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• Study of tumor RNA expression differences between treated and untreated PitNET patients

  The goal of the study is to evaluate response of PitNET to drug therapy before surgery. Patients with and without drug therapy are compared in RNA level. The RNA is extracted from surgery material, sequenced and deferentially expressed genes (DEG) determined.

  Study EGAS00001004736

• RNA sequencing of multiple myeloma identifies genes dysregulated by structural variants.

  Multiple myeloma is a disease of structural changes brought about by copy number abnormalities and translocations. Many of these changes result in super-enhancers being placed next to key oncogenes. Here, we have investigated which genes are commonly dysregulated by these changes.

  Study EGAS00001003411

• Whole-Transcriptomic Profiling of Sorted Human Renal Cell Carcinoma Immune Populations

  It is poorly understood how the tumor immune micro-environment influences disease progression in renal cell carcinoma (RCC). Here we performed whole-transcriptomic profiling of immune cell populations which were derived from RCC patients representing distinct flow-sorted immune lineages.

  Study EGAS00001006593

• Gtag&T single-cell genome and transcriptome data

  This submission contains single-cell genome and transcriptome data that is used for the following manuscript: https://doi.org/10.1101/2023.01.13.521174. All Illumina data deposited here is retrieved from HCC38(BL) cell lines and a melanoma PDX model as described in the paper.

  Study EGAS00001007043

• MCL NGS data

  We have performed a comprehensive and integrative genomic study of mantle cell lymphoma (MCL) to elucidate the features that may determine the different clinical and biological behavior of the two molecular subtypes of this lymphoma, conventional (cMCL) and leukemic non-nodal MCL (nnMCL). This data integrated with epigenomics and transcriptomics has allowed to uncover novel molecular mechanisms in the origin and development of these tumors and provide relevant information to stratify patients in different risk groups.

  Dataset EGAD00001006025

• TTV018 RORC IBD-associated genotype effects on RORgT expression and function in ex vivo T cells (2019-02-15)

  RNA sequencing of peripheral immune cells from patients +/- an IBD risk variant. Peripheral immune cells +/- in vitro test compound treatment. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2019-02-15.

  Dataset EGAD00001004777

• Processed bam files for the whole exome sequencing of primary lung adenocarcinoma samples

  We performed single cell RNA sequencing (scRNA-seq) for 208,506 cells derived from 58 lung adenocarcinomas from 44 patients, which covers primary tumour, lymph node and brain metastases, and pleural effusion in addition to normal lung tissues and lymph nodes. The extensive single cell profiles depicted a complex cellular atlas and dynamics during lung adenocarcinoma progression which includes cancer, stromal, and immune cells in the surrounding tumor microenvironments.

  Dataset EGAD00001010320

• Activating AKT1 and PIK3CA mutations in metastatic castration-resistant prostate cancer

  This dataset contains all available targeted exon sequencing bam files from our study, "Activating AKT1 and PIK3CA mutations in metastatic castration-resistant prostate cancer". Patient identifiers are denoted by the first segment of the sample aliases (e.g. "P1"), and additional information is appended to reflect which serial sample is referenced (1st, 2nd, 3rd, etc.), and whether the sample represents cell-free DNA ("cfdna") or paired white-blood cell control ("WBC"). All samples were sequenced using Illumina technology.

  Dataset EGAD00001006122

• Therapy-related myeloid neoplasms and HSPCs from the International-Berlin-Frankfurt-Münster (I-BFM) Study group

  Dataset contains WGS sequencing data from bulk sorted therapy-related myeloid neoplasms (t-MN) and reference cells (MSCs/B cells/T cells). In addition, from 4 patients, also WGS data from single hematopoietic stem and progenitor cells, obtained from samples of t-MN diagnosis, are included. These are either clonally expanded before WGS, or DNA was directly amplified via the primary template-directed amplification (PTA) protocol (mentioned in the sample name).

  Dataset EGAD00001011256

• RNA-Seq FASTQs for Tang F. et al. Chromatin accessibility profiles of castration-resistant prostate cancers reveal novel subtypes and therapeutic vulnerabilities

  This dataset contains the FASTQ files for a portion of the samples in Tang F. et al. “Chromatin accessibility profiles of castration-resistant prostate cancers reveal novel subtypes and therapeutic vulnerabilities” published in Science. It contains 51 samples sequenced with Illumina HiSeq 2500 or HiSeq 4000. The remaining samples can be found at dbGaP: phs000909.v1.p1

  Dataset EGAD00001008598

• mapped Bam files from whole transcriptome RNA-seq

  In this study we characterized genomic alterations in two to five metachronous bladder tumors from 29 patients initially diagnosed with early stage disease. Fourteen patients (32 tumors) had non progressive disease (NPD) and 15 patients (34 tumors) had progressive disease (PD). Whole exome sequencing (WES, ~50x mean read depth and whole transcriptome RNA-seq was performed (RNA was not advalible for 4 tumors). Data provided here consist of 71 mapped Bam files form whole transcriptome RNA-seq.

  Dataset EGAD00001002718

• Fastq and reference alignment of 19 samples for defining structural variation associated with breast cancer susceptibility by long-read genome sequencing

  Long-read genome sequencing performed on the Oxford Nanopore Technologies' PromethION to resolve variants underlying breast cancer susceptibility in sixteen individuals with pathogenic germline SVs in BRCA1, BRCA2, CHEK2 or PALB2.

  Dataset EGAD00001008690

• Stromal and dendritic cells from lymph nodes: single-cell RNA-seq

  Although cross-species transcriptional analysis has been generated for DCs, transcriptomic conservation between mouse and human FRCs at single-cell resolution has been unclear. To test whether GREM1+ FRCs might also play a role in DC homeostasis in humans, we performed scRNA-seq of CD45–PDPN+ stromal cells, as well as CD45+CD11c+ immune cells from healthy human LNs of three human donors. Data was generated using the 10x platform.

  Dataset EGAD00001008731

• Exome Sequencing of Poor Prognosis Acute Myeloid Leukaemia (2019-08-19)

  We plan to sequence the exomes of 4 AML cases (tumour and germline) in an effort to discover new mutations in this disease that could improve our understanding of leukaemogenesis and guide the development of new targeted therapies. The Sanger Institute will sequence the exomes of 4 Acute Myeloid Leukaemia cases including tumour and germline DNA so that somatically-acquired, AML-specific mutations can be accurately designated. . This dataset contains all the data available for this study on 2019-08-19.

  Dataset EGAD00001005265

• Fusion gene analysis using multiplex single primer extension-based RNA-sequencing

  The whole study comprises of two patient cohorts. Screening cohort: 40 patients of Germany; validation cohort: 40 patients from Asia. Further, bile duct and CCA cell lines have been analyzed. This dataset contains fusion gene analysis using multiplex single primer extension-based RNA-sequencing for a subset of 25 patients of the screening cohort. Data was generated on Illumina NexSeq 550 device in paired-end mode and is stored in compressed FASTQ file format.

  Dataset EGAD00001011326

• A compendium of mutational signatures due to environmental exposures

  Analysis of mutational signatures caused by exposure to known mutagens in human induced pluripotent stem (iPS) cells. A reference human iPS cell-line will be exposed to 100 chemicals known or proposed to be mutagenic. Following exposure to mutagen, cells will undergo a period of recovery before sub clones are generated and sequenced. The progenitor "parental" IPS cell-line will be used to generate reference sequence data, in order to determine the mutational signatures acquired as a result of exposure to different mutagens.

  Dataset EGAD00001005351

• Single circulating tumor cells in hepatocellular carcinoma

  We determined intra- and inter-vascular transcriptional heterogeneity within the circulatory system using single-cell RNA-sequencing of 113 CTCs isolated from four key vascular sites along their dissemination route in ten HCC patients. The dataset consists of 146 paired-end fastq files from 113 sigle CTCs, HuH-7 cell line, Hep3B cellline, white blood cell, tumor and normal bulk tissue.

  Dataset EGAD00001007642

• Colorectal cancer samples WES

  The whole exome was sequenced in two cancer-affected members (II:1 and III:1) of the family. The family subject of this study showed an autosomal dominant mode of CRC inheritance, fulfilling the Amsterdam I clinical criteria with three CRCs in two consecutive generations. The exome capture was performed using SureSelectXT Human All Exon V3 (51Mb, Agilent Technologies), and the library was sequenced on an Illumina HiSeq 2000 platform with paired-end reads of 101bp and a 50x average coverage depth.

  Dataset EGAD00001009170

• ATAC-seq of metastatic prostate tumors

  This dataset includes Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) data, in FASTQ format, from 70 metastatic castration-resistant prostate cancer tumor samples from the SU2C/PCF West Coast Dream Team (WCDT) project. The sequencing data is paired-end, 150 bp sequencing data from an Illumina NovaSeq 6000 machine. ATAC-seq libraries were prepared following the protocol described in Buenrostro et al. Nature Methods. 2013 (PMID: 24097267) and Corces et al. Nature Methods. 2017 (PMID: 28846090).

  Dataset EGAD00001009654

• Dataset RNA-Seq of tumors for ImmuNEO already used in study EGAS00001004813

  Sequencing data of 20 tumor runs (different tumors), which were uploaded to EGAS00001004813 and used in the ImmuNeo publication. The sequencing was always paired and run on Illumina HiSeq sequencers.

  Dataset EGAD00001009670

• Circulating tumor DNA, pathological and immunologic responses to neoadjuvant nivolumab or nivolumab plus relatlimab and chemoradiotherapy in resectable esophageal/gastroesophageal junction cancer

  The dataset for the study “Circulating tumor DNA, pathological and immunologic responses to neoadjuvant nivolumab or nivolumab plus relatlimab and chemoradiotherapy in resectable esophageal/gastroesophageal junction cancer” includes 173 bam files from hybrid capture targeted error-correction next-generation sequencing (TEC-Seq) from plasma cell-free DNA and matched white blood cell DNA from 32 individuals with esophageal/gastroesophageal junction cancer, who received immunotherapy-containing regimens.

  Dataset EGAD00001011822

• Targeted sequencing of follicular lymphoma tumour samples from the UK's Haematological Malignancy Research Network

  Targeted sequencing was applied to an unselected population-based follicular lymphoma (FL) cohort (n=548) diagnosed in the UK's Haematological Malignancy Research Network catchment population of ~4 million (14 centres). DNA extracted from FL samples was sequenced with a 293-gene panel using the Illumina HiSeq 2500. All data are provided in the CRAM format.

  Dataset EGAD00001007657

• The molecular landscape of colorectal cancer reveals genetic mutations - COCA-CN

  We collected tumor samples and adjacent nomal mucosae from 46 patients with colorectal cancer in surgical operation from 2014 to 2016 in the First Affiliated Hospital of Chongqing Medical University (Chongqing, China) and the Research Institute of Surgery, Third Military Medical University (Chongqing, China). the qualified captured library of each sample was then loaded on Illumina HiSeq 2000 (Illumina, San Diego, CA) platforms and subjected to high-throughput sequencing.

  Dataset EGAD00001003304

• The molecular landscape of colorectal cancer reveals genetic mutations（17 cases）

  We collected tumor samples and adjacent nomal mucosae from 17 patients with colorectal cancer in surgical operation from 2014 to 2016 in the First Affiliated Hospital of Chongqing Medical University (Chongqing, China) and the Research Institute of Surgery, Third Military Medical University (Chongqing, China). the qualified captured library of each sample was then loaded on Illumina HiSeq 2000 (Illumina, San Diego, CA) platforms and subjected to high-throughput sequencing.

  Dataset EGAD00001003224

• ChIP-Seq on multiple myeloma and plasma cell leukaemia cell lines

  ChIP-seq data (H3K4Me1, H3K4Me3, H3K27Ac histone modifications) in experimental triplicates on multiple myeloma cell line KMS11 and plasma cell leukaemia cell lines L363 and JJN3. ChIP reactions were performed on a Diagenode SX-8G IP-Star Compact using Diagenode automated Ideal Kit. ChIP libraries were generated using HTP Illumina library preparation kit, and sequenced using Illumina HiSeq 2000 with 100 bp single-ended reads. ChIP-seq files are in BED format.

  Dataset EGAD00001003349

• De novo mutations in cell-free foetal DNA (cffDNA)

  This project is to develop and validate a method to detect de novo mutations in a foetal genome through deep sequencing of cell-free DNA from the plasma of pregnant women. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001000596

• Merged analysis-ready bam files: HiSeq sequencing of matched tumour/normal DNA samples from Pancreatic Ductal Adenocarcinoma cases

  Additional sequencing data for 173 donors in EGAS00001000154, a study of Pancreatic Ductal Adenocarcinoma. WGS libraries were used for high-cellularity cases, WXS sequencing to high depth on low-cellularity cases. HiSeq 2xxx platform was used in all cases. The analysis files associated with this dataset are merged, de-duplicated bams aligned against GRCh37, one tumour and one normal bam per donor.

  Dataset EGAD00001002192

• Clonal expansion of mutated cell population in bladder urothelium

  1cm biospies of from patients undergoing bladder cystectomy will be collected. The underlying muscle and stroma will be removed and the remaining epithelia dissected into small sequential areas which will be sent for ultra-deep exome sequencing using a panel of known cancer and viral genes. Sequence analysis using similar methods to Martincorena I et al (Science 2015, 348:880) will provide an idea of the somatic mutational landscape in these patient samples. Individual patient muscle samples will also be sequenced as a reference.

  Dataset EGAD00001003250

• The molecular landscape of colorectal cancer reveals genetic mutations（5 cases）

  We collected tumor samples and adjacent nomal mucosae from 5 patients with colorectal cancer in surgical operation from 2014 to 2016 in the First Affiliated Hospital of Chongqing Medical University (Chongqing, China) and the Research Institute of Surgery, Third Military Medical University (Chongqing, China). the qualified captured library of each sample was then loaded on Illumina HiSeq 2000 (Illumina, San Diego, CA) platforms and subjected to high-throughput sequencing.

  Dataset EGAD00001003223

• Gene Characterization in Carbohydrate metabolic alterations (neonatel diabetes & congenital hyperinsulinemic) in early childhood (2018-03-14)

  Whole Exome Sequencing of trios (proband + parents) or probands only with Neonatal Diabetes Mellitus (NDM) or Congenital Hyperinsulinism of Infancy (CHI) of unknown genetic origin. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2018-03-14.

  Dataset EGAD00001004040

• Mitochondrial DNA (mtDNA) sequences from subjects with intellectual disability (ID) and austism spectrum disorder (ASD)

  Sequences from 95 subjects presenting intellectual disability (ID) and 98 subjects presenting intellectual disability and a diagnosis of autism spectrum disorder (ASD). The mtDNA was amplified by long-range PCR with 3 pairs of primers producing overlapping fragments. The three fragments were mixed in equimolar ratios and each sample was sequenced in an Ion Torrent Personal Machine according to manufacturer's user guide (reference genome: NC_012920.1 (rCRS)).

  Dataset EGAD00001004213

• Whole genome sequencing of a Grem1 mutant human tumour

  The BMP antagonist Grem1 has been shown to be associated with a rare human polyposis syndrome (HMPS). We have shown that there is a 40KB duplication on chrom 15 found in some patients with HMPS. Traditional serrated adenomas (rare sporadic polyps) share some morphological features with HMPS polyps and it has long been hypothesised that they are the sporadic version of HMPS polyps. We have obtained of one of these lesions and in this project we aim to characterise this tumour.

  Dataset EGAD00001002182

• Spectrum of Response to Platinum and PARP Inhibitors in Germline BRCA Associated Pancreatic Cancer in the Clinical and Pre-clinical Setting

  Whole genome sequencing data for germline BRCA pancreatic cancer

  Dataset EGAD00001011129

• Translation of non-canonical open reading frames as a cancer cell survival mechanism in childhood medulloblastoma - Ribo-Seq

  This study aims to investigate the dysregulation of RNA translation and identify functional non-canonical open reading frames (ORFs) as potential targets for medulloblastoma treatment. The study involves ribosome profiling and RNAseq of medulloblastoma tissues and cell lines to observe the translation of non-canonical ORFs. Multiple CRISPR-Cas9 screens will be used to identify functional non-canonical ORFs implicated in medulloblastoma cell survival.

  Dataset EGAD00001011193

• Comprehensive Deep Sequencing Atlas in HCC tumors

  The atlas aims to unravel the intricate genetic landscape of HCC, providing a detailed characterization of genomic alterations, transcriptomic profiles, and key mutations associated with liver tumors. The integration of WGS, RNAseq, and WES data offers a holistic perspective, facilitating a deeper understanding of the molecular mechanisms driving HCC pathogenesis. The resulting atlas serves as a valuable resource for researchers, clinicians, and the broader scientific community, contributing to advancements in HCC diagnostics, prognostics, and therapeutic interventions.

  Dataset EGAD00001015343

• Single-cell Transcriptomic and Immune Receptor Profiling of PBMCs from Dengue-Infected Individuals with Varying Disease Severities

  This dataset comprises single-cell RNA sequencing (scRNA-seq) and immune receptor (TCR/BCR) profiling of peripheral blood mononuclear cells (PBMCs) collected from individuals infected with dengue virus (DENV) exhibiting different clinical severities: asymptomatic dengue (AD), dengue fever (DF), and dengue hemorrhagic fever (DHF). PBMCs were collected during the acute phase and, in some cases, during convalescence. The data provide a resource for understanding protective versus pathogenic immune responses in dengue infection.

  Dataset EGAD00001015634

• unmapped Bam files from whole transcriptome RNA-seq

  In this study we characterized genomic alterations in two to five metachronous bladder tumors from 29 patients initially diagnosed with early stage disease. Fourteen patients (32 tumors) had non progressive disease (NPD) and 15 patients (34 tumors) had progressive disease (PD). Whole exome sequencing (WES, ~50x mean read depth and whole transcriptome RNA-seq was performed (RNA was not advalible for 4 tumors). Data provided here consist of 71 unmapped Bam files form whole transcriptome RNA-seq.

  Dataset EGAD00001002717

• Non-invasive prenatal diagnosis by genome-wide haplotyping of cell-free plasma DNA

  This dataset contains a total of 10 families and 51 samples presented in 'Non-invasive prenatal diagnosis by genome-wide haplotyping of cell-free plasma DNA' study, in which 9 of them are cfDNA samples and the rest of samples are gDNA samples. All the samples are targeted sequencing data with a custom 45Mb capture library . Raw pair-end fastq files for each sample is available.

  Dataset EGAD00001004989

• Genomic and clinical data from IMmotion010, a phase 3 randomised clinical trial testing adjuvant atezolizumab versus placebo for patients with renal cell carcinoma at increased risk of recurrence following resection

  778 patients were randomized in this study. Pre-treatment bulk RNAseq of primary tumors was conducted for 754 patients. For 80 patients, bulk RNAseq analysis of a metastastic biopsy was conducted. For these 80 pairs, DNA alterations were assessed in pre-treatment and at recurrence using FoundationOne.

  Dataset EGAD50000001827

• mRNA-seq of in vitro differentiation from induced pluripotent stem cells to hepatocyte-like cells

  Fastq files of mRNA-seq data of induced pluripotent stem cells (iPSC), definitive endoderm (DE) and hepatocyte-like cells (HLC). The dataset comprises data from the in vitro differentiation protocol Cellartis (Takara Bio, "CEL", n = 4) and several interventions (11x3 replicates).

  Dataset EGAD00001005935

• Long-read sequencing of prostate adenocarcinoma metastatic to left axillary lymph node. Data used to support Figure 6 in Pubmed ID 32025007 "Pan-Cancer Analysis of Whole Genomes Consortium." Nature 2020 578:8293.

  Oxford Nanopore long-read sequencing of A17-LAxillaryLN2Met-23312 PELICAN sample, identified as D051965 un Pan-Cancer Analysis of Whole Genomes study, and identified as PD13412a by prior Gundem et al whole genome sequencing study (PMID 25830880). Data used to support Figure 6 in Pubmed ID 32025007 "Pan-Cancer Analysis of Whole Genomes Consortium." Nature 2020 578:8293.

  Dataset EGAD00001005974

• FFPE

  The mutational status of 112 recurrently mutated genes in B-cell lymphoma was examined by targeted next-generation sequencing (NGS). Libraries were performed with 150 ng of genomic DNA (gDNA) obtained from formalin-fixed paraffin-embedded (FFPE) biopsy using molecular-barcoded library adapters (ThruPLEX Tag-seq kit; Takara) coupled with a custom hybridization capture based method (SureSelect XT Target Enrichment System Capture strategy, Agilent Technologies Inc.) and sequenced in a MiSeq instrument (Illumina, 2x150bp).

  Dataset EGAD00001006565

• Extended screen by deep amplicon sequencing

  The whole study comprises of two patient cohorts. Screening cohort: 40 patients of Germany; validation cohort: 40 patients from Asia. Further, bile duct and CCA cell lines have been analyzed. This dataset contains targeted DNA sequencing data of 40 tumor/normal pairs from the validation cohort plus 10 tumor/normal pairs of patients from the screening cohort for technical validation. Data was generated on Illumina HiSeq 2000 device in paired-end mode and is stored in BAM file format.

  Dataset EGAD00001011323

• RNAseq in pleural mesothelioma primary cell lines

  Pleural mesothelioma (PM) requires new treatments. Drug repurposing offers a potential approach to finding effective therapies. This study aimed to explore new therapeutic options for PM using RNA sequencing. RNA sequencing was performed on 58 patient-derived PM cell lines. Drug screening of over 1300 compounds was conducted on 11 lines, with further testing of selected drugs on 48 lines. Top candidates were validated in 3D culture and mouse models.

  Dataset EGAD00001015408

• GBM-Space: Spatial Transcriptomic Profiling of Glioblastoma (10x Genomics - Visium)

  Cancer cells display heterogeneous and dynamic states in glioblastoma, but how these malignant states arise and whether they follow a tractable cellular trajectory across tumours is poorly understood. Here, we generate a deep single cell and spatial multi-region atlas of 12 isocitrate dehydrogenase wild-type (IDH-wt) primary glioblastomas that integrates transcriptomic, epigenomic and genomic analysis to comprehensively characterise their tumour heterogeneity. The datasets in this study include sequencing data from Visium spatial transcriptomic (10x Genomics) profiling of these tumours.

  Dataset EGAD00001015527

• ARDSNet 07-08: Randomized, Blinded, Placebo-Controlled, Multi-Center Trial of Omega-3 Fatty Acid, Gamma-Linolenic Acid, and Antioxidants in Acute Lung Injury or ARDS (OMEGA) (ARDSNet-Omega-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. Biospecimens: Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from ARDSNet-Omega include bronchial lavage, plasma, urine, and DNA. Please note that use of biospecimens in genetic research is subject to a tiered consent.Objectives: To determine if dietary supplementation of omega-3 (n-3) fatty acids, γ-linolenic acid and antioxidants to participants with acute lung injury would increase ventilator-free days to study day 28.Background: Early acute lung injury (ALI) is characterized by neutrophilic lung inflammation, permeability, and intravascular and alveolar fibrin deposition. The type and inflammatory activity of eicosanoids liberated during inflammation depends on the membrane phospholipid composition: omega 6 (n-6) fatty acid arachidonate yields highly reactive and inflammatory dienoic prostaglandins and series 4 leukotrienes, whereas omega-3 (n-3) fatty acids favor production of less active and potentially anti-inflammatory trienoic prostaglandins and series 5 leukotrienes. Participants at risk of developing ALI have n-3 levels approximately 25% of normal and those with established ALI have n-3 levels as low as 6% of normal, suggesting a potential role for n-3 dietary supplementation in participants with ALI.Three randomized controlled studies, conducted in participants with ALI or sepsis-induced respiratory failure, demonstrated an association between the administration of an enteral formula enriched in n-3 fatty acids, GLA, and antioxidants and improved oxygenation and respiratory physiology compared with an unenriched, high-fat formula. However, interpretation of these results is limited by the small sample sizes and as-treated analyses of only those participants who tolerated full enteral nutrition. Participants: The total number of participants in the study was 272.Design: Participants were stratified by hospital and the presence of shock at baseline and then randomized to receive either twice-daily enteral supplementation of n-3 fatty acids, GLA, and antioxidants (n-3 supplement) or an isocaloric-isovolemic carbohydrate-rich control. Participants were also simultaneously randomized to a separate ongoing trial (the EDEN study) comparing low- vs full-calorie enteral nutrition in a 2×2 factorial design.The n-3 or control supplement was administered enterally as twice-daily boluses of 120 mL beginning within 6 hours of randomization. Dosing continued until the earliest of 21 days, 48 hours of unassisted breathing, or extubation. The energy provided by the boluses supplemented that provided by each primary physician's choice of standard continuous non–n-3-enriched enteral formula. The rate of continuous enteral feeding was managed by a protocol with an algorithm for gastrointestinal intolerances. The supplement was administered even if enteral nutrition was interrupted, as long as the patient was tolerating enteral medications. Conclusions: The study was stopped by the DSMB for futility at the first interim analysis after 143 participants had been randomized to receive the n-3 supplement and 129 to receive the isocaloric control. Despite an 8-fold increase in plasma eicosapentaenoic acid levels, participants receiving the n-3 supplement had fewer ventilator-free days, intensive care unit–free days, and nonpulmonary organ failure-free days.

  Study phs003744

• NHLBI GO-ESP Family Studies: Pulmonary Arterial Hypertension

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. Pulmonary arterial hypertension (PAH) is a progressive disease characterized by widespread occlusion of the smallest arteries of the lungs. Pulmonary vascular obstruction leads to increased pulmonary vascular resistance, which subsequently causes heart failure with mean survival of 3 years. PAH occurs at all ages and affects women more than twice as frequently as men. Sporadic Idiopathic pulmonary arterial hypertension (IPAH), comprises 94% of what was formerly known as primary pulmonary hypertension, and is clinically and pathologically indistinguishable from familial PAH (FPAH). Most FPAH is due to mutation in BMPR2, including more than 120 families in the US. Our goal here is to find other genes that are a basis for FPAH, so we selected for exome sequencing 5 families among 40 who do not have mutation in BMPR2, or other known genes (ACVRL1, SMAD8, ENG) that rarely are the basis for FPAH.

  Study phs000354

• The Breast and Prostate Cancer Cohort Consortium (BPC3) GWAS of Aggressive Prostate Cancer and ER- Breast Cancer

  The Breast and Prostate Cancer Cohort Consortium (BPC3) was established in 2003 to pool data and biospecimens from nine large prospective cohorts to conduct research on gene-environment interactions in cancer etiology. The BPC3 initially focused on the association of >70 candidate genes in the Steroid Hormone Metabolism and IGF pathways with risk of breast and prostate cancer. The Consortium's work expanded in 2007 to include genome-wide association studies of estrogen receptor negative (ER-) breast cancer and aggressive prostate cancer. ER- breast cancers have specific epidemiologic characteristics and greater lethality, suggesting ER- breast cancer has a different etiology than ER+ breast cancer. Similarly, aggressive forms of prostate cancer, characterized by extraprostatic extension (Stage C/D) or high histologic grade (Gleason score 8+), differ epidemiologically from the vastly more common indolent forms of prostate cancer and are of the greatest clinical importance. By restricting cases to these specific subtypes, the BPC3 GWAS increased power to detect loci associated with ER- and aggressive prostate cancer (Kraft P and Haiman CA, Nature Genetics 2010 Oct;42:819-20, PMID: 20877320 ). The BPC3 GWAS includes the following cohorts: the American Cancer Society Cancer Prevention Study-II (CPS-II); the European Prospective Investigation of Cancer (EPIC); the Physician's Health Study (PHS); the Nurses' Health Studies I and II (NHS and NHSII); the Health Professionals Follow-up Study (HPFS); the Multiethnic Cohort (MEC); the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial; and the Alpha-Tocopherol, Beta-Carotene (ATBC) Study. For the GWAS of ER- cancer, the BPC3 was expanded to include the Polish Breast Cancer Study (PBCS), a population-based case-control study.

  Study phs000812

• Genetic Progression of Head and Neck Squamous Cell Carcinoma

  These data are tumor/normal-matched exome sequencing results on 45 participants (median age of 58.6 years) treated for squamous cell carcinoma of the oropharynx at Mass Eye and Ear (MEE; Boston, MA, USA). Some tumors had two portions sequenced separately. All research complied with all relevant ethical regulations. Human subject research on patients at MEE was approved by the MEE Human Studies Committee under protocol HSC 11-024H, with informed consent obtained from participants. Participants were not compensated. Clinical data, including HPV status, were abstracted from patient records. Sequencing and clinical data were combined with TCGA data on 486 cases of head and neck squamous cell carcinoma (HNSCC). The PhylogicNDT suite of genomic analysis tools was used to infer the relative timing of genetic events during tumor progression for major molecularly defined classes of HNSCC: HNSCC negative for human papillomavirus (HPV), HPV-associated HNSCC, and HPV-negative HNSCC involving mutations in CASP8, NSD1, and NOTCH1. The timing of the development of whole-genome somatic events leading to tetraploidy or triploidy and to increased measures of intratumor genetic heterogeneity was determined. Associations of heterogeneity measures with clinical outcomes were assessed. The analysis identified genes with early mutations that likely play roles in HPV-tumor initiation (FBXW7, NOTCH1, CASP8, FAT1, NSD1, HRAS, EP300, CREBBP, KMT2D). Genes with mutations at later median relative timing (PK3CA, NFE2L2, HLA-A, SPEN, and KMT2C) were more likely to be important for progressing to later stages of the disease. Gain of chromosome arm 3q and loss of arm 11q were found to occur more frequent in HPV+ HNSCC cases. A high prevalence of 3p and 17p loss were also observed in HPV+ HNSCC cases.

  Study phs003139

• The EVE Asthma Genetics Consortium: Building Upon GWAS

  The EVE Asthma Genetics Consortium comprises U.S. investigators who have conducted genome-wide association studies (GWAS) of asthma; the main objective is to combine results of individual studies to increase the overall power to identify loci for asthma and asthma-associated traits. The consortium includes investigators at 9 U.S. institutions with GWAS results for >10,000 individuals representing European American, African American, African Caribbean, U.S. Hispanic, and Mexican populations and includes the following studies: The Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-Ethnicity (SAPPHIRE) The Genetic Research on Asthma in the African Diaspora (GRAAD) Study The Genetics of Asthma in Latino Americans (GALA 1) Study The Childhood Asthma Management Program (CAMP) The Childhood Asthma Research and Education (CARE) Network The Children's Health Study (CHS) Mexico City Childhood Asthma Study (MCCAS) The Chicago Asthma Genetics Study (CAG)* The National Heart, Lung, and Blood Institute Collaborative Studies of the Genetics of Asthma (CSGA)* The Severe Asthma Research Program (SARP)* (*CAG, CSGA, and SARP are part of the NHLBI-supported SNP Typing for Association with Multiple Phenotypes from Existing Epidemiologic Data (STAMPEED) consortium.) For the GWAS, we developed a common set of >1 million genotyped and imputed SNPs from the EVE Asthma Genetics Consortium to be tested for association with asthma and associated phenotypes in all samples and combined p-values for a grand meta-analysis for asthma gene discovery. A subset of 296 individuals representing African American, European American, and Latino ancestry were selected for whole genome sequencing. The broad goals of this project were to characterize the genetic architecture of asthma and associated quantitative phenotypes (e.g., lung function, total serum IgE) in ethnically diverse populations from the U.S., Mexico, Puerto Rico, and Barbados.

  Study phs001156

• Characterization of Human Transcriptome by Computational and HTS Approaches

  We have deeply sequenced total RNA and whole exome of six different post-mortem human snap-frozen tissues (brain, liver, lung, striated muscle, kidney, heart) from three unrelated healthy Caucasian individuals (males, aged 47-54) with the aim to characterize post-transcriptional events due to alternative splicing and RNA editing. In addition, to facilitate the detection of RNA editing sites we have also resequenced the entire genome of each individual. Data are also used to investigate tissue-specific abundance of mitochondrial DNA from exomes and its correlation with mitochondrial transcription, mass and respiratory activity. Tissues were obtained from Cureline (South San Francisco, CA, USA). DNA and RNA were purified using the DNeasy Blood and Tissue Kit (Qiagen, Hilden, Germany) and the RNeasy Plus Mini Kit (Qiagen, Hilden, Germany), respectively. Exome capture was performed using the TruSeq Exome Enrichment Kit (Illumina, San Diego, CA) and the sequencing was carried out at IGA Technology Services in Udine (Italy) on Illumina HiSeq 2000 (generating for each tissue approximately 40 millions of 100bp paired-end reads). Strand-oriented RNA reads (2x100bp) were generated using the TruSeq Stranded Total RNA Sample Prep Kit (Illumina, San Diego, CA, USA) and sequenced at IGA Technology Services in Udine (Italy) on Illumina HiSeq 2000 platform. Whole genome resequencing was performed at Personal Genomics in Italy on an Illumina HiSeq 2000 platform (2x100bp) with a mean coverage of 30X. MiRNA-Seq was instead performed at IBBE Institute (Italy) using the TruSeq Small RNA Sample Prep Kit on Illumina MiSeq platform. Preliminary bioinformatics analyses have been performed to check quality using FASTQC software and inconsistent read regions have been trimmed using trim_galore. All reads were mapped onto the human reference genome (version hg19) using GSNAP.

  Study phs000870

• National Cancer Institute (NCI) Non-Hodgkin Lymphoma Genome-wide Association Study (GWAS)

  Within the framework of the International Lymphoma Epidemiology Consortium (InterLymph) Consortium and NCI-sponsored Cohort Consortium, investigators from 22 studies came together to conduct a genome-wide association study (GWAS) of non-Hodgkin lymphoma (NHL). The goal of the study was to identify common genetic variants associated with the risk of NHL. As described previously (Berndt SI et al., Nature Genetics, 2013, PMID: 23770605 ), cases and controls from 22 studies, including nine prospective cohort studies, eight population-based case-control studies, and five clinic or hospital-based case-control studies were included in this effort. Cases of NHL were ascertained from cancer registries, clinics or hospitals, or through self-report verified by medical and pathology reports. The phenotype information for all NHL cases was reviewed centrally at the InterLymph Data Coordinating Center and harmonized according to the hierarchical classification proposed by the InterLymph Pathology Working Group based on the World Health Organization (WHO) classification (2008). Controls were frequency matched to cases on age and gender by study, and the study was limited to subjects of European ancestry. Participants were genotyped using the Illumina Omni Express. The NCI Non-Hodgkin Lymphoma GWAS is utilized in the following dbGaP sub-studies. To view genotypes and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs000801 NCI Non-Hodgkin Lymphoma GWAS. phs000802 NCI Non-Hodgkin Lymphoma GWAS: CLL phs000818 NCI Non-Hodgkin Lymphoma GWAS: Controls phs000889 NCI Non-Hodgkin Lymphoma GWAS: DLBCL phs000890 NCI Non-Hodgkin Lymphoma GWAS: FL phs000891 NCI Non-Hodgkin Lymphoma GWAS: MZL

  Study phs000801

• Diabetes Control and Complications Trial (DCCT) and Epidemiology of Diabetes Interventions and Complications Study (EDIC)

  The Diabetes Control and Complications Trial (DCCT, 1982-93) and the Epidemiology of Diabetes Interventions and Complications follow-up study (EDIC, 1994-2016) have been ongoing for more than twenty years. After a mean follow-up of approximately 16 years, the DCCT-EDIC cohort of 1,441 Type 1 diabetics had remained remarkably complete with more than 90% of the original cohort being actively followed. Taken together, the DCCT clinical trial and subsequent EDIC longitudinal follow-up provide a uniquely rich source of information on the impact of intensive therapy on glycemia and the its long-term complications for persons with Type 1 diabetes. The DCCT was a multicenter, randomized clinical trial (1, 2) designed to compare intensive with conventional diabetes therapy with regard to their effects on the development and progression of the early complications of Type 1 diabetes. The DCCT trial found that "intensive therapy effectively delays the onset and slows the progression of diabetic retinopathy, nephropathy, and neuropathy" in patients with Type 1 diabetes (1). The goal of the EDIC follow-up was to examine the longer term effects of the original DCCT interventions, especially as they apply to late-occurring complications, such as cardiovascular disease and more advanced stages of retinal and renal disease (3). The EDIC study has been remarkably fruitful in discovering the long term "imprinting" effects (metabolic memory) of the previous intensive therapy, and in delineating the interactions among risk factors with regard to microvascular complications (4-6). In addition, EDIC established, for the first time, the role of intensive therapy and chronic glycemia on atherosclerosis (7-9). Note: This study description has been prepared using materials authored by the DCCT-EDIC Data Coordinating Center. DETAILED DESCRIPTION OF STUDY

  Study phs000086

• Type 1 Diabetes Genetics Consortium (T1DGC): Copy Number Variant (CNV) Study

  Type 1 Diabetes Genetics Consortium (T1DGC) was formed to address issues of limited sample size and consistency of phenotyping that had limited genetic investigations on risk of type 1 diabetes (T1D). The T1DGC first collected affected sib pair (ASP) families from four geographic networks (Asia-Pacific, Europe, North America, United Kingdom). In addition, T1D parent-offspring trios as well as cases and controls were ascertained from existing and de novo collections. For T1D, the genome-wide association study (GWAS) design has been successful at detecting ~50 loci that contribute disease risk. However, in the case of T1D as well as almost all other traits, the sum of these loci does not fully explain the heritability estimated from familial studies. One possibility for the undiscovered contribution to familial aggregation is that additional variants exist but have not yet been found because they have not effectively been targeted by the GWAS design. In this study, we focus on a specific class of large deletions/duplications -- copy number variants (CNVs) - and particularly to the subset of these loci that mutate rapidly, are not tagged by SNPs, and are highly polymorphic. The T1DGC assembled 2,601 T1D ASP families and 69 Parent-T1D offspring trios, that were eligible for this study. All samples included in this series have reported or self-declared European ancestry. All DNA samples were collected after approval from relevant institutional research ethics committees. Importantly, the source of DNA for CNV evaluation was uniform within a family (either all from PBMC or from EBV-transformed cell lines). We use a family based design that was optimized to capture these previously untested variants. We then perform a genome-wide scan to assess their contribution to T1D.

  Study phs000910

• NHLBI GO-ESP: Lung Cohorts Exome Sequencing Project (Asthma): Genetic variants affecting susceptibility and severity

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. The exome sequencing asthma project includes 200 African-Americans with asthma from the NHLBI multicenter Severe Asthma Research Program (SARP). SARP participants were recruited at the NHLBI SARP sites with an emphasis on recruiting severe asthmatics (Moore et al., Am J Respir Crit Care Med, 2010. PMID: 19892860). Asthma status was based on both a physician's diagnosis and either bronchodilator reversibility or hyper-responsiveness to methacholine as well as less than 5 pack years of smoking. All subjects were carefully characterized using the standardized SARP protocol which included spirometry (medication withheld), maximum bronchodilator reversibility, hyper-responsiveness to methacholine (not performed in subjects with low baseline FEV1), skin-tests to common allergens, questionnaires on health care utilization and medication use and sputum, lung imaging and bronchoscopy in a subset. In addition GWAS data are available (phs000355, Illumina platform).

  Study phs000422

• The Human Pancreas Analysis Program (HPAP)

  The past decade has seen a dramatic improvement in our ability to phenotype and molecularly profile human tissues with unprecedented resolution at the genomic, epigenomic, protein, and functional levels. The Human Pancreas Analysis Program (HPAP), part of the Human Islet Research Network and supported by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) through multiple NIH grants, is performing deep phenotyping of the human endocrine pancreas to better understand the cellular and molecular events that precede and lead to beta-cell loss and/or dysfunction in type 1 diabetes (T1D) and type 2 diabetes (T2D) as well as to accumulate, analyze, and distribute high-value data sets to the diabetes research community through the HPAP PANC-DB database (and additional details provided at that site). To this end, HPAP employs state-of-the-art technologies to perform comprehensive analyses of pancreas biology as it pertains to organ donors with T1D, autoantibody-positive donors without diabetes, donors with T2D, and control donors. Pancreas procurement and analyses take advantage of the expertise and extensive network of Organ Procurement Organizations (OPOs) and autoantibody screening centers established through the JDRF/The Lenona M. and Harry B. Helmsley Charitable Trust (HCT) – funded nPOD program. In contrast to nPOD, the major product provided by HPAP is not archived biomaterial subject to broad distribution, but rather, the delivery of extensive and high-quality molecular data sets to the diabetes research community in order to facilitate further discovery. Together, nPOD and HPAP are complementary programs that assist the diabetes community and afford the maximal opportunity for advancing knowledge about the pathogenesis of T1D and T2D.

  Study phs002465

• Binding of Epstein Barr Virus EBNA2 Unifies Multiple Sclerosis Genetic Mechanisms

  This study is focused on multiple sclerosis (MS). MS is likely caused by a combination of genetic and environmental factors; however, the mechanisms contributing to these factors remain poorly understood. Epstein-Barr virus (EBV) in particular is a well-established environmental risk factor for MS. We have created a computational algorithm that systematically searches for common molecular mechanisms that might be impacted at multiple MS-associated loci. Using this algorithm, we have discovered that over 40% of MS-associated loci contain MS genetic variants that fall within regions of the human genome occupied by the EBV-encoded EBNA2 protein. The same MS-associated variants also impact gene expression levels of MS-associated genes in EBV-infected B cell lines. Our hypothesis is that allele-dependent binding of EBNA2 and its co-factors explains the allele-dependent risk at many MS genetic loci. Importantly, this hypothesis links the genetic associations of MS to the known molecular roles played by EBV and Notch signaling in disease processes.Subjects with and without MS were recruited into an Institutional Review Board (IRB)-approved protocol through the Cincinnati Autoimmune Registry and Repository. From each subject, DNA from peripheral blood was isolated for whole genome sequencing (WGS). These data will be used to identify genotype-dependent transcriptional regulation in cells assessed from patients and controls. This WGS data was deposited before the full integration of sequence data with other functional genomic data types.From each subject, 90 mL of blood is drawn for isolation of peripheral blood mononuclear cells from which primary B and T cells will be isolated. For each B cell isolation, an EBV-transformed B cell line will be derived.

  Study phs003240

• Tourette International Collaborative Genetics (TIC Genetics) Study - NJCTS and NIMH

  The Tourette International Collaborative Genetics (TIC Genetics) Study is an international collaboration of scientists and clinicians specialized in Tourette Disorder (TD) from more than 20 sites across the United States, Europe, and South Korea. The study was established to further our understanding of the genetic architecture of tic disorders by developing a large sample of genotypically and phenotypically well-characterized affected probands and their relatives. We employ state-of-the-art genetic technologies to identify major genetic variants contributing to TD and the most commonly comorbid disorders, such as Obsessive-Compulsive Disorder (OCD) and Attention-Deficit/Hyperactivity Disorder (ADHD). TIC Genetics is a direct result of work of the New Jersey Center for Tourette Syndrome (NJCTS) Sharing Repository (Heiman et. al., 2008; PMID: 19036136), funded by a grant from NJCTS Center of Excellence. Established in 2011 (Dietrich et. al., 2015; PMID: 24771252), the TIC Genetic study focuses on both on familial genetic variants with large effects within multiplex affected pedigrees and on de novo mutations ascertained through the analysis of apparently simplex parent-child trios with non-familial tics. In May 2017, we published a whole-exome sequencing study on apparently 311 parent-child trios (Willsey et. al., 2017; PMID: 28472652). These data, both phenotypes and sequencing data, are available through dbGaP. There were 120 subject samples included in the publication that did not have consent for sharing. These are excluded from dbGaP.In November 2021, we published a whole-exome sequencing study on 13 multiplex TD families (Cao et. al., 2021). These data, both phenotypes and sequencing data, are available through dbGaP.

  Study phs001423

• Genetic Investigations of Attention-Deficit/Hyperactivity Disorder

  Design and Aims:We conducted whole-exome DNA sequencing on 152 parent-child trios (456 individuals total) that included a child meeting DSM-IV or DSM-5 criteria for ADHD along with both biological parents to identify rare de novo damaging DNA variants associated with ADHD risk. Mutation rates were compared between 147 ADHD trios and 780 unaffected control trios. We aimed to identify specific ADHD risk genes by combining the de novo trio data with rare variant data from an independent case-control cohort.Population Information:ADHD trios were collected from four sites. The 780 control trios were unaffected siblings from the Simons Simplex Collection who scored in the normal range on the Child Behavior Checklist (CBCL) or Adult Behavior Checklist (ABCL) ADHD subscale.Molecular Technologies:Whole-exome DNA sequencing was performed on the ADHD trios using the IDT xGen V1 or Agilent SureSelect All Exon V7 capture and the Illumina NovaSeq6000 sequencer. Control trios were previously sequenced with the NimbleGen SeqCap EzExomeV2 capture and Illumina HiSeq 2000 sequencer. Joint variant calling was performed for all trios. Rare de novo variants with allele frequency Principal Findings:We found a 1.67-fold enrichment of rare de novo damaging variants and a 1.93-fold enrichment of ultra-rare de novo damaging variants in ADHD cases vs controls. By integrating the de novo data with an independent case-control cohort, KDM5B was identified as a high-confidence ADHD risk gene (FDR=0.04). Three potential risk genes were also identified. Twenty-three genes with ultra-rare damaging de novo variants in ADHD overlapped with previously reported risk genes for other neuropsychiatric conditions. Exploratory analyses showed enrichment of these genes in early neurodevelopmental pathways.

  Study phs003647

• Chromatin Landscape of BET Inhibitor-Treated CD8+ T-cells from Chronic Lymphocytic Leukemia Patients

  The pan-BET (bromodomain and extra-terminal) inhibitor, OPN-51107 (OPN5) was found to alleviate features of T-cell exhaustion in models of chronic lymphocytic leukemia (CLL). To evaluate if OPN5 treatment could relieve fixed chromatin states associated with terminal T-cell dysfunction, ATAC-sequencing was performed on CLL patient T-cells. Peripheral blood mononuclear cells (PBMCs) from 4 treatment-naïve CLL patients were treated ex vivo with 0.5 μM OPN5 or equivalent vehicle (DMSO) in the presence of T-cell activating stimuli (10 μg/mL anti-CD3 and 5 μg/mL anti-CD28) for 16 hours. Live CD8+ T-cells were then isolated via fluorescence-activated cell sorting, and approximately 100,000 viable CD8+ T-cells were subjected to ATAC-sequencing. Libraries were prepared using the Active Motif ATAC-seq kit and underwent paired-end sequencing (2 x 50 bp, 100 cycles) on an Illumina NovaSeq 6000 SP sequencer. Analysis of this data revealed that OPN5 treatment induces a unique chromatin landscape in CLL patient T-cells that is less like that of terminally exhausted T-cells and more like that of effector and memory T-cells. In particular, OPN5 treatment reduced chromatin accessibility at promoter regions of terminal exhaustion-associated genes (e.g., CD101, CCR5, LAG3, BATF3) and increased chromatin accessibility at promoter regions of genes associated with progenitor T-cell function (e.g., TCF7, IL2, CXCR5, IFNG). Individual raw sequencing (fastq) files and processed bigwig files (aligned to the hg38 human reference genome), as well as bigwig files for grouped OPN5- and vehicle-treated samples (aggregate of all 4 patient samples per treatment group) are available via authorized access request through dbGaP.

  Study phs003613

• DAC for Central African ancient demography processes NGS dataset

  Title DAC Ancient tree-topologies and gene-flow processes among human lineages in Africa Contacts: Paul Verdu +33144057317 paul.verdu@mnhn.fr CNRS-MNHN-Université de Paris UMR7206 Eco-anthropology Short description The Data Access Committee for acess to genotype and sample information used in the article "Ancient tree-topologies and gene-flow processes among human lineages in Africa" by Gwenna Breton et al. 2025 ensures that data-access requests comply with the Informed Consent provided by donors, and with ethical and deontological guidelines with respect to privacy. DNA samples from individuals were collected with the subjects’ informed consent following the Declaration of Helsinki guidelines and approved by the following Ethics committees: Institut de Recherche pour le Développement (IRD, France); Cameroon Ministry of Scientific Research and Technology; Central African Republic Ministère de l’Enseignement Supérieur et de la Recherche Scientifique; France Ministère de l’Enseignement Supérieur, de la Recherche et de l’Innovation (Comité de Protection des Personnes DC-2016-2740); French Commission Nationale Informatique et Liberté CNIL (declaration n°1972648); Uganda National Council for Science and Technology; Institutional Review Board of the University of Chicago Biological Sciences Division and the Pritzker School of Medicine University of Chicago Hospitals (protocol number 16986A); Committee for the Protection of Human Subjects of the Trustees of Dartmouth College and the Dartmouth-Hitchcock Medical Center (protocol number 22410); Human Research Ethics Committee (Medical) at the University of the Witwatersrand, Johannesburg (Protocol Numbers: M980553, M050902, M090576, M10270, M180654); Working Group of Indigenous Minorities in Southern Africa (WIMSA); South African San Council (SASC); and the Swedish Ethical Review Authority (Dnr 2019-05174). Requests for accessing all or part of the Central African data used in the article "Ancient tree-topologies and gene-flow processes among human lineages in Africa", by Gwenna Breton et al. 2024 (doi - PENDING), should be addressed to the DAC providing: 1) Data can only be used to explore human genetic evolution, evolutionary ecology and population history 2) The research institution where data will be stored and were analyses will be conducted. 3) The detailed coordinates of the researcher responsible for data storage and analyses. 4) A description (max 20 sentences) of the scientific finality and context of the project and classes of methodological analyses that will be performed to achieve it using the requested data. 5) When applicable, mention also other previously published data sets that will be used jointly with the requested datas et For accessing any or all the Central African genetic data used in the article "Ancient tree-topologies and gene-flow processes among human lineages in Africa", by Gwenna Breton et al. 2024 (doi - PENDING), the requester hereby ensures that: 1) Individual donor privacy should be respected at all times. Data cannot be made publicly available under any circumstances. 2) Data cannot be shared nor transferred to a third party without re-applying for eGA access to the DAC. 3) No direct or indirect commercial use of the data can be made 4) No individual medical genetics or disease diagnostics can be performed with the data 5) No medical or legal forensic investigations can be conducted with the data 6) No genealogical research can be conducted with the data (e.g. no paternity nor maternity testing, no genetic identification, no search of relatives using other datasets) 7) Appropriate citation of the article and data set used for any scientific communication using the data 8) Data is destroyed after the completion of the project. Any further re-use of the data is subject to a novel application to the DAC.

  Dac EGAC50000000447

• Response to Hepatitis B vaccine

  Approximately 5-10% of individuals, who are vaccinated with a hepatitis B (HB) vaccine designed based on the HBV genotype C, fail to acquire protective levels of antibodies. Host genetic factors behind low immune response to the HB vaccine were investigated by GWAS and HLA association tests. GWAS and HLA association tests were carried out using a total of 1,193 Japanese individuals including 107 low responders (HBsAb ?10 mIU/mL), 351 intermediate responders (10 mIU/mL< HBsAb <100 mIU/mL), and 735 high responders (HBsAb ?100 mIU/mL). Classical HLA class II alleles were statistically imputed using the genome-wide SNP typing data. GWAS identified independent associations of HLA-DRB1-DQB1 haplotypes, HLA-DPB1 alleles and BTNL2 gene with immune response to the HB vaccine designed based on the HBV genotype C. Five HLA-DRB1-DQB1 haplotypes and two DPB1 alleles showed significant associations with response to the HB vaccine in a comparison of three groups of 1,193 HB vaccinated individuals. When frequencies of DRB1-DQB1 haplotypes and DPB1 alleles were compared between low immune responders and HBV patients, significant associations were identified for three DRB1-DQB1 haplotypes, and no association was identified for any of DPB1 alleles. In contrast, no association for DRB1-DQB1 haplotypes and DPB1 alleles was identified in a comparison between high immune responders and healthy individuals. The findings in this study clearly show the importance of HLA-DR-DQ (i.e. recognition of a HB vaccine related HBsAg by specific DR-DQ haplotypes) and BTNL2 molecules (i.e. high immune response to the HB vaccine) for response to a HB vaccine designed based on the HBV genotype C.

  Study JGAS000341

• Comparison of capture-based method for transcriptome profiling of formalin-fixed paraffin embedded tumor samples

  Background: The need for fresh frozen (FF) tissue limits implementing RNA sequencing (RNA-seq) in the clinic. The majority of clinical samples are stored as formalin-fixed, paraffin-embedded (FFPE) tissues. Exome capture platforms have been developed for RNA-seq from FFPE samples. However, these methods have not been systematically compared. Methods: Transcriptomic analysis of 32 FFPE tumor samples from 11 patients was performed using three exome capture-based methods: Agilent SureSelect V6, TWIST NGS Exome, and IDT XGen Exome Research Panel. We compared these methods to TruSeq RNA-seq of fresh frozen (FF-TruSeq) tumor samples from the same patients. We assessed the recovery of clinically relevant biological features. Results: The Spearman's correlation coefficients between the global expression profiles of the three capture-based methods from FFPE and matched FF-TruSeq were high (rho = 0.72-0.9, p &lt; 0.05). A significant correlation between the expression of key immune genes between individual capture-based methods and FF-TruSeq (rho = 0.76-0.88, p &lt; 0.05) was observed. All exome capture-based methods reliably detected outlier expression of actionable genes, including ERBB2, MET, NTRK1, and PPARG. In urothelial cancer samples, the Agilent assay was associated with the highest molecular subtype concordance with FF-TruSeq (Cohen's k = 0.7, p &lt; 0.01). Both Agilent and IDT detected all the clinically relevant fusions that were initially identified in FF-TruSeq. Conclusion: All exome capture-based methods had comparable performance and concordance with FF-TruSeq. By enabling the interrogation of FFPE tumor samples, our findings will enable the implementation of RNA-seq in the clinic to guide precision oncology approaches.

  Study EGAS00001005255

• MiR expression profiles of paired primary colorectal cancerand metastases by next-generation sequencing

  MicroRNAs (miRs) have been recognized as promising biomarkers. It is unknown to what extent tumor-derived miRs aredifferentially expressed between primary colorectal cancers (pCRCs) and metastatic lesions, and to what extent the expressionprofiles of tumor tissue differ from the surrounding normal tissue. Next-generation sequencing (NGS) of 220 fresh-frozen samples,including paired primary and metastatic tumor tissue and non-tumorous tissue from 38 patients, revealed expression of 2245known unique mature miRs and 515 novel candidate miRs. Unsupervised clustering of miR expression profiles of pCRC tissue withpaired metastases did not separate the two entities, whereas unsupervised clustering of miR expression profiles of pCRC withnormal colorectal mucosa demonstrated complete separation of the tumor samples from their paired normal mucosa. Twohundred and twenty-two miRs differentiated both pCRC and metastases from normal tissue samples (false discovery rate (FDR)o0.05). The highest expressed tumor-specific miRs were miR-21 and miR-92a, both previously described to be involved in CRC withpotential as circulating biomarker for early detection. Only eight miRs, 0.5% of the analysed miR transcriptome, were differentiallyexpressed between pCRC and the corresponding metastases (FDR o0.1), consisting of five known miRs (miR-320b, miR-320d,miR-3117, miR-1246 and miR-663b) and three novel candidate miRs (chr 1-2552-5p, chr 8-20656-5p and chr 10-25333-3p). Theseresults indicate that previously unrecognized candidate miRs expressed in advanced CRC were identified using NGS. In addition,miR expression profiles of pCRC and metastatic lesions are highly comparable and may be of similar predictive value for prognosisor response to treatment in patients with advanced CRC

  Study EGAS00001001127

• DSRCT RNA genomic sequencing

  Purpose: To further understand the molecular pathogenesis of desmoplastic small round cell tumor (DSRCT), a rare but often fatal malignancy occurring primarily in young males, we used next-generation RNA sequencing to investigate the gene expression profiles intrinsic to this disease.Experimental Design: RNA from DSRCT tumor samples were obtained from the Cooperative Human Tissue Network biorepository. RNA sequencing was completed using the Illumina HiSeq 2000 system. Presence of the EWSR1-WT1 fusion was verified using both RNA-sequencing and PCR. Validation studies, including WT1 ChIP-seq, RNA sequencing, and EWS-WT1 knockdown experiments, were performed on an established DSRCT cell line, JN-DSRCT-1. Protein expression of clinically relevant genes determined by RNA sequencing was confirmed using immunohistochemistry. A panel of immune signature genes was also evaluated to identify possible immune therapeutic targets. Results: We analyzed the RNA from 14 tumor samples, of which two were confirmed negative for the diagnostic EWSR1-WT1 translocation. Principal component analysis of the sequencing data indicated that fusion-negative and fusion-positive tumors are transcriptionally distinct entities. Overlapping the significant ChIP-seq peaks with genes found to be highly expressed in the RNA sequencing data revealed that IGF2 and FGFR4 were both highly expressed, and targets of the EWS-WT1 fusion gene. This finding has potential clinical relevance for targeted therapeutic intervention. In addition, we identified the immune checkpoints CD200 and CD276 as potentially targetable genes whose expression is independent of the EWS-WT1 fusion gene in vitro.Conclusions: Despite the transcriptional complexity of this disease, we were able to identify IGF2, FGFR4, CD200, and CD276 as potential therapeutic targets for patients suffering from DSRCT.

  Study EGAS00001002770

• Immune microenvironment and lineage tracing help deciphering Rosette-forming GlioNeuronal Tumors: a multi-omic analysis of 9 cases

  Rosette-forming GlioNeuronal Tumor (RGNT) is a rare central nervous system neoplasm containing two components, glial and neuronal. The delineation of histological diagnosis of RGNT from similar low-grade tumors such as pilocytic astrocytoma (PA) and ganglioglioma (GG) may be challenging. We performed here a comprehensive molecular analysis of a cohort of tumors with same histology features to identify molecular characteristics of RGNT. A cohort of 9 rosette-forming tumors histologically-diagnosed were analyzed at molecular level using multimodal approaches as Whole Exome Sequencing (WES), RNAseq and methylome. In our cohort, 3 tumors were plotted within the Methylation Class-RGNT (MC-RGNT) characterized by FGFR1 mutation associated with PIK3CA or NF1 mutations. Transcriptome analysis was performed in 7 cases. RNAseq identified a “Hot” and a “Cold” transcriptomic group; the latter includes the 3 MC-RGNT and 1 MC-Pilocytic Astrocytoma and exhibited a “Cold” immune tumor microenvironment in comparison with the “Hot” group. The distinct immune cell content of both groups was confirmed by quantitative immunostainings. Get Set Enrichment Analysis showed that the “Cold” group had upregulated NOTCH pathway and mainly oligodendrocyte precursor cell and neuronal phenotypes while the “Hot” group exhibited predominantly astrocytic and neural stem cell phenotypes. In silico deconvolution identified the cerebellar granule cell lineage as a putative origin and as the cell context to understand the effects of genetic alterations and NOTCH signaling. Histological diagnosis of rosette-forming tumors encompasses heterogeneous tumor entities. Our study identified distinct tumor cell contexts and microenvironments as key features to better understand and manage these neoplasms.

  Study EGAS00001006502

• The data access committee for Evolution of neoantigen landscape during immune checkpoint blockade in non-small cell lung cancer.

  Dac EGAC00001000757

• Profiled samples in the study "Chromatin activation profiling of stereotyped chronic lymphocytic leukemias reveals a subset #8 specific signature"

  Dac EGAC00001002787

• Targeted resequencing of coding regions of ribosomal protein genes in multiple myeloma samples

  Dataset EGAD00001003302

• KDM4A regulates the maternal-to-zygotic transition by protecting broad H3K4me3 domains from H3K9me3 invasion in oocytes

  Study EGAS00001004220

• The transition from normal lung anatomy to minimal and established fibrosis in Idiopathic Pulmonary Fibrosis

  Study EGAS00001004758

• Targeting the Epichaperome As an Effective Precision Medicine Approach in a Novel PML-SYK Fusion Acute Myeloid Leukemia

  Study EGAS00001004992

• Impact of genetic variants in clinical outcome of a cohort of patients with oropharyngeal squamous cell carcinoma

  Study EGAS00001004430

• Deep MRD profiling defines outcome and unveils different modes of treatment resistance in standard and high risk myeloma

  Study EGAS00001004558

• The Genetic Basis of Preeclampsia in an Andean Population Adapted to High Altitude

  Study EGAS00001004625

• ATM germline variants in a young adult with chronic lymphocytic leukemia: 8 years of genomic evolution

  Study EGAS00001006268

• Longitudinal peripheral blood DNA methylation profiling of endoscopic response to tofacitinib in moderate-to-severe ulcerative colitis patients

  Study EGAS00001006968

• EGFR TARGETING IN GASTRO-ESOPHAGEAL CANCER

  WES ON GASTRO-ESOPHAGEAL TUMORS TO IDENTIFY BIOMARKERS OF RESPONSE TO EGFR INHIBITION

  Dac EGAC50000000562

• Olink CRS DAC

  DAC to regulate access to Olink targeted proteomics data in Chronic rhinosinusitis (CRS) patient cohort.

  Dac EGAC50000000547

• Persister cell phenotypes contribute to poor patient outcomes after neoadjuvant chemotherapy in PDAC (Hipo_015)

  Study EGAS00001007143

• Genetic drivers define transcriptomic characteristics and clonal hierarchy within intratumoral heterogeneity in adult T-cell leukemia-lymphoma

  Study JGAS000301

• OncoArray: Prostate Cancer

  Original description of the study: From ELLIPSE (linked to the PRACTICAL consortium), we contributed ~78,000 SNPs to the OncoArray. A large fraction of the content was derived from the GWAS meta-analyses in European ancestry populations (overall and aggressive disease; ~27K SNPs). We also selected just over 10,000 SNPs from the meta-analyses in the non-European populations, with a majority of these SNPs coming from the analysis of overall prostate cancer in African ancestry populations as well as from the multiethnic meta-analysis. A substantial fraction of SNPs (~28,000) were also selected for fine-mapping of 53 loci not included in the common fine-mapping regions (tagging at r2&#62;0.9 across &#177;500kb regions). We also selected a few thousand SNPs related with PSA levels and/or disease survival as well as SNPs from candidate lists provided by study collaborators, as well as from meta-analyses of exome SNP chip data from the Multiethnic Cohort and UK studies. The Contributing Studies: Aarhus: Hospital-based, Retrospective, Observational. Source of cases: Patients treated for prostate adenocarcinoma at Department of Urology, Aarhus University Hospital, Skejby (Aarhus, Denmark). Source of controls: Age-matched males treated for myocardial infarction or undergoing coronary angioplasty, but with no prostate cancer diagnosis based on information retrieved from the Danish Cancer Register and the Danish Cause of Death Register. AHS: Nested case-control study within prospective cohort. Source of cases: linkage to cancer registries in study states. Source of controls: matched controls from cohort ATBC: Prospective, nested case-control. Source of cases: Finnish male smokers aged 50-69 years at baseline. Source of controls: Finnish male smokers aged 50-69 years at baseline BioVu: Cases identified in a biobank linked to electronic health records. Source of cases: A total of 214 cases were identified in the VUMC de-identified electronic health records database (the Synthetic Derivative) and shipped to USC for genotyping in April 2014. The following criteria were used to identify cases: Age 18 or greater; male; African Americans (Black) only. Note that African ancestry is not self-identified, it is administratively or third-party assigned (which has been shown to be highly correlated with genetic ancestry for African Americans in BioVU; see references). Source of controls: Controls were identified in the de-identified electronic health record. Unfortunately, they were not age matched to the cases, and therefore cannot be used for this study. Canary PASS: Prospective, Multi-site, Observational Active Surveillance Study. Source of cases: clinic based from Beth Israel Deaconness Medical Center, Eastern Virginia Medical School, University of California at San Francisco, University of Texas Health Sciences Center San Antonio, University of Washington, VA Puget Sound. Source of controls: N/A CCI: Case series, Hospital-based. Source of cases: Cases identified through clinics at the Cross Cancer Institute. Source of controls: N/A CerePP French Prostate Cancer Case-Control Study (ProGene): Case-Control, Prospective, Observational, Hospital-based. Source of cases: Patients, treated in French departments of Urology, who had histologically confirmed prostate cancer. Source of controls: Controls were recruited as participating in a systematic health screening program and found unaffected (normal digital rectal examination and total PSA &#60; 4 ng/ml, or negative biopsy if PSA &#62; 4 ng/ml). COH: hospital-based cases and controls from outside. Source of cases: Consented prostate cancer cases at City of Hope. Source of controls: Consented unaffected males that were part of other studies where they consented to have their DNA used for other research studies. COSM: Population-based cohort. Source of cases: General population. Source of controls: General population CPCS1: Case-control - Denmark. Source of cases: Hospital referrals. Source of controls: Copenhagen General Population Study CPCS2: Source of cases: Hospital referrals. Source of controls: Copenhagen General Population Study CPDR: Retrospective cohort. Source of cases: Walter Reed National Military Medical Center. Source of controls: Walter Reed National Military Medical Center ACS_CPS-II: Nested case-control derived from a prospective cohort study. Source of cases: Identified through self-report on follow-up questionnaires and verified through medical records or cancer registries, identified through cancer registries or the National Death Index (with prostate cancer as the primary cause of death). Source of controls: Cohort participants who were cancer-free at the time of diagnosis of the matched case, also matched on age (&#177;6 mo) and date of biospecimen donation (&#177;6 mo). EPIC: Case-control - Germany, Greece, Italy, Netherlands, Spain, Sweden, UK. Source of cases: Identified through record linkage with population-based cancer registries in Italy, the Netherlands, Spain, Sweden and UK. In Germany and Greece, follow-up is active and achieved through checks of insurance records and cancer and pathology registries as well as via self-reported questionnaires; self-reported incident cancers are verified through medical records. Source of controls: Cohort participants without a diagnosis of cancer EPICAP: Case-control, Population-based, ages less than 75 years at diagnosis, H&#233;rault, France. Source of cases: Prostate cancer cases in all public hospitals and private urology clinics of d&#233;partement of H&#233;rault in France. Cases validation by the H&#233;rault Cancer Registry. Source of controls: Population-based controls, frequency age matched (5-year groups). Quotas by socio-economic status (SES) in order to obtain a distribution by SES among controls identical to the SES distribution among general population men, conditionally to age. ERSPC: Population-based randomized trial. Source of cases: Men with PrCa from screening arm ERSPC Rotterdam. Source of controls: Men without PrCa from screening arm ERSPC Rotterdam ESTHER: Case-control, Prospective, Observational, Population-based. Source of cases: Prostate cancer cases in all hospitals in the state of Saarland, from 2001-2003. Source of controls: Random sample of participants from routine health check-up in Saarland, in 2000-2002 FHCRC: Population-based, case-control, ages 35-74 years at diagnosis, King County, WA, USA. Source of cases: Identified through the Seattle-Puget Sound SEER cancer registry. Source of controls: Randomly selected, age-frequency matched residents from the same county as cases Gene-PARE: Hospital-based. Source of cases: Patients that received radiotherapy for treatment of prostate cancer. Source of controls: n/a Hamburg-Zagreb: Hospital-based, Prospective. Source of cases: Prostate cancer cases seen at the Department of Oncology, University Hospital Center Zagreb, Croatia. Source of controls: Population-based (Croatia), healthy men, older than 50, with no medical record of cancer, and no family history of cancer (1st &#38; 2nd degree relatives) HPFS: Nested case-control. Source of cases: Participants of the HPFS cohort. Source of controls: Participants of the HPFS cohort IMPACT: Observational. Source of cases: Carriers and non-carriers (with a known mutation in the family) of the BRCA1 and BRCA2 genes, aged between 40 and 69, who are undergoing prostate screening with annual PSA testing. This cohort has been diagnosed with prostate cancer during the study. Source of controls: Carriers and non-carriers (with a known mutation in the family) of the BRCA1 and BRCA2 genes, aged between 40 and 69, who are undergoing prostate screening with annual PSA testing. This cohort has not been diagnosed with prostate cancer during the study. IPO-Porto: Hospital-based. Source of cases: Early onset and/or familial prostate cancer. Source of controls: Blood donors Karuprostate: Case-control, Retrospective, Population-based. Source of cases: From FWI (Guadeloupe): 237 consecutive incident patients with histologically confirmed prostate cancer attending public and private urology clinics; From Democratic Republic of Congo: 148 consecutive incident patients with histologically confirmed prostate cancer attending the University Clinic of Kinshasa. Source of controls: From FWI (Guadeloupe): 277 controls recruited from men participating in a free systematic health screening program open to the general population; From Democratic Republic of Congo: 134 controls recruited from subjects attending the University Clinic of Kinshasa KULEUVEN: Hospital-based, Prospective, Observational. Source of cases: Prostate cancer cases recruited at the University Hospital Leuven. Source of controls: Healthy males with no history of prostate cancer recruited at the University Hospitals, Leuven. LAAPC: Subjects were participants in a population-based case-control study of aggressive prostate cancer conducted in Los Angeles County. Cases were identified through the Los Angeles County Cancer Surveillance Program rapid case ascertainment system. Eligible cases included African American, Hispanic, and non-Hispanic White men diagnosed with a first primary prostate cancer between January 1, 1999 and December 31, 2003. Eligible cases also had (a) prostatectomy with documented tumor extension outside the prostate, (b) metastatic prostate cancer in sites other than prostate, (c) needle biopsy of the prostate with Gleason grade &#8805;8, or (d) needle biopsy with Gleason grade 7 and tumor in more than two thirds of the biopsy cores. Eligible controls were men never diagnosed with prostate cancer, living in the same neighborhood as a case, and were frequency matched to cases on age (&#177; 5 y) and race/ethnicity. Controls were identified by a neighborhood walk algorithm, which proceeds through an obligatory sequence of adjacent houses or residential units beginning at a specific residence that has a specific geographic relationship to the residence where the case lived at diagnosis. Malaysia: Case-control. Source of cases: Patients attended the outpatient urology or uro-onco clinic at University Malaya Medical Center. Source of controls: Population-based, age matched (5-year groups), ascertained through electoral register, Subang Jaya, Selangor, Malaysia MCC-Spain: Case-control. Source of cases: Identified through the urology departments of the participating hospitals. Source of controls: Population-based, frequency age and region matched, ascertained through the rosters of the primary health care centers MCCS: Nested case-control, Melbourne, Victoria. Source of cases: Identified by linkage to the Victorian Cancer Registry. Source of controls: Cohort participants without a diagnosis of cancer MD Anderson: Participants in this study were identified from epidemiological prostate cancer studies conducted at the University of Texas MD Anderson Cancer Center in the Houston Metropolitan area. Cases were accrued in the Houston Medical Center and were not restricted with respect to Gleason score, stage or PSA. Controls were identified via random-digit-dialing or among hospital visitors and they were frequency matched to cases on age and race. Lifestyle, demographic, and family history data were collected using a standardized questionnaire. MDACC_AS: A prospective cohort study. Source of cases: Men with clinically organ-confined prostate cancer meeting eligibility criteria for a prospective cohort study of active surveillance at MD Anderson Cancer Center. Source of controls: N/A MEC: The Multiethnic Cohort (MEC) is comprised of over 215,000 men and women recruited from Hawaii and the Los Angeles area between 1993 and 1996. Between 1995 and 2006, over 65,000 blood samples were collected from participants for genetic analyses. To identify incident cancer cases, the MEC was cross-linked with the population-based Surveillance, Epidemiology and End Results (SEER) registries in California and Hawaii, and unaffected cohort participants with blood samples were selected as controls MIAMI (WFPCS): Prostate cancer cases and controls were recruited from the Departments of Urology and Internal Medicine of the Wake Forest University School of Medicine using sequential patient populations as described previously (PMID:15342424). All study subjects received a detailed description of the study protocol and signed their informed consent, as approved by the medical center&#39;s Institutional Review Board. The general eligibility criteria were (i) able to comprehend informed consent and (ii) without previously diagnosed cancer. The exclusion criteria were (i) clinical diagnosis of autoimmune diseases; (ii) chronic inflammatory conditions; and (iii) infections within the past 6 weeks. Blood samples were collected from all subjects. MOFFITT: Hospital-based. Source of cases: clinic based from Moffitt Cancer Center. Source of controls: Moffitt Cancer Center affiliated Lifetime cancer screening center NMHS: Case-control, clinic based, Nashville TN. Source of cases: All urology clinics in Nashville, TN. Source of controls: Men without prostate cancer at prostate biopsy. PCaP: The North Carolina-Louisiana Prostate Cancer Project (PCaP) is a multidisciplinary population-based case-only study designed to address racial differences in prostate cancer through a comprehensive evaluation of social, individual and tumor level influences on prostate cancer aggressiveness. PCaP enrolled approximately equal numbers of African Americans and Caucasian Americans with newly-diagnosed prostate cancer from North Carolina (42 counties) and Louisiana (30 parishes) identified through state tumor registries. African American PCaP subjects with DNA, who agreed to future use of specimens for research, participated in OncoArray analysis. PCMUS: Case-control - Sofia, Bulgaria. Source of cases: Patients of Clinic of Urology, Alexandrovska University Hospital, Sofia, Bulgaria, PrCa histopathologically confirmed. Source of controls: 72 patients with verified BPH and PSA&#60;3,5; 78 healthy controls from the MMC Biobank, no history of PrCa PHS: Nested case-control. Source of cases: Participants of the PHS1 trial/cohort. Source of controls: Participants of the PHS1 trial/cohort PLCO: Nested case-control. Source of cases: Men with a confirmed diagnosis of prostate cancer from the PLCO Cancer Screening Trial. Source of controls: Controls were men enrolled in the PLCO Cancer Screening Trial without a diagnosis of cancer at the time of case ascertainment. Poland: Case-control. Source of cases: men with unselected prostate cancer, diagnosed in north-western Poland at the University Hospital in Szczecin. Source of controls: cancer-free men from the same population, taken from the healthy adult patients of family doctors in the Szczecin region PROCAP: Population-based, Retrospective, Observational. Source of cases: Cases were ascertained from the National Prostate Cancer Register of Sweden Follow-Up Study, a retrospective nationwide cohort study of patients with localized prostate cancer. Source of controls: Controls were selected among men referred for PSA testing in laboratories in Stockholm County, Sweden, between 2010 and 2012. PROGReSS: Hospital-based, Prospective, Observational. Source of cases: Prostate cancer cases from the Hospital Cl&#237;nico Universitario de Santiago de Compostela, Galicia, Spain. Source of controls: Cancer-free men from the same population ProMPT: A study to collect samples and data from subjects with and without prostate cancer. Retrospective, Experimental. Source of cases: Subjects attending outpatient clinics in hospitals. Source of controls: Subjects attending outpatient clinics in hospitals ProtecT: Trial of treatment. Samples taken from subjects invited for PSA testing from the community at nine centers across United Kingdom. Source of cases: Subjects who have a proven diagnosis of prostate cancer following testing. Source of controls: Identified through invitation of subjects in the community. PROtEuS: Case-control, population-based. Source of cases: All new histologically-confirmed cases, aged less or equal to 75 years, diagnosed between 2005 and 2009, actively ascertained across Montreal French hospitals. Source of controls: Randomly selected from the Provincial electoral list of French-speaking men between 2005 and 2009, from the same area of residence as cases and frequency-matched on age. QLD: Case-control. Source of cases: A longitudinal cohort study (Prostate Cancer Supportive Care and Patient Outcomes Project: ProsCan) conducted in Queensland, through which men newly diagnosed with prostate cancer from 26 private practices and 10 public hospitals were directly referred to ProsCan at the time of diagnosis by their treating clinician (age range 43-88 years). All cases had histopathologically confirmed prostate cancer, following presentation with an abnormal serum PSA and/or lower urinary tract symptoms. Source of controls: Controls comprised healthy male blood donors with no personal history of prostate cancer, recruited through (i) the Australian Red Cross Blood Services in Brisbane (age range 19-76 years) and (ii) the Australian Electoral Commission (AEC) (age and post-code/ area matched to ProsCan, age range 54-90 years). RAPPER: Multi-centre, hospital based blood sample collection study in patients enrolled in clinical trials with prospective collection of radiotherapy toxicity data. Source of cases: Prostate cancer patients enrolled in radiotherapy trials: CHHiP, RT01, Dose Escalation, RADICALS, Pelvic IMRT, PIVOTAL. Source of controls: N/A SABOR: Prostate Cancer Screening Cohort. Source of cases: Men &#62;45 yrs of age participating in annual PSA screening. Source of controls: Males participating in annual PSA prostate cancer risk evaluations (funded by NCI biomarkers discovery and validation grant), recruited through University of Texas Health Science Center at San Antonio and affiliated sites or through study advertisements, enrolment open to the community SCCS: Case-control in cohort, Southeastern USA. Prospective, Observational, Population-based. Source of cases: SCCS entry population. Source of controls: SCCS entry population SCPCS: Population-based, Retrospective, Observational. Source of cases: South Carolina Central Cancer Registry. Source of controls: Health Care Financing Administration beneficiary file SEARCH: Case-control - East Anglia, UK. Source of cases: Men &#60; 70 years of age registered with prostate cancer at the population-based cancer registry, Eastern Cancer Registration and Information Centre, East Anglia, UK. Source of controls: Men attending general practice in East Anglia with no known prostate cancer diagnosis, frequency matched to cases by age and geographic region SNP_Prostate_Ghent: Hospital-based, Retrospective, Observational. Source of cases: Men treated with IMRT as primary or postoperative treatment for prostate cancer at the Ghent University Hospital between 2000 and 2010. Source of controls: Employees of the University hospital and members of social activity clubs, without a history of any cancer. SPAG: Hospital-based, Retrospective, Observational. Source of cases: Guernsey. Source of controls: Guernsey STHM2: Population-based, Retrospective, Observational. Source of cases: Cases were selected among men referred for PSA testing in laboratories in Stockholm County, Sweden, between 2010 and 2012. Source of controls: Controls were selected among men referred for PSA testing in laboratories in Stockholm County, Sweden, between 2010 and 2012. PCPT: Case-control from a randomized clinical trial. Source of cases: Randomized clinical trial. Source of controls: Randomized clinical trial SELECT: Case-cohort from a randomized clinical trial. Source of cases: Randomized clinical trial. Source of controls: Randomized clinical trial TAMPERE: Case-control - Finland, Retrospective, Observational, Population-based. Source of cases: Identified through linkage to the Finnish Cancer Registry and patient records; and the Finnish arm of the ERSPC study. Source of controls: Cohort participants without a diagnosis of cancer UGANDA: Uganda Prostate Cancer Study: Uganda is a case-control study of prostate cancer in Kampala Uganda that was initiated in 2011. Men with prostate cancer were enrolled from the Urology unit at Mulago Hospital and men without prostate cancer (i.e. controls) were enrolled from other clinics (i.e. surgery) at the hospital. UKGPCS: ICR, UK. Source of cases: Cases identified through clinics at the Royal Marsden hospital and nationwide NCRN hospitals. Source of controls: Ken Muir&#39;s control- 2000 ULM: Case-control - Germany. Source of cases: familial cases (n=162): identified through questionnaires for family history by collaborating urologists all over Germany; sporadic cases (n=308): prostatectomy series performed in the Clinic of Urology Ulm between 2012 and 2014. Source of controls: age-matched controls (n=188): age-matched men without prostate cancer and negative family history collected in hospitals of Ulm WUGS/WUPCS: Cases Series, USA. Source of cases: Identified through clinics at Washington University in St. Louis. Source of controls: Men diagnosed and managed with prostate cancer in University based clinic. Acknowledgement Statements: Aarhus: This study was supported by the Danish Strategic Research Council (now Innovation Fund Denmark) and the Danish Cancer Society. The Danish Cancer Biobank (DCB) is acknowledged for biological material. AHS: This work was supported by the Intramural Research Program of the NIH, National Cancer Institute, Division of Cancer Epidemiology and Genetics (Z01CP010119). ATBC: This research was supported in part by the Intramural Research Program of the NIH and the National Cancer Institute. Additionally, this research was supported by U.S. Public Health Service contracts N01-CN-45165, N01-RC-45035, N01-RC-37004, HHSN261201000006C, and HHSN261201500005C from the National Cancer Institute, Department of Health and Human Services. BioVu: The dataset(s) used for the analyses described were obtained from Vanderbilt University Medical Center&#39;s BioVU which is supported by institutional funding and by the National Center for Research Resources, Grant UL1 RR024975-01 (which is now at the National Center for Advancing Translational Sciences, Grant 2 UL1 TR000445-06). Canary PASS: PASS was supported by Canary Foundation and the National Cancer Institute&#39;s Early Detection Research Network (U01 CA086402) CCI: This work was awarded by Prostate Cancer Canada and is proudly funded by the Movember Foundation - Grant # D2013-36.The CCI group would like to thank David Murray, Razmik Mirzayans, and April Scott for their contribution to this work. CerePP French Prostate Cancer Case-Control Study (ProGene): None reported COH: SLN is partially supported by the Morris and Horowitz Families Endowed Professorship COSM: The Swedish Research Council, the Swedish Cancer Foundation CPCS1 &#38; CPCS2: Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev Ringvej 75, DK-2730 Herlev, DenmarkCPCS1 would like to thank the participants and staff of the Copenhagen General Population Study for their important contributions. CPDR: Uniformed Services University for the Health Sciences HU0001-10-2-0002 (PI: David G. McLeod, MD) CPS-II: The American Cancer Society funds the creation, maintenance, and updating of the Cancer Prevention Study II cohort. CPS-II thanks the participants and Study Management Group for their invaluable contributions to this research. We would also like to acknowledge the contribution to this study from central cancer registries supported through the Centers for Disease Control and Prevention National Program of Cancer Registries, and cancer registries supported by the National Cancer Institute Surveillance Epidemiology and End Results program. EPIC: The coordination of EPIC is financially supported by the European Commission (DG-SANCO) and the International Agency for Research on Cancer. The national cohorts are supported by the Danish Cancer Society (Denmark); the Deutsche Krebshilfe, Deutsches Krebsforschungszentrum and Federal Ministry of Education and Research (Germany); the Hellenic Health Foundation, Greek Ministry of Health; Greek Ministry of Education (Greece); the Italian Association for Research on Cancer (AIRC) and National Research Council (Italy); the Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF); the Statistics Netherlands (The Netherlands); the Health Research Fund (FIS), Regional Governments of Andaluc&#237;a, Asturias, Basque Country, Murcia and Navarra, Spanish Ministry of Health ISCIII RETIC (RD06/0020), Red de Centros RCESP, C03/09 (Spain); the Swedish Cancer Society, Swedish Scientific Council and Regional Government of Sk&#229;ne and V&#228;sterbotten, Fundacion Federico SA (Sweden); the Cancer Research UK, Medical Research Council (United Kingdom). EPICAP: The EPICAP study was supported by grants from Ligue Nationale Contre le Cancer, Ligue d&#233;partementale du Val de Marne; Fondation de France; Agence Nationale de s&#233;curit&#233; sanitaire de l&#39;alimentation, de l&#39;environnement et du travail (ANSES). The EPICAP study group would like to thank all urologists, Antoinette Anger and Hasina Randrianasolo (study monitors), Anne-Laure Astolfi, Coline Bernard, Oriane Noyer, Marie-H&#233;l&#232;ne De Campo, Sandrine Margaroline, Louise N&#39;Diaye, and Sabine Perrier-Bonnet (Clinical Research nurses). ERSPC: This study was supported by the DutchCancerSociety (KWF94-869,98-1657,2002-277,2006-3518, 2010-4800), The Netherlands Organisation for Health Research and Development (ZonMW-002822820, 22000106, 50-50110-98-311, 62300035), The Dutch Cancer Research Foundation (SWOP), and an unconditional grant from Beckman-Coulter-HybritechInc. ESTHER: The ESTHER study was supported by a grant from the Baden W&#252;rttemberg Ministry of Science, Research and Arts. The ESTHER group would like to thank Hartwig Ziegler, Sonja Wolf, Volker Hermann, Heiko M&#252;ller, Karina Dieffenbach, Katja Butterbach for valuable contributions to the study. FHCRC: The FHCRC studies were supported by grants R01-CA056678, R01-CA082664, and R01-CA092579 from the US National Cancer Institute, National Institutes of Health, with additional support from the Fred Hutchinson Cancer Research Center. FHCRC would like to thank all the men who participated in these studies. Gene-PARE: The Gene-PARE study was supported by grants 1R01CA134444 from the U.S. National Institutes of Health, PC074201 and W81XWH-15-1-0680 from the Prostate Cancer Research Program of the Department of Defense and RSGT-05-200-01-CCE from the American Cancer Society. Hamburg-Zagreb: None reported HPFS: The Health Professionals Follow-up Study was supported by grants UM1CA167552, CA133891, CA141298, and P01CA055075. HPFS are grateful to the participants and staff of the Physicians&#39; Health Study and Health Professionals Follow-Up Study for their valuable contributions, as well as the following state cancer registries for their help: AL, AZ, AR, CA, CO, CT, DE, FL, GA, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, and WY. IMPACT: The IMPACT study was funded by The Ronald and Rita McAulay Foundation, CR-UK Project grant (C5047/A1232), Cancer Australia, AICR Netherlands A10-0227, Cancer Australia and Cancer Council Tasmania, NIHR, EU Framework 6, Cancer Councils of Victoria and South Australia, and Philanthropic donation to Northshore University Health System. We acknowledge support from the National Institute for Health Research (NIHR) to the Biomedical Research Centre at The Institute of Cancer Research and Royal Marsden Foundation NHS Trust. IMPACT acknowledges the IMPACT study steering committee, collaborating centres, and participants. IPO-Porto: The IPO-Porto study was funded by Funda&#231;&#228;o para a Ci&#234;ncia e a Tecnologia (FCT; UID/DTP/00776/2013 and PTDC/DTP-PIC/1308/2014) and by IPO-Porto Research Center (CI-IPOP-16-2012 and CI-IPOP-24-2015). MC and MPS are research fellows from Liga Portuguesa Contra o Cancro, N&#250;cleo Regional do Norte. SM is a research fellow from FCT (SFRH/BD/71397/2010). IPO-Porto would like to express our gratitude to all patients and families who have participated in this study. Karuprostate: The Karuprostate study was supported by the the Frech National Health Directorate and by the Association pour la Recherche sur les Tumeurs de la ProstateKarusprostate thanks S&#233;verine Ferdinand. KULEUVEN: F.C. and S.J. are holders of grants from FWO Vlaanderen (G.0684.12N and G.0830.13N), the Belgian federal government (National Cancer Plan KPC_29_023), and a Concerted Research Action of the KU Leuven (GOA/15/017). TVDB is holder of a doctoral fellowship of the FWO. LAAPC: This study was funded by grant R01CA84979 (to S.A. Ingles) from the National Cancer Institute, National Institutes of Health. Malaysia: The study was funded by the University Malaya High Impact Research Grant (HIR/MOHE/MED/35). Malaysia thanks all associates in the Urology Unit, University of Malaya, Cancer Research Initiatives Foundation (CARIF) and the Malaysian Men&#39;s Health Initiative (MMHI). MCCS: MCCS cohort recruitment was funded by VicHealth and Cancer Council Victoria. The MCCS was further supported by Australian NHMRC grants 209057, 251553, and 504711, and by infrastructure provided by Cancer Council Victoria. Cases and their vital status were ascertained through the Victorian Cancer Registry (VCR) and the Australian Institute of Health and Welfare (AIHW), including the National Death Index and the Australian Cancer Database. MCC-Spain: The study was partially funded by the Accion Transversal del Cancer, approved on the Spanish Ministry Council on the 11th October 2007, by the Instituto de Salud Carlos III-FEDER (PI08/1770, PI09/00773-Cantabria, PI11/01889-FEDER, PI12/00265, PI12/01270, and PI12/00715), by the Fundaci&#243;n Marqu&#233;s de Valdecilla (API 10/09), by the Spanish Association Against Cancer (AECC) Scientific Foundation and by the Catalan Government DURSI grant 2009SGR1489. Samples: Biological samples were stored at the Parc de Salut MAR Biobank (MARBiobanc; Barcelona) which is supported by Instituto de Salud Carlos III FEDER (RD09/0076/00036). Also sample collection was supported by the Xarxa de Bancs de Tumors de Catalunya sponsored by Pla Director d&#39;Oncologia de Catalunya (XBTC). MCC-Spain acknowledges the contribution from Esther Gracia-Lavedan in preparing the data. We thank all the subjects who participated in the study and all MCC-Spain collaborators. MD Anderson: Prostate Cancer Case-Control Studies at MD Anderson (MDA) supported by grants CA68578, ES007784, DAMD W81XWH-07-1-0645, and CA140388. MDACC_AS: None reported MEC: Funding provided by NIH grant U19CA148537 and grant U01CA164973. MIAMI (WFPCS): ACS MOFFITT: The Moffitt group was supported by the US National Cancer Institute (R01CA128813, PI: J.Y. Park). NMHS: Funding for the Nashville Men&#39;s Health Study (NMHS) was provided by the National Institutes of Health Grant numbers: RO1CA121060. PCaP only data: The North Carolina - Louisiana Prostate Cancer Project (PCaP) is carried out as a collaborative study supported by the Department of Defense contract DAMD 17-03-2-0052. For HCaP-NC follow-up data: The Health Care Access and Prostate Cancer Treatment in North Carolina (HCaP-NC) study is carried out as a collaborative study supported by the American Cancer Society award RSGT-08-008-01-CPHPS. For studies using both PCaP and HCaP-NC follow-up data please use: The North Carolina - Louisiana Prostate Cancer Project (PCaP) and the Health Care Access and Prostate Cancer Treatment in North Carolina (HCaP-NC) study are carried out as collaborative studies supported by the Department of Defense contract DAMD 17-03-2-0052 and the American Cancer Society award RSGT-08-008-01-CPHPS, respectively. For any PCaP data, please include: The authors thank the staff, advisory committees and research subjects participating in the PCaP study for their important contributions. For studies using PCaP DNA/genotyping data, please include: We would like to acknowledge the UNC BioSpecimen Facility and LSUHSC Pathology Lab for our DNA extractions, blood processing, storage and sample disbursement (https://genome.unc.edu/bsp). For studies using PCaP tissue, please include: We would like to acknowledge the RPCI Department of Urology Tissue Microarray and Immunoanalysis Core for our tissue processing, storage and sample disbursement. For studies using HCaP-NC follow-up data, please use: The Health Care Access and Prostate Cancer Treatment in North Carolina (HCaP-NC) study is carried out as a collaborative study supported by the American Cancer Society award RSGT-08-008-01-CPHPS. The authors thank the staff, advisory committees and research subjects participating in the HCaP-NC study for their important contributions. For studies that use both PCaP and HCaP-NC, please use: The authors thank the staff, advisory committees and research subjects participating in the PCaP and HCaP-NC studies for their important contributions. PCMUS: The PCMUS study was supported by the Bulgarian National Science Fund, Ministry of Education and Science (contract DOO-119/2009; DUNK01/2-2009; DFNI-B01/28/2012) with additional support from the Science Fund of Medical University - Sofia (contract 51/2009; 8I/2009; 28/2010). PHS: The Physicians&#39; Health Study was supported by grants CA34944, CA40360, CA097193, HL26490, and HL34595. PHS members are grateful to the participants and staff of the Physicians&#39; Health Study and Health Professionals Follow-Up Study for their valuable contributions, as well as the following state cancer registries for their help: AL, AZ, AR, CA, CO, CT, DE, FL, GA, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, and WY. PLCO: This PLCO study was supported by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHPLCO thanks Drs. Christine Berg and Philip Prorok, Division of Cancer Prevention at the National Cancer Institute, the screening center investigators and staff of the PLCO Cancer Screening Trial for their contributions to the PLCO Cancer Screening Trial. We thank Mr. Thomas Riley, Mr. Craig Williams, Mr. Matthew Moore, and Ms. Shannon Merkle at Information Management Services, Inc., for their management of the data and Ms. Barbara O&#39;Brien and staff at Westat, Inc. for their contributions to the PLCO Cancer Screening Trial. We also thank the PLCO study participants for their contributions to making this study possible. Poland: None reported PROCAP: PROCAP was supported by the Swedish Cancer Foundation (08-708, 09-0677). PROCAP thanks and acknowledges all of the participants in the PROCAP study. We thank Carin Cavalli-Bj&#246;rkman and Ami R&#246;nnberg Karlsson for their dedicated work in the collection of data. Michael Broms is acknowledged for his skilful work with the databases. KI Biobank is acknowledged for handling the samples and for DNA extraction. We acknowledge The NPCR steering group: P&#228;r Stattin (chair), Anders Widmark, Stefan Karlsson, Magnus T&#246;rnblom, Jan Adolfsson, Anna Bill-Axelson, Ove Andr&#233;n, David Robinson, Bill Pettersson, Jonas Hugosson, Jan-Erik Damber, Ola Bratt, G&#246;ran Ahlgren, Lars Egevad, and Roy Ehrnstr&#246;m. PROGReSS: The PROGReSS study is founded by grants from the Spanish Ministry of Health (INT15/00070; INT16/00154; FIS PI10/00164, FIS PI13/02030; FIS PI16/00046); the Spanish Ministry of Economy and Competitiveness (PTA2014-10228-I), and Fondo Europeo de Desarrollo Regional (FEDER 2007-2013). ProMPT: Founded by CRUK, NIHR, MRC, Cambride Biomedical Research Centre ProtecT: Founded by NIHR. ProtecT and ProMPT would like to acknowledge the support of The University of Cambridge, Cancer Research UK. Cancer Research UK grants (C8197/A10123) and (C8197/A10865) supported the genotyping team. We would also like to acknowledge the support of the National Institute for Health Research which funds the Cambridge Bio-medical Research Centre, Cambridge, UK. We would also like to acknowledge the support of the National Cancer Research Prostate Cancer: Mechanisms of Progression and Treatment (PROMPT) collaborative (grant code G0500966/75466) which has funded tissue and urine collections in Cambridge. We are grateful to staff at the Welcome Trust Clinical Research Facility, Addenbrooke&#39;s Clinical Research Centre, Cambridge, UK for their help in conducting the ProtecT study. We also acknowledge the support of the NIHR Cambridge Biomedical Research Centre, the DOH HTA (ProtecT grant), and the NCRI/MRC (ProMPT grant) for help with the bio-repository. The UK Department of Health funded the ProtecT study through the NIHR Health Technology Assessment Programme (projects 96/20/06, 96/20/99). The ProtecT trial and its linked ProMPT and CAP (Comparison Arm for ProtecT) studies are supported by Department of Health, England; Cancer Research UK grant number C522/A8649, Medical Research Council of England grant number G0500966, ID 75466, and The NCRI, UK. The epidemiological data for ProtecT were generated though funding from the Southwest National Health Service Research and Development. DNA extraction in ProtecT was supported by USA Dept of Defense award W81XWH-04-1-0280, Yorkshire Cancer Research and Cancer Research UK. The authors would like to acknowledge the contribution of all members of the ProtecT study research group. The views and opinions expressed therein are those of the authors and do not necessarily reflect those of the Department of Health of England. The bio-repository from ProtecT is supported by the NCRI (ProMPT) Prostate Cancer Collaborative and the Cambridge BMRC grant from NIHR. We thank the National Institute for Health Research, Hutchison Whampoa Limited, the Human Research Tissue Bank (Addenbrooke&#39;s Hospital), and Cancer Research UK. PROtEuS: PROtEuS was supported financially through grants from the Canadian Cancer Society (13149, 19500, 19864, 19865) and the Cancer Research Society, in partnership with the Minist&#232;re de l&#39;enseignement sup&#233;rieur, de la recherche, de la science et de la technologie du Qu&#233;bec, and the Fonds de la recherche du Qu&#233;bec - Sant&#233;.PROtEuS would like to thank its collaborators and research personnel, and the urologists involved in subjects recruitment. We also wish to acknowledge the special contribution made by Ann Hsing and Anand Chokkalingam to the conception of the genetic component of PROtEuS. QLD: The QLD research is supported by The National Health and Medical Research Council (NHMRC) Australia Project Grants (390130, 1009458) and NHMRC Career Development Fellowship and Cancer Australia PdCCRS funding to J Batra. The QLD team would like to acknowledge and sincerely thank the urologists, pathologists, data managers and patient participants who have generously and altruistically supported the QLD cohort. RAPPER: RAPPER is funded by Cancer Research UK (C1094/A11728; C1094/A18504) and Experimental Cancer Medicine Centre funding (C1467/A7286). The RAPPER group thank Rebecca Elliott for project management. SABOR: The SABOR research is supported by NIH/NCI Early Detection Research Network, grant U01 CA0866402-12. Also supported by the Cancer Center Support Grant to the Cancer Therapy and Research Center from the National Cancer Institute (US) P30 CA054174. SCCS: SCCS is funded by NIH grant R01 CA092447, and SCCS sample preparation was conducted at the Epidemiology Biospecimen Core Lab that is supported in part by the Vanderbilt-Ingram Cancer Center (P30 CA68485). Data on SCCS cancer cases used in this publication were provided by the Alabama Statewide Cancer Registry; Kentucky Cancer Registry, Lexington, KY; Tennessee Department of Health, Office of Cancer Surveillance; Florida Cancer Data System; North Carolina Central Cancer Registry, North Carolina Division of Public Health; Georgia Comprehensive Cancer Registry; Louisiana Tumor Registry; Mississippi Cancer Registry; South Carolina Central Cancer Registry; Virginia Department of Health, Virginia Cancer Registry; Arkansas Department of Health, Cancer Registry, 4815 W. Markham, Little Rock, AR 72205. The Arkansas Central Cancer Registry is fully funded by a grant from National Program of Cancer Registries, Centers for Disease Control and Prevention (CDC). Data on SCCS cancer cases from Mississippi were collected by the Mississippi Cancer Registry which participates in the National Program of Cancer Registries (NPCR) of the Centers for Disease Control and Prevention (CDC). The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the CDC or the Mississippi Cancer Registry. SCPCS: SCPCS is funded by CDC grant S1135-19/19, and SCPCS sample preparation was conducted at the Epidemiology Biospecimen Core Lab that is supported in part by the Vanderbilt-Ingram Cancer Center (P30 CA68485). SEARCH: SEARCH is funded by a program grant from Cancer Research UK (C490/A10124) and supported by the UK National Institute for Health Research Biomedical Research Centre at the University of Cambridge. SNP_Prostate_Ghent: The study was supported by the National Cancer Plan, financed by the Federal Office of Health and Social Affairs, Belgium. SPAG: Wessex Medical ResearchHope for Guernsey, MUG, HSSD, MSG, Roger Allsopp STHM2: STHM2 was supported by grants from The Strategic Research Programme on Cancer (StratCan), Karolinska Institutet; the Linn&#233; Centre for Breast and Prostate Cancer (CRISP, number 70867901), Karolinska Institutet; The Swedish Research Council (number K2010-70X-20430-04-3) and The Swedish Cancer Society (numbers 11-0287 and 11-0624); Stiftelsen Johanna Hagstrand och Sigfrid Linn&#233;rs minne; Swedish Council for Working Life and Social Research (FAS), number 2012-0073STHM2 acknowledges the Karolinska University Laboratory, Aleris Medilab, Unilabs and the Regional Prostate Cancer Registry for performing analyses and help to retrieve data. Carin Cavalli-Bj&#246;rkman and Britt-Marie Hune for their enthusiastic work as research nurses. Astrid Bj&#246;rklund for skilful data management. We wish to thank the BBMRI.se biobank facility at Karolinska Institutet for biobank services. PCPT &#38; SELECT are funded by Public Health Service grants U10CA37429 and 5UM1CA182883 from the National Cancer Institute. SWOG and SELECT thank the site investigators and staff and, most importantly, the participants who donated their time to this trial. TAMPERE: The Tampere (Finland) study was supported by the Academy of Finland (251074), The Finnish Cancer Organisations, Sigrid Juselius Foundation, and the Competitive Research Funding of the Tampere University Hospital (X51003). The PSA screening samples were collected by the Finnish part of ERSPC (European Study of Screening for Prostate Cancer). TAMPERE would like to thank Riina Liikanen, Liisa Maeaettaenen and Kirsi Talala for their work on samples and databases. UGANDA: None reported UKGPCS: UKGPCS would also like to thank the following for funding support: The Institute of Cancer Research and The Everyman Campaign, The Prostate Cancer Research Foundation, Prostate Research Campaign UK (now Prostate Action), The Orchid Cancer Appeal, The National Cancer Research Network UK, The National Cancer Research Institute (NCRI) UK. We are grateful for support of NIHR funding to the NIHR Biomedical Research Centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust. UKGPCS should also like to acknowledge the NCRN nurses, data managers, and consultants for their work in the UKGPCS study. UKGPCS would like to thank all urologists and other persons involved in the planning, coordination, and data collection of the study. ULM: The Ulm group received funds from the German Cancer Aid (Deutsche Krebshilfe). WUGS/WUPCS: WUGS would like to thank the following for funding support: The Anthony DeNovi Fund, the Donald C. McGraw Foundation, and the St. Louis Men&#39;s Group Against Cancer.

  Study phs001391

• BLUE CORAL: Biology and Longitudinal Epidemiology of PETAL COVID-19 Observational Study

  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: Long Term Follow-up data has been added with version 2. Biospecimens: Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from PETAL BLUE CORAL include: Bronchial Lavage, Plasma, Tracheal Aspirate, Urine, Whole Blood Buffy Coat, DNA, Plasma, Serum, Urine, and Whole Blood. Please note that use of biospecimens is tiered for both non-genetic and genetic research.Objectives: To measure the incidence and changes over time in symptoms, disability, and financial status after COVID-19&#8211;related hospitalization.Background: For many individuals, the effects of COVID-19 persist after the acute phase and result in prolonged symptoms and disability. This has led to widespread efforts to characterize the epidemiologic characteristics of such post-COVID-19 sequelae. However, accurate data were limited, hindering the ability to counsel patients, caregivers, and policy makers and to plan relevant recovery-focused clinical research. Thus, the BLUE CORAL study was intended to address the knowledge gaps and provide critical data to help guide clinical care, public health, and scientific efforts.Participants: A total of 1376 COVID-19 patents were enrolled, with 825 (444 male, and 379 female) that completed at least one follow-up survey.A subset of the BLUE CORAL adult participants were enrolled in the extension study, FIRE CORAL. FIRE CORAL was a multicenter prospective cohort study of participants recovering from COVID-19 disease after discharge from the hospital. Design: BLUE CORAL was a prospective cohort study. Participants were enrolled between August 24, 2020, and July 20, 2021, with follow-up occurring through March 30, 2022. Posthospital surveys were administered by trained interviewers in English or Spanish to patients or their proxies at 1, 3, and 6 months after enrollment. Cardiopulmonary symptoms were assessed using the Airways Questionnaire 20, the Kansas City Cardiomyopathy Questionnaire, and the Seattle Angina Questionnaire. Fatigue was assessed using the Patient Health Questionnaire-9. Disability was assessed by self-report of limitations in activities of daily living (ADLs) or instrumental activities of daily living (IADLs). Financial problems were assessed using the World Health Organization Disability Assessment Schedule 2.0 question and questions regarding job changes, time off work, and insurance coverage developed with the Mi-COVID-19 study using qualitative interviews. Quality of life was measured using the European Quality of Life 5-dimension 5-level instrument.The primary outcomes were new or worsened cardiopulmonary symptoms, financial problems, functional impairments, perceived return to baseline health, and quality of life. Symptoms that were not present before hospitalization or specifically reported as increased in severity were counted as new or worsened. Conclusions: The findings of this cohort study of people discharged after COVID-19 hospitalization suggest that recovery in symptoms, functional status, and fatigue was limited at 6 months, and some participants reported new problems 6 months after hospital discharge.

  Study phs003419

• Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT-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. ObjectivesHypertension Study: To determine whether treatment with a calcium channel blocker or an angiotensin-converting enzyme inhibitor lowers the incidence of coronary heart disease (CHD) or other cardiovascular disease (CVD) events vs treatment with a diuretic.Lipid Study: To determine whether pravastatin compared with usual care reduces all-cause mortality in older, moderately hypercholesterolemic, hypertensive participants with at least an additional CHD risk factor. BackgroundHypertension Study: Antihypertensive therapy is well established to reduce hypertension-related morbidity and mortality, but the optimal first-step therapy is unknown.Lipid Study: Studies have demonstrated that statins administered to individuals with risk factors for coronary heart disease (CHD) reduce CHD events. However, many of these studies were too small to assess all-cause mortality or outcomes in important subgroups.ParticipantsHypertension Study: A total of 33,357 participants. Lipid Study: A total of 10,355 participants. Baseline mean total cholesterol was 224 mg/dL; LDL-C, 146 mg/dL; high-density lipoprotein cholesterol, 48 mg/dL; and triglycerides, 152 mg/dL. Mean age was 66 years; 49% were women, 38% black and 23% Hispanic, 14% had a history of CHD, and 35% had type 2 diabetes. DesignHypertension Study: A randomized, double-blind, active-controlled clinical trial conducted from February 1994 through March 2002. Participants were randomly assigned to receive chlorthalidone, 12.5 to 25 mg/d (n = 15,255); amlodipine, 2.5 to 10 mg/d (n = 9048); or lisinopril, 10 to 40 mg/d (n = 9054) for planned follow-up of approximately 4 to 8 years. The primary outcome was combined fatal CHD or nonfatal myocardial infarction, analyzed by intent-to-treat. Secondary outcomes were all-cause mortality, stroke, combined CHD (primary outcome, coronary revascularization, or angina with hospitalization), and combined CVD (combined CHD, stroke, treated angina without hospitalization, heart failure (HF), and peripheral arterial disease).Lipid Study: Multicenter (513 primarily community-based North American clinical centers), randomized, non-blinded trial conducted from 1994 through March 2002 in a subset of participants from the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT). The interventions in the trial were pravastatin, 40 mg/d, vs usual care. The primary outcome was all-cause mortality, with follow-up for up to 8 years. Secondary outcomes included non-fatal myocardial infarction or fatal CHD (CHD events) combined, cause-specific mortality, and cancer.ConclusionsHypertension Study: Thiazide-type diuretics are superior in preventing one or more major forms of CVD and are less expensive. They should be preferred for first-step antihypertensive therapy.Lipid Study: Pravastatin did not reduce either all-cause mortality or CHD significantly when compared with usual care in older participants with well-controlled hypertension and moderately elevated LDL-C. The results may be due to the modest differential in total cholesterol (9.6%) and LDL-C (16.7%) between pravastatin and usual care compared with prior statin trials supporting cardiovascular disease prevention.

  Study phs004021

• National Cancer Institute (NCI) Biospecimen Pre-analytical Variables (BPV) Analysis

  The Biospecimen Pre-analytical Variables (BPV) Program is a National Cancer Institute-sponsored study to systematically assess the effects of pre-analytical factors on the molecular profile of biospecimens. A robust biospecimen collection infrastructure was established to prospectively collect biospecimens using rigorous standard operating procedures to control for most variables while introducing experimental conditions to study specific biospecimen handling issues, including the cold ischemic time (delay to formalin fixation), time in formalin, freezing methods, and storage temperatures and durations. RNA and DNA from biospecimens collected under these conditions was analyzed on multiple molecular platforms. The potential effects of these pre-analytical conditions on protein integrity and detection of metabolites were also examined. Data from this study will be used to develop evidence-based biospecimen standard operating procedures and best practices for fit-for-purpose collection, processing, and storage of biospecimens. The BPV Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following sub-studies below or in the &#34;Substudies&#34; box located on the right hand side of this top-level study page phs001304 BPV Cohort. The substudy links will be active once they are released by dbGaP. Preanalytical Impacts on Global Metabolite Profiling - plasma (MassSpec by Metabolon) This study was to evaluate the impact of the storage temperature (s) (-80&#176;C and LN2 vapor) and the length of storage on human plasma quality using LC-MS/MS (liquid-chromatography-mass spectrometry/mass spectrometry) based global metabolite profiling. The study includes 240 plasma samples collected from 40 donors. Investigate the effect of the delay to fixation on the proteome and phosphoproteome -FFPE (MassSpec by Caprion). The study is to do proteome and phosphoproteome analysis on Delay to fixation was carried out using FFPE tumor samples from colon and ovarian cancer patients comparing 2, 3, and 12hr delay to fixation to the 1hr time point. The study includes 100 samples 20 donors. Investigate the effect of storage conditions of tumor specimens on the proteome and phosphoproteome profiling- Frozen tissue and plasma (MassSpec by Caprion). The study was to evaluate the effects of storage conditions on tumor specimens. Plasma samples from 40 cancer patients stored at two different temperatures (-80&#176;C and LN2) for a given period (0-2, 6-8, and 12-14 months) were evaluated. Frozen kidney tumor samples from 20 patients were compared for effects of different snap frozen (dry ice vs. LN2) and storage temperatures (-80&#176;C and LN2). The study includes 100 tissue and 240 plasma samples from 60 donors. Preanalytical Impacts on Genomic Sequencing by Next Generation Sequencing (NGS) technology (mRNA/miRNA and WES by Expression Analysis). The goal of the study is to determine the effects of cold ischemic delay-to-fixation (4 time points) and formalin preservation (FFPE) on the nature and quality of genomic profiles using the matched freshly frozen sample as the gold standard, which including WES, RNAseq. The study includes 395 samples from 37 donors. Preanalytical Impacts on Copy Number Variation (CNV) Detection by aCGH technology (aCGH by Georgetown University). This study was to use aCGH to evaluate the effect of variation in cold ischemia time and time in formalin fixation on CNV in DNA extracted from kidney cancer specimens. The study includes 235 samples from 40 donors. Evaluation of frozen conditions on mRNA profiling by TaqMan assay (mRNA expression by Georgetown University). This study was to utilize gene expression profiling, using custom TaqMan arrays, to compare the molecular profiles of RNA from frozen tumor samples collected using two freezing methods (dry ice or LN2), two storage temperatures (-80&#176;C or LN2 vapor), as well as Optimal Cutting Temperature (OCT) compound and non-OCT embedded. The study includes 100 samples from 20 donors. mRNA signature for stratification by cold ischemia time (mRNA expression by IBBL). The study was to determine the effects of cold ischemic time (delay-to-fixation) and formalin preservation (FFPE) on mRNA detection by Taqman assay using tumor tissue specimens from kidney, colon and ovarian cancer patients. There are160 samples from 40 donors. The Biospecimen PV cohort is utilized in the following dbGaP individual studies. To view molecular data, and derived variables collected in these individual studies, please click on the following individual studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs001304 Biospecimen PV cohort. phs001634 CIT mRNA phs001635 CNV aCGH phs001636 Fixation Delay phs001637 Global Metabolite Profiling phs001638 mRNA TaqMan phs001639 NGS phs001640 Tumor Storage

  Study phs001304

• DATA ACCESS WITH REGARDS TO EXOME-WIDE ASSOCIATION ANALYSIS OF CORONARY ARTERY DISEASE IN THE KINGDOM OF SAUDI ARABIA POPULATION

  Dac EGAC00001000420

• Transcriptional and DNA binding profiling of CEBPE in REH acute lymphoblastic leukaemia cells using shRNA RNA-Seq and ChIP-Seq

  Dac EGAC00001000891

• The data access committee for Multimodal Genomic Features Predict Outcome of Immune Checkpoint Blockade in Non-small Cell Lung Cancer

  Dac EGAC00001001331

• Data access committee for white blood cell and cell-free DNA analyses for detection of residual disease in gastric cancer

  Dac EGAC00001001435

• Data Access Commitee for study Fine-Scale Genomic Analyses Of Admixed Individuals Reveal Unrecognized Genetic Ancestry Components In Argentina

  Dac EGAC00001001634

• Access to aligned sequencing data for study "Loss of SNAI2 in prostate cancer correlates with clinical response to androgen deprivation therapy".

  Dac EGAC00001001809

• Novel de novo pathogenic variant in the GNAI1 as a cause of severe disorders of intellectual development with autistic features

  Dac EGAC00001002145

• Novel de novo pathogenic variant in the GNAI1 as a cause of severe disorders of intellectual development with autistic features

  Dac EGAC00001002151

• Data Access Commitee - Monocyte and macrophage lipid accumulation results in downregulated type-I interferon responses - FH monocytes RNA sequencing data

  Dac EGAC00001002495

• The study of response to EGFR Blockade in Colorectal Cancer

  Dataset EGAD00001001628

• The study of response to EGFR Blockade in Colorectal Cancer

  Dataset EGAD00001001674

• OGVP_HC24_Controls

  Healthy adult volunteers and newborns recruited in various countries across Oceania.

  Dataset EGAD00010000953

• RHD_FJ_OMNI_Cases

  Rheumatic heart disease cases recruited in Fiji with higher density genotyping

  Dataset EGAD00010000955

• GLASS-NL DNA-Methylation

  DNA-methylation data of samples included in the GLASS-NL cohort

  Dataset EGAD00010002647

• Time series analysis of neoadjuvant chemotherapy and bevacizumab treated breast carcinomas reveals a systemic shift in genomic aberrations

  Study EGAS00001003287