Development of skeletal muscle models to study ageing and associated conditions

Rapid ageing of the population together with raised prevalence of chronic metabolic diseases provokes huge economic burden on healthcare systems. Furthermore, age-related loss of skeletal muscle is associated with increase in disability, injuries, dependency and eventually mortality. Given the importance of skeletal muscle mass in both locomotion and homeostasis, developing countermeasures to hinder the raising prevalence of sarcopenia is critical. Human skeletal muscle experiments in vivo are limited due to ethical and safety concerns, and animal models are poor predictors of clinical outcomes and drug responses in humans. Therefore, developing biologically advanced in vitro systems to investigate regulation of skeletal muscle mass and underlying mechanisms is pivotal. Hence, the aim of this project was to develop advanced models to study age related changes in skeletal muscle. This study focused on a) expanding our knowledge on biomarkers regulating muscle ageing and the effect of exercise on these markers; b) investigating the causes of impaired regeneration in aged muscle; and c) developing tissue engineered muscle model with structural and functional properties of native muscle. The findings in this study indicate that using artificial neural network inference (ANNI) analysis we could identify novel age- and exercise related genes such as USP54, JAK2, CHAD, ZDBF2, EIF4A2, NIPAL3, SCFD1 and KDM5D previously not associated with skeletal muscle. Furthermore, we characterise an in vitro human muscle regeneration model and describe the development of novel non-custom-made inserts to fabricate high-throughput tissue engineered muscle. Together, the findings suggest that established models in this project have a potential to contribute to research on muscle ageing by providing high-fidelity platform to further examine regulation of muscle mass across the lifespan and to investigate potential effects of drugs and/or therapies