Comprehensive bioinformatics analysis identifies hub genes associated with immune cell infiltration in early-onset schizophrenia.

BACKGROUND

Early-onset schizophrenia (EOS) occurs between the ages of 13 and 17 years, and neurobiological factors leading to cognitive deficits and psychotic symptoms with varying degrees of positive and negative symptoms. Numerous studies have demonstrated a broad link between immune dysregulation and the central nervous system in EOS, and its pathogenesis involves immune dysfunction, but the exact biological mechanisms have not been elucidated. This study employs immune infiltration analysis and bioinformatics to unveil the pathogenic mechanisms of EOS and identify potential diagnostic biomarkers, aiming for more precise clinical interventions.

METHODS

In this study, we recruited 26 EOS patients and 27 healthy controls (HCs), and microarray data were collected. Crossover genes were identified using weighted gene co-expression network analysis (WGCNA) and differential expression genes (DEGs) analysis. These genes were subjected to genome enrichment analysis (GSEA) and gene ontology (GO) analysis. Hub genes were identified through protein-protein interactions (PPIs) and the GeneMANIA database. The diagnostic potential of immune-associated hub genes was evaluated using ROC analysis. Immune infiltration in EOS was analyzed with CIBERSORT. Regulatory miRNAs for the hub genes were predicted using miRNet, and the correlation between mRNAs and miRNAs was analyzed and validated in clinical samples.

RESULTS

By WGCNA and DEGs analysis, 330 relevant genes were screened in EOS patients compared to HCs. Functional enrichment analysis using Metascape showed significant enrichment in immune system pathways. Subsequently, a PPI network was constructed to select the top 10 potential hub genes, and functional analysis was performed by GeneMANIA, resulting in the identification of four immune-related genes. In addition, significant differences were observed among the four immune cell types in the two groups of samples. ROC analysis showed clinical relevance of the immune-related hub genes, and the AUC of all genes was greater than 0.7. A miRNA-mRNA regulatory network was constructed from miRNA data, and three miRNAs were found to be significantly associated with the immune-related hub genes.

CONCLUSION

Our findings demonstrated that CCL3, IL1B, CXCL8, CXCL10 and miR-34a-5p may be biomarkers that play crucial roles in the underlying mechanisms of EOS immune-related pathways. These findings contribute to the understanding of EOS pathophysiology and may help identify new diagnostic and therapeutic targets.