Metabolite signatures of exercise training in human skeletal muscle relate to mitochondrial remodelling and cardiometabolic fitness

Abstract

Aims/hypothesis: Targeted metabolomic and transcriptomic approaches were used to evaluate the relationship between skeletal muscle metabolite signatures, gene expression profiles and clinical outcomes in response to various exercise training interventions. We hypothesised that changes in mitochondrial metabolic intermediates would predict improvements in clinical risk factors, thereby offering novel insights into potential mechanisms.

Methods: Subjects at risk of metabolic disease were randomised to 6 months of inactivity or one of five aerobic and/or resistance training programmes (n = 112). Pre/post-intervention assessments included cardiorespiratory fitness ([Formula: see text]), serum triacylglycerols (TGs) and insulin sensitivity (SI). In this secondary analysis, muscle biopsy specimens were used for targeted mass spectrometry-based analysis of metabolic intermediates and measurement of mRNA expression of genes involved in metabolism.

Results: Exercise regimens with the largest energy expenditure produced robust increases in muscle concentrations of even-chain acylcarnitines (median 37-488%), which correlated positively with increased expression of genes involved in muscle uptake and oxidation of fatty acids. Along with free carnitine, the aforementioned acylcarnitine metabolites were related to improvements in [Formula: see text], TGs and SI (R = 0.20-0.31, p < 0.05). Muscle concentrations of the tricarboxylic acid cycle intermediates succinate and succinylcarnitine (R = 0.39 and 0.24, p < 0.05) emerged as the strongest correlates of SI.

Conclusions/interpretation: The metabolic signatures of exercise-trained skeletal muscle reflected reprogramming of mitochondrial function and intermediary metabolism and correlated with changes in cardiometabolic fitness. Succinate metabolism and the succinate dehydrogenase complex emerged as a potential regulatory node that intersects with whole-body insulin sensitivity. This study identifies new avenues for mechanistic research aimed at understanding the health benefits of physical activity. Trial registration ClinicalTrials.gov NCT00200993 and NCT00275145 Funding This work was supported by the National Heart, Lung, and Blood Institute (National Institutes of Health), National Institute on Aging (National Institutes of Health) and National Institute of Arthritis and Musculoskeletal and Skin Diseases (National Institutes of Health).

Fig. 1

Muscle acylcarnitines and organic acids: per cent change from baseline and relation to cardiorespiratory fitness (V̇O_2peak) and insulin sensitivity change. Bars represent skeletal muscle metabolite median per cent change for each intervention arm: Inactive; low-amount moderate-intensity aerobic exercise (Low/Moderate); low-amount vigorous-intensity aerobic exercise (Low/Vigorous); high-amount vigorous-intensity aerobic exercise (High/Vigorous); combination of low/vigorous aerobic exercise and resistance training (Low Vigorous/RT); resistance training only (RT). *p<0.01 vs Inactive (non-parametric ANOVAs with post hoc comparisons). Spearman correlations were used to relate per cent changes in skeletal muscle metabolites and per cent changes in cardiorespiratory fitness (V̇O_2peak), insulin sensitivity, and TGs. For acylcarnitine relationships with V̇O_2peak (positive): dashed line, p<0.05; solid line, p≤0.01. For acylcarnitine relationships with insulin sensitivity (positive): ^†p<0.05; ^‡p≤0.01. For acylcarnitine relationships with TGs (negative): ^§p<0.05 ^§§p≤0.01

Fig. 2

Variability in changes in insulin sensitivity. Each bar represents the per cent change in insulin sensitivity for an individual participant; changes are ranked from lowest to highest. (a) Individual changes clustered by intervention arm (Inactive; low-amount moderate-intensity aerobic exercise (Low/Moderate); low-amount vigorous-intensity aerobic exercise (Low/Vigorous); high-amount vigorous-intensity aerobic exercise (High/Vigorous); combination of low/vigorous aerobic exercise and resistance training (Low Vigorous/RT); resistance training only (RT). (b) Individual changes irrespective of group

Fig. 3

Relationship between changes in insulin sensitivity and skeletal muscle metabolites. Scatter plots depicting per cent changes in insulin sensitivity and skeletal muscle succinate (a), free carnitine (b), succinyl carnitine (c) and octenoyl carnitine (d). See Table 2 for Spearman correlations

Fig. 4

Representation of the succinate dehydrogenase node. Metabolic intermediates are centralised around succinate as a nodal point for the convergence of the TCA cycle, BCAA catabolism, β-oxidation, haem biosynthesis and ketone catabolism. Changes in metabolic intermediates associated with changes in insulin sensitivity are shown in orange. ETS, electron transport system; Suc-CoA, succinyl-CoA; SucL, succinate–CoA ligase; αKDH, α-ketoglutarate dehydrogenase; α-KG, α-ketoglutarate, PCC, propionyl-CoA carboxylase; C4DC-carnitine, succinyl carnitine; SCOT, succinyl-CoA : 3-ketoacid-CoA transferase; BHBDH, β-hydroxybutyrate dehydrogenase; KT, 3- ketoacyl-CoA thiolase. LC-AcCarn, long chain acylcarnitine; Lc-AcCoA, long chain acyl-CoA; AcAc-CoA, acetylacetyl-Coa; MMCM, methylmalonyl-CoA mutase

Fig. 5

Flow chart for associations of gene expression with metabolites. ^aPathways: TCA cycle, β-oxidation, amino acid metabolism, ketone synthesis and degradation, lipid metabolism and trafficking, oxidative phosphorylation, BCAA catabolism, succinate metabolism, glycine metabolism

Fig. 6

Relationship between changes in skeletal muscle metabolites and expression of genes involved in fatty acid metabolism. Spearman correlations were performed between changes in skeletal muscle metabolites (first column) and changes in skeletal muscle gene expression (first row). Black indicates significant positive relationship (p<0.001)