Bayesian Rare Variant Analysis Identifies Novel Schizophrenia Putative Risk Genes

Abstract

The genetics of schizophrenia is so complex that it involves both common variants and rare variants. Rare variant association studies of schizophrenia are challenging because statistical methods for rare variant analysis are under-powered due to the rarity of rare variants. The recent Schizophrenia Exome meta-analysis (SCHEMA) consortium, the largest consortium in this field to date, has successfully identified 10 schizophrenia risk genes from ultra-rare variants by burden test, while more risk genes remain to be discovered by more powerful rare variant association test methods. In this study, we use a recently developed Bayesian rare variant association method that is powerful for detecting sparse rare risk variants that implicates 88 new candidate risk genes associated with schizophrenia from the SCHEMA case–control sample. These newly identified genes are significantly enriched in autism risk genes and GO enrichment analysis indicates that new candidate risk genes are involved in mechanosensory behavior, regulation of cell size, neuron projection morphogenesis, and plasma-membrane-bounded cell projection morphogenesis, that may provide new insights on the etiology of schizophrenia.