Combined analysis of exon splicing and genome wide polymorphism data predict schizophrenia risk loci

Christopher Oldmeadow; David Mossman; Tiffany-Jane Evans; Elizabeth G Holliday; Paul A Tooney; Murray J Cairns; Jingqin Wu; Vaughan Carr; John R Attia; Rodney J Scott

doi:10.1016/j.jpsychires.2014.01.011

Combined analysis of exon splicing and genome wide polymorphism data predict schizophrenia risk loci

J Psychiatr Res. 2014 May:52:44-9. doi: 10.1016/j.jpsychires.2014.01.011. Epub 2014 Jan 24.

Authors

Affiliations

¹ Hunter Medical Research Institute and Faculty of Health, University of Newcastle, NSW, Australia. Electronic address: christopher.oldmeadow@newcastle.edu.au.
² Hunter Medical Research Institute and Faculty of Health, University of Newcastle, NSW, Australia; School of Biomedical Sciences and Pharmacy, Faculty of Health, University of Newcastle, NSW, Australia; Schizophrenia Research Institute, Sydney, NSW, Australia.
³ Hunter Medical Research Institute and Faculty of Health, University of Newcastle, NSW, Australia.
⁴ School of Biomedical Sciences and Pharmacy, Faculty of Health, University of Newcastle, NSW, Australia; Schizophrenia Research Institute, Sydney, NSW, Australia.
⁵ Schizophrenia Research Institute, Sydney, NSW, Australia; Research Unit for Schizophrenia Epidemiology, School of Psychiatry, University of New South Wales, Australia.
⁶ Hunter Medical Research Institute and Faculty of Health, University of Newcastle, NSW, Australia; School of Biomedical Sciences and Pharmacy, Faculty of Health, University of Newcastle, NSW, Australia; Division of Molecular Medicine, Hunter Area Pathology Service, John Hunter Hospital, Newcastle, NSW, Australia.

PMID: 24507884
DOI: 10.1016/j.jpsychires.2014.01.011

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.

Keywords: Alternative splicing; Exons; GWAS; Genetics; Phosphorylation; Schizophrenia.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

14-3-3 Proteins / genetics
Analysis of Variance
Brain / metabolism
Cell Cycle Proteins / genetics
Cytoskeletal Proteins
Exons / genetics*
Female
Genetic Predisposition to Disease / genetics*
Genome-Wide Association Study
Humans
Male
Microtubule-Associated Proteins / genetics
Nerve Tissue Proteins / genetics
Nuclear Proteins / genetics
Polymorphism, Single Nucleotide / genetics*
RNA Splicing / genetics*
RNA-Binding Proteins
Schizophrenia / genetics*
Schizophrenia / pathology
Transcription Factors / genetics

Substances

14-3-3 Proteins
BICD2 protein, human
Cell Cycle Proteins
Cytoskeletal Proteins
DLG3 protein, human
MCPH1 protein, human
Microtubule-Associated Proteins
Nerve Tissue Proteins
Nuclear Proteins
RNA-Binding Proteins
Transcription Factors
YWHAH protein, human
ZC3H13 protein, human