whole genome DNA sequencing demonstrated that this was not confounded by copy number alterations. The cerebral hemispheric-specific G34 mutation drives a distinct expression signature through differential genomic binding of the K36 trimethylation mark (H3K36me3). The transcriptional program induced recapitulates that of the developing forebrain, and involves numerous markers of stem cell maintenance, cell fate decisions and self-renewal. Critically, H3F3A G34 mutations cause profound upregulation of MYCN, a potent oncogene which is causative of glioblastomas when expressed in the correct developmental context. This driving aberration is selectively targetable in this patient population by inhibiting kinases responsible for stabilisation of the protein.

  Study EGAS00001001437