Admixture mapping is a potentially powerful tool for finding disease susceptibility genes in complex genetic diseases. The method depends on recent admixture between different ethnic groups for which differences in the distribution of susceptibility genes exist, and ancestry of the chromosomal regions can be distinguished in the admixed population. We believe that this approach will be a useful complement to genome-wide linkage studies that often lack power and association based methodologies that are difficult to apply genome-wide. For providing proof of the applicability of admixture mapping it is necessary to 1) identify a set of markers that distinguish ancestry;2) develop and apply multilocus statistical tests for linkage in the presence of ancestral association to simulations of real genotyping data;and 3) provide an actual demonstration of the method in a real disease. These are the major objectives of this proposal. Preliminary studies by our group as well as other investigators have shown that African Americans are a large admixed population for which admixture mapping is likely to be applicable. Epidemiological studies suggest that systemic lupus erythematosus is a disease that disproportionately affects individuals with African heritage. Preliminary studies provide confidence that a Ancestry Informative Markers (AIMs) can identify African versus European ancestry and that the vast majority of these AIMs in contrast to other markers have only small intra-ethnic differences within the European and African founding populations. Furthermore, the current results of several groups including the Perlegen Sciences screen of over 1.6 million SNPs suggest that a sufficiently large genome-wide set of AIMs is now available for a robust statistical analysis. This proposal will establish a genome wide set of >4000 AIMs that are characterized in African, European American, and African American populations. The typing of 950 African American SLE cases and 500 matched African American controls will provide the necessary data for simulations and testing as well as the opportunity to explore the usefulness of this method for a disease of major importance to the health of African Americans.
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