Comprehensive, integrative and hypothesis-free pathway analysis of genome-wide association data highlights synaptic transmission, dendritic spines and the post-synaptic density in schizophrenia. T. H. Pers1,2, S. Ripke3,4, L. Franke5, J. N. Hirschhorn1,2,6 for the Psychiatric Genetics Consortium 1) Division of Endocrinology, Children's Hospital Boston, Boston, Massachusetts, USA; 2) Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA; 3) Analytical and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, USA; 4) Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA; 5) Department of Genetics, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands; 6) Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA.

   Copy number variation studies and exome sequencing studies have supported hypotheses for the involvement of calcium channels, glutamatergic signaling, synapse plasticity and postsynaptic signaling pathways in schizophrenia. However, analysis of these genetic results with gene set enrichment analysis has been restricted to gene sets corresponding to these a priori hypotheses. Recently the Psychiatric Genomics Consortium identified 108 independent genome-wide significant loci for schizophrenia (based on 34,241 cases and 45,604 controls), but comprehensive, hypothesis-free gene set enrichment approaches failed to identify significantly enriched pathways. Therefore, additional etiologic pathways and the likely causal gene(s) at many associated loci have yet to be discovered. Recently we developed an integrative computational framework - Data-driven Expression-Prioritized Integration for Complex Traits (DEPICT) - which uses gene function predictions derived from 14,461 gene sets and 77,840 microarray samples to systematically identify the most likely causal gene at associated loci, pathways enriched in enriched in genetic associations, and tissues and cell types in which genes from associated loci are highly expressed. DEPICT is already being widely used; here, we applied it to the 108 genome-wide significant schizophrenia loci to prioritize genes and highlight enriched gene sets. We validate our findings with a data set of rare disruptive variants from exome sequencing studies of 5,079 Swedish schizophrenia cases and controls. Based on microarray expression data from 37,427 samples spanning 209 tissue/cell types (a part of the DEPICT framework), we show that genes near associated loci are highly expressed in the brain and mononuclear leukocytes cells at false discovery rates (FDR) below 5%). Next, we show that DEPICT can identify 73 overlapping gene sets (13 after pruning) that are enriched in the associated loci at FDR below 5%). In particular, in this unbiased, hypothesis-free analysis, we highlight pathways related to the function of postsynaptic structures, including the postsynaptic density, and also dendritic spine formation and behavioral mouse phenotypes (all at FDR below 1%). Finally, we report 20 genes that are prioritized across 16 genome-wide significant loci (at FDR below 5%), and show that these genes are more likely to carry rare disruptive mutations in schizophrenia cases compared to controls (P < 0.016).

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