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• The Collaborative Study on the Genetics of Alcoholism (COGA)

  COGA is a family study of alcoholism, in which the subjects have been drawn from the Collaborative Study on the Genetics of Alcoholism (COGA), a large, ongoing family-based study that includes subjects from seven sites around the US. COGA has gathered detailed, standardized data on study participants, including diagnostic and neurophysiological assessments. This project has already proved successful in identifying several genes that influence the risk for alcoholism and neurophysiological endophenotypes, which have been independently replicated. COGA data were included as part of two Genetic Analysis Workshops, and the phenotypes are familiar to the genetics community. Alcoholic probands were recruited from treatment facilities, assessed by personal interview, and 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 an alcoholic proband. Assessment involved a detailed 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. Many participants also came to the laboratories for electroencephalographic studies. Neurophysiological features that have been shown to be useful endophenotypes for which we have linkage and in some cases association results, are included for a subset of the case-control sample: the beta power of the resting electroencephalogram (EEG), the P3(00) amplitude of the visual event-related potential (ERP), and the theta and delta event-related oscillations (EROs) underlying the P3. As part of COGA, a set of informative families was selected to have Genome-Wide Association data obtained within families. Genotyping was performed using the Illumina Human OmniExpress array 12.VI to genotype 2,282 subjects selected from 118 densely affected families. Genotyping was performed at the Genome Technology Access Center at Washington University School of Medicine in St. Louis. In addition, we also included genotypes for subjects (n=275 subjects) from these 118 families who were genotyped in a previous case-control GWAS using the Illumina 1M array. For quality control purposes, 51 of the 275 subjects were genotyped again on the Illumina Human OmniExpress array at the Washington University School of Medicine core facility.In addition, exome sequencing data on a subset of individuals with GWAS were added in version 2 (v2). For v2, a subset had 30X Whole Genome Sequencing (WGS) as part of the NIDA Sequencing Initiative. The subset contained two distinct sets: Sibling pairs where one sibling had at least two dependence diagnoses in the set (alcohol, cannabis, cocaine, and opioid), and the other had none, and non-related Case-Control pairs matched for age and ethnicity where the cases had alcohol and at least 2 other dependence diagnoses and controls had none. After sequencing, some sibling pairs are re-classified as half siblings. Three VCF files (small variants, structural variants, and copy number variations) are provided. Additional substance use variables are made available in v2. We note that the full sample data are deposited in four dbGaP submissions and the sequenced samples are split across all four: CIDR: Collaborative Study on the Genetics of Alcoholism Case Control Study [phs000125]. GWAS data on cases (primarily probands) and controls drawn from the families. Families with highest density of alcohol dependence and/or extreme event-related oscillation data [phs000763]. GWAS data on 119 extended families of European descent are available here, along with extensive documentation. Study on the Genetics of Alcoholism (COGA): African American Family GWAS [phs000976]. GWAS data on all available COGA families of African descent are available. COGA: Smokescreen GWAS [phs001208]. GWAS data on all remaining COGA DNA samples, primarily of other racial background, were genotyped on the Smoke Screen array. A listing of all sequenced pairs is provided in the documentation to facilitate the merging of these samples.

  Study phs000763

• Single Cell Analysis Program - Transcriptome (SCAP-T)

  This initiative is part of the Single Cell Analysis Program (SCAP) and is funded through the NIH Common Fund (See http://nihroadmap.nih.gov/), which supports cross-cutting programs that are expected to have exceptionally high impact. Common Fund initiatives address key roadblocks in biomedical research that impede basic scientific discovery and its translation into improved human health. In addition, these programs capitalize on emerging opportunities to catalyze progress across multiple biomedical fields. Single cell analysis has recently emerged as an important field of research because technologies have improved in sensitivity and throughput sufficiently to begin measuring and understanding heterogeneity in complex biological systems and correlating it with changes in biological function and disease processes. By profiling individual cells it is possible to resolve rare cells, transient cell states, and the influence of organization and environment on such cells and states, which cannot be described by ensemble measurements. The long-term goal of the SCAP is to accelerate this move towards personalizing health to the cellular level by understanding the link between cell heterogeneity, tissue function and emergence of disease through the discovery, development and translation of innovative approaches which will dramatically change the way cells are characterized. The SCAP will focus on research, which will systematically measure, analyze and model cell-to-cell variation, and identify crucial differences and rare biological states, which may have important functional consequences. Under SCAP, there are three studies to evaluate the cellular heterogeneity using transcriptional profiling of single cells (U01): University of Pennsylvania: Role of single cell mRNA variation in systems associated electrically excitable cells University of Southern California: Evaluation of cellular heterogeneity using patchclamp and RNA-seq of single cells University of California at San Diego: Single cell sequencing and in situ mapping of RNA transcripts in human brains The SCAP has been designed as a five-year program with several components: (1) the collection, analysis and sharing of comprehensive expression datasets to understand the role of heterogeneity in tissues and systemically and identify critical parameters and states; (2) the discovery of new, innovative tools for spatiotemporal imaging, manipulation, analysis and modeling of a biologically relevant population of cells with minimal perturbation; (3) milestone-driven validation and translation of technologies for characterizing single cells in situ meeting the needs of end-users; and (4) development and coordination of a multidisciplinary research community through workshops and other collective endeavors. Further details about the NIH SCAP-T program can be found here http://commonfund.nih.gov/singlecell/. The SCAP-T data sets include the detailed phenotype information, experimental protocols, QC information, RNA-sequencing data and NGS results from human heart and human brain cells. The first data release includes 697 single cells from human brain and heart. The second data release includes an additional 978 single cells from human brain and heart. The third data release includes an additional 1631 single cells from human brain and heart. The fourth data release is a correction to this study, but adds no new cells. The fifth data release includes an additional 2984 single cells from human brain and heart. The sixth data release includes an additional 944 single cells from human brain and heart. The seventh data release includes an additional 1977 single cells from human brain and heart. The SCAP-T data portal provides a customized interface for users to quickly identify and retrieve files by phenotypes, and data properties such as sequencing facility or coverage for all of these 9231 single cells. For more information about the SCAP-T study and the data portal, please visit http://www.scap-t.org.

  Study phs000833

• How upcycled prostate cancer sequences enabled key findings on telomeres length

  The length of telomeres, the chromosomes’ end tails, as depicted in the figure below, physiologically shorten with aging. This means that younger cells have longer telomeres compared to their aged counterparts; one could say that the length of cells’ telomeres is a measure of their replicative power. Cancer cells are known to be able to turn this into their favour, and expand their replicative immortality through telomere lengthening and maintenance. Despite being a well-studied pan-cancer hallmark, the relation of the telomeres length to specific cancer genomic features is poorly understood. Julia Livingstone and her colleagues from P.C. Boutros' team in Los Angeles focused their work on prostate cancer. To investigate the relations between telomere length and the clinico-genomics of prostate tumours, they used whole genome sequencing (WGS) of 392 published tumour–reference pairs previously deposited at the EGA under accession numbers EGAS00001000400 and EGAS00001000900. Their work was published on Nature Communications in November 2021. They determined the telomere length of the sequencing sample, from both tumour and non-tumour adjacent tissues, and subsequently ran statistical analysis to investigate possible correlation between the telomeres length with several cancer features. The team discovered that telomeres length does not correlate with any specific driver gene mutation, but it does with the overall frequency of single nucleotides variants in a sample. This finding suggests that tumours with shorter telomeres accumulate more mutations without strong selective pressures for specific ones. While proliferation rate did not correlate directly with telomere length, methylation of almost half of all genes strongly did. The team’s results are massive and reveal a complicated and fascinating relation of different clinical and genomic features of prostate cancer with telomere length. In the paper discussion, they smartly consider different possibilities. As noted above, all these amazing results have been obtained analysing previously sequenced samples. Remarkably, the researchers who generated the samples did not focus at all on telomeres length. They indeed studied specific genes mutations and the features of early and late-onset prostate cancer. This proves, once again, the power of sequencing data re-use. This data is tremendously rich in information, and can hardly be exhausted with any number of analyses. Generating sequencing data, especially Whole Genome Sequencing, even better if tumor-reference paired, is like shopping every last article at the grocery store. You can then cook several recipes, or prepare a seven-course dinner, and still have ingredients left for someone else to borrow and cook something you have not thought about, a recipe that is just not in your cookbook. Noteworthy, the data retrieved from the EGA for this paper is associated with rich and complete metadata, meaning pheno-clinical information regarding the sample donors. As Julia Livingstone and her team wrote, using rich clinical annotations enabled them to assess the relationship between telomere length and patients outcome. This highlights once again the importance of reporting and annotating metadata correctly; It might feel like extra work for the researchers depositing their data, but it really has a huge value. Our team at the EGA is currently working to improve the metadata annotation process, with the aim to maximize the benefits for the scientific community.

  Blog prostate-cancer-sequences-enabled-key-findings-on-telomeres-length

• Data Quality Control

  Data Quality Control High-throughput sequencing techniques have become the leading method to study, decode and discover the genomic origins of biological phenomenons. EGA provides a secure archival of such identifiable genomics data with the purpose of data-upcycling, i.e. to re-use these data for research. High-quality data standards are essential to ensure the quality and credibility of the research. Moreover, a quality check report can assure a researcher beforehand about the data that they will request access, therefore saving time and effort. The EGA has developed a File Quality Control Report (QC Report) to provide generic quality control reports for Fastq, SAM/BAM/CRAM, and VCF files deposited at EGA. This QC Report will allow users to get information regarding the files submitted within a specific dataset. The data requesters will obtain information such as the quality of reads, mapped reads, number of variants, and other features before starting the requesting process, which will save the efforts and time.Accessing file quality control reportsIn each dataset page, the user can explore the files that it contains by clicking the "files" tab. The Quality Control report of a file has two sections. The first one, contains general information about the file, such as the inferred assembly, total reads, the dataset or study where it comes from, etc. The second section contains plots that summarise interesting information about the file, for example, the base coverage distribution, base quality or mapped reads. The description of each plot is accessible by clicking the "i" button at the top-right corner of each plot box. Technical Description For analysing the fastq, SAM/BAM/CRAM and VCF files, the EGA applies a set of tools widely used in the bioinformatics community. FASTQ: FastQC, recognised as the gold standard tool by the community.Per base sequence quality, per sequence quality scores, per base sequence content, per sequence GC content, sequence duplication levels, etc.SAM/BAM/CRAM: samtools, also the gold standard, generates results plots useful to get an overall idea of the quality of the file.base coverage distribution, base quality, % of mapped reads, % of both mates mapped, singletons, duplicates, etc.VCF: vcftools and bcftools, combined with a custom script to infer the genome assembly.site frequency distribution, Ts/Tv, base changes, indel distribution, etc.

  Documentation access/request-data/quality-control-reports

• 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

• The African American Breast Cancer Epidemiology and Risk (AMBER) Consortium Study

  The AMBER Consortium Study was formed to pool interview data, questionnaire data, and biological samples from epidemiological studies of breast cancer in African-American women to discover the potential causes of early-onset and aggressive breast cancer in African-American women. AMBER is funded through a Program Project grant from the National Cancer Institute. Genetic data submitted to dbGaP come from participants in the Carolina Breast Cancer Study, Women's Circle of Health Study, and Black Women's Health Study. The P01 consists of four scientific projects; the aims include follow-up on previous GWAS findings for breast cancer susceptibility in AA women as well as investigation of SNPs in candidate genes in biologically plausible pathways. These SNPs were genotyped using DNA from 3130 African-American women with breast cancer and 3700 controls. Descriptions of the original studies that provided the data and samples for this collaborative study are given below. The Carolina Breast Cancer Study (CBCS): a North Carolina population-based case-control study of breast cancer, conducted in three phases. The current study phase, phase 3 (years 2008-2014), includes women residents in 44 counties. CBCS phases 1 and 2 were conducted in 24 counties. Breast cancer cases are identified using Rapid Case Ascertainment in cooperation with the NC Central Cancer Registry. Controls were identified for phases 1 and 2 only (1993-1996 and 1996-2001), using Division of Motor Vehicles lists for women under age 65 and Health Care Financing Administration lists for women 65 and older. Randomized recruitment was used to oversample AA women and women under age 50. In-depth interviews are conducted by study nurses in participants' homes to obtain information on potential risk factors for breast cancer. DNA samples have been obtained from most participants. Overall response rates for Phases 1 and 2 were 74% for AA cases and 54% for AA controls. Phase 3, conducted in 44 counties from 2008-2014, includes cases only. The response rate for AA cases in Phase 3 was 70.5%. The Women's Circle of Health Study (WCHS): a multi-site case-control study in New York City (NYC) and New Jersey (NJ) aimed at evaluating risk factors for early and aggressive breast cancer in women of AA and EA ancestry. Recruitment in NYC took place between January 2002 and December 2008 and involved hospital-based ascertainment of cases, while controls were identified through random digit dialing (RDD). Recruitment at the NJ site started in March 2006 and is ongoing. Phase I of the study ended in April 2012 and covered seven counties in NJ. WCHS2 includes two additional counties. Cases in NJ were identified from 2006 to 2012 by the NJ State Cancer Registry using rapid case ascertainment. Controls were initially recruited though RDD (2006 to 2010) and later through community-based efforts (2009-2012). In-person interviews ascertained data on established and suspected risk factors for breast cancer. DNA samples were obtained. Among eligible AA women, 75% in NY and 54% in NJ completed an interview and provided a biologic specimen. Black Women's Health Study (BWHS): an ongoing prospective cohort study of health and illness among U.S. black women, with a focus on cancer. The study began in 1995 when 59,000 AA women 21-69 years of age from across the United States completed a 14-page postal health questionnaire. The median age at entry was 38, and participants were residents of 17 states in mainland U.S.: Northeast, 28%; South, 30%; Midwest, 23%; West, 19%. The baseline questionnaire elicited information on a wide range of variables, including demographic factors, use of medical care, family history of breast cancer, reproductive and medical history, cigarette and alcohol use, weight, height, waist and hip circumference, medication use, diet, and exercise. Biennial follow-up questionnaires ascertain new cases of breast cancer and other illnesses and update covariate information. Medical record and cancer registry data are sought for all participants who report a diagnosis of breast cancer. As of 2014, approximately 80% of the baseline cohort have completed follow-up. DNA samples were obtained from about 50% of participants. BWHS data for the AMBER consortium were prepared as a nested case-control study, with controls frequency-matched to cases on year of birth, geographic region, and most recent questionnaire completed prior to the end of the at-risk period.

  Study phs000669

• CIDR: Collaborative Study on the Genetics of Alcoholism Case Control Study

  This is a case-control study of alcoholism, in which the subjects have been drawn from the Collaborative Study on the Genetics of Alcoholism (COGA), a large, ongoing family-based study that includes subjects from seven sites around the US. COGA has gathered detailed, standardized data on study participants, including diagnostic and neurophysiological assessments. This sample has already proved successful in identifying several genes that influence the risk for alcoholism and neurophysiological endophenotypes, which have been independently replicated. COGA data were included as part of two Genetic Analysis Workshops, and the phenotypes are familiar to the genetics community. Alcoholic probands were recruited from treatment facilities, assessed by personal interview, and 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 an alcoholic proband. Assessment involved a detailed 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. Many participants also came to the laboratories for electroencephalographic studies. Neurophysiological features that have been shown to be useful endophenotypes for which we have linkage and in some cases association results are included on a subset of the case-control sample: the beta power of the resting electroencephalogram (EEG), the P3(00) amplitude of the visual event-related potential (ERP), and the theta and delta event-related oscillations (EROs) underlying the P3 (See Porjesz et al., 2005; Porjesz and Rangaswamy, 2007 for reviews). A brief description of COGA is in Edenberg, H. J. (2002) The Collaborative Study on the Genetics of Alcoholism: an update. Alcohol Res Health 26, 214-218., Bierut, LJ, NL Saccone, JP Rice, A Goate, T Foroud, HJ Edenberg, L Almasy, PM Conneally, R Crowe, V Hesselbrock, T-K Li, JI Nurnberger, Jr, B Porjesz, MA Schuckit, J Tischfield, H Begleiter, and T Reich (2002) Defining alcohol-related phenotypes in humans: The Collaborative Study on the Genetics of Alcoholism. Alcohol Res Health 26, 208-213. Edenberg HJ and Foroud T (2006) The genetics of alcoholism: identifying specific genes through family studies. Addiction Biology 11, 386-396. This case-control sample of biologically unrelated individuals was drawn from COGA subjects. All cases meet DSM-IV criteria for alcohol dependence. Controls are individuals who have consumed alcohol, but did not meet any definition of alcohol dependence or alcohol abuse, nor did they meet any DSM-IIIR or DSM-IV definition of abuse or dependence for other drugs (except nicotine). All cases and controls have undergone identical clinical assessments. Many individuals in this case-control sample have not previously been genotyped. The Collaborative Study on the Genetics of Alcoholism (COGA) has four Co-Principal Investigators: B. Porjesz, V. Hesselbrock, H. Edenberg, L. 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 (V. Hesselbrock); Indiana University (H.J. Edenberg, J. Nurnberger Jr., T. Foroud); University of Iowa (S. Kuperman); SUNY Downstate (B. Porjesz); Washington University in St. Louis (L. Bierut, A. Goate, J. Rice); University of California at San Diego (M. Schuckit); Howard University (R. Taylor); Rutgers University (J. Tischfield); Southwest Foundation (L. 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). Funding support for genotyping, which was performed at the Johns Hopkins University Center for Inherited Disease Research, was provided by the National Institute on Alcohol Abuse and Alcoholism, the NIH GEI (U01HG004438),and the NIH contract "High throughput genotyping for studying the genetic contributions to human disease" (HHSN268200782096C). COGA has over 250 publications listed at www.niaaagenetics.org

  Study phs000125

• Research Program on Genes, Environment and Health (RPGEH)

  The Kaiser Permanente Research Program on Genes, Environment, and Health (RPGEH) is a resource developed to facilitate research on genetic and environmental factors on common diseases and healthy aging. The RPGEH resource links biospecimens, health surveys, and comprehensive electronic medical records on broadly consented adult members of Kaiser Permanente Medical Care Plan, Northern California Region (KPNC). KPNC is an integrated health care delivery system with a membership of approximately 3.3 million people in northern California. The membership of KPNC is representative of the general population in the 14 county area in which facilities are located, although extremes of income are underrepresented. At the end of 2013, the RPGEH resource included: (1) demographic and behavioral surveys from over 430,000 participants; (2) biospecimens (DNA, serum, plasma, and/or saliva) from over 204,000 participants, including over 13,000 pregnant women; (3) genome-wide genotype data (70 billion SNP genotypes) on over 100,000 participants, including the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort; and (4) the longitudinal electronic medical records of the participants. The RPGEH was developed beginning in 2005 at the Division of Research of Kaiser Permanente Northern California by Catherine Schaefer (Director), Neil Risch (Co-Director), Lisa Croen, Eric Jorgenson, Lawrence Kushi, Charles Quesenberry, Sarah Rowell, Carol Somkin, Stephen Van den Eeden, Larry Walter, and Rachel Whitmer. Funding of the RPGEH was provided to C. Schaefer (PI) and N. Risch (co-PI) by the Wayne and Gladys Valley Foundation, The Ellison Medical Foundation, the Robert Wood Johnson Foundation, Kaiser Permanente Northern California, and the Kaiser Permanente National and Regional Community Benefit Programs. The GERA cohort was funded by a grant from NIH to RPGEH and UCSF (RC2 AG036607; C. Schaefer and N. Risch, PIs). At the time of the award of the RC2 project in late 2009, the RPGEH had established a cohort of about 140,000 individuals who had answered a detailed survey, provided saliva samples for extraction of DNA, and given broad consent for the use of their data in studies of health and disease. Survey and Cohort Recruitment. Initially, the RPGEH developed electronic disease registries to enable identification of phenotypes, using algorithms applied to EMR data. In 2007, the RPGEH mailed a four page survey to 1.9 million adult (≥ 18 years old) members of KPNC who had been members for two years or more, to obtain data on demographic and behavioral factors complementary to the clinical data in the EMR. The survey materials included a cover letter introducing the RPGEH, a two page list of Frequently Asked Questions, and the survey, which included questions on demographic factors such as education, race-ethnicity, income and marital status, dietary factors, physical activity, smoking, and alcohol consumption, as well as reproductive history and reproductive health. Members whose electronic medical records indicated a preference for written communications in Chinese or Spanish received survey materials both in English and a Chinese or Spanish translation. Approximately 400,000 completed surveys were returned. Saliva Sample Collection. Beginning in July 2008, respondents to the survey were asked to sign and return a consent form and authorization for use and disclosure of protected health information. The consent form authorized broad use of biospecimens, survey data, and data from participants' electronic health records for use in studies of genetic and environmental influences on health and disease. Respondents who returned completed consent forms were mailed (Oragene) saliva collection kits; more than 132,000 saliva samples were collected in two years. Completed saliva kits were scanned and archived in a temporary biorepository at the KPNC Division of Research. In late 2009, the RPGEH began collection of saliva samples from the California Men's Health Study (CMHS), a cohort that had been previously assembled in 2002-2003 and had been excluded from the RPGEH survey mailing with the intent of later adding CMHS participants to the assembled RPGEH cohort. The CMHS was developed to facilitate research on prostate cancer and other conditions in older men; the study protocol is described in Enger, et al., 2006. It enrolled and surveyed more than 40,000 men in KPNC, ages 45-69 years, who were members of KPNC during 2002-2003. CMHS men completed two mailed surveys with demographic and behavioral data similar to that of the RPGEH. The data on analogous variables were reconciled and integrated with the data derived from the RPGEH cohort for use in the RPGEH resource. By 2011, RPGEH collected approximately 15,400 saliva samples from men participating in the CMHS. RPGEH Access and Collaborations Website and Procedures. The RPGEH maintains a web portal for inquiries and applications for collaboration and access to data. The url is: https://rpgehportal.kaiser.org/. RPGEH has an application process and an Access Review Committee that reviews applications for collaboration and use. For more information, please contact RPGEH through the website.

  Study phs000788

• A Genome-Wide Association Study of Heroin Dependence

  This collaboration of Australian and American investigators aims to identify genes associated with liability for heroin dependence. The project uses a case-control design in which cases met lifetime DSM-IV criteria for heroin dependence. Controls included assessed individuals who did not meet DSM-IV heroin dependence criteria and unassessed general population controls. Cases and controls were obtained from the several large investigations including: The Comorbidity and Trauma Study, Heroin Dependence in Western Australia, the OZ-ALC Study, a Twin Study of Mole Development in Adolescence, and ongoing genetic studies of substance dependence conducted by investigators at Yale and collaborating institutions. These projects are briefly described below. The Comorbidity and Trauma Study (PI: Elliot Nelson), a retrospective case-control study examining genetic and environmental factors contributing to heroin dependence liability. The study was funded by the National Institute on Drug Abuse (NIDA), and was run in collaboration with Washington University, the Queensland Institute of Medical Research (QIMR), and the National Drug and Alcohol Research Centre (NDARC), University of New South Wales. Case participants were recruited from maintenance clinics in the greater Sydney area. Control participants were recruited from employment centres and community centres, open street malls, and local press servicing the same geographical area as the opioid maintenance treatment clinics and either denied recreational use of opioids or had used these drugs recreationally fewer than 11 times lifetime. The prevalence in these individuals of non-opioid licit drug dependence and illicit drug dependence as well as childhood trauma exposure and other psychiatric disorders is elevated considerably versus estimates of similar measures in Australian general population samples. Participants provided blood samples as a source of DNA and completed a comprehensive psychiatric diagnostic interview based on the Semi-Structured Assessment of the Genetics of Alcoholism - Australia (SSAGA-OZ) augmented with sections drawn from other instruments assessing childhood trauma exposure, family history, and screening for borderline personality disorder. Heroin Dependence in Western Australia (PI: Sybille Schwab) is a study focusing both on genetic contributions to heroin dependence and response to naltrexone treatment of the disorder. Participants completed a clinical assessment and provided blood samples during their treatment at the Perth Naltrexone Clinic now name as the Fresh Start Recovery Programme. Funding for the project was provided by the Australia Government's National Health and Medical Research Council (Grant # 513862; PI: Sybille Schwab) Affected subjects from ongoing genetic studies of substance dependence conducted by investigators at Yale (PI: Joel Gelernter) and collaborating institutions were collected in the course of several NIDA-funded studies. Those included in the current set were assessed by means of the SSADDA (Semi-Structured Assessment for Drug Dependence and Alcoholism). All are opioid dependent European-Americans, and all list heroin as the opioid must used. Most were collected at Yale University School of Medicine or University of CT School of Medicine under the supervision of Drs Joel Gelernter and Henry Kranzler. Control subjects were also collected in the course of several NIDA- and NIAAA-funded studies. Those included in the current set were assessed by means of the SSADDA (Semi-structured Assessment for Drug Dependence and Alcoholism). Most were collected at Yale University School of Medicine or University of Connecticut School of Medicine under the supervision of Drs Joel Gelernter and Henry Kranzler. The OZ-ALC Study (PI: Andrew Heath) consists of a large group of twins and their family members ascertained from the general population Australian Twin Registry who have participated in ongoing research projects. For the control investigation, we have selected individuals who do meet criteria for illicit drug dependence who have had GWAS genotyping with the Illumina Human CNV370-Quad. Inclusion of individuals with alcohol dependence or nicotine dependence was minimized. For a more detailed description of the study, please see: http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000181.v1.p1 The Twin Study of Mole Development in Adolescence (PI: Nick Martin) is an ongoing investigation of melanocytic naevi funded by the Australian Government's National Health and Medical Research Council (Grant # 389891; PI: Nick Martin). For the current project, unassessed parents of these twins will serve as a control group. These individuals will either have been previously genotyped with the Illumina Human 610-Quad BeadChip or will be genotyped as part of the current project. Parents have largely survived the period of risk for heroin dependence and, by virtue of their participation in this research, are very likely to have a prevalence of heroin dependence lower than that in the general population (i.e., <0.7%). In order to understand the immune modulatory effect of opioids across peripheral blood immune populations, a second study (PI: Christine S. Cheng) analyzed single cell RNA-seq profiles from the PBMCs of a subset of case participants and control participants from the Comorbidity and Trauma Study (PI: Elliot Nelson). The study assessed and identified transcriptional changes between opioid dependent and control samples across naive and LPS stimulated immune populations.

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• eMERGE Network Phase III: HRC SNV and 1000 Genomes SV Imputed Array Data of 105,000 Participants

  The Electronic Medical Records and Genomics (eMERGE) Network is a National Institutes of Health (NIH)-organized and funded consortium of U.S. medical research institutions. The primary goal of the eMERGE Network is to develop, disseminate, and apply approaches to research that combine biorepositories with electronic medical record (EMR) systems for genomic discovery and genomic medicine implementation research. eMERGE was announced in June 2007 and began its third phase in September 2015. eMERGE Phase III (June 2015 - June 2020) consists of 10 study sites, two central sequencing and genotyping facilities, and a coordinating center. Included in this study are: Human Reference Consortium (HRC) single nucleotide variants and 1000 Genomes structural variants imputed array data of 105,108 eMERGE participants from nine Phase III study sites and three Phase II study site collaborators. Corresponding demographics, body mass index measurements. Case/control status for the following phenotypes: Abdominal aortic aneurysm; Ace-Inhibitor/Cough; Attention Deficit Hyperactivity Disorder; Age-related macular disease; Appendicitis; Asthma; Atopic Dermatitis; Autism; Benign Prostatic Hyperplasia; Carotid artery disease as a Quantitative Measure; caMRSA; Cataract; Clostridium difficile colitis; Extreme Obesity; Chronic Kidney Disease; Chronic Kidney Disease and Type 2 Diabetes; Chronic Kidney Disease, Type 2 Diabetes and Hypertension; Colon Polyps; Cardiorespiratory Fitness; Dementia; Diverticulosis; Diabetic retinopathy; Gastroesophageal Reflux Disease; Glaucoma; Height; Heart failure; Hypothyroidism; Lipids; Ocular hypertension; Peripheral Arterial Disease; QRS duration; Red blood cell indices; Remission of Diabetes after ROUX-EN-Y gastric bypass surgery; Resistant hypertension; MACE while on Statins; Type 2 Diabetes; Venous Thromboembolism; White blood cell indices; and Zoster virus infection. Study sites and participants include: Boston Children's Hospital: The Gene Partnership (TGP) is a prospective longitudinal registry at Boston Children's Hospital (BCH) to study the genetic and environmental contributions to childhood health and disease, collect genetic information on a large number of children who have been phenotyped, and implement the Informed Cohort and the Informed Cohort Oversight Board (ICOB). The term "The Gene Partnership" reflects a partnership between researchers and participants. Children seen at BCH are offered enrollment, as are their parents and siblings. DNA is collected on all enrollees. BCH has a comprehensive EMR system, and virtually all inpatient and outpatient data are captured electronically. Clinical data in the BCH EMR is loaded in the i2b2 data warehouse which is available to investigators. Cases, phenotypes, and covariates are ascertained using the i2b2 database. Participants at BCH in TGP have consented to receive any research result and/or incidental finding that arises from studies using TGP that is approved by the Informed Cohort Oversight Board (ICOB) and is in accordance with the participants'preferences;results are returned through the Personally Controlled Health Record (PCHR). BCH and Cincinnati Children's Hospital Medical Center (CCHMC) have partnered as the Pediatric Alliance for Genomic and Electronic Medical Record (EMR) Research (PAGER) site for the eMERGE Phase II network for pediatric institutions, and the cohort for eMERGE at BCH is TGP. Children's Hospital of Pennsylvania (CHOP): The Center for Applied Genomics (CAG) at the Children's Hospital of Philadelphia (CHOP) is a high-throughput, highly automated genotyping and sequencing facility equipped with state-of-the-art genotyping and sequencing platforms. Children who are treated at the Children's Hospital Healthcare Network and their parents may be eligible to take part in a major initiative to collect more than 100,000 blood samples, covering a wide range of pediatric diseases. A large majority of participants consenting to prospective genomic analyses also consent to analysis of their de-identified electronic health records (EHRs). EHRs are longitudinal, with a mean duration of 6.5 years. Cincinnati Children's Hospital Medical Center/Boston's Children's Hospital (CCHMC/BCH): Cincinnati Children's Hospital Medical Center (CCHMC) is a pediatric institution dedicated to improving health and welfare of children and to the discovery and practical application of new genomic information to the ordinary care of children. CCHMC brings an extraordinary faculty to eMERGE III who are committed to gain a better understanding of the genesis of disease and to elucidate the mechanisms of diseases that afflict children, specifically pediatric disease phenotypes that will leverage the available eMERGE adult genomic data and electronic medical records (EMRs) to discover meaningful use results. Generation of EMR phenotype algorithms, informed by natural language processing, using heuristic and machine learning methods is ongoing. CCHMC has developed tools to evaluate adolescent return of results preferences, examined the ethical and legal obligations and potential to reanalyze results, and developed clinical decision support for phenotyping, test ordering, and returning sequencing results. The success of these eMERGE III studies is enhanced by the ongoing institutional investment made in the CCHMC Biobank, the comprehensive EMR (EPIC), the i2b2 de-identified medical record data warehouse, and hundreds of faculty and senior staff who make genomics or informatics an active focus of their research. Columbia University: Columbia University Medical Center/New York Presbyterian (CUMC/NYP) Hospital system is one of the nation's largest and most comprehensive hospital systems with over 2 million inpatient and outpatient yearly visits that serves a racially and ethnically diverse urban patient population. The Columbia University GENomic Integration with EHR (GENIE) research study contributed and shared phenotype and genotype data for individuals who were recruited as part of a diverse array of initiatives within the hospital, including Northern Manhattan Study (NOMAS), Pediatric Cardiac Genomic Consortium (PCGC), Caribbean Hispanics with Familial and Sporadic Late Onset Alzheimer's disease (AD), Alzheimer's Disease Sequencing Project (ADSP), and Genetics of Chronic Kidney Disease study. Some of these individuals had kidney or neurological problems, some were healthy adult volunteers with self-reported health status information from the medically underserved Northern Manhattan community, and others were pediatric patients with cardiac conditions. For the kidney disease cohort, patients with the diagnosis of Chronic Kidney Disease (CKD) and healthy controls were recruited to the Columbia University CKD biobank. For the NOMAS cohort, eligible participants were stroke-free, were 40 years old, and resided for at least 3 months in a Northern Manhattan household with a telephone. The PCGC study recruited parent-offspring trios with pediatric probands diagnosed with congenital heart defects (CHD). For the Caribbean Hispanics with Alzheimer's disease project, individuals from families affected by AD and with sporadic AD were recruited, along with unrelated controls. Samples for the ADSP study have been selected from well-characterized cohorts of individuals with AD diagnosis. Geisinger Health System: A research cohort of adult Geisinger Clinic patients was enrolled from community-based primary care clinics of the Geisinger Health System. Patients were eligible for enrollment if they were a primary care patient of a Geisinger Clinic physician and were scheduled for a non-emergent clinic visit. All participants provided written informed consent and HIPAA authorization. Consenting patients agreed to provide blood samples for broad biomedical research use, and permission to access data in their Geisinger electronic medical record for research. The enrollment rate was 90% of patients approached. The demographics of the cohort approximate those of the Geisinger Clinic outpatient population. Research blood samples were collected during an outpatient clinical phlebotomy encounter. Research blood samples are coded and stored in a central biorepository. Samples are linkable to clinical data in a de-identified manner for research via an IRB-approved data broker process. For genomic analysis, DNA is extracted from EDTA-anticoagulated whole blood. Partners Health Care (Harvard): The Partners HealthCare Biobank is a large research program designed to help researchers understand how people's health is affected by their genes, lifestyle, and environment. This large research data and sample repository provides access to high-quality, consented blood samples to help foster research, advance our understanding of the causes of common diseases, and advance the practice of medicine. For the Partners research community (Massachusetts General Hospital and Brigham and Women's Hospital), the Biobank provides: Banked samples (plasma, serum, and DNA) collected from consented patients Blood samples that were discarded after clinical testing in the Crimson Cores maintained in the Brigham and Women's Hospital and Massachusetts General Hospital Pathology Departments Sample handling and preparation services Link to the biobank data to the Partners Research Patient Data Registry (RPDR) a research instance of our electronic clinical chart Data access through our research portal. To date, over 60,000 Partners patients have given their consent to enroll, give a blood sample, receive research results and agreed to be re-contacted for additional research studies. The Biobank has enabled Partners investigators to compete for nationally recognized grants in personalized medicine such as a clinical electronic Medical Records and Genomics network (eMERGE) site and the national All of US program. The Biobank currently supports over 120 Partners investigators and over 100 million dollars in NIH research. Kaiser Permanente Washington with the University of Washington and the Fred Hutchinson Cancer Research Center: KPWA participants were enrolled in the eMERGE Network through the Northwest Institute of Genetic Medicine (NWIGM) biorepository, and provided the appropriate consent to receive clinically relevant genetic results (N~8,073.) NWIGM is based at the University of Washington and co-managed by the University of Washington and KPWA. The purpose of the NWIGM biorepository is to build infrastructure and resources to carry out a broad range of future genetic research. KPWA members enrolled in the biorepository are asked to provide informed consent to providing a DNA sample for storage in the NWIGM biorepository. The consent is purposefully broad to serve the dual purpose of reducing the burden on researchers who wish to use this biorepository and the IRB committees who will be responsible for reviewing these requests in the future. Participants were eligible if aged 50 - 65 years old at the time of their enrollment into the NWIGM repository, living, enrolled in KPWA's integrated group practice, and had completed an online Health Risk Appraisal. The selection algorithm was based on several data sources from the EHR at KPWA. 1) Demographics - participants with self-reported race as Asian ancestry were prioritized and selected to enrich for non-European ancestry. The KPWA eMERGE cohort includes n=1,245 members of Asian ancestry. 2) Participants were also selected for a history of colorectal cancer (n=1,002), in order to allow us to enrich germline pathogenic variants. Essentia Institute of Rural Health, Marshfield Clinic, Pennsylvania State University (Marshfield): The Marshfield Clinic Personalized Medicine Research Project is a population-based biobank in central Wisconsin with more than 20,000 adult subjects who provided written, informed consent to access their medical records and provided a blood sample from which DNA was extracted and plasma and serum stored. In addition to an average of 30 years of medical history data, a questionnaire about environmental exposures, including a detailed food frequency questionnaire, is available to facilitate gene/environment studies. Mayo Clinic: The Mayo Vascular Disease Biorepository is a disease-specific biobank for vascular diseases including peripheral arterial disease (PAD). PAD patients were identified from individuals referred to the non-invasive vascular laboratory for lower extremity arterial evaluation. Since 1997, laboratory findings have been recorded into an electronic database employing an in-house software package for data archiving and retrieval;this data becomes part of the Mayo EMR. Patients referred to the center with suspected PAD undergo a comprehensive non-invasive evaluation including the ankle-brachial index (ABI) - the ratio of blood pressure measured in the upper arms divided by blood pressure measured at the ankles. Controls subjects are identified from patients referred to the Cardiovascular Health Clinic for stress ECG. The prevalence of PAD in patients with normal exercise capacity who do not have inducible ischemia on the stress ECG , was <1%. Data regarding risk factors for atherosclerosis such as diabetes, dyslipidemia, hypertension, and smoking are ascertained from the EMR. Case control study of venous thromboembolism (PI John Heit) Controls from a case control study of pancreatic cancer (PI Gloria Petersen) Mayo Clinic Biobank. Icahn School of Medicine at Mount Sinai School (Mt. Sinai): The Institute for Personalized Medicine (IPM) Biobank Project is a consented, EMR-linked medical care setting biorepository of the Mount Sinai Medical Center (MSMC) drawing from a population of over 70,000 inpatients and 800,000 outpatient visits annually. MSMC serves diverse local communities of upper Manhattan, including Central Harlem (86% African American), East Harlem (88% Hispanic Latino), and Upper East Side (88% Caucasian/white) with broad health disparities. IPM Biobank populations include 28% African American (AA), 38% Hispanic Latino (HL) predominantly of Caribbean origin, 23% Caucasian/White (CW). IPM Biobank disease burden is reflective of health disparities with broad public health impact: average body mass index of 28.9 and frequencies of hypertension (55%), hypercholesterolemia (32%), diabetes (30%), coronary artery disease (25%), chronic kidney disease (23%), among others. Biobank operations are fully integrated in clinical care processes, including direct recruitment from clinical sites, waiting areas and phlebotomy stations by dedicated Biobank recruiters independent of clinical care providers, prior to or following a clinician standard of care visit. Recruitment currently occurs at a broad spectrum of over 30 clinical care sites. Northwestern University: The NUgene Project is a repository with longitudinal medical information from participating patients at affiliated hospitals and outpatient clinics from the Northwestern University Medical Center. Participants'DNA samples are coupled with data from a self-reported questionnaire and continuously updated data from our Electronic Medical Record (EMR) representing actual clinical care events. Northwestern has a state-of-the art, comprehensive inpatient and outpatient EMR system of over 2 million patients. NUgene has broad access to participant data for all outpatient visits as well as inpatient data via a consolidated data warehouse. NUgene participants consent to distribution and use of their coded DNA samples and data for a broad range of genetic research by third-party investigators. Vanderbilt University Medical Center: BioVU, Vanderbilt's DNA databank, was designed as an enabling resource for exploration of the relationships among genetic variation, disease susceptibility, and variable drug responses. BioVU acquires DNA from discarded blood samples collected from routine patient care. The biobank is linked to de-identified clinical data extracted from Vanderbilt's EMR, which forms the basis for phenotype definitions used in genotype-phenotype correlations. BioVU is currently the largest single site DNA collection world-wide, at >235,000 samples as of spring 2017.

  Study phs001584