F104. GENE CO-EXPRESSION NETWORKS REVEAL PATHWAYS OF CONVERGENCE OF SCHIZOPHRENIA RISK GENES AND OF RESPONSE TO TREATMENT

Abstract Background Schizophrenia (SCZ) is associated with genetic factors, and specific risk loci have been identified. Still, the biology and clinical translation of genetic risk remain largely unknown. Gene co-expression networks are relevant to functional and clinical translation of SCZ risk. We hypothesized that SCZ risk genes may converge into co-expression pathways which, in turn, may be associated with clinical phenotypes in SCZ patients. Methods We used Weighted Gene Co-expression Network Analysis to identify co-expression modules in two prefrontal cortex post-mortem RNA sequencing datasets, including 379 healthy controls (HC) and 309 SCZ. We used four replication datasets (HC=339). To identify modules enriched for SCZ risk genes, we computed hypergeometric tests and corrected for multiple comparisons. To translate post mortem information into clinical phenotypes, we identified polymorphisms predicting co-expression and combined them to obtain an index approximating module co-expression (Polygenic Co-expression Index: PCI). We used two independent replication datasets (HC=131). Finally, we tested the association between PCI and treatment response in two independent SCZ cohorts (SCZ=167). Results We identified and replicated (all p-values