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• Dataset for NSCLC-RNA

  Rare cancer sequencing data of 45 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008846

• Population Architecture using Genomics and Epidemiology (PAGE)

  PAGE II (2013-2017) seeks to expand understanding gained during PAGE I and similar studies of how ancestry-specific differences in allele frequencies and LD may explain differences in risks of common traits and conditions. Recent studies have identified rare genetic variants that are likely to contribute to common diseases and traits and observed that rare variants likely to be functional, such as those in coding and regulatory regions, tend to be population-specific. PAGE II has genotyped over 50,000 samples using MEGA, an Illumina high density custom exomechip array. The MEGA data is being imputed in PAGE to the 1000 Genomes panel. PAGE also sequenced 1,000 samples representative of 21 populations from the Americas. PAGE has harmonized phenotype data for ~300 trait variables. These datasets will be analyzed to continue emphasis on characterizing population-level disease risks in non-European-descent individuals. Cohorts in PAGE II are: CALiCo (Causal Variants Across the Life Course, a consortium of ARIC, CARDIA, HCHS/SOL, Strong Heart Studies), ISMMS (Mount Sinai BioMe Biobank), MEC (Multiethnic Cohort), WHI (Women's Health Initiative), and Stanford University (PAGE Global Reference Panel). Genotyping services were provided by the Center for Inherited Disease Research (CIDR) and sequence data were provided by the McDonnell Genome Institute at Washington University School of Medicine. PAGE I (2008-2013): The first phase of PAGE examined putative causal genetic variants across approximately 100,000 African Americans, Asian Americans, American Indians, European Americans, Hispanic Americans, and Native Hawaiians from four groups representing nine large U.S.-based cohorts. Two genotyping approaches were employed - targeted genotyping of selected SNPs identified in genome-wide association studies of common disease, and a large-scale effort focused on the Metabochip array, which facilitated trans-ethnic fine mapping of several diseases of public health importance. Cohorts in PAGE I were: CALiCo (Causal Variants Across the Life Course, a consortium of ARIC, CARDIA, CHS, HCHS/SOL, Strong Heart Cohort Study, Strong Heart Family Study), EAGLE (Epidemiologic Architecture for Genes Linked to Environment, based on 3 National Health and Nutrition Examination Surveys (NHANES)), MEC (Multiethnic Cohort) and WHI (Women's Health Initiative). Logistical and scientific support is provided by the PAGE Coordinating Center and the NHGRI Division of Genomic Medicine. PAGE II is funded by the NHGRI and the NIMHD. To access PAGE studies currently available in dbGaP, please click on the links below.Please note that some PAGE studies belong to larger cohorts and have been included as PAGE substudies. For those studies, there is an additional link to the parent study. phs000223 PAGE-ARIC and phs000280 ARIC Cohort phs000236 PAGE-CARDIA and phs000285 CARDIA Cohort phs000301 PAGE-CHS and phs000287 CHS Cohort phs000559 PAGE-EAGLE-BioVu phs000208 PAGE-EAGLE-NHANES phs000555 PAGE-HCHS/SOL and phs000810 HCHS/SOL Cohort phs000220 PAGE-MEC phs000580 PAGE-SHS and SHFS phs001033 PAGE Global Reference Panel phs000227 PAGE-WHI and phs000200 WHI Cohort

  Study phs000356

• The Mutational Landscape of CTCL and Sezary Syndrome

  Sezary syndrome is a leukemic and aggressive form of cutaneous T-cell lymphoma (CTCL) resulting from the malignant transformation of skin-homing central memory CD4+ T cells. To identify new genetic alterations involved in Sezary syndrome and CTCL transformation we performed whole-exome sequencing of tumor-normal sample pairs from 26 Sezary syndrome and 16 CTCL patients. These analyses revealed a distinctive pattern of somatic copy number alterations in Sezary syndrome including highly prevalent recurrent chromosomal deletions involving the TP53, RB1, PTEN, DNMT3A, and CDKN1B tumor suppressor genes. Mutation analysis identified a broad spectrum of somatic mutations involving key genes involved in epigenetic regulation (TET2, CREBBP, MLL3, BRD9, SMARCA4 and CHD3) and signaling, including mutations in MAPK1, BRAF, CARD11 and PRKG1 driving increased MAPK, NFKB and NFAT activity upon T-cell receptor stimulation. Collectively, our findings provide new insights into the genetics of Sezary syndrome and CTCL and support the development of personalized therapies targeting key oncogenically activated signaling pathways for the treatment of these diseases.

  Study phs000994

• Genetics of Glucose Regulation in Gestation and Growth (Gen3G) Cohort - Placenta Transcriptomics RNA Sequencing

  The overarching goals of Genetics of Glucose regulation in Gestation and Growth (Gen3G) are to increase our understanding of biological, environmental, and genetic determinants of glucose regulation during pregnancy and their impact on fetal/child development. Gen3G is a prospective cohort study: we initially recruited 1,024 pregnant women between 2010-2013 at Blood Sampling in Pregnancy Clinic during the first trimester of pregnancy (median 9 weeks of gestation) in Sherbrooke, Québec, Canada. We assessed 898 pregnant women at second trimester (median 26 weeks of gestation), when participants completed a 75g oral glucose tolerance test (OGTT) as clinically indicated for screening of gestational diabetes mellitus (GDM). We collected data for 854 mother-child dyads at delivery (from medical records), in addition to placenta and/or cord blood samples in majority of newborns.The overall goal of the grant that supported data that is included in this dbGaP submission was to discover novel placental factors that regulate glucose metabolism in pregnancy and predict GDM by conducting genome-wide transcriptomics (RNA and miRNA) in carefully collected placenta samples from Gen3G.

  Study phs003151

• Single-cell RNA-seq of celiac disease-specific plasma cells

  Disease-specific plasma cells (PCs) reactive with transglutaminase 2 (TG2) or deamidated gluten peptides (DGP) are abundant in celiac disease (CeD) gut lesions. Their contribution toward CeD pathogenesis is unclear. We assessed expression of markers associated with PC longevity in 15 untreated and 26 treated CeD patients in addition to 13 non-CeD controls, and performed RNA-sequencing with clonal inference and transcriptomic analysis of 3251 single PCs. We observed antigen-dependent V-gene selection and stereotypic antibodies. Generation of recombinant DGP-specific antibodies revealed a key role of a heavy-chain residue that displays polymorphism, suggesting that immunoglobulin gene polymorphisms may influence CeD-specific antibody responses. We identified transcriptional differences between CeD-specific vs non-disease-specific PCs and between short-lived vs long-lived PCs. The short-lived CD19+CD45+ phenotype dominated in untreated and short-term-treated CeD, in particular among disease-specific PCs but also in the general PC population. Thus, the disease lesion of untreated CeD is characterized by massive accumulation of short-lived PCs that are not only directed against disease-specific antigens.

  Study EGAS00001004623

• A plasma protein biomarker signature that differentiates acute rheumatic fever from related clinical presentations

  Acute Rheumatic Fever (ARF) is a systemic inflammatory condition triggered by Group A Streptococcus infection, with timely diagnosis critical to prevent Rheumatic Heart Disease. ARF pathogenesis is poorly understood and diagnosis is based on clinical criteria. Here, we compared ARF cases and well-defined controls from two Uganda cohorts. We identified a 5-protein signature that discriminates ARF patients from clinically-similar conditions (receiver operating characteristic-area under the curve (ROC-AUC)=1.0, n=18 definite ARF vs n=9 known alternate diagnosis; ROC-AUC=0.97, n=18 definite ARF vs n=13 unknown alternate diagnosis), which retained very good diagnostic value in a validation cohort (ROC-AUC=0.83 n=26 definite ARF vs n=13 unknown alternate diagnosis). Pathway analysis identified the epithelial-mesenchymal transition pathway as highly-associated with acute ARF, suggesting that tissue damage and repair is central to ARF pathogenesis. Our findings require further validation, yet highlight the potential for proteomics to identify clinically useful diagnostic biomarkers that would revolutionise ARF diagnosis and treatment.

  Study EGAS00001008381

• What is a DAC?

  What is a DAC? Given the complexity, scale, and diversity of global submitters and studies, the EGA operates a distributed data access model in which requests are made to the data controller, not to the EGA. The European Commission defines a data controller, in the General Data Protection Regulation (GDPR), as the person that determines the purposes for which and the means by which personal data is processed. A Data Access Committees, commonly referred to as DACs, comprise on or more individuals (or data controllers) that review data access requests and make decisions on who can access personally identifiable genetic, phenotypic, and clinical data deposited at the EGA. Therefore, the members of a DAC should be individuals who have the authority to approve data access requests. The animation describes how you can authorise access to your sensitive data with the help of Data Access Committee and Authorisation tool. Acknowledgement to CSC - IT Center for Finland, Elixir Finland, Elixir Europe. Frequently Asked Questions How can I create a Data Access Committee? How can I create a Data Access Committee? The members of a DAC can come from different areas of expertise, such as data management, data analysis, information technology, legal and compliance, subject matter experts, privacy and security, and representatives from the organisations or individuals that provide data to the DAC. The specific members of a DAC can vary depending on the needs of the organisation and the type of data being managed. The EGA strongly suggests checking with your organisation to align with its regulations How should a DAC be named? The chosen name must be informative to the applicant.  For example, internal identifiers, such as grant numbers, should not be used. Individual PI names should also not be used. DAC's are often named after the organisation or department of the data source.  Browse the full list of DAC names currently in the EGA. How can I become an EGA DAC contact? To register a DAC at the EGA you must create first as an EGA user. Once your EGA user has been approved by the Helpdesk team, you will be able to log in to the DAC Portal. How can I register a DAC? To register a DAC, follow the DAC Portal instructions.  You will be required to provide a DAC name, name of the individual(s) that make up your DAC and contact details for your DAC including your Institutional email(s). Wherever possible, the DAC should make sure that all points of contact are readily available and able to answer any initial data requests/queries in < 2 weeks.  Once your DAC is registered, you will have to wait upon the validation from our Helpdesk team. As soon as all the validations have been completed, your DAC will be activated. Alternatively, you can also establish a DAC at the EGA during a programmatic submission through Webin API. Which are the possible roles of a DAC contact? There are two possible roles for DAC contacts: member and admin. An admin has additional privileges compared to a member: An “admin” can manage data requests, create and edit policies, edit the content of the DAC, add or remove contacts, and decide the role of each contact. A “member” can manage data requests and create policies. However, a member does not have permission to modify DAC details, edit information from policies where they are not admins, or add/remove contacts. There is no limit to the number of admins in a DAC, and each admin is responsible for deciding who should have editing privileges. This allows for a more decentralised and democratic approach to managing the DAC. How can I modify the information of a DAC? To modify a DAC, follow the instructions here. Keep in mind that only DAC contact with an admin role can modify the information of a DAC. If your DAC was registered before the lauch of the DAC Portal, and its ID is EGAC0 (not EGAC5), you must use the programmatic submission to modify it. Please, do not hesitate to contact our Helpdesk team if you need help with this! To prevent potential data breaches and ensure adherence to GDPR regulations, it is essential that the European Genome-Phenome Archive (EGA) is informed via the Helpdesk team of any changes to the Data Access Committee (DAC). This should be done in addition to any changes being made on the DAC portal. Data Controllers (as per the definition in the DPA) are also responsible for notifying the previous DAC of any modifications. Without proper notification, changes might not be automatically updated in our system, leading to the risk of incorrect permissions being applied and potential data access issues. Therefore, it is imperative that all Data Controllers follow this protocol to maintain data integrity and security. What’s the link between DAC, policy and dataset? A dataset is linked to one single policy. At the same time, one policy has a one to one relationship with a DAC. In this example, you can see that in this dataset page, we are only showing the information of one DAC (1 dataset - 1 DAC). However, the ratio of objects does not work the same in the other direction. One DAC can own multiple policy objects. And each policy object can be reused in several datasets. Thus, one DAC can manage one or more datasets. In this example, you can see that in this DAC page, we are showing all the datasets that are managed by one DAC (1 DAC - >400 datasets). EGA Data Access Committee Best Practices Which are the EGA DAC best practices? Refer to DAC Best Practices What happens if a DAC member changes institutions? EGA is committed to the protection and ownership of the data stored in our systems. We respect the institution's ownership of the data, and as such, if a DAC member changes institutions, the ownership of the data will not be transferred to the new institution. Therefore, before changing institutions, we request that the DAC contact add a new member who will replace them once they no longer work at the institution. This ensures that the data remains protected and is accessible to authorised personnel at the institution. To prevent potential data breaches and ensure adherence to GDPR regulations, it is essential that the European Genome-Phenome Archive (EGA) is informed via the Helpdesk team of any changes to the Data Access Committee (DAC). This should be done in addition to any changes being made on the DAC portal. Data Controllers (as per the definition in the DPA) are also responsible for notifying the previous DAC of any modifications. Without proper notification, changes might not be automatically updated in our system, leading to the risk of incorrect permissions being applied and potential data access issues. Therefore, it is imperative that all Data Controllers follow this protocol to maintain data integrity and security. What happens if EGA detects an unresponsive DAC? EGA defines an unresponsive DAC as a DAC with one or more contacts who do not respond to data access requests. EGA has procedures in place to identify these types of DACs, escalate the issue, and attempt to reassign the DAC to a responsive contact. This is a crucial step in ensuring that data can be accessed and utilised by researchers. If EGA identifies an unresponsive DAC, the organisation will first try to resolve the issue by escalating it to the appropriate parties. This may involve attempting to reassign the DAC to a more responsive contact. Unfortunately, in situations where we cannot reassign the DAC, the dataset will be withdrawn from the public website and the files will be removed from our system. If an EGA ID is referenced in a publication, the EGA will take extra steps to ensure that the public is made aware of the data's unavailability. I don't want to receive an email notification for pending requests. How can I do that? If you are an EGA DAC with pending requests, you will always receive emails for new data access requests. However, the EGA understands that a request resolution can take some time, for this reason, if you add a comment (make sure you save it by clicking the APPLY button!) we will filter those requests at the time of sending the notification! How can I manage data access requests? What documentation does the DAC need to provide? Each dataset that is submitted to the EGA must be linked to a policy object. The policy is a Data Access Agreement (DAA), which defines the terms and conditions of using the dataset, such as how the data files should be stored once downloaded or details of publication embargoes that should be observed by the approved user. As part of the Data Access Agreement, information regarding the application can be captured to help inform the DAC when making its decision. For example, requestors could be asked to provide a proposed title for their research and a proposal of how the data will be used. By asking for provision of such information the DAC can be assured that the requestor fully understands any consents associated with the data. It is important that accounts created at the EGA, are created solely for those individuals that will be downloading the data from the EGA. As part of the data access request, we strongly encourage you to identify individuals that will need an account at the EGA in order to prevent sharing of login details, which is strictly prohibited under EGA user account policy. Such information can easily be captured in the DAA. NOTICE The data access agreement template below is provided for guidance only and should be adapted as you see fit to suit your own purpose. In the interest of promoting data sharing, we suggest that if an agreement cannot be met around clause 19 in this example that both parties should agree to remain silent, and that the clause should be removed from the agreement. Example DAA How can the DAC provide the DAA? The DAC should provide their own DAA when registering a policy. Data requestors will download this document and should fill it in and send it back to the DAC. Data access decisions should be based on such documentation. The DAA can be downloaded through the request data webpage. Once it has been filled in, the signed copy of the DAA can be uploaded back to the request data webpage and sent to the DAC for review. How can I grant access to the data? Once you receive a data access request, you can login to the DAC Portal. In this portal you will see all your pending requests and will be able to grant or decline access to the requestors. I am a member of the Data Access Committee. Could I approve somebody else to deal with the requests on my behalf? If you want to delegate data access decisions to someone else, make sure that the individual's account is officially registered as a member of the DAC. Remember that a DAC contact with an "admin" role can always add new members to an existing DAC, remove members, and modify contact details through the DAC Portal. Can I automatise the process of managing data access requests? The answer is yes! You can use a programmatic approach using our DAC API! Check out the DAC API specification! Data Breach What should a DAC do if they suspect a breach? If a DAC suspects a data breach of one or more of their datasets, they should immediately contact the EGA Helpdesk team at this link. The DAC must provide the following information when contacting the EGA Helpdesk team: A list of affected datasets An estimated date of the data breach (or interval of dates) A list of unauthorised users who accessed the data (if available). Otherwise, they can provide a list of authorised users for the affected datasets Any observations they would like to raise to the EGA team Once the DAC has contacted the EGA team, we will respond within 48 hours (please allow some leeway during peak times) and activate our data breach protocol. What can I expect from the EGA if they detect a breach? Once the EGA determines that a security incident has occurred, we will notify all DAC members that a data breach has been detected, and take steps to contain the incident. Containment approaches may include: Revoking a data provider's access to the EGA resources, such as by changing passwords. Removing affected EGA datasets from distribution, such as by withdrawing a dataset. Disabling certain functions or services, such as the EGA ingestion pipeline. Shutting down the system or disconnecting it from the network. After the incident has been contained, the EGA will determine whether it is necessary to eradicate components related to the incident. Finally, the EGA will enable recovery of the service to normal operation and confirm that all services are functioning normally.

  Documentation access/data-access-committee/what-is-dac

• NHLBI GO-ESP: Family Studies (Hematological Cancers)

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. Two major goals in the study of human malignancies are (i) to understand the genetic basis that underlies the predisposition of certain individuals to develop cancer and (ii) to identify the full spectrum of acquired mutations that occur in human cancers. There has been some progress in both of these areas with respect to hematologic malignancies but much remains to be discovered. As a result of recent advantages in sequencing technologies it is now feasible to sequence multiple individual whole exomes at reasonable cost. Such technologies provide a unique opportunity to transform our understanding of the biological basis of human cancer and to identify inherited genetic variants that predispose individuals to the development of hematologic malignancies. Myeloproliferative neoplasms (MPN), myelodysplastic syndrome (MDS) and acute leukemia are clonal disorders of hematopoieis. Our study involves performing whole exome sequencing of individuals with these disorders for the purpose of identifying (i) novel inherited genetic variants associated with the risk of developing of MPN/MDS/acute leukemia and (ii) novel acquired mutations associated with the development of MPN/MDS/acute leukemia.

  Study phs000632

• Genetic_Heterogeneity_of_the_familial_gastric_neuroendocrine_tumors

  Gastric neuroendocrine tumors (gNETs) occur with an estimated frequency of 2 per 100,000 in the general population. Type I gastric neuroendocrine tumors (NETs) represent the 75% of gNTEs and arise from gastric enterochromaffin-like (ECL) cells. They have late age of onset and usually benigh course. Classically, hypergastrinemia in patients who have autoimmune atrophic gastritis, causes hyperplasia of gastric ECL cells that progresses into type I gastric NETs and parietal cell (PC) destruction. The genetic bases in families with this disease are unknown. We performed an exome sequencing study of an atypical aggressive familial gNETs case (with early age onset, nodal infiltrations and gastric adenocarcinomas) that followed a recessive model. We identified a deleterious mutation in homozygosis in the ATP4A gene, which encodes the proton pump responsible for acid secretion by gastric parietal cells. This mutation lead to achlorhydria first, and hypergastrinemia and gNET developing as consequence (Calvete et al. 2014). Recently, two more families with gNETs, classical clinical traits and recessive model have been studies by WES but we didn't find any mutation in the ATP4a gene. However, putative mutations affecting genes that contribute to the development and the integrity of PC have been found suggesting that genetic alterations associated to this disorder target to a unique cell type (parietal cells). In order to cinfirm this hypothesis, it is necessary the search for new genes implicated in the gNETs, more familial cases are needed to be studied. We have identified four more new familial gNETs cases. Here, we propose their study by WES. The first family is formed by thress siblings with gNETs. The other families include two siblings with gNETs. 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 EGAS00001002273

• Successful immune checkpoint blockade in a patient with advanced stage microsatellite unstable biliary tract cancer (H021)

  Cancers acquire multiple somatic mutations that can lead to the generation of immunogenic mutation-induced neoantigens. These neoantigens can be recognized by the host’s immune system. However, continuous stimulation of immune cells against tumor antigens can lead to immune cell exhaustion, which allows uncontrolled outgrowth of tumor cells. Recently, immune checkpoint inhibitors have emerged as a novel approach to overcome immune cell exhaustion and re-activate anti-tumor immune responses. In particular, antibodies blocking the exhaustion-mediating programmed death receptor (PD-1)/PD-L1 pathway have shown clinical efficacy. The effects were particularly pronounced in tumors with DNA mismatch repair deficiency and a high mutational load, which typically occur in the colon and endometrium. Here, we report on a 24-year old woman diagnosed with extrahepatic cholangiocarcinoma who showed strong and durable response to the immune checkpoint inhibitor pembrolizumab, although treatment was initiated at an advanced stage of disease. The patient’s tumor displayed DNA mismatch repair deficiency and microsatellite instability (MSI), but lacked other features commonly discussed as predictors of response towards checkpoint blockade, such as PD-L1 expression or dense infiltration with cytotoxic T cells. Notably, high levels of HLA class I and II antigen expression were detected in the tumor, suggesting a potential causal relation between functionality of the tumor’s antigen presentation machinery and the success of immune checkpoint blockade. We suggest determining MSI status in combination with HLA class I and II antigen expression in tumors potentially eligible for immune checkpoint blockade even in the absence of conventional markers predictive for anti-PD-1/PD-L1 therapy and in entities not commonly linked to MSI phenotype. Further studies are required to determine the value of these markers for predicting the success of immune checkpoint blockade. (H021)

  Study EGAS00001002441