Context: Overtraining syndrome (OTS) is a condition characterized by a long-term performance decrement, which occurs after a persisting imbalance between training-related and nontraining-related load and recovery. Because of the lack of a gold standard diagnostic test, OTS remains a diagnosis of exclusion. Objective: To systematically review and map biomarkers and tools reported in the literature as potentially diagnostic for OTS. Data Sources: PubMed, Web of Science, and SPORTDiscus were searched from database inception to February 4, 2021, and results screened for eligibility. Backward and forward citation tracking on eligible records were used to complement results of database searching. Study Selection: Studies including athletes with a likely OTS diagnosis, as defined by the European College of Sport Science and the American College of Sports Medicine, and reporting at least 1 biomarker or tool potentially diagnostic for OTS were deemed eligible. Study Design: Scoping review following the guidelines of the Joanna Briggs Institute and PRISMA Extension for Scoping Reviews (PRISMA-ScR). Level of Evidence: Level 4. Data Extraction: Athletes’ population, criteria used to diagnose OTS, potentially diagnostic biomarkers and tools, as well as miscellaneous study characteristics were extracted. Results: The search yielded 5561 results, of which 39 met the eligibility criteria. Three diagnostic scores, namely the EROS-CLINICAL, EROS-SIMPLIFIED, and EROS-COMPLETE scores (EROS = Endocrine and Metabolic Responses on Overtraining Syndrome study), were identified. Additionally, basal hormone, neurotransmitter and other metabolite levels, hormonal responses to stimuli, psychological questionnaires, exercise tests, heart rate variability, electroencephalography, immunological and redox parameters, muscle structure, and body composition were reported as potentially diagnostic for OTS. Conclusion: Specific hormones, neurotransmitters, and metabolites, as well as psychological, electrocardiographic, electroencephalographic, and immunological patterns were identified as potentially diagnostic for OTS, reflecting its multisystemic nature. As exemplified by the EROS scores, combinations of these variables may be required to diagnose OTS. These scores must now be validated in larger samples and within female athletes.

Purpose: Cardiopulmonary exercise testing (CPET) is an important measurement in clinical practice, and its primary outcome, maximal oxygen uptake (V˙O_2peak), is inversely associated with morbidity and mortality. The purposes of this study are to provide CPET reference values for maximal and submaximal parameters across the adult age spectrum of a healthy European cohort, to compare V˙O_2peak values with other reference data sets, and to analyze the associations between physical activity (PA) levels and CPET parameters. Methods: In this cross-sectional study, we prospectively recruited 502 participants (47% female) from 20 to 90 yr old. The subjects performed a CPET on a cycle ergometer using a ramp protocol. PA was objectively and continuously measured over 14 d using a triaxial accelerometer. Quantile curves were calculated for CPET parameters. To investigate the associations between CPET parameters and PA levels, linear regression analysis was performed. Results: V˙O_2peak values observed in the group of 20–29 yr were 46.6 ± 7.9 and 39.3 ± 6.5 mL·kg⁻¹⋅min⁻¹ for males and females, respectively. On average, each age category (10-yr increments) showed a 10% lower V˙O_2peak relative to the next younger age category. V˙O_2peak values of previous studies were on average 7.5 mL·kg⁻¹⋅min⁻¹ (20%) lower for males and 6.5 mL·kg⁻¹⋅min⁻¹ (21%) lower for females. There was strong evidence supporting a positive association between the V˙O_2peak (mL·kg⁻¹⋅min⁻¹) and the level of habitual PA performed at vigorous PA (estimate, 0.26; P < 0.001]. Conclusion: Maximal and submaximal CPET reference values over a large age range are novel, and differences to other studies are clinically highly relevant. Objectively measured vigorous-intensity PA showed a strong positive association with higher V˙O_2peak and other performance-related CPET parameters, supporting the implementation of higher-intensity aerobic exercise in health promotion.

Objective To describe the injury and illness characteristics among participating athletes during the Lausanne 2020 Youth Olympic Winter Games (YOG 2020), 9–22 January 2020. Methods The daily number of athlete injuries and illnesses were recorded (1) through the reporting of all National Olympic Committee (NOC) medical teams and (2) in the polyclinic and medical venues by the Lausanne 2020 medical staff. Results In total, 1783 athletes from 79 NOCs were observed. NOC and Lausanne 2020 medical staff reported 228 injuries and 167 illnesses, equating 11.7 injuries and 8.6 illnesses per 100 athletes over the 14-day period. Injury incidence was highest for snowboard slopestyle (39%), bobsleigh (36%), snowboard big air (29%), ski slopestyle (29%), snowboard cross (24%) and ski cross (21%), and lowest for speed skating, snowboard halfpipe and curling (2%–4%). The highest incidence of illness was recorded for curling (21%), ski mountaineering (15%), snowboard halfpipe (13%), bobsleigh (11%), cross-country skiing (10%) and figure skating (10%). Almost one-third of injuries were expected to result in time loss and 17% of illnesses. Most injuries occurred to the knee (12%) and head (11%), and 64% of illnesses affected the respiratory system. Overall, women suffered more injuries and illness than males. Conclusion Overall, injury and illness rates were similar compared with recent YOG. While the rate and characteristics of injury and illness varied between sports, consistent patterns across YOG are emerging. If addressed, changes in highlighted areas of risk could have a positive impact on the health and well-being of these young athletes.

Coronary artery disease (CAD) remains the leading cause of death worldwide. Expanding patients' metabolic phenotyping beyond clinical chemistry investigations could lead to earlier recognition of disease onset and better prevention strategies. Additionally, metabolic phenotyping, at the molecular species level, contributes to unravel the roles of metabolites in disease development. In this cross-sectional study, we investigated clinically healthy individuals (n = 116, 65% male, 70.8 ± 8.7 years) and patients with CAD (n = 54, 91% male, 67.0 ± 11.5 years) of the COmPLETE study. We applied a high-coverage quantitative liquid chromatography-mass spectrometry approach to acquire a comprehensive profile of serum acylcarnitines, free carnitine and branched-chain amino acids (BCAAs), as markers of mitochondrial health and energy homeostasis. Multivariable linear regression analyses, adjusted for confounders, were conducted to assess associations between metabolites and CAD phenotype. In total, 20 short-, medium- and long-chain acylcarnitine species, along with L-carnitine, valine and isoleucine were found to be significantly (adjusted p ≤ 0.05) and positively associated with CAD. For 17 acylcarnitine species, associations became stronger as the number of affected coronary arteries increased. This implies that circulating acylcarnitine levels reflect CAD severity and might play a role in future patients' stratification strategies. Altogether, CAD is characterized by elevated serum acylcarnitine and BCAA levels, which indicates mitochondrial imbalance between fatty acid and glucose oxidation.

Background: Cardiorespiratory fitness (CRF) is a potent health marker, the improvement of which is associated with a reduced incidence of non-communicable diseases and all-cause mortality. Identifying metabolic signatures associated with CRF could reveal how CRF fosters human health and lead to the development of novel health-monitoring strategies. Objective: This article systematically reviewed reported associations between CRF and metabolites measured in human tissues and body fluids. Methods: PubMed, EMBASE, and Web of Science were searched from database inception to 3 June, 2021. Metabolomics studies reporting metabolites associated with CRF, measured by means of cardiopulmonary exercise test, were deemed eligible. Backward and forward citation tracking on eligible records were used to complement the results of database searching. Risk of bias at the study level was assessed using QUADOMICS. Results: Twenty-two studies were included and 667 metabolites, measured in plasma (n = 619), serum (n = 18), skeletal muscle (n = 16), urine (n = 11), or sweat (n = 3), were identified. Lipids were the metabolites most commonly positively (n = 174) and negatively (n = 274) associated with CRF. Specific circulating glycerophospholipids (n = 85) and cholesterol esters (n = 17) were positively associated with CRF, while circulating glycerolipids (n = 152), glycerophospholipids (n = 42), acylcarnitines (n = 14), and ceramides (n = 12) were negatively associated with CRF. Interestingly, muscle acylcarnitines were positively correlated with CRF (n = 15). Conclusions: Cardiorespiratory fitness was associated with circulating and muscle lipidome composition. Causality of the revealed associations at the molecular species level remains to be investigated further. Finally, included studies were heterogeneous in terms of participants’ characteristics and analytical and statistical approaches. PROSPERO Registration Number: CRD42020214375.