Complex disorders are familial, but do not have simple patterns of transmission and are likely to result from the actions and interactions of multiple genetic and environmental factors. Common complex disorders, including such diseases as type 2 diabetes mellitus, asthma, hypertension, psychiatric illnesses, and coronary disease, account for a large and disproportionate share of health care costs, but remain poorly characterized with respect to the primary defects that may be most amenable to treatment and prevention. Identifying and characterizing the genetic component to complex disorders should be useful in determining not only the primary defects for such disorders, but also in clarifying the role of environmental risk factors, which could also be targets of cost-effective treatment and prevention strategies. Results of genetic studies in complex disorders have been disappointing, however, identifying few regions likely to contain genes with large effects on susceptibility to disease, and fewer still that are replicated in subsequent studies. Such results are likely due to the combined effects of inadequate sample sizes, inadequate models for genetic analysis, and the genuine complexity of the genetic component to disease susceptibility in many complex disorders. The investigators propose to develop and test methods and distribute software implementing new approaches in: (1) robust linkage analysis, including an extension that allows the identification of interactions between loci; (2) assessing linkage disequilibrium that is robust to assumptions about population history and (3) the development of an analytic framework, with components of linkage and linkage disequilibrium analysis, for the positional cloning of genes for complex disorders. The preliminary studies confirm that these approaches can improve the ability to detect and localize genes for complex traits, thereby improving the odds for successful positional cloning.
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