Department of Radiology, Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China.
Department of Radiology, Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China.
Neuroimage. 2021 Jan 15;225:117526. doi: 10.1016/j.neuroimage.2020.117526. Epub 2020 Nov 2.
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.
虽然精神分裂症和灰质体积(GMV)都表现出较高的遗传性,但是导致精神分裂症 GMV 改变的基因仍然知之甚少。基于精神分裂症基因组关联研究的精神分裂症工作组确定的风险基因,我们使用转录-神经影像学关联分析来测试这些基因中哪些与精神分裂症患者的 GMV 变化有关。对于每个脑组织样本,从 Allen 人类大脑图谱的六个捐赠的正常大脑中提取了 196 个精神分裂症风险基因的表达谱,并基于五个独立的病例对照结构 MRI 数据集(276 名患者和 284 名对照)计算了精神分裂症患者和健康对照之间的 GMV 差异。通过在通过协调和荟萃分析集成的五个 MRI 数据集的每个基因的表达水平与病例对照 GMV 差异之间执行跨样本空间相关性,鉴定出与精神分裂症 GMV 变化相关的基因。我们发现,98 个基因的表达水平与精神分裂症的 GMV 变化一致表现出显著的跨样本空间相关性。这些基因在化学突触传递、中枢神经系统发育和细胞投射方面具有功能富集。总体而言,这项研究提供了一组可能与精神分裂症 GMV 变化相关的基因,这些基因可作为候选基因来探索精神分裂症结构损伤的生物学机制。