This study explored the relationship between serum ferritin and hepcidin in athletes. Baseline serum ferritin levels of 54 athletes from the control trial of five investigations conducted in our laboratory were considered; athletes were grouped according to values <30 μg/L (SF100 μg/L (SF>100). Data pooling resulted in each athlete completing one of five running sessions: (1) 8×3 min at 85% vVO_2peak; (2) 5×4 min at 90% vVO_2peak; (3) 90 min continuous at 75% vVO_2peak; (4) 40 min continuous at 75% vVO_2peak; (5) 40 min continuous at 65% vVO_2peak. Athletes from each running session were represented amongst all four groups; hence, the mean exercise duration and intensity were not different (p>0.05). Venous blood samples were collected pre-, post- and 3 h post-exercise, and were analysed for serum ferritin, iron, interleukin-6 (IL-6) and hepcidin-25. Baseline and post-exercise serum ferritin levels were different between groups (p0.05). Post-exercise IL-6 was significantly elevated compared to baseline within each group (p<0.05). Pre- and 3 h post-exercise hepcidin-25 was sequentially greater as the groups baseline serum ferritin levels increased (p100; p<0.05). An athlete's iron stores may dictate the baseline hepcidin levels and the magnitude of post-exercise hepcidin response. Low iron stores suppressed post-exercise hepcidin, seemingly overriding any inflammatory-driven increases.

Caffeine use is widespread among athletes following its removal from the World Anti-Doping Agency banned list, with approximately 75% of competitive athletes using caffeine. While literature supports that caffeine has a small positive ergogenic effect for most forms of sports and exercise, there exists a significant amount of inter-individual difference in the response to caffeine ingestion and the subsequent effect on exercise performance. In this narrative review, we discuss some of the potential mechanisms and focus on the role that genetics has in these differences. CYP1A2 and ADORA2A are two of the genes which are thought to have the largest impact on the ergogenicity of caffeine. CYP1A2 is responsible for the majority of the metabolism of caffeine, and ADORA2A has been linked to caffeine-induced anxiety. The effects of CYP1A2 and ADORA2A genes on responses to caffeine will be discussed in detail and an overview of the current literature will be presented. The role of these two genes may explain a large portion of the inter-individual variance reported by studies following caffeine ingestion. Elucidating the extent to which these genes moderate responses to caffeine during exercise will ensure caffeine supplementation programs can be tailored to individual athletes in order to maximize the potential ergogenic effect.

Background: Body-fluid loss during prolonged continuous exercise can impair cardiovascular function, harming performance. Delta percent plasma volume (dPV) represents the change in central and circulatory body-water volume and therefore hydration during exercise; however, the effect of carbohydrate–electrolyte drinks and water on the dPV response is unclear. Objective: To determine by meta-analysis the effects of ingested hypertonic (> 300 mOsmol kg⁻¹), isotonic (275–300 mOsmol kg⁻¹) and hypotonic (< 275 mOsmol kg⁻¹) drinks containing carbohydrate and electrolyte ([Na⁺] < 50 mmol L⁻¹), and non-carbohydrate drinks/water (< 40 mOsmol kg⁻¹) on dPV during continuous exercise. Methods: A systematic review produced 28 qualifying studies and 68 drink treatment effects. Random-effects meta-analyses with repeated measures provided estimates of effects and probability of superiority (p₊) during 0–180 min of exercise, adjusted for drink osmolality, ingestion rate, metabolic rate and a weakly informative Bayesian prior. Results: Mean drink effects on dPV were: hypertonic − 7.4% [90% compatibility limits (CL) − 8.5, − 6.3], isotonic − 8.7% (90% CL − 10.1, − 7.4), hypotonic − 6.3% (90% CL − 7.4, − 5.3) and water − 7.5% (90% CL − 8.5, − 6.4). Posterior contrast estimates relative to the smallest important effect (dPV = 0.75%) were: hypertonic-isotonic 1.2% (90% CL − 0.1, 2.6; p₊ = 0.74), hypotonic-isotonic 2.3% (90% CL 1.1, 3.5; p₊ = 0.984), water-isotonic 1.3% (90% CL 0.0, 2.5; p₊ = 0.76), hypotonic-hypertonic 1.1% (90% CL 0.1, 2.1; p₊ = 0.71), hypertonic-water 0.1% (90% CL − 0.8, 1.0; p₊ = 0.12) and hypotonic-water 1.1% (90% CL 0.1, 2.0; p₊ = 0.72). Thus, hypotonic drinks were very likely superior to isotonic and likely superior to hypertonic and water. Metabolic rate, ingestion rate, carbohydrate characteristics and electrolyte concentration were generally substantial modifiers of dPV. Conclusion: Hypotonic carbohydrate–electrolyte drinks ingested continuously during exercise provide the greatest benefit to hydration. Graphical