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• Comparison of 3 protocols for deriving pancreatic progenitors from hPSCs (RNA-seq)

  This dataset contains 26 mapped bam files. The samples were generated with 3 different protocols for deriving pancreatic progenitors from hPSC. Three parallel differentiations were performed, all done in a hPSC NKX6.1-GFP reporter line. For each protocol there are three cellular populations: total (presort), GFP+ and GFP- . In summary: 3 differentiations x 3 protocols x 3 cellular populations. We prepared Smart-Seq2 RNA-seq libraries for the 27 samples, 1 sample failed library preparation and is not therefore included in this dataset.

  Dataset EGAD00001004823

• Systematic identification of long non-coding RNAs potentially involved in gastrointestinal carncer

  Recent work has suggested various important functions and molecular mechanisms for long non-coding RNAs (lncRNAs) and they are also thought to play critical roles in cancer. However the importance of lncRNAs in cancer biology is still unclear. In this study, we aim to comprehensively identify novel lncRNAs that are critically involved in tumorigenesis and progression in gastrointestinal cancer.

  Study JGAS000011

• Evolutionary origin and methylation status of human intronic CpG islands that are not present in mouse

  Imprinting of the human RB1 gene is due to the presence of a differentially methylated CpG island (CGI) in intron 2, which is part of a retrogene derived from the PPP1R26 gene on chromosome 9. The murine Rb1 gene does not have this retrogene and is not imprinted. We have investigated whether the RB1/Rb1 locus is unique with respect to these differences. For this we have compared the CGIs from human and mouse by in silico analyses and found out that there are at least 2033 human intronic CGIs that are not present in the mouse. Among these CGIs, 104 show sequences similarities elsewhere in the human genome, which suggests that they arose by retrotransposition. We could narrow down the time points when most of these CGIs appeared during evolution. Their methylation status was analysed in two monocyte methylome datasets from whole genome bisulfite sequencing and in 18 published methylomes. Five CGIs appear to be differentially methylated, which suggests that they are subject of genomic imprinting. They are located in introns of the following genes: RB1, ASRGL1, PARP11, PDXDC1 and MYO1D. Four of these CGIs are parts of retrogenes. Our study supports the notion that imprinting builds on host defence mechanisms by which the genome protects itself against retrotransposed and foreign DNA and that the epigenetic fate of the retrotransposed DNA depends on selective forces at the integration site.

  Study EGAS00001000719

• The European Bank for Induced Pluripotent stem cells (EBiSC) is designed to address the increasing demand by iPSC researchers for quality-controlled, disease-relevant research grade iPSC lines, data and cell services.In this study Whole Genome Sequencing was performed on a selection of lines from the project.

  Induced pluripotent stem (iPS) cells have the potential to significantly advance drug development and health research, yet collections of stem cells are scattered across the world, their quality cannot always be guaranteed, and accessing them is often difficult. The goal of EBiSC is to establish a European iPS cell bank that will be the ‘go-to’ resource for the characterisation, storage and distribution of high quality iPS cells. Ultimately, EBiSC will become an independent organisation, distributing high quality iPS cells on a not-for-profit basis to scientists worldwide.

  Study EGAS00001002755

• Integrating molecular imaging and transcriptomic profiling in advanced HER2-positive breast cancer receiving trastuzumab emtansine (T-DM1): an analysis of the ZEPHIR clinical trial

  Purpose: The ZEPHIR clinical trial evaluated the role of [89Zr]trastuzumab-PET/CT (HER2-PET/CT) and 2-[18F]fluoro-2-deoxy-D-glucose PET/CT ([18F]FDG-PET/CT) in predicting outcomes in patients with advanced HER2-positive breast cancer treated with trastuzumab emtansine (T-DM1). Here, we combined molecular/metabolic imaging and transcriptomic data to investigate the biological processes associated with [89Zr]trastuzumab and [18F]FDG uptake, and to dissect the mechanisms involved in T-DM1 resistance. Experimental design: RNA was extracted from metastasis biopsies obtained at study inclusion in the ZEPHIR trial. HER2-PET/CT and [18F]FDG-PET/CT imaging data of biopsied lesions were integrated with RNA sequencing data. Lesions were compared based on the level of [89Zr]trastuzumab uptake (dichotomized into high/low classes) as well as on the presence/absence of metabolic response, defined comparing baseline and on-treatment [18F]FDG-PET/CT. Results: We analyzed matched transcriptomic and molecular/metabolic imaging data for 24 metastases (one lesion/patient). Pathways involved in extracellular matrix (ECM) organization, glycosylphosphatidylinositol synthesis, and collagen formation were enriched in lesions presenting low [89Zr]trastuzumab uptake. [18F]FDG uptake at baseline correlated with proliferation and immune-related processes. Hypoxia and ECM-related processes were enriched in lesions that showed no metabolic response to T-DM1. Interestingly, immune-related processes (e.g., Fc gamma receptor activation, complement cascade) were associated with high [89Zr]trastuzumab uptake and metabolic response. Conclusions: To our knowledge, this study represents the first correlative analysis between [89Zr]trastuzumab tumor uptake and gene expression profiling in humans. Our findings point toward a role of ECM in impairing [89Zr]trastuzumab tumor uptake and T-DM1 metabolic response in advanced HER2-positive breast cancer, and highlight the potential of molecular imaging to depict tumor microenvironment features.

  Study EGAS50000000470

• Bisulfite-converted duplexes for the strand-specific detection and quantification of rare mutations

  The identification of mutations that are present at low frequencies in clinical samples is an essential component of precision medicine. The development of molecular barcoding for next generation sequencing has greatly enhanced the sensitivity of detecting such mutations by massively parallel sequencing. However, further improvements in specificity would be useful for a variety of applications. We herein describe a technology (BiSeqS) that can increase the specificity of sequencing by at least two orders of magnitude over and above that achieved with molecular barcoding and can be applied to any massively parallel sequencing instrument. BiSeqS employs bisulfite treatment to distinguish the two strands of molecularly barcoded DNA; its specificity arises from the requirement for the same mutation to be identified in both strands. Because no library preparation is required, the technology permits very efficient use of the template DNA as well as sequence reads, which are nearly all confined to the amplicons of interest. Such efficiency is critical for clinical samples, such as plasma, in which only tiny amounts of DNA are often available. We show here that BiSeqS can be applied to evaluate transversions, as well as small insertions or deletions, and can reliably detect one mutation among >10,000 wild type molecules.

  Study EGAS00001002406

• A Genome-Wide Association Study on Cataract and HDL in the Personalized Medicine Research Project Cohort

  The primary goals of this project are to develop and validate electronic phenotyping algorithms, to accurately identify cases and controls while maintaining a positive predictive value (PPV) of >95%, and to conduct a genome wide association study that advances understanding of two specific yet interrelated disease states, while simultaneously engaging the community in these research efforts. Lipid abnormalities and cataracts are both diseases of public health significance, they share common risk factors, and they are both complex diseases which likely have many genes contributing to disease development. Whole genome association studies with these two outcomes and environmental risk factors could yield novel data about the etiology of the two separate outcomes as well as their interaction. PhenX is a project designed to prioritize Phenotypes and eXposure measures for Genome-wide Association Studies (GWAS). The PhenX Toolkit is a valuable resource for researchers who are planning or expanding a study and would like to incorporate well established measures that have been recommended by experts in the field. We are currently interested in gene-environment interactions for "age related cataract".

  Study phs000170

• GEnomics and Transcriptomics of Human INsulinoma (GETHIN)

  The Genomics and Transcriptomics of Human Insulinoma (GETHIN) The common forms of diabetes - Types 1 and 2 - ultimately result from a deficiency of insulin-producing pancreatic beta cells. The Genomics and Transcriptomics of Human Insulinoma (GETHIN) study was performed in order to identify novel approaches to inducing human pancreatic beta cells to replicate and regenerate. As a corollary, developing drugs that are able to expand human beta cell mass in people with diabetes should reverse diabetes. Unfortunately, identifying druggable pathways that can enhance human beta cell replication has been a major challenge. In 2017, there is only one class of drugs - the harmine analogues - that can induce human beta cells to replicate, and in this case, higher replication rates are desirable. Thus, identifying additional drugs and druggable pathways is a priority in diabetes research. Insulinomas are rare, benign adenomas of the pancreatic beta cell that cause excess insulin production and hypoglycemia: exactly the opposite of Types 1 and 2 diabetes. Beta cell proliferation rates in insulinomas are abnormally high. Thus, the premise for The Genomics and Transcriptomics of Human Insulinoma study is that benign human insulinomas hold the genomic and transcriptomic "recipe", and the repertoire of druggable pathways, that can be exploited to induce regeneration or replication of human beta cells in diabetes. Because, insulinomas are so rare, are almost always benign (non-malignant), and are easily resected by laparoscopic surgery, little attention has been paid to understanding the genomics or transcriptomics of insulinoma. There are at present only three published studies employing next-gen sequencing in insulinoma (PMID:24326773; PMID:25787250; and PMID:25763608). These studies contained 10, 7 and 8 insulinomas, respectively, and highlighted likely mutations in YY1 and MEN1. Our goal was to markedly expand the database and to add RNAseq to these earlier studies. The GETHIN study reports next-gen sequencing on 38 insulinomas, by far the largest series of human insulinomas subjected to next-gen sequencing (see the Selected publications section for reference). This includes paired (genomic plus tumor) whole exome sequencing on 26 human insulinomas (22 sequenced at Mount Sinai, 4 downloaded from Cao et al, PMID:24326773), and 25 sets of RNAseq from insulinomas, some of which also had paired whole exome sequencing, and some of which did not. The insulinoma RNAseq was compared to RNAseq from 22 sets of FACS-sorted normal human beta cells. Since insulinomas are so rare, the 38 insulinomas were collected by several investigators at several institutions over several decades, but most (22 whole exome sets, and all RNAseq) were sequenced at the Icahn School of Medicine at Mount Sinai in New York. The current dataset contains whole exome sequencing and RNAseq on the 11 insulinomas harvested at Mount Sinai. The four from Cao et al can be retrieved from Cao et al PMID:24326773. Fastq files from the remaining 23 insulinomas will be added as the local IRBs and Institutional Certifications are acquired. Complete patient data are provided in our Nature Communications report. Going forward, our intention is to expand this series, with the goal of sequencing 100 human insulinomas. These will be added to dbGaP as they accrue. Paired-end whole exome sequencing (mean usable sequencing depth 79X and 105X for blood and insulinoma, respectively) was performed using an Illumina HiSeq 2500. Insulinoma and sorted normal beta cell RNAseq was performed on Ribozero and polyA paired end libraries using the Illumina HiSeq 2500. Complete sequencing and bioinformatic details are provided in our Nature Communications report. The principal findings from the study are that although each insulinoma has a different set of presumptive driver mutations, the majority converge on genes that are members of the Polycomb Complex, Trithorax Complex and other epigenetic modifying enzymes. In addition, 20% of insulinomas have copy number loss or loss of heterozygosity of all or most of chromosome 11, and the majority display abnormalities in CpG methylation and imprinting control on the imprinted Chr 11 p15.5-15.4 region that contains INS, IGF2, CDKN1C, KCNQ1, and other genes involved in beta cell specification and proliferation.

  Study phs001422

• Recurrent somatic DICER1 mutations in non-epithelial ovarian tumors

  Background: Germline truncating mutations in DICER1, an RNase III-type endoribonuclease essential for processing of microRNAs, are seen in families with the pleuropulmonary blastoma-family tumor and dysplasia syndrome; these individuals have a propensity to develop non-epithelial ovarian tumors (i.e. sex-cord stromal and germ cell tumors). Methods: We sequenced the whole transcriptomes or exomes of 14 non-epithelial ovarian tumors and noted closely clustered mutations in the RNase IIIb domain of DICER1 in four cases. Using Sanger sequencing, we then analyzed additional ovarian tumors for mutations in this region. The impact of the mutations on the enzymatic activity of Dicer1 was determined using in vitro RNA cleavage assays. Results: RNase IIIb domain DICER1 mutations were found in 30/102 non-epithelial ovarian tumors (29%), predominantly Sertoli-Leydig cell tumors (26/43, 60%), including 4/4 from individuals with germline DICER1 mutations. The mutations were restricted to metal binding sites within the RNase IIIb catalytic centres critical for miRNA interaction and cleavage, and were somatic in all 14 cases where germline DNA was available for testing. Of 266 epithelial ovarian and endometrial cancers tested, one case, an ovarian carcinosarcoma, had a hotspot mutation. In vitro, the mutant DICER proteins showed reduced RNase IIIb activity but retained RNase IIIa activity. Conclusions: Somatic missense mutations of the RNase IIIb domain of DICER1 are common in non-epithelial ovarian tumors. Genetic, pathologic, and functional evidence suggest that these mutations do not obliterate DICER1 function, rather, they alter it in specific cell types, a novel mechanism through which perturbed microRNA expression is oncogenic.

  Study EGAS00001000135

• A Chromatin Accessibility Atlas of the Developing Human Telencephalon

  Gene expression differs between cell types and regions within complex tissues such as the developing brain. To discover regulatory elements underlying this specificity, we generated genome-wide maps of chromatin accessibility in nine anatomically-defined regions of the developing human telencephalon. Additionally, we defined the histone modification landscape of the prefrontal cortex and generated chromatin accessibility maps of its upper and deep layers. We predicted a subset of open chromatin regions (18%) that are most likely to be active enhancers, many of which are dynamic with 26% differing between early and late mid-gestation and 28% present in only one brain region. These predicted regulatory elements (pREs) are enriched proximal to genes with expression differences across developmental stages, regions, and cortical laminae; they harbor distinct sequence motifs that suggest potential upstream regulators. We leveraged this atlas to predict and validate novel regulatory elements of genes that control cortex laminar identity and genes associated with autism spectrum disorder (ASD). These include enhancers proximal to FEZF2 and BCL11A that were validated in mouse, and an enhancer of ASD gene SLC6A1 containing two functional de novo mutations in individuals with ASD whose enhancer function we validated via CRISPRa. We also include data for transcription factor binding in mid-fetal cortex tissues, using CUT&RUN methods.

  Study phs002033

• Establishment of an iPSC Repository Derived from Healthy Volunteers

  Understanding the interaction between genetic variation and epigenetic variation remains a challenge due to the confounding role of environmental factors. We propose that human induced pluripotent stem cells (iPSCs) are an excellent model to study the relationship between genetic variation and epigenetic variation while controlling for consistent environmental factors. In this study, we have created a comprehensive resource of high-quality genomic, epigenomic, and transcriptomic data of six iPSC lines and three iPS-derived cell types (NSC, Motor Neuron, Monocyte) from three healthy donors. We found that epigenetic variation is most strongly associated with genetic variation at the iPSC stage, and that relationship weakens as epigenetic variation increases in the differentiated cells. Additionally, cell-type is a stronger source of epigenetic variation than genetic variation, highlighting that humans are far more similar than they are different, regardless of genetic background. Further, we have elucidated a utility of studying epigenetic variation in iPSCs and their derivatives for identifying important loci for GWAS studies and the cell-types in which they may be acting.

  Study phs003649

• Analyzing Somatic Mutagenesis in Systemic Sclerosis

  The study was undertaken with the aim of estimating differences in the mutational burden in lung tissues from healthy vs systemic sclerosis (SSc) patients. SSc is an auto-immune disease, with patients often developing cancer. However, the etiology of this phenomenon is poorly understood. As such we sought to uncover potential molecular mechanisms prevalent within SSc tissues that might be potentiating cancer. Samples were randomly collected from individuals from two broad ethnic groups, European (EA) and African American (AA). In total, samples were obtained from 7 individuals belonging to the EA group and 4 individuals from the AA group. For this study, ethnicity was not included as a confounding variable, given that the data set has roughly comparable number of individuals from both ethnicities for the healthy and SSc cohorts. Study participants ranged in age from 37-63 years old. Median age (52 years old) of healthy individuals was comparable to the SSc cohort (~48 years old). Participants were self-described as current/former smokers or non-smokers. Lung tissues were obtained under a protocol approved by the University of Pittsburgh Institutional Review Board. Written informed consent statements were provided to the University of Pittsburgh IRB by the study participants/patients. Sample sizes were determined by the ability of bulk lung fibroblast tissues to stably propagate in culture until single cell clones could be obtained. Samples for which sufficient cell density could not be achieved for downstream high-depth sequencing analysis were excluded from the study and are not reported. Five or greater than 5 samples are collected from each cohort including healthy and SSc patients. Subjects were allocated to two basic cohorts based on diagnosis at the time of explant. Participants with no reported lung anomalies were allocated to the "healthy" cohort, whereas individuals with reported lung abnormalities, primarily SSc with pulmonary fibrosis and/or hypertension were allocated to the "SSc" cohort. All tissue samples were cultured, propagated and processed in identical fashion without requiring individual-specific protocols. Additionally, equivalent amounts of DNA were used for preparing sequencing libraries from both cohorts, and all samples were sequenced using Illumina whole genome sequencing (WGS) and analyzed using identical computational pipelines. Our study primarily discovered that there is a significantly higher burden of somatic mutations in SSc samples, compared to healthy samples. We observed an overall increase in a range of mutations in genomes of SSc patients, including single base substitutions, indels, structural variants and copy number alterations. Additionally, we uncovered a novel mutation signature associated with SSc samples, hinting at the activity of POLH in these samples, and highlighting the potential nexus between inflammation, DNA damage, and cancer.

  Study phs003700

• Induced pluripotent stem cell lines (iPSC lines) produced from skin and blood cells.

  The IMBA stem cell bank, iPSC Biobank, is a collection of induced pluripotent stem cell lines (iPSC lines) produced from skin and blood cells. The iPSC Biobank is integrated into the IMBA Stem Cell Core Facility. It stores and provides high-quality reference control panels of iPSC clones as a tool to the research community. The resource is available to all scientists and commercial institutions. The ethical guidelines of the iPSC Biobank are always based on prevailing laws and internal regulations.

  Study EGAS00001006262

• From research to data sharing: exploring EGA user's experiences

  The Cell Plasticity and Regeneration Group at the Bellvitge Biomedical Research Institute-IDIBELL focuses on the process of recruitment of macrophages that takes place in the small intestine during injury and healing. They recently published a paper titled “Mucosal Macrophages Govern Intestinal Regeneration in Response to Injury" in Gastroenterology Journal. As part of the research, some experiments were conducted using human intestinal organoid lines. These cells were processed for RNA sequencing, and the sequencing data were deposited at the EGA to be made available to the scientific community. When dealing with human genomic information, repositories must ensure the availability of the datasets while ensuring data protection. In this context, the European Genome-phenome Archive stands as a service for secure archiving and sharing of genetic, phenotypic and clinical data resulting from biomedical research. Following the recent publication of their paper, we took the opportunity to talk to Ilias Moraitis, first author, and Jordi Guiu, group leader, to find out about their experience with data sharing. Could you explain the focus of your research? In the lab, we study intestinal regeneration and how immune cells participate in this process. We use several techniques: engineered mouse models, image tracing, as well as mouse and human cells intestinal organoids. What challenges do you face regarding data management? We didn’t have a lot of problems. Always the informatic part, the data analysis, can give problems. But everything was smooth and working. We think it’s very important to deposit the data in repositories. For the mouse data it is very straightforward, but for us it was the first time depositing human data, which is sensitive because it comes from patients, and this is legally regulated. That’s why we thought about the EGA, and it was our first time. Why do you think it is important to submit data to repositories such as EGA? Because we think data is important for the science. Nowadays, we are sequencing a lot everywhere worldwide and having these resources shared with the scientific community it’s not only good for science, but it is also saving money and reducing costs. And there is so much data in there that can be used for other projects and for other questions. And it saves time! How was the process of submitting the data to the EGA? The communication worked very well but it was slower than we would like. But I think this is something we learn on the way. People usually wait until the last minute to do this before publication but if you know it in advance, you can start the process earlier. If you had to repeat the process, would you do anything differently? It’s like everything, isn’t it? For the first time you don’t know, you aren’t sure, but for the second time you know the steps, you know what to do and it’s faster. Of course, we would to do it earlier. Also, there were some things related to the control access that we didn’t know how to manage, but it was something more internal to us. Who is going to receive the communications and when, is our ethical committee going to evaluate this? All these technicalities that we didn’t know before starting this process, so we had to think about all these things. Next time it will be faster on our side. Do you have any suggestions for us to improve the submission process? Maybe we’ll need to ask our bioinformatician who did it! He was in charge of this part. Besides that, we think if the process were faster, it would be better for everyone. Also, in science a lot of times you have to do a lot of things at the very last minute, because of the nature of the experiments, or the need to accomplish for submitting a paper. Being faster in the process would be a plus. On your side, we went through the process and were able to find some information, but there were aspects we weren't aware of and weren't sure how to handle. I'm not sure if other institutes have different protocols for managing data requests or how they handle these internally. We believe the main issue lies in how the forms are filled out. Do you have any recommendations for other submitters? The main advice is to do this with enough time. Submit the data when you have the sequences, and don’t wait until the last minute. And then it can be under embargo, so you don’t need to make it public at that moment. As soon as you sequence, upload it and then it will be there for whenever you need to publish. How do you think we could encourage other researchers to submit their data? There are different layers here. One is that it is mandatory. You have to do this. The other is that we belong to a research community, to the same community and sharing this is making our research community stronger and more efficient. And then, also because this gives you visibility. The data is there, other people can analyse your data, and this also will bring citations to your papers. It has many advantages.

  Blog from-research-to-data-sharing

• Global Anaplastic Thyroid Cancer Initiative

  Thyroid cancer is the most common endocrine malignancy. Most thyroid cancers are of the well-differentiated (non-aggressive) phenotype, and are almost always cured with standard treatments. In contrast, anaplastic thyroid cancer (ATC) is rare, accounting for only 1% of thyroid cancers, however it is perhaps the most lethal human malignancy with an average survival of 3 to 6 months. ATC presents with dramatic and rapid onset of airway and esophageal blockage with frequent spread to the lungs. Interestingly, 21–79% of ATCs have coexisting areas or a previous history of well-differentiated cancers. Although this suggests a progression from well-differentiated cancers to ATC, to date there is little molecular conformation that such a progression exists versus de novo generation of ATC. As ATC is extremely rare and most cases are inoperable, there are a paucity of tissue samples for study at any one center. The Global Anaplastic Thyroid Cancer Initiative (GATCI) aims to unite international institutions in order to pool samples (ATC with or without a paired well-differentiated component) for a comprehensive analysis of the genomic landscape of this disease.

  Study EGAS00001002234

• Determining Genetic Role in Treatment Response to Anti-Platelet Interventions (The PAPI Study)

  CHD is the leading cause of death in the United States. One of the most common ways to prevent CHD is to take an anti-platelet agent, which lessens platelet aggregation. Two of the most common anti-platelet agents are aspirin and clopidogrel. However, up to 25% to 30% of people do not respond to these medications. Evidence indicates that treatment response may be related to genetics. The purpose of this study is to determine specific gene variants that predict response to aspirin and clopidogrel therapy. This study is part of a larger group of studies called the Pharmacogenomics Research Network (PGRN). Participants are from the Old Order Amish of Lancaster, Pennsylvania. They are well suited for genetic studies because they are a homogenous, closed, founder population. Participants received 300 mg of clopidogrel on the first day, then 75 mg of clopidogrel per day for the next 6 days. On the last day of clopidogrel treatment, participants took a single dose of 324 mg aspirin. Participants underwent platelet function tests before and after clopidogrel alone, and then again after taking clopidogrel plus aspirin. Using the gene variation profiles across the genome, researchers analyzed which variants correspond to treatment response.

  Study phs000391

• Genome-wide DNA-methylation assessment by MethylCap-seq and Infinium HumanMethylation450 BeadChips: an independent large-scale comparison

  DNA-methylation is an important epigenetic feature in health and disease. Two cost-efficient genome-scale methodologies to assess DNA-methylation are MethylCap-seq and Illumina's Infinium HumanMethylation450 BeadChips (HM450). However, objective information regarding the best-suited methodology for a specific research question is scant. Therefore, we performed a large-scale evaluation on a set of 70 brain tissue samples obtained from 65 glioblastoma and 5 non-tumoral brain tissues, using a gold standard free Bayesian modeling procedure. While conditional specificity was adequate for both approaches, conditional sensitivity was systematically higher for HM450. Also the genome-wide characteristics were compared, revealing that the HM450 probes assess less than 10% of the regions identified as methylated by MethylCap-seq. Hence the latter method may detect more potentially relevant DNA-methylation, defined by either functional location or previously reported differentially methylated candidate regions. Our results therefore indicate that – at least for the tissue under study - both methodologies are complementary, with a higher sensitivity for HM450, but a far larger genome-wide coverage for MethylCap-seq. Note that here only the relevant MethylCap-seq data is deposited, for the HM450 data we refer to GEO (GSE60274).

  Study EGAS00001001191

• 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

• Substance Dependence GWAS in European- and African - Americans

  This study includes SSADDA (Semi Structured Assessment for Drug Dependence and Alcoholism) assessed subjects (mostly unrelated, but including some affected sibling pairs) recruited in the course of several substance dependence genetics projects. The sample includes 1,531 self-reported African-American (AA) subjects, 1,339 self-reported European-American (EA) subjects, and 2 who reported race as "unknown" or "missing".

  Study phs000952

• Foregut Microbiome and Risk of Gastric Intestinal Metaplasia, and Gastric Cancer Risk

  The study is composed of two sub-studies. The first study, conducted by NYU Grossman School of Medicine, is a case-control study of 89 cases with gastric intestinal metaplasia (IM) and 89 matched controls who underwent upper gastrointestinal endoscopy at three sites affiliated with NYU Langone Health. Shotgun metagenomic sequencing using oral wash samples from the 89 case-control pairs and antral mucosal brushing samples from 55 case-control pairs were conducted. The other study, conducted by Vanderbilt University Medical Center, is a prospective case-control study on the oral microbiome and gastric cancer risk, utilizing shotgun metagenomic sequencing data of pre-diagnostic buccal samples from 319 Asians, 118 African Americans and 51 European Americans. This study includes data from three population-based studies: the Southern Community Cohort Study (SCCS), the Shanghai Women's Health Study (SWHS), and the Shanghai Men's Health Study (SMHS). The SWHS and SMHS include 74,941 women aged 40-70 years and 61,480 men aged 40-74 years, respectively, who were permanent residents of Shanghai and recruited to the cohorts between 1997 and 2006. The SCCS is an ongoing prospective cohort study, including ~86,000 participants recruited during 2002 and 2009 from 12 Southeastern states. Nearly 67% of study participants are African Americans (AAs) and the remaining are European American (EA) subjects.

  Study phs002566

• The Pioneer 100 Wellness Project (P100)

  108 individuals (age 21-89+ years; 59% males, 41% females; 89% Caucasian; not recruited based on any specific phenotype) participated in an IRB-approved study from April 2014 to January 2015. Each individual had the genome sequenced in full. Blood was collected in clinics every three months. Additionally, participants completed at-home collections of saliva, stool, and first morning void urine every three months. Stool and saliva samples were shipped directly to the vendor by the participant, while urine was given back to the study coordinators for distribution to the proper sample vendor. For each successful participant in each round we carried out 218 clinical laboratory tests, measured up to 643 metabolites and 262 proteins, and measured the abundance of 4616 operational taxonomic units (OTUs) in the gut microbiome using 16S rRNA sequencing. The P100 study had four objectives: 1) Establish cost-efficient procedures for generating, storing and analyzing multiple sources of health data obtained over time from participants and analyzed in combination with genomic data; 2) Develop and deploy analytic tools for integrating these diverse datasets and deriving actionable information from their observed interrelationships; 3) Identify novel patterns within the streams of health data that indicate either wellness, or transitions between wellness and disease; 4) Learn how to best interface with and present longitudinal health information to individuals by studying the reactions and feedback from participants as they are presented actionable information.

  Study phs001363

• Tools

  EGA Tools This page provides details of the applications available at the EGA. Submission Tool Description EgaCryptor Encrypt and create md5sum values. Crypt4gh Encrypt, decrypt or re-encrypt files. INBOX Upload your files once encrypted. FTP Upload your files once encrypted. Submitter Portal Submit and manage your submission metadata online (SEQUENCING AND PHENOTYPE ONLY) Submitter Portal API Submit and manage your submission metadata programmatically. Webin Submit and manage your submission metadata online (array data) Webin API Submit metadata using XML files. Aimed to array-based submissions. Star2xml Format conversion tool to transform tabular formats (e.g. spreadsheets) into EGA's XMLs. Used for large programmatic submissions. Data Access Tool Description DAC Portal Manage and control data access request. Download Tool Description PyEGA3 Download and decrypt datasets requested through your EGA web account. Live Outbox Download and decrypt datasets requested through your EGA web account. Fuse Client A quick and convenient way to browse through EGA files without the need for complete downloads. EGA QuickView A quick and convenient way to browse through EGA files without the need for complete downloads.

  Documentation tools

• ACTIV-6: COVID-19 Outpatient Randomized Trial to Evaluate Efficacy of Repurposed Medications

  This study is a platform protocol designed to be flexible so that it is suitable for a wide range of settings within healthcare systems and in community settings where it can be integrated into routine COVID-19 testing programs and subsequent treatment plans. This platform protocol will enroll participants in an outpatient setting with a confirmed polymerase chain reaction (PCR) or antigen test for SARS-CoV-2. Each appendix will describe a repurposed medication (study drug) to meet the protocol objectives. When only one study drug/appendix is under study, allocation between study drug and placebo will be 1:1. If multiple study drugs/appendices are under study, participants will also be randomized among the study drugs for which eligibility is confirmed. Since the route of administration of each study drug may differ, the placebos may also differ. To achieve blinding and an equitable randomization probability, a two-step randomization process will be used.In the first step, the participant will be randomized m:1 active study drug to placebo, where m is the number of active study drugs for which the participant is eligible. Then, participants will be randomized among the m study drugs for which they are eligible. Participants will carry their ‘study drug' versus ‘placebo' randomization with them into the study drug appendix. In this way, a participant allocated to placebo who is randomized to study drug A will be given the placebo that matches study drug A. This achieves equal probability of exposure to a placebo or an active study drug, and equitable distribution among all study arms for which a participant is eligible. Sites will be informed to which study drug appendix the participant is randomized, but not whether they are allocated to the study drug arm or placebo arm within that appendix. For analysis, concurrent placebo participants who were eligible for the study drug appendix will be pooled. This will result in approximately a 1:1 allocation ratio for any study drug to placebo. If a study drug appendix is stopped for efficacy and becomes standard of care, the active study drug arm may serve as a concurrent placebo for other study drugs.Participants will receive complete supply of repurposed medication (study drug) or placebo with length of treatment and amount of study drug/placebo depending on the study drug appendix and arm to which they are randomized.This study is designed so that it can be done completely remotely. However, screening and enrollment may occur in person at sites and unplanned study visits may occur in person or remotely, as deemed appropriate by an investigator for safety purposes. Participants will be on-study for up to 180 days, during which they will complete various questionnaires.

  Study phs003941

• Prostate Cancer Upgrading Reference Set

  This study aimed to investigate clinical, demographic, and molecular features of men diagnosed with low-risk prostate cancer [ISUP Grade Group 1 (GG1)] at biopsy who underwent radical prostatectomy, and for whom an increased tumor grade (ISUP Grade Group 2 or above) was subsequently detected in the resected prostate. This phenomenon is termed upgrading. In collaboration with the Early Detection Research Network (EDRN), a blinded reference set was established to facilitate upgrading biomarker detection and validation. A prospective, multi-institutional, cohort of men with the GG1 prostate cancer and intention to undergo prostatectomy was recruited. Biospecimens (blood, urine) were collected and this biorepository comprises the official EDRN Upgrading Reference Set (URS). Recording of case-control status (case = upgrading at prostatectomy, control = no upgrading at prostatectomy) was coordinated by the Data Management and Coordinating Center (DMCC) of the EDRN, who ensured blinding of all participating researchers. A subset of the reference set (n = 192) was chosen to undergo whole genome sequencing (WGS) for the investigation of a germline genomic biomarker of upgrading. Variant calls from all sequenced URS whole genomes are available through dbGaP, with the exception of one sample for which sequencing was not successful. Among investigated clinical features, prostate-specific antigen (PSA) density and percent of cancer in pre-prostatectomy positive biopsy cores were significantly associated with upgrading. Two polygenic risk score-based biomarkers were computed in the genetic sub-cohort and tested against case-control status. Neither was predictive of upgrading.

  Study phs003670

• Samples from the Greek island of Crete, MANOLIS cohort

  Genome-wide association studies of complex traits have been successful in identifying common variant associations, but a substantial heritability gap remains. The field of complex trait genetics is shifting towards the study of low frequency and rare variants, which are hypothesised to have larger effects. The study of these variants can be empowered by focusing on isolated populations, in which rare variants may have increased in frequency and linkage disequilibrium tends to be extended. This work focuses on isolated populations from Greece. Sequencing is very efficient in isolated populations, because variants found in a few samples will be shared by others in extended haplotype contexts, supporting accurate imputation.

  Study EGAS00001000067