Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, 130021, China.
Mol Neurobiol. 2024 Aug;61(8):5992-6012. doi: 10.1007/s12035-024-03942-x. Epub 2024 Jan 24.
Schizophrenia (SCZ) symptoms can be classified as positive and negative ones, each of which has distinct traits and possibly differences in gene expression and regulation. The co-expression networks linked to PANSS (Positive and Negative Syndrome Scale) scores were identified by weighted gene co-expression network analysis (WGCNA) using the expression profiles of miRNA and mRNA in the peripheral blood of first-episode SCZ patients. The heterogeneity between positive and negative symptoms was demonstrated using gene functional enrichment, gene-medication interaction, and immune cell composition analysis. Then, target gene prediction and correlation analysis of miRNA and mRNA constructed a symptom-related miRNA-mRNA regulatory network, screened regulatory pairs, and predicted binding sites. A total of six mRNA co-expression modules, two miRNA co-expression modules, and ten hub genes were screened to be significantly associated with positive symptoms; five mRNA co-expression modules and eight hub genes were correlated with negative symptoms. Positive symptom-related modules were significantly enriched in axon guidance, actin skeleton regulation, and sphingolipid signaling pathway, while negative symptom-related modules were significantly enriched in adaptive immune response, leukocyte migration, dopaminergic synapses, etc. The development of positive symptoms may have been influenced by potential regulatory pairings such as miR-98-5p-EIF3J, miR-98-5p-SOCS4, let-7b-5p-CLUH, miR-454-3p-GTF2H1, and let-7b-5p-SNX17. Additionally, immune cells were substantially connected with several hub genes for symptoms. Positive and negative symptoms in SCZ individuals were heterogeneous to some extent. miRNAs such as let-7b-5p and miR-98-5p might contribute to the incidence of positive symptoms by targeting mRNAs, while the immune system's role in developing negative symptoms may be more nuanced.
精神分裂症 (SCZ) 症状可分为阳性和阴性症状，每种症状都有其独特的特征，并且可能在基因表达和调控方面存在差异。采用加权基因共表达网络分析 (WGCNA) 方法，基于首发精神分裂症患者外周血 miRNA 和 mRNA 的表达谱，识别与 PANSS（阳性和阴性综合征量表）评分相关的共表达网络。通过基因功能富集、基因-药物相互作用和免疫细胞组成分析，展示阳性和阴性症状之间的异质性。然后，通过预测目标基因和 miRNA 与 mRNA 的相关性，构建了一个与症状相关的 miRNA-mRNA 调控网络，筛选调控对，并预测结合位点。总共筛选到六个与阳性症状显著相关的 mRNA 共表达模块、两个 miRNA 共表达模块和十个枢纽基因；五个与阴性症状相关的 mRNA 共表达模块和八个枢纽基因。阳性症状相关模块在轴突导向、肌动蛋白骨架调节和鞘脂信号通路中显著富集，而阴性症状相关模块在适应性免疫反应、白细胞迁移、多巴胺能突触等方面显著富集。阳性症状的发生可能受到 miR-98-5p-EIF3J、miR-98-5p-SOCS4、let-7b-5p-CLUH、miR-454-3p-GTF2H1 和 let-7b-5p-SNX17 等潜在调控对的影响。此外，免疫细胞与几个与症状相关的枢纽基因密切相关。精神分裂症个体的阳性和阴性症状在一定程度上存在异质性。let-7b-5p 和 miR-98-5p 等 miRNA 可能通过靶向 mRNAs 导致阳性症状的发生，而免疫系统在发展阴性症状中的作用可能更为复杂。
