Nonlinear tests for genetic studies of complex disease

Linkage and association studies are major analytical tools to search for susceptibility genes for complex diseases. With the availability of large collection of single nucleotide polymorphisms (SNPs) and the rapid progresses for high throughput genotyping technologies, together with the ambitious goals of the International HapMap Project, genetic markers covering the whole genome will be available for genome-wide linkage and association studies. In order not to inflate the type I error rate in performing genome-wide linkage and association studies, multiple adjustment for the significant level for each independent linkage and/or association test is required, and this has led to the suggestion of genome-wide significant cut-off as low as 5 × 10 −7. Almost no linkage and/or association study can meet such a stringent threshold by the standard statistical methods. Developing new statistics with high power is urgently needed to tackle this problem. This dissertation proposes and explores a class of novel test statistics that can be used in both population-based and family-based genetic data by employing a completely new strategy, which uses nonlinear transformation of the sample means to construct test statistics for linkage and association studies. Extensive simulation studies are used to illustrate the properties of the nonlinear test statistics. Power calculations are performed using both analytical and empirical methods. Finally, real data sets are analyzed with the nonlinear test statistics. Results show that the nonlinear test statistics have correct type I error rates, and most of the studied nonlinear test statistics have higher power than the standard chi-square test. This dissertation introduces a new idea to design novel test statistics with high power and might open new ways to mapping susceptibility genes for complex diseases. ^

THE ALCOHOL TREATMENT PROFILE SYSTEM: ITS DEVELOPMENT AND AN EVALUATION OF ITS CAPABILITIES

The development of the Alcohol Treatment Profile System (ATPS) was described and an evaluation of its perceived value by various States was undertaken, The ATPS is a treatment needs assessment tool based on the unification of several large national epidemiologic and treatment data sets. It was developed by the National Institute on Alcohol Abuse and Alcoholism (NIAAA) and responsibility for its creation was given to the NIAAA's Alcohol Epidemiologic Data System (AEDS). The ATPS merges county-level measures of alcohol problem prevalence (the specially constructed AEDS Alcohol Problem Indicators), indicating "need" for treatment, and treatment utilization measures (the National Drug and Alcohol Treatment Utilization Survey), indicating treatment "demand." The capabilities of the ATPS in the unique planning and policy-making settings of several States were evaluated.^