We employed an integrated bioinformatics screening approach along with Mendelian randomization (MR) analysis to explore potential genetic targets for varicose veins of lower extremities (VVs) and identify potential treatment options for VVs. Differential expression analysis was conducted using R software to identify differentially expressed genes (DEGs) of VVs from the Gene Expression Omnibus database. Weighted gene co-expression network analysis (WGCNA) was performed to identify co-expression networks. Functional enrichment analyses were conducted for the identified genes. A protein-protein interaction network was constructed to analyze the interactions among the identified genes. Additionally, genome-wide association studies data for VVs were downloaded for MR analysis. Various methods, including inverse-variance weighted, were employed to assess potential causal associations with VVs risk, followed by sensitivity analysis. The DEGs identified from the VVs Gene Expression Omnibus dataset included 180 upregulated genes and 335 downregulated genes. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analysis revealed that the downregulated DEGs were significantly associated with nuclear protein-containing complexes and nucleic acid binding (P < .05). WGCNA highlighted a highly significant "turquoise" module comprising 78 downregulated genes (P = 2e - 04). The protein-protein interaction network analysis of the significant DEGs and the WGCNA "turquoise" module identified 224 nodes and 491 edges, uncovering several hub genes such as BRCA1, NCBP2, GTPBP4, HDAC2, KHDRBS1, and HNRNPR. Detailed functional enrichment analysis indicated involvement in tumor-like cellular proliferation and differentiation processes, including protein acetylation, RNA splicing, and metabolic processes. MR analysis revealed a causal association between the tumor-related gene Ecto-NOX disulfide-thiol exchanger 2 (ENOX2) and the risk of VVs, with a statistical significance (odds ratio: 1.0016; 95% confidence interval: 1.0003-1.0029; P = .015) according to inverse-variance weighted analysis. Sensitivity analysis confirmed the absence of heterogeneity and horizontal pleiotropy in the observed associations (P > .05). "Leave-one-out" validation analysis did not indicate any changes. Our study unveils the involvement of ENOX2 and the related mechanisms in the pathogenesis of VVs, suggesting their potential as genetic targets for treatment.
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