Using brain molecular QTLs to identify novel risk genes shared by multiple psychiatric diseases. C. Liu1, 2, 4, C. Zhang1, 4, C. Chen1, 2, 4, J. A. Badner3, N. Alliey-Rodriguez3, E. S. Gershon3, E. R. Gamazon5, . IOCDF-GC., . TSAICG., N. J. Cox5 1) Dept Psychiatry, Univ of Illinois, Chicago, Chicago, IL; 2) State Key Laboratory of Medical Genetics, Central South University, Changsha, PR China; 3) Dept of Psychiatry, Univ of Chicago, Chicago, IL; 4) Inst. of Human Genetics, Univ of Illinois at Chicago, Chicago, IL; 5) Dept of Medicine, Univ of Chicago, Chicago, IL.

   Genome-wide association studies (GWASs) have detected some common variants associated with psychiatric diseases. Many common SNPs have been found to be associated with gene expression or DNA methylation levels in human brain by quantitative trait loci (QTL) mapping. We and others have shown that SNPs associated with expression or DNA methylation were enriched in GWAS signals. Using expression QTL (eQTL) and DNA methylation QTL (mQTL) mapping results from multiple postmortem brain collections, we studied QTL SNPs (p < 0.001) in GWAS signals (p<0.01) of bipolar disorder (BD), schizophrenia (SCZ), major depression (MDD), autism (ASD), attention deficit and hyperactivity disorder (ADHD), obsessive compulsive disorder (OCD) and Tourette syndrome (TS) for their abilities explaining disease heritability. We further compared lists of eSNPs in disease GWAS signals across two or three diseases to identify putatively functional SNPs that are shared across multiple diseases. After we showed that GWAS signals of psychiatric diseases were significantly enriched with brain eQTL and mQTL SNPs, we further found that 19-50% of psychiatric disease heritability captured by GWAS could be explained by brain eQTLs. Different diseases shared different amount of expression QTL SNPs (eSNPs) in their GWAS signals. SCZ and BD shared the most comparing to other disease combinations. Cerebellum, parietal, and temporal cortex data, gene level and exon level analyses showed consistent pattern of sharing. The pattern clearly indicated a spectrum of genetic relatedness among the seven psychiatric diseases. By examining eSNPs shared by three diseases, we found one eSNP shared by SCZ, BD and MDD; and eight eSNPs shared by SZ, BD and OCD. Fifteen genes were regulation targets of these SNPs. Most of these genes were associated with mouse behavioral phenotypes that may link to psychiatric diseases. Interestingly, type II diabetes, as a control disease, has the fewest brain eSNPs in its GWAS signals than psychiatric diseases. But it still shares one eSNP with SCZ. The shared SNP is associated with expression of CACNA1C, which is a known risk genes of both SCZ and BD. Brain eQTL and mQTL data helped to identify novel functional SNPs and their target genes for multiple diseases. Different diseases share different amount of eSNPs that can be captured by GWAS. Multiple novel risk genes were identified as shared risk genes of psychiatric diseases, even non-psychiatric disease.

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