Systems-level analysis of risk genes reveals the modular nature of schizophrenia.

Schizophrenia (SCZ) is a complex mental disorder with high heritability. Genetic studies (especially recent genome-wide association studies) have identified many risk genes for schizophrenia. However, the physical interactions among the proteins encoded by schizophrenia risk genes remain elusive and it is not known whether the identified risk genes converge on common molecular networks or pathways. Here we systematically investigated the network characteristics of schizophrenia risk genes using the high-confidence protein-protein interactions (PPI) from the human interactome. We found that schizophrenia risk genes encode a densely interconnected PPI network (P = 4.15 × 10-31 ). Compared with the background genes, the schizophrenia risk genes in the interactome have significantly higher degree (P = 5.39 × 10-11 ), closeness centrality (P = 7.56 × 10-11 ), betweeness centrality (P = 1.29 × 10-11 ), clustering coefficient (P = 2.22 × 10-2 ), and shorter average shortest path length (P = 7.56 × 10-11 ). Based on the densely interconnected PPI network, we identified 48 hub genes and 4 modules formed by highly interconnected schizophrenia genes. We showed that the proteins encoded by schizophrenia hub genes have significantly more direct physical interactions. Gene ontology (GO) analysis revealed that cell adhesion, cell cycle, immune system response, and GABR-receptor complex categories were enriched in the modules formed by highly interconnected schizophrenia risk genes. Our study reveals that schizophrenia risk genes encode a densely interconnected molecular network and demonstrates the modular nature of schizophrenia.