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Table of contents
  1. 1. Clinical Trial
  2. 2. Routine Documentation
  3. 3. Registry/Cohort Study
  4. 4. Quality Assurance
  5. 5. Data Standard
  6. 6. Patient-Reported Outcome
  7. 7. Medical Specialty
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- 1/29/25 - 6 forms, 1 itemgroup, 4 items, 1 language
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

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pht002612.v2.p2

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pht002613.v2.p2

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pht002614.v2.p2

1 itemgroup 7 items

pht005037.v1.p2

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- 4/28/24 - 5 forms, 1 itemgroup, 1 item, 1 language
Itemgroup: IG.elig

pht005251.v1.p1

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pht005253.v1.p1

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pht005252.v1.p1

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pht005254.v1.p1

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- 4/28/24 - 5 forms, 1 itemgroup, 1 item, 1 language
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

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pht005178.v1.p1

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pht006203.v1.p1

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pht005177.v1.p1

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- 12/1/23 - 4 forms, 1 itemgroup, 1 item, 1 language
Itemgroup: IG.elig
Principal Investigator: Stephen T. McGarvey, PhD, MPH, Brown University, Providence, RI, USA MeSH: Obesity,Adiposity,Lipids,Blood Pressure https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000972 The individuals sequenced here represent a small subset of the parent study (described below) and were carefully selected for the purpose of creating a Samoan-specific reference panel for imputation back into the parent study. The INFOSTIP algorithm of Gusev et. al. (2012) (PMID: 22135348) was used to optimally choose the individuals for sequencing. The research goal of the parent study (dbGaP ID phs000914) is to identify genetic variation that increases susceptibility to obesity and cardiometabolic phenotypes among adult Samoans using genome-wide association (GWAS) methods. DNA from peripheral blood and phenotypic information were collected from 3,119 adult Samoans, 23 to 70 years of age. The participants reside throughout the independent nation of Samoa, which is experiencing economic development and the nutrition transition. Genotyping was performed with the Affymetrix Genome-Wide Human SNP 6.0 Array using a panel of approximately 900,000 SNPs. Anthropometric, fasting blood biomarkers and detailed dietary, physical activity, health and socio-demographic variables were collected. We are replicating the GWAS findings in an independent sample of 2,500 Samoans from earlier studies. After replication of genomic regions and informative SNPs in those regions, we will determine sequences of the important genes, and determine the specific genetic variants in the sequenced genes that are associated with adiposity and related cardiometabolic conditions. We will also identify gene by environment interactions, focusing on dietary intake patterns and nutrients.

pht005679.v1.p1

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pht005680.v2.p1

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pht005681.v2.p1

1 itemgroup 9 items
- 3/5/23 - 4 forms, 1 itemgroup, 6 items, 1 language
Itemgroup: IG.elig
Principal Investigator: Sharon L.R. Kardia, PhD, University of Michigan, Ann Arbor, MI, USA MeSH: Hypertension,Aging,Arterial Pressure,Arteriosclerosis,Atherosclerosis,Biomarkers,Blood Pressure,Cardiovascular Diseases,Cholesterol,Cholesterol, HDL,Cholesterol, LDL,Coronary Artery Disease,Diabetes Mellitus,Echocardiography,Endophenotypes,Hyperglycemia,Hyperinsulinism,Hypertrophy, Left Ventricular,Inflammation,Kidney Failure, Chronic,Leukoaraiosis,Lipids,Obesity,Obesity, Abdominal,Peripheral Arterial Disease,Renal Insufficiency, Chronic,Triglycerides,Vascular Calcification https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001345 The Genetic Epidemiology Network of Arteriopathy (GENOA) is one of four networks in the NHLBI Family-Blood Pressure Program (FBPP). GENOA's long-term objective is to elucidate the genetics of target organ complications of hypertension, including both atherosclerotic and arteriolosclerotic complications involving the heart, brain, kidneys, and peripheral arteries. The longitudinal GENOA Study recruited European-American and African-American sibships with at least 2 individuals with clinically diagnosed essential hypertension before age 60 years. All other members of the sibship were invited to participate regardless of their hypertension status. Participants were diagnosed with hypertension if they had either 1) a previous clinical diagnosis of hypertension by a physician with current anti-hypertensive treatment, or 2) an average systolic blood pressure = 140 mm Hg or diastolic blood pressure = 90 mm Hg based on the second and third readings at the time of their clinic visit. Only participants of the African-American Cohort were sequenced through TOPMed. The Family Blood Pressure Program (FBPP), GENOA's parent program, is an unprecedented collaboration to identify genes influencing blood pressure (BP) levels, hypertension, and its target-organ damage. This program has conducted over 21,000 physical examinations, assembled a shared database of several hundred BP and hypertension-related phenotypic measurements, completed genome-wide linkage analyses for BP, hypertension, and hypertension associated risk factors and complications, and published over 130 manuscripts on program findings. The FBPP emerged from what was initially funded as four independent networks of investigators (HyperGEN, GenNet, SAPPHIRe and GENOA) competing to identify genetic determinants of hypertension in multiple ethnic groups. Realizing the greater likelihood of success through collaboration, the investigators created a single confederation with program-wide and network-specific goals. Comprehensive phenotypic data for GENOA study participants are available through dbGaP phs001238.

pht008602.v1.p1

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pht008603.v1.p1

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pht008604.v1.p1

1 itemgroup 10 items
- 2/25/23 - 6 forms, 1 itemgroup, 11 items, 1 language
Itemgroup: IG.elig
Principal Investigator: Kathleen Mullan Harris, PhD, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA MeSH: Adolescent Health,National Longitudinal Study of Adolescent Health,Obesity,Body Weight,Cholesterol,C-Reactive Protein,Depression,Alcohol Drinking,Smoking,Personality,Life Style,Ethnic Groups,Health Status,Population Groups,Housing,Socioeconomic Factors,Educational Status,Employment,Family Characteristics,Income,Occupations,Poverty,Risk Factors https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001367 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 data base 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: Design Paper: *The Add Health Study: Design and Accomplishments Kathleen Mullan Harris Carolina Population Center University of North Carolina at Chapel Hill 2013*

pht008249.v1.p1

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pht008245.v1.p1

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pht008246.v1.p1

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pht008247.v1.p1

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pht008248.v1.p1

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- 1/13/23 - 6 forms, 1 itemgroup, 4 items, 1 language
Itemgroup: IG.elig
Principal Investigator: Dharambir Sanghera, PhD, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA MeSH: Diabetes Mellitus, Type 2,Obesity https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000583 The Punjabi Sikh population is a well-defined, carefully collected homogeneous sample from northern India and the US. It has unique characteristics, which are ideal for genetic studies. Sikhs are *strictly* a non-smoking population and about 50% of participants are life-long vegetarians. All subjects included in the genome-wide association studies (GWAS) were recruited from one geographical location. Our population demonstrates a strong familial clustering of type 2 diabetes and related cardio-metabolic disorders that may be genetic and we believe that the contribution of alleles at specific loci are likely to be unique to Punjabi Asians compared to Europeans. Our group first showed that the association of a common variant at rs9939609 in the *FTO* (fat mass and obesity) gene in South Asians was independent of BMI (PMID:18598350) in contrast to Europeans where the association of same variant with T2D is mediated through obesity (PMID:17434869). These findings were later confirmed in an independent sample of South Indians (PMID:19005641), Pakistanis (PMID:21294771), and even East and South Asians in a large meta-analyses study comprising 96,551 individuals (PMID: 22109280). Earlier reported association of *MTNR1B* with fasting glucose concentrations and type 2 diabetes in European GWAS could not be confirmed in our Sikh cohort. On the other hand, our study revealed, for the first time, a significant protective association of another less common variant in *MTNR1B* with fasting glucose levels that was modulated by obesity. Ours was the first report that suggested that the low CETP activity was associated with higher CAD risk (PMID:22143414) in South Asians and that the genetic effects are significantly modulated by environmental factors (alcohol consumption). Our recent GWAS on type 2 diabetes has identified a novel locus at chromosome 13q12 in the *SGCG* gene (p=1.82x10sup-8/sup) associated with type 2 diabetes (PMID:23300278) in Punjabi Sikhs. From these findings, we are optimistic that our resource will provide new insights to gene functions in the diabetic pathway and better help researchers to understand and translate these insights to novel therapeutic treatment and early prevention to T2D that may be important beyond Indians.

pht003292.v1.p1

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pht003293.v1.p1

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pht003295.v1.p1

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pht003296.v1.p1

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pht003294.v1.p1

1 itemgroup 5 items
- 12/13/22 - 4 forms, 1 itemgroup, 1 item, 1 language
Itemgroup: IG.elig
Principal Investigator: Cora E. Lewis, MD, University of Alabama at Birmingham, Birmingham, AL, USA MeSH: Cardiovascular Diseases,Hypertension,Atherosclerosis,Obesity,Lipids,Diabetes Mellitus,Smoking,Pulmonary Function Test,Physical Activities,Energy Intake,Diet https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000309 *For the GENEVA CARDIA project, three genotype call sets were generated from a single set of array scans as a consequence of DNA sample quality problems. These call sets are designated "Birdsuite-1", "Birdsuite-2" and "Beaglecall". ("Beaglecall" used both Birdseed and BEAGLECALL calling algorithms.) An analysis-ready genotypic data set is provided in PLINK format for the "Beaglecall" set only, because it performs very well in QC analyses. Only raw CHP and ALLELE_SUMMARY files are provided for the two Birdsuite call sets because they have significant quality issues. Use of the Beaglecall set is highly recommended. Users of the other two call sets should proceed with caution. More details are given in the genotypic QC report.* The CARDIA study, sponsored by the National Heart, Lung and Blood Institute (NHLBI), is a prospective, multi-center investigation of the natural history and etiology of cardiovascular disease in African-Americans and Whites 18-30 years of age at the time of initial examination. The initial examination included 5,115 participants selectively recruited to represent proportionate racial, gender, age, and education groups from 4 communities: Birmingham, AL; Chicago, IL; Minneapolis, MN; and Oakland, CA. Participants from the Birmingham, Chicago, and Minneapolis centers were recruited from the total community or from selected census tracts. Participants from the Oakland center were randomly recruited from the Kaiser-Permanente health plan membership. From the time of initiation of the study in 1985-1986, five follow-up examinations have been conducted at years 2, 5, 7, 10, 15, and 20. The Year 25 examination is scheduled to begin in 2010. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors associated with variation in longitudinal blood pressure profiles during the critical transition period from young adulthood to early middle-age; and to characterize their interactions with relevant environmental factors, such as body weight profiles. Genotyping was performed at the Broad Institute of MIT and Harvard, a GENEVA genotyping center. Data cleaning and harmonization were performed at the GEI-funded GENEVA Coordinating Center at the University of Washington.

pht001997.v2.p2

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pht001999.v2.p2

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pht001998.v2.p2

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- 11/15/22 - 6 forms, 1 itemgroup, 1 item, 1 language
Itemgroup: IG.elig
Principal Investigator: Nancy F. Butte, PhD, Baylor College of Medicine, Houston, TX, USA MeSH: Obesity,Diabetes Mellitus, Type 2 https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000616 The VIVA LA FAMILIA Study was designed to identify genetic variants influencing childhood obesity and its comorbidities in the Hispanic population. Family recruitment and phenotyping were conducted in 2000-2005 in Houston, TX. All enrolled children (n=1030) and parents gave written informed consent or assent. The protocol was approved by the Institutional Review Boards for Human Subject Research for Baylor College of Medicine and Affiliated Hospitals and for Texas Biomedical Research Institute. The VIVA LA FAMILIA study design and methodology have been described in detail (Butte NF, 2006). Each family was ascertained on an obese proband, defined as a BMI 95th percentile, between the ages 4-19 y. The cross-sectional, longitudinal study design consisted of baseline measurements, with a one-year. GWAS was performed using the Illumina HumanOmni1 v1.0 BeadChips on 815 children from 263 Hispanic families and HumanOmni 2.5-8v1 on an additional 43 children. Exome sequencing is being performed on 822 children using NimbleGen capture, followed by Illumina DNA sequencing. Butte NF, Cai G, Cole SA, Comuzzie AG. Viva la Familia Study: genetic and environmental contributions to childhood obesity and its comorbidities in Hispanic population. Am J Clin Nutr 2006;84(3):646-54. PMID: 16960181

pht003368.v2.p2

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pht003369.v2.p2

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pht003370.v2.p2

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pht003372.v2.p2

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pht003371.v2.p2

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- 10/12/22 - 3 forms, 1 itemgroup, 4 items, 1 language
Itemgroup: pht001035.v1.p1
https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000090 The Atherosclerosis Risk in Communities (ARIC) Study, sponsored by the National Heart, Lung and Blood Institute (NHLBI), is a prospective epidemiologic study conducted in four U.S. communities. The four communities are Forsyth County, NC; Jackson, MS; the northwest suburbs of Minneapolis, MN; and Washington County, MD. ARIC is designed to investigate the etiology and natural history of atherosclerosis, the etiology of clinical atherosclerotic diseases, and variation in cardiovascular risk factors, medical care and disease by race, gender, location, and date. ARIC includes two parts: the Cohort Component and the Community Surveillance Component. The Cohort Component began in 1987, and each ARIC field center randomly selected and recruited a cohort sample of approximately 4,000 individuals aged 45-64 from a defined population in their community. A total of 15,792 participants received an extensive examination, including medical, social, and demographic data. These participants were reexamined every three years with the first screen (baseline) occurring in 1987-89, the second in 1990-92, the third in 1993-95, and the fourth and last exam was in 1996-98. Follow-up occurs yearly by telephone to maintain contact with participants and to assess health status of the cohort. In the Community Surveillance Component, currently ongoing, these four communities are investigated to determine the community-wide occurrence of hospitalized myocardial infarction and coronary heart disease deaths in men and women aged 35-84 years. Hospitalized stroke is investigated in cohort participants only. Starting in 2006, the study conducts community surveillance of inpatient (ages 55 years and older) and outpatient heart failure (ages 65 years and older) for heart failure events beginning in 2005. ARIC is currently funded through January 31, 2012. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to atherosclerosis and cardiovascular disease through large-scale genome-wide association studies of well-characterized cohorts of adults in four defined populations. Genotyping was performed at the Broad Institute of MIT and Harvard, a GENEVA genotyping center. Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

pht000114.v1.p1

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pht001036.v1.p1

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- 10/12/22 - 3 forms, 1 itemgroup, 5 items, 1 language
Itemgroup: pht001240
Principal Investigator: Claire Fraser-Liggett, University of Maryland School of Medicine, Baltimore, MD, USA MeSH: Obesity,Obesity, Morbid https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000258 Emerging evidence that the gut microbiota may contribute in important ways to human health and disease has led us and others to hypothesize that both symbiotic and pathological relationships between gut microbes and their host may be key contributors to obesity and the metabolic complications of obesity. Our "Thrifty Microbiome Hypothesis" poses that gut microbiota play a key role in human energy homeostasis. Specifically, constituents of the gut microbial community may introduce a survival advantage to its host in times of nutrient scarcity, promoting positive energy balance by increasing efficiency of nutrient absorption and improving metabolic efficiency and energy storage. However, in the presence of excess nutrients, fat accretion and obesity may result, and in genetically predisposed individuals, increased fat mass may result in preferential abdominal obesity, ectopic fat deposition (liver, muscle), and metabolic complications of obesity (insulin resistance, hypertension, hyperlipidemia). Furthermore, in the presence of excess nutrients, a pathological transition of the gut microbial community may occur, causing leakage of bacterial products into the intestinal lymphatics and portal circulation, thereby inducing an inflammatory state, further aggravating metabolic syndrome traits and accelerating atherosclerosis. This pathological transition and the extent to which antimicrobial leakage occurs and causes inflammatory and other maladaptive sequelae of obesity may also be influenced by host factors, including genetics. In the proposed study, we will directly test the Thrifty Microbiome Hypothesis by performing detailed genomic and functional assessment of gut microbial communities in intensively phenotyped and genotyped human subjects before and after intentional manipulation of the gut microbiome. To address these hypotheses, five specific aims are proposed: (1) enroll three age- and sex-matched groups from the Old Order Amish: (i) 50 obese subjects (BMI 30 kg/m2) with metabolic syndrome, (ii) 50 obese subjects (BMI 30 kg/m2) without metabolic syndrome, and (iii) 50 non-obese subjects (BMI 25 kg/m2) without metabolic syndrome and characterize the architecture of the gut microbiota from the subjects enrolled in this study by high-throughput sequencing of 16S rRNA genes; (2) characterize the gene content (metagenome) to assess the metabolic potential of the gut microbiota in 75 subjects to determine whether particular genes or pathways are correlated with disease phenotype; (3) characterize the transcriptome in 75 subjects to determine whether differences in gene expression in the gut microbiota are correlated with disease phenotype, (4) determine the effect of manipulation of the gut microbiota with antibiotics on energy homeostasis, inflammation markers, and metabolic syndrome traits in 50 obese subjects with metabolic syndrome and (5) study the relationship between gut microbiota and metabolic and cardiovascular disease traits, weight change, and host genomics in 1,000 Amish already characterized for these traits and in whom 500K Affymetrix SNP chips have already been completed. These studies will provide our deepest understanding to date of the role of gut microbes in terms of 'who's there?', 'what are they doing?', and 'how are they influencing host energy homeostasis, obesity and its metabolic complications? PUBLIC HEALTH RELEVANCE: This study aims to unravel the contribution of the bacteria that normally inhabit the human gastrointestinal tract to the development of obesity, and its more severe metabolic consequences including cardiovascular disease, insulin resistance and Type II diabetes. We will take a multidisciplinary approach to study changes in the structure and function of gut microbial communities in three sets of Old Order Amish patients from Lancaster, Pennsylvania: obese patients, obese patients with metabolic syndrome and non-obese individuals. The Old Order Amish are a genetically closed homogeneous Caucasian population of Central European ancestry ideal for genetic studies. These works have the potential to provide new mechanistic insights into the role of gut microflora in obesity and metabolic syndrome, a disease that is responsible for significant morbidity in the adult population, and may ultimately lead to novel approaches for prevention and treatment of this disorder.

pht001242.v2.p1

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pht001241.v2.p1

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- 10/12/22 - 5 forms, 1 itemgroup, 11 items, 1 language
Itemgroup: IG.elig

pht002438.v1.p1

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pht002439.v1.p1

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pht002440.v1.p1

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pht002441.v1.p1

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