Genetic dissection of complex trait has become one of the most important genetic research topics in recent years, because of its healthcare implications. Although genome-wide association studies are thought to hold the promise to identify susceptibility genes responsible to complex diseases, methodologies to take full advantage of the genotyping data are still lacking. Standard DNA marker-based approaches typically only consider a limited number of hypotheses, most of which are on the effect of a single locus or a relative few loci, therefore do not accommodate the full range of genetic mechanisms that may contribute to the disease phenotype. First Genetic Trust Inc (FGT) is developing an innovative data analysis method to map complex traits that consider all possible genetic mechanisms. Tailored to family-based and population-based association studies, this method utilize a novel pattern discovery-based approach and a collection of theoretically and empirically derived statistics to identify multi-locus disease associations. Instead of assuming a few possible genetic models, this method considers correlations among multiple markers at genome scale and allows detection of complex genetic models of inheritance for a disease. As the result, it could have significant more power than conventional single-locus analysis methods. The proposed research will investigate whether this pattern discovery-based approach is able to detect known susceptibility loci for a disease, and whether other susceptibility loci and interactions among susceptibility loci can be discovered and confirmed. In this research proposal, the novel method as well as several conventional genetic analysis methods will be applied to real dataset collected from association study for comparison. Detailed genomic database search on identified susceptibility loci will provide biological insight to validate results. Upon the validation of this method, FGT will develop a software package including the novel algorithm and the corresponding statistical framework and use it to support its clinical genetic discovery services. If indeed the utility of this pattern-based multi-locus analysis method is confirmed by the proposed research and subsequent follow-ups, this work will open up a completely new direction in the hunt for the genes responsible for common diseases that are complex and heterogeneous in nature. ? ?
