This is a request for a Career Development Award. The purpose of this application is to ensure the applicant adequate time for research, necessary to the continued development of her career as an independent investigator in statistical genetics with psychiatric applications, as well as to provide additional clinical training. The candidate is an expert in the application of statistical methods in psychiatric research. From 1990-1995 she has been supported by a prior NIMH Career Development Award. During the time she has acquired a broad background in human and psychiatric genetics and developed her skills in her own area of expertise, and she has already made several fundamental contributions to the field of statistical methods in psychiatric research. She has recently been recruited to join the faculty of The College of Medicine at the University of Iowa which has an outstanding research program in psychiatry and a strong commitment to genetics research. The discovery of genetic mechanisms underlying psychiatric disorders can facilitate diagnosis and prevention, aid in the development of more effective interventions, and broaden understanding of the contributions of both nature and nurture to psychopathology. Enormous technologic advances in recent years have made sophisticated modeling of complex genetic disorders feasible in principle. However, what is available in theory is not always feasible in practice. A fundamental source of difficulty involves proper procedures for sampling (ascertainment of families) and proper mathematical treatment of sampling in data analysis. Unresolved sampling problems can make planning and executing a genetic study of a complex disorder extremely difficult. The proposed research will address major sampling issues for complex genetic analysis using both analytic mathematical approaches and simulation studies. The candidate maintains ongoing established collaborations with clinicians on genetic studies of panic disorder, autism, and obsessive-compulsive disorder. All theoretical work will be both guided by and applied to the analysis of data from these studies.
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