Protein-interaction-network-based analysis for genome-wide association analysis of schizophrenia in Han Chinese population

Abstract

Schizophrenia is a severe neuropsychiatric disorder with a strong and complex genetic background. Recent genome-wide association studies (GWAS) have successfully identified several susceptibility loci of schizophrenia. In order to interpret the functional role of the genetic variants and detect the combined effects of some of these genes on schizophrenia, protein-interaction-network-based analysis (PINBA) has emerged as an effective approach. In the current study, we conducted a PINBA of our previous GWAS data taken from the Han Chinese population. In order to do so, we used dense module search (DMS), a method that locates densely connected modules for complex diseases by integrating the association signal from GWAS datasets into the human protein–protein interaction (PPI) network. As a result, we identified one gene set with a joint effect significantly associated with schizophrenia and gene expression profiling analysis suggested that they were mainly neuro- and immune-related genes, such as glutamatergic gene (GRM5), GABAergic genes (GABRB1, GABARAP) and genes located in the MHC region (HLA-C, TAP2, HIST1H1B). Further pathway enrichment analysis suggested that these genes are involved in processes related to neuronal and immune systems, such as the Adherens junction pathway, the Neurotrophin signaling pathway and the Toll-like receptor signaling pathway. In our study, we identified a set of susceptibility genes that had been missed in single-marker GWAS, and our findings could promote the study of the genetic mechanisms in schizophrenia.