3311 results for "*geneti*"

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• Diabetes Multi-Omic Investigation of Drug Response (DIAMOND)

  The Diabetes Multi-omic Investigation of Drug Response (DIAMOND) cohort is a population-based cohort of individuals with type-2 diabetes (T2D) who receive their care through a large health system serving southeast Michigan and metropolitan Detroit. The cohort represents the diversity of the population from which it was created. Because of their health plan membership, participants have a rich dataset of longitudinal clinical health information related to their care. The intent of the DIAMOND study is to use genomic profiling, drug exposure information, and electronic health record (EHR) derived outcome data to identify genetic predictors of treatment response. Genome-wide genotyping was performed using the AxiomTM Precision Medicine Research Array (ThermoFisher Scientific Inc.).

  Study phs003350

• Genetic Predictors of Ibrutinib-Related Cardiovascular Side Effects in Patients with Chronic Lymphocytic Leukemia

  The goal of this study was to identify genetic polymorphisms associated with ibrutinib-related cardiovascular side effects (CVSEs). This is an observational non-interventional pharmacogenomic study of 50 patients with newly diagnosed or relapsed refractory chronic lymphocytic leukemia (NDCLL or RRCLL) receiving ibrutinib 420 mg for at least six months. The ibrutinib-related CVSEs included atrial fibrillation and hypertension, which occurred in 20% of patients. DNA obtained from buccal swabs was genotyped for 40 single nucleotide polymorphisms (SNPs) in GATA4, SGK1, KCNQ1, KCNA5, NPPA, and SCN5A using a customized next generation sequencing panel. It was found that GATA4 rs804280 AA (P =.043), KCNQ1 rs163182 GG (P =.036) and KCNQ1 rs2237895 AA (P =.023) were associated with the ibrutinib-related CVSEs. Patients with a high-risk score had at least two of the three significant risk genotypes identified in univariate analysis for GATA4 rs804280 A>C, KCNQ1 rs162182 G>C and KCNQ1 rs2237895 A>C, and patients with a low-risk score had either one or none of these genotypes. In multivariate analysis, 18 patients with at least two of the three high-risk genotypes had an 11.5-fold higher odds of CVSEs (P =.019; 1.79-119.73 at 95% CI).

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• Genomic Studies in Charcot-Marie-Tooth Disease

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

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• Epigenetic Changes in Immune Response and Oncogenesis Related Genes Caused by Heavy Metal Long-Term Exposure

  Our study investigated methylation changes in CpG islands located in immune response and oncogenesis related genes in humans induced by long-term environmental heavy metal exposure. We assessed the methylation levels of 654 CpG sites located on NFKB1, CDKN2A, ESR1, APOA5 and IGF2/H19 genes by targeted bisulfite sequencing (target enrichment by 48.48 Access Array Integrated Fluidic Circuit (Fluidigm, USA) in a cohort of 40 subjects living near a metal mining area (the Kapan mining region, Armenia) and 40 unexposed subjects. We performed linear regression on our data to find differentially methylated positions with adjustment for gender, age, BMI class, smoking, and plasma concentrations of 21 essential and non-essential metals detected by ICP-MS. Our study showed hypomethylation of five CpG sites in the NFKB1 promoter region in the exposed group. According to our findings, the methylation changes of CpG sites in NFKB1, CDKN2A, IGF2 and ESR1 genes are associated with multiple and specific metal exposures. Targeted bisulfite sequencing data obtained for 80 subjects who participated in this study are available through dbGaP. The tables contain information about age, sex, BMI, smoking and exposure status, as well as race and ethnicity of the study participants.

  Study phs003392

• Dysregulation of Naive T Cell Quiescence during Aging

  TEA-seq (novel trimodal single-cell analysis of mRNA transcripts, surface protein epitopes, and chromatin accessibility) was performed on CD3+ T cells isolated from peripheral blood of healthy pediatric (11–13 yrs, n = 8) and older adult (55–65 yrs, n = 8) female donors. Single-cell RNA sequencing (scRNA-seq) was additionally performed on peripheral blood mononuclear cells (PBMCs) from a healthy cohort of 16 pediatric, 16 young adult (25–35 yrs), and 16 older adult donors with equal sex distribution. Using these data, we dissected the compositional and molecular alterations within the T cell compartment across the spectrum of healthy age, showing broad transcriptional and epigenetic alterations within the T cell compartment of older adults compared to children, as well as a novel population of pediatric-specific CD8aa T cells.

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• MILK-Omics: Systems Biology of Human Milk and Its Links to Maternal and Infant Health

  The primary objective of the project is to generate a systems-level view of human milk in the context of healthy mothers and their term infants. The study uses biospecimens and clinical data from the Mothers and Infants LinKed for Healthy Growth Study (MILk Study), a prospective observational cohort of approximately 500 exclusively breastfeeding women and their infants who are followed to 6 months of age. The project focuses on mature milk samples collected at 1 month postpartum and infant gut microbiome samples collected at 1 and 6 months of age. Specific Aim 1 is to identify maternal genetic and clinical factors that shape human milk gene expression. Using bulk and single-cell RNA sequencing of the milk cell pellet and genotypes from maternal DNA, we will identify novel genetic determinants of the milk transcriptome and assess potential modification of these genetic associations by gestational weight gain, diet, and other clinical factors. Specific Aim 2 is to describe key features of the normative human milk biosystem and their interactions with one another. Specifically, machine learning techniques will be used to characterize interaction networks and correlational structures among the following features of human milk: transcriptomics, microbiomes, oligosaccharides, metabolomics, lipidomics, and milk macronutrient composition. Specific Aim 3 is to establish how the milk biosystem is related to variation in infant gut microbiomes and health. dbGaP will house the maternal genotype and milk transcriptomics data.The infant microbiome sequence data are associated with BioProject PRJNA1019702.

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• Resistance Development in Basal Cell Nevus Syndrome through the Basal to Squamous Transition

  While basal cell carcinomas (BCCs) arise from ectopic hedgehog pathway activation and can be treated with pathway inhibitors, sporadic BCCs display high resistance rates, while tumors arising in Gorlin syndrome patients with germline Patched (PTCH1) mutations are uniformly suppressed by inhibitor therapy. In rare cases, Gorlin syndrome patients on long-term inhibitor therapy will develop individual resistant tumor clones that rapidly progress, but the basis of this resistance remains unstudied. Here we report a case of a Smoothened inhibitor (SMOi)-resistant tumor arising in a Gorlin patient on suppressive SMOi for nearly a decade. Using a combination of multi-omics and spatial transcriptomics, we define the tumor populations at the cellular and tissue level to conclude that Gorlin tumors can develop resistance to SMOi through the previously described basal to squamous cell carcinoma transition (BST). Intriguingly, through spatial whole exome genomic analysis, we nominate PCYT2, ETNK1, and the phosphatidylethanolamine biosynthetic pathway as novel genetic suppressors of BST resistance. These observations provide a general framework for studying tumor evolution and provide important clinical insight into mechanisms of resistance to SMOi for not only Gorlin syndrome but sporadic BCCs as well.

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• Transcriptomic and Epigenetic Profiling of SCLC Patient Samples

  Small cell lung cancer (SCLC) is an aggressive disease with poor outcomes and limited treatment options. Recent studies have identified transcriptionally defined subsets of SCLC that may allow for the personalization of treatment. Here we use transcriptomic sequencing and methylation profiling (RRBS) of biopsy and cfDNA to develop a highly accurate DNA methylation-based classifier to distinguish SCLC subtypes. These results demonstrate the clinical feasibility of molecular subtyping of SCLC.

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• Whole-Exome Sequencing Study of Diabetic Nephropathy

  To identify rare variants of diabetic kidney disease (DKD), we conducted a whole-exome sequencing (WES) study. This study employed an extreme case–control design, which included a selection of the 593 most rapidly progressing DKD cases from the Chronic Renal Insufficiency Cohort (CRIC) Study (phs000524). In this two-stage WES study of DKD, participants with DKD from the CRIC were compared with control groups of participants without DKD from another cohort in the first stage. Suggestive signals identified in the first stage were confirmed in the second stage analysis among a diverse population with existing whole-genome sequencing (WGS) data. Generalized linear mixed models, which accounted for genetic relatedness and adjusted for age, sex and ancestry, were used to test associations between single variants and DKD. Gene-based aggregate rare variant analyses were conducted using an optimized sequence kernel association test implemented within our mixed model framework. As a result, we identified four novel gene loci, DIS3L2, KRT6B, ERAP2 and NPEPPS, that achieved exome-wide significance and may play an important role in the DKD disease course. This large WES study provides novel insights into DKD's molecular mechanisms.

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• Circulating Genomic Determinants of Treatment Failure in Hodgkin Lymphoma

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

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• Investigating Genetics in Suspected Congenital Syndromes

  We employed forward and reverse genetics to identify individuals with heterozygous JAK1 variants associated with autoimmune and inflammatory diseases. We first recruited six unrelated probands and seven affected family members presenting with a range of autoimmune and inflammatory conditions. Whole exome sequencing revealed 4 different variants spanning all domains of the JAK1 protein: FERM domain (chr1: 64873438-G>A; c.415C>T; p.E139K), SH2 domain (chr1: 64855641-G>A; c.1516C>T; p.R506C), pseudokinase domain (chr1: 64845529-C>T; c.2099G>A; p.S700N, and kinase domain (chr1: 64838479-C>T; c.2953G>A; p.V985I). We then performed a systematic review of electronic health records of the BioME BioBank database and identified 43 additional individuals with at least one of these JAK1 variants. Comparing variant-positive and variant-negative individuals, our study revealed increased occurrences of autoimmunity, atopy, colitis, and dermatitis in patients harboring these JAK1 gain-of-function variants. We have deposited in dbGaP the whole exome sequencing files of the 43 patients identified in the BioME biobank, as well as their phenotype information.

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• Breast Cancer in Blacks: Impact of Genomics, Healthcare Use and Lifestyle on Outcomes (BRIGHT)

  Young Black females bear a disproportionate burden of breast cancer (BC) mortality compared to White females and are underrepresented in clinical studies. It remains critical to understand factors that contribute to the high mortality from BC among young Black females in order to improve outcomes. The higher BC mortality rate among young Black females with breast cancer is partially attributed to the disproportionately higher proportions who develop the aggressive triple-negative breast cancer (TNBC). In addition to biologic factors, timely access to care, and lifestyle factors contribute to this disparity. Consequently, we sought to evaluate the interplay between biologic and non-biologic contributors to BC outcomes (i.e., BC disease-free survival (DFS)), and to better characterize the highly aggressive TNBC among young Black females based on distinct molecular subtypes. Ultimately, it is critical to assess both biologic and non-biologic factors to fully understand and address existing health disparities in this population. Through prior and subsequent recruitment of a population-based study of young Black females diagnosed with invasive breast cancer spanning 2009-2016, we: 1) assessed the contribution of biologic and non-biologic factors on BC-DFS observed among young Black females with BC, and 2) investigated molecular features of the subgroup with TNBC. Through this study, consented participants were asked to provide a saliva sample from which DNA was extracted for germline analyses, including germline inherited cancer genetic testing and Infinium Expanded Multi-Ethnic Genotyping Array. Breast cancer tumor specimens were also collected, and tumor RNA was extracted from viable FFPE tumor samples. Tumor RNA analyses included gene expression profiling through NanoString PAM50.Data that will be available through dbGaP for this study include SNP array data and PAM50 data.

  Study phs003466

• Genetic Markers of Lipids in Indians: A Validation Study of Most Relevant Findings of Genome-Wide Association Studies

  We aimed to validate the GWAS loci (identified in European populations) related to serum lipid levels (total cholesterol, triglycerides, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and very low-density lipoprotein cholesterol (VLDL-C)) in the Indian population originally recruited to examine the 20-year trend of cardiometabolic risk factors in rural and urban areas around National Capital region in India. Isolated DNA was processed for genotyping of 12 established GWAS variants using multiplex Sequenom Mass ARRAY technology. We examined the association of these genetic variants with different lipid levels and found association of eight variants for lipid levels. We also derived weighted genetic risk scores (wGRAS) using the validated variants. The wGRS for triglycerides and VLDL-C was derived based on four associated variants (rs174546 at FADS1, rs17482753 at LPL, rs2293889 at TRPS1, rs4148005 at ABCA8, rs4420638 at APOC1) which was associated with 36.31 mg/dL elevated triglycerides and VLDL-C (β=0.95, SE=0.16, pTRPS1 and rs4147536 at ADH1B) was associated with 40.62 mg/dL higher total cholesterol (β=1.01, SE=0.23, pTRPS1, rs4147536 at ADH1B, rs4420638 at APOC1 and rs660240 at CELSR2). The wGRS derived from five associated variants (rs174546 and FADS1, rs17482753 at LPL, rs4148005 at ABCA8, rs4420638 at APOC1 and rs7832643 at PLEC) was associated with 10.64 mg/dL lower HDL-C (β= -0.87, SE =0.14, pThe phenotypic and genotypic data will be made available on the dbGaP portal for access.

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• PIEZO1 Loss of Function Compound Heterozygous Mutation in the Rare Congenital Human Disorder Prune Belly Syndrome

  Prune Belly Syndrome (PBS) is a rare congenital myopathy that is incompletely understood genetically. In this IRB approved study, one white Non-Hispanic 35 year-old male PBS proband was prospectively enrolled and phenotyped. Blood lymphocyte DNA from the proband underwent paired-end Whole Exome Sequencing using the Illumina SureSelect kit and HiSeq2500 sequencer with data pipeline analysis. We aligned the subject's sequence against the GRCh38/hg19 assembly and variant calling was performed using data training sets from the 1000 Genomes Project, Omni 2.5 M SNP microarray, and HapMap phase 3.3. These variants were filtered for rare minor allele frequency ( 0.9, CADD score > 20, GERP > 4, MutationTaster = “DC”, Mutation Assessor = “M” or “NE”, and Vest > 3.00. Rare and novel candidate functional variants were screened in the ClinVar database for prior association with smooth muscle myopathy (SMM). Only variants that met these criteria were included for further analysis. Confirmed variants had inheritance analysis performed on available samples. Our WES analysis identified novel compound heterozygous variants in the PIEZO1 gene. We conducted an extensive functional analysis of the PIEZO1 PBS variants that revealed loss-of-function characteristics. Thus, PIEZO1 mutations may be causal for PBS. Our WES data will be available through dbGaP.

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• Postmortem Analysis of the Caudate Nucleus in Schizophrenia

  This postmortem study examines genomic signatures (gene, transcript, exon, and exon-exon junction) in the caudate nucleus of individuals with or without psychiatric illnesses. We characterized genetic and epigenetic changes across the lifespan of 443 donor subjects, including 245 individuals without psychiatric illness, 154 individuals with schizophrenia, and 44 individuals with bipolar disorder. The subjects are 210 from African and 233 from European ancestries. Combining expression quantitative trait loci (eQTL) analysis, Mendelian randomization with the latest schizophrenia genome-wide association study (GWAS), transcriptome-wide association study (TWAS) and differential expression analysis, we identified many genes associated with schizophrenia risk, including potentially the dopamine D2 receptor short isoform. We found that antipsychotic medication has an extensive influence on caudate gene expression. We constructed caudate nucleus gene expression networks that highlight interactions involving schizophrenia risk. These analyses provide a resource for the study of schizophrenia and insights into risk mechanisms and potential therapeutic targets. There are 120 subjects in this study which are also present in the study phs000417.

  Study phs003495

• Identification of Host Genetic Factors That Are Determinant for the Development of Severe Forms of COVID-19

  We conducted whole exome sequencing (WXS) on 21 cases of Multisystem Inflammatory Syndrome in Children (MIS-C) related to COVID-19 from Brazil. All patients who were hospitalized underwent serum (ELISA) and molecular (RT-PCR) testing for SARS-CoV-2, and the main clinical symptoms associated with SARS-CoV-2 infection were collected. During hospitalization, data on complications, medical interventions, and laboratory findings were also collected. Our results revealed in an unprecedented way the occurrence of several rare loss-of-function variants in the NLRP12 gene among the affected children, and three other SNVs, predicted to be highly pathogenic, were identified in the IL17RC gene. An additional nonsense variant, in the IFNA10 gene, was identified in a single patient. Through in vitro functional analysis, we unequivocally demonstrated that these mutations impact NF-kB activation. These findings are similar to those observed in NLRP12-associated systemic autoinflammatory disorders, characterized by altered innate immune response, with increased NF-κB activation and excessive production of inflammatory cytokines. To our knowledge, our study is the first to provide a plausible molecular mechanism for MIS-C involving inborn errors in NLRP12. We suggest that some patients with MIS-C may benefit from Interleukin (IL)-1 pathway blockade treatments.

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• Cell Type-Specific and Disease-Associated eQTL in the Human Lung

  This study was conducted to investigate the genetic control of gene expression in a cell-type and context-specific manner in the human lung. We performed single-cell RNA-sequencing (scRNA-seq) of lung tissue from 66 Interstitial Lung Disease (ILD) cases and 48 unaffected donors. Employing a pseudo-bulk approach, we mapped expression quantitative trait loci (eQTL) across 38 cell types. The scRNA-seq data presented here include previously published (PMID 34262047) and unpublished samples. ILD tissue samples were obtained from lungs removed at the time of lung transplantation at either Vanderbilt University Medical Center (VUMC) or the Norton Thoracic Institute (NTI). Control tissue samples were obtained from lungs declined for organ donation either at the Donor Network of Arizona (DNA) or VUMC. The self-reported ethnicities of donors were 66.7% European, 9.6% African American, 17.5% not available (N/A), and 6.1% other. The smoking history includes 46.5% ever smoker, 29.8% never smoker, 23.7% N/A. For genotyping, flash-frozen tissue in DNA/RNA shield was homogenized via a bullet blender. Genomic DNA was extracted using Zymo Quick DNA/RNA microprep plus kit. Library preparation and low-pass Whole Genome Sequencing (WGS) were carried out at TGen or by Gencove Inc. At TGen, libraries were prepared using PCR-free Watchmaker kits (Watchmaker Genomics) with 200 ng input. Genomes were sequenced on NovaSeq at low coverage (typically 0.4–1x). The resulting sequence data were processed and imputed using Gencove's imputation platform.

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• Integrating Genomic and Transcriptomic Data to Identify Breast Cancer Susceptibility Genes

  Genetic factors play an important role in the etiology of both sporadic and familial breast cancer. Since 2007, common genetic variants in ~200 loci have been identified in genome-wide association studies (GWAS) in relation to breast cancer risk. However, it is often difficult to translate GWAS findings to disease prevention and treatment since causal genes in the large majority of GWAS-identified loci are unknown. Furthermore, a large fraction of breast cancer heritability remains unexplained. Recent studies suggest that nearly 80% of disease heritability can be explained by genetic variants regulating gene expression. Herein, we propose three well-powered transcriptome-wide association studies (TWAS) to systematically investigate the association of breast cancer risk with gene expression across the transcriptome of African, Asian and European descendants. In Aim 1, we will perform RNA sequencing and high-density genotyping assays using normal breast tissue samples, and build race-specific gene expression prediction models using data from 1000 women of African, Asian and European descent. These models will be applied to the GWAS data generated from approximately 320,000 breast cancer patients and controls to impute gene expression for association analyses of predicted gene expression with risk of breast cancer overall, and by estrogen receptor and HER2 status. In Aim 2, we will select the top 50 genes identified in Aim 1 for in vitro functional assays to assess their influence on major cell functions related to cancer biology. In Aim 3, we will evaluate whether TWAS-identified genes may express differently in normal breast tissues and breast cancer tissues collected from African, Asian, and European descendants to assess whether these genes may contribute to racial differences in breast cancer risk by molecular subtypes. With strong methodology and a large sample size, we believe that this proposed study should be able to identify and characterize a large number of novel genes related to breast cancer risk. Uncovering breast cancer susceptibility genes will greatly improve the understanding of the genetic and biological basis for breast cancer and accelerate the translation of genetic findings to disease prevention and patient care.

  Study phs003535

• Action to Control Cardiovascular Risk in Diabetes (ACCORD - Imaging)

  Available DataAction to Control Cardiovascular Risk in Diabetes (ACCORD-Imaging), provides access to ECG signals data from the ACCORD clinical trial. The clinical phenotyping and outcomes data from the trial are associated with ACCORD-BioLINCC, phs003551.ObjectivesThe purpose of this study was to determine if intensive glycemic control, multiple lipid management and intensive blood pressure control could prevent major cardiovascular events (myocardial infarction, stroke or cardiovascular death) in adults with type 2 diabetes mellitus. Secondary hypotheses included treatment differences in other cardiovascular outcomes, total mortality, microvascular outcomes, health-related quality of life and cost-effectiveness.BackgroundGlycemia Trial:Patients with type 2 diabetes mellitus die of cardiovascular disease (CVD) at rates two to four times higher than non-diabetic populations of similar demographic characteristics. They also experience increased rates of nonfatal myocardial infarction and stroke. With the growing prevalence of obesity in the United States, CVD associated with type 2 diabetes is expected to become an even greater public health challenge in the coming decades than it is now. Expected increases in event rates will be associated with a concomitant rise in suffering and resource utilization.The ACCORD study investigated whether intensive therapy to target normal glycated hemoglobin (HbA1c) levels would reduce cardiovascular events in patients with type 2 diabetes who had either established cardiovascular disease or additional cardiovascular risk factors when compared to standard therapy (HbA1c between 7.0% and 7.9%). A separate analysis investigated whether reduction of blood glucose concentration decreases the rate of microvascular complications in these patients.Lipid Therapy Trial:Patients with type 2 diabetes mellitus have an increased incidence of atherosclerotic cardiovascular disease attributable, in part, to associated risk factors such as dyslipidemia. This is characterized by elevated plasma triglyceride levels, low levels of high-density lipoprotein (HDL) cholesterol and small, dense low-density lipoprotein (LDL) particles. The ACCORD Lipid Therapy trial was designed to test the effect of a therapeutic strategy that uses a fibrate to raise HDL-C and lower triglyceride levels and uses a statin for treatment of LDL-C reduce the rate of CVD events compared to a strategy that only uses a statin for treatment of LDL-C on cardiovascular outcomes in patients with type 2 diabetes that were at high risk for cardiovascular disease.Blood Pressure Trial:Diabetes mellitus increases the risk of cardiovascular disease at every level of systolic blood pressure. Because cardiovascular risk in patients with diabetes is graded and continuous across the entire range of levels of systolic blood pressure, even at prehypertensive levels, the Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (JNC 7) recommended beginning drug treatment in patients with diabetes who have systolic blood pressures of 130 mm Hg or higher, with a treatment goal of reducing systolic blood pressure to below 130 mm Hg. There is, however, a paucity of evidence from randomized clinical trials to support these recommendations. The ACCORD Blood Pressure trial tested the effect of a target systolic blood pressure below 120 mm Hg on major cardiovascular events among high-risk persons with type 2 diabetes compared to a strategy that targeted a SBP of EYE Substudy:Diabetic retinopathy, an important microvascular complication of diabetes, is a leading cause of blindness in the United States. Randomized, controlled clinical trials in cohorts of patients with type 1 diabetes and those with type 2 diabetes have shown the beneficial effects of intensive glycemic control and intensive treatment of elevated blood pressure on the progression of diabetic retinopathy. Elevated serum cholesterol and triglyceride levels have been implicated, in observational studies and small trials, as additional risk factors for the development of diabetic retinopathy and visual loss. The ACCORD EYE Substudy evaluated the effects of the ACCORD medical strategies on the progression of diabetic retinopathy in a subgroup of trial patients.MIND Substudy:Studies suggest that older persons with type 2 diabetes have at least twice the likelihood of developing late-life cognitive impairment or dementia compared to those without. The mechanisms underlying these cognitive disorders are increasingly thought to reflect a mixed pathology pattern with contributions from vascular, neurodegenerative and neurovascular processes. Pathophysiological mechanisms that have been described include inflammation, oxidative stress, energy imbalance, protein misfolding, glucocorticoid-mediated effects and differences in genetic susceptibilities. The ACCORD MIND substudy took as a premise that early intervention with the ACCORD therapeutic strategies to improve glycemic control could mitigate the adverse effects of type 2 diabetes on the brain.Subjects10,251 patients with type 2 diabetes and HbA1c concentrations of 7.5% or more participated in the trial. Of these patients, 5518 were assigned to the lipid therapy arm and 4733 to the blood pressure arm. EYE Substudy:A subgroup of 2856 patients was evaluated for the effects of the ACCORD interventions at 4 years on the progression of diabetic retinopathy. Patients who, at baseline, had a history of proliferative diabetic retinopathy that had been treated with laser photocoagulation or vitrectomy were excluded.MIND Substudy:A subgroup of 2977 patients was evaluated for cognitive function and brain volume. The ACCORD MIND substudy excluded patients aged DesignPatients were randomly assigned to undergo either intensive glycemic control (targeting a glycated hemoglobin level EYE Substudy:EYE Substudy patients were evaluated at two standardized and comprehensive eye examinations for the effects of the ACCORD interventions at 4 years on the progression of diabetic retinopathy by 3 or more steps on the Early Treatment Diabetic Retinopathy Study Severity Scale (as assessed from seven-field stereoscopic fundus photographs, with 17 possible steps and a higher number of steps indicating greater severity) or the development of diabetic retinopathy necessitating laser photocoagulation or vitrectomy.MIND Substudy:The cognitive primary outcome, the Digit Symbol Substitution Test (DSST) score, was assessed at baseline, 20 and 40 months. Total brain volume (TBV), the primary brain structure outcome, was assessed with MRI at baseline and 40 months in a sub-set of 632 patients. All patients with follow-up data were included in the primary analyses.ConclusionsGlycemia Trial:As compared with standard therapy, the use of intensive therapy to target normal glycated hemoglobin levels for 3.5 years increased mortality and did not significantly reduce major cardiovascular events. (NEJM. 2008; 358(24): 2545-59).Microvascular Outcomes of the Glycemia Trial:Intensive therapy did not reduce the risk of advanced measures of microvascular outcomes, but delayed the onset of albuminuria and some measures of eye complications and neuropathy. Microvascular benefits of intensive therapy should be weighed against the risk of increased total and cardiovascular disease-related mortality, increased weight gain, and higher risk for severe hypoglycemia. (Lancet. 2010; 376(9739): 419-30)Lipid Therapy Trial:The combination of fenofibrate and simvastatin did not reduce the rate of fatal cardiovascular events, nonfatal myocardial infarction or nonfatal stroke, as compared with simvastatin alone. These results do not support the routine use of combination therapy with fenofibrate and simvastatin to reduce cardiovascular risk in the majority of high-risk patients with type 2 diabetes (NEJM. 2010; 362(17): 1563–1574).Blood Pressure Trial:In patients with type 2 diabetes at high risk for cardiovascular events, targeting a systolic blood pressure of less than 120 mm Hg, as compared with less than 140 mm Hg, did not reduce the rate of a composite outcome of fatal and nonfatal major cardiovascular events (NEJM. 2010; 362: 1575-1585).EYE Substudy:Intensive glycemic control and intensive combination treatment of dyslipidemia, but not intensive blood-pressure control, reduced the rate of progression of diabetic retinopathy (NEJM. 2010; 363: 233-244).MIND Substudy:Although significant differences in TBV favored the intensive therapy, cognitive outcomes were not different. Combined with the unfavorable effects on other ACCORD outcomes, MIND findings do not support using intensive therapy to reduce the adverse effects of diabetes on the brain in patients similar to MIND patients (Lancet Neurol. 2011; 10(11): 969–977).

  Study phs003562

• HG Transcriptome sequencing in the INTERVAL cohort

  We performed bulk RNA-sequencing on peripheral blood collected from 4,732 blood donors recruited as part of the INTERVAL study. Using these data, we mapped gene expression and splicing quantitative trait loci (QTLs). Then, we integrated these data with protein, metabolite and lipid QTLs in the same individuals. The study aimed to identify the shared genetic etiology across transcriptional phenotypes, molecular traits and health outcomes in humans.

  Study EGAS00001003346

• How to use the EGA search box

  Tips on how to search Tip 1: Use simple and clear keywords No matter what you are searching: a study, a dataset or a committee; the search will look recursively in all the fields of all the entities in the database. Thus, there is no need to specify which type of data you are looking for. Try to use single and specific words and avoid long and complex expressions. Try it out: cancer rna-seq instead of cancer studies using RNA-seq. Tip 2: Narrow your results using search operators Search operators give you more control over the results. They manage the way keywords are used to restrict the search. By default, the search engine applies an OR operator when a space is inserted between two words. Include AND (capitalised) between the keywords in your search in order to show only pages containing both terms. Try it out: Search all the studies based on transcriptomic data, including those ones that use RNA sequencing to obtain this data. Tip 3: Do not worry about details The search engine automatically checks for the most common spelling mistakes of given words and suggests the use of the correct version. It also ignores capital letters and most punctuation so none of these mistakes will hamper the accuracy of your search. Besides, when using a combination of words, the search engine will suggest similar combinations with a higher number of results. Tip 4: Use words that are likely to appear within the text Unfortunately, our search engine is not able to interpret words yet. Therefore, words which do not appear in the body text will not return any result despite them denoting a group of present terms. For instance, if we are looking for studies focused on neurological diseases, using neurological as a keyword would not be the best option. Instead, you should use the name of each neurological disease such as bipolar disorder, schizophrenia or depression. In the same fashion, incomplete words do not return any result. Please include an asterisk (*) before and/or after the incomplete word in order to allow for partial matching. Try it out: canc* instead of canc(without wildcard). Also you can try out *oma, or even *geneti* Tip 5: Narrow down your search by filtering the results You can filter the results by the following options: general, study, and dataset. Under these categories, you will find more sub-filters to refine your search. Make sure that you click on Apply in order to filter the results. You can clear the filtering anytime. Advanced Searches Additional example queries: Search for DUO:0000005 and word lung example query Or write: DUO:0000005 AND lung Search for an exome sequencing study in dbGaP example query Or write: study_type: "exome sequencing" AND repository:dbGaP Search for an exome sequencing study in EGA example query Or write: study_type: "exome sequencing" AND repository:ega Search for a dataset that is at the EGA beacon and with type "Whole genome sequencing" and with number of samples between 100 and 2000 and with technology "Illumina HiSeq 2000" example query Or write: is_in_beacon:true AND dataset_types:"Whole genome sequencing" AND samples:[100 TO 2000] AND dataset_technologies:"Illumina HiSeq 2000" Search for PMIDS example query Or write: pmids:32025007

  Documentation discovery/metadata/search-box

• What is a DAC?

  What is a DAC? Given the complexity, scale, and diversity of global submitters and studies, the EGA operates a distributed data access model in which requests are made to the data controller, not to the EGA. The European Commission defines a data controller, in the General Data Protection Regulation (GDPR), as the person that determines the purposes for which and the means by which personal data is processed. A Data Access Committees, commonly referred to as DACs, comprise on or more individuals (or data controllers) that review data access requests and make decisions on who can access personally identifiable genetic, phenotypic, and clinical data deposited at the EGA. Therefore, the members of a DAC should be individuals who have the authority to approve data access requests. The animation describes how you can authorise access to your sensitive data with the help of Data Access Committee and Authorisation tool. Acknowledgement to CSC - IT Center for Finland, Elixir Finland, Elixir Europe. Frequently Asked Questions How can I create a Data Access Committee? How can I create a Data Access Committee? The members of a DAC can come from different areas of expertise, such as data management, data analysis, information technology, legal and compliance, subject matter experts, privacy and security, and representatives from the organisations or individuals that provide data to the DAC. The specific members of a DAC can vary depending on the needs of the organisation and the type of data being managed. The EGA strongly suggests checking with your organisation to align with its regulations How should a DAC be named? The chosen name must be informative to the applicant.  For example, internal identifiers, such as grant numbers, should not be used. Individual PI names should also not be used. DAC's are often named after the organisation or department of the data source.  Browse the full list of DAC names currently in the EGA. How can I become an EGA DAC contact? To register a DAC at the EGA you must create first as an EGA user. Once your EGA user has been approved by the Helpdesk team, you will be able to log in to the DAC Portal. How can I register a DAC? To register a DAC, follow the DAC Portal instructions.  You will be required to provide a DAC name, name of the individual(s) that make up your DAC and contact details for your DAC including your Institutional email(s). Wherever possible, the DAC should make sure that all points of contact are readily available and able to answer any initial data requests/queries in < 2 weeks.  Once your DAC is registered, you will have to wait upon the validation from our Helpdesk team. As soon as all the validations have been completed, your DAC will be activated. Alternatively, you can also establish a DAC at the EGA during a programmatic submission through Webin API. Which are the possible roles of a DAC contact? There are two possible roles for DAC contacts: member and admin. An admin has additional privileges compared to a member: An “admin” can manage data requests, create and edit policies, edit the content of the DAC, add or remove contacts, and decide the role of each contact. A “member” can manage data requests and create policies. However, a member does not have permission to modify DAC details, edit information from policies where they are not admins, or add/remove contacts. There is no limit to the number of admins in a DAC, and each admin is responsible for deciding who should have editing privileges. This allows for a more decentralised and democratic approach to managing the DAC. How can I modify the information of a DAC? To modify a DAC, follow the instructions here. Keep in mind that only DAC contact with an admin role can modify the information of a DAC. If your DAC was registered before the lauch of the DAC Portal, and its ID is EGAC0 (not EGAC5), you must use the programmatic submission to modify it. Please, do not hesitate to contact our Helpdesk team if you need help with this! To prevent potential data breaches and ensure adherence to GDPR regulations, it is essential that the European Genome-Phenome Archive (EGA) is informed via the Helpdesk team of any changes to the Data Access Committee (DAC). This should be done in addition to any changes being made on the DAC portal. Data Controllers (as per the definition in the DPA) are also responsible for notifying the previous DAC of any modifications. Without proper notification, changes might not be automatically updated in our system, leading to the risk of incorrect permissions being applied and potential data access issues. Therefore, it is imperative that all Data Controllers follow this protocol to maintain data integrity and security. What’s the link between DAC, policy and dataset? A dataset is linked to one single policy. At the same time, one policy has a one to one relationship with a DAC. In this example, you can see that in this dataset page, we are only showing the information of one DAC (1 dataset - 1 DAC). However, the ratio of objects does not work the same in the other direction. One DAC can own multiple policy objects. And each policy object can be reused in several datasets. Thus, one DAC can manage one or more datasets. In this example, you can see that in this DAC page, we are showing all the datasets that are managed by one DAC (1 DAC - >400 datasets). EGA Data Access Committee Best Practices Which are the EGA DAC best practices? Refer to DAC Best Practices What happens if a DAC member changes institutions? EGA is committed to the protection and ownership of the data stored in our systems. We respect the institution's ownership of the data, and as such, if a DAC member changes institutions, the ownership of the data will not be transferred to the new institution. Therefore, before changing institutions, we request that the DAC contact add a new member who will replace them once they no longer work at the institution. This ensures that the data remains protected and is accessible to authorised personnel at the institution. To prevent potential data breaches and ensure adherence to GDPR regulations, it is essential that the European Genome-Phenome Archive (EGA) is informed via the Helpdesk team of any changes to the Data Access Committee (DAC). This should be done in addition to any changes being made on the DAC portal. Data Controllers (as per the definition in the DPA) are also responsible for notifying the previous DAC of any modifications. Without proper notification, changes might not be automatically updated in our system, leading to the risk of incorrect permissions being applied and potential data access issues. Therefore, it is imperative that all Data Controllers follow this protocol to maintain data integrity and security. What happens if EGA detects an unresponsive DAC? EGA defines an unresponsive DAC as a DAC with one or more contacts who do not respond to data access requests. EGA has procedures in place to identify these types of DACs, escalate the issue, and attempt to reassign the DAC to a responsive contact. This is a crucial step in ensuring that data can be accessed and utilised by researchers. If EGA identifies an unresponsive DAC, the organisation will first try to resolve the issue by escalating it to the appropriate parties. This may involve attempting to reassign the DAC to a more responsive contact. Unfortunately, in situations where we cannot reassign the DAC, the dataset will be withdrawn from the public website and the files will be removed from our system. If an EGA ID is referenced in a publication, the EGA will take extra steps to ensure that the public is made aware of the data's unavailability. I don't want to receive an email notification for pending requests. How can I do that? If you are an EGA DAC with pending requests, you will always receive emails for new data access requests. However, the EGA understands that a request resolution can take some time, for this reason, if you add a comment (make sure you save it by clicking the APPLY button!) we will filter those requests at the time of sending the notification! How can I manage data access requests? What documentation does the DAC need to provide? Each dataset that is submitted to the EGA must be linked to a policy object. The policy is a Data Access Agreement (DAA), which defines the terms and conditions of using the dataset, such as how the data files should be stored once downloaded or details of publication embargoes that should be observed by the approved user. As part of the Data Access Agreement, information regarding the application can be captured to help inform the DAC when making its decision. For example, requestors could be asked to provide a proposed title for their research and a proposal of how the data will be used. By asking for provision of such information the DAC can be assured that the requestor fully understands any consents associated with the data. It is important that accounts created at the EGA, are created solely for those individuals that will be downloading the data from the EGA. As part of the data access request, we strongly encourage you to identify individuals that will need an account at the EGA in order to prevent sharing of login details, which is strictly prohibited under EGA user account policy. Such information can easily be captured in the DAA. NOTICE The data access agreement template below is provided for guidance only and should be adapted as you see fit to suit your own purpose. In the interest of promoting data sharing, we suggest that if an agreement cannot be met around clause 19 in this example that both parties should agree to remain silent, and that the clause should be removed from the agreement. Example DAA How can the DAC provide the DAA? The DAC should provide their own DAA when registering a policy. Data requestors will download this document and should fill it in and send it back to the DAC. Data access decisions should be based on such documentation. The DAA can be downloaded through the request data webpage. Once it has been filled in, the signed copy of the DAA can be uploaded back to the request data webpage and sent to the DAC for review. How can I grant access to the data? Once you receive a data access request, you can login to the DAC Portal. In this portal you will see all your pending requests and will be able to grant or decline access to the requestors. I am a member of the Data Access Committee. Could I approve somebody else to deal with the requests on my behalf? If you want to delegate data access decisions to someone else, make sure that the individual's account is officially registered as a member of the DAC. Remember that a DAC contact with an "admin" role can always add new members to an existing DAC, remove members, and modify contact details through the DAC Portal. Can I automatise the process of managing data access requests? The answer is yes! You can use a programmatic approach using our DAC API! Check out the DAC API specification! Data Breach What should a DAC do if they suspect a breach? If a DAC suspects a data breach of one or more of their datasets, they should immediately contact the EGA Helpdesk team at this link. The DAC must provide the following information when contacting the EGA Helpdesk team: A list of affected datasets An estimated date of the data breach (or interval of dates) A list of unauthorised users who accessed the data (if available). Otherwise, they can provide a list of authorised users for the affected datasets Any observations they would like to raise to the EGA team Once the DAC has contacted the EGA team, we will respond within 48 hours (please allow some leeway during peak times) and activate our data breach protocol. What can I expect from the EGA if they detect a breach? Once the EGA determines that a security incident has occurred, we will notify all DAC members that a data breach has been detected, and take steps to contain the incident. Containment approaches may include: Revoking a data provider's access to the EGA resources, such as by changing passwords. Removing affected EGA datasets from distribution, such as by withdrawing a dataset. Disabling certain functions or services, such as the EGA ingestion pipeline. Shutting down the system or disconnecting it from the network. After the incident has been contained, the EGA will determine whether it is necessary to eradicate components related to the incident. Finally, the EGA will enable recovery of the service to normal operation and confirm that all services are functioning normally.

  Documentation access/data-access-committee/what-is-dac

• Data Use Ontology (DUO)

  Data Use Ontology Data Use Ontology at EGA The EGA is committed to its involvement in the work of GA4GH. In an effort to enhance data discoverability and streamline data access, EGA have implemented the use of the Data Use Ontology (DUO), based on consent codes as described in Dyke et al. 2017. The Data Use Ontology codes will be displayed on the live dataset page of your submission to advise any would be requestor on how the data can be used and also to enhance data discoverability as users will be able to search on these codes to find applicable datasets. DUO can be browsed online via the Ontology Lookup Service Learn more reading the Data Use Ontology publication and the GA4GH Machine-Readable Consent Guidance! Check our DAC Portal Take The Tour and learn how to add DUO codes to your policy! Term Shorthand Label Description DUO:0000004 NRES no restriction This data use permission indicates there is no restriction on use. DUO:0000042 GRU general research use This data use permission indicates that use is allowed for general research use for any research purpose. DUO:0000006 HMB health or medical or biomedical research This data use permission indicates that use is allowed for health/medical/biomedical purposes; does not include the study of population origins or ancestry. DUO:0000007 DS disease specific research This data use permission indicates that use is allowed provided it is related to the specified disease. DUO:0000011 POA population origins or ancestry research only This data use permission indicates that use of the data is limited to the study of population origins or ancestry. DUO:0000012 RS research specific restrictions This data use modifier indicates that use is limited to studies of a certain research type. DUO:0000015 NMDS no general methods research This data use modifier indicates that use does not allow methods development research (e.g., development of software or algorithms). DUO:0000016 GSO genetic studies only This data use modifier indicates that use is limited to genetic studies only (i.e., studies that include genotype research alone or both genotype and phenotype research, but not phenotype research exclusively) DUO:0000018 NPUNCU not for profit, non commercial use only This data use modifier indicates that use of the data is limited to not-for-profit organizations and not-for-profit use, non-commercial use. DUO:0000019 PUB publication required This data use modifier indicates that requestor agrees to make results of studies using the data available to the larger scientific community. DUO:0000020 COL collaboration required This data use modifier indicates that the requestor must agree to collaboration with the primary study investigator(s). DUO:0000021 IRB ethics approval required This data use modifier indicates that the requestor must provide documentation of local IRB/ERB approval. DUO:0000022 GS geographical restriction This data use modifier indicates that use is limited to within a specific geographic region. DUO:0000024 MOR publication moratorium This data use modifier indicates that requestor agrees not to publish results of studies until a specific date. DUO:0000025 TS time limit on use This data use modifier indicates that use is approved for a specific number of months. DUO:0000026 US user specific restriction This data use modifier indicates that use is limited to use by approved users. DUO:0000027 PS project specific restriction This data use modifier indicates that use is limited to use within an approved project. DUO:0000028 IS institution specific restriction This data use modifier indicates that use is limited to use within an approved institution. DUO:0000029 RTN return to database or resource This data use modifier indicates that the requestor must return derived/enriched data to the database/resource. DUO:0000043 CC clinical care use This data use modifier indicates that use is allowed for clinical use and care. DUO:0000044 NPOA population origins or ancestry research prohibited This data use modifier indicates use for purposes of population, origin, or ancestry research is prohibited. DUO:0000045 NPU not for profit organisation use only This data use modifier indicates that use of the data is limited to not-for-profit organisations. DUO:0000046 NCU non-commercial use only This data use modifier indicates that use of the data is limited to not-for-profit use. Point to Notice: For the consent code DUO:0000007 where data is restricted to use on a specific disease, please accompany it with an appropriate ontology from MONDO e.g., If the data is restricted to the use of research into juvenile idiopathic arthritis the code should be displayed as DUO:0000007; MONDO:0011429.

  Documentation access/data-access-committee/data-use-ontology

• How to request data

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

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

• Projects

  Projects Jointly managed by the European Bioinformatics Institute (EMBL-EBI) in Cambridge (UK) and the Centre for Genomic Regulation (CRG) in Barcelona, the EGA provides an invaluable service to the worldwide biomedical research community. The teams leading the EGA are involved in several international partnerships and consortia in numerous scientific fields, where they contribute to ambitious projects. In addition to the project listed below, The EGA is in a long-standing partnership with the Global Alliance for Genomics and Health (GA4GH), as described on the dedicated page. On-going projects Project Duration Domain Funder Tags EASIGEN-DS | The EASIGEN-DS project aims to conduct a design study to establish a new European Research Infrastructure on Advanced Genomics Technologies, EASIGEN. To develop an excellent scientific, technological and operational design, we will conduct landscape studies, stakeholder consultations, and community surveying. 2025-2028 Genomic and health data Horizon Europe DATA MANAGEMENT DOCUMENTATION INFRASTRUCTURE Go-IMPaCT | Go-IMPaCT will contribute sequenced genomes and provide infrastructure as part of IMPaCT-Cohort, one of the three fundamental pillars of the Precision Medicine Infrastructure associated with Science and Technology (IMPaCT) program in Spain. Along with the Genome of Europe (GoE) project, around 18.000 people will have their genomes sequenced, also contributing to Spain's commitments in 1+MG. Go-IMPaCT will fund the development of an EGA node to manage and share this genomic and phenoclinic data, laying the foundations for regional and ethnic genomic variability in Spain to be available for research purposes. The IMPaCT cohort is created with the spirit of being an open research tool, compatible with the rest of the health research ecosystem, and other international initiatives. 2025-2027 Large-scale genomics and health data; personalised medicine Instituto de Salud Carlos III ACCESS DISCOVERY INFRASTRUCTURE METADATA STANDARDS FAIR-FEGA | This project seeks to accelerate data depositions into FEGA, significantly increasing the data flow in and from FEGA nodes. It will build capacity within the FEGA nodes and increase awareness in a wide range of stakeholders, thus altogether achieving the ultimate goal of enhancing data reuse. The project will be carried out by a strategic consortium comprising seven ELIXIR nodes and two ELIXIR communities. 2025-2026 Not applicable ELIXIR ACCESS DISCOVERY DOCUMENTATION INFRASTRUCTURE METADATA STANDARDS FEGA-Connect | A consortium of six ELIXIR nodes plus the Polish FEGA node (in-kind contribution) joining forces to build a solid base to develop solutions for effective multi-omic sensitive data integration between FEGA nodes and other infrastructures and specialised Data repositories. We aim to promote a more coherent data deposition, discoverability and retrieval of multi-omics datasets, providing FAIRer data and consequently accelerating research. 2025-2026 Multi-omics data ELIXIR ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE METADATA STANDARDS IMPaCT-Data 2 | IMPaCT-Data 2 will develop a digital platform for the integration and modelling of biomedical data associated with IMPaCT (Precision Medicine Infrastructure associated with Science and Technology) projects in Spain. It will deploy a sustainable infrastructure that facilitates the integration, standardisation, interoperability and analysis of clinical, genomic, molecular and medical imaging data. This platform will be aligned with European projects such as Genome of Europe (GoE), the first project to make use of the European Genomic Data Infrastructure (GDI), and EUCAIM. IMPaCT-Data 2 will benefit from advanced Artificial Intelligence and High Computing Capacity Systems capabilities, offering robust and accessible tools for researchers from the National Health System in Spain. 2025-2026 Large-scale genomics and health data; personalised medicine Instituto de Salud Carlos III ACCESS DISCOVERY INFRASTRUCTURE METADATA STANDARDS ERDERA | The European Rare Disease Research Alliance (ERDERA) takes over EJPRD to deliver concrete health benefits to rare disease patients in the next decade by advancing prevention, diagnosis and treatment research. To leave no one behind, over 170 organisations championed by the European Union and member states are working hand in hand to make Europe a world leader in rare diseases research and innovation. 2024-2034 Rare diseases Horizon Europe; "La Caixa" Foundation cofunds CRG's contribution ACCESS DATA ANALYSIS DISCOVERY INFRASTRUCTURE GoE | The Genome of Europe initiative aims to build a European network of national genomic reference cohorts of at least 500.000 citizens. These reference cohorts will be selected to be representative of the European population. 2024-2028 Large-scale genomic and health data Horizon Europe ACCESS DISCOVERY INFRASTRUCTURE METADATA STANDARDS HEREDITARY | HEREDITARY aims to transform the way we approach disease detection, prepare treatment response, and explore medical knowledge by building a robust, interoperable, trustworthy, and secure framework that integrates multimodal health data (including genetic data) while ensuring compliance with cross-national privacy-preserving policies. 2024-2027 Neurodegenerative disorders, gut-brain interplay Horizon Europe DATA MANAGEMENT DATA ANALYSIS EOSC-ENTRUST | The mission of EOSC-ENTRUST is to create a European network of trusted research environments for sensitive data and to drive European interoperability by joint development of a common blueprint for federated data access and analysis. 2024-2026 Trusted Research Environment Horizon Europe INFRASTRUCTURE EBV-MS | "Targeting Epstein-Barr Virus Infection for Treatment and Prevention of Multiple Sclerosis". The ambitious goals of the project are to answer the questions why only a few EBV infected persons develop MS, and define the underlying mechanism of this process, as well as clarify if targeting the EBV infection can prevent MS or improve the disease course. 2023-2028 Viral-host genetics; immune response; disease modelling; Disease prevention Horizon Europe DATA MANAGEMENT DATA ANALYSIS WISDOM | WELL-BEING IMPROVEMENT THROUGH THE INTEGRATION OF HEALTHCARE AND RESEARCH DATA AND MODELS WITHOUT BORDER FOR CHRONIC IMMUNE-MEDIATED DISEASES aims to deploy novel approaches for data processing, harmonisation, management, and secure data sharing and federated access for diseases like multiple sclerosis. Using an end-user guided approach, it will facilitate responsible and critical assessment of the use of AI in healthcare. 2023-2028 Chronic immune-mediated diseases Horizon Europe DATA MANAGEMENT INFRASTRUCTURE EUCAIM | EUropean Federation for CAncer IMages is a project that will build a highly secure, federated and large-scale European cancer imaging platform, with capabilities that will greatly enhance the potential of Artificial Intelligence in oncology. 2023-2027 Cancer Digital Europe Programme (DIGITAL) DISCOVERY CONTAGIO | CONTAGIO (COhorts Network To be Activated Globally In Outbreaks) aims to create coordination mechanisms to rapidly react to infectious disease (re-)emergence in low- and middle-income countries (LMICs). 2023-2026 Infectious Diseases European Commission - Horizon Europe ACCESS DATA MANAGEMENT DISCOVERY Youth-GEMs | Youth-GEMS (Gene Environment Interactions in Mental Health TrajectorieS of Youth) will conduct research into the genetic and environmental factors of mental health in young European people. 2022-2027 Mental health European Commission - Horizon Europe DATA MANAGEMENT DISCOVERY GDI | The European Genomics Data Infrastructure project is enabling access to genomic and related phenotypic and clinical data across Europe. It is doing this by establishing a federated, sustainable and secure infrastructure to access the data. 2022-2026 Genomic and health data European Commission - Horizon Europe; "La Caixa" Foundation cofunds CRG's contribution DISCOVERY DOCUMENTATION INFRASTRUCTURE EOSC4Cancer | EOSC4Cancer builds on existing projects, research outcomes and established community solutions to create the federated FAIR data, analysis and services infrastructure needed for European Cancer research programmes. 2022-2025 Cancer European Commission - Horizon Europe DISCOVERY IMPaCT-T2D | The IMPaCT-T2D project aims at studying the complete genomes of a large cohort of patients with Type 2 Diabetes mellitus (T2D), using modern sequencing technologies and artificial intelligence (AI) in order to improve the stratification and pharmacological treatment in the context of precision medicine. 2022-2025 Cardiovascular and Complex Diseases Spanish Ministry of Science and Innovation; Instituto de Salud Carlos III ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE EuCanImage | A European Cancer Image Platform Linked to Biological and Health Data for Next-Generation Artificial Intelligence and Precision Medicine in Oncology. 2020-2025 AI Solutions in Oncology European Commission - H2020 Programme; "La Caixa" Foundation cofunds CRG's contribution DATA MANAGEMENT METADATA STANDARDS GenoMed4ALL | A consortium built to empower personalised medicine in the field of haematological diseases through the use of AI and the pooling of genomic and clinical data. 2020-2025 Hematological diseases European Commission - H2020 Programme DISCOVERY METADATA STANDARDS Completed projects Project Duration Domain Funder Tags BY-COVID | The BeYond-COVID project aims to make COVID-19 data accessible to scientists in laboratories but also to anyone who can use it, such as medical staff in hospitals or government officials. Going beyond SARS-CoV-2 data, the project will provide a framework for making data from other infectious diseases open and accessible to everyone. 2021-2024 Infectious diseases European Commission - H2020 Programme ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE IMPaCT-Data | IMPaCT-Data aims to create the infrastructure for secondary use of data from Spanish healthcare systems - electronic health records, medical imaging and genomic repositories - and contribute with the knowledge and methodology produced to the healthcare system. 2021-2024 Large-scale genomics and health dataSpanish Ministry of Science and Innovation; Instituto de Salud Carlos III ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE LaMarató | It is a project aimed at creating and developing a catalan interhospitalary network to interrogate genetic variants from thousands of genetic tests carried out in patients with rare diseases from the main catalan hospitals. 2021-2024 Genomic and health data Fundació La Marató de TV3 (catalan foundation) DISCOVERY HealthyCloud | This consortium will contribute a Strategic Agenda towards the European Health Research and Innovation Cloud. The project will work in collaboration with a broad range of stakeholders to ensure that all voices are included and that the results are technically and ethically sound. 2021-2023 Not Applicable European Commission - H2020 Programme DOCUMENTATION B1MG | Beyond 1 Million Genomes aims to create a network of genetic and clinical data across Europe. The project provides coordination and support to the 1+ Million Genomes Initiative (1+MG). This initiative is a commitment of 24 EU countries, the UK and Norway to give cross-border access to one million sequenced genomes by 2022. 2020-2023 Not applicable European Commission - Horizon Europe DATA MANAGEMENT INFRASTRUCTURE METADATA STANDARDS ELIXIR-CONVERGE | An alliance with the goal of Connecting and aligning ELIXIR Nodes to deliver sustainable FAIR life-science data management services. 2020-2023 Data Management and Infectious Diseases European Commission - H2020 Programme DATA MANAGEMENT INFRASTRUCTURE METADATA STANDARDS IHCC | The International HundredK+ Cohorts Consortium aims to create a global platform for translational research – informing the biological and genetic basis for disease and improving clinical care and population health. 2020-2022 Translational research NIH; The Wellcome Trust; CZI INFRASTRUCTURE METADATA STANDARDS PPCG | The Pan Prostate Cancer Group aims to harmonise and interrogate Whole Genome DNA Sequence data generated around the world from over 2000 men with prostate cancer, with associated transcriptome and methylome data to include men from different clinical categories, and ethnicities. This project is about providing breakthrough advances through analysis of a very large series of Whole Genome DNA data from prostate cancer contributed by many of the leading scientists and clinicians working in prostate cancer genomics. 2019-2024 Cancer Cancer Research UK DATA MANAGEMENT CINECA | Consortium providing a Federated solution enabling population-scale genomic and biomolecular data accessible across international borders accelerating research and improving the health of individuals resident across continents. 2019-2023 Large-scale Genomics and Health Data European Commission - H2020 Programme ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE EASI-Genomics | A project designed to provide easy access to cutting-edge DNA sequencing technologies to researchers from academia and industry, within a framework that ensures compliance with ethical and legal requirements, as well as FAIR and secure data management. 2019-2023 Next Generation Sequencing European Commission - H2020 Programme ACCESS EJP-RD | An European consortium built to create a comprehensive, sustainable ecosystem allowing a virtuous circle between research, care, and medical innovation. 2019-2023 Rare diseases European Commission - H2020 Programme ACCESS DATA MANAGEMENT DOCUMENTATION METADATA STANDARDS EOSC-Life | EOSC-Life brings together the 13 Life Science research infrastructures (LS RIs) to create an open, digital and collaborative space for biological and medical research. The project will publish 'FAIR' data and a catalogue of services provided by participating RIs for the management, storage and reuse of data in the European Open Science Cloud (EOSC). 2019-2023 Not applicable European Commission - H2020 Programme DOCUMENTATION EUCANCan | A federated network aiming at implementing a cultural, technological and legal integrated framework across Europe and Canada, to enable and facilitate the efficient sharing of cancer genomic data. 2019-2023 Cancer European Commission - H2020 Programme DATA MANAGEMENT METADATA STANDARDS The Federated EGA framework: supporting sensitive data management across the ELIXIR Nodes | This project is a direct continuation of the FHD IS with the goal to position the FEGA framework as the core infrastructure driver to support human data sharing for research. 2019-2023 Human genomic data ELIXIR INFRASTRUCTURE UK Biobank | UK Biobank is a large-scale biomedical database and research resource, containing in-depth genetic and health information from half a million UK participants. This project is to archive whole genome sequencing and other genetic data for UK Biobank participants. 2019-2023 Large-scale Genomics and Health Data The Wellcome Trust; UKRI; Amgen; AstraZeneca; GSK; Johnson & Johnson DATA MANAGEMENT INFRASTRUCTURE VEIS | The core mission of VEIS is to create an open ecosystem of technologies that will address and adapt to the requirements of the systems used to analyse and interpret -omics and clinical data in research and application environments in biomedicine. The aim of the project is to leverage the value of the EGA for both industry and society. 2019-2022 Oncology and Rare diseases Generalitat de Catalunya and European Regional Development Fund (ERDF) ACCESS DISCOVERY ELIXIR BEACON IS | This study follows on from a number of earlier activities that have established the ELIXIR Beacon Project. The main aim is to extend the Beacon protocol, developed at EGA, to become the reference ELIXIR Data Discovery product 2019-2021 Not applicable ELIXIR DISCOVERY ELIXIR FHD IS | This project coordinates the delivery of FAIR compliant metadata standards, interfaces, and reference implementation to support the federated ELIXIR network of human data resources. 2019-2021 Human genomic data ELIXIR INFRASTRUCTURE ELIXIR Rare Disease | The Rare Disease Community extends and generalises the system of access authorisation and high volume secure data transfer developed within the EGA. The goal of the Community is to create a federated infrastructure that will enable researchers to discover, access and analyse different rare disease repositories across Europe. It is doing this in partnership with other European infrastructure projects, namely RD-CONNECT, BBMRI-ERIC and E-Rare.2019-2021 Rare diseases ELIXIR INFRASTRUCTURE Solve-RD | Solve-RD - solving the unsolved rare diseases - is a research project funded by the European Commission. It echoes the ambitious goals set out by the International Rare Diseases Research Consortium (IRDiRC) to deliver diagnostic tests for most rare diseases by 2020. The current diagnostic and subsequent therapeutic management of rare diseases is still highly unsatisfactory for a large proportion of rare disease patients - the unsolved RD cases. For these unsolved rare diseases, we are unable to explain the etiology responsible for the disease phenotype, predict the individual disease risk and/or rate of disease progression, and/or quantitate the risk of relatives to develop the same disorder. 2018-2024 Rare diseases European Commission - H2020 Programme ACCESS DATA MANAGEMENT METADATA STANDARDS EuCanShare | An EU-Canada joint infrastructure for next-generation multi-Study Heart research. 2018-2022 Cardiovascular Diseases European Commission - H2020 Programme ACCESS METADATA STANDARDS

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