Mapping Adiposity QTLS in the NHLBI Family Heart Study

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DESCRIPTION (provided by applicant): Obesity has become a national epidemic. We propose to seek DNA polymorphisms associated with higher BMI, to identify genes involved in obesity. This application builds upon a genome scan for BMI performed in the NHLBI Family Heart Study (FHS) on 4,211 subjects in 718 families. We will extend this work by disequilibrium mapping under one of the largest linkage peaks on chromosome 13q 14 (lod=3.2). We will focus our efforts on 144 families (715 individuals) with the highest contribution to the support for the linkage. We will refine the location of the underlying QTL by statistically modeling epistatic effects, sex effects, and possible pleiotropic effects. A series of candidate genes falling in the linkage region will be evaluated by SNP-typing, and if no associations are found, disequilibrium mapping techniques will be applied to the anonymous region under the linkage peak. We will begin with three well-motivated candidate genes - HRT2A, EDNRB, and LMO7 - and we have identified 12 others using bioinformatics resources. In a related aim, we will also test obesity candidate genes located in other regions of suggestive linkage (1.5<1od<2.0), using a case-control sample, comprised of subjects with the highest and lowest BMIs in the study. Two groups of 350 unrelated subjects each, equally distributed over the 4 field centers and 2 sexes, aged 40-70 years, will be genotyped. We will test adiponectin and apoD (3q29), PPARgamma (3p25), and ADRB2 (5q31). A variety of statistical modeling techniques will be used including haplotype analysis, hierarchical linkage disequilibrium mapping incorporating information on block structure, and a Bayesian approach to evaluating all possible haplotypes within a region. We believe that the state-of-the-art approaches proposed here, as well as the experience of the investigative team in all relevant realms - study design, genotyping and bioinformatics, and statistical model development and analysis - will lead to new discoveries of the genes and specific variants influencing human obesity.