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Proliferating cancer cells shift their metabolism towards glycolysis, even in the presence of oxygen, to especially generate glycolytic intermediates as substrates for anabolic reactions. We hypothesize that a similar metabolic remodelling occurs during skeletal muscle hypertrophy. We used mass spectrometry in hypertrophying C2C12 myotubes in vitro and plantaris mouse muscle in vivo and assessed metabolomic changes and the incorporation of the [U‐13C6]glucose tracer. We performed enzyme inhibition of the key serine synthesis pathway enzyme phosphoglycerate dehydrogenase (Phgdh) for further mechanistic analysis and conducted a systematic review to align any changes in metabolomics during muscle growth with published findings. Finally, the UK Biobank was used to link the findings to population level. The metabolomics analysis in myotubes revealed insulin‐like growth factor‐1 (IGF‐1)‐induced altered metabolite concentrations in anabolic pathways such as pentose phosphate (ribose‐5‐phosphate/ribulose‐5‐phosphate: +40%; P= 0.01) and serine synthesis pathway (serine: −36.8%; P= 0.009). Like the hypertrophy stimulation with IGF‐1 in myotubes in vitro, the concentration of the dipeptide l‐carnosine was decreased by 26.6% (P= 0.001) during skeletal muscle growth in vivo. However, phosphorylated sugar (glucose‐6‐phosphate, fructose‐6‐phosphate or glucose‐1‐phosphate) decreased by 32.2% (P= 0.004) in the overloaded muscle in vivo while increasing in the IGF‐1‐stimulated myotubes in vitro. The systematic review revealed that 10 metabolites linked to muscle hypertrophy were directly associated with glycolysis and its interconnected anabolic pathways. We demonstrated that labelled carbon from [U‐13C6]glucose is increasingly incorporated by ~13% (P= 0.001) into the non‐essential amino acids in hypertrophying myotubes, which is accompanied by an increased depletion of media serine (P= 0.006). The inhibition of Phgdh suppressed muscle protein synthesis in growing myotubes by 58.1% (P< 0.001), highlighting the importance of the serine synthesis pathway for maintaining muscle size. Utilizing data from the UK Biobank (n= 450 243), we then discerned genetic variations linked to the serine synthesis pathway (PHGDHand PSPH) and to its downstream enzyme (SHMT1), revealing their association with appendicular lean mass in humans (P< 5.0e‐8). Understanding the mechanisms that regulate skeletal muscle mass will help in developing effective treatments for muscle weakness. Our results provide evidence for the metabolic rewiring of glycolytic intermediates into anabolic pathways during muscle growth, such as in serine synthesis.

This review links science and best practice recommendations by quantitatively analysing 92 publicly available marathon training plans for sub-elite marathon runners.Weekly planned running distance in the last 12 weeks before the marathon ranged from 107.7 km for high volume, 58.5 km for middle volume, to 42.9 km for low volume training plans, with the longest run in these plans ranging from 35.2 km for high to 30.9 km for low volume plans.Following a five-zone intensity model, training intensity distribution for all volume categories followed a low, middle, and high intensity pyramidal structure with 13.2% in zone 1, 65.6% in zone 2, 15.1% in zone 3, 3.0% in zone 4, and 3.0% in zone 5. Most of the training volume was recommended to be run in zone 2.

Aims Exercise is a trigger for acute coronary events especially in the untrained. Identifying subjects at risk remains a challenge. We set out to assess whether a distinct pattern of micro ribonucleic acids (miRNAs) expressed in response to an acute bout of all-out exercise might exist that would allow discrimination between health and disease.Methods Twenty healthy subjects and 20 patients with coronary artery disease (CAD) performed an all-out cycle ergometry. Total RNA was extracted from blood drawn before and after exercise. Each blood sample was analysed for 187 target miRNAs by quantitative reverse transcription polymerase chain reaction.Results At baseline, 18 miRNAs allowed discrimination between healthy subjects and CAD patients. In response to an acute all-out exercise in healthy subjects 51 miRNAs and in CAD patients 60 miRNAs were significantly modulated (all p< 0.05). Using logistic regression analysis, a unique pattern of pre-exercise miR-150-5p, post-exercise miR-101-3p, miR-141-3p and miR-200b-3p together with maximal oxygen uptake and maximal power corrected for bodyweight allowed discrimination between healthy subjects and CAD patients with an accuracy of 92.5%.Conclusion In this most comprehensive analysis of exercise effects on circulating miRNAs to date we demonstrate for the first time that a distinct combination of miRNAs together with variables of exercise capacity allow robust discrimination between healthy subjects and CAD patients. We postulate that miRNAs may eventually serve as biomarkers to identify patients with CAD and possibly even those at risk of exercise-induced cardiac events.

Background Recent findings revealed negative effects of deregulated molecular circadian rhythm in coronary artery disease (CAD) and type 2 diabetes mellitus (T2DM). Physical exercise training (ET) has been shown to promote anti-diabetic and anti-atherogenic responses in skeletal muscle of these patients, but the role of the circadian clock-machinery remains unknown. This study investigated whether mRNA expression of clock genes in skeletal muscle of CAD and T2DM patients is influenced by physical ET intervention.Methods Nineteen patients with CAD and T2DM (age 64 ± 5 years) were randomised to either six months of ET (four weeks of in-hospital ET followed by a five-month ambulatory programme) or usual care. At the beginning of the study, after four weeks and after six months parameters of metabolic and cardiovascular risk factors, and physical exercise capacity were assessed. Gene expression was measured in skeletal muscle biopsies by quantitative real-time polymerase chain reaction (PCR).Results A selection of clock genes and associated components (circadian locomoter output cycle kaput protein (CLOCK), period (PER) 1, cryptochrome (CRY) 2 and aminolevulinate-deltA-synthase-1 (ALAS1)) was reliably measured and used for further analysis. A time-dependent effect in gene expression was observed in CLOCK (p= 0.013) and a significant interaction between time and intervention was observed for ALAS1 (p= 0.032; p= 0.014) as a result of ET.Conclusion This is the first study to analyse clock gene expression in skeletal muscles of patients with CAD and T2DM participating in a long-lasting exercise intervention. ET, as one of the cornerstones in prevention and rehabilitation of CAD and T2DM, exerts no effects on CLOCK genes but meaningful effects on the clock-associated gene ALAS1.

Background High-intensity interval training has recently emerged as superior to continuous endurance training in cardiac rehabilitation upon other training regimes. Individually tailored continuous endurance training and pyramid training could induce comparable effects on peak work capacity as high intensity interval training.Design A prospective, randomized study.Methods Effects of the following isocaloric cycle ergometer protocols on peak work capacity have been assessed in patients with coronary artery disease (n= 60) during 6 weeks of outpatient cardiac rehabilitation, i.e. 18 supervised sessions of exercise training: (1) continuous endurance training (n= 20): 33 min at 65–85% peak heart rate; (2) high intensity interval training (n= 20): 4 × 4 min intervals at 85–95% peak heart rate, each followed by 3 min of active recovery at 60–70% peak heart rate; (3) pyramid training (n= 20): 3 × 8 min of stepwise load increase and subsequent decrease from 65–95–65% peak heart rate, supplemented by 2 min recovery at 60–70% peak heart rate between pyramids. All protocols were preceded by 5 min of warm-up and followed by 5 min cool-down at 60–70% peak heart rate.Results Attendance during exercise sessions was 99.2%. There were significant increases in peak work capacity of comparable magnitude in all three training groups (begin vs. end: continuous endurance training: 136.0 ± 49.6 W vs. 163.4 ± 60.8 W (21.1 ± 8.5%); high-intensity interval training: 141.0 ± 60.4 W vs. 171.1 ± 69.8 W (22.8 ± 6.6%); pyramid training: 128.7 ± 50.6 W vs. 158.5 ± 57.9 W (24.8 ± 10.8%); within groups all p< 0.001; between groups, p= not significant).Conclusion Endurance training protocols assessed in this study all led to significant increases in peak work capacity of comparable magnitude. Our findings suggest that these protocols can be used interchangeably, which will lead to further individualization of exercise prescription and may therefore result in improved adherence to lifelong behavioural changes.

Background: Exercise changes the concentrations of many metabolites, which are small molecules (&lt; 1.5 kDa) metabolized by the reactions of human metabolism. In recent years, especially mass spectrometry-based metabolomics methods have allowed researchers to measure up to hundreds of metabolites in a single sample in a non-biased fashion. To summarize human exercise metabolomics studies to date, we conducted a systematic review that reports the results of experiments that found metabolite concentrations changes after a bout of human endurance or resistance exercise. Methods: We carried out a systematic review following PRISMA guidelines and searched for human metabolomics studies that report metabolite concentrations before and within 24 h after endurance or resistance exercise in blood, urine, or sweat. We then displayed metabolites that significantly changed their concentration in at least two experiments. Results: Twenty-seven studies and 57 experiments matched our search criteria and were analyzed. Within these studies, 196 metabolites changed their concentration significantly within 24 h after exercise in at least two experiments. Human biofluids contain mainly unphosphorylated metabolites as the phosphorylation of metabolites such as ATP, glycolytic intermediates, or nucleotides traps these metabolites within cells. Lactate, pyruvate, TCA cycle intermediates, fatty acids, acylcarnitines, and ketone bodies all typically increase after exercise, whereas bile acids decrease. In contrast, the concentrations of proteinogenic and non-proteinogenic amino acids change in different directions. Conclusion: Across different exercise modes and in different subjects, exercise often consistently changes the average concentrations of metabolites that belong to energy metabolism and other branches of metabolism. This dataset is a useful resource for those that wish to study human exercise metabolism.