Investigating shared diagnostic genes and mechanisms between metabolic syndrome and dry eye disease via integrated bioinformatics analysis and in vivo validation

Abstract

Recent research has established a bidirectional connection between metabolic syndrome (MetS) and dry eye disease (DED); however, the underlying mechanisms driving their co-occurrence remain poorly understood. This study employed bioinformatics and in vivo validation to investigate the shared diagnostic genes and underlying mechanisms linking MetS and DED. Differential expression analysis using Limma and weighted gene co-expression network analysis (WGCNA) identified 247 shared driver genes from MetS and DED cohorts. Functional enrichment analysis indicated that these genes are associated with immune regulation and inflammatory responses. Key diagnostic genes (Ccl5, Cxcr4, Ccl4, Spp1) were identified via PPI network analysis and validated using a receiver operating characteristic (ROC) curve. The MetS-DED mouse model further demonstrated CXCR4 overexpression in corneal epithelium and liver. These findings elucidate overlapping biomarkers and pathogenic pathways between MetS and DED, providing critical insights for advancing their diagnosis and therapeutic strategies.