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• Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples (T2D-GENES) Follow-Up Study: Research Studies in Hong Kong

  The ~52,000 sample Type 2 Diabetes Exome Sequencing project is a collaboration of six consortia with various funding mechanisms that have joined together to investigate genetic variants for type 2 diabetes (T2D) using the largest T2D case/control sample set compiled to date. This includes samples from: Type 2 Diabetes Genetic Exploration by Next-generation sequencing in Multi-Ethnic Samples (T2D-GENES) Genetics of Type 2 Diabetes (GoT2D) Exome Sequencing Project (ESP) Slim Initiative in Genomic Medicine for the Americas (SIGMA) Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCAMP) Progress in Diabetes Genetics in Youth (ProDIGY) This data generated from the Hong Kong cohort was part of the T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) consortium, which is a NIDDK-funded international research consortium that seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. The T2D-GENES Project is a multi-ethnic sequencing study designed to assess whether less common variants play a role in T2D risk and to assess similarities and differences in the distribution of T2D risk variants across ancestry groups. The individuals were obtained from over 20 cohorts across the 6 consortia that are listed in Table 1. The strategy was to perform deep exome sequencing of individuals, 24,991 with T2D and 24,953 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. The T2D-GENES, ProDIGY and SIGMA studies, sequencing was performed at the Broad Institute using the Agilent v2 capture reagent or Illumina Rapid Capture on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, two of the cohorts below are not in dbGaP, due to the samples not being consented for deposition. This includes the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study and Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) study. The Exome Sequencing Project (ESP) was deposited in dbGaP as part of their initial study and the phs numbers for that project can be found here: https://esp.gs.washington.edu/drupal/dbGaP_Releases. Table 1. 52,000 sample T2D Case/Control Whole Exome Sequencing Studies Ancestry Consortia Study Countries of Origin # Cases # Controls African American T2D-GENES Project 1 Jackson Heart Study US 500 526 African American T2D-GENES Project 1 Wake Forest School of Medicine Study US 518 530 African American ESP Exome Sequencing Project (ESP) US 467 1374 African American T2D-GENES Follow-Up Study BioMe Biobank Program (BioMe) US 1297 1256 East Asian T2D-GENES Project 1 Korea Association Research Project Korea 526 561 East Asian T2D-GENES Project 1 and Follow-Up Study Singapore Diabetes Cohort Study; Singapore Prospective Study Program Singapore (Chinese) 1486 1568 East Asian T2D-GENES Follow-Up Study Korea SNUH South Korea 450 475 East Asian T2D-GENES Follow-Up Study Research Studies in Hong Kong (Hong Kong) Hong Kong 493 485 European T2D-GENES Project 1 Ashkenazi US, Israel 506 352 European T2D-GENES Project 1 Metabolic Syndrome in Men Study (METSIM) Finland 484 498 European GoT2D Finland-United States Investigation of NIDDM Genetics (FUSION) Study Finland 472 476 European GoT2D Kooperative Gesundheitsforschung in der Region Augsburg (KORA) Germany 97 90 European GoT2D UK Type 2 Diabetes Genetics Consortium (UKT2D) UK 322 320 European GoT2D Malmö-Botnia Study Finland, Sweden 478 443 European LuCamp Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) Denmark 997 997 European ESP Exome Sequencing Project (ESP) US 390 2843 European T2D-GENES Follow-Up Study Genetics of Diabetes and Audit Research Tayside Study (GoDARTS) Scotland, UK 960 966 European T2D-GENES Follow-Up Study Framingham Heart Study (FHS) US 396 596 Hispanic T2D-GENES Project 1 San Antonio Family Heart Study, San Antonio Family Diabetes/ Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component US 272 218 Hispanic T2D-GENES Project 1 and SIGMA v2 Starr County, Texas US 1762 1738 Hispanic SIGMA v1 Mexico City Diabetes Study Mexico 281 549 Hispanic SIGMA v1 and SIGMA v2 Multiethnic Cohort (MEC) US 1476 1443 Hispanic SIGMA v1 and SIGMA v2 UNAM/INCMNSZ Diabetes Study (UIDS) Mexico 1998 1977 Hispanic SIGMA v1 and SIGMA v2 Diabetes in Mexico Study (DMS) Mexico 1522 1546 Multiethnic ProDIGY Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) US 3097 0 Multiethnic ProDIGY SEARCH for Diabetes in Youth (SEARCH) US 553 0 South Asian T2D-GENES Project 1 London Life Sciences Population Study (LOLIPOP) UK (Indian Asian) 531 538 South Asian T2D-GENES Project 1 and Follow-Up Study Singapore Indian Eye Study Singapore (Indian Asian) 1640 1478 South Asian T2D-GENES Follow-Up Study Pakistan Risk of Myocardial Infarction Study (PROMIS) Pakistan 914 932 The research studies in Hong Kong contributed 493 cases and 485 controls to T2D-GENES Follow-Up study.

  Study phs001504

• Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples (T2D-GENES) Follow-Up Study: BioMe Biobank Program

  The ~52,000 sample Type 2 Diabetes Exome Sequencing project is a collaboration of six consortia with various funding mechanisms that have joined together to investigate genetic variants for type 2 diabetes (T2D) using the largest T2D case/control sample set compiled to date. This includes samples from: Type 2 Diabetes Genetic Exploration by Next-generation sequencing in Multi-Ethnic Samples (T2D-GENES) Genetics of Type 2 Diabetes (GoT2D) Exome Sequencing Project (ESP) Slim Initiative in Genomic Medicine for the Americas (SIGMA) Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCAMP) Progress in Diabetes Genetics in Youth (ProDIGY) This data generated from the BioMe Biobank cohort was part of the T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) consortium, which is a NIDDK-funded international research consortium that seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. The T2D-GENES Project is a multi-ethnic sequencing study designed to assess whether less common variants play a role in T2D risk and to assess similarities and differences in the distribution of T2D risk variants across ancestry groups. The individuals were obtained from over 20 cohorts across the 6 consortia that are listed in Table 1. The strategy was to perform deep exome sequencing of individuals, 24,991 with T2D and 24,953 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. The T2D-GENES, ProDIGY and SIGMA studies, sequencing was performed at the Broad Institute using the Agilent v2 capture reagent or Illumina Rapid Capture on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, two of the cohorts below are not in dbGAP, due to the samples not being consented for deposition. This includes the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study and Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) study. The Exome Sequencing Project (ESP) was deposited in dbGAP as part of their initial study and the phs numbers for that project can be found here: https://esp.gs.washington.edu/drupal/dbGaP_Releases. Table 1. 52,000 sample T2D Case/Control Whole Exome Sequencing Studies Ancestry Consortia Study Countries of Origin # Cases # Controls African American T2D-GENES Project 1 Jackson Heart Study US 502 527 African American T2D-GENES Project 1 Wake Forest School of Medicine Study US 518 532 African American ESP Exome Sequencing Project (ESP) US 467 1374 African American T2D-GENES Follow-Up Study BioMe Biobank Program (BioMe) US 1294 1254 East Asian T2D-GENES Project 1 Korea Association Research Project Korea 526 561 East Asian T2D-GENES Project 1 and Follow-Up Study Singapore Diabetes Cohort Study; Singapore Prospective Study Program Singapore (Chinese) 1486 1568 East Asian T2D-GENES Follow-Up Study Korea SNUH South Korea 450 475 East Asian T2D-GENES Follow-Up Study Research Studies in Hong Kong (Hong Kong) Hong Kong 493 485 European T2D-GENES Project 1 Ashkenazi US, Israel 506 355 European T2D-GENES Project 1 Metabolic Syndrome in Men Study (METSIM) Finland 484 498 European GoT2D Finland-United States Investigation of NIDDM Genetics (FUSION) Study Finland 472 476 European GoT2D Kooperative Gesundheitsforschung in der Region Augsburg (KORA) Germany 97 90 European GoT2D UK Type 2 Diabetes Genetics Consortium (UKT2D) UK 322 320 European GoT2D Malmö-Botnia Study Finland, Sweden 478 443 European LuCamp Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) Denmark 997 997 European ESP Exome Sequencing Project (ESP) US 390 2843 European T2D-GENES Follow-Up Study Genetics of Diabetes and Audit Research Tayside Study (GoDARTS) Scotland, UK 960 966 European T2D-GENES Follow-Up Study Framingham Heart Study (FHS) US 396 596 Hispanic T2D-GENES Project 1 San Antonio Family Heart Study, San Antonio Family Diabetes/ Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component US 272 218 Hispanic T2D-GENES Project 1 and SIGMA v2 Starr County, Texas US 1762 1738 Hispanic SIGMA v1 Mexico City Diabetes Study Mexico 281 549 Hispanic SIGMA v1 and SIGMA v2 Multiethnic Cohort (MEC) US 1476 1443 Hispanic SIGMA v1 and SIGMA v2 UNAM/INCMNSZ Diabetes Study (UIDS) Mexico 1998 1977 Hispanic SIGMA v1 and SIGMA v2 Diabetes in Mexico Study (DMS) Mexico 1522 1546 Multiethnic ProDIGY Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) US 3097 0 Multiethnic ProDIGY SEARCH for Diabetes in Youth (SEARCH) US 553 0 South Asian T2D-GENES Project 1 London Life Sciences Population Study (LOLIPOP) UK (Indian Asian) 531 538 South Asian T2D-GENES Project 1 and Follow-Up Study Singapore Indian Eye Study Singapore (Indian Asian) 1640 1478 South Asian T2D-GENES Follow-Up Study Pakistan Genomic Resource (PGR) Pakistan 914 932 The BioMe Biobank study contributed 1294 cases and 1254 controls to T2D-GENES Follow-Up Study.

  Study phs001490

• Type 2 Diabetes Genetic Exploration by Next-generation Sequencing in Multi-Ethnic Samples (T2D-GENES) Follow up Study: Pakistan Genomic Resource (PGR)

  The ~52,000 sample Type 2 Diabetes Exome Sequencing project is a collaboration of six consortia with various funding mechanisms that have joined together to investigate genetic variants for type 2 diabetes (T2D) using the largest T2D case/control sample set compiled to date. This includes samples from: Type 2 Diabetes Genetic Exploration by Next-generation sequencing in Multi-Ethnic Samples (T2D-GENES) Genetics of Type 2 Diabetes (GoT2D) Exome Sequencing Project (ESP) Slim Initiative in Genomic Medicine for the Americas (SIGMA) Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCAMP) Progress in Diabetes Genetics in Youth (ProDIGY) This data generated from the Pakistan Genomic Resource (PGR) cohort was part of the T2-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) consortium, which is a NIDDK-funded international research consortium that seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. The T2D-GENES Project is a multi-ethnic sequencing study designed to assess whether less common variants play a role in T2D risk and to assess similarities and differences in the distribution of T2D risk variants across ancestry groups. The individuals were obtained from over 20 cohorts across the 6 consortia that are listed in Table 1. The strategy was to perform deep exome sequencing of individuals, 24,991 with T2D and 24,953 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. The T2D-GENES, ProDIGY and SIGMA studies, sequencing was performed at the Broad Institute using the Agilent v2 capture reagent or Illumina Rapid Capture on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, two of the cohorts below are not in dbGAP, due to the samples not being consented for deposition. This includes the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study and Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) study. The Exome Sequencing Project (ESP) was deposited in dbGAP as part of their initial study and the phs numbers for that project can be found here: https://esp.gs.washington.edu/drupal/dbGaP_Releases. Table 1. 52,000 sample T2D Case/Control Whole Exome Sequencing Studies Ancestry Consortia Study Countries of Origin # Cases # Controls African American T2D-GENES Project 1 Jackson Heart Study US 502 527 African American T2D-GENES Project 1 Wake Forest School of Medicine Study US 518 532 African American ESP Exome Sequencing Project (ESP) US 467 1374 African American T2D-GENES Follow-Up Study BioMe Biobank Program (BioMe) US 1297 1256 East Asian T2D-GENES Project 1 Korea Association Research Project Korea 526 561 East Asian T2D-GENES Project 1 and Follow-Up Study Singapore Diabetes Cohort Study; Singapore Prospective Study Program Singapore (Chinese) 1486 1568 East Asian T2D-GENES Follow-Up Study Korea SNUH South Korea 450 475 East Asian T2D-GENES Follow-Up Study Research Studies in Hong Kong (Hong Kong) Hong Kong 493 485 European T2D-GENES Project 1 Ashkenazi US, Israel 506 355 European T2D-GENES Project 1 Metabolic Syndrome in Men Study (METSIM) Finland 484 498 European GoT2D Finland-United States Investigation of NIDDM Genetics (FUSION) Study Finland 472 476 European GoT2D Kooperative Gesundheitsforschung in der Region Augsburg (KORA) Germany 97 90 European GoT2D UK Type 2 Diabetes Genetics Consortium (UKT2D) UK 322 320 European GoT2D Malmö-Botnia Study Finland, Sweden 478 443 European LuCamp Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) Denmark 997 997 European ESP Exome Sequencing Project (ESP) US 390 2843 European T2D-GENES Follow-Up Study Genetics of Diabetes and Audit Research Tayside Study (GoDARTS) Scotland, UK 960 966 European T2D-GENES Follow-Up Study Framingham Heart Study (FHS) US 396 596 Hispanic T2D-GENES Project 1 San Antonio Family Heart Study, San Antonio Family Diabetes/ Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component US 272 218 Hispanic T2D-GENES Project 1 and SIGMA v2 Starr County, Texas US 1762 1738 Hispanic SIGMA v1 Mexico City Diabetes Study Mexico 281 549 Hispanic SIGMA v1 and SIGMA v2 Multiethnic Cohort (MEC) US 1476 1443 Hispanic SIGMA v1 and SIGMA v2 UNAM/INCMNSZ Diabetes Study (UIDS) Mexico 1998 1977 Hispanic SIGMA v1 and SIGMA v2 Diabetes in Mexico Study (DMS) Mexico 1522 1546 Multiethnic ProDIGY Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) US 3097 0 Multiethnic ProDIGY SEARCH for Diabetes in Youth (SEARCH) US 553 0 South Asian T2D-GENES Project 1 London Life Sciences Population Study (LOLIPOP) UK (Indian Asian) 531 538 South Asian T2D-GENES Project 1 and Follow-Up Study Singapore Indian Eye Study Singapore (Indian Asian) 1640 1478 South Asian T2D-GENES Follow-Up Study Pakistan Genomic Resource (PGR) Pakistan 903 930 The PGR study contributed 903 cases and 930 controls to T2D-GENES Follow-Up Study.

  Study phs001552

• Immunophenotyping in a COVID-19 Cohort (IMPACC) Transcriptomics and Genotyping Assays

  IMPACC (IMmunoPhenotyping Assessment in a COVID-19 Cohort) is a prospective longitudinal cohort study (NCT04378777) launched in May 2020 in response to the worldwide pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It was funded by the National Institute of Allergy and Infectious Diseases (NIAID) of the National Institute of Health (NIH). Patient enrollment and sample analysis involved 20 hospitals associated with 15 U.S. biomedical research centers and 11 centralized Core immunoassay laboratories.The study aimed to enable the identification of potential biomarkers and inform future therapeutic interventions using a longitudinal approach encompassing the whole disease course for a comprehensive understanding of the contributions of the pathogen and host immune response in modulating the manifestations, severity, and post-acute sequelae of the infection. IMPACC enrolled close to 1200 adult symptomatic, molecularly confirmed hospitalized COVID-19 patients in the study within 48 hours of their hospital admission. Clinical data and biological samples (blood, mid-turbinate nasal swabs, and esophageal aspirant) were collected according to minimal risk guidelines at enrollment and on days 4, 7, 14, 21, and 28. Biological samples were collected at 3-month intervals up to 12 months after hospital discharge to assess functional and immunologic recovery measures. Sample collection, processing, and storage procedures were standardized across sites, and samples were transported to centralized assay-specific core laboratories (Core Labs) in batches for testing and analysis. The description of outcome severity was not limited to survival versus death but encompassed a clinical trajectory approach using 5 groups leveraging longitudinal data based on time in the hospital, disease severity by ordinal scale based on the degree of respiratory illness, and presence or absence of limitations at discharge. Disease severity was assessed based on the degree of respiratory illness using a 7-point ordinal scale adapted from the World Health Organization COVID-19 and NIAID disease ordinal severity scales. DNA for genetic analyses was collected from whole blood at a single time point. To identify any genomic determinants of severe COVID-19 disease, single-nucleotide polymorphism (SNP) genotyping and exome sequencing were conducted to assess genetic variants associated with individual susceptibility to severe disease. In addition, IMPACC included bulk transcriptomic analysis of upper airway (nasal swaps) samples, lower airway (esophageal aspirant) samples, and peripheral blood mononuclear cells (PBMCs) to evaluate dynamic changes in cellular composition and cellular response during the course of the disease. Reads were aligned to the GRCh38 human reference genome. Additional information for the IMPACC study has been submitted to The Immunology Database and Analysis Portal (ImmPort) under study accession SDY1760. Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Dr. Steven Kleinstein (steven.kleinstein@yale.edu).

  Study phs002686

• Longitudinal Immune Dynamics of Mild COVID-19 Define Signatures of Recovery and Persistence

  SARS-CoV-2 has infected over 160 million and caused more than 3 million deaths to date. Most individuals (>80%) have mild symptoms and recover in the outpatient setting, but detailed studies of immune responses have focused primarily on moderate to severe COVID-19. We deeply profiled the longitudinal immune response in individuals with mild COVID beginning with early time points post-infection (1-15 days) and proceeding through convalescence to >100 days after symptom onset. We correlated data from single cell analyses of peripheral blood cells, serum proteomics, virus-specific cellular and humoral immune responses, and clinical metadata. Acute infection was characterized by vigorous coordinated innate and adaptive activation, including an early cellular and proteomic signature that correlated with the amplitude of virus-specific humoral responses after day 30. We characterized signals associated with recovery and convalescence to define a new signature of inflammatory cytokines, gene expression, and chromatin accessibility that persists in individuals with post-acute sequelae of SARS-CoV-2 infection (PASC).

  Study phs002576

• Genomic Analysis of Relapsed/Refractory DLBCL

  Molecular phenotyping techniques have established a landscape of genomic variants in diagnostic Diffuse Large B Cell Lymphoma (DLBCL), however these have not yet been applied in large scale studies of relapsed/refractory DLBCL resulting in incomplete characterization of mechanisms driving tumor progression and treatment resistance. Here, we performed an integrated multiomic analysis on relapsed/refractory DLBCL samples. Tumors from 87 relapsed/refractory DLBCL patients were included in this study and were available for data deposition [Tumor whole exome sequencing (WES): n=75, Germline WES: n=73, RNA sequencing (RNA-Seq): n=72]. Tumor DNA was extracted from formalin-fixed, paraffin embedded (FFPE) tissue sections, germline DNA was extracted from blood, and WES of all samples was performed using the Agilent SureSelect XT All Exon v6 kit and sequencing was carried out on an Illumina NovaSeq, 100 x 2 paired end reads. Tumor RNA was extracted from FFPE tissue sections and RNA-Seq was performed using the Illumina TruSeq RNA Exome Kit (Illumina) for library preparation, sequencing platform HiSeq 4000, 100 x 2 paired end reads.

  Study phs003868

• Identification of improved IL28B SNPs and haplotypes for prediction of drug response in treatment of hepatitis C using massively parallel sequencing in a cross-sectional European cohort

  The hepatitis C virus infects nearly 3% of the World’s population, causing severe liver disease in many. Standard of care therapy is currently pegylated interferon alpha and ribavirin (PegIFN/R), which is effective in less than half of those infected with the most common viral genotype. Two IL28B SNPs, rs8099917 and rs12979860, predict response to (PegIFN/R) therapy in treatment of hepatitis C virus infection. These SNPs were identified in genome wide analyses using Illumina genotyping chips. In people of European ancestry, there are 6 common (>1%) haplotypes for IL28B, one tagged by rs8099917 minor allele, four tagged by rs12979860. We used massive parallel sequencing of the IL28B and IL28A gene regions generated by PCR from pooled DNA samples from 100 responders and 99 non-responders to therapy, to identify common variants. Variants that had high odds ratios and were validated were then genotyped in a cohort of 905 responders and non-responders. Their predictive power was assessed, alone and in combination with HLA-C. Only SNPs in the IL28B linkage disequilibrium block predicted drug response. Eighteen SNPs were identified with evidence for association with drug response, and with a high degree of confidence in the sequence call. We found that two SNPs, rs4803221 (homozygote minor allele positive predictive value (PPV) of 77%) and rs7248668 (PPV 78%), predicted failure to respond better than the current best, rs8099917 (PPV 73%) and rs12979860 (PPV 68%) in this cross-sectional cohort. The best SNPs tagged a single common haplotype, haplotype 2. Genotypes predicted lack of response better than alleles. However, combination of IL28B haplotype 2 carrier status with the HLA-C C2C2 genotype, which has previousl y been reported to improve prediction in combination with IL28B, provides the highest PPV (80%). The haplotypes present alternative putative transcription factor binding and methylation sites. Massive parallel sequencing allowed identification and comparison of the best common SNPs for identifying treatment failure in therapy for HCV SNPs tagging a single haplotype have the highest PPV, especially in combination with HLA-C. The functional basis for the association may be due to altered regulation of the gene. These approaches have utility in improving diagnostic testing and identifying causal haplotypes or SNPs.

  Study EGAS00001000096

• Acute Respiratory Distress Network (ARDSNet) Studies 01 and 03 Lower Versus Higher Tidal Volume, Ketoconazole Treatment and Lisofylline Treatment (ARMA/KARMA/LARMA) (ARDSNet-ARMA/KARMA/LARMA-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Biospecimens Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from ARDSNet-ARMA/KARMA/LARMA include plasma, serum and urine. Please note that use of biospecimens in genetic research is subject to a tiered consent. Objectives The ARDS Network is a consortium of clinical centers and a coordinating center to design and test novel therapies for the treatment of Acute Lung Injury (ALI) and Acute Respiratory Distress Syndrome (ARDS). The primary objective of the KARMA trial was to investigate the efficacy and safety of Ketoconazole and Respiratory Management in the treatment of ALI and ARDS. The Ketoconazole arm of the study was later stopped due to an inability to show efficacy. Participants continued to be randomized to the respiratory management arms of the study (ARMA), which compared two ventilator strategies: a tidal volume of 6 mL/kg versus 12 mL/kg. The LARMA phase of the study investigated the efficacy of Lisofylline and Respiratory Management. Background Participants suffering from ARDS are extremely ill, require mechanical ventilation and, despite improvements in medical care and technology, had a mortality rate as high as 50 percent. An excessive inflammatory response is characteristic of ALI of which ARDS represents the most severe end of the pathophysiologic spectrum. The inflammatory response includes increased numbers of neutrophils activated to produce cytokines, proteases, and reactive oxygen intermediates. Pulmonary injury may also be enhanced by alveolar and tissue macrophages as a producer of vasoactive substances, neutrophil chemoattractants, and procoagulant substances. Ketoconazole, a synthetic antifungal imidazole, also has anti-inflammatory activities and may inhibit neutrophil recruitment via several different pathways known to be involved in the development of ALI and ARDS. Lisofylline causes a marked decrease in the circulating levels of the major oxidizable species of free fatty acids and also inhibits proinflammatory intracellular signaling. Mechanical ventilation in participants with ALI and ARDS have traditionally used tidal volumes of 10 to 15 ml per kilogram of body weight. These large tidal volumes are often necessary to achieve normal partial pressure of arterial carbon dioxide and pH, but may induce inflammatory responses through disruption of pulmonary epithelium and endothelium. Mechanical ventilation at lower tidal volumes may reduce injurious lung stretch and decrease the inflammatory response. Participants The Ketoconazole and Lisofylline trials were designed as 2 x 2 factorials and included 220 participants in each trial. A total of 860 participants were randomized into the ventilator management trial. Participants enrolled in the Lisofylline or Ketoconozole studies had to be concurrently enrolled in the ventilator management study and were first randomized into a ventilator strategy and then to drug or placebo. Conclusions Ketoconazole was found to be safe but did not reduce mortality, duration of mechanical ventilation, or improve lung function. Lisofylline was also found to be safe and to have no beneficial effect for participants with ALI or ARDS. Ventilation at lower tidal volumes resulted in reduced mortality and an increase in the number of days without ventilator support. (PMIDs: 10789668, 11902249, 10793162).

  Study phs003734

• Common Fund (CF) Genotype-Tissue Expression Project (GTEx)

  Lay Description The aim of the Genotype-Tissue Expression (GTEx) Project is to increase our understanding of how changes in our genes affect human health and disease with the ultimate goal of improving health care for future generations. GTEx will create a database that researchers can use to study how inherited changes in genes lead to common diseases. GTEx researchers are studying genes in different tissues obtained from many different people. The GTEx project also includes a study of the GTEx donor consent process - this study will help ensure that the consent process and other aspects of the project effectively address the concerns and expectations of participants in the study. GTEx is a pioneering project that uses state-of-the-art protocols for obtaining and storing a large range of organs and tissues, and for testing them in the lab. Until now, no project has analyzed genetic variation and expression in as many tissues from the same person in such a large population as planned for GTEx. Scientific Description Understanding the role of variation in the human genome is crucial to elucidating genetic contributions to human health and disease. Despite the results of genome-wide association studies (GWAS) documenting strong statistical associations between genetic variation and human traits, the functional role for most of these variants is largely unexplained. Nearly 90% of these GWAS-implicated sites lie outside of protein-coding sequences, suggesting that these variants might regulate gene expression. The goal of the Genotype-Tissue Expression (GTEx) project is to establish a resource database and tissue biobank in which to study the relationship between genetic variation and gene expression and other molecular phenotypes in reference/non-diseased tissues. The ultimate resource will include approximately 960 post-mortem donors with several dozen tissues from each, a resource large enough to study both cis- and trans- gene expression quantitative trait loci (eQTLs). Some tissue will also be banked for additional molecular analyses. To request biosamples, please see the Biobank page for more information. GTEx was initially funded as a 2-year pilot project by the NIH Common Fund (CF) in 2010, and has been scaled up after demonstration of feasibility. The project will collect and analyze RNA levels in many different human tissues and each donor will be characterized for germline genetic variation through dense genotyping arrays and sequencing of either whole exomes or whole genomes. By treating RNA expression levels as quantitative traits, eQTLs will be identified as sites containing genetic variation that correlate with changes in RNA expression. Such eQTLs have been associated with 4%-12% of expressed human genes, and with common complex human diseases, including obesity, atherosclerosis, type 2 diabetes, Crohn's disease, and asthma. Additionally, few studies have examined the tissue specificity of eQTLs. A subset of banked tissue samples will also be analyzed for other molecular phenotypes, such as DNA methylation, DNaseI hypersensitivity sites, and proteomics. The GTEx project will thus serve as a resource database and tissue bank for many future studies, especially for understanding the functional basis of inherited susceptibility to disease. All GTEx releases since Version 5 follow the NIH Genomic Data Sharing (GDS) Policy whereby there are no restrictions on use or publication after release. Additional information about the GTEx Data Release and Publication policy can be found on the GTEx Data Portal at www.gtexportal.org.

  Study phs000424

• Study on the Genetics of Alcoholism (COGA): African American Family GWAS

  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 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. As part of COGA, a set of informative African American families were selected to have Genome-Wide Association data obtained within families. Genotyping was performed using the Illumina Omni2.5_080814_1 chip to genotype 3,438 subjects selected from densely affected families. Genotyping was performed at CIDR. This sample complements a set of densely affected European American families previously made available under dbGaP study accession phs000763. In addition, exome sequencing data on a subset of individuals with GWAS were added in version 2.For version 3, 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 abuse variables are made available in version 3. 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 phs000976