This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Phylogenetic application to complex psychiatric phenotypes : Testing for genetic linkage along a continuum of psychosis Emil Kraepelin dichotomously classified manic-depressive insanity (bipolar disorder) and dementia praecox (schizophrenia) at the turn of the 20th century, a view which has predominated to present day. However almost immediately following the introduction of Kraepelins classifications many (including Kreapelin himself) questioned their validity, recognizing that these categorical distinctions as well as those of many other psychiatric disorders define broad, heterogeneous diagnostic groups with significant overlap of behavioral phenotypes among several of these categories. The alternative to categorical classifications is the suggestion that psychiatric disorders are related as part of a continuum of psychosis. Some have even argued that psychiatric disorders are not only themselves interrelated but represent the extreme variants of personality traits in the general population with normal individuals who do not meet standards for a medically relevant diagnosis possessing symptoms of these disorders. The concept of a continuum of psychosis lends support to the notion that multiple genes may contribute to certain behavioral symptoms shared by these diagnostic categories or shared by a subset of individuals within a diagnostic category. We present an analytical approach based on phylogenetic methods used in evolutionary biology to examine the genetic basis of behavioral phenotypes of psychiatric patients along a continuum of psychosis, irrespective of their previous psychiatric diagnosis. The individuals are grouped in a network generated using the parsimony optimality criterion on the basis of shared behavioral symptoms along a continuum. The network is determined by taking a consensus of all equally optimal networks obtained by arranging individuals in such a way so as to minimize the number of times all symptoms change state (i.e., from present to absent) on the network. Groups of phenotypically similar individuals are tested for significant genetic linkage in increasingly more inclusive groups based on the topology of this network. Behavioral symptoms defining potentially homogeneous phenotypic groups are tested for linkage in subsets of families, thus potentially identifying genetically significant phenotypic subtypes. Empirical p values are calculated to correct for the testing of multiple phenotypic groups, genetic models and genetic markers. We apply this approach to 1,789 subjects belonging to 296 families taken from a genetic study of schizophrenia for which a whole genome scan was previously reported in DeLisi et. al. (Am. J. Psychiatry, 159:5, 2002).
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