Complex genetic mechanisms underlie susceptibility to schizophrenia. The goal of this proposed collaborative R01 project, submitted as part of the Clinical Studies of Mental Disorders (CSMD) program, is to combine genetic and neurobiologic paradigms enabling detection and localization of genes that modulate susceptibility to schizophrenia and related phenotypes. As part of a major collaborative effort between the University of Pennsylvania (UPENN, Dr. R. Gur, P.I.), the University of Pittsburgh (UPITT, Dr. V. Nimgaonkar, P.I.) And the Southwest Foundation for Biomedical Research (SFBR, Dr. L. Almasy, Dr. J. Blangero, P.Is.), we propose to shift the focus on the genetic basis of schizophrenia to the detailed dissection of correlated endophenotypes. We anticipate that these continuously distributed phenotypes related to brain function will serve as reliably measured risk factors and indicators of schizophrenia liability in a way that is similar to the multiple risk factors that are routinely assessed as indicators of chronic common diseases (e.g., the relationship of cholesterol measures to risk of atherosclerosis). It is likely that neurocognitive endophenotypes are more proximal functions of gene action than schizophrenia itself and therefore any contributing genetic loci should be substantially easier to localize and characterize. A combined sample of 50 multiplex multigenerational families with about 1000 members will be ascertained at the UPENN and the UPITT. Comprehensive diagnostic assessment will include the DIGS, the FIGS and scales for dimensionalizing symptoms. DSM-IV diagnoses will be made by consensus best-estimate procedures. Quantitative neurocognitive measures will be obtained using efficient computerized testing that produces a neurocognitive profile of endophenotypic markers leading to characterization of brain function. SFBR will provide the expertise in genetics of complex traits and carry out the molecular and statistical genetic analyses. Using highly polymorphic genetic markers spaced at approximately 10 cM intervals, we will localize quantitative trait loci (QTLs) influencing phenotypic variation in te neurocognitive endophenotypes employing a novel oligogenic linkage analysis method. Additionally, multivariate linkage analysis will localize pleiotropic genes that jointly influence endophenotypic variation and schizophrenia liability. All collected data will become part of the NIMH-sponsored archival database for schizophrenia.
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