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• ERDERA Diagnostic Research Workstream DAC

  The ERDERA Diagnostic Research Workstream DAC decides on data access requests according to the principles defined in the ERDERA Data Sharing Framework Agreement.

  Dac EGAC50000000728

• Dutch - BP

  The dataset encompasses 1110 Runs from the WGSPD Project 3 - Genomic Strategies to Identify High-impact Psychiatric Risk Variants Project

  Dataset EGAD50000001738

• Dutch - SCZ

  The dataset encompasses 804 Runs from the WGSPD Project 3 - Genomic Strategies to Identify High-impact Psychiatric Risk Variants Project

  Dataset EGAD50000001739

• Infant HGG WES

  Whole exome sequencing of infant high grade gliomas. BAM files of paired end reads aligned to GRCh37 with bwa

  Dataset EGAD00001005247

• Nyamasati study

  Illumina whole genome sequencing to high depth (x50) of four Tanzanian individuals. Genomic DNA derived from peripheral whole blood.

  Dataset EGAD00001004370

• Type 1 Diabetes Genetics Consortium (T1DGC): Genome-Wide Association Study in Type 1 Diabetes, 2008

  Cases with Type 1 Diabetes (T1D) in the UK, were part of the Wellcome Trust Case Control Consortium (WTCCC) - http://www.wtccc.org.uk - that first reported in 2007: Wellcome Trust Case Control Consortium (2007) Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature, 447, 661-678. [PubMed: 17554300] In this genome-wide association study (GWAS), funded by the NIH and JDRF, and sponsored by the Type 1 Diabetes Genetics Consortium (T1DGC), we were able to extend the case and control groups used in the WTCCC, with the intention of performing a well-powered meta-analysis. The study is written up as: Barrett, J.C., Clayton, D.G., Concannon, P., Akolkar, B., Cooper, J.D., Erlich, H.A., Julier, C., Morahan, G., Nerup, J., Nierras, C., Plagnol, V., Pociot, F., Schuilenburg, H., Smyth, D.J., Stevens, H., Todd, J.A., Walker, N.M., Rich, S.S. and The Type 1 Diabetes Genetics Consortium Genome-wide association study and meta-analysis find that over 40 loci affect risk of type 1 diabetes. Nature Genetics, PMID: 19430480. Resources - data: * Case data from this study is deposited here (i.e. in dbGaP) * Control data from this experiment - with subjects from the 1958 British Birth Cohort - is deposited with the European Genotype Archive (EGA): http://www.ebi.ac.uk/ega/ from where the WTCCC data is also available. * A complete description of how to request all components of the meta-analysis is available at: http://www.t1dbase.org/page/PosterView/display/poster_id/324 * Additional genetic data on the same case subjects, including some HLA types, are available from the Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory (JDRF/WT-DIL): http://www-gene.cimr.cam.ac.uk/todd/ Resources - samples: Case and control DNA samples are also available: * Case DNA samples are available from the JDRF/WT-DIL, as above, and will be available from the NIDDK Genetics Repository at Rutgers: https://www.niddkrepository.org * Control DNA samples are available from the 1958 British Birth Cohort (aka National Child Development Study): http://www.cls.ioe.ac.uk/studies.asp?section=000100020003 Use restrictions: There are access limitations to both data and samples, in order to keep their use in line with subjects' consent.

  Study phs000180

• National Institute of Mental Health (NIMH) Duke Cognition Cohort

  The overall goal is to identify genetic variants influencing normal variation between humans, with a focus on cognitive and neurosensory traits. Because of the focus of funding agencies on disease, very few studies of the genetics of non-disease traits have been performed. The genetic variation underlying the vast majority of differences between humans therefore remains not only undiscovered, but also unexplored. We have assessed >1,200 healthy volunteers for >70 diverse, non-disease phenotypes, with a focus on cognitive and neurosensory traits that are understudied and seem to have a strong biological basis. Our study includes measurements of face recognition, night vision, cognitive performance, auditory pitch discrimination, contagious yawn susceptibility, time perception, sense of direction, taste preferences, personality, sexual behaviors, sleep habits, acne, headache locations, synesthesia, and teeth sensitivity. This method is very different from the focus of most studies on collecting cohorts of patients with disease and controls with minimal phenotypic information. Because we phenotype the same healthy volunteers for multiple highly variable yet heritable traits, we can perform genetic analyses on a large number of phenotypes by just investing once in sequencing the DNA of these participants. An additional >2,000 participants in our cohort have been measured just for cognitive performance instead of for the more extensive phenotyping. Most of the genetic studies in this cohort have been about cognitive perfromance. The number of participants with genetic data generated who have undergone the more extensive phenotyping is limited. Our studies of the more novel traits like contagious yawning have therefore focused more on correlations between different phenotypes until we have a sufficient sample size to truly attempt to make genetic discoveries. . The dataset also includes two small challenge studies. In one study, the cognitive performance of 150 healthy volunteers was measured before and after an acute dose of the antiepileptic drug topiramate. In the other study, the cognitive performance of 13 healthy volunteers was measured before and after 24 hours of sleep deprivation.

  Study phs001406

• NIDDK IBD Genetics Consortium Ulcerative Colitis Genome-Wide Association Study

  This dataset contains data for 1,028 white, non-Hispanic, European ancestry individuals with ulcerative colitis who were included in a genome-wide association study published by Silverberg et al. (2009). These individuals were ascertained in North America and selected to have either left-sided or extensive disease (i.e., individuals with proctitis only were excluded). Genotyping was performed using the Illumina HumanHap300v2 (n = 540) and HumanHap550v3 (n = 488) Genotyping BeadChips at the Feinstein Institute for Medical Research. Control data (not included) were obtained from the NIDDK IBD Genetics Consortium's Crohn's Disease GWAS (available from dbGaP) and from studies 64 and 65 deposited in the Illumina iControlDB. Seven hundred eighty individuals in this dataset were taken from the NIDDK IBD Genetics Consortium cell line repository (http://www.niddkrepository.org). These individuals are identified in the file dbGaP_SubjectDS.txt. The subject IDs for these individuals may be used to request corresponding samples for follow-up research through the repository. In addition, complete phenotype data for these individuals are included, collected using the Consortium's forms and phenotyping manual (both included). The remaining 248 individuals were identified from pre-existing collections ascertained by members of the Consortium or their collaborators. For these samples, several of the items in the phenotype file are incomplete. Those who wish to replicate the results in Silverberg et al. should note that 6 individuals with missing genotype rates > 0.07 were excluded from that analysis (leaving 1,022 affected samples total). In addition, the minor allele frequencies (MAFs) reported in the publication were calculated using only those individuals who were included in the allelic association tests (n = 977 for SNPs included in the HumanHap300 and n = 476 for SNPs included only in the HumanHap550). These tests were performed using conditional logistic regression on gender-ancestry strata; individuals who were not placed in a stratum (using the procedure described in the supplementary information for Silverberg et al.) were excluded. The indicator variables hh300 and hh550 in the file dbGaP_PhenotypeDS.txt identify the samples included in the allelic association tests, and may be used to replicate the published MAFs among affected individuals.

  Study phs000345

• Exploring the Genetic Variants Associated with Brain Growth in Children

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

  Study phs000962

• Genome-Wide Association Study of Genetic Susceptibility for Graft-vs-Host Disease Cohort 1

  Allogeneic hematopoietic stem cell transplantation (Allo-HSCT) is the only curative therapy for many advanced hematologic malignancies. Allo-HSCT is associated with significant morbidities and mortality, mainly because of the graft-versus-host disease (GVHD) caused by donor T cells recognizing antigens present in recipient tissues, and initiating an alloimmune response resulting in damage to many organs including the skin, gastrointestinal (GI) tract, and liver in recipient. More than half of all Allo-HSCT recipients develop different degrees of GVHD (grades I-IV). About 20% of recipients develop severe GVHD (grades III-IV) that is associated with a very high morbidity and mortality. The most important factor determining the severity of GVHD is the genetic disparities between donors and recipients, as is reflected in human leukocyte antigen (HLA) haplotypes that are routinely checked for donor selection. Even when donors and recipients are HLA-identical, many recipients develop severe GVHD. As a result, non-HLA antigens are important determinants of acute GVHD. An interesting and unique aspect of GVHD is that it is the consequence of an interaction between antigens present in one individual with the immune system of another individual. As a result, genotypes of both donor and recipient, and their interactions affect the pathogenesis of GVHD. To determine the genetic risk factors for GVHD, in the first aim (discovery phase), we will conduct Genome-Wide Association Studies (GWAS) in 3,000 patients who underwent Allo-HSCT and in their respective donors (6000 DNA samples) that are provided to us by the Center for International Blood and Marrow Transplant Research (CIBMTR), a research collaboration between the NMDP and Medical College of Wisconsin. In the second aim, we will validate the association between high risk genotypes detected in the first aim and severe GVHD in 1,750 donors and 1,750 recipients of Allo-HSCT, and perform the joint analysis with the discovery samples. In the third aim, we will investigate the functional effect of SNPs detected and validated to be significantly correlated with the severity of acute GVHD in mixed lymphocyte reaction (MLR), as an ex vivo surrogate for an alloimmune response.

  Study phs002185

• German early-onset prostate cancer cohort of the Pan-Prostate Cancer Genome (PPCG) project

  Prostate cancer is the most frequent malignant tumor in males and the second most frequent cause of cancer-related death. Currently, in Germany, more than 60,000 prostate cancers are diagnosed every year. Although most of these patients are treated in a curative attempt, more than 10,000 German men die from prostate cancer annually. Owing to the demographic changes of our society, a further doubling of prostate cancer incidences during the next 20 years is expected. Prostate cancer is generally considered a tumor of elderly men. However, a fraction of prostate cancers are diagnosed at the age of 55 years or less. For several reasons, these “early onset prostate cancers” may represent a key entity for the understanding of prostate cancer biology. First, it is likely that early onset prostate cancers represent a distinct molecular subgroup of prostate cancer (PCa), potentially characterized by relatively small numbers of genetic changes, some of which may be particularly strong driver mutations for PCa development. Second, a fraction of prostate cancers in young individuals could represent classical prostate cancers that are detected at a very early stage and might therefore have accumulated molecular changes/mutations occurring that are most instrumental for prostate cancer early detection. Third, PCa with hereditary backgrounds are likely to accumulate in the age group below 55 years. A comparison with other sample sets (e.g. from other ICGC consortia), a systematic genomic analysis of young men with PCa could therefore lead to the detection of mechanisms for hereditary PCa. Fourth, a better understanding of these tumors is particularly relevant as finding optimal treatment regimens is most critical in young cancer patients. We are analyzing the entire genomic DNA sequences of at least 200 PCas (and matched non-tumorous DNA) of young men (≤ 55y), to at least 30 fold coverage, and integrate single-nucleotide variants and genomic structural variations with differential methylation, mRNA and miRNA expression data.Tissues were collected at the University Medical Center Hamburg-Eppendorf. Sequencing was performed at DKFZ and NCT (Heidelberg), EMBL (Heidelberg), and MPIMG (Berlin). Data management and bioinformatic data analyses is being conducted at DKFZ.

  Study EGAS00001003373

• Evolution and clinical impact of genetic epistasis within EGFR-mutant lung cancers

  The current understanding of tumorigenesis is largely centered on a monogenic driver oncogene model. This paradigm is incompatible with the prevailing clinical experience in most solid malignancies: monotherapy with a drug directed against an individual oncogenic driver typically results in incomplete clinical responses and eventual tumor progression1-7. By profiling the somatic genetic alterations present in over 2,000 cases of lung cancer, the leading cause of cancer mortality worldwide, we show that combinations of functional genetic alterations, i.e. genetic collectives dominate the landscape of advanced-stage disease. We highlight this polygenic landscape and evolution of advanced-stage non-small cell lung cancer (NSCLC) through the spatial-temporal genomic profiling of 7 distinct tumor biopsy specimens and 6 plasma specimens obtained from an EGFR-mutant NSCLC patient at (1) initial diagnosis of early-stage disease, (2) metastatic progression, (3) sequential treatment and resistance to 2 EGFR inhibitors, (4) death. The comprehensive genomic analysis of this case, coupled with circulating free (cf) tumor DNA profiling of additional advanced-stage EGFR-mutant NSCLC clinical cohorts with associated treatment responses uncovered features of evolutionary selection for multiple concurrent gene alterations: including the presence of EGFR inhibitor-sensitive (EGFRL858R;EGFRexon19del) or inhibitor-resistant (EGFRT790M;EGFRC797S) forms of oncogenic EGFR along with cell cycle gene alterations (e.g. in CDK4/6, CCNE1, RB1) and activating alterations in WNT/β-catenin and PI3K pathway genes, which our data suggest can cooperatively impart non-redundant functions to limit EGFR targeted therapy response and/or promote tumor progression. Moreover, evidence of an unanticipated parallel evolution of both EGFR T790M and two distinct forms of oncogenic PIK3CA was observed. Our study provides a large-scale clinical and genetic dataset of advanced-stage EGFR-mutant NSCLC, a rationale for specific polytherapy strategies such as EGFR and CDK4/6 inhibitor co-treatment to potentially enhance clinical outcomes, and prompts a re-evaluation of the prevailing paradigm of monogenic-based molecular stratification for targeted therapy. Instead, our findings highlight an alternative model of genetic collectives that operate through epistasis to drive lung cancer progression and therapy resistance.

  Study EGAS00001002604

• TK-EPN862 - Patient-dervied xenograft model of Posterior Fossa A Ependymoma - RNAseq

  Ependymomas (EPN) are the third most common malignant brain cancer in children. Treatment strategies for pediatric EPN have remained unchanged over recent decades, with 10-year survival rates stagnating at just 67% for children aged 0-14 years. Moreover, patients who survive treatment for the most common subtype of pediatric EPN (posterior fossa A (PFA)), often suffer long-term neurological side effects as a result of therapy. It is evident that there is a need for safer, more effective treatments for pediatric EPN patients. There are ten distinct subgroups of EPN, each with their own molecular and prognostic features. To identify and facilitate the testing of new treatments for EPN, in vivo laboratory models representative of the diverse molecular subtypes are required. Here, we describe the establishment of a patient-derived orthotopic xenograft (PDOX) model of PFA EPN, derived from a metastatic cranial lesion. Patient and PDOX tumors were analyzed using immunohistochemistry, DNA methylation profiling, whole genome sequencing (WGS) and RNA sequencing. Both patient and PDOX tumors classified as PFA EPN by methylation profiling, and shared similar histological features consistent with this molecular subgroup. RNA sequencing revealed that gene expression patterns were maintained across the primary and metastatic tumors, as well as the PDOX. Copy number profiling revealed gains of chromosomes 7, 8 and 19, and loss of chromosomes 2q and 6q in the PDOX and matched patient tumor. No clinically significant single nucleotide variants were identified, consistent with the low mutation rates observed in PFA EPN. Overexpression of EZHIP RNA and protein, a common feature of PFA EPN, was also observed. Despite the aggressive nature of the tumor in the patient, this PDOX was unable to be maintained past two passages in vivo. Others who have successfully developed PDOX models report some of the lowest success rates for EPN compared to other pediatric brain cancer types attempted, with loss of tumorigenicity not uncommon, highlighting the challenge in propagating these tumors in the laboratory. Here, we discuss our collective experiences with PFA EPN PDOX model generation and propose potential approaches to improve future success in establishing preclinical EPN models

  Study EGAS00001006844

• Concepción Aguilera belongs to the Department of Biochemistry and Molecular Biology II from the University of Granada and is head of the molecular biology research group BIONIT (CTS-461).

  Dac EGAC00001000779

• PBAT sequencing of human embryonic stem cells

  To assess the DNA methylation landscape of naïve human embryonic stem cells derived from ERKi or control blastocysts using PXGL or UXGL media.

  Dac EGAC50000000606

• Aggressive PDACs show hypomethylation of repetitive elements and the execution of an intrinsic IFN program linked to a ductal cell-of-origin

  Study EGAS00001004660

• Finnish - THL SUPER

  The dataset encompasses 852 Runs from the WGSPD Project 3 - Genomic Strategies to Identify High-impact Psychiatric Risk Variants Project

  Dataset EGAD50000001466

• Time course acetalax bisacodyl treatment

  RNA-Seq raw data of PDX treated with acetalaxor bisacodyl for 4h00 to 24h00.

  Dataset EGAD50000000875

• methylation_normal_adjacent_breast

  Raw methylation data from normal breast tissue adjacent to a malignancy (TNBC)

  Dataset EGAD00010002074

• Myeloproliferative Neoplasms (MPN) Exome Validation Study

  Experiments using targeted pulldown methods will be sequenced to validate findings in the exomes of patients with Myeloproliferative Neoplasms (MPN).

  Dataset EGAD00001000619

• BASIS Genome Validation Study

  Bespoke validation experiments will be performed on ER+ Breast Cancer cases to confirm the presence of mutations found in whole genome sequencing.

  Dataset EGAD00001000661

• Infant HGG WGS

  Whole genome sequencing of infant high grade gliomas. BAM files of paired end reads aligned to GRCh37 with bwa

  Dataset EGAD00001005246

• CSC DDR dataset

  CSC DDR dataset contains 4 bam files of two pairs of colorectal CSCs sensitive and resistant to ATR or CHK1 inhibitor

  Dataset EGAD00001006774

• NHLBI TOPMed: Chicago Initiative to Raise Asthma Health Equity (CHIRAH)

  The CHIRAH project was a community-based study of the factors associated with asthma morbidity in the African American population. CHIRAH evaluated the role of various variables (biologic/environmental, psychologic/behavioral, and socioeconomic) on asthma morbidity and the function of changes in these variables on asthma morbidity in a longitudinal fashion. This involved collection of a cohort-based on school screening which was sampled to include similar numbers of underprivileged and non-underprivileged subjects which roughly equally represented self-reported African Americans and self-reported non-African Americans. Subjects were followed up every 3 months of this cohort over the course of 2 years.

  Study phs001605

• The EGA joins EUCAIM, the European project powering AI and imaging in cancer research

  EUCAIM (EUropean Federation for CAncer IMages) is the cornerstone of the European Cancer Imaging Initiative, one of the flagships of the Europe’s Beating Cancer Plan (EBCP). The European Genome-Phenome Archive (EGA), as member of the EUCAIM consortium, attended the kick-off meeting organized this week in Brussels for the launch of the Initiative. The EGA will contribute to the project with the experience gained in the deployment of our federated network, the Federated EGA (FEGA), and the experience gained as partners of EuCanImage (AI4HI initiative) contributing to the definition of common data models, ontologies and data standards. The ultimate goal of the project is to unlock the power of imaging and Artificial Intelligence for the benefit of cancer patients, clinicians and researchers. The consortium will deploy a pan-European digital federated infrastructure hosting cancer-related images, and associated pathology, molecular and laboratory data from Real-World. This endeavour will provide a comprehensive dashboard for imaging data discovery, federated search, metadata harvesting, annotation and distributed data processing. EUCAIM joins 76 partners, gathering the experience and previous effort made by the different repositories of the AI4HI initiative, European Research Infrastructures and national/regional repositories. Find out more information about the EUCAIM launch here

  Blog the-ega-joins-eucaim