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• ENGAGE - Amendment "500 genes exon sequencing"

  The ENGAGE project is a FP7 funded EU project aiming to combine genetic and phenotype information from European population based cohorts. In this sub-project we aim to do whole exome sequencing of individuals selected from Health 2000 and FINRISK cohorts. Individuals have been selected based on their metabolic trait phenotypes

  Dataset EGAD00001000403

• Genome-Wide Predictors of Treatment-Related Toxicities in SWOG S0221 Trial

  When undergoing treatment for breast cancer, many women experience severe side effects, some of which result in treatment-related death and some that can persist for years. Little is understood regarding factors that may predict drug toxicities. Pharmacogenetics, the investigation of variants in candidate genes in drug metabolism pathways, has been used to determine susceptibility to treatment-related toxicities, as well as to cancer recurrence. Although there have been some strong and important findings using this approach, such as identification of single nucleotide polymorphisms (SNPs) that predispose to side effects associated with thiopurines and irinotecan, there has been less progress in assessment of genetic variants that predispose to toxicities resulting from the multi-drug regimen commonly used to treat breast cancer, anthracyclines (A), cyclophosphamide (C), and taxanes (T). These difficulties in identification of key gene variants may be due to the complex metabolic pathways of these drugs, the lack of rate limiting enzymes in the processes, or the limitations of single SNP analysis, rather than capturing all of the variability across the genes. In addition to drug metabolism pathways, however, there may be a number of constitutional factors or other processes that affect damage to normal tissues in the course of chemotherapy, some known or hypothesized, such as DNA repair and oxidative stress pathways, and others not yet discovered. However, there have been no clear candidate genes that account for a large part of the variation in drug or treatment response, and there are likely important genes that influence sensitivity of cells to chemotherapy through unknown pathways which have not yet been identified or hypothesized. The present technological capabilities to screen the entire genome for variants that discriminate populations allows the opportunity to identify these as yet unknown pathways, and open the doors to exciting new avenues of research into mechanisms that had not been previously considered. We conducted a genome-wide scan (GWAS) in a clinical trial (S0221), in which women with high risk breast cancer were treated with different dosing schedules of C, A and T. Blood specimens were collected and banked, and DNA extracted for genotyping on the Illumina OMNI 1M platform. The GWAS data were used to examine genetic variants significantly associated with grades 3 and 4 toxicities, including peripheral neuropathy recorded during the T segment. In S0221, toxicities were graded according to the NCI Common Toxicity Criteria for Adverse Events (CTCAE). The neurotoxicity is predominantly a distal sensory neuropathy, which is characterized by pain, numbness, tingling, and reduced functional capacity in the extremities. Other symptoms include parasthesias, ataxia, impaired vibration and joint position sense, and loss of tendon reflexes. By using a GWAS approach, it is likely that important pathways not previously considered can be revealed as important in susceptibility to treatment-related toxicities, identifying those at greatest risk for alternate drugs or dose reduction, and opening new areas of research for prevention of taxanes-related neuropathy among patients receiving chemotherapy for breast cancer.

  Study phs001428

• NHLBI TOPMed: The Jackson Heart Study (JHS)

  Since there is a greater prevalence of cardiovascular disease among African Americans, the purpose of the Jackson Heart Study (JHS) is to explore the reasons for this disparity and to uncover new approaches to reduce it. The JHS is a large, community-based, observational study whose 5306 participants were recruited from among the non-institutionalized African-American adults from urban and rural areas of the three counties (Hinds, Madison, and Rankin) that make up the Jackson, MS, metropolitan statistical area (MSA). Jackson is the capital of Mississippi, the state with the largest percentage (36.3%) of African Americans in the United States. The JHS design included participants from the Jackson ARIC study who had originally been recruited through random selection from a drivers' license registry. Approximately six months before the JHS was to begin, an amendment to the federal Driver's Privacy Protection Act was passed that changed the level of consent for public release of personal information from driver's license lists from an "opt out" to an "opt in" basis. The Mississippi Highway Patrol was no longer able to release a complete listing of all persons with driver's licenses or state identification cards, which prevented its use in the JHS. New JHS participants were chosen randomly from the Accudata America commercial listing, which provides householder name, address, zip code, phone number (if available), age group in decades, and family components. The Accudata list was deemed to provide the most complete count of households for individuals aged 55 years and older in the Jackson MSA. A structured volunteer sample was also included in which demographic cells for recruitment were designed to mirror the eligible population. Enrollment was opened to volunteers who met census-derived age, sex, and socioeconomic status (SES) eligibility criteria for the Jackson MSA. In addition, a family component was included in the JHS. The sampling frame for the family study was a participant in any one of the ARlC, random, or volunteer samples whose family size met eligibility requirements. Eligibility included having at least two full siblings and four first degree relatives (parents, siblings, children over the age of 21) who lived in the Jackson MSA and who were willing to participate in the study. No upper age limit was placed on the family sample. Known contact information was obtained during the baseline clinic examination from the index family member with a verbal pedigree format to identify name(s), age(s), address (es), and telephone number(s). Recruitment was limited to persons 35-84 years old except in the family cohort, where those 21 years old and above were eligible. Only persons who otherwise met study criteria but were deemed to be physically or mentally incompetent by trained recruiters were excluded from study eligibility.1 1 Wyatt SB, Diekelmann N, Henderson F, Andrew ME, Billingsley G, Felder SH et al. A community-driven model of research participation: the Jackson Heart Study Participant Recruitment and Retention Study. Ethn Dis 2003; 13(4):438-455 (PMID: 14632263).

  Study phs000964

• Kids First: Genomic Studies of Orofacial Cleft Birth Defects

  The Gabriella Miller Kids First Pediatric Research Program (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in pediatric cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource). Both childhood cancers and structural birth defects are critical and costly conditions associated with substantial morbidity and mortality. Elucidating the underlying genetic etiology of these diseases has the potential to profoundly improve preventative measures, diagnostics, and therapeutic interventions. WGS and phenotypic data from this study are accessible through dbGaP and kidsfirstdrc.org, where other Kids First datasets can also be accessed. The Kids First study of nonsyndromic orofacial cleft birth defects (OFCs) is a whole genome sequencing study of 415 White parent-case trios drawn from ongoing collaborations led by Dr. Mary L. Marazita of the University of Pittsburgh Center for Craniofacial and Dental Genetics, including collaborations with Dr. George Wehby of the University of Iowa, Dr. Jacqueline Hecht of the University of Texas, and Dr. Terri Beaty of Johns Hopkins University. Sequencing was done by the Washington University McDonell Genome Institute. The case in each of the Kids First trios has cleft lip (CL, Figure A), cleft palate (CP, Figure B), or both (CL+CP, Figure C): OFCs are genetically complex structural birth defects caused by genetic factors, environmental exposures, and their interactions. OFCs are the most common craniofacial anomalies in humans, affecting approximately 1 in 700 newborns, and are one of the most common structural birth defects worldwide. On average a child with an OFC initially faces feeding difficulties, undergoes 6 surgeries, spends 30 days in hospital, receives 5 years of orthodontic treatment, and participates in ongoing speech therapy, leading to an estimated total lifetime treatment cost of about $200,000. Further, individuals born with an OFC have higher infant mortality, higher mortality rates at all other stages of life, increased incidence of mental health problems, and higher risk for other disorders (notably including breast, brain, and colon cancers). Prior genome-wide linkage and association studies have now identified at least 18 genomic regions likely to contribute to the risk for nonsyndromic OFCs. Despite this substantial progress, the functional/pathogenic variants at OFC-associated regions are mostly still unknown. Because previous OFC genomic studies (genome-wide linkage, genome-wide association studies (GWAS), and targeted sequencing) are based on relatively sparse genotyping data, they cannot distinguish between causal variants and variants in linkage disequilibrium with unobserved causal variants. Moreover, it is unknown whether the association or linkage signals are due to single common variants, haplotypes of multiple common variants, clusters of multiple rare variants, or some combination. Finally, we cannot yet attribute specific genetic risk to individual cases and case families. Therefore, the goal of the current study is to identify specific OFC risk variants in Whites by performing whole genome sequencing of parent-case trios.

  Study phs001168

• Heart Failure Network - Xanthine Oxidase Inhibition for Hyperuricemic Heart Failure Patients (HFN EXACT-BioLINCC)

  ObjectivesTo determine the effect of allopurinol after 24 weeks on a composite clinical endpoint that classifies subject's clinical status (improved, worsened, unchanged) in patients with heart failure and high uric acid levels.BackgroundMorbidity and mortality rates for patients with heart failure are high, despite guideline-recommended therapy. Heart failure is characterized by an imbalance between left ventricular (LV) performance and myocardial energy consumption. There is a growing body of evidence that suggests oxidative stress contributes to ventricular and vascular remodeling, and disease progression in heart failure. Targeting potential source(s) of oxidative stress, e.g. Xanthine oxidase (XO), was the focus of recent clinical trials and epidemiological studies. Increased XO activity has been shown to lead to production of superoxide and uric acid (UA). Serum uric acid levels are included in heart failure risk scores, and hyperuricemia is present in about 25% of patients with heart failure. Hyperuricemia is associated with exercise intolerance, reduced survival, and worsening symptoms. The EXACT-HF trial tested allopurinol, an inhibitor of XO, as a potential target therapy for hyperuricemic heart failure patients.Subjects253 subjects were enrolled in the EXACT-HF study. 128 participants were randomized to the allopurinol arm, and of those participants, 119 completed the trial and 9 did not. 125 participants were randomized to the placebo arm, and of those participants, 116 completed the trial and 9 did not.DesignEXACT-HF was a multi-center, double-blind, placebo controlled, 24-week trial of allopurinol. Eligible participants had to be receiving a stable regimen for at least two weeks (3 months for beta-blockers) prior to randomization. Participants were randomized by an automated system to either the allopurinol or placebo arm, and started treatment within 12 hours of completing the baseline visit. During the first week, participants in both treatment arms received 300mg daily of the respective medications. For the following 23 weeks, participants in both treatment arms received 600mg daily of the respective medications. Patients unable to tolerate 600 mg were maintained on 300 mg.The primary endpoint was a composite clinical endpoint (CCE) that classified a subject's clinical status as improved, worsened, or unchanged at 24 weeks. The CCE was determined based on the following: death; hospitalization, emergency room visit or emergent clinic visit for worsening HF; medication change for worsening HF; and Patient Global Assessment using a 7-point scale. Secondary endpoints at 12 and 24 weeks included changes in quality of life as assessed by the Kansas City Cardiomyopathy Questionnaire, and submaximal exercise capacity as assessed by a 6-minute walk test.ConclusionsParticipants who received allopurinol had significantly less serum uric acid laboratory levels after 24 weeks; however, no significant difference was observed in the primary and secondary endpoints between the allopurinol and placebo-treated patients. Therefore, in high-risk HF patients with reduced ejection fraction and elevated uric acid levels, xanthine oxidase inhibition with allopurinol failed to improve clinical status, exercise capacity, quality of life, or LVEF at 24 weeks (Circulation. 2015 May 19; 131(20):1763-71).

  Study phs003533

• How to request data

  Request Data Access If you're looking to access data from the EGA for your research, you are in the right documentation page! In this page you will find a step by step guide on how to request data archived at the EGA, as well as some frequently asked questions you might find useful. When requesting data, you'll need to provide information about your research project and intended use of the data. Keep in mind that your data access request may require additional approvals or agreements depending on the datasets and data providers involved. Step by step guide Register yourself as an EGA user. Validate your account. A validation link will be sent to your email to activate your EGA user account. Log into the EGA page. Search the dataset of interest from the dataset catalogue or search bar. Click on “Request access” Add a comment requesting these files and send your request Your request is successfully registered, and the DAC will receive a notification about your request In addition to submitting your request, you should also contact the DAC directly via e-mail. You can access the DAC's contact information from the relevant dataset page. Frequently Asked Questions (FAQ) Which is the role of the EGA in the data access process? The European Genome-phenome Archive (EGA) facilitates the secure distribution under controlled access of personally identifiable genetic and phenotypic data. Data Access Committee (DAC) is a body of one or more individuals who are responsible for data release to external requestors, based on participant consent and/or National Research Ethics terms. How do I request access to multiple datasets? To request access for multiple datasets managed by the same Data Access Committee (DAC), please start by visiting the DAC catalogue to locate the DAC of your choice. Once you've found the relevant DAC, proceed to its dedicated page where you'll find a "Request access" button. After logging in to the EGA website, you'll be presented with a comprehensive list of datasets under the chosen DAC. Select the datasets you're interested in, and then compose a message indicating your access request. Click the "Send" button to submit your request, which will include the chosen datasets. Please be sure to review the data usage policies for the requested datasets, as policies can vary among datasets managed by the same DAC. I am a co-applicant. Will I be given a joint access account? Each applicant needs to create an EGA account themselves, with unique login details. User log-in details are for individual use only and should never be shared, under any circumstances. EGA services are only provided to EGA account holders. Therefore, the co-applicant will send a formal request to the DAC. What happens if a co-applicant leaves or a new member needs to be added to an existing DAC application? The appropriate Data Access Committee (DAC) should be contacted and informed about the required changes so that the application can be updated. I have changed my place of work since my EGA account was created. Can I still have access to data? You must contact the relevant Data Access Committee (DAC). The DAC did not reply to my data access request. How should I proceed? There is no estimated time for DAC response. Please allow up to four weeks for a response. In the meantime, please send them a weekly reminder of the status of your request by emailing them directly.If the DAC becomes unresponsive, meaning that they fail to communicate with a requestor within the specified time frame, please contact the EGA Helpdesk team. I have an account with the EGA and would like access to further datasets. How should I proceed? You need to reapply to the relevant Data Access Committee (DAC). Once the DAC has approved your application your account will be updated and an email will be sent to notify you of a change made to your account. How do I download files of the datasets I have been granted access to? The preferred method for data download and decryption is the EGA Secure Download Client. Please carefully review the provided documentation. How do I download metadata? Metadata is retrieved from the EGA webpage; you will not need to use any download client. Be informed that you will only be able to download metadata of your approved datasets. For such download, you should first log in the EGA webpage with your credentials. Then browse the metadata's dataset you have gained access and you will find a metadata download button. You may also want to have a look our metadata schema. I have forgotten or misplaced my user account password; how do I get a new one? Click on “Log in”, located in the top right corner of the EGA homepage. Then click “Forgot password”, type in your registered institutional email address, and instructions for resetting your password will be sent to you. Please check both regular and junk/spam folders. I was sent a link to set a password for my download account, but it seems like the link has expired. What should I do? The procedure is the same as the one for a forgotten password, explained in the previous question.

  Documentation access/request-data/how-to-request-data

• Surveillance, Epidemiology and End Results (SEER) Formalin Fixed Paraffin Embedded (FFPE) Tissue Feasibility Study

  Next Generation Sequencing (NGS) technologies are being used for detection of somatic mutations in tumors and studies of germline variation. However, most NGS studies used DNA isolated either from whole blood or fresh frozen tissue specimens. Meanwhile, the tissue specimens available from most National Cancer Institute (NCI) funded cohorts and the Surveillance, Epidemiology and End Results (SEER) registries (http://seer.cancer.gov/biospecimen) are primarily formalin fixed paraffin embedded (FFPE). There are limited data, on a small number of FFPE tissue samples, which suggest NGS is feasible. Much less is known about the feasibility of these technologies for large scale studies or using older FFPE specimens (e.g. 5-30 years old). The SEER cancer registries cover approximately 28% of the United States population, providing high quality demographic, clinical, pathologic, and survival data. The SEER Residual Tissue Repository (RTR) program was established in 2003. The RTR maintains biospecimens obtained from three of SEER' population-based cancer registries: Iowa, Hawaii, and Los Angeles. Investigators at government, academic, and nonprofit institutions may apply to the program to obtain annotated FFPE tumor tissue specimens to study biomarkers, etiology, and other aspects with a population-based sample of cancer cases. The main objective of this project was to conduct a pilot study to determine whether the DNA obtained from archival FFPE tissue from 3 SEER Registries is of sufficient quality and quantity to conduct NGS. For Exome sequencing, sixty high-grade serous ovarian adenocarcinomas from FFPE tissues which were between 7 and 31 years old were obtained from three SEER registries. DNA was extracted, quantified, quality assessed, and subjected to whole exome sequencing. DNA extraction (yields and quality) and whole exome sequencing (depths of coverage and exome coverage obtained) results from this study will be presented. For RNA-sequencing, sixty-seven high-grade serous ovarian adenocarcinomas from FFPE tissues which were between 7 and 31 years old were obtained from three SEER registries. Total RNA was extracted, quantified, quality assessed, and subjected to whole transcriptome sequencing. Ultimately data derived from this analysis could serve as the basis for determining the utility of archival FFPE biospecimens for characterization and discovery projects utilizing NGS technologies instead of relying on frozen biospecimens.

  Study phs000950

• Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples (T2D-GENES) Project 1: KARE

  T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples) is a NIDDK-funded international research consortium which seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. T2D-GENES Project 1 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 14 cohorts that are listed in Table 1. The strategy was to perform deep exome sequencing of 12,940 individuals, 6,504 with T2D and 6,436 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. Sequencing was performed at the Broad Institute using the Agilent v2 capture reagent on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study does not have a sub study, as it is not consented to be deposited in dbGAP. Table 1. T2D-GENES Whole Exome Sequencing Studies Ancestry Study Countries of Origin # Cases # Controls African American Jackson Heart Study US 502 527 African American Wake Forest School of Medicine Study US 518 532 East Asian Korea Association Research Project Korea 526 561 East Asian Singapore Diabetes Cohort Study; Singapore Prospective Study Program Singapore (Chinese) 486 592 European Ashkenazi US, Israel 506 352 European Metabolic Syndrome in Men Study (METSIM) Finland 484 498 European Finland-United States Investigation of NIDDM Genetics (FUSION) Study Finland 472 476 European Kooperative Gesundheitsforschung in der Region Augsburg (KORA) Germany 97 90 European UK Type 2 Diabetes Genetics Consortium (UKT2D) UK 322 320 European Malmö-Botnia Study Finland, Sweden 478 443 Hispanic 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 272 219 Hispanic Starr County, Texas US 749 704 South Asian London Life Sciences Population Study (LOLIPOP) UK (Indian Asian) 530 538 South Asian Singapore Indian Eye Study Singapore (Indian Asian) 563 585 The Korea Association Research Project (KARE) studies contributed 526 cases and 561 controls to T2D-GENES Project 1.

  Study phs001096

• Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples (T2D-GENES) Project 1: Ashkenazi

  T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples) is a NIDDK-funded international research consortium which seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. T2D-GENES Project 1 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 14 cohorts that are listed in Table 1. The strategy was to perform deep exome sequencing of 12,940 individuals, 6,504 with T2D and 6,436 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. Sequencing was performed at the Broad Institute using the Agilent v2 capture reagent on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study does not have a sub study, as it is not consented to be deposited in dbGAP. Table 1. T2D-GENES Whole Exome Sequencing Studies Ancestry Study Countries of Origin # Cases # Controls African American Jackson Heart Study US 502 527 African American Wake Forest School of Medicine Study US 518 532 East Asian Korea Association Research Project Korea 526 561 East Asian Singapore Diabetes Cohort Study; Singapore Prospective Study Program Singapore (Chinese) 486 592 European Ashkenazi US, Israel 506 352 European Metabolic Syndrome in Men Study (METSIM) Finland 484 498 European Finland-United States Investigation of NIDDM Genetics (FUSION) Study Finland 472 476 European Kooperative Gesundheitsforschung in der Region Augsburg (KORA) Germany 97 90 European UK Type 2 Diabetes Genetics Consortium (UKT2D) UK 322 320 European Malmö-Botnia Study Finland, Sweden 478 443 Hispanic 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 272 219 Hispanic Starr County, Texas US 749 704 South Asian London Life Sciences Population Study (LOLIPOP) UK (Indian Asian) 530 538 South Asian Singapore Indian Eye Study Singapore (Indian Asian) 563 585 The Ashkenazi study contributed 506 cases and 352 controls to T2D-GENES Project 1.

  Study phs001095

• National Heart Lung and Blood Institute (NHLBI) GO-ESP: Heart Cohorts Component of the Exome Sequencing Project (ARIC)

  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. HeartGO is a consortium of six well-phenotyped NHLBI cohorts: Atherosclerosis Risk in Communities (ARIC) study, the Coronary Artery Risk Development in Young Adults (CARDIA) study, the Cardiovascular Health Study, the Framingham Heart Study, the Jackson Heart Study, and the Multi-Ethnic Study of Atherosclerosis. Together, these cohorts have provided DNA and phenotype datasets from a diverse cohort of individuals of African-American, Caucasian, Asian, and Hispanic ancestry to be made available for use by qualified investigators in dbGaP. HeartGO investigators will conduct genotype-phenotype analyses for phenotypes related not only to heart disease but with other variables that will be contributed to dbGaP. The HeartGO dataset provides investigators with genotype-phenotype analytic opportunities for traits not only related to heart disease but also associated with ancillary variables that will be contributed to dbGaP, including disease endpoints, risk factors, biomarkers, and subclinical disease measures. The phenotypes planned for investigation as part of the GO-ESP HeartGO project include early-onset myocardial infarction (EOMI), low density lipoprotein (LDL) cholesterol, body mass index/type 2 diabetes (BMI/T2D), blood pressure and ischemic stroke. Results of the proposed analyses as well as relevant replication/follow-up analyses will be reported in peer-reviewed journals. This study phs000398 contains the Atherosclerosis Risk in Communities (ARIC) subset of GO-ESP/Heart-GO. Additional GO-ESP data is also available via dbGaP.

  Study phs000398