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• The National Institute of Neurological Disorders and Stroke (NINDS) Stroke Genetics Network (SiGN)

  The NINDS Stroke Genetics Network (SiGN) is a large international collaboration designed to detect genetic variants that predispose to subtypes of ischemic stroke. The study implements a genome wide association study (GWAS) methodology with all stroke cases undergoing phenotypic and stroke-subtype classification using the same web-based Causative Classification of Stroke (CCS) system, with data entered by trained and certified adjudicators at participating Research Centers (GRC's). SiGN includes ischemic stroke cases from 24 GRC's, 13 from the US and 11 from Europe. Each GRC has access to well-characterized ischemic stroke cases in which extensive phenotype data and high-quality DNA was available. Genome-wide data was available for many cases and for those without, new genome-wide genotyping, including exome chip genotyping of rare variants, was done through the Center for Inherited Diseases Research (CIDR). To maximize power for subtype analyses, genotyping resources were allocated almost exclusively to cases. With few exceptions, controls were drawn from studies with publicly available genome-wide data.

  Study phs000615

• The Northern Manhattan Family Study - a Sub-Study of the Epidemiologic Study of Stroke Outcome in 3 Ethnic Groups: The Northern Manhattan Study

  The Northern Manhattan Family Study is a sub-study of the Northern Manhattan Study (NOMAS), a population-based cohort study investigating stroke and stroke risk factors among individuals from three ethnic groups residing in northern Manhattan. The overall goal for the Northern Manhattan Family Study was to determine the genetic factors associated with stroke precursor phenotypes. A subset of Caribbean Hispanic probands from the NOMAS Study were selected for inclusion in the family study. Selected probands were at high risk for cardiovascular disease, defined as either 1. Having a sibling with a history of myocardial infarction or stroke, or 2. Having two of the following three risk phenotypes above the 75th percentile in NOMAS; maximal carotid plaque thickness, left ventricular mass or homocysteine level. Probands for the family study were enrolled in northern Manhattan and family members were enrolled at two locations: New York at Columbia University and in the Dominican Republic (DR) at the Clinicas Corazones Unidos in Santo Domingo. A subset of Caribbean Hispanic NOMAS participants were included as a replication sample.

  Study phs002406

• Adolescent Idiopathic Scoliosis (AIS) 1000 Exomes Study

  Adolescent idiopathic scoliosis (AIS) is the most common pediatric spinal deformity. Although the Bracing in AIS Trial (BrAIST) recently demonstrated the effectiveness of bracing for preventing scoliosis progression in some patients, more than 20,000 children undergo major spinal fusion surgery at an annual cost of $3 billion. Spinal fusion surgery is a major operation with considerable risks and complications. Accurate methods of predicting curve progression are needed to develop personalized prevention strategies for those at high risk and to eliminate screening and treatment of those at low risk of progression. Previously identified risk factors for scoliosis curve progression include sex, age of onset, curve type, and presence of an underlying disorder. However, currently available algorithms for predicting AIS curve progression are inaccurate, possibly because the role of genetic factors has been largely unexplored. Because there is little a priori knowledge of the genetic variants involved in AIS pathology, an unbiased genome-wide approach is likely to provide the best opportunity to comprehensively identify disease-associated genes. This is a multicenter exome sequencing study of extreme cases with severe scoliosis.

  Study phs001677

• NHLBI GO-ESP: Family Studies (Dilated Cardiomyopathy)

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. The goals for this project are to conduct exome sequencing for novel dilated cardiomyopathy (DCM) gene discovery in families with DCM. These families have already been sequenced for 15 DCM genes, accounting for approximately 75% of known genetic cause, without rare coding variants identified.

  Study phs000581

• Molecular Genetics of Schizophrenia - nonGAIN Sample (MGS_nonGAIN)

  This study is part of the Molecular Genetics of Schizophrenia (MGS) genome wide association study (GWAS) of 3,972 cases (2,686 EA and 1,286 AA) and 3,629 controls (2,656 EA and 973 AA) (analyzed sample remaining after quality control exclusions), comprised of European ancestry (EA) and African American (AA) samples. We genotyped about half of the EA sample and almost all of the AA sample under the auspices of the Genetic Association Information Network (GAIN) with the Affymetrix 6.0 platform at the Broad Institute. The remainder of the included sample was also genotyped with the Affymetrix 6.0 platform at the Broad Institute, and we refer to this component as the nonGAIN sample. Cases met criteria for schizophrenia (SCZ) or schizoaffective disorder (SA) per the Diagnostic and Statistical Manual of Mental Disorders version IV (DSM-IV) for all three collections (SGI, MGS1, and MGS2) comprising these cases. However, for the older SGI collection, codes for the secondary diagnoses refer to the older DSM-III-R version. Controls were screened briefly and excluded if they endorsed a history of these illnesses.

  Study phs000167

• A Pharmcogenetic Study of Bipolar Disorder in a Taiwanese Han Chinese Population (TWBP)

  Objective: To identify genetic variants associated with response to lithium prophylaxis treatment. Materials: 294 bipolar I (BPI) patients receiving lithium treatment, a subset of 1761 bipolar I (BPI) patients recruited by the Taiwan Bipolar Consortium. Lithium response was assessed based on the Alda Scale. Methods: Responders to lithium treatment were defined if the patients' Alda Scale > 4, 5, 6, and 7. Genome-wide association (GWA) analysis was carried out on the 294 BPI patients for the 4 definitions of responders. The SNPs showing strongest association in the GWAS were then tested for association in a replication sample of 100 patients and further tested in a prospective follow-up series of 24 patients. Results: Two SNPs on GADL1 showed the strongest associations in the four GWA analyses and in the replication set of 100 patients. These two SNPs had a sensitivity of 0.93 for predicting lithium response and differentiated between the good and poor responders in the follow-up cohort. Summary: These genetic variants are associated with response to lithium prophylaxis treatment for BPI.

  Study phs000692

• Circulating, Cell-Free DNA Methylation Patterns Indicate Cellular Sources of Allograft Injury after Liver Transplant

  Post-transplant complications reduce allograft and recipient survival. Current approaches for detecting allograft injury non-invasively are limited and do not differentiate between cellular mechanisms. Here, we monitor cellular damages after liver transplants from cell-free DNA (cfDNA) fragments released from dying cells into the circulation. We analyzed longitudinal blood samples collected from patients at different time points after transplant. Sequence-based methylation of cfDNA fragments were mapped to an atlas of cell-type-specific DNA methylation patterns derived from 476 methylomes of purified cells. For liver cell types, DNA methylation patterns and multi-omic data integration show distinct enrichment in open chromatin and regulatory regions functionally important for the respective cell types. We find that multi-tissue cellular damage post-transplant recovers in patients without allograft injury during the first post-operative week. However, sustained elevation of hepatocyte and biliary epithelial cfDNA within the first month indicates early-onset allograft injury. Further, cfDNA composition differentiates amongst causes of allograft injury indicating the potential for non-invasive monitoring and timely intervention.

  Study phs003610

• Fetal Genomics Consortium (FGC)

  Many of the congenital anomalies and associated genomic variants identified during prenatal care are rare, requiring aggregation and harmonization to assure their appropriate clinical interpretation and to support the expanding utility of genomics in perinatal medicine. The primary step in accomplishing this is the creation of interoperability allowing collection, collaborative storage, dissemination and use of harmonized and vetted genomic and phenotypic data. The overall goal of this project is to generate a prenatal repository for both clinical care and research ensuring data are Findable; Accessible; Interoperable; and Reusable. The specific goals are: (1) collect and organize data contributions from multiple sites using the cloud-based Terra platform; (2) establish a governance structure for data contributions across sites; (3) develop and implement a pipeline for phenotype driven analysis and implementation of fetal specific Phenopackets on Terra; (4) generate a searchable callset of genomic variants and phenotype features on Terra; and (5) explore methods for facilitating broad access and sharing of longitudinal phenotype and genomic data facilitating genomic analysis in the prenatal space.

  Study phs003193

• dbGaP Collection: NIH Autism -omics Studies

  Autism Spectrum Disorders (ASD) are early onset neurodevelopmental syndromes characterized by impairments in reciprocal social interaction and communication, accompanied by restricted and repetitive behaviors. ASDs afflict ~1% of the human population, and represent a major public health burden. Evidence for the etiology of ASD has consistently pointed to a strong genetic component, though the genetic architecture is indisputably complex. This dbGaP Collection consists of studies that include GWAS, sequencing (targeted, exome, whole genome), transcriptomics, etc, across many different cohorts. Many of the datasets have been curated and harmonized with NDAR prior to submission to dbGaP. Researchers who request and are approved to access this collection will be granted access to all related substudies in dbGaP as well as all NDAR data. Individual level genomics data will only be available for download through dbGaP along with minimal phenotype and pedigree information. Detailed phenotype and available imaging data related to these same research subjects are available for query and download within NDAR. The NDAR GUID will allow individual genomic data to be associated with all NDAR data collected for those subjects.

  Study phs000764

• Ten colorectal cancer patients with locally advanced primary tumors who underwent primary tumor resection following neoadjuvant chemotherapy (NAC).

  Background We aim to investigate the utility of serial gene mutation tracking for locally advanced CRC in those who underwent curative resection following neoadjuvant chemotherapy. Methods We prospectively collected 10 locally advanced CRC cases for which curative resection was performed following preoperative neoadjuvant chemotherapy. Tissues from the primary tumour, distant metastatic tumours, and blood plasma were obtained during serial treatment. Comprehensive mutation analysis of 47 cancer-associated genes was performed using a pre-designed gene panel and next-generation sequencing. Results All cases showed a partial response to neoadjuvant chemotherapy, and pathological R0 resection was accomplished. In primary tumours, non-synonymous mutations were detected at between 1 and 14 sites before chemotherapy and at between 1 and 2 sites after. Founder mutations were precisely detected in blood plasma and metastatic tumours during longitudinal treatment. Conclusions Serial mutational analysis indicated that subclonal selection occurs during chemotherapy and that plasma can substitute for tumourous tissue in mutational analysis for drug selection and treatment decisions.

  Study JGAS000222

• Host factors dictate gut microbiome alterations in chronic kidney disease more strongly than to kidney function

  Despite recent progress, microbial markers in Chronic Kidney Disease (CKD) remain inconclusive. We combined quantitative faecal metagenomics (N=130 CKD cohort) and cross-study biomarker comparisons (Ntotal=4420) to study microbiome associations with glomerular filtration rate (eGFR; kidney function) and 4-year CKD progression. Transit time (TT) and medications primarily explained microbiome variation, trumping eGFR-related effects. Metagenome analysis showed increased p-cresol and indole synthesis potential and decreased plant-to-animal CAZyme ratios with lower eGFR, coupled to a Bact1 to Rum enterotype shift, suggesting saccharolytic-to-proteolytic microbiome transitions linked to dietary guidelines and slowed-down TT. Peritoneal dialysis patients showed increased (dysbiotic) Bact2 prevalence and linked intestinal inflammation. Only Escherichia coli, an unnamed Alistipes species and Bifidobacterium adolescentis were confounder-independent markers for eGFR, but these nor previous markers convincingly replicated across 11 studies. No predictors for CKD progression were found. Together, poor evidence for microbiome biomarkers but substantial eGFR-independent effects were found, suggesting potential for nutritional and TT interventions in CKD.

  Study EGAS50000000646

• Clinical Cancer Genomic Profiling by Three-Platform Sequencing of Whole Genome, Whole Exome and Transcriptome

  To evaluate the potential of an integrated clinical test to detect diverse classes of somatic and germline mutations relevant to pediatric oncology, we performed three-platform whole-genome (WGS), whole exome (WES) and transcriptome (RNA-Seq) sequencing of tumors and normal tissue from 78 pediatric cancer patients in a CLIA-certified, CAP-accredited laboratory. Our analysis pipeline achieves high accuracy by cross-validating variants between sequencing types, thereby removing the need for confirmatory testing, and facilitates comprehensive reporting in a clinically-relevant timeframe. Three-platform sequencing has a positive predictive value of 97-99%, 99% and 91% for somatic SNVs, indels and structural variations, respectively, based on independent experimental verification of 15,225 variants. We report 240 pathogenic variants across all cases, including 84 of 86 known from previous diagnostic testing (98% sensitivity). Combined WES and RNA-Seq, the current standard for precision oncology, achieved only 78% sensitivity. These results emphasize the critical need for incorporating WGS in pediatric oncology testing.

  Study EGAS00001002217

• Whole genome sequencing data of pediatric B-other subtype acute lymphoblastic leukemia

  For a long time, approximately 70% of childhood B-ALL cases could be classified routinely, and the remaining 30% were classified into the “B-other” group lacking the known genetic features. However, more recently, new genomic tools have uncovered new subtypes among the B-other groups. Approximately 10% of B-ALL cases lack the recurrent genetic abnormalities, and are referred as "B-other". They are typically more heterogeneous than other subtypes of B-ALL, and their prognoses are more variable. In a more recent update of the B-ALL classification, 27 subtypes were identified (Arber et al., 2022). The identification of some of these subtypes is dependent on NGS methods, such as RNA sequencing, which are not routinely used in all clinical laboratories. For example, ETV6::RUNX1-like and DUX4-rearranged subtypes have been identified using RNA sequencing. For this study, subtype predictions for some of the cases is acquired from ALLIUM (Krali et al., NPJ Precis Oncol., 2023) and ALLCatchR (Beder et al., Blood, 2022) based on the RNA-seq profiles.

  Study EGAS50000001497

• Genotype and exome data for an Australian Aboriginal population: a reference panel for health-based research

  Genetic analyses, including genome-wide association studies and whole exome sequencing (WES), provide powerful tools for the analysis of complex and rare genetic diseases. To date there are no reference data for Aboriginal Australians to underpin the translation of health-based genomic research. Here we provide a catalog of variants called after sequencing the exomes of 72 Aboriginal individuals to a depth of 20X coverage in 80% of the sequenced nucleotides. We determined 320,976 single nucleotide variants (SNVs) and 47,313 insertions/deletions using the Genome Analysis Toolkit. We had previously genotyped a subset of the Aboriginal individuals (70/72) using the Illumina Omni2.5 BeadChip platform and found 99% concordance at overlapping sites, which suggests high quality genotyping. Finally, we compared our SNVs to six publicly available variant databases, such as dbSNP and the Exome Sequencing Project, and 70,115 of our SNVs did not overlap any of the single nucleotide polymorphic sites in all the databases. Our data set provides a useful reference point for genomic studies on Aboriginal Australians.

  Study EGAS00001001585

• Genome-wide prediction of human embryos

  BACKGROUND: Preimplantation genetic diagnosis (PGD) enables profiling of embryos for genetic disorders prior to implantation. The majority of PGD testing is restricted in the scope of variants assayed or by the availability of extended family members. While recent advances in single cell sequencing show promise, they remain limited by bias in DNA amplification and the rapid turnaround time (<36 h) required for fresh embryo transfer. Here, we describe and validate a method for inferring the inherited whole genome sequence of an embryo for preimplantation genetic diagnosis (PGD). METHODS: We combine haplotype-resolved, parental genome sequencing with rapid embryo genotyping to predict the whole genome sequence of a day-5 human embryo in a couple at risk of transmitting alpha-thalassemia. RESULTS: Inheritance was predicted at approximately 3 million paternally and/or maternally heterozygous sites with greater than 99% accuracy. Furthermore, we successfully phase and predict the transmission of an HBA1/HBA2 deletion from each parent. CONCLUSIONS: Our results suggest that preimplantation whole genome prediction may facilitate the comprehensive diagnosis of diseases with a known genetic basis in embryos.

  Study EGAS00001001020

• Automated image-based profiling of complex drug induced phenotypes in patient-derived organoids

  We established a platform for high-throughput confocal fluorescence microscopy and automated image analysis to perform large-scale drug response profiling with patient derived organoids (PDOs). Using PDO lines newly established from colorectal cancer patients with a standardized workflow, we performed chemical perturbations with more than 500 experimental and clinically used compounds. Subsequently, we captured approx. six million images by confocal microscopy. To analyze drug-induced PDO re-organization on a single organoid level we developed SCOPE, a software framework for automated PDO high-throughput image analysis. We observed a rich variety of divergent and reoccurring compound induced phenotypes in organoids. Perturbation of cellular processes, including signaling by MEK, GSK3β, cyclin dependent kinases (CDKs) and others, led to recurring and distinct architectural changes. Highlighting the clinical relevance, PDO viability was heterogeneous after perturbation with anticancer drugs and matched clinical response of corresponding colorectal cancer patients. Our work opens new avenues for image-based profiling for accelerated drug discovery and clinical decision-making.

  Study EGAS00001003140

• Selective targeting of TBXT with DARPins identifies regulatory networks and therapeutic vulnerabilities in chordoma

  The embryonic transcription factor TBXT (brachyury) drives chordoma, a spinal neoplasm without effective drug therapies. TBXT’s regulatory network is poorly understood, and strategies to disrupt its activity for therapeutic purposes are lacking. We developed designed ankyrin repeat proteins that block TBXT-DNA binding (T-DARPins). In chordoma cells, T-DARPins reduced cell cycle progression, spheroid formation, and tumor growth in mice and induced signs of senescence and differentiation. Transcriptomic and proteomic analyses identified gene networks involved in cell cycle regulation, embryonic cell identity, and interferon response and revealed features of regulome components, such as druggability for future translational studies and the fine-tuning of TBXT downstream effectors through IGFBP3. Finally, we found high interferon signaling in chordoma cell lines and patient tumors, which was promoted by TBXT and associated with sensitivity to JAK2 inhibitors. These findings demonstrate the potential of DARPins for probing nuclear proteins to understand the regulatory networks of transcription factor-driven cancers, including entry points for therapies that warrant testing in patients.

  Study EGAS00001008140

• Resource for Genetic Epidemiology Research on Adult Health and Aging (GERA)

  The Resource for Genetic Epidemiology Research on Aging (GERA) Cohort was created by a RC2 "Grand Opportunity" grant that was awarded to the Kaiser Permanente Research Program on Genes, Environment, and Health (RPGEH) and the UCSF Institute for Human Genetics (AG036607; Schaefer/Risch, PIs). The RC2 project enabled genome-wide SNP genotyping (GWAS) to be conducted on a cohort of over 100,000 adults who are members of the Kaiser Permanente Medical Care Plan, Northern California Region (KPNC), and participating in its RPGEH. The purpose of the RPGEH is to facilitate research on the genetic and environmental factors that affect health and disease by linking together clinical data from electronic health records, survey data on demographic and behavioral factors, and environmental data from various sources, with genetic data derived from biospecimens collected from participants. 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. To maximize the diversity of the resulting sample, the GERA cohort was formed by including all racial and ethnic minority participants with saliva samples (N = 20,925; 19%); the remaining participants were drawn sequentially and randomly from white non-Hispanic participants (89,341; 81%). A total of 110,266 participant samples were included to ensure that at least 100,000 were successfully assayed. The resulting GERA cohort is 42% male, 58% female, and ranges in age from 18 to over 100 years old with an average age of 63 years at the time of the RPGEH survey (2007). The sample is ethnically diverse, generally well-educated with above average income. Approximately 69% of the participants are married or living with a partner. Length of membership in KPNC averages 23.5 years. UCSF and RPGEH investigators worked with the genomics company Affymetrix to design four custom microarrays for genotyping each of the four major race-ethnicity groups included in the GERA Cohort, described in detail in Hoffmann et al., 2011a and 2011b. Following genotyping and quality control procedures, and after removal of invalid, discordant, or withdrawn samples, about 103,000 participants were successfully genotyped. The resulting genotypic data were linked to survey data and data abstracted from the electronic medical records. As described below, all RPGEH participants were mailed new consent forms with explicit discussion of the placement of data in the NIH-maintained dbGaP. About 77% of participants returned completed consent forms, resulting in a final sample size of 78,486 participants in the GERA Cohort with data for deposit into dbGaP. Origins of the RPGEH GERA Cohort The goal in creating the RPGEH GERA cohort was to create a large, multiethnic, and comprehensive population-based resource for research into the genetic and environmental basis of common age-related diseases and their treatment, and factors influencing healthy aging and longevity. The GERA Cohort consists of a diverse cohort of more than 100,000 adults who are members of the Kaiser Permanente Medical Care Plan, Northern California Region (KPNC), and participating in its Research Program on Genes, Environment and Health (RPGEH). KPNC is an integrated health care delivery system with a population of about 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 the membership is underrepresented for the extremes of income at both ends of the spectrum. The RPGEH utilizes the longitudinal electronic health records (EHR) of KPNC to obtain clinical, laboratory, imaging and pharmacy information on all cohort members, to which personal demographic, behavioral and health characteristics have been added through member surveys. The GERA Cohort comprises a subsample of the RPGEH participant cohort, and was created through the RC2 award from the NIA, NIMH, and NIH Common Fund as described above. GERA Study Design The GERA Cohort is a subsample, as described above, of the longitudinal cohort enrolled in the Kaiser Permanente RPGEH. The RPGEH cohort includes about 400,000 survey participants of whom about 200,000 have provided broad consent and a sample of saliva or blood for use in studies of genetic and environmental factors in health and disease. The GERA Cohort was developed from a mailed survey sent to all adult members of KPNC who had been members for two years or more in 2007. All survey respondents were contacted and asked to complete a consent form; those who completed consent forms were asked to provide a saliva sample. Additional male participants were added to the RPGEH through inclusion of the Northern California sample of the California Men's Health Study (CMHS) cohort of about 40,000 men from KPNC, ages 45-69 years old at the time of the CMHS survey in 2002-2003. The CMHS participants contributed about 15,400 saliva samples to the RPGEH and were eligible for inclusion in the GERA Cohort. CMHS participants were included according to the same sampling design as for the RPGEH cohort as a whole. Specifically, all minority participants were selected for inclusion in order to maximize representation of minorities in the GERA Cohort, and Non-Hispanic White participants were selected at random to complete the sample of 110,266 GERA Cohort participants. GERA Genotypic Data High-density genotyping was conducted at UCSF using custom designed Affymetrix Axiom arrays, as described in Hoffmann et al. (2011a; 2011b). To maximize genome-wide coverage of common and less common variants, four specific arrays were designed for individuals of Non-Hispanic White (EUR), East Asian (EAS), African-American (AFR), and Latino (LAT) race/ethnicity. There was broad overlap among the SNPs on the arrays, which were designed using a hybrid greedy imputation algorithm (Hoffmann et al., 2011b) applied to genotype information validated by Affymetrix from the 1000 Genomes Project. However, in order to capture low frequency variants specific to particular race-ethnicity groups, SNP content varies between arrays. A more detailed description of the process of genotyping and results is included in Genotyping of DNA Samples. Description of the analyses of population structure and development of principal components for adjustment of population structure is included in Population Structure Analysis. GERA Phenotypic Data RPGEH and CMHS Survey Data. The sources of data on demographic and behavioral factors deposited in dbGaP for the GERA Cohort are the RPGEH and CMHS surveys. Data on common demographic factors such as gender, race/ethnicity, marital status, and education and on behavioral factors such as smoking, alcohol consumption, and body mass index, have been cleaned, edited, reconciled between the two surveys, and compiled into summary indices, where appropriate, for deposition into dbGaP. A more complete description of the survey variables is included in Survey Variables Documentation. Please note that the terms of use of the GERA Cohort Data, as specified in the Data Use Certification (DUC), prohibit the use of survey variables as outcomes in analyses. For example, a genome-wide association study (GWAS) of education or smoking is not permitted as specified by the DUC. Only health conditions can be used as outcome variables in analyses. Health Conditions derived from Kaiser Permanente Electronic Medical Records. Data on the occurrence of health conditions in participants in the GERA Cohort have been derived from summarizing ICD-9 coded diagnoses in Kaiser Permanente's electronic medical records. An algorithm that aggregates specific ICD-9 codes into appropriate diagnostic groups for selected conditions is applied to outpatient and inpatient databases; see Disease and Conditions Definitions Documentation for details. The criterion for including a condition as "present" for a participant is the occurrence of two or more diagnoses within a diagnostic category occurring on separate days. Two or more is used as the criterion in order to reduce false positives due to mistakes or rule-out diagnoses. When compared with validated disease registries, the criterion of 2+ diagnoses yields high specificity and good sensitivity. ICD-9 codes in the electronic records are specified in several ways. For outpatient visits occurring during the period 1995 to 2006, diagnoses were assigned by the treating physician who endorsed specific diagnoses on an optically scanned list that varied by specialty. Beginning in 2006 with the advent of an integrated, fully electronic medical record, outpatient diagnoses are made by physicians/ providers using a pull down menu. Discharge diagnoses from inpatient stays are specified by physicians and coded by specially trained coders. Databases of ICD-9 codes for diagnoses assigned at outpatient visits, or as one of the discharge diagnoses following inpatient stays, are complete and available for all KPNC members dating back to 1995. Although the average length of KPNC membership among GERA cohort members is 23.5 years in 2007, not all have been members since 1995, so the history for some conditions, such as those that are not chronic or recurrent, may not be complete for all cohort members. The year of first membership in KPNC is included as a variable in the list of survey variables, enabling investigators to estimate the number of years of observation of each Cohort member. 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 details, please contact RPGEH through the website.

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• 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

• Baylor Hopkins Center for Mendelian Genomics (BH CMG)

  The Centers for Mendelian Genomics project uses next-generation sequencing and computational approaches to discover the genes and variants that underlie Mendelian conditions. By discovering genes that cause Mendelian conditions, we will expand our understanding of their biology to facilitate diagnosis and new treatments.

  Study phs000711

• Broad Institute Center for Mendelian Genomics

  The Centers for Mendelian Genomics project uses next-generation sequencing and computational approaches to discover the genes and variants that underlie Mendelian conditions. By discovering genes that cause Mendelian conditions, we will expand our understanding of their biology to facilitate diagnosis and new treatments.

  Study phs001272

• University of Washington Center for Mendelian Genomics (UW-CMG)

  The Centers for Mendelian Genomics project uses next-generation sequencing and computational approaches to discover the genes and variants that underlie Mendelian conditions. By discovering genes that cause Mendelian conditions, we will expand our understanding of their biology to facilitate diagnosis and new treatments.

  Study phs000693

• Developing therapeutics for ovarian cancer using ovarian cancer organoids

  To identify effective drugs for clear cell ovarian cancer (CCC) and high-grade serous ovarian cancer (HGSC) through high-throughput drug screening using ovarian cancer organoids and to identify novel therapeutic targets based on the biological characteristics of CCC and HGSC through omics analysis.

  Study JGAS000764

• Development of actionable molecular targets and/or biomarkers for prognostication and patient stratification in gynecological cancer based on whole-exome sequencing and epigenomic analysis

  We collected 187 samples of normal and primary tumor tissues in 69 cases of endometrial carcinoma. The purpose of this study is to develop actionable molecular targets and/or biomarkers for prognostication and patient stratification.

  Study JGAS000174

• WTCCC case-control study for Bipolar Disorder - Combined Controls

  WTCCC genome-wide case-control association study for Bipolar Disorder (BD) using six disease collections together with the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000002