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• 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

• 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

• 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

• Heart Failure: A Controlled Trial Investigating Outcomes of Exercise Training (HF-ACTION-BioLINCC)

  Accessing Data Please refer to “Authorized Access” below regarding accessing data through the BioData Catalyst ecosystem. The data from this accession is not available for download through dbGaP.ObjectivesThe HF-ACTION study examined whether exercise training reduces a composite endpoint of all-cause mortality or all-cause hospitalization for patients with left ventricular systolic dysfunction and heart failure symptoms. Background Heart failure (HF) is a major and growing cardiovascular syndrome that is the end result of many cardiovascular disorders. Although evidence-based drug and device therapies decrease mortality, hospitalizations, and HF symptoms and improve quality of life, many patients treated with these regimens often remain burdened by dyspnea and fatigue, diminished exercise tolerance, reduced quality of life, recurrent hospitalizations, and early mortality. Whereas rest was traditionally recommended for HF patients, there has been evidence that physical deconditioning may play a key role in the progression of symptoms and poor outcomes. Previous studies have shown positive effects of exercise training on exercise capacity, quality of life, and biomarkers and suggest that exercise training might improve survival and decrease HF hospitalizations. Nonetheless, there remains a safety concern regarding exercise training in HF and a large scale, multicenter, controlled clinical trial was needed to provide definitive clinical outcome data. Participants A total of 2,331 participants were randomized. 2,130 consented to share data with non-commercial entities, and 1,753 consented to share for commercial purposes. Design All participants underwent baseline cardiopulmonary exercise testing. Test results were reviewed by investigators to identify significant arrhythmias or ischemia that would prevent safe exercise training, to determine appropriate levels of exercise training, and to establish training heart rate ranges. Demographics, socioeconomic status, past medical history, current medications, physical exam, and the most recent laboratory tests were obtained prior to randomization. All participants received detailed self-management educational materials which included information on medications, fluid management, symptom exacerbation, sodium intake, and physical activity. Participants randomized to the exercise training arm first participated in a structured, group-based, supervised exercise program, with a goal of 3 sessions per week for a total of 36 sessions in 3 months. The primary exercises were walking, treadmill, or stationary cycling. Exercise was initiated at 15 to 30 minutes per session at a heart rate corresponding to 60% of heart rate reserve, and was increased after 6 sessions to 30 to 35 minutes duration and 70% of heart rate reserve. Participants began home-based exercise after completing 18 supervised sessions and were to fully transition to home exercise after 36 supervised sessions. The target training regimen for home exercise was 5 times per week for 40 minutes at a heart rate of 60% to 70% of heart rate reserve. Participants randomized to the usual care group were not provided with a formal exercise prescription. To provide comparable levels of attention from study personnel, all participants were called every 2 weeks for the first 9 months, monthly until 24 months of follow-up, and quarterly thereafter. Participants returned for clinic visits every 3 months for the first 2 years of participation and yearly thereafter for up to 4 years. Follow-up assessments included cardiopulmonary exercise testing, a 6-minute walk test, and a physical activity questionnaire. The primary end point was a composite of all-cause mortality or all-cause hospitalization. Secondary end points included all-cause mortality, the composite of cardiovascular mortality or cardiovascular hospitalization, and the composite of cardiovascular mortality or HF hospitalization. Conclusions After adjustment for highly prognostic predictors of the primary end point, exercise training was associated with modestly significant reductions for both all-cause mortality or hospitalization and cardiovascular mortality or heart failure hospitalization.

  Study phs003599

• National Human Genome Research Institute (NHGRI) Clinical Sequencing Exploratory Research (CSER) The MedSeq Project: Integration of Whole Genome Sequencing into Clinical Medicine (HG006500)

  Whole genome sequencing (WGS) and whole exome sequencing (WES) services are currently available to and being utilized by physicians and their patients in both research and clinical settings, and recently to anyone in the general public via direct-to-consumer companies. But the widespread availability and use of WGS and WES in the practice of clinical medicine is imminent. In the very near future, sequencing of individual genomes will be inexpensive and ubiquitous, and patients will be looking to the medical establishment for interpretations, insight and advice to improve their health. Developing standards and procedures for the use of WGS information in clinical medicine is an urgent need, but there are numerous obstacles related to integrity and storage of WGS data, interpretation and responsible clinical integration. The MedSeq Project is an exploratory trial of WGS in clinical medicine. At the conclusion of this study, we will have helped create innovative protocols and novel outcome measures that can be applied safely in future large-scale multi-site randomized clinical trials with larger numbers of physicians from broad specialties and with more economically and ethnically diverse patients. Together with our colleagues from across the nation through the U01 consortium formed as a result of this funding from the NIH, we will have invented a process of implementation and evaluation whereby the fruits of the Human Genome Project can be applied for the first time to the daily practice of medicine for the betterment of human health. The objectives of the MedSeq Project are to: Recruit, consent and enroll 2 study groups: 10 primary care physicians and 100 of their healthy middle-aged patients 10 cardiologists and 100 of their patients with cardiomyopathy. Randomize each study group to receive standard of care versus standard of care plus WGS. Monitor the entire protocol for subject safety. Only half the enrolled patients were selected for sequencing. Fifty subjects were selected from the primary care cohort and fifty were selected from the cardiomyopathy cohort. Whole genome sequencing was performed at 30x coverage in Illumina's CLIA-certified laboratory on these 100 individuals. Generate and optimize an algorithm for interpreting WGS data covering the spectrum of human genetic variation, in terms of both previously reported and novel variants likely to influence the health of patients. Create patient reports and provide an interface for communicating clinically relevant genomic information to practicing physicians. Describe physicians' and patients' attitudes toward, and preferences for, the disclosure of WGS results at the start of the study. Evaluate physicians' experiences with receiving and interpreting patients' genetic test results and how they communicate these results to their patients. Explore how patients respond to and use WGS results by administering validated scales of psychological impact, personal utility, and behavioral responses, as well as economic and health outcomes. Although we do not have a large enough sample size for statistical comparisons of outcomes, we will conduct exploratory comparisons: Exploratory Hypotheses: Patients who receive WGS results will show equivalent levels of distress compared to patients who receive family history only. Patients with higher genetic literacy and better understanding will report greater satisfaction and less decisional regret. Patients who receive WGS will (a) be more likely to change health behaviors and (b) utilize more health care resources than those who do not receive WGS.

  Study phs000958

• INCLUDE Data Hub: NDA GUIDs for Down Syndrome Research

  The INCLUDE (INvestigation of Co-occurring conditions across the Lifespan to Understand Down syndromE) Project is an NIH-wide collaboration that seeks to improve health and quality of life for people with Down syndrome. The INCLUDE Project Data Coordinating Center (DCC) and partners created the INCLUDE Data Hub, a centralized data resource that allows access to large-scale clinical and multi-omics datasets specific to Down syndrome and supports collaborative, cloud-based analysis to accelerate scientific discoveries related to Down syndrome and its co-occurring conditions. The INCLUDE Data Hub includes an innovative researcher data repository, a portal, and a cloud-based platform for data analysis. The portal provides access to de-identified demographics and clinical metadata, as well as multi-omics datasets, including whole genome sequences, transcriptomes, proteomes, and metabolomes. The INCLUDE Data Hub uses a 'registered access' model, whereby users can access the portal and associated data after agreeing to terms of use. From the Data Hub, users can also reach 'controlled access' data (e.g., whole genome sequences) only for those studies for which they have obtained approval by an NIH Data Access Committee through the corresponding dbGaP study. A thoughtful linkage strategy to identify duplicate participants across studies enables researchers to merge multiple datasets and data types to create richer datasets and reduce costly redundancies in large-scale data generation (e.g., -omics) while mitigating potential risks introduced by linkage.Based on recommendations from the NICHD Office of Data Science and Sharing, which completed a comprehensive assessment of existing Privacy Protecting Record Linkage (PPRL) and associated data governance solutions, the INCLUDE DCC and the associated NIH Steering Committee have implemented NIMH Data Archive Global Unique Identifiers (NDA GUIDs) in the INCLUDE Data Hub. The NDA GUID Tool is a government-owned and operated PPRL technology that enables researchers to link data from multiple sources to the same individual without revealing personally identifiable information (PII). With the NDA GUID Tool, the same participant information will return the same GUID whenever or wherever it is entered. The GUID itself is not personally identifiable information or protected health information. Sharing data with NDA GUIDs allows approved researchers to link together data on a single participant, even if the data were collected at different locations or through different studies or are distributed from different data repositories. This dbGaP study enables researchers to access an INCLUDE GUID Mapping File that includes all available NDA GUIDs and their associations to study-specific Participant IDs across studies in the INCLUDE Data Hub. This dbGaP study only distributes NDA GUIDs associated with the INCLUDE Data Hub datasets. To access the associated controlled-access datasets, add the corresponding dbGaP studies to your Data Access Request. A list of these studies is available on the INCLUDE Data Hub Portal: https://portal.includedcc.org/studies.

  Study phs003678

• South African breast cancer GWAS genotype data in VCF format

  South African breast cancer GWAS genotype data for 2823 female African breast cancer cases. The data was generated using the H3Africa Custom microarray and genotyped on the Illumina HiScan instrument. The dataset is in VCF format.

  Dataset EGAD00010002732

• Meniere Disease Genomic Data Access Committee

  This Data Access Committee is responsible for reviewing and managing data access requests related to genomic variant files from whole exome sequencing of patients diagnosed with Meniere disease. This includes data from both familial and sporadic forms of the disease.

  Dac EGAC50000000708

• pediatric AML genomic sequences

  This dataset contains whole sequencing data from 30 patients with pediatric AML. For each patient, there is one dataset derived from tumor cells and one dataset derived from a matched non-malignant control.

  Dataset EGAD50000001572

• Shank2 Gene knockout/modified WGS data

  Whole genome sequncing data of original/SHANK2 modified/SHANK2 knockout. Note that the SHANK2 knockout sample is a different sample from 1_0441_003. Please refer to other paper for the data.

  Dataset EGAD00001004575