S100A9 as a shared biomarker and mediator of metabolic dysfunction in peripheral artery disease and sarcopenia.

Backgrounds: Peripheral artery disease (PAD) frequently causes to persistent functional impairment in skeletal muscle even after successful revascularization, implicating non-ischemic pathological mechanisms. Sarcopenia, a myopathy characterized by progressive loss of muscle mass, strength, and function-shares these non-ischemic features and affects approximately one-third of PAD patients, yet the molecular basis of their comorbidity remains poorly defined. Methods: Three transcriptome datasets (GSE120642, GSE181930, and GSE226151) were included in the analysis, covering skeletal muscle samples from peripheral artery disease (PAD) and sarcopenia. Weighted gene co-expression network analysis (WGCNA) was performed independently for each disease cohort, followed by parallel feature selection using three machine learning algorithms (LASSO, Random Forest, and Boruta) to identify shared diagnostic biomarkers. Immune cell infiltration was deconvoluted using CIBERSORT. Drug-gene interaction analysis was conducted via DGIdb. The functional role of the lead candidate S100A9 was validated by untargeted metabolomic profiling of C2C12 myoblasts treated with recombinant S100A9. Results: Seventy-six overlapping disease-associated genes were identified from WGCNA, and five core diagnostic biomarkers-BCKDHB, PIM1, JAML, NFE2, and S100A9 - were selected through three-way machine learning consensus. Enrichment analyses revealed shared involvement of innate immune activation, granulocyte infiltration, and branched-chain amino acid (BCAA) catabolism. CIBERSORT deconvolution confirmed elevated neutrophil abundance as a convergent immune feature of both diseases. Metabolomic profiling demonstrated that recombinant S100A9 disrupted nucleotide and energy homeostasis, induced mitophagy dysregulation, and promoted oxidative stress in C2C12 myoblasts. DGIdb screening identified Paquinimod, a selective S100A9 inhibitor with Phase II clinical safety data, as a candidate for therapeutic repositioning. Conclusion: This study reveals that upregulation of skeletal muscle inflammation and abnormal branched-chain amino acid metabolism may be common features of PAD and sarcopenia. BCKDHB, PIM1, JAML, NFE2, and S100A9 were identified as common diagnostic biomarkers, and metabolomics further confirmed that S100A9 may be a potential intervention target.