Integrated bioinformatics analysis identifies a ubiquitination-related gene signature in schizophrenia with peripheral clinical validation

Background Dysregulation of the ubiquitin proteasome pathway is implicated in the pathogenesis of schizophrenia (SCZ). The objective of this study is to identify the dysregulation of the ubiquitin-proteasome pathway and the potential mechanisms associated with SCZ by comprehensive analysis using integrated GEO datasets. Methods We integrated three SCZ related datasets containing 1847 ubiquitination-related genes (URGs) from GeneCards and PubMed, addressing batch effects and normalization with R packages. Subsequent Gene Ontology enrichment analysis was applied to the identified URGs, and an 8-gene molecular signature was constructed to distinguish schizophrenia from control brain tissues, and the discriminatory performance was evaluated by the area under the Receiver Operating Characteristic curve. SCZ samples were categorized into high-risk and low-risk groups based on median Risk Scores, followed by gene set enrichment analysis. Results A total of 13 SCZ-associated ubiquitin-related differentially expressed genes were significantly identified, with eleven being extremely statistically significant and two highly statistically significant. An 8-gene LASSO-derived molecular signature was constructed and validated, effectively discriminating SCZ patients from controls and classifying SCZ patients into high-risk and low-risk subgroups. The study also constructed protein-protein interaction and regulatory networks and conducted immune infiltration analysis, indicating statistically significant differences in six types of immune cells between the SCZ group and the control group, including CD56bright natural killer cells and central memory CD4+ T cells. ELISA validation in an independent clinical cohort confirmed elevated plasma S100A8 in SCZ patients versus controls, with no significant correlation to PANSS five-factor scores, suggesting S100A8 as a candidate peripheral biomarker reflecting disease state rather than current symptom severity. Conclusions Together with the identification of 13 ubiquitination-related DEGs and an eight-gene LASSO signature demonstrating moderate discriminative accuracy for stratifying SCZ patients, this multi-faceted analysis reveals altered ubiquitination patterns in SCZ and provides a hypothesis-generating foundation for future prospective studies incorporating drug-naïve first-episode patients, longitudinal sampling, and appropriate disease controls.