Network analysis of human skeletal muscle adaptation under different loading states
Lead Research Organisation:
UNIVERSITY OF EXETER
Department Name: Sport and Health Sciences
Abstract
As people grow older skeletal muscle gradually becomes smaller and weaker. This progressive muscle weakness results in reduced mobility, independence and quality of life, and increased incidence of frailty-related falls and injury in ageing populations. A commonly observed feature that might contribute to age-related muscle decline is blunted growth responses to exercise training, and a likely impairment in muscular regeneration from individual bouts of activity. Whilst the mechanisms underpinning this phenomenon are poorly understood, failure of exercise-responsive molecular signals are logical candidates for investigation. However, many cross-talking signalling pathways are involved in the post-exercise remodelling process, and systematic evaluation of all associated regulatory molecules and their dysregulation in ageing muscle is not feasible in humans. This project will therefore employ an interdisciplinary approach to predict novel signalling networks regulating exercise-induced metabolic/functional adaptation, and examine the physiological role of these networks directly in ageing people during acute post-exercise muscle remodelling. Bioinformatic predictive modelling will be used to filter candidate network components involved in muscle adaptation to exercise. The relevance of these networks to ageing muscle decline will then be examined using state-of-the-art immunofluorescent imaging techniques, applied to human muscle biopsy samples collected during the acute post-exercise remodelling period. The dynamic temporo-spatial responses of putative regulators of muscle regeneration, overlaid onto the direct functional responses to exercise in humans, will provide new insight into the mechanisms underpinning exercise-mediated muscle adaptation and its deregulation during the ageing process.
Organisations
People |
ORCID iD |
Timothy Etheridge (Primary Supervisor) | |
Craig Willis (Student) |
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
BB/M009122/1 | 01/10/2015 | 31/03/2024 | |||
1771616 | Studentship | BB/M009122/1 | 01/10/2016 | 31/03/2021 | Craig Willis |
Description | The Physiological Society Travel Grant scheme |
Amount | £500 (GBP) |
Organisation | Physiological Society |
Sector | Charity/Non Profit |
Country | Global |
Start | 06/2019 |
End | 07/2019 |
Description | University of Exeter Institute of Data Science and Artificial Intelligence Travel Award |
Amount | £965 (GBP) |
Organisation | University of Exeter |
Sector | Academic/University |
Country | United Kingdom |
Start | 04/2019 |
End | 07/2019 |
Description | Pint of Science: Stimulating the Natural World (Sidmouth; October 2018) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Public/other audiences |
Results and Impact | The general research themes of this particular award were presented to members of the general public as part of a Pint of Science event centred around using mathematical and computational models to simulate biological systems ('Stimulating the Natural World') . In particular, the specific talk focussed on using gene networks to predict molecules that may be key to exercise-induced muscle adaptation in young and older adults, and which could subsequently hold promise as therapeutic targets for optimising exercise strategies to promote a healthy muscle mass across the lifespan (i.e. mitigating the decline in muscle mass that is a common feature of the ageing process). Notably, a large proportion of the audience present were older individuals and thus a primary target group for engagement with. This talk therefore sparked plenty of questions and discussion afterwards, along with interested for further information by some. |
Year(s) Of Engagement Activity | 2018 |
URL | https://pintofscience.co.uk/event/simulating-the-natural-world |