|Institution:||Wake Forest University|
|Full text PDF:||http://hdl.handle.net/10339/39269|
It is estimated that over 25 million people in the United States are diabetic, which equates to approximately 8% of the population. Type 2 Diabetes (T2D) is the most common form of diabetes, being identified by high blood glucose levels due to the body not producing enough insulin and not responding to the insulin it does produce. This disease is also a major risk factor for developing cardiovascular disease (CVD). There are many risk factors for cardiometabolic disease (the global risk of developing T2D and/or CVD). These include altered glucose homeostasis, abnormal lipid metabolism, and increased inflammation, as well as the environmental and genetic components underlying these conditions. Previous genetic research has mainly focused on searching for common genetic variants which contribute to risk, however, these variants have only managed to explain ~10% of genetic risk. The "missing heritability" may be due to other factors such as rare variants. The purpose of this project was to determine whether rare or low frequency coding variants play a meaningful and detectable role in cardiometabolic traits. These projects utilized the Insulin Resistance Atherosclerosis Family Study (IRASFS), a well phenotyped cohort of large Hispanic- and African-American families. We have tested whether coding variants were the basis for linkage peaks for complex traits in 42 African-American and 90 Hispanic families using Illumina HumanExome Beadchips. Greater than 80,000 variants in each population were polymorphic and tested using two-point linkage, single variant association, and gene-based analyses with 37 cardiometabolic phenotypes. Additionally, a detailed analysis of the performance of both two-point linkage and single variant association analyses was performed on Chromosome 3 with the trait adiponectin, in order to determine the characteristics of these results when a known low frequency, high impact variant is present. This analysis also incorporated genotype data from a Genome-Wide Association Study performed as part of the GUARDIAN Consortium. These projects demonstrate the continued utility of linkage analysis in the modern era. Combined with association analysis, linkage is a powerful tool to identify variants contributing significantly to phenotypic variance. Additionally, two-point linkage analysis can be used to localize novel, un-genotyped variants to a specific genomic region.