The impact of exercise on the serum proteomes and metabolomes of elite athletes participating in various sports disciplines

Abstract

Regular exercise induces multi-tissue adaptations impacting cardiovascular, muscle, bone, and joint health, influenced by genetic and environmental factors. However, research on the proteomic and metabolomic aspects of elite athletes' long-term exercise remains limited. To address this, we utilized LC-MS-based proteomics and metabolomics to investigate protein and metabolite expression across various sports disciplines and exercise types. For proteomic analysis, we employed the Data-Independent Acquisition (DIA) method, constructing an in-house spectral library from serum samples using Data-Dependent Acquisition (DDA) and Gas-Phase Fractionation (GPF)-DIA. Additionally, we optimized an analysis method for efficiently analyzing large-scale samples of athletes. By utilizing DIA analysis, we quantified approximately 400 proteins on average. Furthermore, we developed an 18-minute method capable of analyzing 80 samples per day, streamlining pre-treatment from 24 hours to 6 hours. For metabolomic analysis, we applied a large-scale targeted approach, screening over 300 substances in a 20-minute analysis, allowing faster processing of large samples compared to conventional methods. Utilizing these techniques, we conducted large-scale proteomic and metabolomic profiling of elite athletes. Our comprehensive analysis provides insights into the molecular mechanisms underlying long-term exercise and underscores the importance of integrated proteomic and metabolomic approaches in sports science.