Psychiatric genome-wide association study analyses implicate neuronal, immune and histone pathways

Abstract

Genome-wide association studies (GWAS) of psychiatric disorders have identified multiple genetic associations with such disorders, but better methods are needed to derive the underlying biological mechanisms that these signals indicate. We sought to identify biological pathways in GWAS data from over 60,000 participants from the Psychiatric Genomics Consortium. We developed an analysis framework to rank pathways that requires only summary statistics. We combined this score across disorders to find common pathways across three adult psychiatric disorders: schizophrenia, major depression and bipolar disorder. Histone methylation processes showed the strongest association, and we also found statistically significant evidence for associations with multiple immune and neuronal signaling pathways and with the postsynaptic density. Our study indicates that risk variants for psychiatric disorders aggregate in particular biological pathways and that these pathways are frequently shared between disorders. Our results confirm known mechanisms and suggest several novel insights into the etiology of psychiatric disorders.

Figure 1

Overview of statistical approach for integrative pathway analysis of GWAS data. A summary of an analysis of one disorder is shown. Simulated data were generated by drawing from a null pathway P-value distribution for each method and for each disease that accounted for correlations between methods. Pathway results from all disorders were subsequently combined using Fisher’s method.

Figure 2

Quantile-quantile plot showing P-value distribution for a combined analysis combining results from five pathway analysis methods and six pathway databases. (a,b) Data are shown for schizophrenia (SCZ), bipolar disorder (BIP) and major depressive disorder (MDD; a) and SCZ, HIV acquisition and a null simulated data set (b).

Figure 3

Multidimensional scaling plot of top 50 pathways with suggestive (<0.1) q-values ranked across five methods and three disorders (schizophrenia, bipolar disorder and major depressive disorder). The number of genes in each pathway is listed in Table 2. Color reflects rank (red represents top-ranking sets with lowest P values). Sizes reflect the number of genes in the set (maximum of 200, minimum of 11). See Supplementary Data for source data.

Figure 4

Gene coexpression networks across brain development and regions for genes in all pathways with FDR < 0.1. (a) Network plot of ten hubs genes from each module showing clustering across neuroanatomical regions and developmental epochs. The nodes (genes) are annotated by gene-set membership while the edges reflect positive correlations across brain regions and development. (b) Regional and temporal patterns of gene expression as summarized by the average expression level of genes in each module. (c) Enrichment for cell type–specific genes across multiple brain regions and cell types; asterisks highlight enrichments passing FDR-adjusted P < 0.05.