1217 results for ""initial+cohort"+"mid-2020s"+"consortium"+"scholarly+exchange"+"university""

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• Study of Addiction: Genetics and Environment (SAGE)

  This study is part of the Gene Environment Association Studies initiative (GENEVA) funded by the National Human Genome Research Institute. The overarching goal is to identify novel genetic factors that contribute to addiction through a large-scale genome-wide association study of DSM-IV alcohol dependent (and frequently illicit drug dependent) cases and non-dependent, unrelated control subjects of European and African American descent. The focus of this proposal is a case-control design of unrelated individuals for a genetic association study of addiction. Cases are defined as individuals with DSM-IV alcohol dependence (lifetime) and potentially other illicit drug dependence. In addition to the categorical diagnosis, we have data on ordinal measurements of number of DSM-IV symptoms for alcohol, nicotine, marijuana, cocaine, opiates and other drugs so that we will able to construct quantitative measurements of addiction severity over a wide range of substances. Controls are defined as individuals who have been exposed to alcohol (and possibly to other drugs), but have never met lifetime diagnosis for alcohol dependence or dependence on other illicit substances. Analyses that include refinement of the phenotype and incorporation of important demographic and environmental factors into association studies will be pursued. Cases and controls were selected from three large, complementary datasets: the Collaborative Study on the Genetics of Alcoholism (COGA), the Family Study of Cocaine Dependence (FSCD), and the Collaborative Genetic Study of Nicotine Dependence (COGEND). COGA: COGA was initiated in 1989 and is a large-scale family study that has had as its primary aim the identification of genes that contribute to alcoholism susceptibility and related characteristics. COGA is funded through the National Institute on Alcohol Abuse and Alcoholism (NIAAA). Subjects were recruited from 7 sites across the U.S. Alcohol dependent probands were recruited from treatment facilities and assessed by personal interview. After securing permission, other family members were also assessed. A set of comparison families was drawn from the same communities as the families recruited through the alcohol dependent probands. Assessment involved a comprehensive personal interview developed for this project, the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA), which gathers detailed information on alcoholism related symptoms along with other drugs and psychiatric symptoms. Families with three or more first-degree relatives who were alcohol dependent were invited for more extensive testing, including neurophysiology evaluations (ERPs and EEGs) and a battery of neuropsychological assessments. Blood was obtained for genetic studies. Institutional Review Boards at all sites approved the protocols, including sharing in the NIAAA national repository. COGA has four Co-Principal Investigators Bernice Porjesz, Victor Hesselbrock, Howard Edenberg, and Laura Bierut. COGA includes nine different centers where data collection, analysis, and storage take place. The nine sites and Principal Investigators and Co-investigators are: University of Connecticut (Victor Hesselbrock); Indiana University (Howard Edenberg, John Nurnberger, Jr., Tatiana Foroud); University of Iowa (Samuel Kuperman); SUNY Downstate (Bernice Porjesz); Washington University in St. Louis (Laura Bierut, Alison Goate, John Rice); University of California at San Diego (Marc Schuckit); Howard University (Robert Taylor); Rutgers University (Jay Tischfield); Southwest Foundation (Laura Almasy). Q. Max Guo serves as the NIAAA Staff Collaborator. This national collaborative study is supported by the NIH Grant U10AA008401 from the National Institute on Alcohol Abuse and Alcoholism (NIAAA) and the National Institute on Drug Abuse (NIDA). Family Study of Cocaine Dependence (FSCD): This project was initiated in 2000 as a case-control family study of cocaine dependence funded through the National Institute on Drug Abuse (NIDA; PI: Laura Bierut). The primary goal was to increase the understanding of the familial and non-familial antecedents and consequences of cocaine dependence. Cocaine dependent individuals were systematically recruited from chemical dependency treatment units (both public and private; residential and outpatient) in the greater St. Louis metropolitan area. Community based control subjects were identified through a Missouri Driver's License Registry (maintained at Washington University for research purposes) and matched by age, race, gender, and residential zip code. As a supplement to this project, blood samples were collected for future genetic analysis and were included in the NIDA Genetics Consortium. Phenotypic data, DNA, and cell lines are in the NIDA Center for Genetics Studies. Collaborative Genetic Study of Nicotine Dependence (COGEND): COGEND was initiated in 2001 as a three-part program project grant funded through the National Cancer Institute (NCI; PI: Laura Bierut). The three projects included a study of the familial transmission of nicotine dependence, a genetic study of nicotine dependence, and a study of the relationship of nicotine dependence with nicotine metabolism. The primary goal is to detect, localize, and characterize genes that predispose or protect an individual with respect to heavy tobacco consumption, nicotine dependence, and related phenotypes and to integrate these findings with the family transmission and nicotine metabolism findings. The primary design is a community based case-control family study. All subjects were recruited from Detroit and St. Louis. Nicotine dependent cases and non-dependent smoking controls were identified and recruited. In addition, one sibling for each case and control subject was recruited in a subset of the sample. Over 56,000 subjects aged 25-44 years were screened by telephone, over 3,100 subjects were personally interviewed, and over 2,900 donated blood samples for genetic studies. All three studies (COGA, COGEND, FSCD) include measures of basic socio-demographic variables, including age, sex, race/ethnicity, family income, educational attainment, religious participation, and family structure. Other important covariates and/or potential moderators of genetic effects include comorbid addictions and age at initiation of use for cigarettes, alcohol and drugs. The assessments also include measures of various life stressors, such as physical and sexual abuse, which have been implicated in gene-environment interactions for several disorders. Coding for both individual variables and indices has been standardized across studies. All subjects were assessed in person by trained research assistants. Funding support for genotyping, which was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR), was provided by the NIH GEI (U01HG004438), the National Institute on Alcohol Abuse and Alcoholism, the National Institute on Drug Abuse, and the NIH contract "High throughput genotyping for studying the genetic contributions to human disease"(HHSN268200782096C). Note for Publications Related to Study: The Study of Addiction: Genetics and Environment (SAGE) has not yet generated publications. Below is a listing of publications related to the three studies from which the SAGE sample was selected. COGA has over 228 publications listed at www.niaaagenetics.org This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to addiction through a large-scale genome-wide association study of DSM-IV alcohol dependent (and frequently illicit drug dependent) cases and non-dependent, unrelated control subjects of European and African American descent. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000092

• Genomic Landscape of Cutaneous Diffuse Large B Cell Lymphoma

  Cutaneous diffuse large B cell lymphomas (DLBCL) are aggressive lymphomas with a poor prognosis. To elucidate their genetic bases, we performed whole exome capture and massively parallel sequencing on 19 tumor samples of diffuse large B cell lymphoma, leg type (DLBCL-LT) and 6 samples of secondary cutaneous diffuse large B cell lymphoma, not otherwise specified (DLBCL-NOS). Tumor specimens and their associated sequencing data were from multiple institutions, including Northwestern University (Chicago, IL), Massachusetts General Hospital (Boston, MA), and Medical University of Graz (Graz, Austria).

  Study phs001645

• FEGA Sweden Helpdesk

  FEGA Sweden is an archive for storing and sharing all kinds of data resulting from biomedical research projects. As a national node of the Federated European Genome-phenome Archive (FEGA), we enable researchers to store their data in Sweden in a way that meets the requirements of the General Data Protection Regulation (GDPR). Any data submitted to the archive is subject to controlled access, meaning access to the data only will be granted after a formal application procedure. Using FEGA Sweden for storing and sharing data is free of charge for academic users affiliated with a Swedish university. However, the university must have a signed Data Processing Agreement (DPA) with Uppsala University. The current list of universities with a signed DPA can be found here: https://fega.nbis.se/submission/complying-with-gdpr.html. FEGA Sweden is hosted by the National Bioinformatics Infrastructure Sweden (NBIS), which legally is part of Uppsala University. NBIS forms the bioinformatics platform at SciLifeLab and constitutes the Swedish node of the European organisation ELIXIR. Contact the FEGA Sweden Helpdesk at fega-sweden@nbis.se for further questions.

  Dac EGAC50000000077

• The BIOS Consortium: Biobank-based Integrative Omics Studies

  Dac EGAC00001000277

• MacTel_cohort_Omni5_genotypes

  MacTel Projet consortium case and control genotypes from Ilumina Omni5 chip

  Dataset EGAD00010001204

• University of Bergen Rare Monogenic Autoimmune Syndrome (APS-1) Data Access Committee

  This is the DAC appointed by the University of Bergen for the datasets related to the study of APS-1 in the Department of Clinical Sciences . These data are from single cell transcriptomic analysis of expanded Tregs from patients with the rare monogenic autoimmune syndrome “APS-1” compared to healthy donors.

  Dac EGAC50000000081

• Haukeland University Hospital Data Access Committee for ParkOme-1 datasets archvied in Federated EGA Norway

  Data Access Committee appointed by Haukeland University Hospital for omics datasets for Parkinson's disease and related disorders, generated in studies under the ParkOme-1 project. Omics datasets of different types are generated from fresh frozen brain tissue from individuals with neurodegenerative parkinsonisms and neurologically healthy controls.

  Dac EGAC50000000193

• University Health Network DAC

  Dac EGAC00001002751

• University Health Network DAC

  Dac EGAC00001003401

• National Institute of Dental and Craniofacial Research (NIDCR) Sjögren's International Collaborative Clinical Alliance (SICCA): Center for Inherited Disease Research (CIDR) Genome-Wide Genotyping

  The Sjögren's International Collaborative Clinical Alliance (SICCA) is a multisite observational cohort study that recruited a large cohort of geographically diverse participants. Enrollment of participants began in late 2004 at five (one domestic and four international) sites, in which all groups used the same protocol-directed methods to provide uniform evaluations; collect oral, ocular, and rheumatologic data; and collect specimens. The sites were located at the University of Buenos Aires, Argentina; Peking Union Medical College, Beijing, China; Rigshopitalet (formerly at Glostrup Hospital), Copenhagen, Denmark; Kanazawa Medical University, Ishikawa, Japan; King's College, London, UK (joined in 2007); and the University of California, San Francisco (UCSF). In 2009, Aravind Eye Hospital, Madurai, India; Johns Hopkins University, Baltimore, MD; and University of Pennsylvania, Philadelphia, PA were added as additional SICCA sites. UCSF is the coordinating center for SICCA. All specimens and data collected for SICCA are housed at UCSF. To facilitate the research focused on understanding the genetics of Sjögren'sSjögren's syndrome, high-density SNP genotype data and SICCA clinical information are being made available to the research community. This includes participants recruited from all SICCA research groups (RG). These participants (3,382), blood relatives (439), and unrelated healthy controls (25) had their whole blood or saliva sample (Oragene) extracted for DNA for the GWAS at the UCSF DNA Bank. Eighty eight percent of the participants are women, most are of European or Asian ancestry and the median age is 55. To assess potential batch effects when doing case-control comparisons using planned external controls, 30 DNA samples from each of three studies were genotyped with SICCA DNA samples: The Genetic Architecture of Smoking and Smoking Cessation - Collaborative Genetic Study of Nicotine Dependence (COGEND) - PI: Laura Bierut. NEI-Age-related disease study (AREDS) - Genetic Variation in Refractive Error Substudy - PI: Dwight Stambolian. Controls from the National Institute of Mental Health's (NIMH's) Human Genetics Initiative. Genome-Wide Association Study of Schizophrenia - PI: Pablo V. Gejman. Molecular Genetics of Schizophrenia - nonGAIN Sample (MGS_nonGAIN) - PI: Pablo V. Gejman. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data quality control, dbGaP preparation and posting, and imputation to 1000 Genomes to increase SNP density was performed by the Center for Biomedical Statistics at the University of Washington. Data analysis was performed at UCSF using software PLINK, EIGENSOFT, and SNPTEST.

  Study phs000672