LncRNA-miRNA‒mRNA Network in Schizophrenia

Schizophrenia (SCZ) is a severe mental disorder that significantly impacts the social functioning of patients and can reduce their life expectancy and quality of life. However, the specific causes of SCZ remain unknown, and the evidence indicates that long noncoding RNAs (lncRNAs) play critical roles in its pathogenesis. Analyzing lncRNA expression in peripheral blood samples from patients could reveal the biological mechanisms underlying the disease and help in the identification of biomarkers for early diagnosis and treatment. This study utilized whole-transcriptome sequencing to analyze lncRNA expression in 5 SCZ patients and 5 healthy controls. We constructed lncRNA‒microRNA (miRNA) and miRNA‒messenger RNA (mRNA) interaction pairs and established a competing endogenous RNA (ceRNA) network. Additionally, a weighted gene coexpression network analysis (WGCNA) and lncRNA‒RNA binding protein (RBP) network construction were performed. The potential functions of the mRNAs were predicted using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. A total of 438 differentially expressed lncRNAs (DElncRNAs) were identified in patients with SCZ compared with controls, with 260 upregulated and 178 downregulated. The ceRNA network comprised 383 DElncRNAs, 304 miRNAs, and 1849 mRNAs. GO and KEGG analyses indicated that these genes are involved in pathways such as the HIF-1 signaling pathway and oxidative phosphorylation, both of which are relevant to SCZ. Based on the ceRNA network-derived mRNAs, WGCNA identified three disease-associated modules. Furthermore, interactions between RBPs and DElncRNAs may play a significant role in the pathophysiology of SCZ. This study identifies 438 dysregulated lncRNAs in SCZ, constructs a ceRNA network implicating HIF-1 signaling and oxidative phosphorylation pathways, and reveals disease-associated coexpression modules and RBP-lncRNA interactions, providing novel insights into SCZ pathogenesis and potential diagnostic biomarkers.