Search Results - EGA European Genome-Phenome Archive

BLUEPRINT release August 2016, ChIP-Seq for germinal center B cell, on genome GRCh38

ChIP-Seq data for 4 germinal center B cell sample(s). 24 run(s), 22 experiment(s), 22 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

Dataset EGAD00001002442

BLUEPRINT release August 2016, ChIP-Seq for immature conventional dendritic cell - GM-CSF_IL4_T=6_days, on genome GRCh38

ChIP-Seq data for 3 immature conventional dendritic cell - GM-CSF_IL4_T=6_days sample(s). 20 run(s), 20 experiment(s), 20 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

Dataset EGAD00001002485

BLUEPRINT release August 2016, ChIP-Seq for adult endothelial progenitor cell, on genome GRCh38

ChIP-Seq data for 2 adult endothelial progenitor cell sample(s). 16 run(s), 14 experiment(s), 14 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

Dataset EGAD00001002487

BLUEPRINT release August 2016, ChIP-Seq for endothelial cell of umbilical vein (resting), on genome GRCh38

ChIP-Seq data for 2 endothelial cell of umbilical vein (resting) sample(s). 13 run(s), 13 experiment(s), 13 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

Dataset EGAD00001002488

BLUEPRINT release August 2016, ChIP-Seq for CD4-positive, alpha-beta thymocyte, on genome GRCh38

ChIP-Seq data for 1 CD4-positive, alpha-beta thymocyte sample(s). 3 run(s), 3 experiment(s), 3 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

Dataset EGAD00001002386

BLUEPRINT release August 2016, RNA-Seq for conventional dendritic cell, on genome GRCh38

RNA-Seq data for 2 conventional dendritic cell sample(s). 2 run(s), 2 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

Dataset EGAD00001002345

BLUEPRINT release August 2016, Bisulfite-Seq for effector memory CD8-positive, alpha-beta T cell, terminally differentiated, on genome GRCh38

Bisulfite-Seq data for 2 effector memory CD8-positive, alpha-beta T cell, terminally differentiated sample(s). 34 run(s), 3 experiment(s), 4 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_bisulphite_analysis_CNAG_20160816

Dataset EGAD00001002346

BLUEPRINT release August 2016, RNA-Seq for memory B cell, on genome GRCh38

RNA-Seq data for 1 memory B cell sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

Dataset EGAD00001002347

BLUEPRINT release August 2016, RNA-Seq for regulatory T cell, on genome GRCh38

RNA-Seq data for 1 regulatory T cell sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

Dataset EGAD00001002351

BLUEPRINT release August 2016, RNA-Seq for blast forming unit erythroid, on genome GRCh38

RNA-Seq data for 1 blast forming unit erythroid sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

Dataset EGAD00001002365

BLUEPRINT release August 2016, ChIP-Seq for monocyte - RPMI_BG_T=4hrs, on genome GRCh38

ChIP-Seq data for 3 monocyte - RPMI_BG_T=4hrs sample(s). 8 run(s), 8 experiment(s), 8 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

Dataset EGAD00001002368

BLUEPRINT release August 2016, ChIP-Seq for monocyte - RPMI_LPS_T=1hr, on genome GRCh38

ChIP-Seq data for 2 monocyte - RPMI_LPS_T=1hr sample(s). 8 run(s), 6 experiment(s), 6 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

Dataset EGAD00001002376

BLUEPRINT release August 2016, RNA-Seq for segmented neutrophil of bone marrow, on genome GRCh38

RNA-Seq data for 3 segmented neutrophil of bone marrow sample(s). 3 run(s), 3 experiment(s), 3 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

Dataset EGAD00001002380

BLUEPRINT release August 2016, RNA-Seq for alternatively activated macrophage, on genome GRCh38

RNA-Seq data for 7 alternatively activated macrophage sample(s). 9 run(s), 7 experiment(s), 7 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

Dataset EGAD00001002387

BLUEPRINT release August 2016, ChIP-Seq for monocyte - RPMI_LPS_T=24hrs, on genome GRCh38

ChIP-Seq data for 3 monocyte - RPMI_LPS_T=24hrs sample(s). 8 run(s), 8 experiment(s), 8 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

Dataset EGAD00001002388

Bam files from Whole exome sequencing (WES, ~50x mean read depth) of metachronous bladder tumors

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 122 Bam files for WES (83 Tumors and 39 blood)

Dataset EGAD00001002716

The effect of anti-HER2/CD3 TDB on transcription in human CD8 T cells (bulk RNA-seq)

RNA was isolated from purified human CD8 cells that were incubated with anti-HER2/CD3 TDB in the presence of SK-BR-3 cells. Sequencing libraries were generated and submitted for transcriptome profiling by high-throughput sequencing. Experiments were performed in triplicates for anti-HER2/CD3 TDB treatment and control. This Dataset is associated with the following ArrayExpress Experiment: E-MTAB-8211 - The effect of anti-HER2/CD3 TDB on transcription in human CD8 T cells (bulk)

Dataset EGAD00001005187

Keratinocyte CRISPR screens (2019-08-14)

Immortalised HaCaT keratinocytes were transduced with Cas9 and the CRISPR-KO v1.1 genome-wide gRNA library. The gRNA library was prepared from genomic DNA isolated 14 days post library transduction. gRNA representation will be compared to the original CRISPR-KO v1.1 library to reveal genes essential for HaCaT survival and growth. . This dataset contains all the data available for this study on 2019-08-14.

Dataset EGAD00001005252

The identification of genetic vulnerabilities in head and neck cancers for the development of novel treatments. (2019-06-10)

Exome Sequencing in a set of Asian Head and Neck cancer cell lines, to identify mutations that can be used to genomically classify the cell lines. . This dataset contains all the data available for this study on 2019-06-10.

Dataset EGAD00001005082

Spatial RNA-sequencing of metastatic melanoma

We performed RNA sequencing of 48 different regions sub-sampled from a metastatic melanoma biopsy that was treated with anti-PD-1 inhibitor. RNAseq was performed on samples with a minimum RNA integrity number (RIN) of 5.5 except for two cases (6A10 and 8A3) with RINs greater than 3. A minimum of 700ng of RNA were required for all samples undergoing RNAseq. Paired-end transcriptome reads were aligned using TopHat2, to the UCSC hg19 reference genome.

Dataset EGAD00001005820

RNA sequencing of human intra- and extracranial endothelial cells

This data set contains the raw .fastq files from one RNA-sequencing experiment. Endothelial cells of the basilar artery and endothelial cells of the carotid artery were post-mortem derived with laser microdissection and sequenced. For this analysis both the basilar- and the carotid artery endothelial cells of eleven individuals were sequenced. For more details please see: DMA Hermkens et al. "Profiling the Unique Protective Properties of Intracranial Arterial Endothelial Cells" Acta Neuropathol Commun. 2019 Oct 14; PMID: 31610812.

Dataset EGAD00001006203

Bottleneck Sequencing Of Human Tissue (Wgs) (2020-10-20)

Bottleneck sequencing of human tissue including neurons, cord blood, sperm. 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 2020-10-20.

Dataset EGAD00001006459

CRUK Accelerator: Non-small cell lung cancer whole exome and RNA sequencing

Whole exome and RNASeq raw sequencing data for a cohort 24 patients with non-small cell lung cancer, 15 adenocarcinoma (8 female, 7 male) and 9 squamous cell carcinoma(5 female, 4 male). Median age at diagnosis was 69. Tumour tissue and PBMCs were used for whole exome sequencing and RNA sequencing. This data was generated as part of a study funded by a Cancer Research UK Centres Network Accelerator Award Grant (A21998).

Dataset EGAD00001007934

DATA ACCESS AGREEMENT CGNT- GROUP COMMITTEE for project "Exome sequencing of 22 Pheochromocytoma/paraganglioma tumors" at Gothenburg University.

Dac EGAC00001000411

DAC for Greenland Studies of University of Copenhagen and University of Southern Denmark.

Dac EGAC00001000736

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

Dac EGAC00001000757

Data Access Committee for the study "Somatic chronology of treatment-resistant prostate cancer via deep whole-genome ctDNA sequencing"

Dac EGAC00001002479

Access Committee for Separation, characterization, and identification of individuals from multi-person blood mixtures

Dac EGAC00001002646

ASTAR Skin Research Laboratory

Data Access Committee for A*STAR Skin Research Laboratory, A*STAR Research Institutes, Singapore.

Dac EGAC50000000109

Data for paper Mold, Weissman et al. 'Clonally heritable gene expression imparts a layer of diversity within cell types'

Dac EGAC50000000102

DAC - organotypic co-cultures @IEO

DAC for RNAseq data on patient-derived organotypic models (Battistini et al, CDDis 2024)

Dac EGAC50000000238

eQTL-CHiC DAC

The Data Access Committee for eQTL-CHiC and related data from Ray-Jones et al., 2024.

Dac EGAC50000000445

DAC for Transcriptomic and genomic profiling of fragile X syndrome unmethylated full mutation carriers

Dac EGAC50000000416

DKFZ-HIPO DACO for "Patient-derived tumoroids from CIC::DUX4 rearranged sarcoma identify MCL1 as a therapeutic target"

Dac EGAC00001003559

Data Access Committee for Patient-derived tumoroids from CIC::DUX4 rearranged sarcoma identify MCL1 as a therapeutic target

Dac EGAC00001003558

DAC_Circadian_Neuroendocrinology

DAC for projects of the group Circadian Neuroendocrinology at the Department of Endocrinology and Metabolism at Amsterdam UMC.

Dac EGAC50000000692

Distinct Phenotypes of Human Intrahepatic and Extrahepatic Bile duct Organoids and their Applications for Biliary Disease Modeling

Study EGAS00001003792

Cryopreservation of human cancers conserves tumour heterogeneity for single-cell multi-omics analysis

Study EGAS00001005115

Patient WGS for #198

Whole genome sequencing of patient tumour and blood

Dataset EGAD50000000217

Genotypes_343_Japanese

Genotype data for 343 Japanese subjects obtained with Infinium Asian Screening Array.

Dataset EGAD00010002449

TumorSNP

SNP data for 473 tumor samples

Dataset EGAD00010002038

Genomic Sequencing of Triple Negative Breast Cancer - Exome data

Exome data for study EGAS00001008261

Dataset EGAD00001015687

WGS dataset

4 WGS bam files for 4 cases with fusion

Dataset EGAD00001004359

PDAC

ctDNA and protein markers for earlier detection of pancreatic cancers

Dataset EGAD00001004399

Nimblegen SeqCap Custom Panel Sequencing

Nimblegen SeqCap Custom Panel Sequencing for pNet

Dataset EGAD00001005494

Health and Retirement Study (HRS)

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

Study phs000428

Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples (T2D-GENES) Follow-Up Study: Research Studies in Hong Kong

The ~52,000 sample Type 2 Diabetes Exome Sequencing project is a collaboration of six consortia with various funding mechanisms that have joined together to investigate genetic variants for type 2 diabetes (T2D) using the largest T2D case/control sample set compiled to date. This includes samples from: Type 2 Diabetes Genetic Exploration by Next-generation sequencing in Multi-Ethnic Samples (T2D-GENES) Genetics of Type 2 Diabetes (GoT2D) Exome Sequencing Project (ESP) Slim Initiative in Genomic Medicine for the Americas (SIGMA) Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCAMP) Progress in Diabetes Genetics in Youth (ProDIGY) This data generated from the Hong Kong cohort was part of the T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) consortium, which is a NIDDK-funded international research consortium that seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. The T2D-GENES Project is a multi-ethnic sequencing study designed to assess whether less common variants play a role in T2D risk and to assess similarities and differences in the distribution of T2D risk variants across ancestry groups. The individuals were obtained from over 20 cohorts across the 6 consortia that are listed in Table 1. The strategy was to perform deep exome sequencing of individuals, 24,991 with T2D and 24,953 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. The T2D-GENES, ProDIGY and SIGMA studies, sequencing was performed at the Broad Institute using the Agilent v2 capture reagent or Illumina Rapid Capture on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, two of the cohorts below are not in dbGaP, due to the samples not being consented for deposition. This includes the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study and Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) study. The Exome Sequencing Project (ESP) was deposited in dbGaP as part of their initial study and the phs numbers for that project can be found here: https://esp.gs.washington.edu/drupal/dbGaP_Releases. Table 1. 52,000 sample T2D Case/Control Whole Exome Sequencing Studies Ancestry Consortia Study Countries of Origin # Cases # Controls African American T2D-GENES Project 1 Jackson Heart Study US 500 526 African American T2D-GENES Project 1 Wake Forest School of Medicine Study US 518 530 African American ESP Exome Sequencing Project (ESP) US 467 1374 African American T2D-GENES Follow-Up Study BioMe Biobank Program (BioMe) US 1297 1256 East Asian T2D-GENES Project 1 Korea Association Research Project Korea 526 561 East Asian T2D-GENES Project 1 and Follow-Up Study Singapore Diabetes Cohort Study; Singapore Prospective Study Program Singapore (Chinese) 1486 1568 East Asian T2D-GENES Follow-Up Study Korea SNUH South Korea 450 475 East Asian T2D-GENES Follow-Up Study Research Studies in Hong Kong (Hong Kong) Hong Kong 493 485 European T2D-GENES Project 1 Ashkenazi US, Israel 506 352 European T2D-GENES Project 1 Metabolic Syndrome in Men Study (METSIM) Finland 484 498 European GoT2D Finland-United States Investigation of NIDDM Genetics (FUSION) Study Finland 472 476 European GoT2D Kooperative Gesundheitsforschung in der Region Augsburg (KORA) Germany 97 90 European GoT2D UK Type 2 Diabetes Genetics Consortium (UKT2D) UK 322 320 European GoT2D Malmö-Botnia Study Finland, Sweden 478 443 European LuCamp Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) Denmark 997 997 European ESP Exome Sequencing Project (ESP) US 390 2843 European T2D-GENES Follow-Up Study Genetics of Diabetes and Audit Research Tayside Study (GoDARTS) Scotland, UK 960 966 European T2D-GENES Follow-Up Study Framingham Heart Study (FHS) US 396 596 Hispanic T2D-GENES Project 1 San Antonio Family Heart Study, San Antonio Family Diabetes/ Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component US 272 218 Hispanic T2D-GENES Project 1 and SIGMA v2 Starr County, Texas US 1762 1738 Hispanic SIGMA v1 Mexico City Diabetes Study Mexico 281 549 Hispanic SIGMA v1 and SIGMA v2 Multiethnic Cohort (MEC) US 1476 1443 Hispanic SIGMA v1 and SIGMA v2 UNAM/INCMNSZ Diabetes Study (UIDS) Mexico 1998 1977 Hispanic SIGMA v1 and SIGMA v2 Diabetes in Mexico Study (DMS) Mexico 1522 1546 Multiethnic ProDIGY Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) US 3097 0 Multiethnic ProDIGY SEARCH for Diabetes in Youth (SEARCH) US 553 0 South Asian T2D-GENES Project 1 London Life Sciences Population Study (LOLIPOP) UK (Indian Asian) 531 538 South Asian T2D-GENES Project 1 and Follow-Up Study Singapore Indian Eye Study Singapore (Indian Asian) 1640 1478 South Asian T2D-GENES Follow-Up Study Pakistan Risk of Myocardial Infarction Study (PROMIS) Pakistan 914 932 The research studies in Hong Kong contributed 493 cases and 485 controls to T2D-GENES Follow-Up study.

Study phs001504

Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples (T2D-GENES) Follow-Up Study: BioMe Biobank Program

The ~52,000 sample Type 2 Diabetes Exome Sequencing project is a collaboration of six consortia with various funding mechanisms that have joined together to investigate genetic variants for type 2 diabetes (T2D) using the largest T2D case/control sample set compiled to date. This includes samples from: Type 2 Diabetes Genetic Exploration by Next-generation sequencing in Multi-Ethnic Samples (T2D-GENES) Genetics of Type 2 Diabetes (GoT2D) Exome Sequencing Project (ESP) Slim Initiative in Genomic Medicine for the Americas (SIGMA) Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCAMP) Progress in Diabetes Genetics in Youth (ProDIGY) This data generated from the BioMe Biobank cohort was part of the T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) consortium, which is a NIDDK-funded international research consortium that seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. The T2D-GENES Project is a multi-ethnic sequencing study designed to assess whether less common variants play a role in T2D risk and to assess similarities and differences in the distribution of T2D risk variants across ancestry groups. The individuals were obtained from over 20 cohorts across the 6 consortia that are listed in Table 1. The strategy was to perform deep exome sequencing of individuals, 24,991 with T2D and 24,953 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. The T2D-GENES, ProDIGY and SIGMA studies, sequencing was performed at the Broad Institute using the Agilent v2 capture reagent or Illumina Rapid Capture on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, two of the cohorts below are not in dbGAP, due to the samples not being consented for deposition. This includes the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study and Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) study. The Exome Sequencing Project (ESP) was deposited in dbGAP as part of their initial study and the phs numbers for that project can be found here: https://esp.gs.washington.edu/drupal/dbGaP_Releases. Table 1. 52,000 sample T2D Case/Control Whole Exome Sequencing Studies Ancestry Consortia Study Countries of Origin # Cases # Controls African American T2D-GENES Project 1 Jackson Heart Study US 502 527 African American T2D-GENES Project 1 Wake Forest School of Medicine Study US 518 532 African American ESP Exome Sequencing Project (ESP) US 467 1374 African American T2D-GENES Follow-Up Study BioMe Biobank Program (BioMe) US 1294 1254 East Asian T2D-GENES Project 1 Korea Association Research Project Korea 526 561 East Asian T2D-GENES Project 1 and Follow-Up Study Singapore Diabetes Cohort Study; Singapore Prospective Study Program Singapore (Chinese) 1486 1568 East Asian T2D-GENES Follow-Up Study Korea SNUH South Korea 450 475 East Asian T2D-GENES Follow-Up Study Research Studies in Hong Kong (Hong Kong) Hong Kong 493 485 European T2D-GENES Project 1 Ashkenazi US, Israel 506 355 European T2D-GENES Project 1 Metabolic Syndrome in Men Study (METSIM) Finland 484 498 European GoT2D Finland-United States Investigation of NIDDM Genetics (FUSION) Study Finland 472 476 European GoT2D Kooperative Gesundheitsforschung in der Region Augsburg (KORA) Germany 97 90 European GoT2D UK Type 2 Diabetes Genetics Consortium (UKT2D) UK 322 320 European GoT2D Malmö-Botnia Study Finland, Sweden 478 443 European LuCamp Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) Denmark 997 997 European ESP Exome Sequencing Project (ESP) US 390 2843 European T2D-GENES Follow-Up Study Genetics of Diabetes and Audit Research Tayside Study (GoDARTS) Scotland, UK 960 966 European T2D-GENES Follow-Up Study Framingham Heart Study (FHS) US 396 596 Hispanic T2D-GENES Project 1 San Antonio Family Heart Study, San Antonio Family Diabetes/ Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component US 272 218 Hispanic T2D-GENES Project 1 and SIGMA v2 Starr County, Texas US 1762 1738 Hispanic SIGMA v1 Mexico City Diabetes Study Mexico 281 549 Hispanic SIGMA v1 and SIGMA v2 Multiethnic Cohort (MEC) US 1476 1443 Hispanic SIGMA v1 and SIGMA v2 UNAM/INCMNSZ Diabetes Study (UIDS) Mexico 1998 1977 Hispanic SIGMA v1 and SIGMA v2 Diabetes in Mexico Study (DMS) Mexico 1522 1546 Multiethnic ProDIGY Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) US 3097 0 Multiethnic ProDIGY SEARCH for Diabetes in Youth (SEARCH) US 553 0 South Asian T2D-GENES Project 1 London Life Sciences Population Study (LOLIPOP) UK (Indian Asian) 531 538 South Asian T2D-GENES Project 1 and Follow-Up Study Singapore Indian Eye Study Singapore (Indian Asian) 1640 1478 South Asian T2D-GENES Follow-Up Study Pakistan Genomic Resource (PGR) Pakistan 914 932 The BioMe Biobank study contributed 1294 cases and 1254 controls to T2D-GENES Follow-Up Study.

Study phs001490

Type 2 Diabetes Genetic Exploration by Next-generation Sequencing in Multi-Ethnic Samples (T2D-GENES) Follow up Study: Pakistan Genomic Resource (PGR)

The ~52,000 sample Type 2 Diabetes Exome Sequencing project is a collaboration of six consortia with various funding mechanisms that have joined together to investigate genetic variants for type 2 diabetes (T2D) using the largest T2D case/control sample set compiled to date. This includes samples from: Type 2 Diabetes Genetic Exploration by Next-generation sequencing in Multi-Ethnic Samples (T2D-GENES) Genetics of Type 2 Diabetes (GoT2D) Exome Sequencing Project (ESP) Slim Initiative in Genomic Medicine for the Americas (SIGMA) Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCAMP) Progress in Diabetes Genetics in Youth (ProDIGY) This data generated from the Pakistan Genomic Resource (PGR) cohort was part of the T2-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) consortium, which is a NIDDK-funded international research consortium that seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. The T2D-GENES Project is a multi-ethnic sequencing study designed to assess whether less common variants play a role in T2D risk and to assess similarities and differences in the distribution of T2D risk variants across ancestry groups. The individuals were obtained from over 20 cohorts across the 6 consortia that are listed in Table 1. The strategy was to perform deep exome sequencing of individuals, 24,991 with T2D and 24,953 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. The T2D-GENES, ProDIGY and SIGMA studies, sequencing was performed at the Broad Institute using the Agilent v2 capture reagent or Illumina Rapid Capture on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, two of the cohorts below are not in dbGAP, due to the samples not being consented for deposition. This includes the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study and Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) study. The Exome Sequencing Project (ESP) was deposited in dbGAP as part of their initial study and the phs numbers for that project can be found here: https://esp.gs.washington.edu/drupal/dbGaP_Releases. Table 1. 52,000 sample T2D Case/Control Whole Exome Sequencing Studies Ancestry Consortia Study Countries of Origin # Cases # Controls African American T2D-GENES Project 1 Jackson Heart Study US 502 527 African American T2D-GENES Project 1 Wake Forest School of Medicine Study US 518 532 African American ESP Exome Sequencing Project (ESP) US 467 1374 African American T2D-GENES Follow-Up Study BioMe Biobank Program (BioMe) US 1297 1256 East Asian T2D-GENES Project 1 Korea Association Research Project Korea 526 561 East Asian T2D-GENES Project 1 and Follow-Up Study Singapore Diabetes Cohort Study; Singapore Prospective Study Program Singapore (Chinese) 1486 1568 East Asian T2D-GENES Follow-Up Study Korea SNUH South Korea 450 475 East Asian T2D-GENES Follow-Up Study Research Studies in Hong Kong (Hong Kong) Hong Kong 493 485 European T2D-GENES Project 1 Ashkenazi US, Israel 506 355 European T2D-GENES Project 1 Metabolic Syndrome in Men Study (METSIM) Finland 484 498 European GoT2D Finland-United States Investigation of NIDDM Genetics (FUSION) Study Finland 472 476 European GoT2D Kooperative Gesundheitsforschung in der Region Augsburg (KORA) Germany 97 90 European GoT2D UK Type 2 Diabetes Genetics Consortium (UKT2D) UK 322 320 European GoT2D Malmö-Botnia Study Finland, Sweden 478 443 European LuCamp Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) Denmark 997 997 European ESP Exome Sequencing Project (ESP) US 390 2843 European T2D-GENES Follow-Up Study Genetics of Diabetes and Audit Research Tayside Study (GoDARTS) Scotland, UK 960 966 European T2D-GENES Follow-Up Study Framingham Heart Study (FHS) US 396 596 Hispanic T2D-GENES Project 1 San Antonio Family Heart Study, San Antonio Family Diabetes/ Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component US 272 218 Hispanic T2D-GENES Project 1 and SIGMA v2 Starr County, Texas US 1762 1738 Hispanic SIGMA v1 Mexico City Diabetes Study Mexico 281 549 Hispanic SIGMA v1 and SIGMA v2 Multiethnic Cohort (MEC) US 1476 1443 Hispanic SIGMA v1 and SIGMA v2 UNAM/INCMNSZ Diabetes Study (UIDS) Mexico 1998 1977 Hispanic SIGMA v1 and SIGMA v2 Diabetes in Mexico Study (DMS) Mexico 1522 1546 Multiethnic ProDIGY Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) US 3097 0 Multiethnic ProDIGY SEARCH for Diabetes in Youth (SEARCH) US 553 0 South Asian T2D-GENES Project 1 London Life Sciences Population Study (LOLIPOP) UK (Indian Asian) 531 538 South Asian T2D-GENES Project 1 and Follow-Up Study Singapore Indian Eye Study Singapore (Indian Asian) 1640 1478 South Asian T2D-GENES Follow-Up Study Pakistan Genomic Resource (PGR) Pakistan 903 930 The PGR study contributed 903 cases and 930 controls to T2D-GENES Follow-Up Study.

Study phs001552

DAC for high resolution genomic data generated by the Gisselsson Group at the Department of Clinical Genetics, Lund University.

Dac EGAC00001000534

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

Dac EGAC00001001331

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

Okayama University Hospital, CGM center, DAC

Okayama University Hospital, Japan Centre for Comprehensive Genomic Medicine (CGM) Data Access Committee

Dac EGAC50000000250

Next generation sequencing of plasma cell neoplasms

Includes raw data for genome sequencing studies performed at the University of Miami

Dac EGAC50000000593

CDK4 phosphorylation status and rational use for combining CDK4/6 and BRAF/MEK inhibition in advanced thyroid carcinomas

Study EGAS00001007577

Ampliseq library dataset

This is the dataset for Ampliseq sequencing

Dataset EGAD50000000536

PDX WES for #039 and #049

Exome sequencing of PDX and matched patient blood

Dataset EGAD50000000034

PDX WGS for #264

WGS of tumour PDX and matched patient blood

Dataset EGAD50000000033

BreastCancer_Control_Micorarays

Genotyping array data for normal mammary gland control samples

Dataset EGAD00010002250

Genotypes_Farmers

Genotype data for Palanan farmers Philippines

Dataset EGAD00010002141

Genotypes_BaYaka

Genotype data for BaYaka hunter-gatherers Congo

Dataset EGAD00010002139

DATA FILES FOR PCGP SJACT WGS

Dataset EGAD00001001874

DAC for "CUT&RUN-sequencing identifies PTK7 as a direct Wnt target in patient-derived colorectal cancer organoids"

Dac EGAC00001003592

An approach for evaluating the effects of dietary fiber polysaccharides on the human gut microbiome and plasma proteome

Study EGAS00001005330

AML WGS bam

WGS bam files for paired diagnostic and remission samples

Dataset EGAD00001015515

Global Anaplastic Thyroid Cancer Initiative

Raw exome sequence data(fastq) for the GATCI project

Dataset EGAD00001003235

Summary statistics for cervical cancer GWAS

Summary statistics from GWAS meta-analysis of cervical cancer

Dataset EGAD00001004361

Metastatic Prostate Follow Up

Validation/deeper sequencing for metastatic prostate cancer samples

Dataset EGAD00001000988

GATCI exome sequencing fastqs

Raw whole exome sequencing data (fastq) for the GATCI project

Dataset EGAD00001005808

National Institute on Aging (NIA) Late-Onset Alzheimer's Disease Genetics Initiative: The Multiplex Family Study

Multiplex Family StudyThe purpose of the NIA Genetics Initiative: Multiplex Family Study is to identify families with multiple members diagnosed with late-onset Alzheimer's Disease. Families will be characterized clinically and blood samples will be collected to establish cell lines. If a blood sample is not available, autopsy samples will be collected for DNA extraction and storage. Our goal is to recruit 1,000 families over the course of the study. Clinical and demographic data from these families will be collected at the local site and coded data, without identifiers, will be sent and included in a national database of families with Alzheimer's Disease. This database, along with the biological samples, will be housed at the National Cell Repository for Alzheimer's Disease (NCRAD) at Indiana University. The Center or provider and the Cell Repository must sign a Material Transfer Agreement for shipment of biological samples and phenotypic data to NCRAD. The biological samples and data from these families will be available to qualified researchers, who must sign a Material Transfer Agreement before receiving DNA and data. An oversight committee known as the Cell Bank Advisory Committee (CBAC) will review and monitor the process of family identification and enrollment, data collection, the establishment of cell lines and access to samples. LOAD CIDR ProjectThe first 362 families of the Multiplex Family Study (including 2,105 family members) were included in a 6K SNP genome-wide scan at the NIH-supported, Center for Inherited Disease Research (CIDR). An additional 297 unrelated, healthy controls were also genotyped at CIDR. The average age of onset of AD in the genotyped sample is 74 years and 62% of the sample is women. While primarily Caucasian, 3% are African-American, and 3% are of Hispanic ancestry. 72% of the families had at least 2 affected siblings, whereas 21% had 3 or more sampled affected individuals and 7% had 4 or more genotyped, affected family members.

Study phs000160

Ghana Breast Health Study

The Ghana Breast Health Study (GBHS) was a multi-disciplinary, population-based case-control study conducted in Accra and Kumasi, Ghana that was designed to investigate breast cancer etiology in the West Africa region. The study enrolled 1,126 invasive breast cancer cases and 2,106 frequency matched population-based controls using census-based sampling. GHBS participants were between the ages of 18 to 74 years of age. Breast cancer cases were recruited at the time they presented with lesions suspicious of breast cancer at three hospitals: Korle Bu Teaching Hospital (Accra), Komfo Anoyke Teaching Hospital (Kumasi) and Peace and Love Hospital (Kumasi). These hospitals are the primary providers of treatment for breast cancer in Ghana, allowing for cases in our study to represent most breast cancers diagnosed in these areas during the study period. The following publications describe the GBHS in detail: 1) Brinton LA et al. Design considerations for identifying breast cancer risk factors in a population-based study in Africa. Int J Cancer 2017;140:2667-2677 (PMID:28295287). 2) Nyante SJ et al. Recruiting population controls for case-control studies in sub-Saharan Africa: The Ghana Breast Health Study. PloS one 2019;14:e0215347 (PMID:30990841)Among subjects with an available source of germline DNA genotyping was performed using the Infinium Global Screening Array-24 per the manufacturer’s guidelines using the Infinium automated protocol. We excluded probable duplicates and close relatives, and samples with a call rate < 95% or samples with extreme heterozygosity. Female sex was verified by Identifiler using X chromosome heterozygosity and the X chromosome inbreeding coefficient F statistics. The GLU genetics’ ld.tagzilla module was used to confirm African ancestry. To resolve more detailed population substructure, principal components analysis was conducted among all unrelated subjects using the EIGENSOFT v7.2.1. Imputation was performed using the Michigan imputation server Minimac3 with 1K genomes phase3 as reference panel.

Study phs002387

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

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

Study phs000454

Advancing Precision Oncology in a Humanized, Fully Autologous Mouse Model

Progress in the early detection and treatment of cancer requires accurate model systems to further evaluate new, promising discoveries. Small animal and, in particular, mouse model systems are attractive to researchers for numerous reasons, including their ease of use and well-described platforms. The ability to grow human tumors in immune-deficient mice (so-called patient-derived xenografts, or PDXs) allows researchers to work directly with human cancer tissue in a controlled setting. However, PDX models are limited by their lack of an intact immune system. Immunotherapy has revolutionized clinical oncology, but lacks pre-clinical models of the human immune system and human cancer to investigate new modalities and limitations/toxicities of treatment regimens. The broad objective of this study is to validate an in vivo model to evaluate human tumors in the context of a complete and intact human immune system in a completely personalized and autologous fashion to study cancer immunotherapy. Herein, we will: (1) validate the ability of our humanized system to serve as a model for cancer immunotherapy treatment response and toxicity in patients with melanoma, including immunotherapy checkpoint blockade and vaccine strategies, and (2) extend our current work in melanoma by validating the ability to establish humanized mice and evaluate tumor growth and leukocyte development in autologous human pancreatic and colorectal tumors established in humanized mice. In each of these areas, we will leverage our multi-institutional team's individual expertise along with our institutional infrastructure to maximize the success of the experimental aims. The results from this project will be widely available to the general research community for future, hypothesis-driven research. Taken together, our study will meet multiple goals and address several unmet needs in cancer immunotherapy, thus significantly enhancing the applicability of a fully autologous and immunocompetent precision model system for use in translational oncology research.

Study phs003090

Childhood Cancer Data Initiative (CCDI): Enhancement of Data Sharing in Pediatric, Adolescent and Young Adult Cancers

NCI's Childhood Cancer Data Initiative (CCDI) is building a community centered around childhood cancer care and research data. Through enhanced data sharing, we can improve our understanding of cancer biology to improve preventive measures, treatment, quality of life, and survivorship, as well as ensure that researchers learn from every child with cancer. While childhood cancers represent the leading cause of death in children over the age of 1, they are collectively rare, comprising approximately 1%‒3% of cancers diagnosed annually in the United States. Information on diagnosis, treatment, and outcomes is often stored at the hospital or institution where a child is treated, making it difficult to answer scientific questions about childhood cancer. Sharing clinical care and research data generated by children's hospitals, clinics, or networks broadly with the community can help us learn faster and, on a scale much larger than any single institution caring for children can learn on its own. To exploit the rapid advances in high-throughput DNA sequencing technologies and realize the goals of precision cancer medicine, the UMICH Cancer Center established the Michigan Oncology Sequencing Center (MI-ONCOSEQ). This UMICH Cancer Center provisions genomic data derived from the Michigan Oncology Sequencing Center (MI-ONCOSEQ) clinical sequencing assay for patients that fall within the inclusion criteria of the CCDI data sharing initiative. An "integrative sequencing approach" carried out in a CLIA-certified laboratory is utilized to provide a comprehensive landscape of the genetic alterations in individual tumor specimens for the purpose of identifying informative and/or actionable mutations. Using a number of computational pipelines that we have developed in-house or have adapted from the public domain, candidate molecular aberrations are nominated and then analyzed by scientists for clinical significance and/or relevance. This approach enables the detection of point mutations, insertions/deletions, gene fusions and rearrangements, amplifications/deletions, and outlier expressed genes. Furthermore, we can identify certain germline alterations that may also be relevant.

Study phs002431

Precision High Intensity Training Through Epigenetics (PHITE)

Exercising regularly promotes health, but these benefits are complicated by acute inflammation induced by exercise. A potential source of exercise-induced inflammation is cell-free DNA (cfDNA), yet the cellular origins, molecular causes, and immune system interactions of exercise-induced cfDNA are unclear. To study these, 10 healthy individuals were randomized to a 12-week exercise program of either high-intensity tactical training (HITT) or traditional moderate-intensity training (TRAD). Blood plasma was collected pre- and post exercise at weeks 0 and 12 and after 4 week of detraining upon program completion. Whole-genome enzymatic methylation sequencing (EM-seq) with cell-type proportion deconvolution was applied to cfDNA obtained from the 50 plasma samples and paired to concentration measurements for 90 circulating cytokines. Acute exercise increased the release of cfDNA from neutrophils, dendritic cells (DCs), and macrophages proportional to exercise intensity (HITT > TRAD). Exercise training reduced cfDNA released in HITT participants but not TRAD and from DCs and macrophages but not neutrophils. For most participants, training lowered mitochondrial cfDNA at rest, even after detraining. Using a sequencing analysis approach we developed, we concluded that rapid extracellular traps (ETosis) was the likely source of cfDNA, demonstrated by enrichment of nuclear DNA. Further, several cytokines were induced by acute exercise, such as IL-6, IL-10, and IL-16, and training attenuated the induction of only IL-6 and IL-17F. Cytokine levels were not associated with cfDNA induction, suggesting that these cytokines are not the main cause of exercise-induced cfDNA. Overall, exercise intensity and training modulated cfDNA release and cytokine responses, contributing to the anti-inflammatory effects of regular exercise. One additional subject was also used in the methyl-seq data as a control for comparing bisulfite-sequencing to enzymatic methyl sequencing. DNA methylation for MPO gene was found to be significantly different as well, in line with interpretation that neutrophils are primarily undergoing ETosis.

Study phs003873

POU4F3 mutation screening in Japanese hearing loss patients.

A variant in a transcription factor gene, POU4F3, is responsible for autosomal dominant nonsyndromic hereditary hearing loss, DFNA15. To date, 14 variants, including a whole deletion of POU4F3, have been reported to cause HL in various ethnic groups. In the present study, genetic screening for POU4F3 variants was carried out for a large series of Japanese hearing loss (HL) patients to clarify the prevalence and clinical characteristics of DFNA15 in the Japanese population. Massively parallel DNA sequencing of 68 target candidate genes was utilized in 2,549 unrelated Japanese HL patients (probands) to identify genomic variations responsible for HL. The detailed clinical features in patients with POU4F3 variants were collected from medical charts and analyzed. Novel 12 POU4F3 likely pathogenic variants (six missense variants, three frameshift variants, and three nonsense variants) were successfully identified in 15 probands (2.5%) among 602 families exhibiting autosomal dominant HL, whereas no variants were detected in the other 1,947 probands with autosomal recessive or inheritance pattern unknown HL. To obtain the audiovestibular configuration of the patients harboring POU4F3 variants, we collected audiograms and vestibular symptoms of the probands and their affected family members. Audiovestibular phenotypes in a total of 24 individuals from the 15 families possessing variants were characterized by progressive HL, with a large variation in the onset age and severity with or without vestibular symptoms observed. Pure-tone audiograms indicated the most prevalent configuration as mid-frequency HL type followed by high-frequency HL type, with asymmetry observed in approximately 20% of affected individuals. Analysis of the relationship between age and pure-tone average suggested that individuals with truncating variants showed earlier onset and slower progression of HL than did those with non-truncating variants. The present study showed that variants in POU4F3 were a common cause of autosomal dominant HL.

Study JGAS000093

Molecular analysis of diffuse cerebellar gliomas

Among diffuse gliomas, oligodendrogliomas show relatively better prognosis, respond well to radiotherapy and chemotherapy, and seldom progress to very aggressive tumors. To elucidate the genetic and epigenetic background for such behavior and tumor evolution during tumor relapse, we comparatively analyzed 12 pairs of primary and recurrent oligodendrogliomas with 1p/19q-codeletion. Initial treatment for these patients was mostly chemotherapy alone. Temozolomide was used for 3, and procarbazine, nimustine and vincristine (PAV chemotherapy) were used for 7 patients. World Health Organization histological grade at recurrence was mostly stable; it was increased in 2, the same in 9, and decreased in 1 cases. Whole-exome sequencing demonstrated that the rate of shared mutation between the primary and recurrent tumors was relatively low, ranging from 3.2-57.9% (average, 33.3%), indicating a branched evolutionary pattern. The trunk alterations that existed throughout the course were restricted to IDH1 mutation, 1p/19q-codeletion, and TERT promoter mutation, and mutation of the known candidate tumor suppressor genes CIC and FUBP1 were not consistently observed between primary and recurrent tumors. Multiple sampling from different regions within a tumor showed marked intratumoral heterogeneity. Notably, in general, the number of mutations was not significantly different after recurrence, remaining under 100, and no hypermutator phenotype was observed. FUBP1 mutation, loss of chr. 9p21, and TCF12 mutation were among a few recurrent de novo alterations that were found at recurrence, indicating that these events were clonally selected at recurrence but were not enough to enhance malignancy. Genome-wide methylation status, measured by Illumina 450 K arrays, was stable between recurrence and the primary tumor. In summary, although oligodendroglioma displays marked mutational heterogeneity, histological malignant transformation accompanying events such as considerable increase in mutation number and epigenetic profile change were not observed at recurrence, indicating that noticeable temporal and spatial genetic heterogeneity in oligodendrogliomas does not result in rapid tumor progression.

Study JGAS000106

Assessing the impact of low frequency coding variants on disease risk using the Exomechip

Following several rounds of Genome Wide Association (GWA) scans and subsequent meta-analyses of results multiple risk loci have been identified for many common diseases. However, in most instances the implicated common variants identified so far explain only a modest fraction of the genetic risk. In parallel to our efforts to identify the causative variants in the known loci it is necessary to assess the full spectrum of sequence variants for disease risk and in particular low frequency and rare variants that have not been tested in a comprehensive way so far. To this end an international effort by investigators who have performed whole exome sequencing in circa 12,000 individuals have assembled a set of ~250,000 exonic variants of low frequency – defined as seen in at least two studies and a minimum of three individuals (non-sysnonymous) or two individuals for SNPs altering splice sites / stop codons. The SNP content from the exome studies was complemented with additional interesting SNP sets totalling 25,000 markers (GWA tag SNPs, grid of common variants, HLA, Mitochondrial, Y-chromosome etc) and were used to generate a custom iSELECT array, the exome chip. Adequately powered association studies to test low frequency variants for association to disease risk are still very expensive if conducted by whole exome sequencing. The exome chip provides a cost efficient way to undertake such an experiment and the Wellcome Trust Cases Control Consortium will be applying this approach to eight diseases, type 1 and type 2 diabetes, coronary artery disease, hypertension, multiple sclerosis, rheumatoid arthritis, bipolar, and ankylosing spondylitis. The first objective will be to generate a large set of at least 10,000 common UK controls as analysis of lower frequency variants will require large sample sizes. This includes ~6000 samples from the 1958 Birth Cohort.

Study EGAS00001000584

UK10K_NEURO_ASD_FI

In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches.These samples are a subset of a nationwide collection of Finnish autism spectrum disorder (ASD) samples. The samples have been collected from Central Hospitals across Finland in collaboration with the University of Helsinki. The samples consist of 93 individuals with a diagnosis of autistic disorder or Asperger syndrome from 36 families with at least two affected individuals. Of these individuals, 16 can be genealogically connected to form two large pedigrees originating from Central Finland, suggesting possible genetic risk factors shared identical by descent within the pedigrees. All diagnoses are based on ICD-10 and DSM-IV diagnostic criteria for ASDs. Additional phenotypic data is available for a subset of the individuals.For further information with regard to this cohort please contact Aarno Palotie (Aarno.palotie@helsinki.fi).

Study EGAS00001000110

Bulk-RNA Sequencing of high-grade pancreatic and non-pancreatic Neuroendocrine Neoplasms

Therapeutic decisions in oncology depend on a precise pathological classification of individual neoplasms. Recent years have seen an intensification of research activities aimed at the extraction of clinically relevant information from patient-derived 'omics' data based on Machine-Learning models. However, a comprehensive training of Machine-Learning models requires sufficiently large numbers of training samples, which are usually not available for rare cancer types. The problem is worsened when individual tissues segregate into different cancer subtypes, as their discrimination would require even more training samples. Methods: Here, we report on a new data-augmentation technique to support the training of Machine-Learning models on ‘omics’ data from pancreatic neuroendocrine neoplasms (panNEN). PanNENs display all properties described above: Only about 2-3% of all pancreatic neoplasms are neuroendocrine and they fall into different subtypes with distinctly different prognosis, which makes the precise classification of such samples both difficult and important for therapy decisions. The approach reconstructs a given transcriptome based on healthy pancreatic cell type signatures and creates a Machine-Learning model that integrates the observed reconstruction error and predicted cell type proportions as features. Results: A benchmark of the deconvolution model predictions with the ground-truth found that the model could efficiently predict the sample grading, disease-related patient survival time, and differentiate between different subtypes in four panNEN and one mixed panNEN and non-pancreatic NENs dataset. We compared the predictive performance of the deconvolution-trained model to that of a model trained directly on the transcriptomic data, under inclusion of the Ki-67 classification gold standard biomarker, and found the performances to be comparable. Conclusion: Our approach serves as a data-augmentation technique to facilitate the training of Machine Learning models for rare cancer types via utilization of data from healthy origin. Additionally, the deconvolution results were clinically interpretable and further research can render the deconvolution approach an effective complementary asset for the clinical classification of neoplasms.

Study EGAS00001004861

Same-day genomic and epigenomic diagnosis of brain tumors using realtime nanopore sequencing

Molecular classification of cancer has entered clinical routine to inform diagnosis, prognosis and treatment decisions. At the same time, new tumor entities have been identified that cannot be defined histologically. For central nervous systems tumors, the current World Health Organization classification explicitly demands molecular testing, e.g. for 1p/19q- codeletion or IDH mutations, to make an integrated histomolecular diagnosis. However, a plethora of sophisticated technologies is currently needed to assess different genomic and epigenomic alterations and turnaround times are in the range of weeks, which makes standardized and widespread implementation difficult and hinders timely decision making. Here, we explored the potential of a pocket-size nanopore sequencing device for multimodal and rapid molecular diagnostics of cancer. Low-pass whole genome sequencing was used to simultaneously generate copy number (CN) and methylation profiles from native tumor DNA in the same sequencing run. Single nucleotide variants in IDH1, IDH2, TP53, H3F3A and the TERT promoter region were identified using deep amplicon sequencing. Nanopore sequencing yielded ~0.1X genome coverage within six hours and resulting CN and epigenetic profiles correlated well with matched microarray data. Diagnostically relevant alterations, such as 1p/19q codeletion, and focal amplifications could be recapitulated. Using ad hoc random forests, we could perform supervised pan-cancer classification to distinguish gliomas, medulloblastomas and brain metastases of different primary sites. Single nucleotide variants in IDH1, IDH2 and H3F3A were identified using deep amplicon sequencing within minutes of sequencing. Detection of TP53 and TERT promoter mutations shows that sequencing of entire genes and GC-rich regions is feasible. Nanopore sequencing allows same-day detection of structural variants, point mutations and methylation profiling using a single device with negligible capital cost. It outperforms hybridization-based and current sequencing technologies with respect to time-to diagnosis and required laboratory equipment and expertise, aiming to make precision medicine possible for every cancer patient, even in resource restricted settings.

Study EGAS00001002213

WES_of_adult_intellectual_disabilities_with_co_morbid_psychiatric_disorders

ost adults with intellectual disabilities (ID) do not undergo genetic diagnostic investigation as part of their clinical care and have 'missed the boat' with regard to the WES and WGS genetic testing that is now being provided for children with ID. There is a dramatically increased risk of psychistric disorders in adults with ID, e.g. the risk of psychoses is 10X higher than in the general population. It remains an open question as to how much of adult ID is genetic in origin and how similar the genetic forms of adult ID are to those being diagnosed in children, in part due to survivor bias. There is also the opportunity to identify adults with treatable forms of ID, of which over 80 have been described, thus improving their clinical management. Furthermore, analysis of medical records of adults with genetic forms of ID can help to characterise the 'natural history' of individual disorders, resulting in more accurate prognoses for diagnosed children and identifying opportunities for improved management and possibly therapeutic intervention (e.g. optimal anti-epileptic therapy). Here we propose to exome sequence (to ~50X coverage) 200 adults with ID and co-morbid psychiatric disorders. This cohort has previously been assayed with chromosomal microarrays (Wolfe et al 2017 EJHG, 25, 66–72) identifying a diagnostic yield of ~11% which is comparable to the CNV diagnostic yield in various child ID cohorts (10-15%). The authors observed no substantive biases in diagnostic yield between different psychiatric diagnostic classes. The WES data will be analysed using the diagnostic workflows developed in the DDD study to ensure comparability between child and adult ID datasets. This study is intended as a pilot study to demonstrate the value of WES in adults with ID. 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/

Study EGAS00001002962

High-throughput telomere length measurement at nucleotide resolution using the PacBio high fidelity sequencing platform

Telomeres are specialized nucleoprotein structures at the ends of linear chromosomes that are essential for the stability as well as the complete replication of the human genome. The progressive shortening of steady-state telomere length in normal human somatic cells is a promising biomarker for age-associated diseases. However, there remain substantial challenges in quantifying telomere length in clinics and research laboratories due to the lack of accurate and high-throughput telomere length measurement method. Here, we describe a novel workflow to capture and analyze telomeres accurately at the single-nucleotide resolution. By using newly designed telobaits that are complementary to the single-stranded G-rich 3’ telomeric overhangs, we can specifically and efficiently capture full-length telomeres and subject them to single-molecule real-time (SMRT) sequencing. We show that the telomere length can be measured at nucleotide resolution using the PacBio high fidelity (HiFi) sequencing platform, which provides the necessary accuracy and throughput to uncover the steady-state telomere length distribution in human culture cell lines as well as clinical patient samples. This new method is a valuable tool not only in population-wide epidemiology studies but also for the longitudinal assessment of telomere attrition in individuals. Our results also reveal the extreme heterogeneity of telomeric variant sequences (TVSs) that is dispersed throughout the telomere repeat region. Importantly, the unique distribution pattern and sequence of TVSs in individuals may be used as a fingerprint for sample identification. In addition, the presence of TVSs disrupts the continuity of the canonical (5’-TTAGGG-3’)n telomere repeats, which could affect the binding of shelterin complexes at the chromosomal ends. Therefore, TVSs may act as a form of genetic polymorphisms that impairs telomere protection. Together with the absolute telomere length in each individual, TVSs may have profound implications in human aging and diseases.

Study EGAS00001006103

The G2 gene expression signature and MYC overexpression are independent poor prognostic factors in childhood high-grade osteosarcoma

Purpose In high-grade osteosarcoma, prognostic factors at diagnosis are insufficient for stratifying patients into relevant subgroups. Recently, a transcriptomic study developed the G1/G2 gene expression signature, in which the G2 signature was associated with unfavorable survival. An orthogonal study identified MYC amplification as an unfavorable prognostic factor using targeted next-generation sequencing. The purpose of this study was to validate the independent prognostic value and to investigate the combined prognostic value of the G1/G2 signature with, MYC amplification and/or MYC expression for survival prediction. Material and methods This study included pediatric and adolescent patients with high-grade osteosarcoma. RNA sequencing was performed in 48 patients. Whole-exome sequencing was performed in 40 patients. Gene expression signature scores, MYC amplification (defined as > 7 copies) and MYC expression levels were calculated. Multivariable Cox proportional hazards analysis was performed for event-free survival (EFS) (primary endpoint) and overall survival (OS) (secondary endpoint). Results In the full cohort, the 3-year event-free survival rate was 37%. In multivariable Cox regression analysis with metastatic disease stage (n=21, 44%) as covariate, the G2 signature and MYC expression were independently associated with worse outcomes in terms of EFS (Hazard ratio (HR) 3.32, 95% confidence interval (CI) 1.34-8.21 and HR 3.38, 95%-CI 1.71-6.66, respectively) and OS (HR 4.07, 95%-CI 1.19-13.9 and HR 2.88, 95%-CI 1.22-6.76, respectively). MYC amplification was not associated with EFS or OS in univariable analysis (HR 1.88, 95% -CI 0.74-4.77 and HR 0.79, 95%-CI 0.21-3.05, respectively). Conclusion The G2 gene expression signature and MYC expression were independently associated with unfavorable outcomes in a pediatric cohort of patients with high-grade osteosarcoma. The combined prognostic value warrants further prospective validation and could potentially serve as a stratification marker for future osteosarcoma treatment protocols.

Study EGAS00001008073

High-throughput telomere length measurement at nucleotide resolution using the PacBio high fidelity sequencing platform, P49-P104 and run1 replicates

Telomeres are specialized nucleoprotein structures at the ends of linear chromosomes that are essential for the stability as well as the complete replication of the human genome. The progressive shortening of steady-state telomere length in normal human somatic cells is a promising biomarker for age-associated diseases. However, there remain substantial challenges in quantifying telomere length in clinics and research laboratories due to the lack of accurate and high-throughput telomere length measurement method. Here, we describe a novel workflow to capture and analyze telomeres accurately at the single-nucleotide resolution. By using newly designed telobaits that are complementary to the single-stranded G-rich 3’ telomeric overhangs, we can specifically and efficiently capture full-length telomeres and subject them to single-molecule real-time (SMRT) sequencing. We show that the telomere length can be measured at nucleotide resolution using the PacBio high fidelity (HiFi) sequencing platform, which provides the necessary accuracy and throughput to uncover the steady-state telomere length distribution in human culture cell lines as well as clinical patient samples. This new method is a valuable tool not only in population-wide epidemiology studies but also for the longitudinal assessment of telomere attrition in individuals. Our results also reveal the extreme heterogeneity of telomeric variant sequences (TVSs) that is dispersed throughout the telomere repeat region. Importantly, the unique distribution pattern and sequence of TVSs in individuals may be used as a fingerprint for sample identification. In addition, the presence of TVSs disrupts the continuity of the canonical (5’-TTAGGG-3’)n telomere repeats, which could affect the binding of shelterin complexes at the chromosomal ends. Therefore, TVSs may act as a form of genetic polymorphisms that impairs telomere protection. Together with the absolute telomere length in each individual, TVSs may have profound implications in human aging and diseases.

Study EGAS00001006595

Whole genome and whole exome sequencing of serial biopsies of relapsed/refractory diffuse large B-cell lymphoma.

Purpose: Diffuse large B-cell lymphoma (DLBCL) is cured in more than 60% of patients, but outcomes remain poor for patients experiencing disease progression or relapse (refractory or relapsed DLBCL [rrDLBCL]), particularly if these events occur early. Although previous studies examining cohorts of rrDLBCL have identified features that are enriched at relapse, few have directly compared serial biopsies to uncover biological and evolutionary dynamics driving rrDLBCL. Here, we sought to confirm the relationship between relapse timing and outcomes after second-line (immuno)chemotherapy and determine the evolutionary dynamics that underpin that relationship. Patients and methods: Outcomes were examined in a population-based cohort of 221 patients with DLBCL who experienced progression/relapse after frontline treatment and were treated with second-line (immuno)chemotherapy with an intention-to-treat with autologous stem-cell transplantation (ASCT). Serial DLBCL biopsies from a partially overlapping cohort of 129 patients underwent molecular characterization, including whole-genome or whole-exome sequencing in 73 patients. Results: Outcomes to second-line therapy and ASCT are superior for late relapse (>2 years postdiagnosis) versus primary refractory (<9 months) or early relapse (9-24 months). Diagnostic and relapse biopsies were mostly concordant for cell-of-origin classification and genetics-based subgroup. Despite this concordance, the number of mutations exclusive to each biopsy increased with time since diagnosis, and late relapses shared few mutations with their diagnostic counterpart, demonstrating a branching evolution pattern. In patients with highly divergent tumors, many of the same genes acquired new mutations independently in each tumor, suggesting that the earliest mutations in a shared precursor cell constrain tumor evolution toward the same genetics-based subgroups at both diagnosis and relapse. Conclusion: These results suggest that late relapses commonly represent genetically distinct and chemotherapy-naïve disease and have implications for optimal patient management.

Study EGAS00001007053

Data access agreement for ATRT

Dac EGAC00001000306

Data Access Commitee for Schulte-Schrepping et al., 2020: Severe COVID-19 is marked by a dysregulated myeloid cell compartment

Dac EGAC00001001684

DAC for the study molecular biomarkers associated with the diagnosis and severity of genetic and diseases from PAIDI-BIO354 GENYO-UGR)

Dac EGAC00001003090

DAC for BCP-LBL Kiel

Whole exome sequencing and RNA sequencing of B-Cell Precursor Lymphoblastic Lymphoma tissue biopsies.

Dac EGAC50000000181

DAC for study involving the spatial transcriptomics analysis of HPV-dependent and HPV-independent vulval squamous cell carcinoma at Imperial College London.

Dac EGAC00001003515

FRIGE IHG Data Access Committee reviews the aim and methodology of the proposed study for which access to anonymised data is requested.

Dac EGAC00001003629

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