Exploring the multifactorial causes and therapeutic strategies for anabolic resistance in sarcopenia: A systems modeling study
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Background
Sarcopenia is the progressive loss of skeletal muscle mass, strength, and function with age, driven by dysregulation in the rates of muscle protein synthesis (MPS) and breakdown (MPB). Although MPB contributes to net protein balance (NB), a primary contributor of sarcopenia is anabolic resistance, defined as the blunted MPS response to anabolic stimuli such as feeding. While candidate mechanisms of anabolic resistance have been identified, none singularly explains the reduction in MPS. Instead, multiple mechanisms likely act simultaneously and interactively to suppress MPS. Studying these interactions experimentally is challenging. Alternatively, mathematical modeling is well suited to analyzing complex biological phenomena such as anabolic resistance.
Methods
We analyzed a previously developed kinetic model of leucine-mediated signaling and protein metabolism in human skeletal muscle to systematically investigate potential mechanisms contributing to anabolic resistance. A global sensitivity analysis identified key controllers of MPS, MPB, and NB. We then simulated an essential amino acid feeding intervention in older adults, classified the responses as either anabolic sensitive or resistant, and compared the resulting parameter distributions of the two groups. A targeted analysis evaluated the effects of individual and combined dysregulated putative mechanisms of anabolic resistance on muscle metabolism. Finally, we simulated therapeutic interventions aimed at restoring muscle metabolism.
Results
Sensitivity analysis revealed that MPS and MPB are primarily controlled by their proximal signaling controllers, while NB is largely driven by MPS dynamics. Exploratory simulations showed that several parameters and signaling protein concentrations, particularly those controlling MPS, differed significantly between anabolic sensitive and resistant groups. Targeted simulations indicated that multiple dysregulated mechanisms were required to account for the experimentally observed reductions in MPS in older adults. Therapeutic simulations showed that while single-target interventions could largely restore MPS when isolated mechanisms were perturbed (e.g., enhancing p70S6K levels, increasing mTORC1 sensitivity), a multifactorial approach was required to recover muscle metabolism when all anabolic resistance mechanisms were present.
Conclusion
This study demonstrates the multifactorial nature of anabolic resistance. We provide a framework for the experimental manipulation of independent and related factors that could underpin age-related anabolic resistance. The results motivate new hypotheses regarding the mechanisms most likely to be impaired and support the development of multi-target therapeutic strategies to help restore muscle protein metabolism in aging.
