精神分裂症(面向对象编程)
神经影像学
候选基因
全基因组关联研究
基因
遗传关联
生物
遗传学
神经科学
心理学
精神科
基因型
单核苷酸多态性
作者
Yuan Ji,Xue Zhang,Zirui Wang,Wen Qin,Huaigui Liu,Kaizhong Xue,Jie Tang,Qiang Xu,Dan Zhu,Feng Liu,Chunshui Yu
出处
期刊:NeuroImage
[Elsevier]
日期:2020-11-02
卷期号:225: 117526-117526
被引量:79
标识
DOI:10.1016/j.neuroimage.2020.117526
摘要
Although both schizophrenia and gray matter volume (GMV) show high heritability, however, genes accounting for GMV alterations in schizophrenia remain largely unknown. Based on risk genes identified in schizophrenia by the genome-wide association study of the Schizophrenia Working Group of the Psychiatric Genomics Consortium, we used transcription-neuroimaging association analysis to test that which of these genes are associated with GMV changes in schizophrenia. For each brain tissue sample, the expression profiles of 196 schizophrenia risk genes were extracted from six donated normal brains of the Allen Human Brain Atlas, and GMV differences between patients with schizophrenia and healthy controls were calculated based on five independent case-control structural MRI datasets (276 patients and 284 controls). Genes associated with GMV changes in schizophrenia were identified by performing cross-sample spatial correlations between expression levels of each gene and case-control GMV difference derived from the five MRI datasets integrated by harmonization and meta-analysis. We found that expression levels of 98 genes consistently showed significant cross-sample spatial correlations with GMV changes in schizophrenia. These genes were functionally enriched for chemical synaptic transmission, central nervous system development, and cell projection. Overall, this study provides a set of genes possibly associated with GMV changes in schizophrenia, which could be used as candidate genes to explore biological mechanisms underlying the structural impairments in schizophrenia.
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