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• Natural genetic variation of the cardiac transcriptome in non-diseased donors and patients with dilated cardiomyopathy

  Background: Genetic variation is an important determinant of RNA transcription and splicing, which in turn contributes to variation in human traits including cardiovascular diseases.Results: Here we report the first in-depth survey of heart transcriptome variation using RNA-sequencing in 149 (97)* patients with dilated cardiomyopathy and 113 (108)* non-diseased controls. We reveal extensive differences of gene expression and splicing between dilated cardiomyopathy patients and controls, affecting known as well as novel dilated cardiomyopathy genes. Moreover, we show a widespread effect of genetic variation on the regulation of transcription, isoform usage and allele specific expression. Systematic annotation of genome wide association SNPs identifies 60 functional candidate genes for heart phenotypes, representing 20% of all published heart genome wide association loci. Focusing on the dilated cardiomyopathy phenotype we found that eQTL variants are also enriched for dilated cardiomyopathy genome wide association signals in two independent cohorts.Conclusions: RNA transcription, splicing and allele specific expression are each important determinants of the DCM phenotype and are controlled by genetic factors. Our results represent a powerful resource for the field of cardiovascular genetics. (*) numbers in parentheses represent samples that the publication is based on.

  Study EGAS00001002454

• UK10K_RARE_NEUROMUSCULAR

  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. The neuromuscular disorder samples are part of the “rare disease” group, and will undergo exome sequencing. For further information with regard to this cohort please contact Francesco Muntoni (f.muntoni@ucl.ac.uk).

  Study EGAS00001000101

• UK10K_RARE_FIND

  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. The Raymond samples will be part of the “rare disease” group, and will undergo exome sequencing. For further information with regard to this cohort please contact Lucy Raymond (flr24@cam.ac.uk).

  Study EGAS00001000128

• UK10K_RARE_CILIOPATHIES

  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. The Ciliopathies samples will be part of the rare disease group, and will undergo exome sequencing. For further information with regard to this cohort please contact Phil Beales (p.beales@ich.ucl.ac.uk).

  Study EGAS00001000126

• UK10K_RARE_SIR

  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.The SIR (Severe Insulin Resistance) samples are part of the “rare disease” group, and will undergo exome sequencing. For further information with regard to this cohort please contact Robert Semple (rks16@cam.ac.uk).

  Study EGAS00001000130

• Stratifying and Targeting Pediatric Medulloblastoma through Genomics

  In this project, genomic analyses of pediatric medulloblastoma samples, obtained through the international medulloblastoma consortium, will be performed. RNA and miRNA expression profiles of 1000 samples, representing all four subgroups (Wnt, Shh, Group C, and D), will be studied to identify novel subtypes within each subgroup. The resulting subtype-specific expression profiles will support the development of reliable and robust biomarkers to more accurately and reliably classify medulloblastomas for treatment in clinical trials. For that purpose, two assays will be developed: an antibody-based immunohistochemical assay and an orthogonal nucleic acid-based hybridization assay. Additional genomic DNA analysis of the 300 high risk subgroup cases will support the discovery of subgroup specific somatic mutations in order to inform current clinical trials of targeted therapies, and to identify genes and pathways already targeted in other diseases. Such therapies could be rapidly transitioned to Phase II trials in medulloblastoma. Furthermore, the discovery of somatic mutations could be used for developing as well as validating specific biomarkers. The project team will also try to identify risk factors that predispose children to this type of cancer.

  Study EGAS00001000273

• Genomic Alterations in Gingivo-buccal Cancer: ICGC-India Project_YR02

  As a part of the ICGC, India has undertaken genomic studies on gingivobuccal cancer of the oral cavity, which is the most prevalent form of cancer among men in India. There are various known environmental (life-style) correlates of this cancer, the most important of which are tobacco chewing and HPV infection. Paired DNA samples – isolated from the tumour tissue and from the blood of fifty six patients – have been analyzed to catalog germline and somatic mutations. Association between each observed genomic alteration and exposure to environmental risk factors is being explored.Detailed clinical characterization of the patients, collection of data on demographic and environmental exposures, and isolation of DNA samples from blood and tumour tissues collected from each patient are being done at the Advanced Centre for Research, Treatment and Education on Cancer, Mumbai. Exome capture and deep resequencing are being performed at the National Institute of Biomedical Genomics, Kalyani. We have analyzed the exomes of paired blood and tumour DNA samples using exome capture by Illumina TrueSeq Exome Enrichment kit followed by sequencing on Illumina HiSeq-2000. Each exome is being sequenced at a mean depth of 70x for Tumour and 40x for Blood. In addition, we have used Illumina Omni 2.5 SNP-chips to generate genotype data.

  Study EGAS00001001028

• CRUK-ICGC Prostate Cancer Group Study

  Prostate cancer somatic genomic sequencing data generated from 2011 onwards under auspices of the International Cancer Genome Consortium Prostate Cancer UK consortium (CRUK-ICGC Prostate Group), co-led by Colin Cooper and Ros Eeles, with other Principal Investigators (Brewer, Neal, Bova, McDermott, Wedge, Lynch, Massie, and Foster) and others as listed in study publications. Funded by Cancer Research UK and other funders as listed in study publications. Contents and publications related to each dataset are described with each dataset (EGAD) entry. Our study was funded with the ambition of collecting Whole Genome DNA sequence data from 250 prostate cancers, with matching transcriptome and methylome data. The original aims of the project were: 1.To understand the significance of multifocal prostate cancer. 2.To understand the clinical heterogeneity of prostate cancer to devise markers for predicting outcome and for drug targeting. 3.To understand the molecular basis of development and spread of castration-resistant and metastatic disease 4.To understand the aetiology of prostate cancer particularly the large variation in incidences that occur in different populations and ethnic groups. Please see https://doi.org/10.5281/zenodo.4022439 for links between sample IDs reported in literature and EGA IDs.

  Study EGAS00001000262

• Exploring the role of mtDNA variation in Multiple Sclerosis in a large cohort of discordant monozygotic twins

  Several lines of evidence indicate that mitochondrial DNA (mtDNA) variants might predispose to multiple sclerosis (MS). We examined this in 49 monozygotic (MZ) twin pairs clinically discordant for MS at study entry. Since the nuclear DNA of MZ twins is identical, our study provides a unique setting to functionally associate unique mtDNA variants and skewed heteroplasmy with MS development. In order to identify mtDNA variants in the twin cohort, we deeply sequenced the mitochondrial genome in blood of all 49 MZ twin pairs using next generation sequencing (Illumina, HiSeq or MiSeq) with an average coverage depth of ~25,000 sequences per base. Heteroplasmic variants were validated using targeted deep sequencing (TDS) (Illumina, MiSeq) in DNA isolated from blood and buccal swabs. In addition, whole blood was also available of 5 additional MS-affected or healthy siblings and 1 dizygotic twin pair discordant for MS, comprising in total 6 non-identical sib pairs. Moreover, all cases were screened for pathogenic mtDNA polymerase gamma (POLG) mutations. The data provides valuable insights in the possible involvement of mtDNA variants in the pathogenesis of MS, and gives information on the segregation of heteroplasmic variants within MZ twins and non-identical siblings and across different tissues.

  Study EGAS00001001240

• The Prediction and Prevention of Preeclampsia

  The Prediction and Prevention of Preeclampsia (PREDO) is a prospective birth cohort study of Finnish women who were pregnant between 2005 and 2010 and their children. The PREDO study cohort was set up to identify novel risk factors and biomarkers in pregnant women associated with the development of preeclampsia and intrauterine growth restriction (IUGR). Two groups of pregnant women were enrolled during the first trimester of their pregnancy: first, pregnant women with a known clinical risk factor status for preeclampsia and IUGR (N=1079; 969 of these women had at least one and 110 had none of the known risk factors for preeclampsia and IUGR), and second, pregnant women who volunteered to participate regardless of their risk factor status for preeclampsia and IUGR (N=3698). Both samples were monitored during pregnancy with four clinical visits and bi-weekly self-reports. The post-delivery follow-up has taken place at approximately 2 weeks, 6 months, and 3.5 years after the delivery. The most recent follow-up started in 2016 and is ongoing. In the high-risk sample, cord blood samples were collected and genome-wide genotyping has been conducted with Illumina OmniExpressExome 1.2 and genome-wide methylation status has been analysed with Illumina 450k HM array.

  Study EGAS00001001898

• Whole Exome Sequencing PPGL

  Whole exome sequencing (WES) libraries were prepared with the SureSelectXT Human All Exon V6+COSMIC target enrichment system (Agilent, 5190-9307) by following kit manufacturer`s instructions. 200 ng of genomic DNA from FFPE tumoral samples and 1 µg from FF or germline samples were used as starting material. SureSelectXT HS (Agilent, G9704A) and SureSelectXT2 (Agilent, G9621A) reagent kits were alternatively used for FFPE derived and good quality samples, respectively. DNAs were fragmented on a Covaris S2 sharing instrument based on initial sample’s integrity. Fragmented DNA samples were processed through subsequent enzymatic treatments of end-repair, dA-tailing, and ligation to Illumina's adapters. Adapter-ligated libraries were PCR amplified with Illumina PE primers and subsequently hybridized to SureSelect Oligo Capture Library Mix. Biotinylated hybrids were captured and the enriched fraction eluted. Libraries were completed by limited-cycle PCR with Illumina TruSeq primers and KAPA HiFi HotStart DNA pol (Roche KK2501). Sample-specific libraries were combined into equimolarly balanced pools and applied to Illumina flow cells for cluster generation. Sequencing was performed on either the Illumina HiSeq2500 or NovaSeq6000 in a paired-end 100bp reads mode to a median target coverage of ~200x and ~100x for tumors and germline, respectively.

  Study EGAS00001006043

• Whole genome sequencing delineates regulatory, structural, and cryptic splice variants in early onset cardiomyopathy

  Cardiomyopathy (CMP) is a heritable disorder. Over 50% cases are gene-elusive on clinical gene panel testing. The contribution of variants in non-coding DNA elements that result in cryptic splicing and regulate gene expression has not been explored. We analyzed whole genome sequencing (WGS) data in a discovery cohort of 209 pediatric CMP patients and 1,953 independent replication genomes and exomes. We searched for protein-coding variants, and non-coding variants predicted to affect the function or expression of genes. Thirty-nine % cases harbored pathogenic coding variants in known CMP genes, and 5% harbored high-risk loss-of-function (LoF) variants in additional candidate CMP genes. Fifteen % harbored high-risk regulatory variants in promoters and enhancers of CMP genes (Odds ratio 2.25, p=6.70×10-7 versus controls). Genes involved in α-dystroglycan glycosylation (FKTN, DTNA) and desmosomal signaling (DSC2, DSG2) were most highly enriched for regulatory variants (Odds ratio 6.7-58.1). Functional effects were confirmed in patient myocardium and reporter assays in human cardiomyocytes, and in zebrafish CRISPR knockouts. We provide strong evidence for the genomic contribution of functionally active variants in new genes and in regulatory elements of known CMP genes to early-onset CMP.

  Study EGAS00001004929

• Significant and pervasive effects of RNA degradation on Nanopore direct RNA sequencing

  Abstract Oxford Nanopore direct RNA sequencing (DRS) is capable of sequencing complete RNA molecules and accurately measuring gene and isoform expression. However, as DRS is designed to profile intact RNA, expression quantification may be more heavily dependent upon RNA integrity than alternate RNA-seq methodologies. It is currently unclear how RNA degradation impacts DRS or if it can be corrected for. To assess the impact of RNA integrity on DRS we performed a degradation time-series using SH-SY5Y neuroblastoma cells. Our results demonstrate that degradation is a significant and pervasive factor that can bias DRS measurements, including a reduction in library complexity resulting in an overrepresentation of short genes and isoforms. Degradation also biases differential expression analyses; however, we find explicit correction can almost fully recover meaningful biological signal. In addition, DRS provided less biased profiling of partially degraded samples than nanopore cDNA-PCR sequencing. Overall, we find samples with RIN > 9.5 can be treated as undegraded and samples with RIN > 7 can be utilised for DRS with appropriate correction. These results establish the suitability of DRS for a wide range of samples, including partially degraded in-vivo clinical and post-mortem samples, whilst limiting the confounding effect of degradation on expression quantification.

  Study EGAS00001006542

• FASTQ files of total RNA-Seq data from the POPS PET (pre-eclamptic) samples

  All the samples were obtained from the Pregnancy Outcome Prediction–a prospective cohort study of nulliparous women attending the Rosie Hospital, Cambridge (UK) for their dating ultrasound scan between January 14, 2008, and July 31, 2012. Ethical approval for the study was given by the Cambridgeshire 2 Research Ethics Committee (reference number 07/H0308/163) and all participants provided written informed consent. Cases of preeclampsia (PET) were defined on the basis of the 2013 ACOG criteria and cases of small for gestational age (SGA)infants were confined to severe SGA, i.e. a customized birth weight <5th percentile. Chorionic villi from the corresponding placentas (free from decidua, visible infarction, calcification, hematoma, or damage) were collected and processed within 30 minutes of separation from the uterus. After repeated washes in chilled phosphate buffered saline, the samples were placed in RNA later (Applied Biosystems) and stored at -80°C. Total placental RNA was extracted using mirVana Isolation Kit (Ambion). For each placenta, approximately 5 mg of tissue were homogenized in the Lysis/Binding solution for 20 sec at 6 m/s using a bead beater (FastPrep24) and Lysing Matrix D Tubes (MP Biomedicals). The samples were then spun at 13,000 rpm for 5 min at 4°C and the supernatants recovered. Afterwards, the manufacturer's instructions were followed. Immediately after the RNA extraction, placental RNA samples were DNase-treated using DNA-free DNA Removal Kit (Ambion), aliquoted, and stored in -80°C. Quantity and quality of the RNA samples were assessed using the Agilent 2100 Bioanalyzer, the Agilent RNA 6000 Nano Kit (Agilent Technologies), and Qubit fluorometer. Libraries were prepared starting with 300-500 ng of good quality total RNA (RIN ≥7.5) using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero Human/Mouse/Rat (Illumina), according to the manufacturer's instructions. The kit contains 96 uniquely indexed adapter combinations in order to allow pooling of multiple samples prior to sequencing. After determining their size (with the Agilent 2100 Bioanalyzer and the Agilent High Sensitivity DNA Kit by Agilent Technologies) and concentration (by qPCR with the KAPA Illumina ABI Prism Library Quantification Kit, Kapa Biosystems), libraries have been pooled and sequenced (single-end, 125 bp) using a Single End V4 Cluster Kit and an Illumina HiSeq2500 or HiSeq4000 instrument.

  Dataset EGAD00001003508

• A Genome-Wide Association Analysis in Angiotensin-Converting Enzyme (ACE) Inhibitor-Associated Angioedema and ACE Inhibitor-Exposed Controls; A Collaboration between the NIH Pharmacogenomics Research Network and the RIKEN Yokohama Center for Genomic Medicine

  The purpose of this study is to identify genetic predictors of ACE inhibitor-associated angioedema. In addition to preventing the formation of the pressor angiotensin II, ACE inhibitors prevent the carboxyl-terminal degradation of the vasoactive substances bradykinin and substance P. Angioedema is hypothesized to result from defective amino-terminal degradation of bradykinin or substance P in patients in whom ACE is inhibited. For example, activity of dipeptidyl peptidase IV (DPP-IV), the enzyme responsible for the inactivation of substance P when ACE is inhibited, is decreased in patients with angioedema. In preliminary studies, we have identified SNPs in the DPP4 gene that associate with DPP-IV activity and, in blacks, with risk of angioedema. This project will use genome-wide genotyping to compare 250 cases and 568 ACE inhibitor-exposed control subjects (131 cases and 288 controls ascertained at Vanderbilt and 70 cases and 280 controls ascertained at the Marshfield Clinic). We plan a 2-stage analysis of associations between SNPs and angioedema - first, we will study DPP4 SNPs for association with angioedema and, second, we will explore associations using the full GWAS data set. Depending on the platform, additional DPP4 SNPs will be used to fully tag common genetic variants in both African American and European American samples. Based on the HapMap data, there are 14 tagging SNPs in people of European descent and 34 in Yoruba (selection criteria MAF>0.05 and r2>0.8). Cases were defined as having ACE inhibitor-associated angioedema if they had had swelling of the lips, throat, tongue or face while taking an ACE inhibitor but had never had angioedema while not taking an ACE inhibitor. For simplicity, intestinal edema was excluded. Control subjects were treated for at least 6 months with an ACE inhibitor without angioedema. Because black Americans are known to be overrepresented among patients with ACE inhibitor-associated angioedema, control subjects were prespecified to be 50% black American, 50% white American, and 50% female. At Vanderbilt, the medical history, including the history of angioedema, was confirmed by a research nurse or physician using a detailed case report form. Characteristics of Vanderbilt cases appear in the Table. At Marshfield, medical history will be confirmed by chart review. The Marshfield cohort is 98% white American and 57% female with a mean age of 47.2 years.

  Study phs000438

• DNA methylomes of monozygotic twins clinically discordant for multiple sclerosis

  Multiple sclerosis (MS) is an inflammatory demyelinating disease of the central nervous system. Although genetic susceptibility is important, a modest concordance rate for MS in monozygotic (MZ) twins suggests that interaction with other risk factors is required to develop clinical symptoms. In this study, we examined whether DNA methylation differences contribute to the discordant clinical manifestation of MS in MZ twins, and studied the impact of MS treatments on the DNA methylome. Genome-wide DNA methylation profiles of peripheral blood mononuclear cells (PBMCs) of 45 MZ twins clinically discordant for MS were generated using the Illumina HumanMethylationEPIC array. Repetitive element methylation and selected differentially methylated positions (DMPs) were validated using targeted deep bisulfite sequencing (TDBS). In addition, we performed whole genome bisulfite sequencing (WGBS) to profile CD4+ memory T-cells of a subset of four MS discordant MZ twins. Our results show that interferon treatment causes robust DNA methylation changes and several epigenetic biomarkers for interferon treatment response were identified. However, overall the PBMC-based methylomes of the MS discordant MZ twins were highly similar, since large systematic methylation differences (>5%) were absent in the data. This suggests that previously reported large methylation changes are probably caused by genetic rather than epigenetic differences. In addition, our data does not support the hypothesis that the observed maternal parent-of-origin effect in MS is due to genomic imprinting errors, and no evidence was found that copy number variations explain the discordant phenotype in these MZ twins. Although not genome-wide significant, a couple of DMPs associated with the MS phenotype were identified and successfully technically replicated using TDBS, including a differentially methylated region (DMR) in the promoter of the transmembrane protein encoding gene TMEM232. Another MS-associated DMP, located in an enhancer in the gene body of the transcription factor ZBTB16, was also associated with medium-term glucocorticoid treatment history. WGBS analysis confirmed this DMP as a promising epigenetic biomarker for glucocorticoid treatment. In conclusion, this epigenome-wide association study (EWAS) in genetically identical twins identified a DMR in the TMEM232 promoter as a candidate loci associated with the clinical manifestation of MS. In addition, epigenetic biomarkers for MS treatments were identified, revealing that not only short-term, but also medium-term treatment effects are detectable in immune cells, which should be taken into account in future EWAS designs.

  Study EGAS00001003147

• NHLBI TOPMed - NHGRI CCDG: The BioMe Biobank at Mount Sinai

  The IPM BioMe Biobank, founded in September 2007, is an ongoing, broadly-consented electronic health record (EHR)-linked clinical care biobank that enrolls participants non-selectively from the Mount Sinai Medical Center patient population. BioMe currently comprises >42,000 participants from diverse ancestries, characterized by a broad spectrum of longitudinal biomedical traits. Participants are enrolled through an opt-in process and consent to be followed throughout their clinical care (past, present, and future) in real-time, allowing us to integrate their genomic information with their EHRs for discovery research and clinical care implementation. BioMe participants consent for recall, based on their genotype and/or phenotype, permitting in-depth follow-up and functional studies for selected participants at any time. Phenotypic and genomic data are stored in a secure database and made available to investigators, contingent on approval by the BioMe Governing Board. BioMe uses a "data-broker" system to protect confidentiality. Ancestral diversity - BioMe participants represent a broad racial, ethnic and socioeconomic diversity with a distinct and population-specific disease burden. Specifically, BioMe participants are of African (AA), Hispanic/Latino (HL), European (EA) and other/mixed ancestry. BioMe participants are predominantly of African (AA, 24%), Hispanic/Latino (HL, 35%), European (EA, 32%), and other ancestry (OA, 10%). Participants who self-identify as Hispanic/Latino further report to be of Puerto Rican (39%), Dominican (23%), Central/South American (17%), Mexican (5%) or other Hispanic (16%) ancestry. More than 40% of European ancestry participants are genetically determined to be of Ashkenazi Jewish ancestry. With this broad ancestral diversity, BioMe is uniquely positioned to examine the impact of demographic and evolutionary forces that have shaped common disease risk. Phenotypes available in BioMe - BioMe has a high-quality and validated set of fully implemented clinical phenotype data that has been culled by a multi-disciplinary team of experienced investigators, clinicians, information technologists, data-managers, and programmers who apply advanced medical informatics and data mining tools to extract and harmonize EHRs. BioMe, as a cohort, offers a great versatility for designing nested case-control sample-sets, particularly for studying longitudinal traits and co-morbidity in disease burden. Biomedical and clinical outcomes: The BioMe Biobank is linked to Mount Sinai's system-wide Epic EHR, which captures a full spectrum of biomedical phenotypes, including clinical outcomes, covariate and exposure data from past, present and future health care encounters. As such, the BioMe Biobank has a longitudinal design as participants consent to make all of their EHR data from past (dating back as far as 2003), present and future inpatient or outpatient encounters available for research, without restriction. The median number of outpatient encounters is 21 per participant, reflecting predominant enrollment of participants with common chronic conditions from primary care facilities. Environmental data: The clinical and EHR information is complemented by detailed demographic and lifestyle information, including ancestry, residence history, country of origin, personal and familial medical history, education, socio-economic status, physical activity, smoking, dietary habits, alcohol intake, and body weight history, which is collected in a systematic manner by interview-based questionnaire at time of enrollment. The IPM BioMe Biobank contributed ~10,600 DNA samples for whole genome sequencing to the TOPMed program. Samples were selected for the Coronary Artery Disease (CAD) and the Chronic Obstructive Pulmonary Disease (COPD) working groups. Using a Case-Definition-Algorithm (CDA), we identified ~4,100 individuals with CAD (~50% women) and ~3,000 individuals as controls (65% women). In addition, we identified ~800 individuals with COPD (62% women) and 1800 individuals as controls (72% women). Another 600 BioMe participants with Atrial Fibrillation, all of African ancestry, were included.

  Study phs001644

• DMET Genes, Nicotine Metabolism and Prospective Abstinence

  This study (DA033813; PI: Andrew W Bergen; PMID:26132489) includes samples from two laboratory studies of nicotine metabolism. The Pharmacokinetics of Nicotine Metabolism in Twins study (PKTWIN; PI: Gary E Swan; PMID: 15527659) was based on recruitment from a twin registry (PMID: 23084148). The Integrated Research Project on Tobacco Use and Dependence (IRP; PI: Gary E Swan; PMID: 14578134) was based on recruitment from a pedigree-based longitudinal study of risk factors for substance use, the Smoking in Families study (SMOFAM; DA03706; PI: Hy Hops). These two laboratory studies (PKTWIN and IRP/SMOFAM) served as the Stage I dataset to interrogate Drug Metabolizing Enzyme and Transporter genes with a targeted SNP array for association with the Nicotine Metabolite Ratio (NMR, ratio of trans-3'-hydroxycotinine and cotinine), an established biomarker of nicotine metabolism. In addition to the laboratory studies, samples from eight RCTs (PMID: 23249876) with the NMR and smoking-related measures used to test SNPs identified in Stage I (PMID: 26132489). In a third stage, a lung cancer meta-analysis database (PMID: 24880342) was used to assess association of SNPs identified in Stage II with lung cancer. The objectives of the study were to identify novel genes and SNPs contributing to nicotine metabolism (Stage I), and to validate PK SNPs associated with the NMR from individuals participating in a clinical laboratory protocol with the NMR obtained from treatment-seeking smokers, and then to investigate association with prospective smoking cessation (Stage II). This study built upon existing studies of nicotine metabolism and randomized trials of smoking cessation therapies. Enhanced knowledge of the genes influencing nicotine metabolism and prospective abstinence may help personalize smoking cessation treatment and risk assessment for smoking-related diseases. For Stage I, both subject [fixed-dose NMR, covariates (age, BMI, ethnicity, sex, smoking status, and hormone use), and pedigree relationships] and sample (common DMET SNP genotype, genotyping quality control) data are available in this accession. The analysis protocol, quality control summaries, summary genotype, summary phenotype, and analysis results are available for Stage I, II and III samples (PMID: 26132489). Extensive discussion of the prior CYP2A6 association literature with the NMR, abstinence, smoking heaviness and lung cancer risk is available (PMID: 26132489). The NMR has previously been associated with CYP2A6 activity, response to smoking cessation treatments, and cigarette consumption. We searched for drug metabolizing enzyme and transporter (DMET) gene variation associated with the NMR and prospective abstinence in 2,946 participants of laboratory studies of nicotine metabolism and of clinical trials of smoking cessation therapies. Stage I was a meta-analysis of the association of 507 common single nucleotide polymorphisms (SNPs) at 173 DMET genes with the NMR in 449 participants of two laboratory studies. Nominally significant associations were identified in ten genes after adjustment for intragenic SNPs; CYP2A6 and two CYP2A6 SNPs attained experiment-wide significance adjusted for correlated SNPs (CYP2A6 PACT=4.1E-7, rs4803381 PACT=4.5E-5, rs1137115, PACT=1.2E-3). Stage II was mega-regression analyses of 10 DMET SNPs with pretreatment NMR and prospective abstinence in up to 2,497 participants from eight trials. rs4803381 and rs1137115 SNPs were associated with pretreatment NMR at genome-wide significance. In post-hoc analyses of CYP2A6 SNPs, we observed nominally significant association with: abstinence in one pharmacotherapy arm; cigarette consumption among all trial participants; and lung cancer in four case:control studies. CYP2A6 minor alleles were associated with reduced NMR, CPD, and lung cancer risk. We confirmed the major role that CYP2A6 plays in nicotine metabolism, and made novel findings with respect to genome-wide significance and associations with CPD, abstinence and lung cancer risk. Additional multivariate analyses with patient variables and genetic modeling will improve prediction of nicotine metabolism, disease risk and smoking cessation treatment prognosis.

  Study phs000931

• Ludwig Center for Cancer Genetics and Therapeutics at Johns Hopkins

  Dac EGAC00001000507

• Data access committee for study - The subclonal architecture of metastatic breast cancer: Results from a prospective community-based rapid autopsy program "CASCADE".

  Dac EGAC00001000574

• Data Access Commitee for Dietrich and Wendisch et al., SARS-CoV-2 infection triggers profibrotic macrophage responses and lung fibrosis (Submitted)

  Dac EGAC00001001884

• Data Access Commitee for Dietrich and Wendisch et al., SARS-CoV-2 infection triggers profibrotic macrophage responses and lung fibrosis (Submitted)

  Dac EGAC00001002335

• EXOME_ARRAY_ANALYSIS

  EXOME ARRAY ANALYSIS OF ADVERSE REACTIONS TO FLUOROPYRIMIDINE-BASED THERAPY FOR GASTROINTESTINAL CANCER

  Dataset EGAD00010001499

• DNA methylation for EGAS00001003603

  Genome-wide DNA methylation profiling of Waldenstrom's macroglobulinemia (WM) patient samples

  Dataset EGAD00010001861

• NativeAmericans_InstitutoNacionaldeSalud_hg38_autosomic_3group

  Genome-wide data for 130 Native American individuals from Peru

  Dataset EGAD00010001992

• NativeAmericans_InstitutoNacionaldeSalud_hg37_autosomic_1group

  Genome-wide data for 71 Native American individuals from Peru

  Dataset EGAD00010001991

• NativeAmericans_InstitutoNacionaldeSalud_hg38_autosomic_2group

  Genome-wide data for 59 Native American individuals from Peru

  Dataset EGAD00010001990

• BRACOVID_genotype

  Cohort: Raw genotype files for BRACOVID cohort. Genotype Chip: Axiom_PMRA.r3 array genomic build: b37

  Dataset EGAD00010002172

• Genotype_HSM1_HSM2

  Genotypes for 2 human skeletal muscle samples

  Dataset EGAD00010002248

• OICR-DAC, Ontario Institute for Cancer Research

  Dac EGAC00001000591

• OICR-DAC, Ontario Institute for Cancer Research

  Dac EGAC00001000710

• CCA NanoString data (60CCA)

  Raw .RCC files for NanoString. nCounter PanCancer IO 360 Panel was used

  Dataset EGAD00010002612

• Sample Sheet

  Sample sheet for aligning samples with patients.

  Dataset EGAD50000000484

• Lifelines NEXT HMO Data

  The dataset contains HMO measurements for 1542 samples from Lifelines NEXT cohort

  Dataset EGAD50000000531

• Genome-wide array data from Eivissa and Menorca

  DAC for the Genome-wide array data from 22 Eivissan and 20 Menorcan individuals.

  Dac EGAC50000000297

• Metadata associated with sequencing

  Associated metadata for sequencing data.

  Dataset EGAD50000000528

• Targeted analysis of cell-free circulating tumor DNA is suitable for early relapse and actionable target detection in patients with neuroblastoma

  Study EGAS00001006027

• Analysis of circulating miRNAs for the identification of new prognostic and predictive markers in gastro-entero-pancreatic neuroendocrine tumour (GEP-NET)

  Study EGAS00001007227

• DAC anti-MPO BCR sequences

  DAC for the requests of access to data of anti-MPO BCR sequences in the EGA repository,

  Dac EGAC50000000446

• NGS WGS Data - Unic TDP

  WGS data from the Unicorn-PASS cohort for the Tandem Duplicator Phenotype paper

  Dataset EGAD50000001567

• UMCG Immunogenetics DAC

  DAC for the data generated in the Immunogenetics group in the genetics department of the University Medical Center Groningen

  Dac EGAC50000000785

• Soegaard Laboratory Data Access Committee

  Data Access Committee for data generated by the laboratory of Prof. O.S. Soegaard at Aarhus University Hospital.

  Dac EGAC50000000888

• Liquid biopsy-based minimal residual disease monitoring for early risk stratification and decision-making in advanced non-small cell lung cancer

  Dac EGAC50000000832

• GATCI RNAseq fastqs

  Raw RNA sequence data (fastq) for the GATCI project

  Dataset EGAD00001005810

• 16S sequencing data for Butyricicoccus safety study

  16S rRNA gene sequencing with Illumina MiSeq (V4 hypervariable region)

  Dataset EGAD00001004406

• BotSeq sequences1

  This is the first dataset for the Botseq sequencing project

  Dataset EGAD00001002263

• Melanoma multi site metastases

  These are caveman, pindel and sequenza calls for the metastatic melanoma exomes within this study.

  Dataset EGAD00001005487

• SC_DDD-G-5

  Post-QC (pre-imputation) genotype data for N=2,166, a subset of trios described in EGAD00010001602. These data form N=722 complete trios in which the proband has a neurodevelopmental phenotype (Niemi et al. Nature 2018). Includes HPO phenotype terms for patients. Samples were genotyped on the Illumina HumanOmniExpress BeadChip

  Dataset EGAD00010001606

• Clones derived from early passage tumoroids of colorectal cancer

  We obtained different clones from early passage CRC tumoroids to study mutational signatures specific for truncal or private somatic alterations. These whole genome sequences are part of a larger study on the heterogeneity and evolution of DNA mutation rates in microsatellite-stable colorectal cancer.

  Study EGAS50000000107

• Bulk Iso-Seq from brain tissue and exosomes isolated from brain tissue using long-read PacBio sequencing of poly-adenylated transcripts

  Human brain sEVs were isolated from postmortem human brain tissue. RNA was extracted from both the source brain tissue and sEVs and prepared for long-read sequencing. cDNA was sequenced on the PacBio Sequel II. The data provided have undergone processing using the tool ccs (v6.0.0) to generate circula consensus reads. For further processing, it is recommended to follow the guidelines at https://isoseq.how/, starting with using lima to remove cDNA primers.

  Dataset EGAD50000000043