Search Results - EGA European Genome-Phenome Archive

Studies of a Targeted Risk Reduction Intervention through Defined Exercise (STRRIDE)

The STRRIDE study is the combination of three interventional trials to evaluate dose and intensity of physical activity on cardiometabolic health. The three component studies are Peripheral Effects of Exercise on Cardiovascular Health (STRRIDE I, ClinicalTrials.gov Identifier: NCT00200993), Effects of Resistence and Aerobic Exercise on Cardiovascular Health (STRRIDE II, ClinicalTrials.gov Identifier: NCT00275145) and Exercise Dose-Response Effects in Prediabetes (STRRIDE-PD, ClinicalTrials.gov Identifier: NCT00962962).

Study phs001855

Rapid Acceleration of Diagnostics - Underserved Populations (RADx-UP) Collection of General Research Use Datasets

This individual-level collection of datasets contains all the RADx Underserved Populations (RADx-UP) studies in dbGaP for General Research Use (GRU) and have no further limitations beyond those outlined in the model RADx Data Use Certification Agreement. Access to this study collection will include additional authorized individual-level GRU datasets that become available. Renewal of this study collection is required annually. Access to studies in this collection is on the RADx® Data Hub. To request access to this study collection, select phs003832 in the dbGaP when submitting a data access request.

Study phs003832

Rapid Acceleration of Diagnostics - Tech Program (RADx-Tech) Collection of General Research Use Datasets

This individual-level collection of datasets contains all the RADx® Tech Programs (RADx-Tech) studies in dbGaP for General Research Use (GRU) and have no further limitations beyond those outlined in the model RADx Data Use Certification Agreement. Access to this study collection will include additional authorized individual-level GRU datasets that become available. Renewal of this study collection is required annually. Access to studies in this collection is on the RADx® Data Hub. To request access to this study collection, select phs003831 in the dbGaP when submitting a data access request.

Study phs003831

Rapid Acceleration of Diagnostics - Radical (RADx-rad) Collection of General Research Use Datasets

This individual-level collection of datasets contains all the RADx® Radical (RADx-rad) studies in dbGaP for General Research Use (GRU) and have no further limitations beyond those outlined in the model RADx Data Use Certification Agreement. Access to this study collection will include additional authorized individual-level GRU datasets that become available. Renewal of this study collection is required annually. Access to studies in this collection is on the RADx® Data Hub. To request access to this study collection, select phs003834 in the dbGaP when submitting a data access request.

Study phs003834

Single B cell analysis in pemphigus patients

pemphigus is caused by autoantibodies that target cell-cell adhesion molecules, desmoglein(Dsg). Clinical effect of anti-CD20 antibody therapy suggtests that Dsg-specific memory B cell, the precursor of autoantigen secreting plasmablast, may play an important role of disease activity. This study aimed to isolate Dsg-specific memory B cell using recombinant labeled Dsg proteins and performed single cell RNA-sequence to detect autoimmune B cell specific gene expression. For control, we also isolate non-Dsg specific memory B cells from same patients, or forein antigen (Flu HA) specific memory B cells from vaccinated healthy volunteers.

Study JGAS000281

RNAseq of MCL cell lines

This study profiles the transcriptomic response of the Mino-VEN-R and Jeko-BTK-R mantle cell lymphoma (MCL) cell lines to pirtobrutinib (PBN) treatment using bulk RNA sequencing. Mino-VEN-R models drug-tolerant persister (DTP) cells that arise during exposure to non-covalent BTK inhibitors. Building on our recent findings that DTP cells undergo metabolic and phenotypic state transitions governed by TCA cycle reprogramming, this dataset aims to capture gene expression changes associated with treatment-induced plasticity. The results contribute to a broader multi-omic framework exploring mechanisms of resistance and therapeutic vulnerability in MCL.

Study EGAS50000001087

Center for Common Disease Genomics [CCDG] - Cardiovascular: Pharmacokinetic Polymorphisms in Japanese General Population

This study is a part of NHGRI's Center for Common Disease Genomics, which is a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Current estimates anticipate that the CCDG program will sequence approximately 140K whole genomes and 225K whole exomes during the life of the project. The Cardiovascular Disease working group of the CCDG considered five diseases: early-onset coronary artery disease (EOCAD), stroke, atrial fibrillation, congestive heart failure and type 2 diabetes. Atrial fibrillation will affect between 6-12 million individuals in the US by 2050. AF also is associated with increased risks of stroke, dementia, heart failure, death, and high health care costs. Many risk factors for AF have been identified, including advancing age, cardiovascular disease (CVD), and CVD risk factors. However, there is little knowledge how to prevent AF. Furthermore, therapies for AF are only partially effective, and are themselves associated with substantial morbidity. Previously, heritable forms of AF have been considered rare; yet in the last decade, it has been established that AF, and in particular early-onset forms of AF, are heritable. Genome-wide association studies (GWAS) provide a powerful tool to identify common variants underlying disease risk. The AFGen Consortium currently consists of investigators from more than 25 studies with >20,000 individuals with AF and >100,000 without AF. In the latest analyses, 14 loci have been identified for AF1 . Broadly, the loci implicate genes related to cardiopulmonary development, cardiac-expressed ion channels, and cell signaling molecules.Source: https://ccdg.rutgers.edu/sites/default/files/CCDG_CVD_EOAF_FINAL_w_link.pdfAnalysis of 165 pharmacokinetic-related gene polymorphisms (the number of polymorphisms may increase) using DNA derived from the blood of approximately 1,000 Japanese general populations. Tokai University School of Medicine Molecular Life Sciences 2 Isogo Lab has been trying to find new genes which contribute to the development of multiple diseases and to develop new methods for human genome diversity analysis that will lead to the development of technology for disease screening by finding genes related to diseases and incorporating gene analysis technology. Using this method, we are trying to clarify the relationship between the characteristics of rheumatoid arthritis and psoriasis vulgaris and genes to seek effective treatments and prevention methods. Raw sequencing data, metadata, vcf and phenotype data at individual level are available at https://anvilproject.org/data. For questions about availability contact help@lists.anvilproject.org.

Study phs002985

Efficient prediction of a spatial transcriptomics profile better characterizes breast cancer tissue sections without costly experimentation

Spatial transcriptomics is an emerging technology requiring costly reagents and considerable skills, limiting the identification of transcriptional markers related to histology. Here, we show that predicted spatial gene-expressions in unmeasured regions and tissues can enhance biologists�� histological interpretations. We developed the Deep learning model for Spatial gene Clusters and Expression, DeepSpaCE and confirmed its performance using the spatial-transcriptome profiles and immunohistochemistry images of consecutive human breast cancer tissue sections. For example, the predicted expression patterns of SPARC, an invasion marker, highlighted a small tumor-invasion region that is difficult to identify using raw data of spatial transcriptome alone because of a lack of measurements. We further developed semi-supervised DeepSpaCE using unlabeled histology images and increased the imputation accuracy of consecutive sections, enhancing applicability for a small sample size. Our method enables users to derive hidden histological characters via spatial transcriptome and gene annotations, leading to accelerated biological discoveries without additional experiments.

Study JGAS000290

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

Whole transcriptome RNA sequencing on bone marrow and peripheral blood samples from patients with acute myeloid leukemia at diagnosis or relapse.

One hundred cryopreserved bone marrow and peripheral blood samples from patients with acute myeloid leukemia (AML) with 10-90% blasts were selected from the biobank of the Department of Hematology of Leiden University Medical Center (LUMC). The AML cases cover all subtypes, and specifically include known subtype-defining balanced chromosomal translocations according to the WHO classification. The samples were obtained from 96 patients and include three pairs of de novo and relapsed AML and one pair of de novo and presumed therapy-related AML (tAML). Total RNA was isolated from mononuclear cells without prior enrichment for leukemic blasts. The quality and integrity of total RNA was checked and RNA libraries were prepared using the TruSeq RNA library preparation kit v2 (Illumina, San Diego, CA) in an ISO/IEC 17025-accredited protocol. This workflow started with enrichment of messenger RNA by oligo dT magnetic beads. After fragmentation, cDNA synthesis was performed, followed by adaptor ligation and PCR amplification. Paired-end sequencing with a read length of 126 bp was performed on an Illumina HiSeq 2500 v4 sequencer to at least 12.5 Gbp per sample. Image analysis, base calling, and quality check was performed with Illumina data analysis pipeline RTA v1.18.64 and Bcl2fastq v1.8.4. RNAseq reads are provided in compressed Sanger FASTQ format.

Dataset EGAD00001004187

Heat selection enables highly scalable methylome profiling in cell-free DNA for noninvasive monitoring of cancer patients

Genome-wide analysis of cell-free DNA (cfDNA) methylation profile has been recognized as a promising approach for sensitive and specific detection of many cancers. However, scaling such genome-wide assays for clinical translation is impractical due to the high cost of whole genome bisulfite sequencing. We have shown that the small fraction of GC-rich genome is highly enriched in CpG sites and disproportionately harbors the majority of cancer-specific methylation signature. Here, we report on the simple but effective Heat enrichment of CpG-rich regions for Bisulfite Sequencing (Heatrich-BS) platform that allows for focused methylation profiling in these highly informative regions. Our novel method and bioinformatics algorithm enable accurate tumor burden estimation with high sensitivity and quantitative tracking of colorectal cancer patient’s response to treatment, at much reduced sequencing cost suitable for frequent monitoring. We also show, for the first time, tumor epigenetic subtyping from cfDNA using Heatrich-BS, which could enable patient stratification from non-invasive liquid biopsy. As such, Heatrich-BS holds great potential for highly scalable screening and regular monitoring of cancer using liquid biopsy.

Study EGAS00001006198

DNA methylation landscape of prostate cancer

Metastases from primary prostate cancers to rare locations, such as the brain, are becoming more common due to longer life expectancy thanks to improved treatments. Epigenetic dysregulation is a feature of primary prostate cancer, and distinct DNA methylation profiles are associated with the mutually exclusive SPOP mutant or TMPRSS2-ERG fusion genetic backgrounds. Using a cohort of 42 patients with prostate cancer brain metastases (PCBM), with matched primary samples available for 17 patients, we carried out DNA methylation analysis using Illumina EPIC array. We examined the epigenetic distinction between primary PCa and PCBM, the association between epigenetic alterations and mutational background, and particular epigenetic alterations that may be associated with PCBM in particular. Multiregion sampling of PCBM revealed epigenetic heterogeneity in metastases. We found aberrant methylation in PCBM is associated with mutational background, PRC2 complex activity and upregulation of EZH2, an effect that is particularly pronounced in SPOP mutant PCBM. While we detected a hypermethylator phenotype in PCBM, we also observed hypomethylation occurring at the promoters of genes involved in neuroactive ligand-receptor interactions or the calcium signalling pathway, such as GABRB3 and GRM5, a change not observed in non-brain prostate cancer metastases.

Study EGAS00001006670

Human skin cancer (BCC, SCC, melanoma) and healthy control skin

Smart-seq2 single cell RNA sequencing of human BCC, SCC, melanoma (ALM) and healthy control skin samples.

Dataset EGAD50000000540

Evaluation of size selection on cancer specific sequencing libraries

A couple of previously characterized and sequenced libraries will be repeated using a couple of differing size selection criteria and skim sequenced using an Illumina HiSeq. The resulting sequence will be analyzed to determine the optimal DNA library size for our specific downstream analysis.

Dataset EGAD00001000301

WES data from primary CRC

Whole exome sequencing from ffpe samples DNA was extracted from FFPE tissue samples from colorectal cancer biopsies. Exome libraries where prepared using the KAPA Hyper Plus Kit (Roche Diagnostics) followed by target enrichment by hybridisation capture using the Roche Hyper Exome Kit. Sequenced on NovaSeq6000 to generated 2x 151 paired-end reads.

Dataset EGAD50000000924

GoT2D: Genetics of Type 2 Diabetes, a study of the the genetic architecture of type 2 diabetes using low pass whole genome sequencing and high density SNP genotyping in 2,657 individuals.

The Genetics of Type 2 Diabetes Consortium (GoT2D) is a collaboration between the University of Michigan, the Broad Institute and the Wellcome Trust Centre for Human Genetics. The overall aim is to extend upon recent efforts, such as genome-wide association studies (GWAS) and large scale meta-analyses. While they have proved successful at mapping genomic loci that influence human diseases, like type 2 diabetes, much of the heritability remains unexplained. In this study, we use next generation sequencing and genotyping technologies to query for lower frequency variants in the human genome. Thereby, allowing a deeper characterization of the spectrum of alleles associated with type 2 diabetes risk, and a better assessment of the genes that play a role in the etiology of type 2 diabetes development. We studied 1,326 T2D cases and 1,331 normoglycemic controls from Northern and Central Europe (Sweden, Finland, UK, and Germany). To efficiently characterize the entire genome sequence of each individual, we performed low-coverage (~5x) whole-genome sequencing, augmented by deep coverage (~100x) sequencing of the exome, and dense (2.5M) single nucleotide polymorphism (SNP) genotyping using the HumanOmni2.5 array. The data deposited in EGA will include all the Swedish, Finnish, UK, and German samples.

Study EGAS00001001459

The genomic landscape of cutaneous squamous cell carcinoma from immunosuppressed and immunocompetent patients reveals common drivers and a novel mutational signature associated with chronic azathioprine exposure

Cutaneous squamous cell carcinoma (cSCC) has a high tumour mutational burden (50 mutations per megabase DNA pair). Combining whole exome analyses from 40 primary cSCC tumours, comprising 20 well differentiated and 20 moderately/poorly differentiated tumours, with accompanying clinical data from a longitudinal study of immunosuppressed and immunocompetent patients, coupled with integration of independent gene expression studies has allowed the identification of commonly mutated genes and altered pathways and processes. Mutational signature analysis revealed the presence of a novel signature (signature 32), which was found exclusively in the tumours from immunosuppressed patients who had been exposed to azathioprine. Characterisation of a panel of 15 keratinocyte cancer cell lines derived from tumours from immunocompetent and immunosuppressed patients reveals that they accurately reflect the mutational signatures and genomic alterations of primary tumours and provide a resource for the validation of tumour drivers and therapeutic targets.

Study EGAS00001002612

San Francisco Bay Area Latina Breast Cancer Study

The genome-wide association study (GWAS) includes participants enrolled into two different studies. The first study, the San Francisco Bay Area Cancer Study (SFBCS) is a population-based case-control study of breast cancer conducted in the San Francisco Bay Area and included women ages 35-79 years from three racial/ethnic groups: Non-Hispanic whites, African Americans, and Hispanics/Latinas. For the GWAS, only Hispanic/Latina women were included. Women diagnosed with invasive breast cancer between 1995 and 2002 were identified through the Greater Bay Area Cancer Registry. Controls were identified by random digit dialing and were frequency-matched to cases by age in 5 year increments and by race/ethnicity. Hispanic/Latina ethnicity was assessed by self-report. 175 Hispanic/Latina cases and 307 Hispanic/Latina controls from the SFBCS had given adequate consent and provided biospecimens that were used in the GWAS to be included in this data submission. The second study is the Northern California site of the Breast Cancer Family Registry (NC-BCFR). This population-based family study recruited breast cancer cases ages 18-64 years diagnosed from 1995-2009 that were identified through the Greater Bay Area Cancer Registry. Cases included all women at increased genetic susceptibility for breast cancer who met one or more of the following criteria: (a) being diagnosed with breast cancer at age <35 years; b) having a personal history of ovarian cancer or childhood cancer; (c) being diagnosed with two different breast cancers (bilateral breast cancers), with the first one diagnosed at age <50 years; and d) having one or more first-degree relatives with breast cancer, ovarian cancer or childhood cancer. Cases not meeting these criteria were randomly sampled and racial/ethnic minorities were oversampled. Controls were recruited by random digit dialing and were matched by 5-year age increments and by race/ethnicity. For the current GWAS only Latina/Hispanic cases and controls were included. Latina/Hispanic ethnicity was assessed by self-report. 631 Hispanic/Latina cases and 61 Hispanic/Latina controls from the NC-BCFR had given adequate consent and provided biospecimens that were used in the GWAS to be included in this data submission.

Study phs000912

eMERGE: Northwestern (NUgene) WGS

The NUgene Project is a biorepository with longitudinal medical information from participating patients at Northwestern Medicine affiliated hospitals and outpatient clinics. Participants' DNA samples are coupled with data from a self-reported questionnaire (2 versions were used, 1 before and 1 after February 2006, both are included) and continuously updated data from our Electronic Medical Record (EMR) representing actual clinical care events. Northwestern has a state-of-the art, comprehensive inpatient and outpatient EMR system of over 3 million patients. NUgene has broad access to participant data for all outpatient visits as well as inpatient data via a consolidated enterprise data warehouse. NUgene participants consent to distribution and use of their coded DNA samples and data for a broad range of genetic research by third-party investigators. The electronic MedicalRecords and Genomics (eMERGE) Network is a consortium of 9 clinical sites with EMR linked DNA biobanks, including Northwestern University and its NUgene biobank, funded by the NHGRI (National Human Genome Research Institute) to investigate the use of electronic medical record systems for genomic research. The goal of eMERGE is to conduct genome-wide association studies in approximately 100,000 individuals using EMR-derived phenotypes and DNA from linked biorepositories. Using electronic phenotyping methods, the consortium has been and is using DNA samples from all participating sites to explore the genetic determinants of approximately 80 phenotypes, including both diseases and traits, for which the electronic phenotyping algorithms have or are being published on PheKB.org. Thus, for the eMERGE network, ~900 NUgene subjects were selected, as described in the study inclusion/exclusion criteria section below, to be genotyped using whole genome sequencing (WGS), for use in the eMERGE network as eMERGE subjects. The criteria used below were selected so that these subjects will likely meet the criteria to be cases and/or controls, of diverse races and/or ethnicities, for at least 1 of the ~80 phenotypes being studied within eMERGE, and could be recontacted for future research if needed.

Study phs001191

14988 results for "cancer studies using rna-seq"

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