Schizophrenia is a severe and chronic mental disorder with high heritability and polygenic inheritance. Investigating the neural mechanism underlying the polygenic risk of schizophrenia can provide important clues for the prevention and treatment of the disorder. Therefore, the study combined the genomic and multimodal neuroimaging data from Han Chinese population to investigate the neural mechanism underlying the polygenic risk of schizophrenia.
From the whole situation, this stduy investigated the overall impacts of genomewide variants related to schizophrenia on brain structure and function, which can reflect the neurobiological characterization of schizophrenia. Specifically, to assess the overall genetic influences of schizophrenia, we calculated a polygenic risk score (PGRS) for each participant based on the data from a recent meta-analysis of genome-wide association study (GWAS) that comprised a large number of Chinese samples. Next, neuroimaging data from a large sample of Han Chinese were included in this study. Comparing schizophrenia patients with healthy controls, we examined abnormal gray matter volume and functional connectivity via structural and functional magnetic resonance imaging respectively, and further investigated the association between PGRS and these abnormal neuroimaging measures. The imaging genetic analysis revealed that the individual PGRS showed a significantly negative correlation with the hippocampal gray matter volume and hippocampus-medial prefrontal cortex functional connectivity, both of which were lower in the schizophrenia patients than in the controls. We further found that the observed neuroimaging measures showed weak, but similar changes in unaffected first-degree relatives to those in the patients. These findings suggested that genetically influenced brain gray matter volume and functional connectivity may provide important clues for understanding the pathological mechanisms of schizophrenia and for the early diagnosis of schizophrenia.
In addition, investiageting the neural mechanisms of a specifc gene set is also important for the understanding of schizophrenia. GWAS have consistently revealed that a variant of microRNA 137 (MIR137) shows a quite significant association with schizophrenia, and MIR137 regulated the expression of many genes. Therefore, this study examined the neural mechanisms of MIR137-regulated genes. Specifcally, To evaluate the additive effects of the MIR137 regulated genes (N = 1274), we calculated a MIR137 PGRS for schizophrenia and tested its association with the risk for schizophrenia in the genomic data of a Han Chinese population that included schizophrenia patients and healthy controls. Meanwhile, dorsolateral prefrontal cortex (DLPFC) functional connectivity, a robust correlate of MIR137, may provide plausible endophenotypes.
We then investigated the association between MIR137 PGRS and DLPFC functional connectivity in two independent young healthy cohorts. We found that the MIR137 PGRS successfully captured the differences in genetic structure between the patients and controls, but the single gene MIR137 did not. We then consistently found that a higher MIR137 PRS was correlated with lower functional connectivities between the DLPFC and both the superior parietal cortex and the inferior temporal cortex in two independent cohorts. The findings suggested that these two functional connectivities of the DLPFC could be important endophenotypes linking the MIR137-regulated genetic structure to schizophrenia.
In summary, from whole-genome data to a single gene set, this study investigated the neural mechanisms underlying the polygenic risk of schizophrenia. Our findings may provide important clues for the understanding of complex pathological mechanisms.