Schizophrenia is one of the world's major unsolved public health problems. It is a relatively common, chronic, debilitating disease of variable expression. Little is known about the causes of schizophrenia but there is convincing evidence that genetic factors play some role in the etiology of schizophrenia. However, the mechanism is not known. Most investigators believe schizophrenia is etiologically heterogeneous. Over 20 genome scans for schizophrenia susceptibility loci (SSL) in the last decade have identified multiple regions likely to harbor SSL. Subsequent meta-analyses of these scans confirm contributions of some loci and identify other novel regions which may harbor vulnerability loci. The long-term objective of this study is to elucidate the genetic heterogeneity of schizophrenia by identifying genes associated with susceptibility. We will conduct dense SNP genotyping using both family-based and population based analyses in four candidate chromosomal regions in order to detect SSL. Regions on chromosomes 6p21, 8p21, 13q32 and 22q 11 have been identified based on replicated linkage analyses or confirmed associations. Case-control and linkage disequilibrium studies in a unique genetically homogeneous community (Ashkenazi Jews) will be conducted using state-of-the-art high throughput, robust, and cost-efficient SNP BeadArray technology developed by Illumina. DNA and clinical assessments of 418 individuals with schizophrenia are available (parental dnas are available for 281 of the subjects). An ethnically matched screened control sample of Ashkenazi DNAs will be available for case/control analyses. In order to confirm any detected risk loci, we will ascertain 1) a new clinical sample of 300 Ashkenazi Jewish individuals who have a DSM-IV diagnosis of schizophrenia or schizoaffective disorder and 2) an additional 300 ethnically-matched screened controls. A verification strategy will use DNAs from this replication sample in follow-up case/control analyses. The laboratory plan consists of a 1) a dense search of four candidate regions at an average 25 Kb density using innovative family-based and case/control statistical methods to detect risk haplotypes; 2) evaluation and sequencing of identified positional candidate genes; 3) a staged follow-up and verification strategy in an independent sample. We will make all SNP genotyping data publicly available and deposit dnas and clinical data into the national repository at the NIMH Center for Genetic Studies.
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