Samuel Bennett

The field of exercise physiology has undergone significant technological advancements since the pioneering works of exercise physiologists in the early to mid‐20th century. Historically, the ability to detect metabolites in biofluids from exercising participants was limited to single‐metabolite analyses. However, the rise of metabolomics, a discipline focused on the comprehensive analysis of metabolites within a biological system, has facilitated a more intricate understanding of metabolic pathways and networks in exercise. This review explores some of the pivotal technological and bioinformatic advancements that have propelled metabolomics to the forefront of exercise physiology research. Metabolomics offers a unique ‘fingerprint’ of cellular activity, offering a broader spectrum than traditional single‐metabolite assays. Techniques, including mass spectrometry and nuclear magnetic resonance spectroscopy, have significantly improved the speed and sensitivity of metabolite analysis. Nonetheless, challenges persist, including study design and data interpretation issues. This review aims to serve as a guide for exercise physiologists to facilitate better research design, data analysis and interpretation within metabolomics. The potential of metabolomics in bridging the gap between genotype and phenotype is emphasised, underscoring the critical importance of careful study design and the selection of appropriate metabolomics techniques. Furthermore, the paper highlights the need to deeply understand the broader scientific context to discern meaningful metabolic changes. The emerging field of fluxomics, which seeks to quantify metabolic reaction rates, is also introduced as a promising avenue for future research.

Purpose Carbohydrate (CHO) intake periodization via the sleep low train low (SL‐TL) diet–exercise model increases fat oxidation during exercise and may enhance endurance‐training adaptation and performance. Conversely, training under environmental heat stress increases CHO oxidation, but the potential of combined SL‐TL and heat stress to enhance metabolic and performance outcomes is unknown. Methods Twenty‐three endurance‐trained males were randomly assigned to either control ( n = 7, CON), SL‐TL ( n = 8, SL Temp ) or SL‐TL + heat stress ( n = 8, SL Heat ) groups and prescribed identical 2‐week cycling training interventions. CON and SL Temp completed all sessions at 20°C, but SL Heat at 35°C. All groups consumed matched CHO intake (6 g·kg −1 ·day −1 ) but timed differently to promote low CHO availability overnight and during morning exercise in both SL groups. Submaximal substrate utilization was assessed (at 20°C), and 30‐min performance tests (at 20 and 35°C) were performed Pre‐, Post‐, and 1‐week post‐intervention (Post+1). Results SL Temp improved fat oxidation rates at 60% MAP (~66% VO 2peak ) at Post+1 compared with CON ( p < 0.01). Compared with SL Temp , fat oxidation rates were significantly lower in SL Heat at Post ( p = 0.02) and Post+1 ( p < 0.05). Compared with CON, performance was improved at Post in SL Temp in temperate conditions. Performance was not different between any groups or time points in hot conditions. Conclusion SL‐TL enhanced metabolic adaptation and performance compared with CON and combined SL‐TL and heat stress. Additional environmental heat stress may impair positive adaptations associated with SL‐TL.