Analytical Strategies for Multi-Omics Profiling of Exercise-Induced Muscle Damage and Recovery: From Sampling and Separations to Chemometric Biomarker Discovery

Abstract

Exercise-induced muscle damage (EIMD) triggers a coordinated cascade of molecular responses that drive tissue repair and physiological adaptation. Recent advances in analytical chemistry have enabled multi-omics profiling to capture these complex processes across genomic, transcriptomic, proteomic, and metabolomic layers. This review critically examines the analytical strategies underlying EIMD omics research, emphasizing how modern separation and detection technologies have expanded the depth and resolution of biomolecular measurements. We outline the strengths and trade-offs of invasive and non-invasive biospecimens, highlighting how blood, urine, interstitial fluid, and sweat provide complementary insights into systemic and local muscle responses. Central to this workflow are chemometric and bioinformatic tools that enable dimensionality reduction, feature selection, and predictive modeling, transforming high-dimensional molecular data into actionable biomarkers. Case studies illustrate how metabolite panels and protein signatures can discriminate muscle damage states, reveal pathway dynamics, and support early detection of physiological stress. By linking analytical innovation with data integration, multi-omics approaches are reshaping how exercise stress, adaptation, and recovery are understood. This synthesis also acknowledges current controversies positioning multi-omics as both a powerful scientific tool and a frontier for precision exercise medicine.