Global Skeletal Muscle Metabolomics Reveals Mechanisms Behind Higher Response to Resistance Training in Older Adults
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Background
Resistance training (RT) is a highly effective intervention for combating frailty by improving muscle mass, strength, and function in aging. Older adults often show heterogeneous muscle-related responses to RT. The purpose of this study was to discover how responsiveness to RT manifests in muscle-specific metabolomic responses in a cohort of older adults.
Methods
This study is a scoendary analysis on the vastus lateralis muscle biopsies collected from a completed RT and wehy protein supplementation. We utilsied the data from a total of 50 participants whom performed unilateral knee extensions twice weekly for 10 weeks. One leg completed 1 set, and the other completed 4 sets of 8–15 repetitions. We analysed the 4-set condition, previously shown to induce greater muscle hypertrophy. Response variability was assessed using MRI-measured muscle cross-sectional area (CSA) changes. Utilising the MRI data, we defined responders as those who had hypertrophy exceeding the 1.7% method error. Quadriceps CSA in the lower responder (LowR) increased from 53.6 ± 12.1 cm 2 to 55.4 ± 12.8 cm 2 after 10 weeks of RET (3.3 ± 1.7%, P < 0.001) and increased the absolute CSA in the higher responders (HighR) from 53.7 ± 12.5 cm 2 to 59.2 ± 13.6 cm 2 (10.3 ± 2.0%, P < 0.001). Muscle biopsies were taken from the vastus lateralis before and after RT. We performed untargeted liquid chromatography-mass spectrometry metabolomics to investigate changes in muscle metabolic regulation. The partial least squares discriminant analysis (PLS-DA) yielded the best results using the polar extracts, achieving a 75% average correct classification rate for predicting HighR and LowR. The models were validated by using 1,000 bootstrapping procedures. We then performed N-way ANOVA on each log-transformed metabolic feature to detect whether there are statistically significant differences between before and after RT between HighR (n=25, mean age 67±4 years) and vs. LowR (n=25, mean age 69±5 years).
Results
There was no signifncat differences in metabolomic profile at the basline. Further, the HighR metabolic phenotype showed greater relative levels of amino acids, such as isoleucine, leucine, valine, phenylalanine, lysine, glutamine, methionine, tyrosine, citrulline, tryptophan, kynurenine, and indole); and gut-related metabolites (choline, indole, kynurenic acid, indole, adrenaline, and isoprenaline) (FDR< 0.05). Interestingly, several gut-derived metabolites were significantly elevated in the HighR, including indole metabolites, 4-hydroxyhippurate, proline, and stachydrine (FDR< 0.05). Further, we performed pathways-enrichment analysis using the Mummichog approach; which revealed significant enrichments for tyrosine, aspartate, and tryptophan metabolisms (P-fisher <0.05).
Conclusion
Our findings revealed several metabolic pathways, including branched-chain amino acid catabolism, tryptophan metabolism (indole and kynurenine pathways), the TCA cycle, gut-derived metabolites, carnosine, and acylcarnitine metabolism as prominent pathways disrupted in LowR. We demonstrated that metabolomics can provide new insights and has the potential to identify and enhance interventions targeting muscle metabolism, ultimately improving muscle mass and strength to reduce the risk of sarcopenia and frailty in older age.
