Variant-to-Biomarker Pathways in Peripheral Artery Disease: Multiomics Integration and Clinical Translation

Peripheral artery disease (PAD) is a prevalent, disabling manifestation of systemic atherosclerosis that carries high risks of major adverse cardiovascular and limb events, yet remains incompletely explained by conventional risk factors and haemodynamic indices. Although genome-wide association studies have nominated reproducible susceptibility loci and high-throughput profiling has expanded the landscape of circulating, imaging, vascular and skeletal muscle biomarkers, most signals are noncoding, mechanistic attribution is often uncertain and few biomarkers have demonstrated durable incremental utility for risk stratification or therapeutic guidance in routine care. In this review, we summarise PAD-relevant genetic architectures and multiomics modalities-fine-mapped GWAS with tissue- and cell-resolved functional genomics, proteogenomic and metabolomic profiling and network-based integration across vascular, muscle and circulating compartments-and we appraise translational opportunities that span variant-anchored protein and metabolite prioritisation, composite biomarker panels for limb-specific ischaemic burden and residual atherothrombotic risk and biomarker-informed selection of antithrombotic, lipid-lowering, anti-inflammatory and revascularisation strategies. We also discuss enduring challenges-including ancestry-sensitive transferability of genetic instruments, limited access to disease-relevant tissues, cross-platform standardisation, confounding by disease stage and therapy and the need for prospective validation and trial-ready pharmacodynamic endpoints-that temper implementation. The purpose of this review is to delineate variant-to-biomarker pathways in PAD and specify integrative, clinically actionable solutions for discovery, validation and translation. We further distinguish diagnostic, prognostic, predictive/theragnostic and pharmacodynamic biomarker contexts of use, and emphasise that phenotype definition, sex, diabetes, exposure measurement and treatment effects all condition the interpretation and transferability of PAD multiomic signals.