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Factors Influencing AMPK Activation During Cycling Exercise: A Pooled Analysis and Meta-Regression

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Abstract

Background

The 5ʹ adenosine monophosphate (AMP)-activated protein kinase (AMPK) is a cellular energy sensor that is activated by increases in the cellular AMP/adenosine diphosphate:adenosine triphosphate (ADP:ATP) ratios and plays a key role in metabolic adaptations to endurance training. The degree of AMPK activation during exercise can be influenced by many factors that impact on cellular energetics, including exercise intensity, exercise duration, muscle glycogen, fitness level, and nutrient availability. However, the relative importance of these factors for inducing AMPK activation remains unclear, and robust relationships between exercise-related variables and indices of AMPK activation have not been established.

Objectives

The purpose of this analysis was to (1) investigate correlations between factors influencing AMPK activation and the magnitude of change in AMPK activity during cycling exercise, (2) investigate correlations between commonly reported measures of AMPK activation (AMPK-α2 activity, phosphorylated (p)-AMPK, and p-acetyl coenzyme A carboxylase (p-ACC), and (3) formulate linear regression models to determine the most important factors for AMPK activation during exercise.

Methods

Data were pooled from 89 studies, including 982 participants (93.8% male, maximal oxygen consumption [\(V{\text{O}}_{2\max }\)] 51.9 ± 7.8 mL kg−1 min−1). Pearson’s correlation analysis was performed to determine relationships between effect sizes for each of the primary outcome markers (AMPK-α2 activity, p-AMPK, p-ACC) and factors purported to influence AMPK signaling (muscle glycogen, carbohydrate ingestion, exercise duration and intensity, fitness level, and muscle metabolites). General linear mixed-effect models were used to examine which factors influenced AMPK activation.

Results

Significant correlations (r = 0.19–0.55, p < .05) with AMPK activity were found between end-exercise muscle glycogen, exercise intensity, and muscle metabolites phosphocreatine, creatine, and free ADP. All markers of AMPK activation were significantly correlated, with the strongest relationship between AMPK-α2 activity and p-AMPK (r = 0.56, p < 0.001). The most important predictors of AMPK activation were the muscle metabolites and exercise intensity.

Conclusion

Muscle glycogen, fitness level, exercise intensity, and exercise duration each influence AMPK activity during exercise when all other factors are held constant. However, disrupting cellular energy charge is the most influential factor for AMPK activation during endurance exercise.

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Authors and Affiliations

  1. Sports Performance Research Institute New Zealand (SPRINZ), Auckland University of Technology, Auckland, New Zealand

    Jeffrey A. Rothschild, Andrew E. Kilding, Tom Stewart & Daniel J. Plews

  2. School of Health and Exercise Sciences, University of British Columbia Okanagan, Kelowna, BC, Canada

    Hashim Islam

  3. Institute for Health and Sport (iHeS), Victoria University, Melbourne, VIC, Australia

    David J. Bishop

  4. School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia

    David J. Bishop

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  1. Jeffrey A. Rothschild
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Jeffrey A. Rothschild, Hashim Islam, David J. Bishop, Andrew E. Kilding, Tom Stewart, and Daniel J. Plews have no conflicts of interest that are directly relevant to the content of this article.

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Data can be made available upon request to the lead author. Correlations and model data can be explored using an online app: https://rothschild.shinyapps.io/AMPK_dashboard/

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JAR conceptualized and performed the analyses and wrote the first draft of the manuscript. All authors edited and revised the manuscript and approved the final version of the manuscript.

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Rothschild, J.A., Islam, H., Bishop, D.J. et al. Factors Influencing AMPK Activation During Cycling Exercise: A Pooled Analysis and Meta-Regression. Sports Med 52, 1273–1294 (2022). https://doi.org/10.1007/s40279-021-01610-x

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