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• Health Professionals Follow-Up Study

  Health Professionals Follow-up Study (HPFS) is a prospective cohort study of men designed to evaluate hypotheses about men’s health related to diet and lifestyle to the incidence of serious illnesses, such as cancer, heart disease, and other vascular diseases. It consisted of 51,529 U.S. male health professionals who were 40-75 years old at baseline in 1986 and completed a mailed six-page baseline questionnaire. Information on age, height and weight, ancestry, medications, disease history, physical activity, lifestyle factors, and diet were gathered, with follow-up questionnaires sent biennially to update information and record health outcomes with every four years to update their diet. This datafile includes responses to the 2016 questionnaire, which is available at: https://cdn1.sph.harvard.edu/wp-content/uploads/sites/2471/2017/09/16L.pdf

  Study phs002460

• Hereditary Cancer Predisposition Syndromes and Uveal Melanoma

  Uveal melanoma (UM) is a subtype of melanoma characterized by the strong contribution of genetic rather than environmental factors in the pathogenesis of the disease, making it an ideal model disease to study the genetic basis of cancer. The long-term goal of our laboratory is to determine the genes and mechanisms responsible for hereditary cancer predisposition associated with UM. BAP1 has been identified as a candidate gene with definitive association with predisposition to UM. However, pathogenic variants in BAP1 are detected in only a small subset of UM patients even those with strong personal and family history of cancer suggesting the existence of other candidate genes. The goal of this project is to identify novel candidate genes contributing to hereditary predisposition to UM in patients with no detectable germline pathogenic variant in BAP1.

  Study phs001943

• Transcriptomics of Liver and PBMCs in Alcohol-Associated Liver Disease

  This study was designed to characterize the transcriptome of alcohol-associated hepatitis using RNA sequencing (RNA-seq) technology for both liver tissue biopsies and peripheral blood mononuclear cells (PBMCs) extracted from blood samples, in order to identify expressed genes that are markers of the disease. To distinguish genes that differentiate alcohol-associated hepatitis from other inflammatory liver diseases, we compared the RNA-seq data generated from participants with alcohol-associated hepatitis, alcohol-associated cirrhosis, chronic hepatitis C infection, non-alcohol-associated fatty liver disease, and healthy controls. We utilized computational approaches to demonstrate that gene expression data generated from either liver tissue or blood samples can be used to identify a small set of gene biomarkers to distinguish between these liver diseases. The raw RNA-seq data will be available through dbGaP.

  Study phs003112

• MYC Drives Progression of Small Cell Lung Cancer to a Variant Neuroendocrine Subtype with Vulnerability to Aurora Kinase Inhibition

  Loss of the tumor suppressors RB1 and TP53 and MYC amplification are frequent oncogenic events in small cell lung cancer (SCLC). We show that Myc expression cooperates with Rb1 and Trp53 loss in the mouse lung to promote aggressive, highly metastatic tumors, that are initially sensitive to chemotherapy followed by relapse, similar to human SCLC. Importantly, MYC drives a neuroendocrine-low “variant” subset of SCLC with high NEUROD1 expression corresponding to transcriptional profiles of human SCLC. Targeted drug screening reveals that SCLC with high MYC expression is vulnerable to Aurora kinase inhibition, which combined with chemotherapy strongly suppresses tumor progression and increases survival. These data identify molecular features for patient stratification and uncover a novel targeted treatment approach for MYC-driven SCLC.

  Study EGAS00001002115

• XClone for analyzing somatic copy number alterations

  Somatic copy number alterations (CNAs) are major mutations that contribute to the development and progression of various cancers. Despite a few computational methods proposed to detect CNAs from single-cell transcriptomic data, the technical sparsity of such data makes it challenging to identify allele-specific CNAs, particularly in complex clonal structures. In this study, we present a statistical method, XClone, that strengthens the signals of read depth and allelic imbalance by effective smoothing on cell neighborhood and gene coordinate graphs to detect haplotype-aware CNAs from scRNA-seq data. By applying XClone to multiple datasets with challenging compositions, we demonstrated its ability to robustly detect different types of allele-specific CNAs and potentially indicate whole genome duplication, therefore enabling the discovery of corresponding subclones and the dissection of their phenotypic impacts.

  Study EGAS00001007854

• Exome_sequencing_of_thyroid_disease_in_Val_Borbera

  The Val Borbera is a region characterized by low iodine and high prevalence of thyroid disorders, the commonest endocrine disorders in the general population. About 30% of the participants of the Val Borbera Project were affected by such disorders and were characterized by several parameters, TSH level, anti TPO antibodies, echography, family origin. Individuals with extreme phenotypes were identified and could be clustered based on family origin and genotype. We propose to exome sequence 6 of them, affected with true goiter, at high dept (40-60x) to obtain information on exonic rare variants. Due to the family structure and to the availability of whole genome sequence information on 110 individuals from the isolated population we expect to be able to identify putative causative variants for thyroid disorders that may be studied in the remaining affected individuals.

  Study EGAS00001000344

• Molecular sub-classification of hormone receptor-positive breast cancer

  Patients with estrogen and/or progesterone receptor-positive breast cancer benefit from hormonal treatment, yet high global death burdens due to high prevalence and long-term recurrence risk call for biomarkers to guide additional treatment approaches. From a prospective, observational study of postmenopausal early breast cancer patients treated with tamoxifen or aromatase inhibitors gene expression analyses of 612 tumors was performed using the NanoString® Breast Cancer 360 panel. We identified novel gene expression signatures, i.e. BRCAness and Tumor Inflammation Signature (associated with high tumor lymphocyte infiltration), that may aid to select high-risk patients in order to improve adjuvant treatment by targeting DNA repair deficiency or immune-checkpoints in addition to standard chemo-endocrine treatment. The overall goal is to foster novel concepts for a stratified early breast cancer management.

  Study EGAS00001004594

• Gene expression adaptation of metastases to their host tissue

  The adaptation of metastatic cells to their host tissue critically determines the pathogenicity of a cancer and therefore patient survival. Yet, it remains elusive to what extent the host environment drives gene expression programs in metastatic cells. Here we identify adaptive mechanisms that enable metastases to establish themselves in a novel tissue context. We performed single-cell RNA-sequencing on malignant and benign tissue samples from untreated donors with colorectal adenocarcinoma and liver metastasis to deduce tissue adaptive expression patterns. A novel computational approach identified genes and pathways that consistently adapted to the host tissue at the transition from the primary tumor to the paired metastasis across donors. This analysis revealed that the majority of expression changes in the metastasis reflect an expression signature reminiscent of benign liver epithelial cells. Cellular processes adapting to the liver environment include basic cellular functions such as energy metabolism, as well as tissue-specific pathways such as the regulation of lipid metabolism by PPAR-α. These adaptations potentially increase the pathogenicity of the metastatic cells and may provide new therapeutic strategies.

  Study EGAS50000000817

• Integrating Genomic and Transcriptomic Data to Identify Breast Cancer Susceptibility Genes

  Genetic factors play an important role in the etiology of both sporadic and familial breast cancer. Since 2007, common genetic variants in ~200 loci have been identified in genome-wide association studies (GWAS) in relation to breast cancer risk. However, it is often difficult to translate GWAS findings to disease prevention and treatment since causal genes in the large majority of GWAS-identified loci are unknown. Furthermore, a large fraction of breast cancer heritability remains unexplained. Recent studies suggest that nearly 80% of disease heritability can be explained by genetic variants regulating gene expression. Herein, we propose three well-powered transcriptome-wide association studies (TWAS) to systematically investigate the association of breast cancer risk with gene expression across the transcriptome of African, Asian and European descendants. In Aim 1, we will perform RNA sequencing and high-density genotyping assays using normal breast tissue samples, and build race-specific gene expression prediction models using data from 1000 women of African, Asian and European descent. These models will be applied to the GWAS data generated from approximately 320,000 breast cancer patients and controls to impute gene expression for association analyses of predicted gene expression with risk of breast cancer overall, and by estrogen receptor and HER2 status. In Aim 2, we will select the top 50 genes identified in Aim 1 for in vitro functional assays to assess their influence on major cell functions related to cancer biology. In Aim 3, we will evaluate whether TWAS-identified genes may express differently in normal breast tissues and breast cancer tissues collected from African, Asian, and European descendants to assess whether these genes may contribute to racial differences in breast cancer risk by molecular subtypes. With strong methodology and a large sample size, we believe that this proposed study should be able to identify and characterize a large number of novel genes related to breast cancer risk. Uncovering breast cancer susceptibility genes will greatly improve the understanding of the genetic and biological basis for breast cancer and accelerate the translation of genetic findings to disease prevention and patient care.

  Study phs003535

• Therapeutic Resistance to PI3K-alpha Inhibitors

  We have studied the tumor genomic evolution in a patient with metastatic breast cancer bearing an activating PIK3CA mutation. The patient was treated with the PI3Kα inhibitor BYL719 and achieved a lasting clinical response on BYL719, but eventually progressed to treatment and died shortly thereafter. A rapid autopsy was performed and a total of 14 metastatic lesions were collected for further analysis. In order to identify possible genetic determinants of acquired resistance to PI3Kα inhibition, we took a three-step approach. First, we examined both the primary tumor (before BYL719 treatment) and the new lung metastasis by whole genome sequencing (DNA from the spleen was used as a normal control). Then, we analyzed the primary tumor, lung metastasis, and the peri-aortic lesion that remained stable (responding) at the time of progression to BYL719 therapy by whole exome sequencing. Finally, to confirm and expand our findings, we sequenced the primary tumor and all the metastatic lesions to >500-fold coverage using a custom targeted deep-sequencing assay, MSK-IMPACT. Using this 3-step approach, we have demonstrated that patient’s lesion underwent parallel genetic evolution at multiple metastatic sites with different PTEN genomic alterations leading to a convergent PTEN- null phenotype resistant to PI3Kα inhibition. In order to expand our observations, we analyzed paired samples (pre-treatment and at progression) from six additional patients enrolled in the BYL719 trial. Acquired bi-allelic loss of PTEN was found in one additional patient treated with BYL719 whereas in two patients PIK3CA mutations present in the primary tumor were no longer detected at the time of progression. To functionally characterize our findings, inducible PTEN knockdown in sensitive cells resulted in resistance to BYL719, while simultaneous PI3K-p110β blockade reverted this resistance phenotype, both in cell lines and in PTEN-null xenografts derived from our patient. We conclude that parallel genetic evolution of separate sites with different PTEN genomic alterations leads to a convergent PTEN-null phenotype resistant to PI3Kα inhibition.

  Study EGAS00001000991

• Target Capture Sequencing of 12 patients

  We perfomed target capture DNA sequencing of 12 patients to assess the detailed biological mechanisms of resistance to immune checkpoint inhibitors.

  Study JGAS000589

• Neoadjuvant_Breast_Cancer_Validations

  This study aims to re-sequence findings from whole genome studies using a bespoke pulldown method to validate mutations in those genomes sequenced.

  Study EGAS00001000428

• CRU-Ukrainian National Research Center for Radiation Medicine Trio Study

  Data on transgenerational effects following nuclear accidents are important for understanding fully the consequences of parental exposure to ionizing radiation. Few studies to date have had adequate statistical power to detect effects of the magnitude expected based on animal data, and most have not been of low-dose, protracted exposures associated with nuclear accidents and their aftermath. Although, to date, scant use has been made of the new genomic technologies, in Chernobyl-exposed areas of Ukraine and Belarus, excess minisatellite mutations have been seen in children born after the accident. We propose a study of parent-child trios in which at least one parent was exposed to Chernobyl radiation as a clean-up worker (mean dose>=100 mGy) and/or evacuee from a contaminated area (mean >=50 mGy). The specific aims are to investigate the transgenerational and de novo mutation rates of the spectrum of genetic variants in trios, in particular looking at effects in children and mapping them to possible parental origin of the chromsoome. Together with long-term collaborators at the Research Center for Radiation Medicine (RCRM) in Kiev, epidemiologic data will be collected for up to 450 trios of parents with preconceptional doses and their unexposed offspring. We will use state-of-the-art genomic technologies to characterize the landscape of the genomes of the trios to determine whether parental radiation exposure is associated with genetic mutations transmitted to the offspring, by examining de novo mutation rates, minisatellite mutations, copy number alterations, and variations in telomere length. The analysis will be conducted in peripheral blood and/or buccal samples (when blood is not available) from complete father-mother-child trios. Doses to the gonads from the time of the accident to the time of conception will be reconstructed for all parents using existing records supplemented by interview data. Trio subjects will be selected from representative populations exposed to radiation from Chernobyl who are under active follow-up in the Clinico-Epidemiologic Registry at RCRM. To help identify specific effects of paternal and maternal radiation exposure, we will initially select sets of trio subjects in five categories: (1) exposed father, unexposed mother; (2) unexposed father, exposed mother; (3) both parents exposed; (4) both parents unexposed; and (5) a group of high dose "emergency workers" with acute radiation syndrome. All trio members will be invited to the RCRM outpatient clinic for collection of a 20 ml blood sample (or buccal cells for those who refuse phlebotomy). Both parents will be asked to complete a general questionnaire to obtain demographic and lifestyle data. Then one or both will complete detailed dosimetry questionnaires, based on forms used in previous collaborations with RCRM and administered by specially trained interviewers. Once 50 trios have been recruited (10 from each of the 5 exposure categories), we will conduct an interim evaluation of participation rates, sample collection and quality, and dose reconstruction in order to modify the protocol as needed. The analytical approach will be to correlate the extent, especially for de novo events of genetic alterations in the offspring with parental pre-conceptional radiation dose overall and by parental origin. The statistical power in relation to de novo mutations is very high, in excess of 90%, but somewhat lower for trends in minisatellite mutations. Study findings will contribute importantly to knowledge of the heritable effects of moderate- and low-dose radiation exposure in humans and to radiation risk projection. Eventually data from the Trio Study may be shared with the international community through dbGap.

  Study phs001163

• Biomarker Screen for Efficacy of Oncolytic Virotherapy in Patient-derived Pancreatic Cancer Cultures

  Pancreatic ductal adenocarcinoma (PDAC) is a tumour entity with unmet medical need. To assess the therapeutic potential of oncolytic virotherapy (OVT) against PDAC, different oncolytic viruses (OVs) are currently investigated in clinical trials. However, systematic comparisons of these different OVs in terms of efficacy against PDAC and biomarkers predicting therapeutic response are lacking. We screened fourteen patient-derived PDAC cultures for their sensitivity to five clinically relevant OVs, namely serotype 5 adenovirus Ad5-hTERT, herpes virus T-VEC, measles vaccine strain MV-NIS, reovirus jin-3, and protoparvovirus H 1PV using live cell analysis, quantification of viral genome/gene expression, cell viability as well as cytotoxicity assays. Sensitivity was correlated with transcriptome profiles to identify potential predictive biomarkers for response to OVT. Patient-derived PDAC cultures showed individual response patterns to OV treatment. Twelve of fourteen cultures were responsive to at least one OV, with no single OV proving superior or inferior across all cultures. Known host factors for distinct viruses were retrieved as potential biomarkers. Compared to the basal-like molecular subtype, the quasi-mesenchymal subtype of PDAC was more sensitive to H-1PV, jin-3, and T-VEC. Expression of viral entry receptors did not correlate with sensitivity to OV treatment. Rather, cellular pathways controlling immunological, metabolic, and proliferative signalling appeared to determine outcome. For instance, high baseline expression of interferon-stimulated genes (ISGs) correlated with relative resistance to oncolytic measles virus, whereas cGAS expression was associated with exceptional response. Combination treatment of MV-NIS with a cGAS inhibitor improved tumour cell killing in several PDAC cultures.

  Study EGAS00001007001

• Urethral Microbiome of Adolescent Males

  Urethral microbiome of adolescent males is designed to characterize the microbial communities resident in the urethra of young men, to identify differences in these communities as a function of race/ethnicity, circumcision status, sexual exposures, and uro-genital symptoms. We collect detailed sexual behavior and symptoms data using cellular telephones with Internet access. Specimens are routinely collected at monthly intervals, and intermittently following reported symptoms, specific sexual exposures, or identification of a sexually transmitted infection. We also collect periodic samples from the penile coronal sulcus to better characterize its relationship to the urethral micriobial communities. Participants are ages 14 - 17 at enrollment, and prior history of sexual exposure is not required for participation. Parental permission is obtained for each participant. The planned duration of followup is up to 4 years allowing for prospective observation of both physical and behavioral maturation from middle adolescence into young adulthood. The overall objectives of the project are to better characterize the healthy male urethral microbiome, and to use this information to better understand acquisition of urethritis and sexually transmitted infections, as well as chronic genital pain and prostatitis syndromes that become common among young adults.

  Study phs000259

• Impact of Race and Genetic Factors on Beta Blocker Effectiveness in Heart Failure

  Heart Failure (HF) continues to be an enormous public health problem, despite the many advances in its pharmacotherapy over the past 25 years. The availability of multiple therapeutic options for HF requires individualization of therapy. However, there are currently insufficient tools to guide the optimal selection of therapy. The expansion of human genomic information has led to exciting new opportunities to improve the selection of drug therapy. In order to evaluate whether genetic variation impacts outcomes and drug response in heart failure, we performed a cohort study of patients with heart failure. Our overall plan was to recruit patients who have heart failure and receive treatment through HAP-HFMG. This allowed us to collect clinical outcomes, and quantify medication adherence via electronic pharmacy claims data. We collected whole blood samples for genetic analysis. We then tested whether genetic variants can predict patient outcomes (survival) in the context of their medical therapy (drug exposure). The primary medications of interest were beta blockers. Outcomes were modeled overall, accounting for the amount of exposure to the agent, and adjusting for baseline characteristics.

  Study phs001501

• CIDR Whole Exome Sequencing in Joubert Syndrome

  The purpose of this study is to identify new genetic causes of neurodevelopmental diseases (NDDs) in the Joubert syndrome (JS) spectrum. Joubert syndrome is a recessive disease characterized by cerebellar vermis hypoplasia. Our currently funded NINDS award entitled "Molecular characterization of Joubert syndrome" seeks to identify new genetic causes through a variety of molecular strategies. Although our previous strategies involved whole genome SNP-scans, followed by candidate gene sequencing to arrive at identification of new JS causes, we have recently moved to Whole Exome Sequencing (WES) as a highly efficient methodology that is optimized for recessive disease. In this pilot project, CIDR has sequenced DNA on probands from 20 inbred families with JS spectrum disorders in which known causes have been excluded, that have not previously undergone genome-wide SNP scans. These paired end reads will be subject to our established bioinformatics pipeline including HOMOZGYOSITY, SNP and INDEL callers in our lab to identify potentially deleterious sequence changes (PDSC). This is followed by analysis to include testing each PDSC for segregation in the whole pedigree, for occurrence in a ethnically-matched cohort, as well as a defined patient cohort patients, in order to validate new NDD genes.

  Study phs000382

• Nanobody-Tethered Transposition Allows for Multifactorial Chromatin Profiling at Single-Cell Resolution

  Chromatin states are functionally defined by a complex combination of histone modifications, transcription factor binding, DNA accessibility, and other factors. However, most current single-cell-resolution methods are unable to measure more than one aspect of chromatin state in a single experiment, limiting our ability to accurately measure chromatin states. Here we introduce nanobody-tethered transposition followed by sequencing (NTT-seq), a new assay capable of measuring the genome-wide presence of multiple histone modifications and protein-DNA binding sites at single-cell resolution. NTT-seq utilizes recombinant Tn5 transposase fused to a set of secondary nanobodies (nb). Each nb-Tn5 fusion protein specifically binds to different immunoglobulin-G antibodies, enabling a mixture of primary antibodies binding different epitopes to be used in a single experiment. We apply bulk- and single-cell NTT-seq to generate high-resolution multimodal maps of chromatin states in cell culture and cells of the human immune system, demonstrating the high accuracy and sensitivity of the method. We further extend NTT-seq to enable simultaneous profiling of cell-surface protein expression alongside multimodal chromatin states to study cells of the immune system.

  Study phs003068

• Systems Analysis of Single-Cell Heterogeneity Underlying Glioma Drug Resistance

  This study characterizes the transcriptional regulatory mechanisms that drive responses of two patient-derived glioblastoma multiforme (GBM) stem-like cells (PD-GSCs) that have distinct phenotypes - one sensitive and another resistant to the drug pitavastatin. This study investigates the differing mechanisms driving drug response in the two PD-GSCs at the single-cell level, and provides an approach that can be used to infer transcriptional regulatory network models, which can then be used to identify mechanisms driving cell-state transitions, e.g., proneural-to-mesenchymal transitions (PMT), which has been observed experimentally and clinically in GBM. The use of these network models enabled the identification of transcription factor and gene targets that perturbed drug-induced PMT through 1) simulations of network dynamics network, and 2) characterization of gene program activities over the time-course response to drug treatment. These results enabled the identification of multiple siRNAs and the drug vinflunine as secondary components that potentiate the efficacy of pitavastatin. This work demonstrates an approach to uncover the transcriptional network topology (TRN) topology of PD-GSCs, and use it to rationally predict combinatorial treatments that block treatment escape and acquired resistance to drugs in GBM.

  Study phs003501

• The identification of genetic vulnerabilities in head and neck cancers for the development of novel treatments.

  The global cancer burden is expected to double by the year 2030 and this will disproportionately affect the Asian continent. Head and neck squamous cell carcinoma (HNSCC) is endemic in Asia. It is the sixth most common cancer worldwide and the second most common in Malaysia, with approximately 600,000 new cases per year globally. Longterm survival remains less than 50%, underscoring the need for better therapeutic strategies. In this proposal we aim to bring new technological advancements in the identification of critical genes in HNSCC and the identification of compounds for the development of new therapies in HNSCC. We propose to genomically characterise 16 unique Asian H&N cancer cell lines, to classify sub groups where identification of essential genes that can be targeted for tumor control can be applied in a more rational way. Further, we propose to use zebrafish, an established drug discovery platform to identify promising pathway-specific compounds that could be further studied using CRISPR/Cas9 lethality screens and biological models to better identify novel therapeutic strategies to combat this major health problem in Asia.

  Study EGAS00001002682

• SINGLE_CELL_ANALYSIS_OF_IN_VITRO_ERYTHROPOIESIS

  We are developing a protocol to differentiate mouse and human induced pluripotent stem (IPS) and embryonic stem (ES) cells towards the haematopoietic pathway to generate erythrocytes in vitro. This system has many applications such as the study of the role of specific genes and human polymorphisms in infectious diseases such as malaria, as well as haematological diseases such as myelodysplastic syndrome. The nature of the in vitro differentiation process means that a heterogeneous population of cells is generated. In order to understand the types of cells produced with our protocol, we have performed a single cell analysis, which has the power to reveal the different populations of cells and their characteristics. For this, a cDNA library has been made that needs to be sequenced to obtain the gene expression profiles of the different cells. With this information we will be able to assess the quality of the differentiation protocol and improve it in order to produce better cells for the downstream applications.This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001000764

• About

  About What's the EGA? The European Genome-phenome Archive (EGA) is a global network for permanent archiving and sharing of personally identifiable genetic, phenotypic, and clinical data generated for the purposes of biomedical research projects or in the context of research-focused healthcare systems. Jointly managed by the European Bioinformatics Institute (EMBL-EBI) in Cambridge (UK) and the Centre for Genomic Regulation (CRG) in Barcelona, we aim to advance biomedical research and promote personalised medicine worldwide by enabling discovery of and access to human genomic and health research data. The EGA contains data collected from individuals whose consent agreements authorise data release for specific research use to bona fide researchers. We ensure strict security measures to control access to the data and maintain patient confidentiality. With expertise in data management and technical infrastructure, we promote FAIR data reuse and enable researchers to share their data securely. By leveraging public funding and our strategic partnerships, the EGA provides a free service for permanent data storage, data discovery, and secure data access. In addition, we foster a federated network to provide transnational access to human research data in compliance with legal frameworks. For additional information about the EGA, please contact: Helen Parkinson and Mallory Freeberg EMBL European Bioinformatics Institute Arcadi Navarro, Roderic Guigó, and Jordi Rambla Center for Genomic Regulation History The European Genome-phenome Archive was launched in 2008 at the European Bioinformatics Institute (EMBL-EBI), an outstation of the European Molecular Biology Laboratory (EMBL), to address an identified need for archiving and sharing the results of genome-wide association studies from the Wellcome Trust Case Control Consortium. With the signing of a memorandum of understanding in 2013 and a formal agreement in 2016, the EGA became a joint project of EMBL-EBI and the Centre for Genomic Regulation (CRG). The two institutes work together to support the EGA services, including supporting submissions, website, strategic leadership, and data infrastructure developments. In 2022, the Federated EGA was officially launched with the signature of the first five countries: Finland, Germany, Norway, Spain, and Sweden. With more than 20 additional nodes worldwide preparing to join, the Federated EGA aims to become the largest human omics data sharing initiative towards understanding human health and disease. EGA overview If you're a researcher you may need to deposit, manage, or access genomic data in a secure and regulated way. The European Genome-phenome Archive (EGA) is a platform that facilitates these processes, ensuring that sensitive data is stored and shared in accordance with legal and ethical regulations. Submission process To start a submission, you need to become an EGA submitter. For that, you’ll need to sign a Data Processing Agreement (DPA) with us, that defines the terms and conditions under which your data will be processed and shared within the EGA system. The access to each study is controlled by its Data Access Committee (DAC). The DAC is responsible for managing data access requests and ensuring that the release of data is in accordance with the General Data Protection Regulation (GDPR). Please, note that once your data is released, all public metadata related to your study and dataset(s) will be searchable on the EGA website. However, the files are only accessible under controlled access, which means that a DAC has to agree to a previous data access request. Request process It is possible to submit an access request to data stored at the EGA. The DAC assigned to the study will assess the request and, if approved, grant access to the data. Requesters must provide sufficient justification for your request and comply with the intended data usage in order to get access to it. Each dataset is covered by a Data Access Agreement (DAA) that defines the terms and conditions of use for the specified dataset/s. The DAA is created and provided by the DAC, and must be signed by the individual requesting access to the given dataset/s. Download process Once the request for access is approved, the data and metadata can be downloaded. The EGA offers various download options to fit the needs: it is possible to preview files without downloading them, download specific files of interest, or even download terabytes of data. Overall, the EGA provides a secure and regulated environment for depositing, managing, and accessing human data. Regardless of the role - submitter, DAC member, or requester - the EGA provides assistance for each while ensuring that sensitive data is managed in an ethical and responsible manner. More information on how EGA handles data is available in the EGA dataflow.

  Documentation about/ega

• Genome-Wide Association Study of Celiac Disease

  Celiac disease (gluten-sensitive enteropathy, celiac sprue) is a common disease with significant morbidity and mortality. It is caused by sensitivity to the dietary protein gluten, resulting in a chronic enteropathy in the small intestine. Celiac disease is now recognized to be a common disease, with reports that the disease frequency is 1:133 in the United States, similar to European estimates. There is recent evidence to suggest that the incidence of the disease is rising. Occult disease is frequently present with minimal classic symptoms or signs. The ratio of symptomatic to asymptomatic celiac disease is estimated to be 1:7. Some complications of celiac disease include lymphoma, osteoporosis, anemia, miscarriages, seizures, vitamin deficiencies, and co-occurrence of other autoimmune diseases. The only treatment is a gluten-free diet, so that recurrence of symptoms and complications may occur after minor dietary indiscretions. Identifying the underlying genetic causes of celiac disease may allow us to identify susceptible individuals, as well as advance new ways to prevent the disease and to treat it once it occurs. Several genome-wide linkage studies and one genome-wide association study of celiac disease have been conducted. Other than the common locus at HLA, few putative celiac disease loci have been replicated between studies, suggesting that the disease is heterogeneous and complex. A portion of the genetic predisposition can be attributed to HLA, but the etiology is likely due to a number of rare, high penetrant genes (as would be identified in linkage analysis) and to more common, low penetrant genes (as would be identified in association studies). The objective of this study is to identify new loci that increase risk to develop celiac disease. We will capitalize on existing North American resources, including three large collections of celiac cases and controls (Aim 1) and an independent set of celiac cases and their families (Aim 3). We propose a comprehensive multi-stage approach, with the following specific aims. In Aim 1, we will conduct a genome-wide association (GWA) study of single nucleotide polymorphisms (SNPs) and copy number variants (CNVs). The GWA will include1900 disease cases and 3400 matched controls, genotyped using the Illumina Human 610-quad chip. Statistical analyses will be performed to test for associations with celiac disease. In Aim 2, we will conduct a combined analysis of our GWA dataset from Aim 1 and a previous GWA dataset to identify additional low-penetrance loci. In Aim 3, we will attempt to replicate significant findings from the GWA study in two independent sample sets. At the conclusion of this study, we expect to have validated a number of SNPs and CNPs from regions in the genome that alter the risk of developing celiac disease. These SNPs may prove useful at both the clinical and research level. The data from the study will be shared with the scientific community.

  Study phs000274

• dbGaP Collection: NHLBI Heart Failure Related dbGaP Data (No IRB requirement)

  The National Heart, Lung, and Blood Institute (NHLBI) Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research has concluded. The NHLBI will continue to make this collection of data available to the research community.Past information regarding the Data Collection for the NHLBI Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research is below.The National Heart, Lung, and Blood Institute (NHLBI), part of the National Institutes of Health (NIH), is inviting novel Solutions for the NHLBI Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research. The goal of the challenge is to foster innovation in computational analysis and machine learning approaches utilizing large-scale NHLBI-funded datasets to identify new paradigms in heart failure research. The challenge aims to address the need for new open source disease models that can define sub-categorizations of adult heart failure to serve as a springboard for new research hypotheses and tool development in areas of heart failure research from basic to clinical settings. NHLBI has a history of making considerable investments in the creation of deep data resources including: long-standing, deeply-phenotyped epidemiological cohorts, innovative clinical trials, and large-scale precision medicine efforts that have generated whole genome sequencing and "other omics" data for more than one-hundred thousand individuals. To provide challenge participants with streamlined access to data across NHLBI's numerous studies containing heart failure data, the NHLBI has created this dbGaP study collection. Data access for this collection is controlled by NHLBI's Data Access Committee. Challenge participants are required to follow the use restrictions and acknowledgement instructions from the original dataset(s). Please note that the data in this collection are not harmonized across studies or otherwise altered from the original study. The NHLBI Big Data Analysis Challenge: Heart Failure Data Collection contains all NHLBI studies currently in dbGaP that contain data that may be relevant to research on heart failure. The studies in this collection are approved for General Research Use (GRU), Health/Medical/Biomedical Use (HMB), or Disease-Specific Use (DS) that permits research on heart failure. These studies span a variety of study designs, inclusion and exclusion criteria, sample sizes, and provide a wide breadth and depth of phenotype data on study participants. The available genomic data in these studies also varies, including genotyping arrays, sequencing (targeted, exome, whole genome), and additional -omic data (e.g., RNA or metabolite profiles). Please refer to each study's individual accession page to learn more about how study data were collected. Challenge participants are reminded that in addition to dbGaP, NHLBI's Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC) contains other studies that have collected data relevant to heart failure and may wish to utilize BioLINCC data in the development of their Solution. Please refer to the individual accession page for each study in this collection to learn more about the history of each study.

  Study phs001991

• INCLUDE Data Hub: NDA GUIDs for Down Syndrome Research

  The INCLUDE (INvestigation of Co-occurring conditions across the Lifespan to Understand Down syndromE) Project is an NIH-wide collaboration that seeks to improve health and quality of life for people with Down syndrome. The INCLUDE Project Data Coordinating Center (DCC) and partners created the INCLUDE Data Hub, a centralized data resource that allows access to large-scale clinical and multi-omics datasets specific to Down syndrome and supports collaborative, cloud-based analysis to accelerate scientific discoveries related to Down syndrome and its co-occurring conditions. The INCLUDE Data Hub includes an innovative researcher data repository, a portal, and a cloud-based platform for data analysis. The portal provides access to de-identified demographics and clinical metadata, as well as multi-omics datasets, including whole genome sequences, transcriptomes, proteomes, and metabolomes. The INCLUDE Data Hub uses a 'registered access' model, whereby users can access the portal and associated data after agreeing to terms of use. From the Data Hub, users can also reach 'controlled access' data (e.g., whole genome sequences) only for those studies for which they have obtained approval by an NIH Data Access Committee through the corresponding dbGaP study. A thoughtful linkage strategy to identify duplicate participants across studies enables researchers to merge multiple datasets and data types to create richer datasets and reduce costly redundancies in large-scale data generation (e.g., -omics) while mitigating potential risks introduced by linkage.Based on recommendations from the NICHD Office of Data Science and Sharing, which completed a comprehensive assessment of existing Privacy Protecting Record Linkage (PPRL) and associated data governance solutions, the INCLUDE DCC and the associated NIH Steering Committee have implemented NIMH Data Archive Global Unique Identifiers (NDA GUIDs) in the INCLUDE Data Hub. The NDA GUID Tool is a government-owned and operated PPRL technology that enables researchers to link data from multiple sources to the same individual without revealing personally identifiable information (PII). With the NDA GUID Tool, the same participant information will return the same GUID whenever or wherever it is entered. The GUID itself is not personally identifiable information or protected health information. Sharing data with NDA GUIDs allows approved researchers to link together data on a single participant, even if the data were collected at different locations or through different studies or are distributed from different data repositories. This dbGaP study enables researchers to access an INCLUDE GUID Mapping File that includes all available NDA GUIDs and their associations to study-specific Participant IDs across studies in the INCLUDE Data Hub. This dbGaP study only distributes NDA GUIDs associated with the INCLUDE Data Hub datasets. To access the associated controlled-access datasets, add the corresponding dbGaP studies to your Data Access Request. A list of these studies is available on the INCLUDE Data Hub Portal: https://portal.includedcc.org/studies.

  Study phs003678