Evaluating untargeted metabolomics pipelines for sports nutrition research: a review

Untargeted metabolomics has emerged as a transformative approach in sports nutrition research, offering an unbiased means to characterize the complex biochemical responses to exercise, training, and dietary interventions. Unlike targeted assays restricted to predefined metabolites, untargeted strategies capture broad metabolic perturbations across lipid, carbohydrate, amino acid, and nucleotide pathways, enabling the discovery of novel biomarkers and unanticipated physiological mechanisms. This review critically evaluates the design and application of untargeted metabolomic pipelines in the context of exercise and nutrition science, from pre-analytical sample handling and analytical platforms such as NMR, LC-MS, and GC-MS, to data processing using tools like XCMS, MZmine, and MS-DIAL, and subsequent statistical and bioinformatic interpretation. Key applications include delineating acute metabolic shocks induced by endurance exercise, identifying athlete-specific metabolic phenotypes shaped by chronic training, and assessing the impact of nutritional interventions such as fruit intake, amino acid supplementation, or polyphenol-rich foods on exercise recovery and oxidative stress. The integration of metabolomics with other omics, particularly microbiome metagenomics and lipidomics, highlights the potential for systems-level insights into host-microbe-diet interactions. Nonetheless, significant challenges remain, including the reproducibility of findings, difficulties in metabolite identification, and the translational gap between large datasets and actionable nutritional strategies. By synthesizing current strengths, limitations, and controversies, this review emphasizes that the future of sports metabolomics lies in methodological standardization, multi-omics integration, and validation of candidate biomarkers in independent cohorts. Collectively, these efforts position untargeted metabolomics as a cornerstone for advancing precision nutrition and personalized performance monitoring in athletes.