Search Results - EGA European Genome-Phenome Archive

Dataset for the study - Detection of cell-free DNA fragmentation and copy number alterations in cerebrospinal fluid from glioma patients

FASTQ files from sequencing to < 0.4x depth of coverage of thirteen glioma patients. Indexed sequencing libraries were prepared using a commercially available kit (ThruPLEX-Plasma Seq, Rubicon Genomics). Libraries were pooled in equimolar amounts and sequenced on a HiSeq 4000 (Illumina) generating 150-bp paired-end reads.

Dataset EGAD00001004425

Circulating tumour DNA abundance and potential utility in de novo metastatic prostate cancer

We set out to determine ctDNA abundance at de novo mCSPC diagnosis and whether ctDNA provides complementary clinically relevant information to a prostate biopsy. We collected and sequenced 77 plasma cell-free DNA samples from 53 newly diagnosed patients with mCSPC. Targeted sequencing was also performed on DNA from 48 diagnostic prostate tissue samples.

Dataset EGAD00001004526

Cell-free DNA analysis reveals POLR1D-mediated resistance to bevacizumab in colorectal cancer

Bevacizumab is an approved anti-angiogenic drug for patients with metastasized colorectal cancer (mCRC) targeting VEGF. The survival benefit of anti-VEGF therapy in mCRC patients is limited to a few months and acquired resistance mechanisms are greatly unknown. Using plasma DNA, we studied the evolution of tumor genomes in a cohort of patients with mCRC (n=150) and observed a recurrent focal amplification (8.7% of cases) on chromosome 13q12.2. Analysis of TCGA data (n=619) suggested an association with later stages, which we confirmed by longitudinal plasma analyses. We defined the minimally amplified region and studied the mechanistic consequences of copy number gain of the involved genes. The amplification of one gene, POLR1D, impacted cell proliferation, resulting in upregulation of VEGFA, an important regulator of angiogenesis which has been implicated in the resistance to bevacizumab. In several patients, we observed the emergence of this 13q12.2 amplicon under bevacizumab treatment, which was invariably associated with evolution of therapy resistance. Hence, we describe a novel resistance mechanism against a widely applied treatment in mCRC patients which will impact clinical management

Study EGAS00001003791

Kids First: Genomics of Orofacial Cleft Birth Defects in Latin American Families

The Gabriella Miller Kids First Pediatric Research Program) (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in pediatric cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource). Both childhood cancers and structural birth defects are critical and costly conditions associated with substantial morbidity and mortality. Elucidating the underlying genetic etiology of these diseases has the potential to profoundly improve preventative measures, diagnostics, and therapeutic interventions. All of the WGS and phenotypic data from this study are accessible through dbGaP and https://kidsfirstdrc.org, where other Kids First datasets can also be accessed. The Kids First study of nonsyndromic orofacial cleft (OFC) birth defects in Latin American families is a whole genome sequencing study of 283 Latin-American parent-case trios drawn from ongoing collaborations led by Dr. Mary L. Marazita of the University of Pittsburgh Center for Craniofacial and Dental Genetics, and including a collaboration with Dr. Lina Moreno Uribe and Dr. Andrew Lidral of the University of Iowa. All families were ascertained through the Clinica Noel where patients with OFCs receive care from the Antioquia University School of Dentistry in Medellin, Colombia (key on-site colleagues included Dr. Luz Consuelo Valencia-Ramirez and Dr. Mauricio Arcos-Burgos). Genetic studies have shown that this population is comprised of an admixture of immigrant male Caucasians (mainly Spaniards and Basques) and native Amerindian females. Every subject has had a genetic evaluation, including a pedigree analysis for a family history of clefting and other birth defects, a pregnancy history for environmental exposures, and a complete physical exam to rule out suspected or known syndromes or environmental phenocopies. Sequencing was done by the Broad Institute sequencing center funded by the Kids First program (grant number U24-HD090743). The case in each of the Kids First OFC trios has cleft lip (CL, Figure A below), cleft palate (CP, Figure B), or both (CL+CP, Figure C): OFCs are genetically complex structural birth defects caused by genetic factors, environmental exposures, and their interactions. OFCs are the most common craniofacial anomalies in humans, affecting approximately 1 in 700 newborns, and are one of the most common structural birth defects worldwide. On average a child with an OFC initially faces feeding difficulties, undergoes 6 surgeries, spends 30 days in hospital, receives 5 years of orthodontic treatment, and participates in ongoing speech therapy, leading to an estimated total lifetime treatment cost of about $200,000. Further, individuals born with an OFC have higher infant mortality, higher mortality rates at all other stages of life, increased incidence of mental health problems, and higher risk for other disorders (notably including breast, brain, and colon cancers). Prior genome-wide linkage and association studies have now identified at least 18 genomic regions likely to contribute to the risk for nonsyndromic OFCs. Despite this substantial progress, the functional/pathogenic variants at OFC-associated regions are mostly still unknown. Because previous OFC genomic studies (genome-wide linkage, genome-wide association studies (GWAS), and targeted sequencing) are based on relatively sparse genotyping data, they cannot distinguish between causal variants and variants in linkage disequilibrium with unobserved causal variants. Moreover, it is unknown whether the association or linkage signals are due to single common variants, haplotypes of multiple common variants, clusters of multiple rare variants, or some combination. Finally, we cannot yet attribute specific genetic risk to individual cases and case families. Therefore, the goal of the current study is identify specific OFC risk variants in Latin American families by performing whole genome sequencing of parent-case trios.

Study phs001420

RNA-Seq in Patients with Primordial Dwarfism

Transcriptome studies in patients with rare genetic diseases can potentially aid in the interpretation of likely causal genetic variation through identification of altered transcript abundance and/or structure. RNA-Seq is the most sensitive assay for both investigating transcript structure and abundance The primary aim of this pilot project is to investigate to what degree integrating exome-Seq and RNA-Seq data on the same individual can accelerate the identification of causal alleles for rare genetic diseases. There are two main strands to this: (i) identifying which variants discovered in exome-seq appear to be having a functional impact on transcripts, and (ii) identifying transcript outliers, especially among known causal genes, that may not necessarily have a causal variant identified from exome sequencing. The latter may identify the presence of causal variants that lie far from coding regions (e.g. the formation of cryptic splice sites deep within introns, or loss of long range regulatory elements), which can be confirmed with further targeted genetic assays. Just over 50% of all disease-causing variants recorded in the Human Gene Mutation Database (HGMD) affect transcript structure and abundance (e.g. nonsense SNVs, essential splice site SNVs, frameshifting indels, CNVs). This pilot project will study RNA from lymphoblastoid cell-lines from 12 patients with primordial dwarfism syndromes, for 10 of these samples we have previously generate exome data as part of our collaboration with the group of Prof Andrew Jackson. The two remaining samples are positive controls where the causal mutation is known, and is known to affect transcript structure and/or abundance. Primordial dwarfism is a prime candidate for these RNA-seq studies because all known causal mutations to date have key roles in DNA replication and thus, unsurprisingly, the products of the causal genes are typically ubiquitously expressed. Each RNA will be sequenced, with two technical replicates (independent RT-PCR and libraries) per sample, and each replicate run in 1/2 of a HiSeq lane using 100bp paired reads. Samples preparation was as follows :The cells were grown to confluency, then pellets frozen at -80. RNA samples were prepared using the Qiagen RNeasy kit, then nanodropped and analyzed using the bioanalyzer to determine concentration and purity. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

Dataset EGAD00001000640

Gene Expression Signatures in CATHGEN

Case control cohort: The details have been previously published: American Heart Journal. 2010;160:371-379 e372. Briefly, a nested case:control cohort of CATHGEN participants who had experienced death or MI (n = 250) after their index catheterization and age-, sex-, and race-matched controls (n = 250) who were free of death/MI > 2 years after cardiac catheterization was identified as part of the MURDOCK Horizon 1 Cardiovascular Disease Study.21 Sufficient RNA for microarray analysis was available in 447 members of this cohort. Observational cohort: 224 sequential CATHGEN samples were selected for whole blood RNA analysis, of which, 191 had sufficient RNA for microarray analysis.

Study phs000551

RNA sequencing data from glioblastoma primary cell lines treated with indisulam data access committee

Four glioblastoma primary cell lines (BT592/pt1, BT1007/pt2, BT1009/pt3; BT1012/pt4) were derived from glioblastoma Cavitron Ultrasonic Aspirator (CUSA) material and cultured as neurospheres (GB-NS) in DMEM/F12+Glutamax medium containing B27 supplement (Thermofisher, Waltham, MA, USA) and the mitogenic factors epidermal growth factor (EGF) and fibroblast growth factor b (bFGF) (Peprotech, Rocky Hill, NJ, USA). GB-NS were confirmed mycoplasma-free by PCR Test. Cells were seeded in triplicate in 6-well plates, treated with 5 μM indisulam (Sigma Aldrich, Merk), or vehicle control, and collected after 6 and 16 hours for RNA extraction. Total RNA was extracted using TRIzol Reagent (Life Technologies, Thermo Fisher, cat n. 15596026), RNeasy Mini Kit, and RNase-Free DNase Set (Qiagen, cat n. 74104 and 79254). Sample QC, RNA library preparations, and sequencing reactions were conducted at GENEWIZ (Germany GmbH). The concentration of RNA was quantified using a Qubit Fluorometer (Life Technologies, Carlsbad, CA) and RNA integrity was assayed using a TapeStation. Sequencing libraries were prepared with RNA with PolyA selection and ERCC spike-in with standard ERCC kit (ERCC RNA Spike-In Mix,Thermo Fisher 4456740). Final libraries (Illumina, RNA with PolyA selection) were sequenced on a NovaSeq platform, producing 2×150 base paired-end reads.

Dac EGAC50000000407

Rapid response of APC/TP53/KRAS mutated stage IV colorectal cancer under FOLFIRI + Bevacizumab detected by liquid biopsy: a case report

In our non-interventional liquid biopsy study, a male patient in his fifties diagnosed with stage IV colorectal cancer and polytope liver metastases rapidly progressed after completing chemotherapy and deceased 8 months after diagnosis. Retrospective cell free DNA testing showed that the APC/TP53/KRAS major clone responded quickly after 3 cycles of FOLFIRI + Bevacizumab. Retrospective exome sequencing of pre-chemotherapy and post-chemotherapy tissue samples including metastases confirmed that the APC/TP53/KRAS and other major clonal mutations (GPR50, SLC5A, ZIC3, SF3A1 and others) were present in all samples. After the last chemotherapy cycle,

Study EGAS00001004088

Longitudinal copy number variation analysis from plasma DNA of head and neck cancer patients under re-radiotherapy

Recurrent locally advanced head and neck cancer (HNC) patients, receiving re-radiotherapy (re-RT), are presented with short progression-free (PFS) and overall survival. Hence, biomarkers predicting therapy failure are urgently needed. We analyzed copy number variations (CNVs) in blood plasma of HNC patients collected before, during and after re-RT. Detectable CNVs after five and ten fractions of re-irradiation as well as at the end of re-RT were associated with short PFS. Furthermore, we found that CNV kinetics in longitudinally collected plasma reflected therapy response and could detect disease progression in advance of radiographic tumor assessments.

Study EGAS50000000163

Linguistic utterance counts for The admixture histories of Cabo Verde

Datasets used in the article "The genetic and linguistic admixture histories of the islands of Cabo Verde" by Laurent R et al. eLife 2023 (DOI: https://doi.org/10.7554/eLife.79827 - URL: https://elifesciences.org/articles/79827) File name "eGAdeposit_225CaboVerde_FreeSpeech_Utterance_counts_FINAL_01062022.txt" Column 1 corresponds to individual alphanumeric codes as in the "eGAdeposit_233CaboVerde_GenotypeFile_FINAL_01062022.vcf" genotype file. Note that only 225 unrelated Cabo Verdean-born individuals are considered here, out of the 233 individuals in the genotype file. See Material and Methods in Romain Laurent et al. 2022 - doi pending Each 4831 other column correspond to the respective individual's utterance count in the free speech transcribed in ALUPEC and provided as column header. See See Material and Methods in Romain Laurent et al. 2022 - doi pendingColumn 1 corresponds to individual alphanumeric codes as in the "eGAdeposit_233CaboVerde_GenotypeFile_FINAL_01062022.vcf" genotype file. Note that only 225 unrelated Cabo Verdean-born individuals are considered here, out of the 233 individuals in the genotype file. See Material and Methods in Romain Laurent et al. 2022 - doi pending Each 4831 other column correspond to the respective individual's utterance count in the free speech transcribed in ALUPEC and provided as column header. See Material and Methods in Laurent R et al. eLife 2023

Dataset EGAD00001008978

The dataset for Detection and characterization of lung cancer using cell-free DNA fragmentomes

The dataset for Detection and characterization of lung cancer using cell-free DNA fragmentomes includes 872 bam files from whole genome next-generation sequencing on the Illumina HiSeq2500. The samples analyzed include plasma samples from healthy individuals and patients with cancer.

Dataset EGAD00001007796

eMERGE Network Genome-Wide Association Study of Red Cell Indices, White Blood Count (WBC) Differential, Diabetic Retinopathy, Height, Serum Lipid Levels, Specifically Total Cholesterol, HDL (High Density Lipoprotein), LDL (Low Density Lipoprotein), and Triglycerides, and Autoimmune Hypothyroidism.

The electronic Medical Records and Genomics (eMERGE) Network is a consortium of five participating sites (Group Health Seattle, Marshfield Clinic, Mayo Clinic, Northwestern University, and Vanderbilt University) funded by the NHGRI 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 19,000 individuals using EMR-derived phenotypes and DNA from linked Biorepositories. Using electronic phenotyping methods, the consortium used DNA samples from all participating sites to explore the genetic determinants of red cell indices, white blood count (WBC) differential, diabetic retinopathy, height, serum lipid levels, specifically total cholesterol, HDL (high density lipoprotein), LDL (low density lipoprotein), and triglycerides, and autoimmune hypothyroidism as well as using the phenome-wide association study (PheWAS) paradigm to replicate and discover relationships between targeted genotypes with multiple phenotypes. eMERGE led studies for which original genotyping was performed and are included in this merged set: Genome-Wide Association Study on Cataract and HDL in the Personalized Medicine Research Project Cohort, phs000170 Development and Use of Network Infrastructure for High-Throughput GWA Studies, phs000234 Vanderbilt Genome-Electronic Records (VGER) Project: QRS Duration, phs000188 Northwestern NUgene Project: Type 2 Diabetes, phs000237 A Genome-Wide Association Study of Peripheral Arterial Disease, phs000203 Sites and participants include: Vanderbilt University: BioVU, Vanderbilt's DNA databank, is an enabling resource for exploration of the relationships among genetic variation, disease susceptibility, and variable drug responses, and represents a key first step in moving the emerging sciences of genomics and pharmacogenomics from research tools to clinical practice. BioVU acquires DNA from discarded blood samples collected from routine patient care. The biobank is linked to de-identified clinical data extracted from Vanderbilt's EMR, which forms the basis for phenotype definitions used in genotype-phenotype correlations. Marshfield Clinic: The Marshfield Clinic Personalized Medicine Research Project is a population-based biobank in central Wisconsin with more than 20,000 adult subjects who provided written, informed consent to access their medical records and provided a blood sample from which DNA was extracted and plasma and serum stored. In addition to an average of 30 years of medical history data, a questionnaire about environmental exposures, including a detailed food frequency questionnaire, is available to facilitate gene/environment studies. Northwestern University: The NUgene Project is a repository with longitudinal medical information from participating patients at affiliated hospitals and outpatient clinics from the Northwestern University Medical Center. Participants' DNA samples are coupled with data from a self-reported questionnaire 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 2 million patients. NUgene has broad access to participant data for all outpatient visits as well as inpatient data via a consolidated 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. Group Health(GH)/University of Washington (UW): Aging and Dementia eMERGE study biorepository leverages rich population-based longitudinal data from both electronic medical records and in-depth research data to explore genome wide associations. Participants include Seattle-area members of GH (a large integrated health care system in Washington State) consented and enrolled in 1) the UW Alzheimer's Disease Patient Registry (ADPR) and 2) the Adult Changes in Thought (ACT) study. The ADPR (PI: Eric B. Larson; NIH/NIA U01 AG 006781) is a population-based registry of incident dementia cases designed to identify all new Alzheimer's Disease cases within GH from 1987 to 1996. Medical history, physical, laboratory testing, and neuropsychological testing were performed on all consenting potential cases for determination of dementia status by a consensus conference. The study base of the ADPR population was stable with an attrition rate of less than 1%/year. The ACT study (PI: Eric B. Larson; NIH/NIA U01 AG 006781) is an ongoing community-based cohort study of aging and dementia. The original cohort of 2,581 randomly selected dementia-free members age 65 and older was enrolled in 1994-1996 and expanded by 811 in 2000-2002. Continuous enrollment to maintain a cohort of 2,000 dementia free persons began in 2005. Participants receive biennial assessment including cognitive status determination. The ACT sub-sample is stable; for the original cohort, median enrollment in GH was 19 years prior to joining the ACT study, and 85% of the cohort has ≥10 years of GH enrollment. DNA for the ADPR participants were obtained through a companion study, Genetic Differences in Cases and Controls (PI: Walter Kukull; NIH/NIA R01 AG007584). DNA obtained through both studies were extracted from blood using Gentra Systems Puregene methods. DNA concentration is determined by UV optical density. All samples are checked for quality by 260/280 ratio. For long-term storage, samples are aliquoted and stored at -70°C. Mayo Clinic: The Mayo biobank is a disease-specific biobank for vascular diseases including peripheral arterial disease (PAD). PAD patients were identified from individuals referred to the non-invasive vascular laboratory for lower extremity arterial evaluation. Since 1997, laboratory findings have been recorded into an electronic database employing an in-house software package for data archiving and retrieval; this data becomes part of the Mayo EMR. Patients referred to the center with suspected PAD undergo a comprehensive non-invasive evaluation including the ankle-brachial index (ABI) - the ratio of blood pressure measured in the upper arms divided by blood pressure measured at the ankles. Controls subjects are identified from patients referred to the Cardiovascular Health Clinic for stress ECG. The prevalence of PAD in patients with normal exercise capacity who do not have inducible ischemia on the stress ECG, was <1%. Data regarding risk factors for atherosclerosis such as diabetes, dyslipidemia, hypertension, and smoking are ascertained from the EMR.

Study phs000360

Nicotine Addiction Genetics and Correlates

Ascertainment: Families were ascertained through panels of adult Australian twins, and a sample of spouses of Australian twins. Families with at least one offspring who was identified as a current or former smoker in an earlier survey. Screening telephone interviews were conducted with index cases to provide confirmation of a history of heavy cigarette smoking, to obtain confirmation of a history of heavy cigarette smoking, and to obtain additional information on the history of cigarette use and the survival status of other family members, and their full siblings and parents. Index cases were the affected spouse of a twin, or the affected twin from pairs discordant for a history of heavy smoking, or a randomly chosen twin from pairs where both have a history of regular smoking (i.e., has smoked at least 100 cigarettes lifetime), and at least one live biological parent to identify sibships with at least one affected sib pair (ASP) concordant for heavy smoking, and at least one living parent. If permission was granted by the index case, eligible family members were contacted and invited to provide a blood sample and to complete a telephone diagnostic interview. In families with just one available biological parent, and additional unaffected sibling who had never smoked on a regular basis (i.e., has smoked fewer than 100 cigarette lifetime, but has experimented with cigarettes once or twice) was included (when available) to help compensate for the loss of information due to missing parental phenotypes. (Target N=400 Australian families with approximately 600 ASPs; and 600 TDT trios comprised of a nicotine dependent index case and both biological parents). Diagnostic Assessment: The telephone diagnostic interview assessed DSM-IV and modified DSM-IIIR diagnoses (i.e., without time clustering) for nicotine dependence, alcohol and other drug dependence and abuse, major depression, and childhood conduct disorder. Most diagnostic assessments were based on the SSAGA/SSAGA-II, developed for the multi-site gene-mapping alcoholism study (the Collaborative Study on the Genetics of Alcohol. An exception was the tobacco section, which was developed directly from the CIDI and DIS (as the original SSAGA did not include a diagnostic section on nicotine dependence). In version 2 of this study, a text file containing 7704 SNPs with large allele frequency discrepancy as compared to 1000 Genomes is included. Users have the option to exlude these 7704 SNPs.

Study phs001299

Alzheimer's Disease Sequencing Project (ADSP)

NOTICE OF CHANGE IN LOCATION FOR ALZHEIMER'S DISEASE SEQUENCING PROJECT (ADSP) GENETIC AND PHENOTYPIC DATA: ADSP whole exome and whole genome sequence data that are shared through dbGaP were mapped to the Genome Reference Consortium human genome GRCh37 (build 37). These data are from the Discovery Phase of the project (described below) and will continue to be available at this site. Please see the ADSP Design page for the complete study description. All data that are mapped to GRCh38 (hg38) are being shared through the NIA Genetics of Alzheimer's Disease Data Storage Site (NIAGADS) Data Sharing Service (DSS). For instructions on how access the ADSP Build 38 data that are shared through NIAGADS DSS, visit the Application Instructions page. STUDY DESCRIPTION FOR dbGaP BUILD 37 ADSP DATA: The overarching goals of the Alzheimer's Disease Sequencing Project (ADSP) are to: (1) identify new genomic variants contributing to increased risk of developing Alzheimer's Disease (AD), (2) identify new genomic variants contributing to protection against developing AD, and (3) provide insight as to why individuals with known risk factor variants escape from developing AD. These factors will be studied in multi-ethnic populations in order to identify new pathways for disease prevention. Such a study of human genomic variation and its relationship to health and disease requires examination of a large number of study participants and needs to capture information about common and rare variants (both single nucleotide and copy number) in well phenotyped individuals. Using existing samples from NIH funded and other studies, three NHGRI funded Large Scale Sequencing and Analysis Centers (LSAC) - Broad, Baylor, and Washington University - produced the DNA sequence data. Variant call data are being made available to the scientific community through NIH-approved data repositories. Statistical analysis of the sequence data is anticipated to identify new genetic risk and protective factors. The ADSP will conduct and facilitate analysis of sequence data to extend previous discoveries that may ultimately result in new directions for AD therapeutics. Analysis of ADSP data will be done in two phases. The Discovery Phase analysis (2014-2018) is funded under PAR-12-183. The entire Discovery dataset contains whole-genome sequencing data on 584 subjects from 113 families, and pedigree data for > 4000 subjects; whole exome sequencing data on 5096 cases 4965 controls; and whole exome sequence data on an additional 853 (682 Cases [510 Non-Hispanic, 172 Hispanic]), and 171 Hispanic Control subjects from families that are multiply affected with AD. The Replication Phase (2016-2021) analysis will be funded under RFA-AG-16-001 and RFA-AG-16-002 and is expected to include a combination of genotyping and sequencing approaches on at least 30,000 subjects. Targeted sequencing will be done by the LSACs. GRCh37 Data Releases The first ADSP data release occurred on November 25, 2013. It included the whole-genome sequencing data in BAM file format on 410 individuals. The second ADSP data release occurred on March 31, 2014, and included the whole-genome sequencing data in BAM file format for an additional 168 individuals. The third ADSP data release occurred on November 03, 2014 and included whole-exome sequencing data in BAM file format for 10,939 individuals. The fourth ADSP data release occurred on February 13, 2015 and included revised ethnic data for subjects with whole-exome sequencing data. The fifth ADSP data release occurred on July 13, 2015 and included whole-genome genotypes and updated phenotypes as well as changes to pedigree structures and sample IDs. The sixth ADSP data release occurred on December 8, 2015, and included whole-exome genotypes and updated phenotypes as well as changes to subject IDs. This seventh ADSP data release on April 12, 2016 includes: (1) WES and WGS SNV VCF files (2) WES and WGS Indel PLINK files ADSP Data Available through dbGaP: ADSP - Whole Genome Sequencing ADSP - Whole Exome Sequencing Comments DNA-Seq (BAM) n=578 n=10913 Sequence data available (plus n=38 replications w/out genotype data) Concordant SNV Genotypes (PLINK format) N/A n=10913 QC'ed genotypes that are concordant between the Atlas (Baylor's) and GATK (Broad's) calling pipelines (a subset of the consensus genotype set) Consensus Genotypes (PLINK and VCF format) n=578 n=10913 QC'ed genotypes that are concordant between Atlas and GATK pipelines as well as those that that were called uniquely by Atlas or GATK Concordant Indel Genotypes (PLINK format) n=578 n=10913 QC'ed genotypes that are concordant between the Atlas and GATK calling pipelines Phenotype Data n=4735 n=10913 Data of n=53 phenotype variables available (plus administrative data), including APOE genotype. WGS phenotypes include data of connecting family members. Please use the release notes provided by dbGaP to obtain detailed information about study release updates. The ADSP data portal provides a customized interface for users to quickly identify and retrieve files by covariates, phenotypes, and data properties such as sequencing facility or coverage. For more information about the ADSP study and the data portal, please visit https://www.niagads.org/adsp/.

Study phs000572

WGS data of paediatric ETV6::RUNX1 B cell acute lymphoblastic leukemia (set3)

The dataset includes FASTQ and CRAM files from diagnostic and matched remission (control) samples of two ETV6::RUNX1 ALL patients (ALLT-397, ALLK-132). Sequencing libraries were made using PCR free-based WGS library preparation (PCR-), using Novogene NGS DNA Library Prep Set (Cat No. PT004). Both diagnostic (90x) and remission (30x) samples were sequenced using Illumina NovaSeqX Plus.

Dataset EGAD50000002287

WGS data of paediatric B-other B cell acute lymphoblastic leukemia (set2)

The dataset includes FASTQ and BAM files from diagnostic and matched remission (control) samples of four B-other ALL patients (ALLT-321, ALLT-311, ALLT-314, ALLT-319). Sequencing library was made using PCR free-based WGS library preparation (PCR-), using TruSeq DNA PCRfree library preparation kit v1. Both diagnostic (60x) and remission (30x) samples were sequenced using HiSeq X.

Dataset EGAD50000002156

TGL49_LFS cfMeDIP

Cell-free methylated DNA immunoprecipitation sequencing of plasma samples from patients with Li-Fraumeni syndrome.

Dataset EGAD00001010013

How to request data

Request Data Access If you're looking to access data from the EGA for your research, you are in the right documentation page! In this page you will find a step by step guide on how to request data archived at the EGA, as well as some frequently asked questions you might find useful. When requesting data, you'll need to provide information about your research project and intended use of the data. Keep in mind that your data access request may require additional approvals or agreements depending on the datasets and data providers involved. Step by step guide Register yourself as an EGA user. Validate your account. A validation link will be sent to your email to activate your EGA user account. Log into the EGA page. Search the dataset of interest from the dataset catalogue or search bar. Click on “Request access” Add a comment requesting these files and send your request Your request is successfully registered, and the DAC will receive a notification about your request In addition to submitting your request, you should also contact the DAC directly via e-mail. You can access the DAC's contact information from the relevant dataset page. Frequently Asked Questions (FAQ) Which is the role of the EGA in the data access process? The European Genome-phenome Archive (EGA) facilitates the secure distribution under controlled access of personally identifiable genetic and phenotypic data. Data Access Committee (DAC) is a body of one or more individuals who are responsible for data release to external requestors, based on participant consent and/or National Research Ethics terms. How do I request access to multiple datasets? To request access for multiple datasets managed by the same Data Access Committee (DAC), please start by visiting the DAC catalogue to locate the DAC of your choice. Once you've found the relevant DAC, proceed to its dedicated page where you'll find a "Request access" button. After logging in to the EGA website, you'll be presented with a comprehensive list of datasets under the chosen DAC. Select the datasets you're interested in, and then compose a message indicating your access request. Click the "Send" button to submit your request, which will include the chosen datasets. Please be sure to review the data usage policies for the requested datasets, as policies can vary among datasets managed by the same DAC. I am a co-applicant. Will I be given a joint access account? Each applicant needs to create an EGA account themselves, with unique login details. User log-in details are for individual use only and should never be shared, under any circumstances. EGA services are only provided to EGA account holders. Therefore, the co-applicant will send a formal request to the DAC. What happens if a co-applicant leaves or a new member needs to be added to an existing DAC application? The appropriate Data Access Committee (DAC) should be contacted and informed about the required changes so that the application can be updated. I have changed my place of work since my EGA account was created. Can I still have access to data? You must contact the relevant Data Access Committee (DAC). The DAC did not reply to my data access request. How should I proceed? There is no estimated time for DAC response. Please allow up to four weeks for a response. In the meantime, please send them a weekly reminder of the status of your request by emailing them directly.If the DAC becomes unresponsive, meaning that they fail to communicate with a requestor within the specified time frame, please contact the EGA Helpdesk team. I have an account with the EGA and would like access to further datasets. How should I proceed? You need to reapply to the relevant Data Access Committee (DAC). Once the DAC has approved your application your account will be updated and an email will be sent to notify you of a change made to your account. How do I download files of the datasets I have been granted access to? The preferred method for data download and decryption is the EGA Secure Download Client. Please carefully review the provided documentation. How do I download metadata? Metadata is retrieved from the EGA webpage; you will not need to use any download client. Be informed that you will only be able to download metadata of your approved datasets. For such download, you should first log in the EGA webpage with your credentials. Then browse the metadata's dataset you have gained access and you will find a metadata download button. You may also want to have a look our metadata schema. I have forgotten or misplaced my user account password; how do I get a new one? Click on “Log in”, located in the top right corner of the EGA homepage. Then click “Forgot password”, type in your registered institutional email address, and instructions for resetting your password will be sent to you. Please check both regular and junk/spam folders. I was sent a link to set a password for my download account, but it seems like the link has expired. What should I do? The procedure is the same as the one for a forgotten password, explained in the previous question.

Documentation access/request-data/how-to-request-data

Liquid Biopsy Versus Tissue Biopsy to Assess Acquired Resistance and Tumor Heterogeneity in Gastrointestinal Cancers

Tumor heterogeneity can drive the evolution of multiple tumor subclones harboring unique molecular resistance alterations in different metastatic lesions in an individual patient, under the selective pressure of therapy1-3. Studies have suggested that liquid biopsy may better capture the heterogeneity of acquired resistance, but systematic, direct comparisons of post-progression liquid vs. standard single-lesion tumor biopsies are lacking. In a prospective cohort of 44 patients with molecularly-defined gastrointestinal cancers and acquired resistance to targeted therapy, direct comparison of post-progression liquid vs. tumor biopsy revealed that liquid biopsy more frequently identified clinically-relevant resistance alterations and multiple resistance mechanisms, detecting resistance alterations not detected in matched tumor biopsy in 78% of cases. Whole-exome sequencing of serial cell-free DNA, tumor biopsies and rapid autopsy specimens elucidated geographic and evolutionary characteristics of heterogeneity. Our data suggest that acquired resistance is frequently characterized by profound tumor heterogeneity and highlight the potential clinical utility of liquid biopsy. Burrell, R. A. & Swanton, C. Tumour heterogeneity and the evolution of polyclonal drug resistance. Molecular oncology 8, 1095-1111, doi:10.1016/j.molonc.2014.06.005 (2014). Misale, S. et al. Emergence of KRAS mutations and acquired resistance to anti-EGFR therapy in colorectal cancer. Nature 486, 532-536, doi:10.1038/nature11156 (2012). Ahronian, L. G. et al. Clinical Acquired Resistance to RAF Inhibitor Combinations in BRAF-Mutant Colorectal Cancer through MAPK Pathway Alterations. Cancer Disco 5, 358-367, doi:10.1158/2159-8290.Cd-14-1518 (2015).

Study phs001853

Neoadjuvant immunotherapy leads to pathological responses in MMR proficient and MMR deficient early stage colon cancers

PD-1 plus CTLA-4 blockade is highly effective in advanced-stage, mismatch repair (MMR)-deficient (dMMR) colorectal cancers, yet not in MMR-proficient (pMMR) tumors. We postulated a higher efficacy of neoadjuvant immunotherapy in early-stage colon cancers. In the exploratory NICHE study (ClinicalTrials.gov: NCT03026140), patients with dMMR or pMMR tumors received a single dose of ipilimumab and two doses of nivolumab before surgery, the pMMR group with or without celecoxib. The primary objective was safety and feasibility; 40 patients with 21 dMMR and 20 pMMR tumors were treated, and 3 patients received nivolumab monotherapy in the safety run-in. Treatment was well tolerated and all patients underwent radical resections without delays, meeting the primary endpoint. Of the patients who received ipilimumab + nivolumab (20 dMMR and 15 pMMR tumors), 35 were evaluable for efficacy and translational endpoints. Pathological response was observed in 20/20 (100%; 95% exact confidence interval (CI): 86–100%) dMMR tumors, with 19 major pathological responses (MPRs, ≤10% residual viable tumor) and 12 pathological complete responses. In pMMR tumors, 4/15 (27%; 95% exact CI: 8–55%) showed pathological responses, with 3 MPRs and 1 partial response. CD8+PD-1+ T cell infiltration was predictive of response in pMMR tumors. These data indicate that neoadjuvant immunotherapy may have the potential to become the standard of care for a defined group of colon cancer patients when validated in larger studies with at least 3 years of disease-free survival data.

Study EGAS00001004160

Exome Sequencing Of 75 Individuals From Multiply Affected Coeliac Families

Coeliac disease is a highly heritable common autoimmune disease involving chronic small intestinal inflammation in response to dietary wheat. The human leukocyte antigen (HLA) region, and 40 newer regions identified by genome wide association studies (GWAS) and dense fine mapping, account for ~40% of the disease heritability. We hypothesized that in pedigrees with multiple individuals with coeliac disease rare [minor allele frequency (MAF) <0.5%] mutations of larger effect size (odds ratios of ~ 2 – 5) might exist. We sequenced the exomes of 75 coeliac individuals of European ancestry from 55 multiply affected families. We selected interesting variants and genes for further follow up using a combination of: an assessment of shared variants between related subjects, a model-free linkage test, and gene burden tests for multiple, potentially causal, variants. We next performed highly multiplexed amplicon resequencing of all RefSeq exons from 24 candidate genes selected on the basis of the exome sequencing data in 2,248 unrelated coeliac cases and 2,230 controls. 1,335 variants with a 99.9% genotyping call rate were observed in 4,478 samples, of which 939 were present in coding regions of 24 genes (Ti/Tv 2.99). 91.7% of coding variants were rare (MAF <0.5%) and 60% were novel. Gene burden tests performed on rare functional variants identified no significant associations (P<1x10-3) in the resequenced candidate genes. Our strategy of sequencing multiply affected families with deep follow up of candidate genes has not identified any new coeliac disease risk mutations.

Study EGAS00001001093

TRACERx 100: whole exome data of the first 100 TRACERx tumours

BACKGROUNDTRACERx (TRAcking Cancer Evolution through therapy (Rx)) is a prospective cohort study designed to investigate intratumor heterogeneity (ITH) in relation to clinical outcome, and to determine the clonal nature of driver events and evolutionary processes in early stage non-small cell lung cancer (NSCLC). METHODSMultiregion high-depth whole-exome sequencing (M-seq) was performed on 100 early stage NSCLC tumors resected prior to systemic therapy. A total of 327 tumor regions were sequenced and analyzed to define evolutionary histories, obtain a census of clonal and subclonal events, and assess the relationship between ITH and recurrence-free survival (RFS). RESULTSWidespread ITH was observed for both somatic copy number alterations (median 48% [0.03-88%]) and mutations (median 30% [0.5-93%]). Driver mutations in EGFR, MET, BRAF and TP53 were almost always clonal. However, heterogeneous driver alterations occurring later in evolution were found in over 75% of tumors and were common in PIK3CA, NF1 and genes involved in chromatin modification and DNA response and repair. Genome doubling and ongoing dynamic chromosomal instability (CIN), illustrated by mirrored subclonal allelic imbalance, were identified as causes of ITH resulting in parallel evolution of driver copy number events, including amplifications of CDK4, FOXA1, and BCL11A. Elevated copy number heterogeneity was associated with shorter RFS (HR=4.9, P=0.00044), which remained significant in a multivariate analysis.CONCLUSIONSITH mediated through CIN, rather than point mutational heterogeneity, was associated with increased risk of relapse, supporting its value as a prognostic predictor, and the need to target this high-risk phenotype.

Study EGAS00001002247

Clinical relevance of somatic copy-number alterations in plasma circulating tumor DNA from advanced EGFR-mutated NSCLC patients treated with osimertinib

Background: Somatic copy-number alterations (SCNAs) are associated with drug resistance in patients with advanced epidermal growth factor receptor (EGFR)-mutated non-small cell lung cancer (NSCLC) treated with EGFR-tyrosine kinase inhibitors (TKIs). The purpose of our study was to assess the clinical relevance and development of genome-wide SCNAs in plasma circulating tumor DNA (ctDNA) under osimertinib therapy.Methods: We included 43 patients with advanced EGFR T790M-positive lung adenocarcinoma who were treated with osimertinib after progression under previous EGFR-TKI therapy. We performed genomic profiling of ctDNA in plasma samples from each patient obtained pre-osimertinib and after patients developed resistance to osimertinib. SCNAs were detected by shallow whole-genome plasma sequencing and EGFR mutations were assessed by droplet digital PCR.Results: SCNAs in resistance-related genes (rrSCNAs) were detected in 10 out of 39 (25.6%) evaluable patients before start of osimertinib. The presence of rrSCNAs in plasma before initiation of osimertinib therapy was associated with a lower response rate to osimertinib (50% versus 86%, p=0.02) and was an independent predictor for shorter progression-free survival (adjusted HR 3.26, 95% CI 1.37-7.75, p=0.008) and overall survival (adjusted HR 2.41, 95% CI 1.09-5.34, p=0.03).Conclusions: Genomic profiling of plasma ctDNA is clinically relevant and affects the efficacy and clinical outcome of osimertinib. Our approach allows comprehensive assessment of SCNAs in plasma samples of lung adenocarcinoma patients and may help to guide genotype-specific therapeutic strategies in the future.

Study EGAS00001004539

Download Metadata

Metadata Distribution Welcome to the realm of Metadata Distribution within the EGA ecosystem! Our Metadata REST API empowers you to effortlessly retrieve metadata from the expansive landscape of EGA. By utilising this API, you gain access to publicly available insights across various EGA domains, including studies, samples, experiments, runs, analyses, policies, DACs, and datasets. Furthermore, this API facilitates cross-referencing of objects, enabling you to gather, for example, all the datasets associated with a specific DAC, seamlessly. In addition, we have added the ability to query private data using the metadata API. If you possess the necessary permissions, you can access behind-the-login private data for a specified list of datasets. Metadata Distribution Index Identifiers Dataset Mappings Website Download Metadata API - Private Identifiers At the core of EGA's organisational structure are unique accessions that serve as essential tags for our diverse objects. Here's a quick overview of the accessions and their corresponding object types: EGA Accession ID EGA Object description EGAS EGA Study Accession ID EGAC EGA DAC Accession ID EGAP EGA Policy Accession ID EGAN EGA Sample Accession ID EGAR EGA Run Accession ID EGAX EGA Experiment ID EGAZ EGA Analysis Accession ID EGAD EGA Dataset Accession ID EGAB EGA Submission ID EGAF EGA File Unique Accession ID For further information check our metadata schema documentation. Dataset Mappings For authorised datasets, comprehensive mappings reveal meaningful connections: Sample_file: This file presents information about the linkage between samples and files available in the dataset. Study_experiment_run_sample: This file presents information about the linkage between studies, experiments, runs, and samples within the dataset. Study_analysis_sample: This file presents information about the linkage between studies, analyses, and samples contained within the dataset. Run_sample: This file presents information about the linkage between runs and samples within the dataset. Analysis_sample: This file presents information about the linkage between analyses and samples within the dataset. An empty file indicates the absence of corresponding information. Website Download Our website serves as your gateway to downloading metadata. Simply navigate to the dataset page, and you'll find a blue Metadata button. Once authenticated, you can click this button for authorised datasets. If you lack permissions for a particular dataset, request access by clicking the 'Request Access' button. For authorised datasets, choose your preferred metadata format: CSV, TSV, or JSON. Metadata API - Private Leverage the power of programmatic metadata downloads! Start by authenticating yourself with your credentials to obtain an access token. With this token, programmatically query private information. Queries mirror the structure of the Public Metadata API. However, behind the login, you can delve into specific mapping information (as mentioned above in dataset mappings) alongside object-level exploration. Authentication An active session is required to work with the API. Each time you log in with your credentials a new session is started, which is identified by an access_token. Below an example on how to obtain one using curl: curl https://idp.ega-archive.org/realms/EGA/protocol/openid-connect/token \ -d 'client_id=metadata-api' \ -d 'username=...' \ --data-urlencode 'password=...' \ -d 'grant_type=password' All responses from the API are in JSON format. A successful response should include a new token to be used for the session: {"access_token":"eyJhbGciOiJSUzI1NiIsInR5cCIgOiA...TNw", "expires_in":300, "refresh_expires_in":1800, "refresh_token":"eyJhbGciOiJIUzI1NiIsInR5cCIgOiA...pTX10", "token_type":"Bearer", ... } Save the access_token value and include it in the API call headers. Example query usage Below you can find some example of queries available behing authentication and authorisation. Querying study-experiment-run-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/study_experiment_run_sample \ -H 'Authorization: Bearer access_token' Querying run-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/run_sample \ -H 'Authorization: Bearer access_token' Querying study-analysis-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/study_analysis_sample \ -H 'Authorization: Bearer access_token' Querying analysis-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/analysis_sample \ -H 'Authorization: Bearer access_token' Querying sample-file mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/sample_file \ -H 'Authorization: Bearer access_token' You can get a different output format by adding one of these options to the curl command: -H 'Accept: text/tsv' -H 'Accept: application/json' -H 'Accept: text/csv' For more detailed information, refer to the Metadata API Specification.

Documentation access/download/metadata

ILyAD (Indolent Lymphoma And vitamin D)

Indolent non-Hodgkin lymphomas are incurable diseases, and require intermittent and often morbid and expensive therapy during their prolonged natural history. Lower intensity and better-tolerated, cost-effective treatment strategies are needed for these patients. Low vitamin D levels at diagnosis of indolent lymphomas are strongly associated with inferior outcomes to treatment. Standard therapy for low tumor burden, indolent lymphoma includes a single agent monoclonal antibody (rituximab). In our double-blind, placebo-controlled, randomized trial we evaluated if vitamin D supplementation with 2000IU oral cholecalciferol daily for three years improved the progression-free survival of patients with indolent lymphoma treated with single agent rituximab. Stratification factors for randomization included histology and Follicular Lymphoma International Prognostic Index (FL-IPI) prognostic score. The primary endpoint of the trial was progression-free survival over three years; secondary endpoints included response at 13 weeks, and overall survival. Eligible participants were adults with biopsy proven follicular lymphoma (grades 1-3a), small lymphocytic lymphoma, marginal zone lymphoma and mucosal-associated lymphoid tissue with no prior anti-lymphoma systemic therapy. Participants had Ann Arbor stage II or greater, measurable disease defined by Lugano criteria. Participants with osteoporosis requiring prescription treatment, symptomatic primary hyperthyroidism, hypercalcemia, creatinine greater than 1.5 times the upper limit of normal or a history of calcium-related kidney stones were excluded. Germline DNA was isolated from saliva samples obtained from participants at baseline. Whole exome sequencing was performed and SNPs were analyzed using the Agilent SureSelectXT Human All Exon V6 +UTR array. SNP data from 185 participants are available through dbGaP.

Study phs003503

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