Localization of chromosomal regions influencing the phenotypes of the metabolic syndrome
The goal of this project was to study the genetic structure of the metabolic syndrome. The first objective was to locate chromosomal regions influencing insulin resistance in Mexican Americans of the San Antonio Family Heart Study (SAFHS). Two studies were performed to achieve this objective using a genomewide scan. In the first study using data from the first visit of the SAFHS, we detected significant linkage evidence on chromosome 8p between marker D8S1130 and D8S1106 and on chromosome 13q between marker D13S787 and D13S252. In the second study that used data from the second visit of the SAFHS, markers D1S1663 on chromosome 1 and D2S436 on chromosome 2 were found to be linked to insulin sensitivity indices. Candidate genes on detected locations were proposed. The significant findings in both studies duplicate those of previous investigations. The second objective of this project was to identify the genetic locations related to the quantitative traits that constitute the metabolic syndrome in the same population of Mexican Americans. Principal component factor analysis (PCFA) was conducted, and significant and suggestive evidence for linkage of lipid (factor 4) and body size/adiposity (factor 1) were found on chromosome 4 near marker D4S403 and chromosome 1 near marker D1S1597, respectively. The third objective of this project was to explore the genetic pleiotropy between insulin resistance and adiposity, especially visceral obesity using the baboon as a model. The present study is the first to use omental tissue to investigate gene pleiotropy between visceral fat and insulin resistance. The results from the baboon study in this thesis, coupled with research in humans, suggest that a common set of genes contribute to insulin resistance and obesity in both species. It is also plausible that those two groups of genes completely overlap each other. At present, the variance decomposition based, multipoint linkage analysis is a mathematical model that can provide useful information for susceptible gene mapping. Future finemapping and the positional candidate gene approach will be helpful to further our understanding of the genetic structure of this complex disease.