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• Add Health: Longitudinal Study of a Nationally Representative Sample of Adolescents in Grades 7-12 in the United States during the 1994-95 School Year, Followed into Adulthood with Five Interviews/Surveys in 1995, 1996, 2001-02, 2008, and 2016-18

  The National Longitudinal Study of Adolescent to Adult Health [Add Health] is an ongoing longitudinal study of a nationally representative U.S. cohort of more than 20,000 adolescents in grades 7-12 (aged 12-19 years) in 1994 followed into adulthood with five interviews/surveys in 1995, 1996, 2001-02, 2008, and 2016-18. Add Health was designed to understand how social environments and behaviors in adolescence are linked to health and achievement outcomes in young adulthood. Add Health contains unprecedented environmental, behavioral, psychosocial, biological, and genetic data from early adolescence and into adulthood on a large, nationally representative cohort with unprecedented racial, ethnic, socioeconomic, and geographic diversity. Add Health has a large, multidisciplinary user base of over 50,000 researchers around the world who have published over 3,400 research articles. Add Health is housed at the Carolina Population Center of the University of North Carolina at Chapel Hill. Add Health datasets are distributed according to a tiered data disclosure plan designed to protect the data from the risk of direct and indirect disclosure of respondent identity. Add Health's large sample size, population diversity and rich longitudinal database of psychosocial, physical, and contextual data will permit investigation of an exceptionally broad range of phenotypes with known genetic variation. Prospective longitudinal measures are available to document change over time in each of these phenotypes, as well as change in the social environment and life experiences, making the Add Health sample ideal for understanding genetic linkages with health and behavior across the life course. The original design of Add Health included important features for understanding biological processes in health and developmental trajectories across the life course of young people, including an embedded genetic sample with more than 3,000 pairs of adolescents with varying biological resemblance (e.g., twins, full sibs, half sibs, and adolescents who grew up in the same household but have no biological relationship), testing of saliva and urine for sexually transmitted infections and HIV, and biomarkers of cardiovascular health, metabolic processes, immune function, renal function, and inflammation. Add Health therefore has critical objective indicators of health status and disease markers in young adulthood, well before chronic illness or its complications emerge in later adulthood. Because DNA has been collected on the full sample at Wave IV, it is possible to link genetic profiles with social, behavioral, and biological measures over time from adolescence into adulthood. Add Health sampled the multiple environments in which young people live their lives, including the family, peers, school, neighborhood, community, and relationship dyads, and provides independent and direct measurement of these environments over time. Add Health contains extensive longitudinal information on health-related behavior, including life histories of physical activity, involvement in risk behavior, substance use, sexual behavior, civic engagement, education, and multiple indicators of health status based on self-report (e.g., general health, chronic illness), direct measurement (e.g., overweight status and obesity), and biomarkers. No other data resource with this expanse of genotype and phenotype data on a large nationally representative longitudinal sample with race, ethnic, socioeconomic, and geographic diversity exists. A complete reference guide on study design and accomplishments can be found on the Add Health website: https://cdr.lib.unc.edu/concern/articles/6t053j27s.

  Study phs001367

• Privacy Notice for the Account User

  Privacy Notice for EGA User Account This Privacy Notice explains what personal data is collected by the specific service you are requesting, for what purposes, how it is processed, and how we keep it secure. Note that this service collects personal data directly provided by the user, and also collects personal data from users that is provided by other organisations. 1. Who controls your personal data and how to contact us? European Genome- Phenome Archive - EGA offers a service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects, jointly managed by European Molecular Biology Laboratory – European Bioinformatics Institute (EMBL-EBI) and Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG). EMBL-EBI and CRG represent joint Data Controllers’ of processing of your personal data. They and their Data protection officers may be contacted for data protection queries and for exercising your rights under Section 8. You may contact EMBL-EBI, represented by dr. Thomas Keane, by: email at: tk2@ebi.ac.uk or post at EMBL-EBI, Wellcome Genome Campus, CB10 1SD Hinxton, Cambridgeshire, UK. EMBL’s Data Protection Officer may be contacted by: telephone at +49 6221 387-8590, email at dpo@embl.org, or post at EMBL Heidelberg, Data protection officer, Meyerhofstraße 1, 69117 Heidelberg, Germany. You may contact CRG, whose EGA team is represented by dr. Jordi Rambla de Argila, by: email at jordi.rambla@crg.eu, or post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), Dr.Aiguader 88, PRBB Building, 08003 Barcelona, Spain. CRG Data protection officer may be contacted by: email at dpo@crg.eu post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), C/ Dr. Aiguader, 88, PRBB Building, 08003 Barcelona, Spain. 2. Which is the lawful basis for processing personal data? We process your personal data on the grounds of important public interest. For monitoring your activities on the website, we process your personal data on the grounds of important public interest. Such legal basis is found in Article 5(1)(a) of EMBL Internal Policy No 68 on General Data Protection (hereinafter IP 68), which is equivalent to Article 6 (1)(e) of the EU General Data Protection Regulation (hereinafter GDPR) and upon which personal data are processed for the achievement of the aims laid down in 1973 agreement establishing EMBL, such as the promotion of the cooperation in the fundamental research, in the development of advanced instrumentation and in advanced teaching in molecular biology and dissemination of information. 3. What personal data is collected from users of the service? How do we use this personal data? We collect the following personal data from you: Name Email address Title/Position Organisation Organisational affiliation Username and password (to authenticate access to the system) IP Address (for anonymous usage statistics) We process your personal data: to provide you with the authenticated access to the EGA service (opening and managing submission and distribution account), to publicly publish some aggregate data to facilitate scientific research (e.g. number of accounts, geographic distribution), to better understand the needs of the users and to guide future improvements of the service, to create anonymous usage statistics. If you do not provide us with your personal data we will not be able to open the user account and offer you our services or we will only provide you a subset of functionalities available within the service. 4. Who will have access to your personal data? The personal data will be disclosed to: Authorised staff in the data controller’s institutions acting on data controller`s behalf and instructions (for all user account data), Requested dataset Data access committee – DAC will have access to the name, email, organization, affiliation, title/position of the distribution user account, using it for their own purpose of granting access to their datasets. 5. Will your personal data be transferred to third countries (i.e. countries not part of EU/EEA) and/or international organisations? Distribution user account data are in the process of granting access disclosed to dataset(s) DAC, which might be a recipient in countries outside of the European Economic Area. Insofar as the second joint controller may be subject to GDPR, data transfer to and from the first joint controller (EMBL-EBI) is necessary for important reasons of public interest embedded in the aims of the EMBL and justified in the Article 9(4) of IP 68 (equivalent to Article 49(1)(d) of GDPR) read in conjunction with EMBL`s 1973 establishing agreement and Article 179(2) of the Treaty on the Functioning of the European Union. 6. How long do we keep your personal data? All data are stored for as long as you have the account open. Thereafter the storage is prolonged for as long as our service is live, even if you stop using our services. This prolongation is necessary for further scientific research, to ensure legal compliance and security and to facilitate internal and external audits it they arise. By contrast, the log files for the data categories related to anonymous usage statistics (raw web service logs) are processed only for 30 days and thereafter erased. 7. The joint Data Controllers provide these rights regarding your personal data You have the right to: Not be subject to decisions based solely on an automated processing of data (i.e. without human intervention) without you having your views taken into consideration. Request at reasonable intervals and without excessive delay or expense, information about the personal data processed about you. Under your request we will inform you in writing about, for example, the origin of the personal data or the preservation period. Request information to understand data processing activities when the results of these activities are applied to you. It must be clarified that rights under points 4 and 5 are only available whenever you need support whilst using our website. For other processing based on the grounds of important public interest you cannot exercise your rights to object, rectify or erase your personal data according to the Article 13(2)(a)(b) of IP 68 (equivalent to Article 17(3)(b)(d) and Article 21(6) of the GDPR). 8. Supervisory authority If you wish to complain against the processing of your personal data, you may do so by post at: EMBL Heidelberg, Data Protection Committee, Meyerhofstraße 1, 69117 Heidelberg, Germany, or Autoritat Catalana de Protecció de Dades (Catalan Data Protection Authority), C/Rosselló 214, Esc A, 1r 1a, Barcelona 08008, Spain. Published at: February 6, 2019

  Documentation data-protection/privacy-notice/ega-user-account

• Implementation of the GDPR

  Data Protection 1 About the EGA The European Genome-phenome Archive (EGA) was formally 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. In late 2012, with the signing of a memorandum of understanding (and subsequent formal agreement in 2016) between EMBL-EBI and the Centre for Genomic Regulation (CRG), the EGA formally became a joint project of the two institutes. The two institutes work together to support the EGA services, including supporting submissions, web site, strategic leadership, and data infrastructure developments. 2 EMBL-EBI & GDPR The EGA is co-managed by EMBL-EBI and CRG. EMBL-EBI is an international organisation established by treaty and has certain privileges and immunities (e.g. exemptions from the application of national law) and also may self-regulate its activities (e.g. establish its own institutional legal framework) within the framework of its founding act of 1973. The General Data Protection Regulation (GDPR) is a European Union (EU) regulation that legislates how organisations can share and process personal data of EU citizens. EMBL places great value in maintaining collaboration with researchers who are subject to GDPR. For that reason, it is of utmost importance for EMBL to handle data received from those collaborators in a secure and responsible manner. Mindful of its public mandate and the sensitivity of the data it handles, EMBL has always ensured a high level of data protection in its activities. Since the introduction of GDPR in May 2018, EMBL has established its internal policy on General Data Protection (IP68), exercising its right to self-regulate its operations,., IP 68 establishes a robust personal data protection framework that provides for data protection principles, enforceable data subject rights and oversight and redress mechanisms offering a level of protection comparable with GDPR. 3 CRG & GDPR The Centre for Genomic Regulation (CRG) is an international biomedical research institute of excellence, created in July 2000 and mainly participated by the Catalan Government. It is a non-profit foundation and its mission is to discover and advance knowledge for the benefit of society, public health and economic prosperity. The CRG is a CERCA center. CERCA is the collective organisation for all research centres of excellence in Catalonia. CERCA ensures these centres develop successfully by promoting synergies and strategic cooperation improving their visibility and the impact of their research and promoting the dialogue amongst both public and private stakeholders. As a legal entity based in Spain and operating within the EU, the CRG ensures the compliance with the GDPR and the legal regulations on personal data protection applicable at the national level, as well as any other legislation that may replace, modify or supplement the above-mentioned in terms of personal data protection. 4 EGA & GDPR EGA GDPR Schema 4.1 Genetic and phenotypic data Within GDPR, there are two main actors: data controllers and data processors. Data controllers are persons or entities which determine the purposes and means that the personal data may be processed, e.g. companies, researchers, or universities. For EGA, the data controller is ultimately the data producer and the submitter(s) who submit the data to EGA. The data controller also creates a Data Access Committee (DAC) who will decide on data access permissions at EGA. Data processors are the persons or entities which process the data on behalf of a data controller. With regard to GDPR, EGA is a data processor as it processes data as instructed by the data controller. GDPR applies to any organisation which accesses personal data from an individual within the EU. Under GDPR, personal data is defined as any data that is identifiable, including names and email addresses as well as health-related and genetic data. EGA does not accept personally identifiable data except genetic and phenotypic data, so all other data submitted to EGA, such as names and addresses, must be pseudonymised. GDPR requires that data controllers implement data protection principles, such as data minimisation, to minimise the risk of data leakage, and protect the rights of the data subjects. As a data processor, EGA has a set of security policies that are followed to minimise the risk of unauthorised data access or data loss. In its role as a data processor, EGA requires all submitters to sign a Data Processing Agreement (DPA) when the submission account is first created. This agreement is only required to be signed once per submitter, and will remain valid for future submissions to EGA. 4.2 Other personal data The EGA also collects personal data as part of our interactions with submitters, data access committees, and researchers accessing data distributed by EGA. The below privacy notices explain what personal data is collected by the specific service you are requesting, for what purposes, how it is processed, and how we keep it secure. Privacy Notices for EGA Title Version Last Updated EGA Data Access Committee Account Privacy Notice for EGA Data Access Committee Account 1.0 February 6, 2019 EGA User Account Privacy Notice for EGA User Account 1.0 February 6, 2019 EGA Helpdesk Service Privacy Notice for EGA Helpdesk Service 1.0 February 6, 2019 EGA Website Service Privacy Notice for EGA Website Service 1.0 February 6, 2019 Documentation Title Version Description EGA Security Overview Security Document 1.1 The EGA Security Document provides an overview of EGA’s practices in ensuring the security of data stored at EGA. EGA Data Processing Agreement Data Processing Agreement 1.5 The Data Processing Agreement must be completed and returned as part of the submission process. Please note that this document is non-negotiable. Authorised Submitters Authorised Submitters Formulary 1.0 The Authorised Submitters Form must be completed and returned as part of the submission process. Please list all those that should have access to the submission account in order to submit to the EGA should be detailed here. Dispute Resolution Any controversy or claim arising out of, or relating to, the DPA (including the enforceability or breach thereof, any question regarding its existence, validity or termination) or relating to the EGA Service shall be resolved using the internal dispute resolution mechanisms of EGA including those related to Data Protection. The EGA’s internal dispute resolution mechanism has the following procedure: EGA OPERATIONAL PHASE: Meetings between EGA staff and the Data Controller.LEGAL MANAGEMENT PHASE: Meetings between legal teams of EMBL, CRG and the Data Controller. DIRECTION MANAGEMENT PHASE: Negotiation between the legal representatives of EMBL, the CRG and the Data Controller. If the internal dispute resolution mechanism doesn’t resolve the controversy or claim the next phase is:ARBITRATION PHASE: Resolution by arbitration under the WIPO Expedited Arbitration Rules (“Rules”).

  Documentation about/privacy-notice

• University of Illinois at Chicago (UIC) Autism Centers of Excellence (ACE) Exome Sequencing Analysis

  Autism spectrum disorder (ASD) is highly heritable with recent sibling recurrence risk estimates of 19% overall and 26% in males. The heritable phenotype of hyperserotonemia, or elevated levels of platelet serotonin (5HT), in ~35% of people with ASD is a well-established biomarker. The efficacy of drugs like risperidone and potent serotonin transporter inhibitors at treating behaviors related to Insistence on Sameness, along with evidence of the contribution of hyperserotonemia to autism susceptibility collectively support the hypothesis that dysfunction in the 5HT system is a significant etiological target for investigation of the genetic component to autism. ASD genetic architecture is complex; common variants of large effect do not contribute substantially to overall ASD risk, but there are clearly common variants with small effects and rare genetic/genomic variation of larger effect among ASD genetic risk factors. The NIH ARRA Autism Sequencing Consortium, including Dr. Sutcliffe and Dr. Cook among others, has initiated exome sequencing studies to identify more of the rare variants contributing to ASD. Data from our group and others reveal numerous rare de novo and inherited sequence mutations, and the number of de novo and other functional mutations that are found to affect molecules encoding 5HT signaling and its regulation further reinforces our hypothesis that regulation of serotonin levels is important in autism genetic susceptibility. Integrin receptor signaling pathways were prominently featured among identified de novo mutations, thus defining a set of interrelated gene networks that control 5HT signaling. We propose to extend our findings to date by conducting exome sequencing on ACE subjects, for whom we also have 5HT biochemical data, to identify rare variants (including CNVs) in 5HT-related gene networks. In total we propose to have exome sequencing completed on 523 samples. The purpose of the proposed research is two-fold: 1) we will conduct more extensive investigations to determine the support for the hypothesis that genetic variation at genes regulating platelet serotonin levels affect susceptibility to ASD and 2) we will combine the exome sequence data from these studies with sequence data for autism being accumulated in a variety of other research projects to further the goal of identifying and characterizing the genetic component to ASD.

  Study phs000712

• A Genome-Wide Association Study in Patients Experiencing Breast Events While Receiving Adjuvant Aromatase Inhibitors for Early Breast Cancer on NCIC CTG Trial MA.27

  Source of patients:The source of the patients for this genome-wide case-control study was MA.27, which was conducted as a multi-cooperative group effort under the auspices of the NCI Breast Cancer Intergroup of North America. The NCIC Clinical Trials Group (CTG) serves as the coordinating group, with participation by the NCI-sponsored North Central Cancer Treatment Group, Eastern Cooperative Oncology Group (ECOG), Southwest Oncology Group, and Cancer and Leukemia Group B (CALGB). MA.27 involved postmenopausal women with histologically confirmed and completely resected invasive breast cancer with surgical margins clear of invasive carcinoma in the following TMN categories (AJCC Version 6): pT1, pT2, pT3; pNx, pN0, pN1, pN2, pN3 (only when the sole basis is presence of 10 or more involved axillary nodes); MO. The primary tumor must have been estrogen receptor (ER) and/or progesterone receptor positive. Patients were stratified by lymph node status at diagnosis, prior adjuvant chemotherapy, and trastuzumab use and were randomized to 5 years of adjuvant therapy with anastrozole or exemestane. The trial was activated on May 26, 2003, and reached its accrual objectives on July 31, 2008, after the randomization of 6827 North American patients, with the majority (79%) providing DNA and consent for genetic testing. Non-North American patients were also entered by the International Breast Cancer Study Group but they did not contribute DNA. From 2003 to December 21, 2004, patients also underwent a second randomization to celecoxib 400 mg twice daily or placebo but, after the entry of 1,622 patients, this treatment was discontinued because of reports of increased cardiovascular risk associated with celecoxib. The final results of this study have been published, see Goss et al., 2013 (23358971). The patients in this analysis came from three cohorts: Cohort 1 consisted of 870 patients genotyped on the Illumina Human610-Quad BeadChip studied in a GWAS with the phenotype of musculoskeletal adverse event, see Ingle et al., 2010 (20876420), Cohort 2 consisted of 882 patients genotyped on the Illumina OmniExpress platform studied in a GWAS with the phenotype of fragility fractures, see Liu et al., 2014 (25148458), and the remaining 2913 patients were genotyped with the Illumina OmniExpressExome platform.

  Study phs001043

• Title: Divergent levels of CD112 and INKA1 define a distinct subset of human long-term hematopoietic stem cells

  The data provided here was critical in establishing that human long-term hematopoietic stem cells (LT-HSC), previously described as the most primitive HSC population, is actually composed of distinct subsets that can be prospectively isolated. Via mechanistic studies centering around the Rho-GTPase effector kinase PAK4 and its inhibitor INKA1, we identified the immune checkpoint ligand CD112 as a marker for hematopoietic stem and progenitor cells, that is highest expressed on LT-HSC. More importantly, CD112 can be used to stratify functionally distinct subsets within LT-HSC: In response to regeneration-mediated stress, the CD112low subset exhibits a transient restraint (termed latency) before contributing to hematopoietic reconstitution, while the CD112high subset is primed to respond rapidly. High resolution RNA-seq of the CD112 surface expression spectrum within rare LT-HSC subsets (human umbilical cord blood) demonstrated that more genes are differentially upregulated in the deeper quiescent and less metabolic active subset. Genes enriched in this subset centre around cell adhesion and Rho-GTPase signaling. This is in agreement with the scRNAseq data from human G-CSF mobilized peripheral blood (mPB) generated here that was used as an model of in vivo activation/priming revealing via RNA-velocity and pseudo-time analysis that INKA1high versus PAK4high, CDK6high and CD112high enrichment are either detected early or late in diffusion pseudotime indicative of quiescent versus primed cell status, respectively. RNAseq following INKA1 overexpression in LT-HSC and ST-HSC revealed by GSEA an overall stemness preserving phenotype and particularly in LT-HSC, but not in short-term HSC (ST-HSC), suppression of transcriptional programs linked to activation. Collectively, our data decipher the molecular intricacies underlying HSC heterogeneity and self-renewal regulation and point to latency as an orchestrated physiological response that integrates quiescence control with HSC fate choices to preserve a stem cell reservoir.

  Dataset EGAD00001006541

• National Cancer Institute (NCI) TARGET: Therapeutically Applicable Research to Generate Effective Treatments

  The Therapeutically Applicable Research to Generate Effective Treatments (TARGET) Initiative seeks to accelerate research in novel marker and drug development, along with understanding the molecular basis of pediatric malignancy, through identification of genomic changes associated with the following childhood cancers: Acute Lymphoblastic Leukemia (ALL) - A fast-growing type of blood cancer in which too many immature white blood cells are found in the blood and bone marrow. Acute Myeloid Leukemia (AML), including AML Induction Failure cases (AML-IF) - Another type of blood cancer marked by too many myeloblasts, an alternate type of immature white blood cell, are found in the blood and bone marrow. Upon diagnosis, AML patients without high-risk genetic markers undergo standard chemotherapy regimen, called the primary induction phase, to eliminate most cancer cells and induce a remission state. Clear Cell Sarcoma of the Kidney (CCSK) - A rare type of kidney cancer, in which the inside of the cells looks clear when viewed under a microscope. Clear cell sarcoma can spread from the kidney to other organs, most commonly the bone, but also including the lungs, brain, and soft tissues of the body. Neuroblastoma (NBL) - Cancer of cells of the sympathetic nervous system. Cancer Model Systems (MDLS), including PPTP - MDLS includes acute leukemia cell lines and xenografts with matched primary and/or relapsed tumor information, NBL cell lines and xenografts with matched controls, kidney tumor cell lines, normal brain tissues, and embryonic stem cell lines that were sequenced for some TARGET disease projects. Osteosarcoma (OS) - A cancer of the bone that primarily affects children and adolescents. Rhabdoid Tumor (RT) - A rare, fast-growing cancer that usually forms in the kidney or central nervous system (the brain and spinal cord) but can also form in soft tissues in other areas of the body. Rhabdoid tumors tend to spread quickly, are hard to treat, and have a poor prognosis. Wilms' Tumor (WT) - A cancer of cells in the kidney that can spread to the liver, lung and lymph nodes. More information can be found about each TARGET subproject by following the links on the top of this page. Together these cancers account for the majority of the more than 10,000 childhood cancer cases diagnosed in the United States each year. TARGET has employed a set of advanced and complementary genome analysis technologies, including large scale 2nd and 3rd generation genome sequencing, to strategically characterize alterations in both gene expression and in genomic structure (such as deletions and amplification) that are involved in childhood cancers. The goal of this coordinated effort has been to create a comprehensive genomic and transcriptomic profile of each cancer. Integrated analysis of the TARGET data has identified those genes that are either altered in their expression level or mapped to the chromosome regions of deletion/amplification/translocation, as these genes represent strong candidates for therapeutic targeting. To learn more about the TARGET project, which is now completed, visit the website at https://www.cancer.gov/ccg/research/genome-sequencing/target. TARGET data is accessible at the NCI's Genomic Data Commons (GDC) via the GDC's Data Portal and from each of the TARGET Publication Pages at the GDC (Please see the "Supplemental Links" section of any TARGET publication's "Publication Information and Associated Data Files page" at the GDC.). Available datasets include raw sequencing data, datasets generated by the original TARGET research teams (fully annotated clinical information and higher-level/analyzed molecular characterization data - gene expression, copy number variation, epigenetics, targeted sequencing), as well as higher level data generated by the GDC. Please see the TARGET Use and Publication Guidelines for updated details on the sharing of any TARGET substudy data, including how to cite TARGET.

  Study phs000218

• The UCSD / O'Connor "TSP" (Twin/Sibling/Pedigree) Resource in Hypertension

  Study Design: The UCSD / O'Connor "TSP" (Twin/Sibling/Pedigree) Resource in Hypertension contains N=797 participants. At the time of recruitment individuals ranged from 15-84 years of age and had varying ethnic backgrounds (Whites, African-Americans and Hispanics). The cohort was developed to study the genetic basis of autonomic dysfunction in human essential hypertension (reviewed in Zhang et al. Curr Hypertens Rep. 2011 13: 36-45. PMID: 21104344) and contains cross-sectionally collected phenotypes related to blood pressure regulation.  Phenotypes: Phenotype data specifically focuses on the sympathetic branch of the autonomic system, which is a key regulator of blood pressure. Data includes circulating concentrations of the secretory "quantum" (catecholamines, neuropeptides, chromogranins) which influence vascular responses to sympatho-adrenal activation resulting in blood pressure. Other measures on the twins and a subset of family members include a standard urine panel with absolute concentrations of potassium, sodium, uric acid, phosphorous; DynaPulse acquired heart rate and blood pressure measures including systolic and diastolic blood pressure, mean arterial pressure, heart rate, Left Ventricular (LV) ejection time, LV contractility, cardiac output, stroke volume data including; and absolute concentrations of plasma aldosterone, endothelin, leptin, and insulin. Phenotype data is included for the 697 individuals sequenced here and 100 family members.  Whole Genome Sequence Data Generation: Whole genome sequencing (20X coverage) was conducted on plasma-derived DNA. The WGS was generated using the Illumina HiSeq X Ten sequencing platform with variants called by Human Longevity, Inc (HLI; Ref 1). Preparation of sample libraries was conducted by mechanical shearing of gDNA (100-800 bp), isolation of DNA fragments 300-500bp in size, followed by library PCR amplification employing high-fidelity, low-bias PCR to amplify library fragments consisting of appropriate adapter sequences on both ends. BAM files were created by alignment of sequence reads to the reference genome (GRCh38) using iSAAC-01.14.02.06 (Python2.7). Note: The user may want to realign the sequence data and recall variants. In total, the WGS dataset contains 30 monozygotic twin pairs represented by one member of the twin pair, 133 monozygotic twin pairs with both individuals sequenced, 7 dizygotic twin pairs represented by one member of the twin pair, 67 dizygotic twin pairs with both individuals sequenced, 8 twin pairs with undetermined zygosity (both individuals sequenced) and 1 triplet with mother (all individuals sequenced). The dataset also contains sequences of 260 family members of twins including their mother, father, non-twin sibling, and offspring. Table 1 describes the composition of families ("sibling" refers to a non-twin sibling in the cohort). Note: We suggest users check gender and family relatedness. Table 1: Description of the families with sequence data                                                                                                               Units with:Twin PairsTwin (no pairs)No twinSibshipsMother and Father511Mother only1222Father only113One or more siblings22133Mother and siblings132Father and siblings(s)211Offspring of twins11Non twin siblings2Sib with unknown relative1Only one member of8The UCSD/O'Connor "TSP" (Twin/Sibling/Pedigree) Resource in Hypertension is now being managed at the UCSD School of Medicine's Institute for Genomic Medicine (IGM). The TSP Resource has collected a wide range of information (phenotypic, genotypic, demographic, metabolomic) and reagents (blood, plasma, urine, DNA, human induced pluripotent stem cells). For additional information about the resource, including other data types available as well as references and links to data from studies with previous collaborators, please go to the resource website at IGM [http://igm.ucsd.edu/research/twins-resource.shtml] or contact Dr. Brinda Rana at UCSD [bkrana@ucsd.edu]. 

  Study phs002230

• How to use EGA Webin?

  EGA Webin EGA Webin serves as a platform for registering metadata for array based submissions, large scale sequence submission as well as for legacy EGA submission accounts (ega-box-XXXX). For large scale submitters of sequence data you have also the option to submit metadata via XMLS programmatic submission, while new submitters are advised to utilise the Submitter Portal for their submissions. You can request a legacy EGA submission account (ega-box-XXXX) by populating this form. Please, allow two business days for our Helpdesk team to contact you after populating this form. WEBIN actions: Register metadata for a sequence submission Register study, samples, experiments, runs, DAC, policy and dataset/s after file upload. Register components for your array-based metadata submission Register study, samples, DAC or policy before uploading files. Edit existing submission metadata Change or update previously submitted metadata. Register metadata for a sequence submission Ensure that all sequence files have been encrypted before uploading them to your submission account using the EgaCryptor. Go to the EGA Webin and log in using your submission account name (ega-box-XXX) and password. Register components of your metadata submission Study Samples Data Access Committee (DAC) Data access policy Dataset For array-base submissions: Study, Samples, Data Access Committee (DAC) and Data access policy may all be registered BEFORE file upload and dataset registration through the array-base template. Register your Study Go to the “Studies (Projects)” box Click on “Register Study” and fill in the information related to your study. Click on “Submit”, this will save the information and generate an EGA study ID. To use the study accession number in a publication, the study has to be previously released on the EGA website, we suggest the following format: "Sequence data has been deposited at the European Genome-phenome Archive (EGA), which is hosted by the EBI and the CRG, under accession number EGASXXXXXXXXXXX.Further information about EGA can be found on https://ega-archive.org and “The European Genome-phenome Archive in 202 "(10.1093/nar/gkab1059)" Register your Samples Go to the “Samples” box Click on “Register Samples” Select “Download spreadsheet to register samples” and customise your template, there is a default EGA template (EGA default checklist) but more attributes can be added if required. For the EGA default checklist, there are mandatory,recommended and optional attributes. As well custom fields which can be added if required. Mandatory attributes Field Name Description tax_id Taxonomy ID of the organism as in the NCBI Taxonomy database. Entries in the NCBI Taxonomy database have integer taxon IDs. See our tips for sample taxonomy here scientific_name Scientific name of the organism as in the NCBI Taxonomy database. Scientific names typically follow the binomial nomenclature. For example, the scientific name for humans is Homo sapiens. sample_alias Unique name of the sample. If not selected system will auto generate an unique alias sample_title Title of the sample sample_description Description of the sample phenotype *** Where possible, please use the Experimental Factor Ontology (EFO) to describe your phenotypes. Recommended attributes Field Name Description subject_id Identifier for the subject where the sample has been derived from gender * Sex Optional attributes Field Name Description sex sex of the organism from which the sample was obtained disease_site Affected organ sample type Affected organ donor_id ** Identifier of the donor where the sample has been derived from *Gender should be described as 'male', 'female' or 'unknown'. If 'unknown' due to a known sex chromosome aneuploidy, please create a user defined attribute called 'Sex chromosome karyotype' and add the appropriate value, for example, 'XXY'. **Donor id (Subject id) should be a de-identified subject handle. If unknown, please add 'unknown' to the field. ***Phenotypes should, where possible, be an Experimental Factor Ontology accession. If a term cannot be found to describe your phenotype please use free text. All sample phenotypes considered important for further analysis of the data should be provided (for example, tumour type), additional phenotype attributes can be created by defining your own attributes; use the notion 'phenotype2', 'phenotype3', etc. After you have customised the fields for the sample submission, download the template and fill in the information. Example of the sample template: Finally upload the sample template to get the EGA accession IDs for the samples. Register your Data Access Committee (DAC) Further information on the role of your DAC Go to the “Data Access” box Click on “Register Dacs” Input the information about the DAC and register at least one main DAC contact. Register your Data Access Policy Your Data Access Policy provides the terms and conditions of data use, this is also referred to as the Data Access Agreement (DAA). Completion of a DAA by the applicant/s should form part of the application process to the Data Access Committee (DAC). Go to the “Data Access” box Click on “Register Policies” Select the DAC to which this policy will be linked to and fill in the policy information. Submitting your Runs and Analyses This section is only for sequence data submission, for array-based submission it can be skipped. Please refer to our Submitting array based metadata Runs Registration Go to the “Raw Reads (Experiments and Runs)” box Click on “Submit Reads” Select “Download spreadsheet template for Read submission” Select the template corresponding to your submission type For the templates you have the option to customise the optional fields. To check their description click on “Show Description “ Download the template and fill in the required information. Example of the runs template: We recommend that Fastq, BAM, and CRAM read files are submitted using Webin-CLI When using this interface instead of Webin-CLI, raw sequences must be uploaded in one of the supported data formats before they can be submitted. The files can be uploaded using FTP or Aspera. The study and the sequenced samples must be pre-registered before the raw reads are submitted. Please note that each individual study and sample should be registered only once. You will be asked to provide information about the sequencing libraries and instruments. Submitting your Dataset This section is only for sequence data submissions, for array based submissions it can be skipped. Please refer to our Submitting array based metadata The dataset describes the data files, defined by the run (EGARXXXXXXXXXXX) and analysis (EGAZXXXXXXXXXXX) accessions that make up the dataset and links the collection of data files to a specified Data Access Committee and Data Access Policy. As a result, you must have registered your Reads and experiments, Data Access Committee (DAC) and Data access policy before submitting your Dataset. Please consider the number of datasets that your submission consists of, for example, a case control study is likely to consist of at least two datasets. In addition, we suggest that multiple datasets should be described for studies using the same samples but different sequence technologies. Please contact EGA Helpdesk for further assistance. Go to the “Data Access” box Click on “Register Dataset” Select the Data Access Committee (DAC) and Data access policy Register your dataset After submitting your dataset you should contact the EGA Helpdesk to provide a release date for your dataset. Datasets are automatically held (i.e. not released) unless they are affiliated to a study that has already been released. Edit/update existing submission metadata Go to the “Report” section of the object you would like to edit. Locate the object and click on the arrow under action. An option menu will be displayed. Objects can be edited through their XML or with the WEBIN menu. After an object has been edited, changes would be available on the website until the submission is released again. Please contact the EGA Helpdesk if you require further assistance.

  Documentation submission/metadata/submission/EGA_webin

• Heart Failure Network: Diuretic Optimization Strategies Evaluation in Acute Heart Failure (HFN DOSE-BioLINCC)

  ObjectivesThe DOSE study sought to evaluate the most effective dosing (high vs. low) and administration (continuous infusion vs. intermittent boluses) combination of the diuretic Furosemide in the treatment of patients with acute decompensated heart failure.BackgroundAcute decompensated heart failure is the most common cause of hospital admissions among patients older than 65 years of age and is responsible for more than 1 million hospitalizations annually in the United States. Intravenous loop diuretics are an essential component of current treatment and are administered to approximately 90% of patients who are hospitalized with heart failure. Despite decades of clinical experience with these agents, prospective data to guide the use of loop diuretics are sparse, and current guidelines are based primarily on expert opinion. As a result, clinical practice varies widely with regard to both the mode of administration and the dosing.SubjectsA total of 308 patients were enrolled between March 2008 and November 2009 at 26 clinical sites in the United States and Canada. DesignThe DOSE study was a prospective, randomized, double-blind, controlled trial with a 2-by-2 factorial design. Patients were randomly assigned to either a low-dose strategy (total intravenous furosemide dose equal to their total daily oral loop diuretic dose in furosemide equivalents) or a high-dose strategy (total daily intravenous furosemide dose 2.5 times their total daily oral loop diuretic dose in furosemide equivalents) and to administration of furosemide either by intravenous bolus every 12 hours or by continuous intravenous infusion.The study treatment, with group assignments concealed, was continued for up to 72 hours. At 48 hours, the treating physician had the option of adjusting the diuretic strategy on the basis of the clinical response. An assessment of biomarkers, including creatinine, cystatin C, and N-terminal pro-brain natriuretic peptide, was performed at a central core laboratory at baseline, 72 hours, and 60 days. Patients were followed for clinical events to day 60. The coprimary end points were patients' global assessment of symptoms, quantified as the area under the curve (AUC) of the score on a visual-analogue scale over the course of 72 hours, and the change in the serum creatinine level from baseline to 72 hours.ConclusionsAmong patients with acute decompensated heart failure, there were no significant differences in patients' global assessment of symptoms or in the change in renal function when diuretic therapy was administered by bolus as compared with continuous infusion or at a high dose as compared with a low dose. (Felker et. al., 2011, PMID: 21366472)

  Study phs003524