Childhood obesity in the United States has dramaticallyincreased in the past decade. The proportion of children exceeding the 95lh and 85vhpercentiles for body mass index (BMI) is among the greatest in Mexican-Americans. Despite the high prevalence of obesity among Hispanic children, the genes underlying the heightened susceptibility to childhood-onset obesity in Hispanic populations have not been investigated. The specific goal of this project is to test the hypothesis that a number of genes, each with a measurable effect on the expression of childhood obesity, can be identified by the use of a systematic genomic screen.
The specific aims are:1) to identify and phenotype 300 obese Hispanic probands (ages 4-18 y) and their biological parents and siblings, 2) to construct a 10cM map for 1600 Hispanic individuals to be used in a genome-wide scan for loci that affect quantitative phenotypes of adiposity and energy expenditure using high-throughput genotyping techniques, 3) to perform a multipoint genome scan to find and localize QTLs that influence quantitative variation in adiposity, and energy expenditure in children by performing variance component linkageanalysis,and 4) to use multivariate quantitative trait linkage analysis to test whether QTLs localized in Aim 3 have measurable pleiotropic effects across phenotypes. Our target sample will include 1600 genotyped individualsdispersed over 300 nuclear families with a minimum of threechildren, ascertained on the obese proband using a bivariate scheme (i.e., >95lh percentile for BMI and >85'h percentile for fat mass).Phenotyping will includeanthropometry and body composition, as well as factors associated with the development of obesity: energy partitioning during growth, energy expenditure, physical fitness and activity, hormones, metabolites, and neurotransmitters. Anthropometry and body composition measurements will be repeated after 1 y to determine body weight and fat change in the children. Approximately 360 hyper-variable STR markers willbe typed for each individualto produce a 10cM genome map. Multipoint linkage analysis using variance components methods will be applied to nuclear family data to search for QTLs influencing obesity-related phenotypes in Hispanic children.We will test the null hypothesis that the additivegenetic variance due to a QTL equals zero (no |linkage) jy comparing the likelihood of this restricted model with that of a model in which the variance is estimated. This QTL method will be mplemented in the program package SOLAR using estimationprocedures from FISHER. Lastly, we will test for pleiotropic effects of obesity-related QTLs across phenotypes. PERFORMANCE S1TE(S) (organization, city, state) Baylor College of Medicine USDA/ARS Children's Nutrition Research Center Houston, TX Southwest Foundation for Biomedical Research San Antonio, TX KEY PERSONNEL. See instructions on Page Name Nancy F. Butte, Ph.D. Carlos A. Bacino, M.D. Anthony G. Comuzzie, Ph.D. Kenneth J. Ellis, Ph.D. James E. Hixson, Ph.D. 11. Use cunrinuaiion pages as needed to provide the required information in the format shown below. Organization Role on Project Baylor College of Medicine Investigator USDA/ARS Children's NutritionResearch Center Baylor College of Medicine Investigator Texas Children's Hospital Southwest Foundation for Biomedical Research Investigator Baylor College of Medicine USDA/ARS Children's NutritionResearch Center Investigator Southwest Foundation for Biomedical Research Investigator PHS 398 (Rev. 4/98) Page 2 BB Number pages consecutively at the bottom throughoutthe;application. Do not use suffixes such as 3a, 3b. cc Priru Investigator/Program Director (Last, first, middle): jtte, Nancy F., Ph.D. Type the name of the principal investigator/program directorat the top of each page and each continuation page. (For type specifications, see instructions on page 6.) RESEARCH GRANT TABLE OF CONTENTS Page Numbers Face Page 1 Description,
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