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Updated: May 3, 2026

A Strategy to Identify de Novo Mutations in Common Disorders such as Autism and Schizophrenia
Published on: June 15, 2011
Combined analysis of exon splicing and genome wide polymorphism data predict schizophrenia risk loci
Christopher Oldmeadow1, David Mossman2, Tiffany-Jane Evans1
1Hunter Medical Research Institute and Faculty of Health, University of Newcastle, NSW, Australia.
Abstract:
Schizophrenia has a strong genetic basis, and genome-wide association studies (GWAS) have shown that effect sizes for individual genetic variants which increase disease risk are small, making detection and validation of true disease-associated risk variants extremely challenging. Specifically, we first identify genes with exons showing differential expression between cases and controls, indicating a splicing mechanism that may contribute to variation in disease risk and focus on those showing consistent differential expression between blood and brain tissue. We then perform a genome-wide screen for SNPs associated with both normalised exon intensity of these genes (so called splicing QTLs) as well as association with schizophrenia. We identified a number of significantly associated loci with a biologically plausible role in schizophrenia, including MCPH1, DLG3, ZC3H13, and BICD2, and additional loci that influence splicing of these genes, including YWHAH. Our approach of integrating genome-wide exon intensity with genome-wide polymorphism data has identified a number of plausible SZ associated loci.
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