Revealing the Oxidative Stress-Related Molecular Characteristics and Potential Therapeutic Targets of Schizophrenia through Integrated Gene Expression Data Analysis

Abstract

Schizophrenia is a severe mental disorder characterized by oxidative stress imbalances. The underlying mechanisms of oxidative stress-related gene expression in schizophrenia require further investigation. Additionally, the diagnosis of schizophrenia lacks sensitive and specific biomarkers as well as predictive models for assessing susceptibility. We analyzed genome-wide mRNA expression profiles from GSE38484 (schizophrenia = 106, control = 96) and GSE54913 (schizophrenia = 18, control = 12) using Weighted Gene Co-expression Network Analysis and machine learning to identify oxidative stress-related hub genes in schizophrenia. Subsequent analyses included Gene Set Enrichment Analysis, protein-protein interaction networks, immune cell infiltration, and molecular docking. A diagnostic model was also constructed. We identified five hub genes associated with oxidative stress in schizophrenia: CTSB, RNH1, REC8, ITIH4, and TNFAIP8L1, and constructed a diagnostic model (AUC = 0.954). Five hub genes and twenty co-expressed genes were enriched in pathways related to endopeptidase and endoribonuclease activities. Significant differences in the abundance of seven immune cell types were noted in schizophrenia samples. Drug prediction and molecular docking suggested UREA and COUMARIN as potential therapeutic agents targeting CTSB. We identified five hub genes associated with oxidative stress in schizophrenia: CTSB, RNH1, REC8, ITIH4, and TNFAIP8L1. We carried out downstream analyses and constructed a diagnostic model for schizophrenia.

Keywords: Biomarkers; Diagnosis; Drug prediction; Hub gene; Oxidative stress; Schizophrenia.