14977 results for "cancer studies using rna-seq"

in 23.04 milliseconds.

• Multi-region WGS of a RET fusion positive cancer

  high depth WGS sequencing of 8 sites of a RET fusion tumour

  Dataset EGAD00001006878

• Prostate WGS data (late onset)

  Whole genome sequencing for 12 late onset prostate cancer tumor/control pairs (ICGC)

  Dataset EGAD00001003290

• 20180208_EGA_Trench_MetCellLine.1

  Illumina platform sequencing data of SureSelect exome libraries prepared from 3 samples from one donor: a normal, primary breast cancer, and cell line derived from metastasis

  Dataset EGAD00001003956

• OT2_Illumina_RNA_MET

  RNAseq on Illumina HiSeq2000/2500 of colorectal cancer metastasis sample (OT2_cohort)

  Dataset EGAD00001003364

• Whole exome sequencing data for paired non-serous endometrial and ovarian carcinomas from 27 patients with concurrent tumours.

  Dataset for Synchronous Endometrial and Ovarian Cancer

  Dataset EGAD00001015680

• Targeted gene sequencing of gallbladder cancer

  The dataset includes the targeted gene sequencing data from51 pairs of gallbladder caner tissues and patient-matched normal tissues.

  Dataset EGAD00001000902

• GIST SSGXVIII trial targeted gene sequencing

  Targeted cancer gene sequencing of samples enrolled in the SSGXVIII trial from Finland.

  Dataset EGAD00001001427

• WES

  WES was performed on 2 TURP, 6 biopsies, 1 CDX, 1 cell line, 6 CTCs, 1 DNA germline and 1WBC from prostate cancer

  Dataset EGAD00001006009

• LLD PhIPSeq

  LLD PhIP-Seq reads. Oligopeptides were designed at Eran's Segal group at Weizmann Institute of Science. Dataset include 1,783 plasma samples. In 340 participants, a second time point was taken after a 4-year follow-up.

  Dataset EGAD00001010104

• Whole genome sequencing with linked reads of pediatric glioblastoma samples

  Pediatric glioblastoma (pGBM) is a lethal cancer with no effective therapies. To understand mechanisms of tumor evolution in this cancer, we performed whole genome sequencing with linked reads on longitudinally resected pGBM samples. Our analyses showed that all diagnostic and recurrent samples were collections of genetically diverse subclones. Clonal composition rapidly evolved at recurrence, with less than 8% of non-synonymous single nucleotide variants being shared in diagnostic-recurrent pairs. In order to track the origins of the mutational events we observed in pGBM, we generated whole genome datasets for two patients and their parents. These trios showed that genetic variants could be (i) somatic, (ii) inherited from a healthy parent, or (iii) arose de novo in the germlines of pGBM patients. Analysis of variant allele frequencies supported a model of tumor growth involving slow-cycling cancer stem cells that give rise to fast-proliferating progenitor-like cells and to non-dividing cells. Interestingly, radiation and anti-mitotic chemotherapeutics did not increase overall tumor burden upon recurrence. These findings support an important role for slow-cycling stem cell populations in contributing to recurrences, since slow-cycling cell populations are expected to be less prone to genotoxic stress induced by these treatments and to accumulate few mutations. Our results highlight the need for new targeted treatments that account for the complex functional hierarchies and genomic heterogeneity of pGBM.

  Study EGAS00001003432

• Partner-independent fusion gene detection by multiplexed CRISPR/Cas9 enrichment and long-read Nanopore sequencing

  Fusion genes are hallmarks of various cancer types and important determinants for diagnosis, prognosis and treatment possibilities. The promiscuity of fusion genes with respect to partner choice and exact breakpoint-positions restricts their detection in the diagnostic setting, even for known and recurrent fusion gene configurations. To accurately identify these gene fusions in an unbiased manner, we developed FUDGE: a FUsion gene Detection assay from Gene Enrichment. FUDGE couples target-selected and strand-specific CRISPR/Cas9 activity for enrichment and detection of fusion gene drivers (e.g. BRAF, EWSR1, KMT2A/MLL) - without prior knowledge of fusion partner or breakpoint-location - to long-read Nanopore sequencing. FUDGE encompasses a dedicated bioinformatics approach (NanoFG) to detect fusion genes from Nanopore sequencing data. Our strategy is flexible with respect to target choice and enables multiplexed enrichment for simultaneous analysis of several genes in multiple samples in a single sequencing run. We observe on average a 508-fold on-target enrichment and identify fusion breakpoints at nucleotide resolution - all within two days. We demonstrate that FUDGE effectively identifies fusion genes in cancer cell lines, tumor samples and on whole genome amplified DNA irrespective of partner gene or breakpoint-position in 100% of cases. Furthermore, we show that FUDGE is superior to routine diagnostic methods for fusion gene detection. In summary, we have developed a rapid and versatile fusion gene detection assay, providing an unparalleled opportunity for pan-cancer detection of fusion genes in routine diagnostics.

  Study EGAS00001003964

• A Study to Assess the Cardiovascular, Cognitive, and Subjective Effects of Atomoxetine in Combination with Intravenous Methamphetamine

  The Study to Assess the Cardiovascular, Cognitive, and Subjective Effects of Atomoxetine in Combination with Intravenous Methamphetamine started in 2007 and ended in 2011. It was a small pilot study that included methamphetamine abusing individuals and healthy control participants aged 18-50 years. Participants who qualified over the telephone were scheduled to visit the London Laboratory at the UCLA Semel Institute for Neuroscience and Human Behavior for the In-Person Screening Phase. The screening procedures, usually scheduled over two visits, determined if participants were eligible to complete the subsequent study visits. Both groups completed identical screening procedures, including a SCID diagnostic interview to rule out any major psychiatric disorders. Methamphetamine users also answered questionnaires specific to their drug use. Urine toxicology for marijuana, opiates, cocaine, methamphetamine, and benzodiazepines were monitored at the beginning and throughout the study. Additionally, participants had blood samples to test for Rapid Plasma Reagin (exposure to syphilis), purified protein derivative (PPD), HIV and Hepatitis-C (HCV). Positive test results were relayed by a study physician and resulted in termination from continuing in the study. The inpatient portion of the study lasted a total of 24 days. To confirm compliance with abstinence from illicit and prescription drug use for the duration of the study, urine and breath alcohol testing was performed for both inpatient (methamphetamine users) and outpatient (healthy control) groups. Each subject was randomized to receive either atomoxetine (80 mg daily) or placebo. During inpatient days of the study, a study physician oversaw research subjects daily and experimental procedures were conducted in the General Clinical Research Center (GCRC). During drug administration sessions, heart rate and blood pressure were assessed at frequent intervals. Experimental sessions lasted around three hours and were conducted at approximately the same time of day for a given participant. Lunch was provided to participants at 11:30am with the prohibition of caffeine on study days involving methamphetamine administration. Participants were provided with smoke breaks as needed to assure that acute nicotine withdrawal did not negatively impact performance on cognitive testing. The following outlines the day to day procedures for a methamphetamine inpatient: Phase I Inpatient Study (15 days total) Days 1-3: On the day of admission, participants received blood tests and an EKG in order to determine that they had no occult medical conditions which would make their participation in the study medically contraindicated. A three day washout period was provided at the beginning of the study to establish an appropriate methamphetamine-free baseline for testing. Days 4-6: Participants completed cognitive test batteries to assess inhibitory control including self-report measures and cognitive testing, as well as up to three MRI scanning sessions. Day 7: On day 7, at 9AM and 1PM, participants received methamphetamine in a single-blinded condition. It was administered as two IV infusions of 15mg separated by a 60min break. The total dose of IV methamphetamine was 30mg. Participants were clinically evaluated by continuous cardiac telemetry, serial EKG and measurement of vital signs, during and after infusions, in order to determine the medical safety of methamphetamine infusion in the absence of study medication. Day 8: On day 8 we evaluated the safety and residual effects of the methamphetamine administered on the previous day. Days 9-10: After demonstrating medical and psychiatric stability of the initial methamphetamine infusion, participants were then randomized to receive placebo or atomoxetine (0 or 40mg) under double-blind conditions, which would be given at 8AM on both study days. Days 11-12: On days 11 and 12, participants remained in the GCRC and took two doses of test compound atomoxetine (0 or 40mg) at 8AM and 8PM. On the morning of day 12, participants completed a series of cognitive testing. Day 13: On day 13, participants remained in the GCRC, and took two doses of the test compound atomoxetine (0 or 40mg) at 8AM and 8PM. At 9AM and noon, they received methamphetamine under double-blind conditions administered non-contingently as two infusions of 0 or 15mg by IV (intravenously), with each infusion separated by 60min. The total dose of IV methamphetamine that each participant received was 30mg. As before, participants were clinically evaluated by continuous cardiac telemetry, serial EKG and measurement of vital signs, during and after infusions, in order to determine the medical safety of methamphetamine infusion in those participants receiving study medication. Day 14: On day 14 at 8AM, participants received their final dosing of the first test compound (atomoxetine 0 or 40mg). At 9AM and 1PM, participants selected between methamphetamine infusion or money using double-blind conditions in a multiple-choice self-administration paradigm. Participants were able to take up to two infusions of 0 or 15mg of methamphetamine, separated by 60min. The total dose of IV methamphetamine that each participant received on day 14 was 30mg. Participants were clinically evaluated by continuous cardiac telemetry, serial EKG and measurement of vital signs, during and after infusions, in order to determine the medical safety of methamphetamine infusion in those participants receiving study medication. At 5pm on day 14 discharge laboratory studies were drawn. Day 15: On day 15, a final EKG was performed as well as a review of discharge laboratory studies, including review of the EKG and continued medical and psychiatric stability. Upon clearance from a physician, participants were discharged on day 15. Participants spent at least 2 weeks (14 days) out of the hospital prior to returning to the UCLA GCRC for inpatient Phase II. Phase II Inpatient Study (9 days total) Day 1-2: On the day of re-admission, participants received blood tests and an EKG. A two day washout period was provided at the beginning of the study to establish an appropriate methamphetamine free condition for safe administration of the second test compound condition. Days 3-4: On days 3 and 4, given medical stability, participants were then switched to the opposite test compound (atomoxetine 0 or 40mg) under double-blind conditions, in the same manner as in Days 9-10 in Phase I. Days 5-6: Same procedure as in Days 11-12 in Phase I but with opposite medication condition. Day 7: Same procedure as in Day13 in Phase I but with opposite medication condition. Day 8: Same procedure as in Day14 in Phase I but with opposite medication condition. Day 9: Same procedure as in Day14 in Phase I but with opposite medication condition. For healthy control participants, the study consisted of 30 days or fewer of out-patient testing. Healthy control participants had an extensive screening, including a history and physical exam performed by a study physician, an EKG, and laboratory studies performed to assess for medical or psychiatric conditions. Control participants meeting criteria were invited back to UCLA to undergo cognitive testing, and some participants received fMRI scans. Participants were required to refrain from illicit and prescription drug use for the duration of the study, which was confirmed with urine toxicology and breath alcohol level testing on examination days. Caffeine was restricted on study days for least 2 hours prior to cognitive testing and MRI scans. Participants were permitted to drink their normal daily intake of caffeine, given the caveat above. On study days, cigarette smoking was permitted to match conditions used with methamphetamine users. The incorporation of smoke breaks during the test day assured that acute nicotine withdrawal did not negatively impact performance on cognitive tests or neuroimaging. The following outlines procedures for healthy control participants: For normal controls, participation involved one day of outpatient screening, and one day of baseline cognitive testing and possible MRI scans. After these procedures were completed, participants were randomized to the first test compound (atomoxetine 40mg or placebo), to be taken once daily in the morning for 2 days. It was then increased to twice daily for the next 3 days, followed by a final dose (40mg or placebo) on the sixth day of study medication. Participants were also asked to bring their pill packages to assess compliance with the study medication. Additionally, control participants completed a series of repeated-measures cognitive testing (on placebo or atomoxetine, respectively) and possibly two fMRI sessions (separated by a short break). After at least a four-day washout period, control participants were instructed to start the opposite test compound (atomoxetine 40mg or placebo), again to be taken once daily in the morning for two days, then twice daily for 3 days, reaching the final dose (40mg or placebo) of the second test compound in the morning. Participants were again asked to bring their pill packages to assess compliance and had blood drawn to assess atomoxetine levels. Control participants then completed another series of cognitive testing and fMRI testing sessions. They were subsequently discharged from the study. Normal control participants returned two weeks after completion of both study phases in order to complete assessments to their physical and psychological status following treatment.

  Study phs001195

• eMERGE Network Imputed GWAS for 41 Phenotypes

  The electronic Medical Records and Genomics (eMERGE) Network is a consortium of ten participating sites (Cincinnati Children's Hospital Medical Center/Boston Children's Hospital, Children's Hospital of Philadelphia, Essentia Institute of Rural Health, Marshfield Clinic Research Foundation and Pennsylvania State University, Geisinger Clinic, Group Health Cooperative/University of Washington, Mayo Clinic, Icahn School of Medicine at Mount Sinai, Northwestern University, Vanderbilt University Medical Center) funded by the NHGRI to investigate the use of electronic medical record (EMR) systems for genomic research. The goal of eMERGE is to conduct genome-wide association studies in approximately 55,000 individuals using EMR-derived phenotypes and DNA from linked Biorepositories. Using electronic phenotyping methods, the consortium used DNA samples from all participating sites to explore the genetic determinants of over forty phenotypes, including 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, as well as using the phenome-wide association study (PheWAS) paradigm to replicate and discover relationships between targeted genotypes with multiple phenotypes. Sites and participants include: 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 medical records (EMRs). EMRs 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) and Boston Children's Hospital (BCH) are pediatric institutions dedicated to improving health and welfare of children and to the shared purpose of discovery and practical application of new genomic information to the ordinary care of children. The CCHMC/BCH site has been built on a five-year history of collaboration, particularly in patient electronic record (ERM)-related informatics, the basis of much of eMERGE II. CCHMC and BCH together bring an extraordinary faculty to eMERGE II who are committed to diseases that afflict children, specifically phenotypes that focus upon diseases of children in ways that will leverage the available eMERGE adult GWAS and EMRs to discover meaningful use results. CCHMC/BCH plans to demonstrate real-time execution of phenotypic selection across their two distinct pediatric institutions as a model for ensuring phenotypic standardization and for national scalability. They will also look carefully at parents' responses to results and use of their children's research results and better understand the factors that influence their decisions about learning incidental findings. In addition to patient and parent perceptions CCHMC/BCH will also explore clinician perceptions of pharmacogenetic research results after EMR integration. 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. Group Health(GH)/University of Washington (UW): GH participants for the PGx project 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~6300.) Participants were eligible if aged 50 - 65 years old at the time of their enrollment into the NWIGM repository, living, enrolled in GH'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 Group Health: 1. Demographics - participants with self-reported race as Asian or African ancestry were prioritized and selected to enrich for non-European ancestry; 2. Diagnosis and procedure codes - participants were selected if found to have a history of hypertension, atrial fibrillation (AF), or congestive heart failure (CHF). Participants with a history of arrhythmia were added if the entire selection algorithm did not generate 900 individuals. We also enriched for participants with EHR evidence of actionable indications related to PGRNSeq genes. Participants were selected if found to have an ICD9 code for malignant hyperthermia, hypertension, atrial fibrillation, congestive heart failure or long QT syndrome (LQTS); 3. Laboratory values - if participants had any laboratory event of creatine kinase (CK) >1000, and were dispensed statins within 6 months of the event, then they were selected; and 4. Medications - participants were excluded if ever on carbamazepine or had a current regimen of warfarin. 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 biobank 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. 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: BioVU, Vanderbilt's DNA databank, is an enabling resource for exploration of the relationships among genetic variation, disease susceptibility, and variable drug responses, and represents a key first step in moving the emerging sciences of genomics and pharmacogenomics from research tools to clinical practice. 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.

  Study phs000888

• 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.

  Study phs000674

• Data Access Committee of divisions B060 and B062, German Cancer Research Center (DKFZ)

  Dac EGAC00001000219

• EGAD00010000644

  Affymetrix SNP6.0 cancer cell line exome sequencing data

  Dataset EGAD00010000644