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通过网络分析识别与精神分裂症风险相关的基因集并确定其优先级。

Identification and prioritization of gene sets associated with schizophrenia risk by network analysis.

作者信息

Yu Minglan, Tan Qingyu, Dong Wei, Xiang Bo

机构信息

Institute of Cardiovascular Research, Sleep Medical Center, Department of Psychiatry, Fundamental and Clinical Research on Mental Disorders Key Laboratory of Luzhou, Affiliated Hospital, Southwest Medical University, Luzhou, Sichuan Province, 646000, China.

Department of Psychosomatic Medicine, Deyang People's Hospital, Deyang, Sichuan Province, 646000, China.

出版信息

Psychopharmacology (Berl). 2025 Sep 10. doi: 10.1007/s00213-025-06867-y.

Abstract

RATIONALE

Genome-wide association studies (GWASs) are used to identify genetic variants for association with schizophrenia (SCZ) risk; however, each GWAS can only reveal a small fraction of this association.

OBJECTIVES

This study systematically analyzed multiple GWAS data sets to identify gene subnetwork and pathways associated with SCZ.

METHODS

We identified gene subnetwork using dmGWAS program by combining SCZ GWASs and a human interaction network, performed gene-set analysis to test the association of gene subnetwork with clinical symptom scores and disease state, meanwhile, conducted spatiotemporal and tissue-specific expression patterns and cell-type-specific analysis of genes in the subnetwork.

RESULTS

We identified a gene subnetwork comprising 48 genes was associated with SCZ, and confirmed gene subnetwork's gene-set association with SCZ (Case vs. Control) in two independent cohorts. Gene prioritization identified CALM1 and TCF4 as hub genes in the subnetwork. Meanwhile, using gene-set analysis, it was determined that the gene subnetwork was also linked to generality symptoms and Positive and Negative Syndrome Scale (PANSS) total score in SCZ. 12 out of 48 genes were higher expression in early prenatal brain. In addition, expressions of CALM1, NCAM1, and TCF4 were dysregulated in cerebral organoids of SCZ patients compared with healthy controls. CALM1 and NCAM1 were mainly expressed on the surface of glutamatergic neurons.

CONCLUSIONS

Our findings identified CALM1, NCAM1, and TCF4 as SCZ risk genes and provided important clues to support the neurodevelopmental hypothesis and new therapeutic targets of SCZ.

摘要

原理

全基因组关联研究(GWAS)用于识别与精神分裂症(SCZ)风险相关的基因变异;然而,每个GWAS只能揭示这种关联的一小部分。

目的

本研究系统分析多个GWAS数据集,以识别与SCZ相关的基因子网和通路。

方法

我们通过结合SCZ的GWAS和人类相互作用网络,使用dmGWAS程序识别基因子网,进行基因集分析以测试基因子网与临床症状评分和疾病状态的关联,同时,对子网中的基因进行时空和组织特异性表达模式以及细胞类型特异性分析。

结果

我们确定了一个由48个基因组成的与SCZ相关的基因子网,并在两个独立队列中证实了该基因子网与SCZ(病例组与对照组)的基因集关联。基因优先级分析确定CALM1和TCF4为子网中的核心基因。同时,通过基因集分析确定该基因子网也与SCZ的一般症状和阳性与阴性症状量表(PANSS)总分相关。48个基因中有12个在产前早期大脑中表达较高。此外,与健康对照相比,SCZ患者类脑器官中CALM1、NCAM1和TCF4的表达失调。CALM1和NCAM1主要在谷氨酸能神经元表面表达。

结论

我们的研究结果确定CALM1、NCAM1和TCF4为SCZ风险基因,并为支持神经发育假说和SCZ的新治疗靶点提供了重要线索。

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