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Modelos de datos seleccionados

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- 29/1/25 - 6 formularios, 1 itemgroup, 4 items, 1 idioma
Itemgroup: pht005036
Principal Investigator: David Weir, PhD, University of Michigan, Ann Arbor, MI, USA MeSH: Aging,Neoplasms,Arthritis,Lung Diseases, Obstructive,Dementia,Heart Diseases,Heart Failure,Hypertension,Myocardial Infarction,Diabetes Mellitus,Hypercholesterolemia,Obesity,Body Weight,Mobility Limitation,Pain,Cholesterol,Hemoglobin A, Glycosylated,C-Reactive Protein,Cystatin C,Depression,Alcohol Drinking,Smoking,Personality,Life Style,Cognition,Demography,Ethnic Groups,Health Status,Population Groups,Housing,Independent Living,Socioeconomic Factors,Career Mobility,Educational Status,Employment,Family Characteristics,Income,Occupations,Poverty,Social Change,Social Class,Social Conditions,Risk Factors https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000428 *Introduction to V2: *This data release comprises data from the V1 release combined with approximately 3,000 additional samples, collected during the HRS 2010 field period. The 2010 data include samples from a random half of the new cohort enrolled in 2010 along with a significant expansion of the minority sample. *Description:* The University of Michigan Health and Retirement Study (HRS) is a longitudinal panel study that surveys a representative sample of approximately 20,000 people in America over the age of 50 every two years. Supported by the National Institute on Aging (NIA U01AG009740) and the Social Security Administration, the HRS explores the changes in labor force participation and the health transitions that individuals undergo toward the end of their work lives and in the years that follow. The study collects information about income, work, assets, pension plans, health insurance, disability, physical health and functioning, cognitive functioning, and health care expenditures. Through its unique and in-depth interviews, the HRS provides an invaluable and growing body of multidisciplinary data that researchers can use to address important questions about the challenges and opportunities of aging. Because of its innovation and importance, the HRS has become the model and hub for a growing network of harmonized longitudinal aging studies around the world. *Origins of the HRS.* As the population ages it is increasingly important to obtain reliable data about aging and topics that are relevant to a range of policy issues in aging. To address this need, the National Institutes on Aging (NIA) established a cooperative agreement with the University of Michigan Institute for Social Research to collect such data. The HRS launched data collection in 1992 and has re-interviewed the original sample of respondents every two years since then. By adding new cohorts and refreshing the sample, the HRS has grown to become the largest, most representative longitudinal panel study of Americans 50 years and older. *HRS Study Design.* The target population for the original HRS cohort includes all adults in the contiguous United States born during the years 1931-1941 who reside in households, with a 2:1 oversample of African-American and Hispanic populations. The original sample is refreshed with new birth cohorts (51-56 years of age) every six years. The sample has been expanded over the years to include a broader range of birth cohorts as well. The target population for the AHEAD survey consists of United States household residents who were born in 1923 or earlier. Children of the Depression (CODA) recruits households born 1924-1930, War Babies 1942-47, Early Boomers 1948-53, and Mid-Boomers 1954-59. Data collection includes a mixed mode design combining in-person, telephone, mail, and Internet. For consenting respondents, HRS data are linked at the individual level to administrative records from Social Security and Medicare claims. *Genetic Research in the HRS.* The HRS has genotyped 2.5 million single nucleotide polymorphisms (SNPs) on respondents using Illumina's Human Omni2.5-Quad (Omni2.5) BeadChip. The genotyping was performed by the NIH Center for Inherited Disease Research (CIDR). Saliva was collected on half of the HRS sample each wave starting in 2006. In 2006, saliva was collected using a mouthwash collection method. From 2008 onward, the data collection method switched to the Oragene kit. Saliva completion rates were 83% in 2006, 84% in 2008, and 80% in 2010 among new cohort enrollees. HRS Phenotypic data. Phenotypic data are available on a variety of dimensions. Health measures include physical/psychological self-report, various health conditions, disabilities, cognitive performance, health behaviors (smoking, drinking, exercise), physical performance and anthropomorphic measures, and biomarkers (HbA1c, Total Cholesterol, HDL, CRP, Cystatin-C). Data are also available on health services including utilization, insurance and out-of-pocket spending with linkage to Medicare records. Economic measures include employment status/history, earnings, disability, retirement, type of work, income by source, wealth by asset type, capital gains/debt, consumption, linkage to pensions, Social Security earnings/benefit histories. There is also extensive information on family structure, proximity, transfers to/from of money, time, social and psychological characteristics, as well as a wide range of demographics. Performance on a cognitive test combining immediate and delayed word recall was selected as an example trait for the dbGaP data release. In the immediate word recall task the interviewer reads a list of 10 nouns to the respondent and asks the respondent to recall as many words as possible from the list in any order. After approximately five minutes of asking other survey questions, the respondent is asked to recall the nouns previously presented as part of the immediate recall task. The total recall score is the sum of the correct answers to these two tasks, with a range of 0 to 20. Researchers who wish to link to other HRS measures not in dbGaP will be able to apply for access from HRS. A separate Data Use Agreement (DUA) will be required for linkage to the HRS data. See the HRS website (http://hrsonline.isr.umich.edu/gwas) for details.

Eligibility

1 itemgroup 6 items

pht002612.v2.p2

1 itemgroup 4 items

pht002613.v2.p2

1 itemgroup 5 items

pht002614.v2.p2

1 itemgroup 7 items

pht005037.v1.p2

1 itemgroup 5 items
- 28/4/24 - 5 formularios, 1 itemgroup, 1 item, 1 idioma
Itemgroup: IG.elig
Principal Investigator: Ruth Loos, PhD, The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA MeSH: Cardiovascular Diseases,Obesity,Diabetes Mellitus, Type 2,Glucose,Kidney Failure, Chronic,Cholesterol, HDL,Cholesterol, LDL,Triglycerides,Coronary Disease,Myocardial Infarction,Inflammation,Stroke,Body Height https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000925 The Institute for Personalized Medicine (IPM) Bio*Me* Biobank 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 Bio*Me* Biobank populations include 28% African American, 38% Hispanic Latino predominantly of Caribbean origin, 23% Caucasian/White. IPM BioMe Biobank disease burden is reflective of health disparities with broad public health impact. 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. This study is part of the Population Architecture using Genomics and Epidemiology (PAGE) study (phs000356).

pht005176.v1.p1

1 itemgroup 4 items

pht005178.v1.p1

1 itemgroup 6 items

pht006203.v1.p1

1 itemgroup 6 items

pht005177.v1.p1

1 itemgroup 5 items
- 13/12/23 - 5 formularios, 1 itemgroup, 18 items, 1 idioma
Itemgroup: IG.elig
Principal Investigator: Dan M. Roden, MD, Vanderbilt University, Nashville, TN, USA MeSH: Myocardial Revascularization,Myocardial Infarction https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000963 Coronary heart disease (CHD) is an important public health problem in developed countries. Statins are effective in the prevention and treatment of CHD; nevertheless, many patients receiving statins still suffer cardiovascular events (CV) such as heart attack. Identifying genetic variants responsible for differential clinical responses to statins will not only allow individual patients at high residual risk to be targeted for additional therapies, but also will define new biologic pathways contributing to statin response, and thus new targets for future therapies. Accordingly, the goal of this study is to identify genetic variants associated with clinical CV in patients receiving statins. Subjects identified for study are of European descent and include 1718 subjects with CV while on statins (cases) and 4172 subjects without CV while on statins (controls). Key research resources utilized in this effort include VanderbiltD's BioVU DNA databank and associated Synthetic Derivative database of clinical information, and software tools developed to identify drugs and clinical events using Electronic Health Record-derived structured and unstructured ("free text") data. Most cases and controls identified include three data types: ICD-9 codes, medication regimens, and medical test results. Genotyping, using IlluminaD's Infinium HumanOmniExpressExome BeadChip (OmniExpressExome), was performed by the RIKEN Integrative Medical Sciences Center (IMS) and supported by the Pharmacogenomics Research Network (PGRN)-RIKEN IMS Global Alliance.

pht004856.v1.p1

1 itemgroup 3 items

pht004857.v1.p1

1 itemgroup 3 items

pht004858.v1.p1

1 itemgroup 10 items

pht004859.v1.p1

1 itemgroup 4 items
- 9/5/23 - 5 formularios, 1 itemgroup, 2 items, 1 idioma
Itemgroup: pht006087
Principal Investigator: Sekar Kathiresan, MD, Broad Institute, Cambridge, MA, USA MeSH: Myocardial Infarction,Inferior Wall Myocardial Infarction,Anterior Wall Myocardial Infarction https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001259 The VIRGO study is a four year research project funded by the NHLBI to study young women and men with heart attacks. A total of 2,000 women who are 18 - 55 years of age and a smaller comparison group of 1,000 similarly aged men will be enrolled in this multi-site observational study from approximately 120 different hospitals across the country. Young women have a much greater risk of dying after an acute myocardial infarction (AMI) than similarly aged men. Their mortality risk is markedly higher than that of young men, and limited data on young minority women suggest that they may have the highest risk of any young subgroup. Findings from the small number of published studies of young women with ischemic heart disease suggest that the biology, epidemiology, care, and outcomes of this group are distinct from those of men. To date, there have been no large studies of this population, even as the death toll is comparable to that from breast cancer in this country. This study will help researchers identify key factors that influence recovery from a heart attack and potentially improve the care and outcomes of young women and men with AMI. *Specific Aims:* To investigate the excess risk in young women with AMI and to identify key demographic, clinical, metabolic, psychosocial, health care delivery, and biological determinants of prognosis, we propose a national, prospective, observational study of 2,000 women who are 55 years or younger with AMI and a smaller comparison group of 1,000 men. Our prior work and preliminary studies indicate that the sex differences are most prominent in this age group and suggest that by 1 year after discharge, there are substantial sex differences in outcomes. We will also develop risk stratification tools that will help clinicians to identify young women with the highest and lowest risk. *Specific Aim 1:* Determine sex differences in outcomes following AMI. *Specific Aim 2:* Determine sex differences in the prevalence and prognostic importance of demographic, clinical, and psychosocial risk factors. * Specific Aim 3:*Determine sex differences in quality of care. *Specific Aim 4:* Determine sex differences in the prevalence and prognostic importance of selected biochemical biomarkers following AMI. *These samples have been whole genome sequenced as part of the NHGRI's Center for Common Disease Genetics at the Broad Institute.*

pht006088.v1.p1

1 itemgroup 3 items

pht006089.v1.p1

1 itemgroup 5 items

pht006090.v1.p1

1 itemgroup 4 items

Eligibility

1 itemgroup 22 items

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