3613 results for "*geneti*"

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• Framingham Cohort

  Origins and Research MissionCardiovascular disease (CVD) is the leading cause of death and serious illness in the United States. In 1948, the National Heart Institute (now the National Heart, Lung, and Blood Institute, NHLBI) launched the Framingham Heart Study to identify common factors contributing to cardiovascular disease (CVD), which had become a leading cause of death in the United States. Researchers recruited 5,209 men and women (ages 30–62) from Framingham, Massachusetts who had not yet developed overt CVD symptoms to follow prospectively over time through detailed physical examinations and lifestyle interviews.Study Population and Longitudinal Follow-upThe original cohort was followed for over 75 years with 32 exams completed. To extend the study's reach across generations and represent the changing demographics of the Framingham community, additional cohorts were enrolled: the Offspring cohort (5,124 adult children and spouses of original participants, enrolled 1971, 10 exams to date); the Third Generation cohort (4,095 grandchildren, enrolled 2002, 4 exams to date); and two ethnically diverse Omni cohorts (506 and 410 individuals of African American, Hispanic, Asian, Indian, Native American, and Pacific Islander descent, enrolled 1995 and 2002, respectively, with 5 and 4 exams to date). Additionally, 102 spouses of Offspring participants (New Offspring Spouse cohort) were enrolled in 2002 with 4 exams completed. Across all cohorts, in-person examinations occur at varying intervals (every 2 years for the Original cohort; roughly every 4–7 years for other cohorts) and consist of detailed medical history, physical examination, and laboratory testing.Comprehensive Phenotypic DataOver decades of careful monitoring, FHS research has generated extensive phenotypic data spanning multiple domains: cardiovascular risk factors and biomarkers (blood pressure, cholesterol, triglycerides, HDL, smoking, obesity, diabetes, physical inactivity); subclinical vascular disease detected through advanced imaging (echocardiography, carotid ultrasound, cardiac and aortic CT, brain and cardiac MRI); clinical outcomes (coronary heart disease, stroke, heart failure, intermittent claudication); and chronic conditions beyond CVD (osteoporosis, arthritis, nutritional status, eye disease, hearing disorders, chronic obstructive lung disease, stroke, and dementia including Alzheimer's disease). To view the phenotype variables collected from the Framingham Cohort, please click on the "Variables" tab above.Genetic and Genomic ResourcesLarge-scale genotyping and sequencing projects have been conducted across all FHS cohorts, reflecting advances in genomic technology over time—progressing from microsatellite markers and candidate gene studies to exome chips, GWAS chips, exome, targeted, and whole-genome sequencing. Coverage varies by analysis type and cohort as the research portfolio has evolved. Additionally, mRNA and miRNA expression data, DNA methylation, RNA sequencing, metabolomics, proteomics, and other omics data are available, providing complementary molecular phenotypes for research across the full range of FHS phenotypic domains spanning decades of longitudinal data. The Framingham Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the "Substudies" section of this top-level study page phs000007 Framingham Cohort. phs000342 Framingham SHARe phs000282 Framingham CARe phs000363 Framingham SABRe phs000307 Framingham Medical Resequencing phs000401 Framingham ESP Heart-GO phs000651 Framingham CHARGE-S phs000724 Framingham DNA Methylation phs001610 Framingham T2D-GENES phs002558 Framingham ADSP phs002559 Framingham BRIDGET phs002560 Framingham Cholesterol phs002611 Framingham Post-Mortem Brain Tissue phs002938 Framingham Molecular QTLphs004576 Framingham Platelet RNA Sequencing The unflagging commitment of the research participants in the NHLBI FHS has made more than a half century of research success possible. For decades, the FHS has made its data and DNA widely available to qualified investigators throughout the world through the Limited Access Datasets and the FHS DNA Committee, and the SHARe database will continue that tradition by allowing access to qualified investigators who agree to the requirements of data access. With the SHARe database, we continue with an ambitious research agenda and look forward to new discoveries in the decades to come.

  Study phs000007

• Center for Common Disease Genomics [CCDG] - Neuropsychiatric: Epilepsy: Epi25 Consortium

  Epilepsy genetics research is at an exciting stage where it is now feasible, with the power of a large cohort, to understand the more complex genetic components of epilepsy. The driving principle behind the Epi25 Consortium is collaboration and synergy - it is only possible to achieve this type of research by working together. The Epi25 Consortium was formed by the unification of various consortia, including Epi4K, EPIGEN, EuroEPINOMICS, the Epilepsy Phenome/Genome Project, EpiPGX, SANAD, and EpiCURE, and individual epilepsy investigators. The consortium's sample collection is the best resource in the world for this disease, both in terms of numbers of patients and quality of phenotypic information. As part of the NHGRI Centers for Common Disease Genomics (2016-2020), we aggregated a global sample collection from the various repositories for whole genome genotyping and whole exome sequencing (WES) at the Broad Institute (Cambridge, MA), initiating the largest and most ethnically diverse genetic study of epilepsy to date. The primary epilepsy phenotypes for Epi25 are based on strict standards agreed upon by the epilepsy community. The epilepsy cases contributed by Epi25 sites can be broadly defined as genetic generalized epilepsy (GGE), non-acquired focal epilepsy (NAFE), epileptic encephalopathies (EE), and lesional focal epilepsies. More information about eligibility criteria and phenotyping forms for Epi25, as well as the contributing centers, can be found here: epi-25.org The genomic data will be analyzed iteratively to identify genes and variants that explain these types of epilepsy. Summary clinical data compiled in the Epi25 clinical database will allow retrospective phenotypic analyses of groups of subjects with common genomic variant(s).

  Study phs001489

• NHLBI TOPMed: Genetics of Asthma in Latino Americans (GALA)

  This is a case pharmacogenetic study of bronchodilator drug response (Albuterol) among racially admixed Latino children with asthma between the ages of 8-40. Lung function testing was performed using the KoKo PFT system and each participant was administered albuterol dependent on age. Participants under 16 years of age, were administered 2 puffs of albuterol from a standard metered dose inhaler and 4 puffs for participants over 16 years old. The overall goal is to identify genetic factors which are predictive of drug response in children with asthma. The principal tools include a questionnaire and biological specimen collection. Participants with asthma have physician-diagnosed asthma, symptoms and medications.

  Study phs001542

• NextGen Consortium: The iPSCORE (iPSC Collection for Omic Research) Resource for Studying the Impact of Genetic Variation on Molecular and Physiological Phenotypes - Whole Genome Sequence

  The iPSC Collection for Omic Research (iPSCORE) Resource was created as part of the Next-Gen Consortium funded by NHLBI. The overarching purpose of the resource is to provide a large collection of human induced pluripotent stem cells (iPSCs) for use in studying the impact of genetic variation on molecular and physiological phenotypes. The resource has been used in a number of studies in the Dr. Kelly A. Frazer's Lab examining both the characteristics of human iPSCs and a variety of iPSC-derived cell types including cardiovascular progenitor cells (iPSC-CVPCs), pancreatic precursor cells (iPSC-PPCs), and retina pigment epithelium cells (iPSC-RPEs). We have shown that the iPSCs, CVPCs, and PPCs are suitable surrogate models to identify genetic factors active in early developmental processes because they exhibit fetal-like molecular properties.A total of 273 individuals have participated in the study, of which 222 have had iPSCs generated from fibroblasts. Of the 273 individuals, 181 are part of 55 families that include 24 monozygotic twin pairs and 5 dizygotic twin pairs, allowing for the incorporation of familial relationships into genetic analyses.Germline DNA has been sequenced from blood or fibroblast samples for all 273 individuals (available through dbGaP phs001325) and other genomic data (RNA-seq, DNA methylation, genotype arrays, ATAC-seq, H3K27ac ChIP-seq, HiC-seq) have been generated from the 222 iPSCs as well as derived cell types (available through dbGaP phs000924).QTL analyses were conducted for multiple omics data types and summary statistics are available through dbGaP phs0001325.Important note: Of the 273 individuals, 268 are consented for general research use and 5 are consented for cardiac research only.For detailed information about iPSCORE Collection including samples, methods used to generate the data, and how to access the datasets visit the Frazer lab website.The 222 well characterized iPSC lines that constitute the iPSCORE resource are available, please contact Dr. Kelly A. Frazer (kafrazer@health.ucsd.edu) if you are interested in obtaining the collection.

  Study phs001325

• National Heart, Lung, and Blood Institute (NHLBI) Bench to Bassinet Program: The Gabriella Miller Kids First Pediatric Research Program of the Pediatric Cardiac Genetics Consortium (PCGC)

  Multi-center, prospective observational cohort study of individuals with congenital heart defects (CHD). Phenotypic data and source DNA derived from 300 probands and their parents, and family of interest collected to investigate relationships between genetic factors and phenotypic and clinical outcomes in patients with CHD. This Kids First project represents a subset of the PCGC data. Other PCGC data can be accessed through phs001194 and other Kids First data can be accessed through kidsfirstdrc.org.

  Study phs001138

• Gene Expression and Epigenetic Analyses of Human Myocytes from Different Muscles

  The study contains expression, DNA methylation data and genomic data of in vitro cultured primary myoblasts, immortalized control myoblast, and mutant myoblasts. The primary myoblasts were derived from biopsies of control, facioscapulohumeral dystrophy 1 (FSHD1) and FSHD2 patients from the tibialis anterior, quadricep, bicep and deltoid. FSHD is linked to DUX4 (Gene ID: 100288687) mRNA expression from the last copy of the D4Z4 repeats on chromosome 4q. The control myoblast cell line was derived from a quadricep biopsy of a healthy individual. The mutant cells, carrying either D4Z4 mutations, SMCHD1 (Gene ID: 23347) mutation or both, were generated from the control myoblast cells by CRISPR-mediated genome editing. Expression data is from bulk RNA-seq using the SmartSeq2 protocol for days 0 and 5 of differentiation of the primary myocytes from the bicep and deltoid of FSHD1 patients, and for days 0, 3/4/5 (early myotubes) and 12/13/14 (late myotubes) of differentiation of the immortalized control and mutant myocytes. DNA methylation data was produced using the TruSeq Methyl Capture EPIC kit (Illumina) for days 0, 3 and 12 of in vitro differentiation of primary myocytes from the tibialis anterior and quadricep of healthy individuals and FSHD2 patients. Genomic data for myoblasts was acquired by targeted, amplification-free DNA sequencing using CRISPR/Cas and the Nanopore sequencing platform. For Electrical Pulse Stimulation (EPS), immortalized control and FSHD patient myocytes were subjected to EPS on day 10 of differentiation using a C-Pace EM culture pacer. Cells with or without EPS stimulation were harvested 6 hours after completion of stimulation for RNA extraction.

  Study phs002554

• Add Health: Longitudinal Study of a Nationally Representative Sample of Adolescents in Grades 7-12 in the United States during the 1994-95 School Year, Followed into Adulthood with Five Interviews/Surveys in 1995-96, 2001-02, 2008, and 2016-18

  The National Longitudinal Study of Adolescent to Adult Health [Add Health] is an ongoing longitudinal study of a nationally representative U.S. cohort of more than 20,000 adolescents in grades 7-12 (aged 12-19 years) in 1994 followed into adulthood with five interviews/surveys in 1995, 1996, 2001-02, 2008, and 2016-18. Add Health was designed to understand how social environments and behaviors in adolescence are linked to health and achievement outcomes in young adulthood. Add Health contains unprecedented environmental, behavioral, psychosocial, biological, and genetic data from early adolescence and into adulthood on a large, nationally representative cohort with unprecedented racial, ethnic, socioeconomic, and geographic diversity. Add Health has a large, multidisciplinary user base of over 50,000 researchers around the world who have published over 3,400 research articles. Add Health is housed at the Carolina Population Center of the University of North Carolina at Chapel Hill. Add Health datasets are distributed according to a tiered data disclosure plan designed to protect the data from the risk of direct and indirect disclosure of respondent identity. Add Health's large sample size, population diversity and rich longitudinal database of psychosocial, physical, and contextual data will permit investigation of an exceptionally broad range of phenotypes with known genetic variation. Prospective longitudinal measures are available to document change over time in each of these phenotypes, as well as change in the social environment and life experiences, making the Add Health sample ideal for understanding genetic linkages with health and behavior across the life course. The original design of Add Health included important features for understanding biological processes in health and developmental trajectories across the life course of young people, including an embedded genetic sample with more than 3,000 pairs of adolescents with varying biological resemblance (e.g., twins, full sibs, half sibs, and adolescents who grew up in the same household but have no biological relationship), testing of saliva and urine for sexually transmitted infections and HIV, and biomarkers of cardiovascular health, metabolic processes, immune function, renal function, and inflammation. Add Health therefore has critical objective indicators of health status and disease markers in young adulthood, well before chronic illness or its complications emerge in later adulthood. Because DNA has been collected on the full sample at Wave IV, it is possible to link genetic profiles with social, behavioral, and biological measures over time from adolescence into adulthood. Add Health sampled the multiple environments in which young people live their lives, including the family, peers, school, neighborhood, community, and relationship dyads, and provides independent and direct measurement of these environments over time. Add Health contains extensive longitudinal information on health-related behavior, including life histories of physical activity, involvement in risk behavior, substance use, sexual behavior, civic engagement, education, and multiple indicators of health status based on self-report (e.g., general health, chronic illness), direct measurement (e.g., overweight status and obesity), and biomarkers. No other data resource with this expanse of genotype and phenotype data on a large nationally representative longitudinal sample with race, ethnic, socioeconomic, and geographic diversity exists. A complete reference guide on study design and accomplishments can be found on the Add Health website: https://cdr.lib.unc.edu/concern/articles/6t053j27s.

  Study phs001367

• INCLUDE: Genetic Underpinnings of the Multifactorial Phenotype of Trisomy 21 Patients Unveiled by Multi-Omics Approaches

  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 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.Down syndrome (DS) is the most common chromosomal abnormality in livebirths with an incidence of 1 in 700 in the US. To better understand the pathophysiology of DS, this proposal will generate and analyze sequence data on 777 pediatric DS patients from the Children's Hospital of Philadelphia (CHOP), as well as 321 mothers and 148 fathers. We anticipate that the information derived from this deeply-phenotyped cohort will allow for improved understanding of the pathophysiology and molecular mechanisms underlying DS-associated comorbidities, which may inform on new practices for treatment or innovative future therapies.

  Study phs002983

• Jackson Heart Study (JHS) Cohort

  The Jackson Heart Study (JHS) is a large, community-based, observational study whose participants were recruited from urban and rural areas of the three counties (Hinds, Madison and Rankin) that make up the Jackson, MS metropolitan statistical area (MSA). Participants were enrolled from each of 4 recruitment pools: (1) random, 17%, (2) volunteer, 30%, (3) currently enrolled in the Atherosclerosis Risk in Communities (ARIC) Study, 31%, and (4) secondary family members, 22%. The final cohort of 5,306 participants included 6.59% of all African American Jackson MSA residents, aged 35-84, during the baseline exam (N-76,426, US Census 2000). Among these, approximately 3,600 gave consent that allows genetic research and deposition of data into dbGaP. Major components of three clinic examinations (see study history) include medical history, physical examination, blood/urine analytes, and interview questions on areas such as physical activity, stress, coping and spirituality, racism and discrimination, socioeconomic position, and access to health care. Extensive clinical phenotyping includes anthropometrics, electrocardiography, carotid ultrasound, ankle-brachial blood pressure index, echocardiography, CT chest and abdomen for coronary and aortic calcification, liver fat, and subcutaneous and visceral fat measurements, and cardiac MRI. At 12-month intervals after the baseline clinic visit (Exam 1), participants have been contacted by telephone to update information, confirm vital statistics, document interim medical events, hospitalizations and functional status, and obtain additional sociocultural information. Questions about medical events, symptoms of cardiovascular disease and functional status are repeated annually. Ongoing cohort surveillance includes abstraction of medical records and death certificates for relevant International Classification of Diseases (ICD) codes and adjudication of nonfatal events and deaths. CMS data are currently being incorporated into the dataset. Note: Regarding date variables warehoused in the Jackson Heart Study (JHS) Cohort on dbGaP, the coordinating center has developed an algorithm that will systematically review and de-identify any of the (nearly 100) date-related variable types stored in the data package. To simultaneously minimize (i) de-identifiability of the data and (ii) impact on analyses utilizing sensitive data elements, a participant-level random number was generated to avoid the necessity of sharing any potentially sensitive data. The coordinating center maintains an archived linkage of these data in their raw form and regularly reviews ad hoc requests to utilize the raw data on a project-by-project basis. The JHS Cohort is utilized in the following dbGaP substudies. To view genotypes, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the "Substudies" section of this top-level study page phs000286 JHS Cohort. phs000402 ESP Heart GO JHS phs000498 JHS Allelic Spectrum Seq phs000499 JHS CARephs001069 MI Gen JHS phs001098 T2D GENES Exome Seq phs001356 Exome Chip phs002256 Cardiometabolic Renal Proteomics phs002369 Metabolomics Insulin Resistance

  Study phs000286

• Center for Common Disease Genomics [CCDG] - Neuropsychiatric: Genomics of Autism Spectrum Disorder (GASD)

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants, both in coding and noncoding regions, will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of New York Genome Center (NYGC). WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal.An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases, pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs002509