MetAR: A semi-automated meta-analysis of skeletal muscle androgen receptors association with age

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MetAR: A semi-automated meta-analysis of skeletal muscle androgen receptors association with age

Authors

Williams, R. M.; Engman, V.; Soria, M.; Hiam, D.; Wadley, G. D.; Lamon, S.

Abstract

Background: The maintenance of skeletal muscle health plays a pivotal role in prolonging both the lifespan and healthspan. However, muscle mass and strength exhibit significant declines with age. Ageing is associated with a reduced muscle protein synthesis response to key anabolic stimuli, including the androgen hormone testosterone, termed anabolic resistance. Testosterone enacts its anabolic effects in muscle through androgen receptor (AR) mediated pathways. Emerging evidence suggests that AR availability may represent a rate-limiting factor in androgen signalling, with AR saturation occurring below physiological testosterone levels in some tissues. Prior research in rodents has reported age-related reductions in AR expression, suggesting changes in AR protein content may constitute a key component of anabolic resistance. However, reports of the effects of age on the human skeletal muscle AR are inconclusive and limited by small sample sizes. Therefore, this study aimed to characterise age-related changes in expression of the AR, its regulators and downstream target genes in human skeletal muscle. Methods: We developed and used a novel R-based pipeline, MetAR, to perform reproducible meta-analyses of publicly available bulk RNA-Seq datasets from NCBI GEO and investigate associations between target gene expression and variables of interest without the need for high-performance computing. Eligible datasets included skeletal muscle samples from healthy adult males aged [&ge;]18 years, with an age range of [&ge;] 10 years and sample size [&ge;] 6. Raw counts data were downloaded, appraised and TMM normalised. Dataset-level associations between age and target gene expression were assessed using linear and generalised additive models (GAMs). Random-effects meta-analyses were performed, and heterogeneity, publication bias and leave-one-out sensitivity assessed. Results: Sixteen skeletal muscle bulk RNA-seq datasets (n = 364; age 18-92 years) were eligible for inclusion in the meta-analyses. AR expression was negatively associated with age ({beta} = -0.006 log2 TMM-CPM per year, p < 0.001) corresponding to a 4.4% decrease in expression per decade. Age was also associated with a significant reduction in expression of various regulators of AR stability, transcriptional activity and nuclear transport. Additionally, steroidogenic enzymes and key downstream targets of the AR, including genes encoding for key structural proteins and mitochondrial function were negatively associated with age. Conclusions: Collectively, these findings suggest a multi-faceted age-associated remodelling of AR expression, signalling and nuclear transport that may contribute to the development of anabolic resistance and consequent age-associated muscle loss.

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