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• Investigating Host Genetic Risk Factors for Tuberculosis in Highly Endemic South African Populations

  It is apparent from our recent population genetic and admixture mapping work 1–3 that a substantial part of the ancestral input into the South African Coloured (SAC) population is from the San or Khoe groups, which are not well represented in publicly available genetic databases. It is a reasonable assumption that the SAC population in the Western Cape may have derived more genetic input from the present KhoeSan population in the Northern Cape than the San residing in Namibia. It was concluded by our group that it is indeed the southern African KhoeSan group, the ≠Khomani, that best represent the KhoeSan contribution seen in the SAC 4. More recently, it has been shown that there are ancestry related increases in TB susceptibility, especially with increased Bantu-speaking African and KhoeSan ancestry 5. We aim to elucidate the epidemiological and human-host genetic risk factors for TB and the immunological pathways modulating TB infection. The proposed sub-study will enroll people evaluated for TB at Northern Cape community health clinics and their contacts from their households and/or community. We will conduct a demographic interview, collect saliva, which will be used for genetic analysis, and blood to determine latent TB infection status and capture immunological responses to mycobacterial infections at the cellular level and RNA sequencing.

  Study EGAS00001007850

• CTN - 0051: Extended-Release Naltrexone vs. Buprenorphine for Opioid Treatment (X:BOT)

  The overarching goal of CTN-0051 is to foster adoption of new relapse-prevention pharmacotherapies in community-based treatment programs (CTPs) where these could have a substantial public health impact. To this end CTN-0051 will assess the comparative effectiveness of extended-release injectable naltrexone (XR-NTX, Vivitrol®), an opioid antagonist recently approved and indicated for the prevention of relapse to opioid dependence, versus buprenorphine-naloxone (BUP-NX, Suboxone®), a high affinity partial agonist indicated for maintenance treatment of opioid dependence, as pharmacotherapeutic aids to recovery. The study is conducted in 8 CTN-affiliated CTPs that provide or partner with detoxification services (inpatient/residential) which have the capacity to maintain participants opioid-free for approximately 3-7 days, have the capacity to provide medication-assisted therapy, and can provide a minimum of one group or individual counseling session per week during the 24-week treatment period. Up to 600 eligible participants will be randomized to treatment with XR-NTX or BUP-NX for 24 weeks (sufficient to include 350 participants who are randomized more than 72 hours after their last opioid). To maximize generalizability, the point of randomization is flexible, from shortly after program admission until just prior to program discharge. The primary goal of the study is to estimate the difference, if one exists, between XR-NTX and BUP-NX in the distribution of the time to relapse (i.e., loss of persistent abstinence) during the 6-month trial. The primary outcome measure is the time to the event, with the event called relapse. Secondary objectives are to: (1) compare outcome on XR-NTX versus BUP-NX across a range of clinical safety and secondary efficacy domains, (2) explore demographic, clinical, and genetic predictors of successful treatment and moderators of differential effectiveness (i.e., what variables may help clinicians choose which of these treatments is best for a given patient), and (3) collect a limited dataset to permit analyses of economic costs and benefits of the two treatments.

  Study phs002876

• PROstate Cancer Medically Optimized Genome Enhanced ThErapy (PROMOTE) of Castration Resistant Prostate Cancer (CRPC) Patients Treated with Abiraterone Acetate

  The Prostate Cancer Medically Optimized Genome-Enhanced Therapy (PROMOTE) study uses genetic clues in castration-resistant prostate cancer that may identify an individualized treatment approach for men with the disease. Understanding the molecular biology behind castration-resistant prostate cancer has led to more treatment options, but there are still no definite conclusions about which specific drug best treats patients - maximum suppression of cancer growth while minimizing side effects. The PROMOTE study explores the genetic characteristics of each tumor to predict these treatment paradigms for the future, resulting in more effective and less toxic options for patients. Our long-term goal is to improve treatments for men with advanced prostate cancer by using genomic sequencing to increase life span and quality of life. We also will uncover novel vulnerable targets in the cancer genome that may provide new drug therapies. PARTICIPATION Eligible participants are men: With castration-resistant prostate cancer or prostate cancer not responding to hormone treatments About to begin abiraterone acetate therapy Agreeable to undergoing two tumor biopsies During the study, participants travel to Mayo Clinic for an initial biopsy (before beginning abiraterone acetate) and a second biopsy approximately three months later. The cell tissue collected is analyzed to identify gene alterations in the tumor that could eventually be targeted with treatments. Tissue is preserved for future research. Participants can continue to be treated by their local cancer care team during this period and beyond. In addition, the Mayo team carefully monitors participants' cancer via follow-up studies and the genetic signature of tumors that were biopsied so that patients may benefit from future treatments.

  Study phs001141

• ICR96 exon CNV validation series

  A resource for assessment of exon CNV calling methods in targeted NGS data, we here present the ICR96 exon CNV validation series. The dataset includes high-quality sequencing data from a targeted NGS assay (the TruSight Cancer Panel) together with Multiplex Ligation-dependent Probe Amplification (MLPA) results for 96 independent samples. 66 samples contain at least one validated exon CNV and 30 samples have validated negative results for exon CNVs in 26 genes. The dataset includes 46 exon CNVs in BRCA1, BRCA2, TP53, MLH1, MSH2, MSH6, PMS2, EPCAM and PTEN, giving excellent representation of the cancer predisposition genes most frequently tested in clinical practice. Moreover, the validated exon CNVs include 25 single exon CNVs the most difficult exon CNV to detect.

  Dataset EGAD00001003335

• Deep multi-region whole-genome sequencing reveals heterogeneity and gene-by-environment interactions in treatment-naive, metastatic lung cancer

  Our understanding of genomic heterogeneity in lung cancer is largely based on the analysis of early-stage surgical specimens. Here we used endoscopic sampling of paired primary and intrathoracic metastatic tumors from 11 lung cancer patients to map genomic heterogeneity inoperable lung cancer with deep whole-genome sequencing. Intra-patient heterogeneity in driver or targetable mutations was predominantly in the form of copy number gain. Private mutation signatures, including patterns consistent with defects in homologous recombination, were highly variable both within and between patients. Irrespective of histotype, we observed a smaller than expected number of private mutations, suggesting that ancestral clones accumulated large mutation burdens immediately prior to metastasis. Single-region whole-genome sequencing of from 20 patients showed that tumors in ever-smokers with the strongest tobacco signatures were associated with germline variants in genes implicated in the repair of cigarette-induced DNA damage. Our results suggest that lung cancer precursors in ever-smokers accumulate large numbers of mutations prior to the formation of frank malignancy followed by rapid metastatic spread. In advanced lung cancer, germline variants in DNA repair genes may interact with the airway environment to influence the pattern of founder mutations, whereas similar interactions with the tumor microenvironment may play a role in the acquisition of mutations following metastasis.

  Study EGAS00001003830

• med-pchic-dac

  The data are accessible under the terms of the following Data Access Agreement that needs to be filled in, signed (by yourself and your institution’s official contact) and returned by email to med-pchic-dac@lists.cam.ac.uk

  Dac EGAC00001000523

• RNA-seq of high grade serous ovarian tumours

  Somatic RNA for 40 samples matched to the WGS was extracted using the Qiagen Qiasymphony RNA protcol (cat no 931636). The tissue was initially homogenised using a Qiagen Bioruptor, followed by the manufacturers recommended protocol (including DNase digestion). The resulting RNA the underwent quality control as follows: firstly, A260 and A280nm were measured on a Denovix DS-11 Fx to qualitatively illustrate A260/280nm and A260/230nm ratios as measures of RNA purity. A260/280 had to be 2.0 and A260/230 had to be 2.0-2.2. Then RNA was quantified using LifeTechnologies Qubit RNA BR kit (cat no Q10210). RNAseq was carried out by the Edinburgh Clinical Research Facility on an Illumina NExtSeq500. Total RNA samples were assessed on the Agilent Bioanalyser (Agilent Technologies, #G2939AA) with the RNA 6000 Nano Kit (#5067-1512) for quality and integrity of total RNA, and then quantified using the Qubit 2.0 Fluorometer (Thermo Fisher Scientific Inc, #Q32866) and the Qubit RNA HS assay kit (#Q32855). Libraries were prepared from total-RNA sample using the NEBNext Ultra 2 Directional RNA library prep kit for Illumina (#E7760S) with the NEBNext rRNA Depletion kit (#E6310) according to the provided protocol. 400ng of totalRNA was then added to the ribosomal RNA (rRNA) depletion reaction using the NEBNext rRNA depletion kit (Human/mouse/rat) (#E6310). This step uses specific probes that bind to the rRNA in order to cleave it. rRNA-depleted RNA was then DNase treated and purified using Agencourt RNAClean XP beads (Beckman Coulter Inc, #66514). RNA was then fragmented using random primers before undergoing first strand and second strand synthesis to create cDNA. cDNA was end repaired before ligation of sequencing adapters, and libraries were enriched by PCR using the NEBNext Multiplex oligos for Illumina set 1 and 2 (#E7500). Final libraries had an average peak size of 271bp. Libraries were quantified by fluorometry using the Qubit dsDNA HS assay and assessed for quality and fragment size using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Sequencing was performed using the NextSeq 500/550 High-Output v2 (150 cycle) Kit (# FC- 404-2002) on the NextSeq 550 platform (Illumina Inc, #SY-415-1002). Libraries were combined in an equimolar pool based on the library quantification results and run across 5 High-Output Flow Cell v2.5.

  Dataset EGAD00001009048

• IMCISION DNAseq

  Standard-of-care (SOC) surgery for locoregionally advanced head and neck squamous cell carcinoma (HNSCC) is intensive and results in 30‒50% five-year overall survival. Anti-PD1 immune checkpoint blockade (ICB) durably improves survival rates in recurrent/metastatic HNSCC. We report on the non-randomized phase Ib/IIa IMCISION trial (NCT03003637) of 32 HNSCC patients treated with two doses neoadjuvant nivolumab (NIVO MONO, n=6, phase Ib arm A) or two doses of nivolumab plus a single dose of ipilimumab (COMBO, n=26, 6 in phase Ib arm B and 20 in phase IIa) prior to surgery and, if indicated, adjuvant radiotherapy. Neoadjuvant ICB was feasible in all phase Ib patients, meeting the phase Ib primary feasibility endpoint. One phase IIa patient had progressive disease precluding surgery. Primary tumor pathological response (phase IIa primary endpoint), defined as the % change in viable tumor cells from baseline biopsy to on-treatment resection, was evaluable in 29 patients. . We observed a major pathological response (MPR, 90‒100% response) in 8/23 (35%) evaluable COMBO and 1/6 (17%) NIVO MONO patients. None of the patients with MPR after NIVO MONO or COMBO developed a tumor relapse after 24.0 months median follow-up. FDG-PET-based total lesion glycolysis identified MPR patients prior to surgery. A baseline AID/APOBEC-associated mutational profile and an on-treatment decrease in hypoxia signature expression were observed in MPR patients. Our data indicate that neoadjuvant NIVO MONO and COMBO are safe in HNSCC, and that particularly COMBO ICB shows encouraging effectivity. IMCISION provides rationales for future HNSCC trials aiming to pre-operatively select patients with a likely MPR after neoadjuvant ICB for de-escalation of SOC.

  Study EGAS00001005466

• Wilm's tumor sequencing data

  No. of samples: 80 (28 ULP-WGS, 26 WES, 26 RNA-SEQ) File types: FASTQ (28 ULP-WGS, 19 WES, 18 RNA) and BAM (7 WES, 8 RNA) Technology used: Sequencing - Illumina Novoseq 6000; Map/Align - Illumina DRAGEN v3.7.5; Genome assembly - GrCh38p13 Filename nomenclature: - SampleName_Passage_SampleType_TissueType_SequencingType - Passage of: PX = unknown; PZ = from patient; P0 = first passage from patient on plastic; P1 = first passage from plastic/PDX/organoid - SampleType: STN = normal; STT = tumor - SampleType STN: 00 = tissue unknown; 01 = adjacent normal; 02 = fibroblast; 03 = germline blood; 21 = cell line from patient tissue; 22 = cell line from PDX; 23 = cell line from patient fibroblast - SampleType STT: 00 = tissue unknown; 01 = primary tumor; 21 = cell line from patient; 22 = cell line from PDX - TissueType: WT = Wilm's tumor; 00 = kidney unknown; 01 = kidney left; 02 = kidney right - SequencingType: 00 = unknown; 02 = ultra-low pass whole-genome sequencing; 20 = whole-exome; 61 = bulk RNA-sequencing

  Dataset EGAD00001011111

• RNA-seq of high grade serous ovarian tumours

  Somatic RNA for 37 samples was extracted using the Qiagen Qiasymphony RNA protcol (cat no 931636). The tissue was initially homogenised using a Qiagen Bioruptor, followed by the manufacturers recommended protocol (including DNase digestion). The resulting RNA the underwent quality control as follows: firstly, A260 and A280nm were measured on a Denovix DS-11 Fx to qualitatively illustrate A260/280nm and A260/230nm ratios as measures of RNA purity. A260/280 had to be 2.0 and A260/230 had to be 2.0-2.2. Then RNA was quantified using LifeTechnologies Qubit RNA BR kit (cat no Q10210). RNAseq was carried out by the Edinburgh Clinical Research Facility on an Illumina NExtSeq500. Total RNA samples were assessed on the Agilent Bioanalyser (Agilent Technologies, #G2939AA) with the RNA 6000 Nano Kit (#5067-1512) for quality and integrity of total RNA, and then quantified using the Qubit 2.0 Fluorometer (Thermo Fisher Scientific Inc, #Q32866) and the Qubit RNA HS assay kit (#Q32855). Libraries were prepared from total-RNA sample using the NEBNext Ultra 2 Directional RNA library prep kit for Illumina (#E7760S) with the NEBNext rRNA Depletion kit (#E6310) according to the provided protocol. 400ng of totalRNA was then added to the ribosomal RNA (rRNA) depletion reaction using the NEBNext rRNA depletion kit (Human/mouse/rat) (#E6310). This step uses specific probes that bind to the rRNA in order to cleave it. rRNA-depleted RNA was then DNase treated and purified using Agencourt RNAClean XP beads (Beckman Coulter Inc, #66514). RNA was then fragmented using random primers before undergoing first strand and second strand synthesis to create cDNA. cDNA was end repaired before ligation of sequencing adapters, and libraries were enriched by PCR using the NEBNext Multiplex oligos for Illumina set 1 and 2 (#E7500). Final libraries had an average peak size of 271bp. Libraries were quantified by fluorometry using the Qubit dsDNA HS assay and assessed for quality and fragment size using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Sequencing was performed using the NextSeq 500/550 High-Output v2 (150 cycle) Kit (# FC- 404-2002) on the NextSeq 550 platform (Illumina Inc, #SY-415-1002). Libraries were combined in an equimolar pool based on the library quantification results and run across 5 High-Output Flow Cell v2.5.

  Dataset EGAD00001010139

• Longitudinal sampling in relapsed and refractory Hodgkin lymphoma

  Ultra-deep next-generation panel-sequencing on 59 FFPE-samples (20 LTR, 26 relapsed (rHL: 11 initial-diagnosis, 15 relapse) and 13 primary-refractory (prHL: 8 initial-diagnosis, 5 progression) from 44 cHL-patients applying a hybrid-capture approach. Data was processed as described in the publication and mark duplicated bam files were uploaded.

  Dataset EGAD50000000210

• Resuscitation Outcomes Consortium (ROC) Cardiac Epidemiologic Registry (Cardiac Epistry) Version 3 (ROC-Cardiac Epistry 3-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. Available Data The ROC Cardiac Epistry version 3 include all cardiac arrest cases entered into the ROC database from April 1, 2011 to June 30, 2015. This is separate from versions 1 and 2 because of the major changes in how and which data were collected. Version 3 represents the following major changes to the structure and data collection: separate ED Arrival and Hospital Admits forms, mandatory ED and Hospital elements and a revamped CPR Process form. For ROC traumatic injury Epistry data please see: ROC-Trauma Epistry Objectives To build a prospective population-based registry of participants with out-of-hospital cardiac arrest responded to by Emergency Medical Services (EMS). Specific aims included: to establish whether the results of Resuscitation Outcomes Consortium (ROC) trials can be generalized to the larger population of participants that experience cardiac arrest; to more fully establish the burden of cardiac arrest; and to examine the relationships between variation in EMS structure and process, regional and periodic factors, and participant outcomes. Background Cardiac arrest is a common, serious, debilitating and costly public health problem. Although there has been a steady decline in morbidity and mortality from most cardiovascular diseases, high mortality rates for out-of-hospital cardiac arrests continue to pose a challenge for healthcare providers and a significant public health burden. The Resuscitation Outcomes Consortium (ROC) was established in 2004 to conduct clinical research in the areas of cardiopulmonary arrest and life-threatening traumatic injury with the overall goal of improving resuscitation outcomes. Participant and care characteristics can predict favorable outcomes in cardiac arrests, but there is still a wide variation in outcomes that is not well understood. EMS factors such as service level, number of responding providers, use of procedures or drugs in the field, training, quality assurance/feedback, and response time intervals also vary significantly by region. Variations in geographic, socioeconomic and periodic factors may also be associated with differences in outcomes. Prior to ROC Cardiac Epistry, there were no North American population-based registries for out-of-hospital cardiac arrests. Therefore there was a need for standardized data collection of out-of-hospital cardiac arrests in diverse geographic locations in order to identify the independent effects of prognostic or treatment factors accounting for variations in survival. Participants There were 120,306 participants. Design ROC Epistry collected standardized data regarding episode-specific factors, participant demographics, clinical information, pre-hospital interventions and disposition, hospital information, and participant outcome for all out-of-hospital cardiac arrests in the ROC regions. Each ROC site had to ensure capture of all eligible cases within the EMS service areas. Out-of-hospital data were extracted from existing databases whenever possible and augmented with targeted review of EMS reports. Hospital data were abstracted directly from the hospital file in most cases. Alternative methods included linkage to death registries and obituaries if the death occurred within 30 days. Sites submitted data using a web-based interface or batch uploads. Participants were not contacted directly.

  Study phs003726

• NHLBI TOPMed: TReating Children to Prevent EXacerbations of Asthma (TREXA)

  TREXA is a 44-week randomized, double-blind, double-masked, four-treatment, parallel trial that will evaluate the weaning strategy that provides the best protection against the development of exacerbations in children whose asthma is acceptably controlled on a low dose of ICS (per NAEPP guidelines). Following the 4 weeks of the run-in period on a 1x dose of ICS (100 µg fluticasone b.i.d. or its equivalent), children who do not meet the definition of acceptable asthma control will be randomized to the parallel BADGER protocol; those who meet the definition of acceptable asthma control will be enrolled into the 44-week treatment phase of the study. The primary outcome measure will be time to first exacerbation requiring a prednisone course.

  Study phs001732

• OpACIN-neo – A Multicenter Phase 2 Study to identify the Optimal neo-Adjuvant Combination scheme of Ipilimumab and Nivolumab – Whole exome sequencing

  The outcome of patients with macroscopic stage III melanoma is poor. Neoadjuvant treatment with ipilimumab plus nivolumab at the standard dosing schedule induced pathological responses in a high proportion of patients in two small independent early-phase trials. However, toxicity of the standard ipilimumab plus nivolumab dosing schedule was high, preventing its broader clinical use. The aim of the OpACIN-neo study (NCT02977052) to identify a dosing schedule of ipilimumab plus nivolumab that is less toxic but equally effective. 86 patients with macroscopic stage III melanoma were randomised to one of three dosing schedules: arm A, two cycles of ipilimumab 3 mg/kg plus nivolumab 1 mg/kg once every 3 weeks; arm B, two cycles of ipilimumab 1 mg/kg plus nivolumab 3 mg/kg once every 3 weeks; or arm C, two cycles of ipilimumab 3 mg/kg once every 3 weeks directly followed by two cycles of nivolumab 3mg/kg once every 2 weeks. Within the first 12 weeks, grade 3–4 immune-related adverse events were observed in 12 (40%) of 30 patients in group A, six (20%) of 30 in group B, and 13 (50%) of 26 in group C. Pathological responses occurred in 24 (80%) patients in group A, 23 (77%) in group B, and 17 (65%) in group C. The 2-year estimated relapse-free survival was 84% for all patients, 97% for patients achieving a pathologic response and 36% for nonresponders (p<0.001). High tumor mutational burden (TMB) and high interferon-gamma-related gene expression signature score (IFN-γ score) were associated with pathologic response and low risk of relapse; pathologic response rate (pRR) was 100% in patients with high IFN-γ score/high TMB, patients with high IFN-γ score/low TMB or low IFN-γ score/high TMB had pRRs of 91% and 88%; while patients with low IFN-γ score/low TMB had a pRR of only 39%. These data demonstrate long-term benefit in patients with a pathologic response and show the predictive potential of TMB and IFN-γ score.

  Study EGAS00001004832

• OpACIN-neo – A Multicenter Phase 2 Study to identify the Optimal neo-Adjuvant Combination scheme of Ipilimumab and Nivolumab – RNA sequencing

  The outcome of patients with macroscopic stage III melanoma is poor. Neoadjuvant treatment with ipilimumab plus nivolumab at the standard dosing schedule induced pathological responses in a high proportion of patients in two small independent early-phase trials. However, toxicity of the standard ipilimumab plus nivolumab dosing schedule was high, preventing its broader clinical use. The aim of the OpACIN-neo study (NCT02977052) to identify a dosing schedule of ipilimumab plus nivolumab that is less toxic but equally effective. 86 patients with macroscopic stage III melanoma were randomised to one of three dosing schedules: arm A, two cycles of ipilimumab 3 mg/kg plus nivolumab 1 mg/kg once every 3 weeks; arm B, two cycles of ipilimumab 1 mg/kg plus nivolumab 3 mg/kg once every 3 weeks; or arm C, two cycles of ipilimumab 3 mg/kg once every 3 weeks directly followed by two cycles of nivolumab 3mg/kg once every 2 weeks. Within the first 12 weeks, grade 3–4 immune-related adverse events were observed in 12 (40%) of 30 patients in group A, six (20%) of 30 in group B, and 13 (50%) of 26 in group C. Pathological responses occurred in 24 (80%) patients in group A, 23 (77%) in group B, and 17 (65%) in group C. The 2-year estimated relapse-free survival was 84% for all patients, 97% for patients achieving a pathologic response and 36% for nonresponders (p<0.001). High tumor mutational burden (TMB) and high interferon-gamma-related gene expression signature score (IFN-γ score) were associated with pathologic response and low risk of relapse; pathologic response rate (pRR) was 100% in patients with high IFN-γ score/high TMB, patients with high IFN-γ score/low TMB or low IFN-γ score/high TMB had pRRs of 91% and 88%; while patients with low IFN-γ score/low TMB had a pRR of only 39%. These data demonstrate long-term benefit in patients with a pathologic response and show the predictive potential of TMB and IFN-γ score.

  Study EGAS00001004833

• Single cell RNA sequencing of colorectal cancer patients (KUL5)

  All libraries were sequenced on Illumina NextSeq or NovaSeq6000 until sufficient saturation was reached.

  Dataset EGAD00001008585

• A Multi-Gene Mutation Classification of 468 Colorectal Cancers Reveals a Prognostic Role for APC

  Colorectal cancer (CRC) is a highly heterogeneous disease, for which prognosis has been relegated to clinic-pathologic staging for decades. There is a need to molecularly stratify subpopulations of CRC to better predict outcome and assign therapies. Here we report targeted exome sequencing of 1,321 cancer-related genes on 468 tumor specimens, which identified a subset of 17 genes that best classify CRC, with APC (Gene ID: 324) playing a central role in predicting overall survival. APC may assume 0, 1, or 2 truncating mutations, each with a striking differential impact on survival. Tumors lacking any APC mutation carry a worse prognosis than single APC mutation tumors, but tumors with two APC mutations and KRAS (Gene ID: 3845) and TP53 (Gene ID: 7157) mutations confer the poorest survival among all the subgroups examined. Our study demonstrates a substantial prognostic role for APC and suggests that sequencing of APC may have clinical utility in the routine staging and potential therapeutic assignment for CRC.

  Study phs001111

• Whole Exome Sequencing of paired gDNAs and PPGL tumor DNA from patients with cyanotic congenital heart disease

  Fastq files from Whole Exome Sequencing of 12 paired germline DNA (from blood/saliva) and 14 PPGL tumor DNA (from formalin-fixed paraffin-embedded (FFPE) blocks from surgery) from patients with cyanotic congenital heart disease (CCHD) and pheochromocytoma and paraganglioma (PPGL). Sequencing was performed using the Illumina HiSeq4000.

  Dataset EGAD50000001201

• Whole Genome Sequencing of Therapy-Related Myeloid Neoplasms

  The dataset consists of: 51 paired tumor/normal WGS samples (26 tumors and 25 normals), and 13 normal targeted samples.

  Dataset EGAD00001010026

• BLUEPRINT release August 2016, ChIP-Seq for band form neutrophil, on genome GRCh38

  ChIP-Seq data for 4 band form neutrophil sample(s). 26 run(s), 23 experiment(s), 23 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002454

• What is a DAC?

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

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

• Single-nucleus RNA-sequencing data of kidney biopsies from patients with primary FSGS, maladaptive FSGS, proteinuric controls and healthy controls

  This dataset includes FASTQ files of single-nucleus RNA sequencing of cryopreserved kidney biopsy cores from adult patients with diagnosed primary FSGS (n = 9, all nephrotic), maladaptive FSGS (n = 9, not nephrotic), proteinuric controls (PLA2R-positive membranous nephropathy, n = 3), and healthy controls (n = 4). A total of 120,751 high-quality nuclei were identified, including 2,471 podocytes and 1,574 parietal epithelial cells (PECs). In addition to the raw FASTQ files, the dataset includes processed data files from all 25 samples, generated using Seurat in R: barcode files, features, count matrices, and associated metadata. Details regarding the bioinformatics pipeline can be found at https://github.com/lambrechtslab/FSGS_Deleersnijder_et_al

  Dataset EGAD50000001557

• Cancerous Adaptive Dosing Melanoma WGS Dataset

  Illumina NovaSeq 6000 30x WGS of 26 samples, each with up to 5 matched timepoints. Timepoints A,B,C,D,and E correspond to Pretreatment, Week 3, Week 6, Week 9, and Week 12 after treatment, respectively. Additional sample metadata (sample recurrence, treatment course, age, sex, comorbidities, etc.) are present in sample description.

  Dataset EGAD00001010926

• WGS

  Whole Genome Sequencing

  Dataset EGAD00001001120

• WTCCC case-control study for Hypertension

  WTCCC genome-wide case-control association study for Hypertension (HT) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000009

• Single cell RNAseq FASTQ files of three PDAC organoid lines (P28, P40, P47) using SORT-seq

  This dataset contains raw FASTQ files from single cell RNA sequencing of three patient-derived pancreatic ductal adenocarcinoma (PDAC) organoid lines (P28, P40, P47) cultured under standard conditions. For each line, single cells were FACS sorted into 384-well capture plates, with each well containing a 50nl droplet of barcoded primers. Plates were processed following an adapted SORT-seq protocol, and cDNA libraries were generated using CEL-Seq2 with TruSeq small RNA primers (Illumina). Sequencing was performed on an Illumina NextSeq500 platform using paired-end reads (read 1: 26 cycles, index read: 6 cycles, read 2: 60 cycles). Data are controlled-access and intended for single cell transcriptomic analysis of PDAC organoid heterogeneity and WNT pathway activity.

  Dataset EGAD50000002220

• Biopsy-Derived Organoids in Personalised Early Breast Cancer Care: Challenges of Tumour Purity and Normal Cell Overgrowth Cap Their Practical Utility

  The ability to establish organoids composed exclusively of tumour rather than healthy cells is essential for their implementation into clinical practice. Organoids have in recent years emerged as a powerful tool to expand patient material in culture and generate modifiable 3D models derived from humans or animal models. For translational research, they enable the creation of model systems for an ever-increasing number of cell types and diseases. And in personalised medicine, they potentially allow for functional drug testing with high predictive power in certain settings. We found that using biopsy material from untreated, early-stage primary breast cancer patients poses significant challenges for consistently culturing tumour cells as organoids. Specifically, we observed frequent outgrowth of genetically normal, non-cancerous epithelial cells. We analysed >100 biopsy samples from early-stage breast cancer and present our large collection of >70 organoid lines. We also show methods of assessing successful tumour cell culture in a time and cost-efficient manner, proving a high rate (>85%) of normal cell overgrowth in early-stage breast cancer organoids. Finally, we show a number of successful attempts to culture cancer organoids from mastectomy-derived tissue of advanced, metastatic breast cancer. We conclude that the usefulness of organoids from early breast cancer for translational research and personalised medicine, especially guidance of adjuvant or post-surgical maintenance therapy, is strongly limited by the low success rate of culturing cancerous cells under organoid conditions.

  Study EGAS50000000605

• Whole exome and Transcriptome sequencing of treatment-naïve esophageal adenocarcinoma biopsies and matched peripheral blood mononuclear cells

  Exome sequencing was performed on n=28 treatment-naïve esophageal adenocarcinoma (EACs). Three to four biopsies sampling different areas of each tumor were pooled before nucleic acid extractions to mitigate the elevated heterogeneity described for EAC. WES was performed on EAC biopsies at 120X average coverage, with autologous PBMCs used as germline controls at 80X average coverage. Libraries were prepared from 30 ng of input DNA using the SureSelect QXT Human All Exon V7 kit (Agilent Technologies) and sequenced on the NextSeq 550 (Illumina), 2x150 bp. BCL files were demultiplexed to FastQ files using bcl2fastq2 software (Illumina). Three paired end sequencing batches were analyzed independently (Batch1: samples 8, 10, 11, 12, 15, 17, 18; Batch2: samples 20, 24, 25, 26, 27, 29, 30, 31, 33, 34 ; Batch3: samples 35, 37, 39, 40, 41, 43, 45, 48, 54, 55, 57). RNA sequencing was performed on n=26 treatment-naïve esophageal adenocarcinoma (EACs). Three to four biopsies sampling different areas of each tumor were pooled before nucleic acid extractions to mitigate the elevated heterogeneity described for EAC. RNAseq libraries were prepared on 50 ng of total RNA (with RNA integrity index RIN &gt;=7) with the TruSeq Stranded mRNA library preparation kit (Illumina) in accordance with low-throughput protocol. After PCR enrichment (15 cycles) and purification of adapter-ligated fragments, the concentration and length of DNA fragments were measured using D1000 Screen Tape System (Agilent), obtaining a median insert size of 311 nucleotides. Then, RNAseq libraries were sequenced using the Illumina NovaSeq platform, 1x100 bp, obtaining on average 100 million single reads per sample.

  Dataset EGAD00001010876

• Cell-free DNA Methylome Analysis Enables Early Preeclampsia Prediction

  This dataset contains in solution target-enrichment bisulfite sequencing of placental tissue, buffy coat and plasma DNA from pregnant women. Blood samples were taken for cell-free DNA (cfDNA) DNA extraction from 64 women at the time of early-onset preeclampsia (PE) diagnosis, or from 38 controls (uncomplicated pregnancies) at a similar gestational age that did not develop preeclampsia subsequently. Among these subjects, plasma samples from 7 PE patients and 6 controls were also subjected to oxidative bisulfite sequencing. Placental tissues from 11 PE and 26 control subjects after delivery, and buffy coat from 16 PE and 16 control subjects at the same time of cfDNA sampling were profiled. A discovery cohort for early PE assessment in the first trimester was collected. In this cohort, cfDNA from 75 pregnancies that went on to develop early-onset PE and from 124 matched controls were collected and methylome sequencing were carried out. An independent validation cohort to validate early PE assessment with methylome profiling was collected as well. This validation cohort includes cfDNA samples from 61 PE and 136 control pregnancies.

  Dataset EGAD00001010159

• How to upload GPG files

  Uploading files Users that holds an ega-box-XXX account can upload files using either INBOX or FTP. Users who have a Submitter role associated with their email will only be able to upload files using INBOX. Before uploading your files please make sure that any files that will be uploaded to EGA do not use special characters in their naming convention such as # ? ( ) [ ] / \ = + < > : ; " ' , * ^ | &. This can cause issues with the archiving process, leading to problems for end users. The EGA is a shared, public service with limited storage. In order to manage the available resources, we enforce a limit of 10Tb per submission account at any one time. Please do not exceed this limit. INBOX FTP The FTP is only compatible with files encrypted using the EGACryptor tool Before uploading Once your submission files have been prepared using the EGAryptor, the resulting encrypted files and associated md5sum files can be uploaded to your submission account using Aspera or FTP. The EGA is a shared, public service with limited resources. In order to manage the available resources, EGA submission boxes should not exceed 8Tb in size, and cannot exceed 12Tb. If you are approaching this limit please contact contact EGA Helpdesk so that we can advise on how to register the associated metadata and trigger the archiving of files, so that you can continue with your submission. If we note that your submission account increases above 10Tb on a consistent base your password will be changed until metadata is associated. Aspera Download Aspera Using Aspera FTP FTP windows FTP Linux / Unix FTP client (Filezilla) FTP and TLS Troubleshooting Troubleshooting Aspera Download Aspera is a commercial file transfer protocol that may provide faster transfer speeds than ftp especially over longer distances. The Aspera ascp command line client. Please select Aspera Connect. The ascp command line client is distributed as part of the aspera connect highperformance transfer browser plugin and is free to use, without registration. The minimum required version of the IBM Aspera Cli is V4. Further instructions. Using the Aspera ascp command line program The location of the ascp program in the filesystem: Mac: on the desktop go cd /Applications/Aspera\ Connect.app/Contents/Resources/ there you'll see the command line utilities where you're going to use ascp. Windows: the downloaded files are a bit hidden. For instance, in Windows 7 the ascp.exe is located in the users home directory in: AppData\Local\Programs\Aspera\Aspera Connect\bin\ascp.exe Linux: should be in your user's home directory, cd /home/username/.aspera/connect/bin/ there you'll see the command line utilities where you're going to use ascp. Your command should look similar to this: ascp -P33001 -O33001 -QT -l300M -L- /path/file ega-box-N@fasp.ega.ebi.ac.uk:/path If you wish to upload several files without being requested the password, please use the below command : ASPERA_SCP_PASS=ega-box-password ascp -P33001 -O33001 -QT -l300M /path/file ega-box-N@fasp.ega.ebi.ac.uk:/path/ Explanation of parameters l300M option sets the upload speed limit to 30MB/s. You may wish to lower this value to increase the reliability of the transfer. L option is for printing logs out while transferring files to upload can be a file mask (e.g. '/homes/submitter/*.srf) or a list of files. ega-box-N is your submission account login. Add k2 switch for transfer restarts Check the command line transfer usage for more configuration details. Using FTP to upload your prepared files Use your preferred ftp client. For example, lftp is a popular choice for Linux and Mac users. Use binary mode for file transfers. Use ftp.ega.ebi.ac.uk as the target host. Login with your ega-box username and password. Upload files to your private ega-box upload area. Depending on your network setting you might wish to start FTP in passive or active mode. Using default FTP command line client in Windows Start the command line interpreter: press WinR, type cmd, hit enter Enter ftp ftp.ega.ebi.ac.uk Enter your submission username Enter your submission password Type binary to enter binary mode for transfer To see a list of available ftp commands type help. Type ls command to check the content of your submission account. Type prompt to switch off confirmation for each file uploaded. Use mput command to upload files: mput *.bam* Use bye command to exit the ftp client. Use exit command to exit the command line interpreter. Using default FTP command line client in Linux / Unix Open a terminal and type ftp ftp.ega.ebi.ac.uk Enter your submission username Enter your submission password Type binary to enter binary mode for transfer To see a list of available ftp commands type help. Type ls command to check the content of your submission account. Type prompt to switch off confirmation for each file uploaded. Use mput command to upload files: mput *.bam* Use bye command to exit the ftp client. Using FTP client FileZilla We recommend the use of FileZilla, a free FTP client . FileZilla is open source software distributed free of charge under the terms of the GNU General Public License. Use the following connection details (File - Site Manager) and add yoursubmission account username and password: Using FTP client FileZilla Select the files you wish to upload and then select upload: Using FTP client Filezilla Using LFTP with TLS We recommend the following to force the use of a secure connection. lftp > set ftp:ssl-force yes We also recommend setting the following for not encrypting the bulk data itself for performance reasons (theauthentication will still be encrypted): lftp > ftp:ssl-protect-data no In order to verify the certificate,the recommended way would be to use the CA certificates from your machine. To do that use this command in lftp adjusting the path to your ca-certificates location. lftp > ssl:ca-file "/etc/ssl/certs/ca-certificates.crt" If that is not possible or certificates are old and you can't update them, you can download the certificates needed from Quo Vadis Digital Repository The two certificates to download in PEM format are: QuoVadis Root CA2 G3 QuoVadis EV SSL ICA G3 Then you can concatenate them in a file one after the other and save it as lftp-certificates.pem Once this is done you have to point the ssl:ca-file variable to the path lftp > set ssl:ca-file "/path/to/lftp-certificates.pem" Also note that you can save this configuration at ~/.lftp/rc Another option is to download the certificates and add them to the ca-certificates of your machine. For example: In RHEL7 and cenots and others box the process to add the certificates globally is: Download the two certificates (in PEM or DER format, doesn't matter) and save them to "/etc/pki/ca-trust/source/anchors/" Run "update-ca-trust extract" Another less secure option is to turn off certificate verification with the following command: lftp > set ssl:verify-certificate false Troubleshooting If you are having problems with Aspera connection timeouts, it can be down to either one of the following. Transfers cannot start the connection fails instantly. Ensure that TCP traffic on port 33001 is allowed (open) for outbound connections through your computer's firewall and network's firewall. The connection is made, transfers are started, but 0 bytes (0%) are uploaded for each file. Ensure that UDP traffic on port 33001 is allowed (open) for outbound connections through your computer's firewall and network's firewal

  Documentation submission/data/uploading-files/ftp

• WTCCC case-control study for Rheumatoid Arthritis

  WTCCC genome-wide case-control association study for Rheumatoid Arthritis (RA) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000011

• WTCCC case-control study for Type 1 Diabetes

  WTCCC genome-wide case-control association study for Type 1 Diabetes (T1D) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000014

• WTCCC case-control study for Type 2 Diabetes

  WTCCC genome-wide case-control association study for Type 2 Diabetes (T2D) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000016

• WTCCC case-control study for Coronary Artery Disease

  WTCCC genome-wide case-control association study for Bipolar disorder (CAD) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000003

• Longitudinal snRNAseq and DNAseq of IDHmutant glioma

  We collected longitudinal glioma samples from 35 patients with an IDH-mutant oligodendroglioma (n = 13) or IDH-mutant astrocytoma (n = 22) diagnosis based on 2021 WHO glioma classification at two or three time points (n = 75 samples). For each patient, we designated the two earliest samples as the initial and recurrence for longitudinal analyses. In 17 of 35 longitudinal pairs, the initial sample was obtained at primary diagnosis, whereas the remaining 18 cases the initial samples were collected at a subsequent surgery. Between the initial and recurrence samples, 26 of 35 patients received radiotherapy and/or alkylating chemotherapy, whereas no adjuvant treatment was reported for the remaining patients. To comprehensively investigate IDH-mutant glioma evolution, we used snRNAseq and bulk DNA/RNA sequencing from the same resected glioma samples. A subset of these samples was profiled with simultaneous snRNA-ATAC sequencing (48 out of 75), including 21 matched longitudinal pairs,

  Dac EGAC50000000973

• NHLBI TOPMed: Best ADd-on Therapy Giving Effective Response (BADGER)

  BADGER is a 56-week randomized, double-blind, three-treatment, three-period cross-over trial that will evaluate the differential improvement in control that is achieved following three separate treatment interventions in children whose asthma is not acceptably controlled on a low dose of ICS (per NAEPP guidelines). All participants will enter an 8-week run-in period during which time they will receive a dose of 1x ICS (fluticasone 200 &#956;g/day). During this 8-week time period, running 2-week averages to establish the lack of acceptable asthma control will be calculated. Thus, a child could qualify for randomization at any time during this 8-week run-in period. This approach should maximize both patient safety and successful enrollment. Children will continue to receive 1x ICS during the entire treatment phase. During each period of the treatment phase, they also will receive one add-on therapy in the form of LABA, LTRA or additional 1x ICS. The order of the add-on therapy assignment will be determined by randomization into one of six treatment sequences (order determined randomly). Each treatment period will be 16 weeks in length; the initial 4 weeks of each period will be considered to be the washout period for the previous treatment. The primary outcome measures will be frequency of asthma exacerbations, asthma control days, and FEV1.

  Study phs001728

• RNA-seq samples

  Raw FASTQ files obtained by RNA sequencing of tumor samples from patients (age 12-29) with newly diagnosed, recurrent intermediate or high-grade sarcoma.

  Dataset EGAD00001008393

• Mitochondrial DNA sequencing of human iPSC, parental cells, and iPSC derived cardiomyocytes

  Dataset contains whole mitochondrial DNA sequencing data in fastq format (Illumina MiSeq paired-end) of 62 samples, in total. Those samples include sequencing data of the endothelial cell populations of 10 different donors and of 26 early-passage iPSC clones derived thereof. Moreover, the dataset contains the data of 7 of those iPSC clones sequenced additionally in passage 30 and 50, each. Lastly, 4 iPSC clones were sequenced during directed cardiomyocyte differentiation, each at day 0, 5, and 15 of differentiation.

  Dataset EGAD00001008021

• Collagen XVII Promotes Pancreatic Cancer Through Regulation of PIK3R5

  Pancreatic ductal adenocarcinoma (PDAC) contains a desmoplastic stroma that promotes the aggressive biology of this disease. While the varied mechanisms by which fibrillar collagens contribute to PDAC have been defined, little is known about the contribution of transmembrane collagens. Among this class of collagens, Collagen XVII uniquely contains an extensive intracellular domain that connects intracellular cytoplasmic components with the extracellular matrix. Collagen XVII is best characterized as the defining component of the type I hemidesmosome, an anchoring complex that attaches epithelial cells to the underlying basement membrane. In this study, we characterize the expression of collagen XVII in PDAC and the mechanisms by which it contributes to PDAC biology. We demonstrate that crosstalk between PDAC cells and cancer associated fibroblasts drive collagen XVII expression in vitro and xenograft tumor models in vivo. Genetic depletion of collagen XVII in low-passage patient derived cell lines diminishes their metastatic potential and ability to form tumors in mice. Whole transcriptome sequencing of tumors formed by cells with diminished collagen XVII levels revealed dramatically lower levels of PIK3R5, a regulatory subunit of class IB phosphatidylinositol-3-kinase (PI3K) that interacts with G protein-coupled receptors. Consistent with this, collagen XVII-deficient tumors exhibited lower levels of phosphorylated AKT, a downstream effector of PI3K. The studies highlight the importance of collagen XVII signaling in PDAC and define a novel mechanism by which collagen XVII mediates activation of PI3K.

  Study phs003641

• Genome-Wide Association Studies of Prematurity and Its Complications (African American)

  Preterm delivery resulting in the birth of a premature infant is a complex problem with a devastating impact on individuals, families and society. The prevalence of preterm birth has increased steadily in developed countries over the last 20 years and more than three million children die of preterm birth worldwide each year. Despite the importance of the problem and its disproportionate occurrence in poor and minority populations, the underlying causes have been difficult to identify. Spontaneous preterm labor has as its suspected triggers infection, stress, poor nutrition and inherited factors. The single best predictor for preterm delivery is a previous preterm birth. Studies of twins and of recurrences within families provide evidence that genetic factors underlie a substantive component of the risk for prematurity. One major challenge in studying genetic factors in prematurity is that the risk case is not truly established. The genetic risk could reside either in the mother and her uterus or in the infant/placenta. Identification of genetic factors in the mother and/or infant could provide insights into identifying relevant environmental covariates that may be more amenable to rapid interventions but difficult to find using standard epidemiology alone. A comprehensive genome-wide association study (GWAS) is the ideal way to identify those genes that would not be suspected based on our current understanding of the biology of parturition. We are using 2200 African American samples with term or preterm labor. A subset of these (~800) are infant samples recruited by the Neonatal Research Network as part of a study on cytokines and infection in extremely low birth weight infants (Schelonka RL, et al., 2011. PMID: 21145756). Therefore, this group consists of infants &lt;1,000 grams with clinical outcome data for the infant allowing study of the genetic contributors for not only preterm birth but also the complications that often accompany preterm birth. The result will enable a better understanding of the biology of parturition and suggest environmental modifications that can prolong gestations to improve neonatal and adult outcomes. 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 preterm birth through large-scale genome-wide association studies of African-American cases and controls from multiple sites in the United States. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000353

• WTCCC2 case-control study for Ulcerative Colitis

  WTCCC2 project genome-wide case-control association study for Ulcerative Colitis (UC) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000084

• DNA methylation database for gynecological cancer detection, classification and assay development

  MeD-seq data (fastq files) from gynecological cancers and associated healthy tissues. In total 292 fastq files generated by MeD-seq are deposited consisting of: healthy tissues (vulva n=11, cervix n=15, endometrium n=13, fallopian tube n=18 and ovary n=13), precursor lesions of cancer (vulva n=23 and cervix n=46) and cancer (vulva n=21, cervix n=45, endometrium n=26, fallopian tube n=8 and ovary n=33)

  Dataset EGAD50000000611

• From research to data sharing: exploring EGA user's experiences

  The Cell Plasticity and Regeneration Group at the Bellvitge Biomedical Research Institute-IDIBELL focuses on the process of recruitment of macrophages that takes place in the small intestine during injury and healing. They recently published a paper titled “Mucosal Macrophages Govern Intestinal Regeneration in Response to Injury" in Gastroenterology Journal. As part of the research, some experiments were conducted using human intestinal organoid lines. These cells were processed for RNA sequencing, and the sequencing data were deposited at the EGA to be made available to the scientific community. When dealing with human genomic information, repositories must ensure the availability of the datasets while ensuring data protection. In this context, the European Genome-phenome Archive stands as a service for secure archiving and sharing of genetic, phenotypic and clinical data resulting from biomedical research. Following the recent publication of their paper, we took the opportunity to talk to Ilias Moraitis, first author, and Jordi Guiu, group leader, to find out about their experience with data sharing. Could you explain the focus of your research? In the lab, we study intestinal regeneration and how immune cells participate in this process. We use several techniques: engineered mouse models, image tracing, as well as mouse and human cells intestinal organoids. What challenges do you face regarding data management? We didn’t have a lot of problems. Always the informatic part, the data analysis, can give problems. But everything was smooth and working. We think it’s very important to deposit the data in repositories. For the mouse data it is very straightforward, but for us it was the first time depositing human data, which is sensitive because it comes from patients, and this is legally regulated. That’s why we thought about the EGA, and it was our first time. Why do you think it is important to submit data to repositories such as EGA? Because we think data is important for the science. Nowadays, we are sequencing a lot everywhere worldwide and having these resources shared with the scientific community it’s not only good for science, but it is also saving money and reducing costs. And there is so much data in there that can be used for other projects and for other questions. And it saves time! How was the process of submitting the data to the EGA? The communication worked very well but it was slower than we would like. But I think this is something we learn on the way. People usually wait until the last minute to do this before publication but if you know it in advance, you can start the process earlier. If you had to repeat the process, would you do anything differently? It’s like everything, isn’t it? For the first time you don’t know, you aren’t sure, but for the second time you know the steps, you know what to do and it’s faster. Of course, we would to do it earlier. Also, there were some things related to the control access that we didn’t know how to manage, but it was something more internal to us. Who is going to receive the communications and when, is our ethical committee going to evaluate this? All these technicalities that we didn’t know before starting this process, so we had to think about all these things. Next time it will be faster on our side. Do you have any suggestions for us to improve the submission process? Maybe we’ll need to ask our bioinformatician who did it! He was in charge of this part. Besides that, we think if the process were faster, it would be better for everyone. Also, in science a lot of times you have to do a lot of things at the very last minute, because of the nature of the experiments, or the need to accomplish for submitting a paper. Being faster in the process would be a plus. On your side, we went through the process and were able to find some information, but there were aspects we weren't aware of and weren't sure how to handle. I'm not sure if other institutes have different protocols for managing data requests or how they handle these internally. We believe the main issue lies in how the forms are filled out. Do you have any recommendations for other submitters? The main advice is to do this with enough time. Submit the data when you have the sequences, and don’t wait until the last minute. And then it can be under embargo, so you don’t need to make it public at that moment. As soon as you sequence, upload it and then it will be there for whenever you need to publish. How do you think we could encourage other researchers to submit their data? There are different layers here. One is that it is mandatory. You have to do this. The other is that we belong to a research community, to the same community and sharing this is making our research community stronger and more efficient. And then, also because this gives you visibility. The data is there, other people can analyse your data, and this also will bring citations to your papers. It has many advantages.

  Blog from-research-to-data-sharing

• 10x Genomics raw data of intestinal plasma cells

  The dataset contains raw fastq files (fastq.gz) for Chromium Single Cell 5’ gene expression (GEX), human B cell VDJ and feature barcode (CSP) sequencing from transglutaminase 2-specific and other small intestinal plasma cells isolated from four untreated celiac disease patients. Single cell 5’ gene expression, V(D)J-enriched and cell surface protein libraries were generated using Chromium single cell kits, and barcoded cDNA from a total of 5,000-10,000 cells per sample was generated using the 10x Genomics Chromium Controller. The libraries were pooled prior to sequencing on a NovaSeq 6000 instrument (Illumina) using the following configuration: read 1: 26 cycles, read 2: 89 cycles, index read 1: 8 cycles.

  Dataset EGAD50000000342

• Genomewide Association Study of Inflammatory Bowel Disease

  WTCCC genome-wide case-control association study for Inflammatory Bowel Disease (IBD) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000006

• Variability in immune response genes and prediction of severe SARS-CoV-2 infection (INMUNGEN-Cov2 project)

  Genetic factors may contribute to explain the variable clinical response to SARS-CoV-2 infection. To this end we sequenced the DNA of 392 COVID-19 patients from Spain. Whole Exome Sequencing (WES) was performed at two different sequencing centers. Half of the samples were sequenced at a commercial service, NIMGenetics, whereas the other half were sequenced by the EASI-Genomics consortium. Finally, Variant Call Format (VCF) files for each sample was also obtained.

  Study EGAS50000000066

• Genome-Wide Association Study of HIV-1 Host Genetics Among Injection Drug Users

  The overarching goal of this project is to identify and characterize genetic determinants of HIV 1 susceptibility and resistance in samples of African American (AA) and European American (EA) injection drug users (IDUs) by conducting (1) a case/control genome-wide association (GWA) study of HIV 1 infection (positive/negative); (2) a case-only GWA study of viral load among HIV+ IDUs. The study uses existing samples and data from Urban Health Study (UHS) (PI: Alex Kral), which was the longest-running study of street-recruited IDUs in North America, from 1986-2005. UHS was a serial, cross-sectional sero-epidemiological study. Data were collected every 6 months in communities with a high prevalence of injection drug use in the San Francisco Bay Area. It used targeted sampling in neighborhoods at easily accessible community field sites, such as churches, single room occupancy hotels, and community centers. Eligibility criteria for initial entry to the study were (1) injection drug use in past 30 days; (2) ability to provide informed consent; and (3) age 18 or older. The UHS cohort includes over 9,000 African American and European American IDUs whose serum samples have been stored and data are available on HIV antibody status, HIV risk behaviors, drug abuse and demographics. The current study includes 985 HIV+ cases and 5,222 HIV- controls. Approximately six HIV- controls per case were frequency matched on: (1) self-reported ancestry; (2) sex; (3) age; (4) year of ascertainment; and (5) HIV risk class. This GWAS (DA026141) was funded by the National Institute on Drug Abuse (NIDA; PI: Eric O. Johnson). Funding support for genotyping, which was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR), was provided by NIDA and the NIH contract "High throughput genotyping for studying the genetic contributions to human disease"(HHSN268200782096C).

  Study phs000454

• Germline RUNX1 Variation and Predisposition to Childhood Acute Lymphoblastic

  Somatic mutations of RUNX1, which encodes the myeloid and lymphoid transcriptional factor RUNX1, are common in both B- and T- acute lymphoid leukemia (ALL) and are associated with poor prognosis of T-ALL. However, there has been no comprehensive investigation of the pattern or prevalence of RUNX1 germline mutation in both B- and T-ALL. Here we report germline RUNX1 variants in 1.23% of B-ALL and 2.11% of T-ALL, identifying 31 unique variants in 62 B-ALL and 18 unique variants in 26 T-ALL children. The majority of frameshift and nonsense variants affected RUNX1 function in transcriptional regulation, hematopoiesis, and cellular proliferation. We identified JAK3 as the most frequent somatic mutation in T-ALL with RUNX1 variants. These results not only identify RUNX1 as a leukemia predisposition gene but also further underline the importance of germline genetic variants to the development of ALL

  Study EGAS00001005403

• Non-coding mutations reveal cancer driver cistromes in luminal breast cancer

  Whole-genome sequencing of primary breast tumors enabled the identification of cancer driver genes and non-coding cancer driver plexuses from somatic mutations. However, differentiating between driver and passenger events among non-coding genetic variants remains a challenge to understand the etiology of cancer and inform the delivery of personalized cancer medicine. Herein, we reveal enrichment of non-coding mutations in cis-regulatory elements that cover a subset of transcription factors linked to tumor progression in luminal breast cancers. Using a cohort of 26 primary luminal ER+PR+ breast tumors, we compiled a catalogue of ~100,000 unique cis-regulatory elements from ATAC-seq data. Integrating this catalogue with somatic mutations from 350 publicly available breast tumor whole genomes, we identified four recurrently mutated individual cis-regulatory elements. By then partitioning the non-coding genome into cistromes, defined as the sum of binding sites for a transcription factor, we uncovered cancer driver cistromes for ten transcription factors, namely CTCF, ELF1, ESR1, FOSL2, FOXA1, FOXM1 GATA3, JUND, TFAP2A, and TFAP2C in luminal breast cancer. Nine of these ten transcription factors were shown to be essential for growth in breast cancer, with four exclusive to the luminal subtype. Collectively, we present a strategy to find cancer driver cistromes relying on quantifying the enrichment of non-coding mutations over cis-regulatory elements concatenated into a functional unit drawn from an accessible chromatin catalogue derived from primary cancer tissues.

  Study EGAS00001005235

• Bleomycin Induced Pneumonitis WGS dataset

  This is whole genome sequencing data from a cohort of 18 patients with germ cell tumours or Hodgkin Lymphoma, who developed clinically significant bleomycin-induced pneumonitis despite low clinical risk. DNA was extracted from whole blood, and 150-base paired-end reads were generated on an Illumina NovaSeq 6000 instrument to a minimum 30x depth. Sequence reads were aligned to the GRCh38 reference with BWA MEM, and germline variants were called following GATK best practice procedures. The dataset comprises per-sample read alignment files in BAM format, and a joint-called germline variant file in VCF format.

  Dataset EGAD50000002221

• WTCCC case-control study for Hypertension - Combined Controls

  WTCCC genome-wide case-control association study for Hypertension (HT) using six disease collections together with the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000010

• Benchmarking for alignment and variant calling

  Background: Lung cancer is a heterogeneous disease and the primary cause of cancer-related mortality worldwide. Somatic mutations, including large structural variants, are important biomarkers in lung cancer for selecting targeted therapy. Genomic studies in lung cancer have been conducted using short-read sequencing. Emerging long-read sequencing technologies are a promising alternative to study somatic structural variants, however there is no current consensus on how to process data and call somatic events. In this study, we preformed whole genome sequencing of lung cancer and matched non-tumour samples using long and short read sequencing to comprehensively benchmark three sequence aligners and six structural variant callers comprised of four generic callers (Sniffles2, cuteSV, SVIM and DELLY in generic mode) and two somatic callers (nanomonsv and DELLY in somatic modes). Results: Different combinations of aligners and variant callers influenced somatic structural variant detection. The choice of caller had a significant influence on somatic structural variant detection in terms of variant type, size, sensitivity, and accuracy. The performance of each variant caller was assessed by comparing to somatic structural variants identified by short read sequencing. When compared to somatic structural variants detected with short read sequencing, more events were detected with long read sequencing. The mean recall of somatic variant events identified by short read sequencing was higher for the somatic callers (64%) than generic callers (52%), with nanomonsv (69%) showing the best performance. Conclusion: Long read sequencing can identify somatic structural variants. The longer reads have the potential to improve our understanding of cancer development and inform personalized cancer treatment.

  Study EGAS00001007819

• Variant calling dataset from the whole-exome study of familial pulmonary fibrosis in the Canary Islands-VCF files

  Sequence reads were obtained from a set of 13 families with familial pulmonary fibrosis in the Canary Islands, Spain, using Illumina paired-end reads, respectively, at the Institute of Technology and Renewable Energy (ITER). Briefly, we used bcl2fastq v2.18 to perform sample demultiplexing and BWA-MEM v0.7.15 (https://github.com/lh3/bwa) to align reads to GRCh37/hg19 reference. Resulting BAM files were assessed with SAMtools v1.3 (http://www.htslib.org) and Picard v2.10.10 (https://broadinstitute.github.io/picard/) for quality control steps. Small insertions/deletions (< 50 bp) and single nucleotide variants (SNVs) were identified using an in-house bioinformatics pipeline based on GATK HaplotypeCaller v3.8 (https://gatk.broadinstitute.org/hc/en-us/articles/360037225632-HaplotypeCaller). This pipeline follows the Best Practices recommendations for germline variant calling and its description is publicly available (https://github.com/genomicsITER/benchmarking/tree/master/WES).

  Dataset EGAD50000001152

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

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

  Dataset EGAD00001008314

• Genome-Wide Association Studies of Prematurity and Its Complications

  Preterm labor resulting in the delivery of a premature child is a complex problem with an enormous impact on individuals, families and society. An estimated 500,000 children are born prematurely in the U.S. each year, and 5 million worldwide die annually of prematurity and its complications. Prematurity is also the single largest contributor to disability-adjusted life years, a measure of the lifetime impact of a disease. Despite the importance of the problem and its disproportionate occurrence in poor and minority populations, its underlying etiology (or etiologies) remains unknown; the single best predictor for preterm delivery is a previous preterm birth. The largest single cause of prematurity is spontaneous preterm labor, and suspected triggers for this include infection, stress, poor nutrition and genetic factors. Family and twin studies provide strong evidence that genetic factors underlie about 40% of the risk for prematurity. A major challenge in studying genetic factors in prematurity is maternal/uterine factors, fetal/placental factors, or both may influence risk. Thus, any approach to studying preterm birth should account for both infant and maternal risk, environmental covariates and interactions. The Danish National Birth Cohort (DNBC) is a well-established, prospective cohort that enrolled women early in pregnancy, prior to any adverse pregnancy outcomes, to minimize bias in data collection and sampling. See details at: http://www.ssi.dk/English. The DNBC followed over 100,000 pregnancies beginning in the first trimester and has extensive biological material and epidemiologic data on health outcomes in both mother and child. The current study posted on dbGaP contains data from a genome-wide case/control study using approximately 1,000 preterm mother-child pairs from the DNBC most with spontaneous onset of labor or preterm premature rupture of membranes (PPROM), along with 1,000 control pairs where the child was born at ~40 weeks&#39; gestation. After data cleaning some small changes in case/control status and other variables resulted in minor changes in numbers of cases or controls in certain categories. Environmental variables are being used as covariates in the analysis. To replicate positive findings, we are using additional mother-child pairs from the DNBC and from the general Danish population, as well as 2200 samples coming primarily from an African-American population known to have high rates of preterm labor and delivery. This group includes over 1000 mostly very low birthweight infants, over 500 infant term controls, 326 term mother/baby pairs and 180 preterm mother/baby pairs. The data from these additional cohorts will be available in separate dbGaP postings. The study is expected to yield a better understanding of the biology of parturition, identify common genetic factors that play a role in preterm birth and its complications and suggest environmental modifications that can prolong gestation, with the goal of improving both neonatal and adult outcomes. 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 prematurity and its complications through large-scale genome-wide association studies of a well-characterized cohort of Danish mothers and babies. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000103

• Regulatory T cell transcriptomic reprogramming characterizes adverse events by checkpoint inhibitors in solid tumors

  Tregs were sorted as CD4+CD25+CD127- cells from peripheral blood of patients with advanced metastatic melanoma, stage III(B-D)-IV, who were receiving treatment with anti-PD1 (n =26); and patients with kidney, non-small cell lung, liver and bladder cancer who were receiving treatment with anti-PD1. RNA was extracted and polyA libraries were prepared using the Illumina Truseq sample preparation kit v.2. Single-end sequencing was performed on NextSeq500.

  Dataset EGAD00001006415

• WTCCC case-control study for Rheumatoid Arthritis - Combined Controls

  WTCCC genome-wide case-control association study for Rheumatoid Arthritis (RA) using six disease collections together with the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000012

• WTCCC case-control study for Bipolar Disorder

  WTCCC genome-wide case-control association study for Bipolar disorder (BD) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000001

• Defining Cutaneous Gene Expression Signatures in Juvenile Dermatomyositis

  Skin inflammation in juvenile dermatomyositis (JDM) can signal disease onset or flare up and prevent complete disease remission. Our objective was to evaluate JDM cutaneous expression signatures through tape stripping in both lesional and non-lesional skin and as compared to paired blood. A total of 28 JDM and 20 control (CTL) patients participated in the study. All patients had tape strip sampling of non-lesional (NL) skin at enrollment visit. Within our JDM cohort, paired lesional (L) skin was additionally sampled if rash was present. 16/28 of JDM patients had at least one additional skin sample associated with a follow-up (FU) visit (total number of follow-up samples included = 26 NL and 4 L). We identified a common innate immune signature in both lesional and non-lesional JDM skin. Using unsupervised hierarchical clustering of skin expression data, we distinguished a JDM molecular subgroup characterized by a mitochondrial dysfunction signature. In comparison to blood expression data, we determined that skin may more effectively highlight the JDM subgroup characterized by a mitochondrial dysfunction expression signature. Data available include bulk RNA-sequencing data from tape strips and blood of the JDM and control patients from this study.

  Study phs003884

• PyEGA3 download client

  PyEGA3 Checks prior to download - Is the dataset available for download? Most datasets are available using the PyEGA3 Download client, except for specific legacy datasets. For these ones, refer to Live Outbox distribution, an alternative way to download these datasets.If the dataset you've been granted access to begins with the ID EGAD5XXXXXXX, please refer to the Live Outbox distribution. If the dataset you have been granted access to contains encrypted data (filename ending in .gpg), contact EGA Helpdesk for detailed information on how to download these files.General Information The PyEGA3 download client is available at its GitHub repository. In its README you will find a step by step guide on how to use it to download files you have been granted access to. PyEGA3 implements the GA4GH-compliant HTSGET protocol supporting requests over genomic ranges. This enables the download of specific regions of interest rather than the entire file. HTSGET is not possible for all the files held by EGA: if the dataset does not contain index files (e.g. filename ending in *.crai), then genomic range requests cannot be performed. The maximum number of connections allowed is 30. If more than 30 connections are used, the download client will encounter 500 errors. The recommended number of connections for maximum output is one. Check out our video tutorial! Frequently Asked Questions General questions How do I download the datasets to which I have been granted access? After setting up your EGA download account, you can proceed to download using the EGA download client – PyEGA3. The pyEGA3 download client is a python-based tool for viewing and downloading files from authorised EGA datasets. This download client is continuously being developed for more user-friendly download experiences. Can I download the dataset’s metadata via the download client? No, the download client cannot be used to download metadata. Registered EGA users can download metadata of an authorised dataset by logging into the EGA webpage and navigating to the dataset of choice. Approximately two thirds down the page you will find the option to download the metadata as a zip file. How do I download large datasets as quickly as possible? The main EGA download client is pyEGA3 download client, a python-based tool for viewing and downloading files from authorised EGA datasets.We could exceptionally consider the option of an Aspera download for users experiencing very slow download rates or facing particular issues.Contact the EGA Helpdesk for further information. Pre-requirement and Installation What are the major requirements for the PyEGA3 download client installation and usage? The PyEGA3 client is compatible with any OS with Python 3.6+ installed. The client requires a connection to the internet, sufficient space on the destination drive, and the EGA download account credentials. Where can I find the PyEGA3 download client installation and download instructions? We strongly recommend checking our video tutorial demonstrating the usage of PyEGA3 from installation to file download. More detailed information is available at PyEGA3 GitHub. What ports are required for the PyEGA3 download client to function? PyEGA3 makes HTTPS calls to the EGA Data API (https://ega.ebi.ac.uk:8443). This port 8443 must be reachable from the location where PyEGA3 is executed to avoid timeouts. PyEGA3 download client How to update the PyEGA3 download client to be on the latest version? Updating the client to the latest version can be achieved by running the following command: pip3 install pyega3 --upgrade I do not have an active EGA account. Can I test the download with the PyEGA3 download client? An EGA download test account (ega-test-data@ebi.ac.uk) has been created for troubleshooting and training purposes. The test account does not require an EGA username and password because it contains publicly accessible files from the 1000 Genomes Project. More information about the use of this account and log in details are available at pyEGA3. I lost my connection while the download was in progress. Does this mean that I have to download the file again from the start? The PyEGA3 download client supports automatic resumption of downloads. To enable quicker download speeds, the API breaks files into up to four segments and downloads them in parallel. With the resume feature, downloads will automatically resume if you encounter any errors or if the connection is interrupted. How can I improve the overall download speed of the PyEGA3 download client? Download speeds can be optimised using the --connections parameter which will parallelise download at the file level. If the --connections parameter is provided, all files >100Mb will be downloaded using the specified number of parallel connections. It is important to note that files are still downloaded sequentially, so using multiple connections does not mean downloading multiple files in parallel. The maximum number of connections allowed is 30. If more than 30 connections are used, the download client will encounter 500 errors. The recommended number of connections for maximum output is one. Why is my file taking a long time to be saved? Please note that when a file is being saved, it goes through two processes. First, the downloaded file "chunks" are pieced back together to reconstruct the original file. Secondly, PyEGA3 calculates the checksum of the file to confirm that the file was downloaded successfully. Larger files will take more time to reconstruct and validate the checksum. Why is the HTSGET protocol not working with my dataset of interest? PyEGA3 implements the GA4GH-compliant htsget protocol for supporting requests over genomic ranges. This exciting new feature means that for data files with accompanying index files (e.g. .crai for CRAM files) users can download specific regions of interest rather than the entire file, saving both time and storage space. Please note that in order for the genomic range requests to work for a BAM, CRAM or VCF file there must be an associated BAI, CRAI or TBI file, respectively. If the dataset does not contain these index files then genomic range requests cannot be performed. After download Do I need to decrypt data files downloaded through the pyEGA3 download client? Files are transferred over secure HTTPS connections and received unencrypted, thus there is no need for decryption after data download. What is the purpose of an MD5 file? After the download completes, file integrity is verified using checksums. The PyEGA3 download client automatically verifies each file’s unencrypted md5 after download to ensure that the file was downloaded correctly from the EGA. Errors Why do I get a “400 Client Error” while trying to access the download client? Ensure that your credentials are formatted correctly. Please contact the EGA Helpdesk if you are unsure about your account’s username (i.e. your email address). Why do I get a “500 Server Error”? It is important to note that files are still downloaded sequentially, so using multiple connections does not mean downloading multiple files in parallel. The maximum number of connections allowed is 30. If more than 30 connections are used, the download client will encounter 500 errors. The recommended number of connections for maximum output is one. Otherwise, 500 server errors are internal server errors from EGA’s end. Retry after some time and, if the 500 error persists: check our homepage or Twitter for any outage information or report it to EGA Helpdesk. Why do I get a “slice error”? This type of error occurs when one slice download was prematurely interrupted. Please re-start the same download. The download client will pick up any partial download and download any missing slices. Why do I get the error “Dataset' EGADXXXXXXXXXXX' is not in the list of your authorised datasets”? Please note that the data access was given to the email (username) provided to the Data Access Committee (DAC) in your official request. Therefore, you shall check that the account that you are using is the same one that you sent to the DAC. Why do I get “ERROR:root:Failed to obtain IP address”? This might mean that the connection ports are blocked. Check that the port 8443 is reachable.In case the port is reachable and the error persists, please try to modify the file pyega3.py on line 44 in the python module installation: Replace endpoint = 'https://ipinfo.io/json' with endpoint = 'https://api.myip.com' Why do I get the error “Invalid username, password or secret key - please check and retry”? Make sure that you are using the correct credentials (username and password) and there is no typo. Contact EGA Helpdesk if the problem persists.

  Documentation access/download/files/pyega3

• Trisomy21: Risk Factors for Chromosome Nondisjunction (T21NDJ)

  The overall goal of the project is to identify genetic risk factors associated with chromosome 21 nondisjunction in the oocyte. The dataset derives from multi-site collection of live birth probands with Down syndrome due to standard trisomy 21 (T21) and their biological parents. The type of nondisjunction error (NDJ)(maternal or paternal) in all cases has been determined to be maternal in origin based on the chromosome 21 variants contributed from parent to proband. The Center of Inherited Disease with support from NICHD has conducted genome-wide genotyping using the Illuminia Human OmniExpress Plus Exome array on approximately 800 women who have been identified through their offspring with DS and have been characterized as having a maternal meiois I (MI) or meiosis II (MII) nondisjunction error. Genotypes from biological fathers of the offspring with DS can be used with the data on mothers to better define the type of nondisjunction error (MI or MII) and to refine the chromosome 21 recombination profile. We provide the type of nondisjunction error, knowing that this will be updated based on the new panel. We do not provide the recombination profile, as this can be best defined using the new comprehensive set of SNPs in the OmniExpress panel.

  Study phs000718

• WTCCC case-control study for Coronary Artery Disease - Combined Controls

  WTCCC genome-wide case-control association study for Coronary Artery Disease (CAD) using six disease collections together with the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000004

• WTCCC case-control study for Type 1 Diabetes - Combined Controls

  WTCCC genome-wide case-control association study for Type 1 Diabetes (T1D) using six disease collections together with the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000015

• WTCCC case-control study for Type 2 Diabetes - Combined Controls

  WTCCC genome-wide case-control association study for Type 2 Diabetes (T2D) using six disease collections together with the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000017

• Study of Controlled Human Malaria Infections to Evaluate Protection After Intravenous or Intramuscular Administration of PfSPZ Vaccine in Malaria-Naive Adults

  The study was performed to evaluate whole-blood transcriptomic profiles via RNA-seq before, during, and after immunization with the PfSPZ Vaccine in malaria-na&#239;ve, health adults enrolled in VRC 314 (NCT02015091). VRC 314 was designed as an open-label evaluation of the safety, tolerability, immunogenicity, and protective efficacy of the PfSPZ Vaccine. This study was designed to substantiate the initial results with the IV vaccination route for protection against CHMI that was observed in VRC 312 (NCT01441167). Based on the potential importance of dose and schedule in optimizing sustained immunity with this vaccine, an increase in PfSPZ IV dosage on schedules of 3 to 5 vaccinations was evaluated for protection against CHMI conducted early (about 3 weeks) and late (about 24 weeks) after completion of vaccinations. To assess if a higher dose given by another route confers protection, one group received PfSPZ IM, with half of the amount administered in each arm on a schedule with 4 vaccination. The primary objectives of the study were related to the safety and tolerability of vaccinations by the IV and IM routes of administration and protection against Plasmodium falciparum (Pf) challenge performed via a well-established CHMI procedure early (2-4 weeks) after completing schedules of 3 to 5 vaccinations. The secondary objective was related to the durability of protection at 20-26 weeks after the last vaccination, and exploratory objectives were related to the immunogenicity of the PfSPZ Vaccine and identifying potential immune correlates of protection. To further determine potential molecular correlates of immunogenicity and/or protection, RNA-seq was performed on whole blood collected from subjects in all dose groups at time points before, during, and after immunization.

  Study phs002423

• WTCCC case-control study for T1D and RA - combined cases

  WTCCC genome-wide case-control association study using two disease collections together with the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000013

• Genomewide Association Study of Inflammatory Bowel Disease - Combined Controls

  WTCCC genome-wide case-control association study for Inflammatory Bowel Disease (IBD) using six disease collections together with the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000007

• GeneScreen, a Population Based, Targeted Genomic Screening Study

  The GeneScreen research study was based at the University of North Carolina (UNC) at Chapel Hill. It brought together researchers from different disciplines, including genetics, clinical medicine, bioethics, sociology, anthropology, psychology, and public health, to study the best ways to offer targeted genetic screening to the general adult population. DNA samples were collected from people who joined GeneScreen to look at a targeted panel of 17 genes. It tested for genetic differences (called mutations) that can cause one of 11 rare, but preventable or treatable conditions, including certain types of cancer and heart disease. Each condition has specific medical advice people can follow with their doctors to prevent or treat a serious health problem. The GeneScreen study was approved by the UNC Institutional Review Board and by the Kaiser Permanente Center for Health Research Institutional Review Board. GeneScreen is funded by the National Human Genome Research Institute of the National Institutes of Health.

  Study phs001817

• 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&#8211;FGFR3 fusions/rearrangements; n=49 Activating FGFR1&#8211;FGFR3 non-kinase domain single nucleotide variants (SNVs); n=32 FGFR1&#8211;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 &#8805; 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

• Identification of putative multiple myeloma (MM) susceptibility genes

  We sought to identify novel MM susceptibility genes using a collection of families with multiple cases of MM/MGUS, including 189 affected individuals from 40 families, and index cases from an additional 88 families, along with 170 early-onset (EO) MM cases (≤ 55 years). We analyzed a total of 347 affected individuals using whole exome (N=321) and whole genome (N=26) sequencing. Samples were identified and collected through nation-wide efforts in France, Sweden and Greece. We focused on rare (MAF<0.5%) germline protein truncating and likely deleterious missense variants in genes harboring variants in at least two families showing variant-disease segregation, and in additional index (≥2) and/or early-onset (≥2) cases.

  Study EGAS50000001259

• Atezolizumab and Bevacizumab in Treating Patients With Rare Solid Tumors

  This phase Ib/II single-arm study evaluated atezolizumab + bevacizumab for patients with treatment-refractory metastatic HPV+ anal cancer. The primary endpoint was best overall response, and secondary endpoints included progression-free survival, overall survival, and safety/tolerability. Paired tissue biopsies were collected in patients before treatment and at the time of first restaging and analyzed for whole-exome sequencing, RNAseq (Bulk), and multiplex immunofluorescence. The overall response rate among 20 patients was 10%. WES and RNAseq data are provided here.

  Study phs003845

• WTCCC case-control study for Inflammatory Bowel Disease, T1D and RA - combined cases

  WTCCC genome-wide case-control association study using three disease collections together with the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000008

• A Genome-Wide Association Study of Fuchs' Endothelial Corneal Dystrophy (FECD)

  Fuchs&#39; Endothelial Corneal Dystrophy (FECD) is a common disease that results in loss of vision associated with progressive corneal edema and loss of corneal transparency. In the initial stages of the disease, excrescences on Descemet&#39;s membrane with the appearance of an abnormal posterior collagenous layer, result in the clinical and pathologic appearance of guttae. Corneal edema ensues as endothelial function is compromised that may result in stromal edema, epithelial edema, and painful bullous keratopathy. Penetrating or endothelial keratoplasty is the only definitive treatment, with palliative care the only option prior to surgery. The pathophysiology underlying FECD, particularly in the common cases that affect older individuals, remains unknown, with a genetic predisposition being reported as the single best predictor of disease. Three independent groups funded by the National Eye Institute (NEI), with well-established programs in the genetics of FECD, conducted a genome-wide association study of FECD. The collaboration comprised investigators from Case Western University (CWRU), Duke University (DUEC), and Johns Hopkins University (JHU). CWRU and DUEC contributed samples that were genotyped at CIDR for the GWAS. Johns Hopkins University (JHU) provided samples for the replication phase of the study, where their data are not listed in dbGaP. Cohorts of FECD cases and controls were assembled. Synchronization of clinical and coded data was performed to unify the information across centers. The family history, clinical, demographic information, and genome-wide genotype data for samples from CWRU and DUEC were deposited in dbGaP.

  Study phs000421

• Heart Failure Network: Diuretic Optimization Strategies Evaluation in Acute Heart Failure (HFN DOSE-BioLINCC)

  ObjectivesThe DOSE study sought to evaluate the most effective dosing (high vs. low) and administration (continuous infusion vs. intermittent boluses) combination of the diuretic Furosemide in the treatment of patients with acute decompensated heart failure.BackgroundAcute decompensated heart failure is the most common cause of hospital admissions among patients older than 65 years of age and is responsible for more than 1 million hospitalizations annually in the United States. Intravenous loop diuretics are an essential component of current treatment and are administered to approximately 90% of patients who are hospitalized with heart failure. Despite decades of clinical experience with these agents, prospective data to guide the use of loop diuretics are sparse, and current guidelines are based primarily on expert opinion. As a result, clinical practice varies widely with regard to both the mode of administration and the dosing.SubjectsA total of 308 patients were enrolled between March 2008 and November 2009 at 26 clinical sites in the United States and Canada. DesignThe DOSE study was a prospective, randomized, double-blind, controlled trial with a 2-by-2 factorial design. Patients were randomly assigned to either a low-dose strategy (total intravenous furosemide dose equal to their total daily oral loop diuretic dose in furosemide equivalents) or a high-dose strategy (total daily intravenous furosemide dose 2.5 times their total daily oral loop diuretic dose in furosemide equivalents) and to administration of furosemide either by intravenous bolus every 12 hours or by continuous intravenous infusion.The study treatment, with group assignments concealed, was continued for up to 72 hours. At 48 hours, the treating physician had the option of adjusting the diuretic strategy on the basis of the clinical response. An assessment of biomarkers, including creatinine, cystatin C, and N-terminal pro-brain natriuretic peptide, was performed at a central core laboratory at baseline, 72 hours, and 60 days. Patients were followed for clinical events to day 60. The coprimary end points were patients' global assessment of symptoms, quantified as the area under the curve (AUC) of the score on a visual-analogue scale over the course of 72 hours, and the change in the serum creatinine level from baseline to 72 hours.ConclusionsAmong patients with acute decompensated heart failure, there were no significant differences in patients' global assessment of symptoms or in the change in renal function when diuretic therapy was administered by bolus as compared with continuous infusion or at a high dose as compared with a low dose. (Felker et. al., 2011, PMID: 21366472)

  Study phs003524

• Resuscitation Outcomes Consortium (ROC) Cardiac Epidemiologic Registry (Cardiac Epistry) Versions 1 and 2 (ROC-Cardiac Epistry 1 and 2-BioLINCC)

  Data Access NOTE: Please refer to the &#8220;Authorized Access&#8221; section below for information about how access to the data from this accession differs from many other dbGaP accessions. Available Data: The ROC Cardiac Epistry versions 1 and 2 include all cardiac arrest cases entered into the ROC database from December 1, 2005 to April 1, 2011. ROC Cardiac Epistry 3 includes cardiac arrest cases captured between 2011 and 2015, and introduced significant changes in how and which data were collected.For ROC traumatic injury Epistry data, please see: ROC-Trauma Epistry Objectives: To build a prospective population-based registry of participants with out-of-hospital cardiac arrest responded to by Emergency Medical Services (EMS). Specific aims: to establish whether the results of Resuscitation Outcomes Consortium (ROC) trials can be generalized to the larger population of participants that experience cardiac arrest;to more fully establish the burden of cardiac arrest; and to examine the relationships between variation in EMS structure and process, regional and periodic factors, and participant outcomes.Background: Cardiac arrest is a common, serious, debilitating and costly public health problem. Although there has been a steady decline in morbidity and mortality from most cardiovascular diseases, high mortality rates for out-of-hospital cardiac arrests continue to pose a challenge for healthcare providers and a significant public health burden. The Resuscitation Outcomes Consortium (ROC) was established in 2004 to conduct clinical research in the areas of cardiopulmonary arrest and life-threatening traumatic injury with the overall goal of improving resuscitation outcomes. Participant and care characteristics can predict favorable outcomes in cardiac arrests, but there is still a wide variation in outcomes that is not well understood. EMS factors such as service level, number of responding providers, use of procedures or drugs in the field, training, quality assurance/feedback, and response time intervals also vary significantly by region. Variations in geographic, socioeconomic and periodic factors may also be associated with differences in outcomes.Prior to ROC Cardiac Epistry, there were no North American population-based registries for out-of-hospital cardiac arrests. Therefore there was a need for standardized data collection of out-of-hospital cardiac arrests in diverse geographic locations in order to identify the independent effects of prognostic or treatment factors accounting for variations in survival. Participants: The registry included 109,326 cardiac arrest events from 264 EMS agencies transporting to 287 acute care hospitals from the following regional centers: Birmingham, Alabama; Dallas, Texas; Iowa City, Iowa; Milwaukee, Wisconsin; Pittsburgh, Pennsylvania; Portland, Oregon; San Diego, California; Seattle/King County, Washington; Ottawa, Ontario; Toronto, Ontario; and Vancouver, British Columbia.Design: ROC Epistry collected standardized data regarding episode-specific factors, participant demographics, clinical information, pre-hospital interventions and disposition, hospital information, and participant outcome for all out-of-hospital cardiac arrests in the ROC regions. Each ROC site had to ensure capture of all eligible cases within the EMS service areas. Out-of-hospital data were extracted from existing databases whenever possible and augmented with targeted review of EMS reports. Hospital data were abstracted directly from the hospital file in most cases. Alternative methods included linkage to death registries and obituaries if the death occurred within 30 days. Sites submitted data using a web-based interface or batch uploads. Participants were not contacted directly.

  Study phs003803

• Whole-genome Sequencing Suggests Mechanisms for 22q11.2 deletion-associated Parkinson’s disease

  Objectives: To investigate disease risk mechanisms of early-onset Parkinson’s disease (PD) associated with the recurrent 22q11.2 deletion, a genetic risk factor for early-onset PD. Methods: In a proof-of-principle study, we used whole-genome sequencing (WGS) to investigate sequence variants in nine adults with 22q11.2DS, three with neuropathologically confirmed early-onset PD and six without PD. Adopting an approach used recently to study schizophrenia in 22q11.2DS, here we tested candidate gene-sets relevant to PD. Results: No mutations common to the cases with PD were found in the intact 22q11.2 region. While all were negative for rare mutations in a gene-set comprising PD disease-causing and risk genes, another candidate gene-set of 1000 genes functionally relevant to PD presented a nominally significant (P=0.03) enrichment of rare putatively damaging missense variants in the PD cases. Polygenic score results, based on common variants associated with PD risk, were non-significantly greater in those with PD. Conclusions: The results of this first-ever pilot study of WGS in PD suggest that the cumulative burden of genome-wide sequence variants may contribute to expression of early-onset PD in the presence of threshold-lowering dosage effects of a 22q11.2 deletion. We found no evidence that expression of PD in 22q11.2DS is mediated by a recessive locus on the intact 22q11.2 chromosome or mutations in known PD genes. These findings offer initial evidence of the potential effects of multiple within-individual rare variants on the expression of PD and the utility of next generation sequencing for studying the etiology of PD.

  Study EGAS00001002275

• WTCCC case-control study for Bipolar Disorder - Combined Controls

  WTCCC genome-wide case-control association study for Bipolar Disorder (BD) using six disease collections together with the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000002

• 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

• Tremelimumab +/- durvalumab in combination with paclitaxel as immune induction in metastatic urothelial cancer: clinical and translational results of the ICRA trial

  DESCRIPTION: New therapeutic strategies for therapy-refractory metastatic urothelial carcinoma (mUC) patients are still needed. In the phase I-II ICRA trial, we evaluated whether paclitaxel plus tremelimumab (T; anti-CTLA-4), with or without durvalumab (D; anti-PD-L1), could induce a tumor response in mUC patients who had already received platinum chemotherapy and immune checkpoint inhibition (ICI). After a dose-escalation safety phase, patients were randomized between three arms: A (n=20 after expansion) paclitaxel plus T750mg (cycles 2-8); B (n=12) paclitaxel plus T300mg (cycle 2) plus D1500mg (cycles 2-13); C (n=12) T750mg (cycles 1-7). The objective response rate in arm A was 26% (88% confidence interval (CI) = [14,36%]) versus 17% (88% CI = [3,42%]) in arm B and 8% (88% CI = [0.3,33%]) in arm C. Grade 3-4 treatment-related adverse events occurred in (A) 45%, (B) 75%, and (C) 25% of patients. Murine experiments showed attenuated tumor outgrowth for paclitaxel plus anti-CTLA-4 compared to monotherapy with either agent. Transcriptomic analyses showed upregulation of inflammation signatures in on-treatment tumor tissue biopsies. This study demonstrated encouraging antitumor activity in therapy-refractory mUC treated with paclitaxel plus high-dose anti-CTLA-4 and suggests immune induction may still be possible after failure to anti-PD-(L)1 therapy. PROJECT GOAL: We aimed to explore both potential biomarkers for response to combination ICB, as well as treatment dynamics to gain a better understanding of the effects of ICB on the urothelial cancer tumor microenvironment (TME).

  Study EGAS50000001574

• Region-specific Transcriptome Analysis of the Human Retina and Retinal Pigment Epithelium (RPE)/Choroid

  Proper spatial differentiation of retinal cell types is necessary for normal human vision. Many retinal diseases, such as Best disease and male germ cell associated kinase (MAK)-associated retinitis pigmentosa, preferentially affect distinct topographic regions of the retina. While much is known about the distribution of cell types in the retina, the distribution of molecular components across the posterior pole of the eye has not been well-studied. To investigate regional difference in molecular composition of ocular tissues, we assessed differential gene expression across the temporal, macular, and nasal retina and retinal pigment epithelium (RPE)/choroid of human eyes using RNA-Seq. RNA from temporal, macular, and nasal retina and RPE/choroid from four human donor eyes was extracted, poly-A selected, fragmented, and sequenced as 100 bp read pairs. Digital read files were mapped to the human genome and analyzed for differential expression using the Tuxedo software suite. Retina and RPE/choroid samples were clearly distinguishable at the transcriptome level. Numerous transcription factors were differentially expressed between regions of the retina and RPE/choroid. Photoreceptor-specific genes were enriched in the peripheral samples, while ganglion cell and amacrine cell genes were enriched in the macula. Within the RPE/choroid, RPE-specific genes were upregulated at the periphery while endothelium associated genes were upregulated in the macula. Consistent with previous studies, BEST1 expression was lower in macular than extramacular regions. The MAK gene was expressed at lower levels in macula than in extramacular regions, but did not exhibit a significant difference between nasal and temporal retina. The regional molecular distinction is greatest between macula and periphery and decreases between different peripheral regions within a tissue. Datasets such as these can be used to prioritize candidate genes for possible involvement in retinal diseases with regional phenotypes. Reprinted from Whitmore, S.S., Wagner, A.H., DeLuca, A.P., Drack, A.V., Stone, E.M., Tucker, B.A., Zeng, S., Braun, T.A., Mullins, R.F., Scheetz, T.E., 2014. Transcriptomic analysis across nasal, temporal, and macular regions of human neural retina and RPE/choroid by RNA-Seq. Experimental Eye Research. Used under Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported license. Additional RNA sequencing was performed on temporal, macular, nasal, inferior, and superior retina from a fifth subject and is included in this dataset. See original publication for details.

  Study phs001151

• Genetic mechanisms of resistance to chemotherapy in breast cancer

  Resistance towards chemotherapy is one of the main causes of treatment failure and deathamong breast cancer patients.The main objective of this project is toidentify genetic mechanisms causing some breast cancer patients not torespond to a particluar type of chemotherapy (epirubicin) while otherpatients respond very well to the same treatment. In the project wewill perform genome / exome sequencing of a selection of breast cancerpatients (n=30). These patients are drawn from a cohort where allpatients have recieved treatment with epirubicin monotherapy before surgical removal of alocally advanced breast tumour, and where all patients have beensubjected to objective evaluation of the response to thetherapy. Subsequent to sequencing, we will analyse the data andcompare with the clinical data for each patient (object response totherapy). The main aim being to identify mutations that are associatedwith resistance to epirubicin. Identification of mutations with strongpredictive value, may have a direct impact on cancer treatment sinceit opens the possibility for genetic testing of a tumour, and desicionon which drug is likely to work best, prior to treatment start.

  Dataset EGAD00001000264

• A Randomized, Double-Blind, Crossover Study of Sodium Phenylbutyrate (Buphenyl) and Low-Dose Arginine (100 mg/kg/day) Compared to High-Dose Arginine (500 mg/kg/day) Alone on Liver Function, Ureagenesis and Subsequent Nitric Oxide Production in Patients with Argininosuccinic Aciduria (ASA)

  Individuals with Urea Cycle Disorders (UCD) cannot remove ammonia, a waste product, from the blood. At present there is little information on the use of sodium phenylbutyrate (Buphenyl&#8482;) in children with argininosuccinic aciduria (ASA). It is hoped that this drug may help lower ammonia and argininosuccinic acid levels in patients with ASA. Through this study we hope to learn whether the use of sodium phenylbutyrate (Buphenyl&#8482;) in patients with ASA, in addition to diet and arginine therapy, will decrease liver damage and the number of periods during which ammonia levels are high. The primary study objective is to determine if the treatment of ASA patients with sodium phenylbutyrate (Buphenyl&#8482;) in conjunction with lowered doses of arginine improves liver function as measured by short-term assessment of synthetic activity and the use of stable isotope tracers to assess ureagenesis and nitric oxide production. Twelve patients with ASA will be studied using a randomized, cross-over design. Medical records will be reviewed to confirm the diagnosis prior to enrollment. Patients will be on the each arm of the study for one week each preceded by a three day washout period. Patients will come to the Baylor College of Medicine General Clinical Research Center in Texas Children&#39;s Hospital for an inpatient hospitalization. This hospitalization is for diet control, clinical evaluation, and stable isotope infusions for measurement of in vivo rates of ureagenesis and nitric oxide production. During the washout periods Buphenyl&#8482; or other alternative route medications, e.g., benzoate, will be discontinued and arginine will be administered at the standard therapeutic dose of 500 mg/kg/day or 10 grams/m2. Following randomization, subjects will be maintained on either high-dose arginine (500 mg/kg/day or 10 grams/m2) alone, or the alternative of low-dose arginine (100 mg/kg/d or 2 grams/m2) along with sodium phenylbutyrate (500 mg/kg/day or 10 grams/m2). For the second week they will be crossed over to the other arm of the study preceded by another three day washout. Previous medications and dietary protein intake (0.6 g/kg/day or current metabolic diet) will be continued during both arms of the study. The two arms may be performed as separate ten-day admissions. The decision to design the study with two arms, high-dose arginine and low-dose arginine/Buphenyl&#8482;, was reached after weighing several considerations. First, the current accepted practice for treatment of ASA is high-dose arginine. Based on metabolic flux studies, we have quantified the effects of this dose of arginine as compared to standard doses of Buphenyl&#8482;/phenylacetate on ureagenesis. Since the study is not designed or intended to address the independent effects of Buphenyl&#8482; as compared to arginine alone, Buphenyl&#8482; was added for safety reasons to accommodate loss of clearance of nitrogen by decreasing the arginine dose. Moreover, based on our experience with recruiting for previous versions of this study, most ASA patients with liver dysfunction are on an alternative route ammonia scavenger medication in addition to arginine. We found that this has in fact become an accepted practice. Hence, when considering study design from both a safety and recruitment perspective, it was most reasonable to design the study to investigate specifically the hypothesis that the production and presence of argininosuccinic acid leads to liver dysfunction. Since both low-dose arginine with Buphenyl&#8482; and high-dose arginine alone lead to a decreased production of argininosuccinic acid, and both are currently accepted therapies in ASA and UCDs in general, the need to address their effects distinctly is not being investigated at this time. Sodium phenylbutyrate dosage will be 500 mg/kg/day in patients weighing less than 20kg and 10 g/m2/day in larger patients. Daily dosage will be given in equally divided doses 4 times per day. In order to ensure that the study remains double-blind to investigators, study staff and subjects, the Investigational Pharmacy Service at Texas Children&#39;s Hospital will dispense both the Buphenyl&#8482; and arginine in powder form which is compounded into capsules or will be mixed with syrpalta (up to 5 grams will dissolve in 10cc liquid) and administered orally or through nasogastric or gastrostomy tube. No nasogastric tube should be placed or gastrostomy performed solely for the purpose of inclusion in this study. Because the reported adverse effects of sodium phenylbutyrate include gastritis, participants will be started on a standard dose of ranitidine (Zantac&#8482;), or comparable drug, during both arms of the study.

  Study phs001305

• Epigenome analysis of human trophoblast stem cells

  Trophoblast cells play an essential role in the interactions between the fetus and mother. Mouse trophoblast stem (TS) cells have been derived and used as the best in vitro model for molecular and functional analysis of mouse trophoblast lineages. However, attempts to derive human TS cells have so far been unsuccessful. In this study, we derived human TS cells from human blastocysts. Epigenome analysis revealed that the human TS cells maintained epigenome profiles similar to those of primary trophoblast cells. JGA submission accessions: JGA000122,JGA00000000122

  Study JGAS000112

• Center for Common Disease Genomics [CCDG] - Inflammatory Bowel Disease (IBD) - Global Microbiome Conservancy Host Exomes

  The human body is a complex ecosystem, hosting tens of billions of bacteria, primarily in the gut. This community, known as the &#39;gut microbiome&#39;, is vital to human health, affecting functions ranging from metabolism, immunity, and development, to behavior. Conversely, reduced microbiome diversity and other imbalances of the gut community (dysbiosis) are associated with many diseases of the industrialized world, such as metabolic syndrome, asthma, and inflammatory bowel diseases among others. Microbiome-based interventions thus hold the potential to revolutionize our understanding of, and therapeutic approaches to, many aspects of human health and disease. Despite many advances, current understanding of the human microbiome is largely limited to majority ethnic groups in industrialized nations, and does not reflect the full diversity of human commensal microbiota. In addition to the scientific ramifications of minority underrepresentation, there are significant translational and ethical implications as well: First, failing to capture the full diversity of healthy human microbiota may limit our ability to understand and generate effective therapeutics for many microbiome-associated diseases. Second, underrepresented groups are less likely to benefit from microbiome-based medical advances tailored to well-studied populations, propagating healthcare inequities. The window of opportunity to characterize human microbiome diversity is closing rapidly. Human gut microbial diversity is diminishing around the globe, due to the spread of Westernized diets and lifestyles, which are associated with reduced microbiome biodiversity. The Global Microbiome Conservancy (GMbC) is a non-profit collaboration between scientists and communities around the world that aims to 1) preserve the full biodiversity of the human gut microbiome, 2) characterize its evolution across populations and host lifestyles and 3) investigate its interactions with the human host. We are collecting gut microbiome and human DNA samples from diverse populations around the world, from isolated groups to urbanized populations, to culture and study this essential biodiversity and to preserve it in a living "seed bank" as a long-term safeguard against future extinctions. The National Human Genome Research Institute (NHGRI) has funded a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Called the Centers for Common Disease Genomics (CCDG), this initiative will explore a range of diseases with the ultimate goal of: Undertaking variant discovery for enough different examples of disease architectures and study designs to better understand the general principles of the genomic architecture underlying common, complex inherited diseases. Understanding how best to design rare variant studies for common disease. Developing resources, informatics tools, and innovative approaches and technologies for multiple disease research communities and the wider biomedical research community. The initial focus of the CCDGs will be in cardiovascular disease (early-onset coronary artery disease, atrial fibrillation, hemorrhagic stroke), neuropsychiatric disease (epilepsy, autism), and autoimmune/inflammatory disease (type 1 diabetes, inflammatory bowel disease). The Broad Institute is one of four selected CCDG project centers. Both exome and genotyping information of GMbC participants will help understanding how recruited human populations are structured and genetically related. This human genetic structure will be analyzed in light of gut microbiome compositional and genomic differences to illuminate associations between specific microbiome traits and human groups and the evolutionary processes involved in the co-evolution of human hosts and their gut microbiome. It will also provide variant information for critical genes shaping the composition of microbiomes, such as genes involved in innate and adaptive immunity (e.g. antimicrobial peptides) or in the regulation of the immune response (e.g. Nod2). Association studies between specific variants in these genes and microbiome features will be performed, which will then be validated with in vitro and in vivo experiments. Human data from GMbC cohorts will also increase the genetic diversity of human populations, providing additional variant information for many susceptible loci that were found to be associated with Crohn&#39;s disease and ulcerative colitis. The whole genome sequencing data generated is comprised of samples from diverse and indigenous populations. Raw sequencing data, metadata, vcf and phenotype data at the individual level for a subset of the cohort&#39;s samples are available at https://anvilproject.org/data. For questions about availability, contact help@lists.anvilproject.org. Microbiome data for the samples sequenced in this study can be found in phs002235 Global Microbiome Conservancy Sequence Data.

  Study phs002205

• Security Overview

  Security Overview The European Genome-phenome Archive (EGA) houses consented human data under controlled access. Access decisions are handled by the relevant Data Access Committee (DAC), which autonomously manages requests through the DAC Portal. This document provides an overview of EGA’s practices in ensuring the security of data stored at EGA. As security is a prime concern of the EGA, the EGA is a member of the Global Alliance for Genomics and Health (GA4GH) Data Security work stream. The EGA contributes and helps develop the recommendations outlined the GA4GH Security Technology Infrastructure document, which defines guidelines, best practices, and standards for building and operating an infrastructure that promotes responsible data sharing in accordance with the GA4GH Privacy and Security Policy. Explore the EGA dataflow to gain deeper insights! Accessing data in the EGA involves several steps. First, users need to create an EGA account. Once logged in, they can request access to data controlled by a DAC through the EGA website (see documentation). The DAC oversees these requests through the DAC Portal, and if approved, grants the necessary permissions to the user's EGA account, allowing them to access and download all relevant data and metadata for the requested dataset(s). The key points of EGA security strategy are: 1 Regular Risk Assessment The EGA regularly identifies and assesses risk related to the following: Breach of confidentiality,Breach of privacy or autonomy,Malicious or accidental corruption or destruction of data archived at EGA,Disruption of services provided by the EGA. 2 Risk mitigation The EGA implements and maintains safeguards to minimise the risks identified above in accordance with the 6 control objectives listed in Appendix 1 and outlined in the GA4GH Security and Infrastructure document.If a breach is discovered, the EGA applies a defined protocol to minimise damage. 3 Identity and authorisation management The EGA authenticates the identity of individuals or software accessing controlled access data held at the EGA.The EGA ensures an appropriate level of assurance (LoA) is applied to the identity consistent with the risk associated with that individual, such as multi-factor authentication for DACs.The EGA provides the minimum access rights and privileges consistent with the user’s identity, allowing access consistent with the GA4GH Privacy and Security Policy, as determined by the appropriate DAC. 4 Audit Logs The EGA maintains a set of logs recording: Changes to user access rights,Data access requests,Resource usage. 5 Cryptography, communication security, and data integrity The EGA ensures data transmission integrity using a hash function.All data transmitted to or from the EGA is end-to-end encrypted.All data at EGA is stored using strong encryption.Encryption keys are not stored in the same system as the encrypted data.All data archived at EGA must be accompanied by a signed submission statement ensuring appropriate consent or ethical approval has been obtained, and is in accordance with all applicable laws and regulations. The EGA has a defined protocol defining the response in the event of a security breach, and is continuing to work with the GA4GH Data Security Work Stream to help define best practice and associated standards for breach responses. Appendix 1 GA4GH Control Objectives Control Objective 1: Implement technology safeguards to minimise the risk of unauthorised access, use, or disclosure of confidential and private data.Control Objective 2: Implement technology safeguards to minimise the risk of discovery, access, and use of individuals’ clinical and genomic data, and individual identities, other than as authorised by applicable jurisdictional law, institutional policy, and individual consents.Control Objective 3: Implement technology safeguards to minimise the risk of accidental or malicious corruption or destruction of data.Control Objective 4: Implement technology safeguards to minimise the risk of disruption, degradation, and interruption of services enabling access to data.Control Objective 5: Implement technology safeguards to minimise the risk of potential security attacks and misuse of authorised accesses and privileges.Control Objective 6: Implement technology safeguards to promptly detect the failure to attain the above control objectives and to respond with proper countermeasures.Appendix 2Refer to the document below to learn more about EGA long-term data preservation policy and procedures at EMBL-EBI.Long-term data preservation

  Documentation about/security

• WTCCC case-control study for Coronary Artery Disease, Hypertension, T2D - combined cases

  WTCCC genome-wide case-control association study using the cardiovascular disease CAD, HT and T2D as combined case collection and the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000005

• Genome Studies in Hereditary Spastic Paraplegia

  Next-generation sequencing technology is opening up new opportunities to rethink the way we identify disease causing genetic variation. An early application, whole exome sequencing, has now been established by a small number of research labs, including ours. Exome sequencing allows obtaining a near complete set of protein coding genomic variation in single individuals for less than $5,000. Promising targets for exome sequencing studies are Mendelian diseases, such as hereditary spastic paraplegias (HSP). HSP comprise a genetically very heterogeneous set of neurological disorders with currently 39 different HSP chromosomal loci being reported; yet, the identified genes explain only 60% of the genetic effect at best. Traditional methods of gene identification require linkage analysis of large families, but face increasing difficulties to identify such extended pedigrees for rare HSP forms. However, the innovative approach described in this application will overcome some of these limitations and utilize relatively small pedigrees for highly effective gene identification. We will apply exome sequencing, which will characterize all coding changes and flanking exonic variation in two individuals of a family. We have developed a multi-tiered strategy to reduce the number of identified novel variants to the very causative change in an individual family. We propose to study at least 60 HSP families, which are too small to yield conclusive results with linkage analysis. If the developing technology permits we will consider a larger sample or perform whole genome sequencing. Beyond the important benefit to genetics of HSP, this study will allow us to further establish this new method, which will benefit a large range of additional disease studies.

  Study phs001080

• Inflammatory Bowel Disease Exome Sequencing Study

  The Broad Institute and Massachusetts General Hospital (MGH) are launching a new initiative to perform large-scale exome sequencing in inflammatory bowel disease (Crohn&#39;s disease and ulcerative colitis). Given the considerable unmet therapeutic need in inflammatory bowel disease (IBD), the recent emergence of rapid and efficient genome sequencing technologies and the compelling evidence for the role of genetics in these disorders have motivated the founding of a collaborative sequencing effort geared toward the discovery of high-impact genetic variants influencing IBD risk that can serve as guides to future therapeutic development and diagnostic tools. The initiative will be directed by experienced IBD researchers from MGH and the Broad Institute but aims to develop a collaborative exome sequencing network that will partner with researchers worldwide. Two large pilot exome sequencing projects are being launched immediately as part of this initiative based on established genetic study designs that enrich for the discovery of rare, high-impact risk and protective variants. 1) Early-onset pediatric IBD: a major focus of the work will surround full-exome sequencing of the earliest-onset childhood IBD cases. It has long been recognized in many diseases that penetrant genetic risk factors are much more likely to be found in cases with unusually early onset. The Broad Institute has completed more than 50,000 exomes in the past two years; and their technical expertise in generating and processing such sequencing data, along with population genetic variation patterns from these experiments, will provide a foundation for obtaining the best outcome in the interpretation of these cases. Samples with IBD onset before 6 years of age - and in some cases going up to age 10 - collected by IBD researchers around the world are welcomed for inclusion in this study. 2) Adult-onset IBD case-control study: Genetic mapping has provided dramatic insights into IBD pathogenesis in recent years, but a substantial amount of heritability - in particular the role of strong-acting rare mutations - is yet to be elucidated. To deliver those insights, IBD cases with an unusually low burden of known genetic risk factors (particularly emphasizing those with positive family history and/or from isolated or enriched populations) will be contrasted with population controls that have an extremely high burden of known IBD risk factors, enhancing discovery of critical protective variants that may provide the best clues for therapeutic development. This project will also be initiated as an international collaboration, particularly among researchers with sample sets with Immunochip genotyping that will enable the immediate genetic identification of these enriched target populations. This project will be supported by the NHGRI Large-Scale Sequencing Program, with all generated data made publicly available to the research community through standard NIH databases.

  Study phs001076

• Somatic copy number alteration and fragmentation analysis in circulating tumor DNA for cancer screening and treatment monitoring in colorectal cancer patients

  Background: Analysis of circulating free DNA (cfDNA) is a promising tool for personalized management of colorectal cancer (CRC) patients. Untargeted cfDNA analysis using whole-genome sequencing (WGS) does not need a priori knowledge of the patient´s mutation profile. Methods: Here we established LIquid biopsy Fragmentation, Epigenetic signature and Copy Number Alteration analysis (LIFE-CNA) using WGS with ~6x coverage for detection of circulating tumor DNA (ctDNA) in CRC patients as a marker for CRC detection and monitoring. Results: We describe the analytical validity and a clinical proof-of-concept of LIFE-CNA using a total of 259 plasma samples collected from 50 patients with stage I-IV CRC and 61 healthy controls. To reliably distinguish CRC patients from healthy controls, we determined cutoffs for the detection of ctDNA based on global and regional cfDNA fragmentation patterns, transcriptionally active chromatin sites, and SCNAs. We further combined global and regional fragmentation pattern into a machine learning classifier to accurately predict ctDNA for cancer detection. By following individual patients throughout their course of disease, we show that LIFE-CNA enables the reliable prediction of response or resistance to treatment up to 3.5 months before commonly used CEA. Conclusion: In summary, we developed and validated a sensitive and cost-effective method for untargeted ctDNA detection at diagnosis as well as for treatment monitoring of all CRC patients based on genetic as well as non-genetic tumor-specific cfDNA features. Thus, once sensitivity and specificity have been externally validated, LIFE-CNA has the potential to be implemented into clinical practice. To the best of our knowledge, this is the first study to consider multiple genetic and non-genetic cfDNA features in combination with ML classifiers and to evaluate their potential in both cancer detection and treatment monitoring.

  Study EGAS00001006490

• Paired-end Whole Exome-seq analysis of the 3D evolution of glioma cell populations. Part 2.

  Dataset contains paired-end Whole Exome sequencing data from 257 glioma samples from 28 patients. 26 normal blood samples are also included.

  Dataset EGAD00001009496

• Characterization of mutational signatures in human cancer cell lines reveals episodic APOBEC mutagenesis

  Multiple signatures of somatic mutations have been identified in human cancer genomes. To investigate whether mutational signatures continue to be generated, and if so their temporal patterns of activity, subsets of cell lines were cultured in vitro for extended periods and subjected to single cell cloning and whole genome or exome sequencing or directly to single cell whole genome sequencing. As expected, signatures of past exogenous exposures, such as tobacco smoke and ultraviolet light, were not generated in vitro. In contrast, signatures of normal and defective DNA repair and replication continued to be generated at essentially constant mutation rates. Signatures of APOBEC cytidine deaminase DNA-editing activity exhibited a distinctive pattern with substantial fluctuations in mutation rate over time and episodic bursts of mutations. The initiating factors for these bursts are unclear although retrotransposon mobilisation may play a role. This cell line set now constitutes a comprehensive resource of live experimental models of mutational processes of both known and unknown aetiologies potentially retaining the patterns of activity and regulatory influences operative in human cells in vivo.

  Dataset EGAD00001004202

• Providing safe access to sensitive human data across borders: Federated EGA becomes a reality

  Enabling discovery and access to sensitive data across national boundaries is vital for improving human health. It enables more powerful and efficient research by increasing the volume and diversity of data available for analysis. It allows us to better understand the causes of diseases – cancer, rare diseases, infectious diseases like COVID-19 – and develop new medicines and treatments. Sensitive human omics data are typically generated by research initiatives and shared using specialist repositories which provide services for data submission, discovery, and access. The EGA is one such repository. Established in 2008 at EMBL’s European Bioinformatics Institute (EMBL-EBI) in the UK, since 2012 the EGA (“Central EGA”) has been jointly managed by EMBL-EBI and the Centre for Genomic Regulation (CRG) in Spain. Many countries have emerging personalised medicine programmes which generate data from national initiatives. These programmes are driving a transition in human genomics from being research-driven to receiving funding through healthcare. Data generated in a clinical context are subject to stricter governance than research data and must follow national data protection legislation. To solve these challenges, the Federated EGA provides a network of connected resources to enable transnational discovery of and access to human omics data for research, while also respecting jurisdictional data protection regulations. In this way, the Federated EGA infrastructure supports the goals of European initiatives such as the 1+ Million Genomes initiative (1+MG), the European Health Data Space, and a number of EU-funded 1+MG implementation projects including Beyond 1 Million Genomes. The Federated EGA is made up of “Nodes” – typically nationally funded and operated – which store and manage data locally while allowing global discovery within the Federated EGA network. Since 2016, multiple parallel efforts, supported by ELIXIR and other transnational and national initiatives, have created technical and legal frameworks for establishing the Federated EGA. In 2022, the first five Nodes – Finland, Germany, Norway, Spain, and Sweden – officially joined the Federated EGA by signing Federated EGA Collaboration Agreements with Central EGA. The Finnish FEGA Node is operated by CSC - IT Center for Science and provides data management services according to national laws and the requirements of the EU General Data Protection Regulation (GDPR). These services provide tools and support for the whole life-cycle of sensitive research data from collating to analysis, publication, and authorised re-use. The development of the services has been a joint effort with the other Nordic nodes within NeIC's Tryggve and Heilsa projects, and funded by Finnish Ministry of Education and Culture and projects coordinated by ELIXIR Finland. Read more about Finnish FEGA signing. The German Human Genome-Phenome Archive (GHGA) strives to provide a national infrastructure as well as an ethical and legal framework that balances FAIR omics data usage and data protection needs for Germany. As a Germany-wide consortium funded by the German Research Foundation under the umbrella of the NFDI association, GHGA combines the expertise of 21 universities and research institutions to form a federated national infrastructure. Read more about GHGA signing. The German Human Genome-Phenome Archive (GHGA) strives to provide a national infrastructure as well as an ethical and legal framework that balances FAIR omics data usage and data protection needs for Germany. As a Germany-wide consortium funded by the German Research Foundation under the umbrella of the NFDI association, GHGA combines the expertise of 21 universities and research institutions to form a federated national infrastructure. Read more about GHGA signing. In Norway, a key component of the infrastructure is the services of The Sensitive Data Service (TSD) offered by USIT at University of Oslo. The Federated EGA Norway Node is developed by ELIXIR Norway and operated by the University of Oslo as the responsible legal entity. Core software modules are developed jointly with the other Nordic nodes in the NeIC Tryggve and Heilsa projects. Read more about FEGA Norway signing. The Spanish FEGA (es-FEGA) is a national service for storing sensitive biomedical data in Spain. Supported by the Spanish Institute of Bioinformatics (INB) in collaboration with Central EGA, sensitive research datasets are primarily hosted at the Barcelona Supercomputing Centre facilities. The Swedish Sensitive Data Archive is a secure data archive and sharing platform for sensitive datasets. It was developed by the National Bioinformatics Infrastructure Sweden (NBIS) in collaboration with other Nordic ELIXIR Nodes through the Tryggve and Heilsa projects funded by NeIC and coordinated with Central EGA through ELIXIR. Read more about the Swedish Node signing. The Swedish Sensitive Data Archive is a secure data archive and sharing platform for sensitive datasets. It was developed by the National Bioinformatics Infrastructure Sweden (NBIS) in collaboration with other Nordic ELIXIR Nodes through the Tryggve and Heilsa projects funded by NeIC and coordinated with Central EGA through ELIXIR. Read more about the Swedish Node signing. By providing a solution for secure and efficient management of human omics data, the Federated EGA aims to foster data reuse, enable reproducibility, accelerate biomedical research, and improve human health. Find out more Interested in setting up your own Federated EGA Node? Check out the FEGA Onboarding Knowledge Base for more information. The ELIXIR Federated Human Data Community is a great entry point for anyone interested in learning more about the Federated EGA. You can: Join the ELIXIR Federated Human Data Community mailing list (select “Human Data”) Attend the ELIXIR Federated Human Data Community calls

  Blog safe-access-to-sensitive-human-data-federated-ega

• FEGA and European GDI: working together to improve human health

  The Federated EGA is a global resource for discovery of and access to sensitive human omics and associated data consented for secondary use, through a network of human data repositories to accelerate biomedical research and improve human health. The Federated EGA network was launched in September 2022 with five inaugural nodes, and since 2023 seven operational nodes can share data across national borders in adherence to European and national laws. A few weeks after FEGA's official launch, in November 2022, the European Genomic Data Infrastructure (GDI) project was kicked-off . This European Commission co-funded project, coordinated by ELIXIR, is aimed to deliver federated, sustainable and secure data infrastructure to access genomic and related phenotypic and clinical data across Europe. This project supports the aim of the 1+MG initiative (25 EU countries, Norway and UK) to enable personalised medicine and health through a shared framework and infrastructure for securely accessing and integrating high quality genomic data and other health data across borders.1+MG will be an integral component of the European Health Data Space (EHDS) for secondary use (Healthdata@EU) as an authorised participant. How are Federated EGA and GDI similar? Given their shared visions, the Federated EGA and European GDI networks have a lot in common. To begin, they share the same overall goal of establishing networks of “nodes” that host sensitive human data within a jurisdiction and connecting these nodes in a global network to support data discovery and promote human genome data access for research and healthcare. FEGA and GDI are both initially focused on enabling access to human genomic data, while FEGA ambition is to expand the scope to clinical research data and other omics data in the future. FEGA and GDI are both built on open and interoperable software solutions, a subset of which are based on the LocalEGA components. FEGA and GDI implementation solutions are based on international community standards, for example those developed by the Global Alliance for Genomics and Health, which contributes to making them interoperable. Both FEGA and GDI allow for the nodes to make use of any solution that is fully compatible. As illustrated in Figure 1, a final key point is the significant overlap of institutions involved in envisioning and operating FEGA and GDI nodes, with the clear wish to keep them interoperable in the future. What distinguishes Federated EGA from GDI? Despite being largely similar, there are some differences between the FEGA and GDI networks, which we aim to clarify in this post. The first difference is the governance model that the nodes will operate to comply with national laws and GDPR. In the FEGA network, nodes have taken inspiration from the EGA data access model, where the infrastructure is a data processor of the hosted data and data controllership remains with the originating Data Access Committees (i.e. Data controllers) for each dataset. On the other hand, in the GDI network the controllership of datasets will be transferred to a 1+MG European Digital Infrastructure Consortium (EDIC) legal entity created by the Member States (MS), who will make data access decisions, with data holders having veto powers for their datasets. Importantly, FEGA nodes have the flexibility to choose another model to fit with their data protection framework, including becoming data controllers for their datasets. The second difference is the inclusion criteria for data. While FEGA nodes are designed to accept almost any type of omics data in need of control access (e.g. genomics, transcriptomics, genotyping, single cells sequencing, patient-tracked metagenomics), GDI nodes are initially, but not only, focused on accepting whole genome and exome sequencing data and affiliated data from sources such as (i) the Genome of Europe use case of the 1+MG initiative which specifically aims to fulfil the mission of building “a European network of national genomic reference cohorts of at least 500,000 citizens”) (ii) data collection of other types of genomic data identified by countries through the 1+MG dashboard and (iii) genomic data coming from data holders which would need to fulfil EHDS requirements. The third difference is the maturity of the software stacks. The FEGA network provides a set of software for data and metadata submission, storage, permissions management, and file distribution (the LocalEGA package). GDI is building a complete set of open source reference for the five functionalities covering the full data life cycle (a few more compared to the LocalEGA) including federated processing (analytics, AI/ML), which is still under active development. Notably, one of the GDI functionalities - storage and interfaces - can be satisfied by using the LocalEGA storage solution, highlighting the ability of FEGA and GDI to be interoperable. In both FEGA and GDI, nodes are allowed to use alternative solutions as long as they are fully interoperable with the networks. Figure 1 provides a simple overview of these described commonalities and differences. Figure1: schematic overview of the main commonalities and difference among a FEGA and a GDI node Can the same institute run a FEGA and a GDI node at the same time? The answer is Yes! We believe this is entirely possible and encouraged. As long as 1+MG requirements are continuously fulfilled in the implementation. The same trained personnel could operate the infrastructure and leverage the same national funding to run a FEGA and a GDI node. Several European nodes, especially GDI vanguard nodes like Norway, Sweden, Finland and Spain are following this model. The idea is that a lot of the work can be reused, given the overlapping scope and the interoperable technology. Thus, the hosted datasets can be discovered via the two catalogues, perhaps accessible under the same or different governance models. From a FEGA node perspective, the GDI datasets could simply be a subset of the datasets hosted in the FEGA node, which have their specific governance as any other. What's next? So, the amazing teams of people building the Federated EGA network and the European GDI network are working together to create infrastructures able to provide secure access to human genomic and associated data around Europe. Because we all know how much human genomics can improve healthcare and precision medicine. And we all want to collaborate to make it happen. This article has been reviewed collectively by members of the EGA and the GDI coordination team.

  Blog fega-and-gdi

• Beta-Blocker Evaluation in Survival Trial (BEST-BioLINCC)

  Data Access NOTE: Please refer to the &#8220;Authorized Access&#8221; section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives The Beta-Blocker Evaluation of Survival Trial was designed to determine whether bucindolol hydrochloride- a nonselective beta-adrenergic blocker and mild vasodilator- would reduce the rate of death from any cause among patients with advanced heart failure and to assess its effects in various subgroups defined by ethnic background and demographic criteria- specifically women and members of minority groups. Background Although beta-adrenergic-receptor antagonists reduce morbidity and Mortality in participants with mild-to-moderate chronic heart failure, their effort on survival in participants with more advanced heart failure is unknown. Participants There were 2,708 participants. Conclusions Bucindolol resulted in no significant overall survival benefit. (Krause-Steinrauf et al., 2001, PMID: 11386264).

  Study phs003730

• 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.

  Study phs001422

• Characterization_of_individual_foci_of_multicentric_multifocal_breast_cancer_using_targeted_next_generation_sequencing

  Multifocality or multicentricity in breast cancer may be defined as the presence of two or more tumor foci within a single quadrant of the breast or within different quadrants of the same breast, respectively. This original classification of the breast cancer as multicentric or multifocal was based on the assumption that cancers arising in the same quadrant were more likely to arise from the same ductal structures than those occurring in separate areas of the breast. The problem with these definitions is that the “quadrants” of the breast are arbitrary external designations, as no internal boundaries do exist. This project will therefore focus both on synchronous multifocal and multicentric tumors. The incidence of multifocal and multicentric breast cancers was reported to be between 13 and 75% depending on the definition used, the extent of the pathologic sampling of the breast and whether in situ disease is considered evidence of multicentricity (1). Although this incidence is variable, those figures show that it is a frequent phenomenon. Multiple (multifocal/multicentric) breast carcinomas, especially when occurring in the same breast, represent a real challenge for both pathologists and clinicians in terms of identifying the cellular origin and the best therapeutic management of the cancer. Multifocality or multicentricity has been associated with a number of more aggressive features including an increased rate of regional lymph node metastases and adverse patient outcome when compared with unifocal tumors (2-3), and a possible increased risk of local recurrence following breast conserving surgery (4). For the moment, the literature is divided on whether there is a corresponding impact on survival outcomes. Today, the current convention to stage and to treat multifocal and multicentric tumors is the classical tumor-node-metastasis (TNM) staging guidelines with which tumor size is assessed by the largest tumor focus without taking other foci of disease into consideration. If some papers, as the recent one from Lynch and colleagues, support the current staging convention (3), others, however, as Boyages et al. suggested that aggregate size and not the size of the largest lesion should be considered in order to refine the prognostic assessment of those tumors (5). On the top of that, the question whether multifocal/multicentric carcinomas are due to the spread of a single carcinoma throughout the breast or is due to multiple carcinomas arising simultaneously has been a matter of debate. Some studies suggested that multifocal breast cancer may result from either intramammary spread from a single primary tumor or multiple synchronous primary tumors; whereas others suggest that multiple breast carcinomas always arise from the same clone (6-8). Recently, Pietri and colleagues analyzed the biological characterization of a series of 113 multifocal/multicentric breast cancers (8) which were diagnosed over a 5-year period. The expression of estrogen (ER) and progesterone (PgR) receptors, Ki-67 proliferative index, expression of HER2 and tumor grading were prospectively determined in each tumor focus, and mismatches among foci were recorded. Mismatches in ER status were present in 5 (4.4%) cases and PgR in 18 (15.9%) cases. Mismatches in tumor grading were present in 21 cases (18.6%), proliferative index (Ki-67) in 17 (15%) cases and HER2 status in 11 (9.7%) cases. Interestingly, this heterogeneity among foci has led to 14 (12.4%) patients receiving different adjuvant treatments compared with what would have been indicated if we had only taken into account the biologic status of the primary tumor. This study therefore showed that differences in biological characteristics of multifocal/multicentric lesions play a crucial role in the adjuvant treatment decision making process. In this study, we will concentrate on a larger series of patients with multifocal invasive ductal breast cancer lesions. We aim at: 1. Evaluating the incidence of multifocality according to the different breast cancer molecular subtypes (ER-/HER2-, HER2+, ER+/HER2-). 2. Evaluating the incidence of multifocality in patients with hereditary breast cancer disease (presence of germline BRCA1 or BRCA2 mutations). Moreover, we would like to investigate if multifocal lesions with BRCA1 or BRCA2 mutations exhibit a characteristic combination of substitution mutation signatures and a distinctive profile of deletions as demonstrated recently by Nik-Zainal and colleagues (9). 3. Correlating multifocality with clinical information in order to define its influence on patients’ survival (DFS and OS). 4. Carrying high coverage targeted gene sequencing of driver cancer genes and genes whose mutation is of therapeutic importance in order to compare clinically-relevant genetic differences between several multifocal breast cancer lesions. 5. Evaluating the impact of the distance between the different lesions on the clinical outcome but also on the genetic differences. 6. Comparing gene expression patterns between several multifocal breast cancer lesions and correlate them with the results of the targeted genes screen. 7. Characterizing the genomic and transcriptomic status of cancer related genes in metastatic lesions (local recurrence, positive lymph node or distant metastatic sites) from the same multifocal invasive ductal breast cancer patients in order to evaluate the consequence of genomic and transcriptomic heterogeneity of multifocal lesions on metastatic lesions. Multiple (multifocal/multicentric) breast carcinomas, especially when occurring in the same breast, represent a real challenge for both pathologists and clinicians in terms of identifying the cellular origin and the best therapeutic choice. This project has the potential to identify genetic/transcriptomic differences existing between several lesions constituting multifocal breast cancers, which in the routine clinical practice are usually considered to be homogeneous among them. We foresee validating significant results in a larger series of patients and this, in turn, could have a remarkable impact on the treatment and clinical management of multifocal breast cancers. Indeed, we hope to provide some evidence whether or not each focus matters in multifocal and multicentric breast cancer to define the adequate therapeutic approach, especially in the context of targeted therapies. The work to be done at Sanger will be target gene screen pooling of 1400 samples.

  Study EGAS00001000407

• National Eye Institute (NEI) Age-Related Eye Disease Study (AREDS)

  The Age-Related Eye Disease Study (AREDS) was initially designed as a long-term multi-center, prospective study of the clinical course of age-related macular degeneration (AMD) and age-related cataract. In addition to collecting natural history data, AREDS included a clinical trial of high-dose vitamin and mineral supplements for AMD and a clinical trial of high-dose vitamin supplements for cataract. AREDS participants were 55 to 80 years of age at enrollment and had to be free of any illness or condition that would make long-term follow-up or compliance with study medications unlikely or difficult. On the basis of fundus photographs graded by a central reading center, best-corrected visual acuity and ophthalmologic evaluations, 4,757 participants were enrolled in one of several AMD categories, including persons with no AMD. The clinical trials for AMD and cataract were conducted concurrently. AREDS participants were followed on the clinical trials for a median time of 6.5 years. Subsequent to the conclusion of the clinical trials, participants were followed for an additional 5 years and natural history data were collected. The AREDS research design is detailed in AREDS Report 1. AREDS Report 8 contains the mainline results from the AMD trial; AREDS Report 9 contains the results of the cataract trial. Blood samples were also collected from 3,700+ AREDS participants for genetic research. Genetic samples from 600 AREDS participants (200 controls, 200 Neovascular AMD cases, and 200 Geographic Atrophy cases) were selected using data available in March 2005 and then were evaluated with a genome-wide scan. These data, as well as selected phenotypic data, were made available in the dbGaP. DNA from AREDS participants, which is currently being stored in the AREDS Genetic Repository, is available for research purposes. However, not all of the 3,700+ AREDS participants who submitted a blood sample currently have DNA available. In addition to including the data from the genome-wide scan on the 600 original samples, this second version of the AREDS dbGaP database provides a comprehensive set of data tables with extensive clinical information collected for the 4,757 participants who participated in AREDS. The tables include information collected at enrollment/baseline, during study follow-up, fundus and lens pathology, nutritional estimates, quality of life measures and measures of morbidity and mortality. In November 2010, over 72,000 high quality fundus and lens photographs of 595 AREDS participants (of the original 600 selected for the genome-wide scan) were made available in the AREDS dbGaP. In addition to the genome-wide scan data, the fundus and lens grading data for these participants are also available through the AREDS dbGaP. Details about the ocular photographs that are available may be found in the document "Age-Related Eye Disease Study (AREDS) Ocular Photographs". In January 2012, a measure of daily sunlight exposure was added in a separate &#34;sunlight&#34; table. Furthermore, the &#34;followup&#34; table has been revised. The visual acuity for the right eye was inadvertently missing at odd-numbered visits (01, 03, 05, etc.). This data is now part of the table. In February 2014 over 134,500 high-quality fundus photographs (macular field F2) of 4613 AREDS participants were added to the existing AREDS dbGaP resource. The AREDS dbGaP image archive already contains over 72,000 high quality fundus and lens photographs of 595 AREDS participants for whom dbGaP-accessible genotype data exist. Information about the available ocular photographs found in the document "Age-Related Eye Disease Study (AREDS) Ocular Photographs" has been updated with an addendum. It is hoped that this resource will better help researchers understand two important diseases that affect an aging population. These data may be applied to examination and inference on genetic and genetic-environmental bases for age-related diseases of public health significance and may also help elucidate the clinical course of both conditions, generate hypotheses, and aid in the design of clinical trials of preventive interventions. Definitions of Final AMD Phenotype Categories Please see phd001138.1 for a detailed description of how AREDS participants&#39; final AMD phenotype was categorized. User&#39;s Guide for AREDS Phenotype Data A detailed User&#39;s Guide for the AREDS phenotype data is available. This User&#39;s Guide is meant to be a comprehensive document which explains the complexities of the AREDS data. It is recommended that all researchers using AREDS phenotype data make use of this User&#39;s Guide.

  Study phs000001

• Genomic consequences of aberrant DNA repair mechanisms stratify ovarian cancer histotypes

  Aberrant DNA repair processes are a hallmark of human tumours. How these deficiencies variously impact the genomes of ovarian cancer between and within histotypes remains unknown. We studied the whole genome pointmutation and structural variation patterns of 133 tumours (59 high grade serous (HGSC), 35 clear cell (CCOC), 29 endometrioid (ENOC), and 10 adult granulosa cell tumours (GCT)) as a substrate for class discovery in ovarian cancer. Ab-initio clustering of integrated point mutation and structural variation signatures revealed seven novel subgroups, comprising between and within histotype stratification. Prevalence of fold-back inversions (FBI) co-localised with high level amplification events divided HGSC into two prognostically significant subgroups. This finding was recapitulated in two additional independent cohorts (total n=576 cases), and transcended gene based mutation status and gene expression as prognostically relevant features of HGSC. CCOC were divided into one group harbouring a signature reflective of active genome editing via APOBEC enzymes (26%) and a complementary group with an age-relatedmutational signature. ENOC were divided intomicrosatellite instable (MSI) cases (28%) with a distinctmismatch repairmutation signature and an outlying mutation rate, with the remainder of cases distributed amongst the remaining six groups. We suggest the FBI, MSI, and APOBEC groups represent biologic strata that could direct treatment strategies. Taken together, our work establishes the efficacy of the somatic genome as a biomarker to stratify ovarian cancers, simultaneously identifying patients that may benefit from emerging therapeutics and distinct subgroups within classic ovarian cancer histotypes.

  Study EGAS00001002390

• Study on the proliferation history of colorectal adenomas

  Mismatch repair (MMR) deficient colorectal adenomas are composed of transformed cells that descend from a common founder and progressively accumulate genomic alterations but their proliferation history is still largely unknown. Here we rebuilt the proliferation history of four MMR deficient colorectal adenomas from male individuals by deep sequencing the X chromosome and mapping the somatic mutations that were progressively acquired during tumor growth. We developed a novel method to call high and low frequency mutations, to cluster them according to their frequencies and rebuild the proliferation trees directly from these mutation clusters using a recursive algorithm. The trees of all four lesions were formed of a dominant subclone that coexisted with other genetically heterogeneous subpopulations of cells. Despite this similar hierarchical organization, however, the growth dynamics varied among and within tumors, likely depending on a combination of tumor-specific genetic and environmental factors. Our study provides insights into the biological properties of individual MMR deficient colorectal adenomas that may influence their growth and also the response to therapy. Extended to other solid tumors, our approach could inform on the mechanisms of cancer progression, thus providing insight into the best choice of cancer treatment methods.

  Study EGAS00001000883

• 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