Hyperglycaemia is associated with impaired muscle signalling and aerobic adaptation to exercise

Abstract

Increased aerobic exercise capacity, as a result of exercise training, has important health benefits. However, some individuals are resistant to improvements in exercise capacity, probably due to undetermined genetic and environmental factors. Here, we show that exercise-induced improvements in aerobic capacity are blunted and aerobic remodelling of skeletal muscle is impaired in several animal models associated with chronic hyperglycaemia. Our data point to chronic hyperglycaemia as a potential negative regulator of aerobic adaptation, in part, via glucose-mediated modifications of the extracellular matrix, impaired vascularization and aberrant mechanical signalling in muscle. We also observe low exercise capacity and enhanced c-Jun N-terminal kinase activation in response to exercise in humans with impaired glucose tolerance. Our work indicates that current shifts in dietary and metabolic health, associated with increasing incidence of hyperglycaemia, might impair muscular and organismal adaptations to exercise training, including aerobic capacity as one of its key health outcomes.

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Fig. 1: Glucose intolerance and hyperglycaemia develop in WD-fed and STZ-injected mice.
Fig. 2: Metabolic outcomes in response to exercise training.
Fig. 3: Exercise capacity and muscle phenotype in response to exercise training.
Fig. 4: Impaired glucose tolerance and hyperglycaemia are associated with muscle ECM accretion.
Fig. 5: In vitro angiogenesis and muscle gene expression changes in response to hyperglycaemia.
Fig. 6: Hyperglycaemia is associated with altered muscle signalling with acute exercise.
Fig. 7: Exercise-induced JNK activation increases with glucose intolerance in humans.
Fig. 8: Hypothesized mechanisms by which hyperglycaemia may blunt aerobic adaptations with exercise.

Data availability

Source data for western blots are available online. All other data that support the findings of this study are available from the corresponding author upon reasonable request. Source data are provided with this paper.

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Acknowledgements

Research reported in this publication was supported by a Pilot and Feasibility award granted to S.J.L., and Diabetes Research Center core facilities funded by the NIH (NIDDK) award number P30DK036836. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. This work was also supported by an American Heart Association grant to S.J.L. (award number 15SDG25560057) and the Boston Nutrition and Obesity Research Center (BNORC) Pilot Program (P30DK046200, subaward no. 7513). T.L.M. was supported by a postdoctoral fellowship from the American Heart Association (no. 19POST34381036). P.Pattamaprapanont was supported by a Mary K. Iacocca Senior Visiting Fellowship. E.C.F. was supported by the São Paulo Research Foundation (grant no. FAPESP 2017/21676-3). Core facilities used for histological analysis were supported in part by NCI Cancer Center Support grant no. NIH 5 P30 CA06516 and NINDS P30 Core Center grant no. NS072030. The LRT-HRT rat model is funded by the Office of Infrastructure Programs grant no. P40ODO21331 (to L.G.K. and S.L.B.) from the NIH. Rat models for low and high response to exercise training are maintained as an international resource with support from the Department of Physiology and Pharmacology, The University of Toledo College of Medicine, Toledo, OH. Contact L.G.K. (lauren.koch2@utoledo.edu) or S.L.B. (brittons@umich.edu) for information on the rat models. For human studies, we acknowledge support by the Joslin Clinical Research Center and thank its philanthropic donors.

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Conceptualization of the idea came from T.L.M. and S.J.L. The methodology was devised by T.L.M., P. Pattamaprapanont, P. Pathak, S.H., J.M., S.L.B., L.G.K. and S.J.L. Validation was conducted by T.L.M., P. Pattamaprapanont, P. Pathak, N.F., E.C.F. and S.J.L. Formal analysis was conducted by T.L.M., P. Pattamaprapanont, P. Pathak, N.F., E.C.F. and S.J.L. Investigation was done by T.L.M., P. Pattamaprapanont, P. Pathak, N.F., E.C.F., S.H., J.M., S.L.B., L.G.K. and S.J.L. Resources were provided by S.L.B., L.G.K. and S.J.L. The original draft was written by T.L.M. and S.J.L. Reviews and editing were done by T.L.M., P. Pattamaprapanont, P. Pathak, N.F., E.C.F., S.H., J.M., S.L.B., L.G.K. and S.J.L. The visualization was done by T.L.M. and S.J.L. Supervision was done by T.L.M. and S.J.L. Funding acquisition was done by T.L.M., P. Pattamaprapanont, E.C.F. and S.J.L.

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Correspondence to Sarah J. Lessard.

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Extended data

Extended Data Fig. 1 Extended Data Figure 1: 24 h wheel running behaviour.

A cohort of mice in control (CON, n=4), Western Diet-fed (WD, n=4) and Streptozotocin (STZ, n=4) groups undergoing exercise training were placed in cages to assess wheel running patterns. Wheel revolutions were counted per 1 h interval and recorded. a, An average trace over 24 h is shown; and mean for time spent running in the dark (%) is shown in Table b. Data are shown as mean ± SEM. Group differences in time spent dark running were compared by one-way ANOVA.

Extended Data Fig. 2 Extended Data Figure 2: Baseline exercise capacity.

Three separate cohorts of CD-1 mice were fed with Western Diet (WD), injected with streptozotocin (STZ) or maintained on a control diet (CON). After 8 weeks of treatment, all mice underwent aerobic exercise capacity testing in a and were found to have similar exercise capacities prior to being allocated to treatment groups for the training intervention (CON n=34, WD n=32, STZ n=42). Mice from each treatment group (CON, WD, STZ) were then allocated to remain sedentary or undergo voluntary wheel running (exercise-training) for a further 8 weeks. Baseline (pretraining) exercise capacity, shown in b, was similar among all six treatment groups (CON SED n=17, WD SED n=16, STZ SED n=22; CON EXT n=17, WD EXT n=16, STZ EXT n=20). Main effects were determined by one-way ANOVA relative to CON group in a and by two-way ANOVA in b. Data is represented as a point for the result of each individual animal, or mean ± SEM.

Extended Data Fig. 3 Extended Data Figure 3: JNK activation with treadmill running during acute and chronic hyperglycaemia.

a, To determine whether JNK activation with exercise is due to hyperglycemia, NOD mice completed an acute exercise bout (AEX n=18; 30 min treadmill running) or remained sedentary (SED n=6) and JNK signaling was measured in gastrocnemius muscle to determine correlation with random blood glucose. Representative blots (n= 1 SED; n= 2 AEX) shown here correspond with data shown in Figure 6g. To determine whether JNK activation with exercise is affected by acute increases in blood glucose, CD-1 mice were maintained on a control chow diet and fasted for 2 h prior to being split into four groups: a) control sedentary (n=5), b) acute glucose sedentary (n=5), c) control 30 min exercise (n=4) and d) acute glucose 30 min exercise (n=5). Mice allocated to glucose treatment were injected with 3 g/kg glucose to rapidly increase circulating glucose levels. b, JNK is activated with acute exercise (AEX) in gastrocnemius muscle, but acute glucose elevation does not alter JNK signaling with moderate treadmill running. c, Relative increases in blood glucose in control animals versus mice injected with 3 g/kg glucose. d, Mice were maintained on control diet (CON) or Western Diet (WD) for 8 (CON n=4; WD n=5), 16 (CON n=10; WD n=7), or 32 weeks (CON n=9, WD n=10) and an acute running experiment was performed at each time point. JNK activation with moderate treadmill running (30 min) was significantly higher in WD mice vs. CON mice by 16 weeks and worsened by 32 weeks; (right) representative blots showing n= 2/group per time point. Data is represented as mean ± SEM in all panels. Main effects were determined by two-way ANOVA in a and c. In d, differences in JNK activation between groups and over time were determined by two-way repeated measured ANOVA and indicated with “P”; differences between CON and WD groups at each 16 and 32 wk timepoint are indicated with “p.”. Source data

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Source Data Fig. 6

Unprocessed western blots

Source Data Fig. 7

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Source Data Extended Data Fig. 3

Unprocessed western blots

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MacDonald, T.L., Pattamaprapanont, P., Pathak, P. et al. Hyperglycaemia is associated with impaired muscle signalling and aerobic adaptation to exercise. Nat Metab (2020). https://doi.org/10.1038/s42255-020-0240-7

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