Association and linkage analyses of RGS4 polymorphisms in schizophrenia
Kodavali, V. Chowdari; Mirnics, Karoly; Semwal, Prachi; Wood, Jeol; Lawrence, Elizabeth; Bhatia, Triptish; Deshpande, N. Smita; Thelma, B.K.; Ferrel, E. Robert; Middleton, A. Frank; Devlin, Bernie; Levitt, Pat; Lewis, A. David and Nimgaonkar, L. Vishwajit (2002) Association and linkage analyses of RGS4 polymorphisms in schizophrenia. Human Molecular Genetics, 11 (12). pp. 1373-1380.
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Gene expression analyses of postmortem cerebral cortex suggest that transcription of the regulator of G-protein signaling 4 (RGS4) is decreased in a diagnosis-specific manner in subjects with schizophrenia. To evaluate the possible role of RGS4 in the pathogenesis of schizophrenia, we conducted genetic association and linkage studies using samples ascertained independently in Pittsburgh and New Delhi and by the NIMH Collaborative Genetics Initiative. Using the transmission disequilibrium test, significant transmission distortion was observed in the Pittsburgh and NIMH samples. Among single-nucleotide polymorphisms (SNPs) spanning approximately 300 kb, significant associations involved four SNPs localized to a 10 kb region at RGS4, but the associated haplotypes differed. A trend for transmission distortion was also present in the Indian sample for haplotypes incorporating the same SNPs. Consistent with the linkage/association observed from the family-based tests, samples with affected siblings (NIMH, India) showed higher levels of allele sharing, identical by descent, at RGS4. When the US patients were contrasted to two population-based control samples, however, no significant differences were observed. To check the specificity of the transmission bias, we therefore examined US families with bipolar I disorder (BD1) probands. This sample also showed a trend for transmission distortion, and differed significantly from the population-based controls for the four-SNP haplotypes tested in the other samples. The transmission distortion is unlikely to be due to chance, but its mechanism and specificity require further study. Our results illustrate the potential power of combining gene expression profiling and genomic analyses to identify susceptibility genes for genetically complex disorders.
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