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• Best Practices for DACs

  Best Practices Data access committees (DACs) are institutional safeguards responsible for ensuring a balance between data protection and accessibility. However, there are no procedural standards that apply across DACs, which can lead to inconsistencies in their reviews and compromise their quality and effectiveness. Standardising DAC processes can foster trust and mutual recognition, paving the way for greater coordination, collaboration, and delegation between DACs and other oversight bodies to improve the efficiency of data access without sacrificing protection. To provide guidance, the following are suggestions for actions a DAC might take upon receiving a data access request: Aim to respond to all initial requests in less than 2 weeks. Failure to do so may result in follow-up emails from the EGA, journals, and ultimately dataset withdrawal. First, check that the data/EGAD number is consistent with your data submission. In other words, ensure that the requester has contacted the correct DAC. Verify that the user will be using the data within the terms of consent by asking them to sign up to the terms within the DAA. Ensure that data users who are granted access to the data comply with the terms of a Data Access Agreement (DAA) and to use the data only in approved ways. Look for an institutional email address for the requester. Search for evidence that the requester is "appropriately qualified/bona fide" for using the data, for example on PubMed, Research Gate, LinkedIn, etc. Confirm that the affiliated organisation is real and that the requester still works there. Inquire with the requester about who should have accounts created at the EGA under the terms of the agreement. If a negative decision is made, promptly communicate it to the requester and support it with the terms of the Data Access Policy that the requester has not met or cannot meet. Keep the information in the DAC up to date. If you leave your institution and are unable to manage data access requests on their behalf, you should add your replacement as a new contact in the DAC. Assist with data access requests for any further questions related to your data. The EGA can only check information that has been deposited in the repository. If the user has a specific question that the EGA cannot answer, we will redirect the user to the DAC. All the EGA studies and datasets referenced in a publication under your DAC must be publicly searchable on the EGA website before the paper is released. If possible, describe the permitted purposes for subsequent research projects, including associated limits and conditions, for all resources hosted in a repository using a common ontology, such as the GA4GH Data Use Ontology (DUO). It is considered best practice to try and release data only to those with an institutional email address. This gives reassurance to the EGA, research participants, and the general public that an appropriate individual is accessing and using the data. 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.

  Documentation access/data-access-committee/best-practices

• Molecularly matched targeted therapies plus radiotherapy in patients with newly diagnosed glioblastoma without MGMT promoter hypermethylation (N2M2/NOA-20 phase I/IIa umbrella trial)

  Background: Patients with glioblastoma without MGMT promoter hypermethylation are unlikely to benefit from temozolomide (TMZ). Trials aiming at replacing TMZ with targeted agents in not molecularly selected patient populations have failed. Methods: This phase I/IIa umbrella trial aimed at showing safety, feasibility, and preliminary efficacy of targeted compounds in addition to standard radiotherapy initiated within 42 days postoperatively. Molecular diagnostics and bioinformatic evaluation are performed within 28 days after surgery. Stratification for treatment takes place in five subtrials, including alectinib, idasanutlin, palbociclib, vismogedib and temsirolimus, according to the best matching molecular alteration. Patients without matching alterations are randomized between subtrials without strong biomarkers using atezolizumab and asunercept and TMZ as standard of care. Primary objective of the phase I parts of the trial was dose finding or dose validation. In the phase IIa trials, centrally determined progression-free survival at six months (PFS-6) is used as endpoint for efficacy with interim analyses for futility (H0: p=0.231). Results: From May 2018 through July 2022, 301 patients were enrolled and 228 treated in 13 German NOA sites. The alectinib and vismodegib subtrials were closed since no molecularly matching patients were accrued; the idasanutlin subtrial was closed prior to the optimal dose at nine patients at discretion of the company providing the drug. The TMZ subtrial showed a PFS-6 of 18.52% (10/54 patients) (p=0.831) and a median overall survival (OS) of 12.1 months. Asunercept: PFS-6 of 15.4% (4/26) (p=0.8825) and OS of 12.8 months. Atezolizumab: PFS-6 of 21.4% (9/42) (p=0.660) and OS of 11.7 months. Palbociclib with patients demonstrating CDK4 amplification or CDKN2A/B codeletion: PFS-6 of 24.4% (10/41) (p=0.4823) and OS of 12.6 months. Temsirolimus with patients demonstrating mTOR activation: PFS-6 of 39.1% (18/46) (p=0.0109) and OS of 15.4 months. The regimen-limiting toxicity (RLT)-rate is 34.8%, which is insignificantly above the predefined unacceptable rate for RLTs of 30%. Most RLTs had severity grade 3, one RLT had severity grade 4. No RLTs resulted in death. Conclusions: N2M2 allows for elaborate molecular testing being integrated into the treatment decision and efficient determination of treatment activity for patients with newly diagnosed glioblastoma. There is clinical activity of temsirolimus in patients with tumors harboring an activated mTOR pathway although this is not positively prognostic without mTOR inhibition; there is no clinical activity for asunercept and atezolizumab in not molecularly selected patients and also palbociclib in molecularly selected patients.

  Study EGAS00001008033

• National Cancer Institute Cancer Genome Characterization Initiative (CGCI)

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

  Study phs000235

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

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

  Dataset EGAD50000000559

• Localised colon cancer WES study contaning WBCs, tissue and plasma samples at different time points

  Decision-making based on circulating tumor DNA (ctDNA) status following curative-intent surgery in stage II-III colon cancer (CC) is where the strongest clinical evidence lies. Commercial or academic assays are predominantly used to detect ctDNA, aiming to reveal minimal residual disease (MRD) and identify patients at high risk of recurrence. However, while current tests demonstrate exceptional specificity in detecting MRD among patients who later experience recurrence, their sensitivity is notably limited, particularly immediately after surgery when decisions regarding ACT are crucial. Additionally, up to 70% of patients with stage II-III colon cancer fail to clear ctDNA after standard adjuvant treatment (ACT) and subsequently experience recurrence. In this study, we performed whole exome sequencing (WES) of ctDNA at different timepoints in relapsed CC patients using two independent cohorts, alongside transcriptomic and proteomic analyses of metastases to gain a deeper understanding of progression mechanisms. An assay based on a tumor-agnostic approach from WES could enhance sensitivity in detecting MRD disease compared to current assays. Immune evasion appears to be the primary driver of progression in the localized CC setting, facilitated by a functional mutational burden at relapse. This suggests that immunotherapy could extend its efficacy to patients with microsatellite stability, broadening treatment options. Moreover, organoid modeling affirms the promising potential of targeted therapy to surpass conventional treatments in eradicating MRD.

  Study EGAS50000000204

• FIGHT-207: Anonymized Genomic Alterations and Clinical Responses

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

  Study phs003590

• Heart Failure Network: Entresto(TM) in Advanced Heart Failure (HFN-LIFE-BioLINCC)

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

  Study phs004171

• Cincinnati Children's Hospital Medical Center (CCHMC) - eMERGE Phase IIIA Data

  This submission includes genotyping or sequencing data from separate cohorts, each is described in separate paragraphs below. Extreme early onset obesity Obesity is a serious epidemic condition and on the rise in the United States. Today, nearly one out of three children is overweight or obese in this country. According to the Center for Disease Control, 35.7% of American adults and 17% of American children are obese. The medical costs associated with obesity are estimated to be in the billions. Without a doubt, interplay of additive genetic effects and common environmental effects influence this complex disease. However, despite being exposed to so-called "obesogenic environment", a large proportion of the population remains of normal weight. These observations suggest that innate, non-environmental, factors make some individuals more susceptible to obesity providing support for biological mechanisms, and thus genetic factors, to underlie the individual's response to the obesogenic environment. In young children with severe obesity the relative role of genetics and in utero programming are likely to outweigh the short duration of environmental and lifestyle exposures. This group is therefore an ideal one to study as they are likely enriched for variants that influence the risk of developing obesity. The purpose of this project is to further study and understand obesity in childhood and to develop a repository of samples for future studies into obesity. Eosinophilic Esophagitis (EoE) Eosinophilic Esophagitis (EoE) is one of the manifestations of eosinophilic gastrointestinal inflammation which have profound effects on a patient's health and development. Results of epidemiologic studies performed through our center demonstrate that eosinophil-associated gastrointestinal disease is not an uncommon entity. While the epidemiology of eosinophilic esophagitis has not been thoroughly studied until recently, there appears to be a significant increase in the diagnosis of EoE in the last decade. Based on our research, this mainly reflects increased disease recognition, but there is also a bona-fide increase in disease incidence which coincides with the increasing incidence of asthma and allergic diseases in the industrialized world. In addition, many patients with intractable symptoms thought in the past to represent atypical GERD or other disorders are now being recognized as having EoE. Diagnosis of EoE requires endoscopy and biopsies to document the characteristic histologic findings of esophageal eosinophilia. In general, this study proposed to elucidate the mechanisms underlying eosinophil growth, survival, migration, and function, and to investigate and further characterize the pathophysiology of, clinical manifestations of, and spectrum of disease severity of eosinophilic esophagitis in humans. The de-identified genotyping and genome wide association data generated as part of this research will be used for further genome research. Familial Sample Repository (FSR) and Directed Sample Repository (DSR) De novo mutations could cause many diseases, which has been demonstrated in mental retardation, autism and many rare genetic disorders. Family-based studies have a variety of advantages over case/control studies, including the elimination of analysis artifacts related to population stratification, the detection of genes that act through a recessive mechanism of inheritance and validation that the trait is not transmitted from a parent, something not possible using a case/control design. Additionally, DNA from families can be used to identify de novo mutations suggesting strong candidate causal polymorphisms. For this project, samples will be collected from families on an on-going basis. Families may be recruited because the patient either has a disease which is thought to be of genetic origin or from the general patient population to serve as controls or future identified diseases. Some phenotypes under study include fibroblastic rheumatism, diaphragmatic hernia, polymicrogyria, severe congenital neutropenia, primary sclerosing cholangitis and staph infection. CLRR-Cincinnati Lupus Registry and Repository Systemic lupus erythematosus (SLE) is a complex, partially understood autoimmune disorder. Genetic origins for SLE are supported by high heritability (> 66%), familial aggregation, increased monozygotic twin concordance, genetic linkages, and candidate gene genetic association, including HLA genes, Fc receptors, and complement components. Relevant environmental factors likely include infections (Epstein-Barr virus), therapeutics, personal habits (smoking), and diet. To continue a research resource facility for collection of well-characterized pedigrees containing a proband with systemic lupus erythematosus we develop this repository. Juvenile Idiopathic Arthritis (JIA) Juvenile Idiopathic Arthritis (JIA) is a debilitating complex genetic disorder characterized by inflammation of the joints and other tissues and shares histopathological features with other autoimmune diseases. It is considered complex genetic traits. There are more than 50,000 children with JIA in the USA, approximately 1 per 1000 births, which is about the same incidence as juvenile diabetes. It is believed that genes in the major histocompatibility complex (MHC) play a role in defining genetic risk, and it can be hypothesized that loci in other chromosomal regions are involved in conferring risk in JIA. These candidate chromosomal regions can be identified using genome-wide association analyses. The long-term goal is a comprehensive understanding of the genetic basis of these disabling arthropathies for which the molecular basis is not presently understood. These data will contribute to a national resource for the study of autoimmunity in children. Better Outcomes for Children-Cytogenetics Since 2007, more than 4000 samples, enriched with various rare or common genetic diseases as well as specific chromosomal abnormalities such as deletions and duplications have been genotyped for the purpose of subsequent GWAS and Phewas analyses and uncovering main genetic effects.

  Study phs001011

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

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

  Study phs000674

• Prognostic and therapeutic significance of leukemia subtypes and minimal residual disease measurements in pediatric acute lymphoblastic leukemia treated with contemporary risk-directed trial: a cohort study

  Background Genomic analyses to identify leukemia subtypes and refinement of minimal residual disease (MRD) determination are two recent advances that would have substantial impact on the management of children with acute lymphoblastic leukemia (ALL). However, the combined application of these two approaches to determine the prognostic and therapeutic significance of MRD measurement and full spectrum of leukemia subtypes in the context of contemporary risk-directed therapy has not been studied comprehensively.MethodsBetween October 29, 2007 and March 26, 2017, 598 consecutive children with newly diagnosed ALL were enrolled in a clinical trial at St. Jude Children’s Research Hospital. Patients were provisional classified according to the presenting clinical and laboratory features including immunophenotype and cytogenetics. Patients with ETV6-RUNX1 and high hyperdiploid B-progenitor ALL were provisionally included in the low-risk groups; those with TCF3-PBX1, hypodiploidy and T-cell ALL in the standard (intermediate)-risk group; and patients with BCR-ABL1, KMT2A and early T-cell precursor ALL in the high-risk group. Final risk assignment was based primarily on MRD levels measured by flow cytometry on Day 15 (≥1%) and Day 42 (<0.01% or ≥1%) of remission induction. Using genomic classification based on cytogenetics and genomic analysis (single nucleotide polymorphism array analysis and transcriptome, exome, and genome sequencing), patients were classified into 17 subtypes. The primary aim was to determine the event-free survival, overall survival and cumulative risk of relapse according to specific leukemia subtypes and MRD levels on Days 8, 15 and 42 of remission induction. This clinical trial was registered at ClinicalTrials.gov, number NCT00549848.FindingsPatients with ETV6-RUNX1, high hyperdiploidy and DUX4-rearranged B-ALL all received low- or standard-risk therapy, and had the highest 5-year event-free survival rates: 98.4% (95% CI, 95.9-100), 95.3% (91.2-99.4), and 95.0% (84.2-100), respectively. All 142 patients with Day 8 MRD<0.01%, except two with KMT2A-rearranged ALL and one with TCF3-PBX1, were in continuous complete remission. The TCF3-PBX1, PAX5alt, T-cell, early T-cell precursor, iAMP21 and hypodiploid ALL had intermediate outcome with 5-year event-free survival rates ranging from 80.0% (39.4-100) to 88.2% (71.7-100). Patients with KMT2A-rearranged, BCR-ABL1, BCR-ABL1-like and ETV6-RUNX1-like ALL had the worst outcomes, with 5-year event-free survival rates between 64.1% (43.9-84.3) and 76.2% (51.9-100), despite most patients receiving standard- or high-risk therapy. Treatment intensification based on MRD and genotype improved outcome. Relapse did not occur in any of the patients with ETV6-RUNX1, DUX4-rearranged, TCF3-PBX1, iAMP21, ZNF384-rearranged, hypodiploid, or BCR-ABL1-like B-ALL who had day 15 MRD≥1% and received standard-risk therapy. However, day 42 MRD<0.01% did not preclude relapse in patients with intermediate-risk or unfavorable subtypes including TCF3-PBX1, PAX5alt, T-cell, iAMP21, BCR-ABL1, BCR-ABL1-like, ETV6-RUNX1-like, KMT2A-rearranged, and MEF2D-rearranged ALL, despite intensified treatment in the standard- or high-risk arms. InterpretationContemporary risk-directed treatment based on genotypes and MRD can cure virtually all patients with ETV6-RUNX1, hyperdiploid>50 and DUX4-rearranged ALL. While intensified treatment improve outcome for patients with high MRD during induction, substantial proportions of patients with intermediate-risk or unfavorable subtypes would still relapse even achieving negative MRD status at the end of induction and require novel therapeutics to improve outcome.

  Study EGAS00001004739

• The British Autozygosity Populations BioResource (2022-04-26)

  This data set contains whole exome sequences of individuals from 8086 (mostly British Pakistani/British Bangladeshi, mostly self-reported parentally related) individuals from the following studies: 1. 5236 British Pakistani/British Bangladeshi adults from East London Genes & Health, now known as Genes & Health 2. 2624 British South Asian mothers from Born in Bradford (mostly Pakistani) 3. 1061 British South Asian adults from Birmingham (mostly Pakistani) This dataset contains all the exome sequence data available for this study on 2022-04-26

  Dataset EGAD00001008736

• Women's Health Initiative Clinical Trial and Observational Study

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

  Study phs000200

• Health and Retirement Study (HRS)

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

  Study phs000428

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

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

  Study phs000494

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

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

  Blog new-dac-portal-v2

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

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

  Study phs001290

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

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

  Study phs000462

• Systolic Blood Pressure Intervention Trial (SPRINT-BioLINCC)

  Available DataThe available data include all elements of the previously released SPRINT Primary Outcome Paper (SPRINT-POP) data, the full SPRINT clinical data including the MRI and MIND data, and select ancillary study data (Ambulatory Blood Pressure Monitoring, APOL1, Acute Kidney Injury, ASK, Heart, FAST, PWV, Renal Resistance, Biomarkers, Plasma AD).ObjectiveThe Systolic Blood Pressure Trial (SPRINT) was conducted to test the hypothesis that treating systolic blood pressure to a target of less than 120 mm Hg, as compared to a target of less than 140 mm Hg, would reduce the incidence of cardiovascular disease.BackgroundHypertension is a highly prevalent condition among adults and is a leading risk factor for myocardial infarction and stroke. Further, isolated systolic hypertension is the most common form of hypertension in adults over 50 years of age. Observational studies have shown a monotonic increase in cardiovascular risk with systolic blood pressures above 115 mm Hg; however, general population clinical trials have only documented the benefits of lowering systolic blood pressure to a target of 150 mm Hg. A 2007 expert panel sponsored by the National Heart, Lung, and Blood Institute designated the hypothesis that lowering the systolic blood pressure goal to a level SubjectsA total of 9361 participants were enrolled, with 4,678 randomized to the intensive-treatment group and 4,683 randomized to the standard-treatment group.DesignSPRINT was a randomized, single blinded (outcome adjudicators were blinded to treatment assignment) treatment trial with participants randomized to a systolic blood-pressure target of either less than 140 mm Hg (the standard-treatment group) or less than 120 mm Hg (the intensive-treatment group). Following randomization, baseline hypertensive regimens were adjusted in accordance with study treatment algorithms established for each group. The study formulary included all major classes of antihypertensive agents. Investigators could prescribe other antihypertensive medications, but the use of drug classes with the strongest evidence for reduction in cardiovascular outcomes was encouraged. This included thiazide-type diuretics as the first-line agent, loop diuretics for participants with advanced chronic kidney disease, and beta-adrenergic blockers for participants with coronary artery disease. Medications for participants in the intensive-treatment group were adjusted on a monthly basis to target a systolic blood pressure of less than 120 mm Hg. Medications for participants in the standard-treatment group were adjusted to target a systolic blood pressure of 135 to 139 mm Hg, and the dose was reduced if systolic blood pressure was less than 130 mm Hg on a single visit or less than 135 mm Hg on two consecutive visits. Lifestyle modification was encouraged as part of the management strategy.Participants were seen monthly for the first 3 months and every 3 months thereafter. Demographic data were collected at baseline. Clinical and laboratory data were obtained at baseline and every 3 months thereafter. A structured interview was used in both groups every 3 months to obtain self-reported cardiovascular disease outcomes. Medical records and electrocardiograms were obtained for documentation of events. Incidences of hypotension, syncope, injurious falls, electrolyte abnormalities, and bradycardia that were evaluated in an emergency department were included in adverse event reporting. Occurrences of acute kidney injury or acute renal failure requiring hospitalization were also monitored. The primary outcome was a composite outcome of myocardial infarction, other acute coronary syndromes, stroke, heart failure, or death from cardiovascular causes.ConclusionsThe blood pressure intervention was stopped in August of 2015 (median follow-up of 3.26 years) after the cardiovascular outcome results exceeded the boundary for efficacy at two consecutive time points. Compared with a systolic blood pressure target of less than 140 mm Hg, an intensive systolic blood pressure target of 120 mm Hg resulted in lower rates of fatal and nonfatal major cardiovascular events and death from any cause. Significantly higher rates of some adverse events were observed in the intensive-treatment group.

  Study phs003483

• Systolic Blood Pressure Intervention Trial (SPRINT-Imaging)

  Available DataSystolic Blood Pressure Intervention Trial, SPRINT-Imaging, provides access to ECG signals data from the SPRINT clinical trial. The clinical phenotyping and outcomes data from the trial are associated with SPRINT-BioLINCC, phs003483.ObjectiveThe Systolic Blood Pressure Trial (SPRINT) was conducted to test the hypothesis that treating systolic blood pressure to a target of less than 120 mm Hg, as compared to a target of less than 140 mm Hg, would reduce the incidence of cardiovascular disease. BackgroundHypertension is a highly prevalent condition among adults and is a leading risk factor for myocardial infarction and stroke. Further, isolated systolic hypertension is the most common form of hypertension in adults over 50 years of age. Observational studies have shown a monotonic increase in cardiovascular risk with systolic blood pressures above 115 mm Hg; however, general population clinical trials have only documented the benefits of lowering systolic blood pressure to a target of 150 mm Hg. A 2007 expert panel sponsored by the National Heart, Lung, and Blood Institute designated the hypothesis that lowering the systolic blood pressure goal to a level SubjectsA total of 9361 participants were enrolled, with 4,678 randomized to the intensive-treatment group and 4,683 randomized to the standard-treatment group. DesignSPRINT was a randomized, single blinded (outcome adjudicators were blinded to treatment assignment) treatment trial with participants randomized to a systolic blood-pressure target of either less than 140 mm Hg (the standard-treatment group) or less than 120 mm Hg (the intensive-treatment group). Following randomization, baseline hypertensive regimens were adjusted in accordance with study treatment algorithms established for each group. The study formulary included all major classes of antihypertensive agents. Investigators could prescribe other antihypertensive medications, but the use of drug classes with the strongest evidence for reduction in cardiovascular outcomes was encouraged. This included thiazide-type diuretics as the first-line agent, loop diuretics for participants with advanced chronic kidney disease, and beta-adrenergic blockers for participants with coronary artery disease. Medications for participants in the intensive-treatment group were adjusted on a monthly basis to target a systolic blood pressure of less than 120 mm Hg. Medications for participants in the standard-treatment group were adjusted to target a systolic blood pressure of 135 to 139 mm Hg, and the dose was reduced if systolic blood pressure was less than 130 mm Hg on a single visit or less than 135 mm Hg on two consecutive visits. Lifestyle modification was encouraged as part of the management strategy. Participants were seen monthly for the first 3 months and every 3 months thereafter. Demographic data were collected at baseline. Clinical and laboratory data were obtained at baseline and every 3 months thereafter. A structured interview was used in both groups every 3 months to obtain self-reported cardiovascular disease outcomes. Medical records and electrocardiograms were obtained for documentation of events. Incidences of hypotension, syncope, injurious falls, electrolyte abnormalities, and bradycardia that were evaluated in an emergency department were included in adverse event reporting. Occurrences of acute kidney injury or acute renal failure requiring hospitalization were also monitored. The primary outcome was a composite outcome of myocardial infarction, other acute coronary syndromes, stroke, heart failure, or death from cardiovascular causes. ConclusionsThe blood pressure intervention was stopped in August of 2015 (median follow-up of 3.26 years) after the cardiovascular outcome results exceeded the boundary for efficacy at two consecutive time points. Compared with a systolic blood pressure target of less than 140 mm Hg, an intensive systolic blood pressure target of 120 mm Hg resulted in lower rates of fatal and nonfatal major cardiovascular events and death from any cause. Significantly higher rates of some adverse events were observed in the intensive-treatment group.

  Study phs003566

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

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

  Study phs003599

• Clonal selection after gene therapy in sickle cell disease

  While gene therapy (GT) provides a potentially curative treatment option for patients with sickle cell disease (SCD), the occurrence of myeloid malignancies in clinical trials has prompted concern. To interrogate potential mechanisms underlying increased cancer risk, we used hematopoietic stem cell (HSC) clonal tracking by whole genome sequencing (WGS) to map the somatic mutation and clonal landscape of 2,592 gene modified as well as unmodified single stem and progenitor cells from six SCD patients undergoing gene therapy (7-26 years old, average 12.7× depth). Pre-GT phylogenetic trees in SCD were highly polyclonal and mutation burdens per cell were elevated in some, but not all, patients. Post-GT, no clonal expansions were identified. However, an increased frequency of driver mutations associated with myeloid neoplasms or clonal hematopoiesis (DNMT3A- and EZH2-mutated clones in particular) were seen in both genetically modified and unmodified cells suggested positive selection of mutant clones during gene therapy. This work sheds light on the mutation landscape and HSC clonal dynamics in gene therapy for SCD and highlights enhanced fitness of some HSCs harboring pre-existing driver mutations following gene therapy. Future studies should define the long-term fate of mutant clones including any contribution to expansions associated with myeloid neoplasms.

  Dataset EGAD00001010913

• Genes and Blood Clotting Study (GABC)

  Objectives: Use genome-wide approaches to identify genetic variants that influence common thrombosis and hemostasis factors, as well as selected common human traits. Design/Methods: The GABC study was a prospective sibling cohort design. Siblings were recruited by targeted email to the undergraduate and graduate student email lists at the University of Michigan. Healthy persons between 14 and 35 years old who had healthy siblings within the same age restriction were able to participate. Study participants agreed to an online informed consent and subsequently completed a 52-question online survey describing their specific bleeding traits as well as many common human traits. Fifty milliliters of blood was collected into a citrate-dextrose solution (ACD) from each participant. An aliquot of whole blood was used for an automated complete blood count analysis and the remainder was processed into platelet poor plasma and buffy coat portions. Plasma and buffy coat aliquots were snap frozen and stored in liquid nitrogen for future studies. 1189 individuals representing 507 sibships were collected between 06/26/2006 and 01/30/2009. Phenotyping Survey Details: To characterize individual bruising and bleeding history, the online survey recorded answers to questions based on a modified von Willebrand Disease (VWD) screening questionnaire. To characterize a collection of participant's common human traits, the survey recorded answers to questions about height, weight, presence of skin tags, history of acne, eye color, hair color, hair line characteristics, skin sunburn sensitivity, skin tanning ability, natural skin color, freckling, cheek dimpling, earlobe shape, shoe size, foot arch characteristics, hand fifth digit morphology, history of dyslexia, history of migraine headaches, history of seasonal allergies, history of apthous ulcers, tendency to sneeze while walking into a bright sunny place, history of dental caries, need for corrective eye lenses, handedness and like or dislike of strongly flavored foods. Biochemical phenotyping: Assays for plasma Von Willebrand Factor (VWF) antigen were performed using ELISA and "Alphalisa" techniques. Automated complete blood count analysis was performed on a Bayer Advia 120 on all participants (including WBC differential, RBC indices, and platelet count.) For the dbGaP v2 update, new biochemical phenotypes have been submitted and include von Willebrand Factor, von Willebrand Factor propeptide, plasminogen, gamma prime fibrinogen, ADAMTS 13, antithrombin III, protein C, and protein S. All new phenotypes were obtained using "Alphalisa" techniques. Genotyping Details: SNP genotyping was performed using genomic DNA extracted from peripheral blood at the Broad Institute, (MIT/Harvard). Genotyping was performed on the Illumina Omni-1 quad chip at the Broad Institute. For the dbGaP v2 update, genotyping data from the Illumina Human Exome was deposited. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to blood clotting through large-scale genome-wide association studies of siblings. Genotyping was performed at the Broad Institute of MIT and Harvard, a GENEVA genotyping center. Data cleaning and harmonization was performed by the primary investigators at the University of Michigan, Ann Arbor, and at the GEI-funded GENEVA Coordinating Center at the University of Washington. This study serves as a resource for investigators who are interested in the genetic determinants of specific plasma proteins in a healthy population. The sibling cohort design allows for linkage analysis in addition to association studies. Analysis of thrombosis and hemostasis related traits should help elucidate specific biochemical and genetic networks that maintain hemostasis. We hope to identify specific genetic determinants of VWF levels in order to better understand the factors that influence the development of VWD.

  Study phs000304

• Metadata Public API

  Metadata Rest Endpoints Common Aspects Functionality Identifiers Requests and Responses Request Response Querying Querying by Object Cross-Querying by Object Common Aspects Functionality The Metadata REST API allows EGA users to request metadata from the EGA. Using this api you will be able to obtain the publicly available information from EGA study, sample, experiment, run, analysis, policy, dac and dataset. The API also allows for objects to be cross-referenced in order to obtain for example all the datasets linked to a dac. Identifiers EGA objects can be identified by their unique accession. These are ID's displayed everywhere, shared among all EGA locations and specific for each data type (More information on the list below) EGA Accession ID EGA Object description EGAS EGA Study Accession ID EGAC EGA DAC Accession ID EGAP EGA Policy Accession ID EGAN EGA Sample Accession ID EGAR EGA Run Accession ID EGAX EGA Experiment ID EGAZ EGA Analysis Accession ID EGAD EGA Dataset Accession ID EGAB EGA Submission ID EGAF EGA File Unique Accession ID Server Request and Response Request All the endpoints implement these two HTTP methods, GET and HEAD. Moreover, there is an authentication layer that allows to disclose the private information about each object if the user runs the endpoint with their token and has permissions to the related dataset. HTTP Method Description GET Returns the objects and their public information (including private information if the user has permissions) HEAD Returns the count of objects to be returned Response API responses are diverse but they always return a status call. Below you have a summary on what these codes mean and some tips that can help you troubleshooting them: HTTP Status Code Description Resolution 200 OK No error handling necessary 206 Partial Content Expected status code when paginating the results. No error handling necessary 400 BAD REQUEST Request incorrectly formulated 401 UNAUTHORISED/FORBIDDEN You do not have permissions over the object you are trying to access. / The authorised user is not permitted to make the given request. 404 NOT FOUND The object/resource you are trying to access does not exist. 500 INTERNAL SERVER ERROR This is a server-side error, try later. If the issue persists, contact the Heldpesk. Querying Querying by Object In the below documentation, worked examples can be found on how to use the API, to query about each unique EGA object. https://metadata.ega-archive.org/analyses/{id} https://metadata.ega-archive.org/dacs/{id} https://metadata.ega-archive.org/datasets/{id} https://metadata.ega-archive.org/runs/{id} https://metadata.ega-archive.org/samples/{id} https://metadata.ega-archive.org/studies/{id} Worked example for the EGA data access committee(DAC) EGAC00001000514 https://metadata.ega-archive.org/dacs/EGAC00001000514 Points to notice Please, be advised that all EGA objects can be queried by using the same endpoint. For example: https://metadata.ega-archive.org/datasets Returns all the datasets registered at the EGA. https://metadata.ega-archive.org/datasets?limit=5&offset=15 Returns 5 results skipping the initial 15 results. Cross-Querying by Object The EGA REST API Metadata also allows for the crossquerying of public metadata. For example, should I want to query the datasets included in the ICGC DAC: https://metadata.ega-archive.org/dacs/EGAC00001000010/datasets Below, you can find worked examples on how to perform the call to the API. https://metadata.ega-archive.org/datasets/EGAD00001000645/analyses https://metadata.ega-archive.org/datasetsEGAD00001000645/files https://metadata.ega-archive.org/datasets/EGAD00001000620/runs https://metadata.ega-archive.org/datasets/EGAD00001000620/samples https://metadata.ega-archive.org/samples/EGAN00001092114/datasets https://metadata.ega-archive.org/files/EGAF00000056146/dacs https://metadata.ega-archive.org/files/EGAF00000056146/datasets https://metadata.ega-archive.org/files/EGAF00000056146/studies There are more endpoints included in this category. Please, find all the possibilities (green tick) in the table below. Table The table displays in a ordered fashion the objects that can be crossreferenced using the metadata API. BY Analysis Dac Dataset Experiment Policy Run Sample Study File Analysis ✔ ✔ Dac ✔ ✔ Dataset ✔ ✔ ✔ ✔ Experiment ✔ ✔ ✔ ✔ Policy ✔ Run ✔ ✔ ✔ Sample ✔ ✔* ✔ Study ✔ ✔ ✔ ✔ ✔ ✔* File ✔ *: These cross queries do not include data from Array-File submissions. Check out the SPEC

  Documentation discovery/metadata/public-metadata-api

• Submission FAQ

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

  Documentation submission/metadata/submission/FAQ

• GEnomics and Transcriptomics of Human INsulinoma (GETHIN)

  The Genomics and Transcriptomics of Human Insulinoma (GETHIN) The common forms of diabetes - Types 1 and 2 - ultimately result from a deficiency of insulin-producing pancreatic beta cells. The Genomics and Transcriptomics of Human Insulinoma (GETHIN) study was performed in order to identify novel approaches to inducing human pancreatic beta cells to replicate and regenerate. As a corollary, developing drugs that are able to expand human beta cell mass in people with diabetes should reverse diabetes. Unfortunately, identifying druggable pathways that can enhance human beta cell replication has been a major challenge. In 2017, there is only one class of drugs - the harmine analogues - that can induce human beta cells to replicate, and in this case, higher replication rates are desirable. Thus, identifying additional drugs and druggable pathways is a priority in diabetes research. Insulinomas are rare, benign adenomas of the pancreatic beta cell that cause excess insulin production and hypoglycemia: exactly the opposite of Types 1 and 2 diabetes. Beta cell proliferation rates in insulinomas are abnormally high. Thus, the premise for The Genomics and Transcriptomics of Human Insulinoma study is that benign human insulinomas hold the genomic and transcriptomic "recipe", and the repertoire of druggable pathways, that can be exploited to induce regeneration or replication of human beta cells in diabetes. Because, insulinomas are so rare, are almost always benign (non-malignant), and are easily resected by laparoscopic surgery, little attention has been paid to understanding the genomics or transcriptomics of insulinoma. There are at present only three published studies employing next-gen sequencing in insulinoma (PMID:24326773; PMID:25787250; and PMID:25763608). These studies contained 10, 7 and 8 insulinomas, respectively, and highlighted likely mutations in YY1 and MEN1. Our goal was to markedly expand the database and to add RNAseq to these earlier studies. The GETHIN study reports next-gen sequencing on 38 insulinomas, by far the largest series of human insulinomas subjected to next-gen sequencing (see the Selected publications section for reference). This includes paired (genomic plus tumor) whole exome sequencing on 26 human insulinomas (22 sequenced at Mount Sinai, 4 downloaded from Cao et al, PMID:24326773), and 25 sets of RNAseq from insulinomas, some of which also had paired whole exome sequencing, and some of which did not. The insulinoma RNAseq was compared to RNAseq from 22 sets of FACS-sorted normal human beta cells. Since insulinomas are so rare, the 38 insulinomas were collected by several investigators at several institutions over several decades, but most (22 whole exome sets, and all RNAseq) were sequenced at the Icahn School of Medicine at Mount Sinai in New York. The current dataset contains whole exome sequencing and RNAseq on the 11 insulinomas harvested at Mount Sinai. The four from Cao et al can be retrieved from Cao et al PMID:24326773. Fastq files from the remaining 23 insulinomas will be added as the local IRBs and Institutional Certifications are acquired. Complete patient data are provided in our Nature Communications report. Going forward, our intention is to expand this series, with the goal of sequencing 100 human insulinomas. These will be added to dbGaP as they accrue. Paired-end whole exome sequencing (mean usable sequencing depth 79X and 105X for blood and insulinoma, respectively) was performed using an Illumina HiSeq 2500. Insulinoma and sorted normal beta cell RNAseq was performed on Ribozero and polyA paired end libraries using the Illumina HiSeq 2500. Complete sequencing and bioinformatic details are provided in our Nature Communications report. The principal findings from the study are that although each insulinoma has a different set of presumptive driver mutations, the majority converge on genes that are members of the Polycomb Complex, Trithorax Complex and other epigenetic modifying enzymes. In addition, 20% of insulinomas have copy number loss or loss of heterozygosity of all or most of chromosome 11, and the majority display abnormalities in CpG methylation and imprinting control on the imprinted Chr 11 p15.5-15.4 region that contains INS, IGF2, CDKN1C, KCNQ1, and other genes involved in beta cell specification and proliferation.

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