Lee, EC, Fragala, MS, Kavouras, SA, Queen, RM, Pryor, JL, and Casa, DJ. Biomarkers in sports and exercise: tracking health, performance, and recovery in athletes.J Strength Cond Res31(10): 2920–2937, 2017—Biomarker discovery and validation is a critical aim of the medical and scientific community. Research into exercise and diet-related biomarkers aims to improve health, performance, and recovery in military personnel, athletes, and lay persons. Exercise physiology research has identified individual biomarkers for assessing health, performance, and recovery during exercise training. However, there are few recommendations for biomarker panels for tracking changes in individuals participating in physical activity and exercise training programs. Our approach was to review the current literature and recommend a collection of validated biomarkers in key categories of health, performance, and recovery that could be used for this purpose. We determined that a comprehensive performance set of biomarkers should include key markers of (a) nutrition and metabolic health, (b) hydration status, (c) muscle status, (d) endurance performance, (e) injury status and risk, and (f) inflammation. Our review will help coaches, clinical sport professionals, researchers, and athletes better understand how to comprehensively monitor physiologic changes, as they design training cycles that elicit maximal improvements in performance while minimizing overtraining and injury risk.

Personalized hydration strategies play a key role in optimizing the performance and safety of athletes during sporting activities. Clinicians should be aware of the many physiological, behavioral, logistical and psychological issues that determine both the athlete’s fluid needs during sport and his/her opportunity to address them; these are often specific to the environment, the event and the individual athlete. In this paper we address the major considerations for assessing hydration status in athletes and practical solutions to overcome obstacles of a given sport. Based on these solutions, practitioners can better advise athletes to develop practices that optimize hydration for their sports.

The feasibility of detecting mild dehydration by using autonomic responses to cognitive stress was studied. To induce cognitive stress, subjects (n = 17) performed the Stroop task, which comprised four minutes of rest and four minutes of test. Nine indices of autonomic control based on electrodermal activity (EDA) and pulse rate variability (PRV) were obtained during both the rest and test stages of the Stroop task. Measurements were taken on three consecutive days in which subjects were “wet” (not dehydrated) and “dry” (experiencing mild dehydration caused by fluid restriction). Nine approaches were tested for classification of “wet” and “dry” conditions: (1) linear (LDA) and (2) quadratic discriminant analysis (QDA), (3) logistic regression, (4) support vector machines (SVM) with cubic, (5) fine Gaussian kernel, (6) medium Gaussian kernel, (7) a k-nearest neighbor (KNN) classifier, (8) decision trees, and (9) subspace ensemble of KNN classifiers (SE-KNN). The classification models were tested for all possible combinations of the nine indices of autonomic nervous system control, and their performance was assessed by using leave-one-subject-out cross-validation. An overall accuracy of mild dehydration detection was 91.2% when using the cubic SE-KNN and indices obtained only at rest, and the accuracy was 91.2% when using the cubic SVM classifiers and indices obtained only at test. Accuracy was 86.8% when rest-to-test increments in the autonomic indices were used along with the KNN and QDA classifiers. In summary, measures of autonomic function based on EDA and PRV are suitable for detecting mild dehydration and could potentially be used for the noninvasive testing of dehydration.

The combination of hyperthermia, dehydration, and strenuous exercise can result in severe reductions in kidney function, potentially leading to acute kidney injury (AKI). We sought to determine whether six days of heat acclimation (HA) mitigates the rise in clinical biomarkers of AKI during strenuous exercise in the heat. Twenty men completed two consecutive 2 h bouts of high-intensity exercise in either hot (n = 12, 40 °C, 40% relative humidity) or mild (n = 8, 24 °C, 21% relative humidity) environments before (PreHA) and after (PostHA) 4 days of 90–120 min of exercise per day in a hot or mild environment. Increased clinical biomarkers of AKI (CLINICAL) was defined as a serum creatinine increase ≥0.3 mg·dL⁻¹ or estimated glomerular filtration rate (eGFR) reduction >25%. Creatinine similarly increased in the hot environment PreHA (0.35 ± 0.23 mg·dL⁻¹) and PostHA (0.39 ± 0.20 mg·dL⁻¹), with greater increases than the mild environment at both time points (0.11 ± 0.07 mg·dL⁻¹, 0.08 ± 0.06 mg·dL⁻¹, p ≤ 0.001), respectively. CLINICAL occurred in the hot environment PreHA (n = 9, 75%), with fewer participants with CLINICAL PostHA (n = 7, 58%, p = 0.007), and no participants in the mild environment with CLINICAL at either time point. Percent change in plasma volume was predictive of changes in serum creatinine PostHA and percent changes in eGFR both PreHA and PostHA. HA did not mitigate reductions in eGFR nor increases in serum creatinine during high-intensity exercise in the heat, although the number of participants with CLINICAL was reduced PostHA.

Current models of afferent inputs to the brain, which influence body water volume and concentration via thirst and drinking behavior, have not adequately described the interactions of subconscious homeostatic regulatory responses with conscious perceptions. The purpose of this investigation was to observe the interactions of hydration change indices (i.e., plasma osmolality, body mass loss) with perceptual ratings (i.e., thirst, mouth dryness, stomach emptiness) in 18 free-living, healthy adult men (age, 23 ± 3 y; body mass, 80.09 ± 9.69 kg) who participated in a 24-h water restriction period (Days 1–2), a monitored 30-min oral rehydration session (REHY, Day 2), and a 24-h ad libitum rehydration period (Days 2–3) while conducting usual daily activities. Laboratory and field measurements spanned three mornings and included subjective perceptions (visual analog scale ratings, VAS), water intake, dietary intake, and hydration biomarkers associated with dehydration and rehydration. Results indicated that total water intake was 0.31 L/24 h on Day 1 versus 2.60 L/24 h on Day 2 (of which 1.46 L/30 min was consumed during REHY). The increase of plasma osmolality on Day 1 (297 ± 4 to 299 ± 5 mOsm/kg) concurrent with a body mass loss of 1.67 kg (2.12%) paralleled increasing VAS ratings of thirst, desire for water, and mouth dryness but not stomach emptiness. Interestingly, plasma osmolality dissociated from all perceptual ratings on Day 3, suggesting that morning thirst was predominantly non-osmotic (i.e., perceptual). These findings clarified the complex, dynamic interactions of subconscious regulatory responses with conscious perceptions during dehydration, rehydration, and reestablished euhydration.

The purpose of this study was to assess the effectiveness of heat acclimatization (HAz) followed by heat acclimation (HA) on physiological adaptations. 25 male endurance athletes (age 36 ± 12 y, height 178.8 ± 6.39 cm, body mass 73.03 ± 8.97 kg, and VO_2peak 57.5 ± 7.0 mL·kg⁻¹·min⁻¹) completed HAz and HA. HAz was 3 months of self-directed summer training. In the laboratory, a 5-day HA prescribed exercise to target a hyperthermic zone (HZHA) of T_rec between 38.50 and 39.75 °C for 60 min. Exercise trials were 60 min of running (59% ± 2% VO_2peak) in an environmental chamber (wet bulb globe temperature 29.53 ± 0.63 °C) and administered at: baseline, post-HAz, and post-HAz+HA. Measured variables included internal body temperature (T_rec), heart rate (HR), and sweat rate (SR). Repeated measure ANOVAs and post hoc comparisons were used to assess statistically significant (p < 0.05) differences. T_rec was lower post-HAz+HA (38.03 ± 0.39 °C) than post-HAz (38.25 ± 0.42 °C, p = 0.009) and baseline (38.29 ± 0.37 °C, p = 0.005). There were no differences between baseline and post-HAz (p = 0.479) in T_rec. HR was lower post-HAz (143 ± 12 bpm, p = 0.002) and post-HAz+HA (134 ± 11 bpm, p < 0.001) than baseline (138 ± 14 bpm). HR was lower post-HAz+HA than post-HAz (p = 0.013). SR was higher post-HAz+HA (1.93 ± 0.47 L·h⁻¹) than post-HAz (1.76 ± 0.43 L·h⁻¹, p = 0.027). Combination HAz and HA increased physiological outcomes above HAz. This method can be used to improve performance and safety in addition to HAz alone.