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An investigation into the physiological and genetic determinants of sarcopenia and the enhancing of current strategies for skeletal muscle screening
Author(s)
Date Issued
2022
Date Available
2022-12-07T17:14:59Z
Abstract
The age-related deterioration of muscle strength and mass, known as ‘sarcopenia’, is a major public health burden, due to its high and increasing prevalence and association with several adverse health outcomes. Although decades of research have been dedicated to understanding its aetiology and developing preventative strategies, sarcopenia effects >40% of those aged =80 years. Thus, there is a clear need to further elucidate the mechanistic pathways underlying sarcopenia, and to enhance current screening and treatment measures. To date, barriers associated with attaining accurate muscle measurements have impeded a proficient implementation of preservative and diagnostic strategies in clinical practice. Correspondingly, the potential benefits of a blood-based sarcopenia assessment, incorporating markers indicative of its aetiological underpinnings, have gained credence. In this regard, although the clinical manifestation of sarcopenia is multifaceted, recent data suggest neural processes to be of principal importance, and so exploring markers of neural integrity is particularly relevant. In addition to barriers associated with muscle quantification, the paucity of suitable, high-quality normative data for certain populations presents further impediments to the clinical interpretation of muscle health across the lifespan. Consequently, the potential for an accurate and timely identification of those at risk of, or with poor muscle health is greatly reduced. In this regard, although sarcopenia is diagnosed as the simultaneous presence of low muscle strength and mass, muscle strength is recognised as the cardinal diagnostic criterion, and so establishing muscle strength norms is particularly urgent. Accordingly, this thesis sought to: a) generate physiological and genetic data to illuminate the aetiological mechanisms underpinning sarcopenia development; b) identify promising blood-based markers that may enhance current screening strategies; and c) establish high-quality normative data and diagnostic thresholds for muscle strength. This thesis incorporated data from 9431 individuals aged 18-92 years (mean age: 44.8 ± 13.4 years; 57% females). Detailed phenotypic data (anthropometrics, body composition, muscle strength, cardiorespiratory fitness, blood sampling, health and lifestyle information) were collected for each participant, while plasma and genetic analyses were performed in subpopulations (n=300, aged 50-83 years; and n=6715, aged 18-83 years, respectively). Results confirmed the relevance of plasma C-terminal agrin fragment, a marker of neuromuscular junction (NMJ) stability, to sarcopenia, and illuminated novel associations between plasma neurofilament light chain, a marker of axonal integrity, and sarcopenia. Additional novel associations are highlighted between genes involved in regulating NMJ health (AGRN and PRSS12) and several phenotypes relevant to sarcopenia. Collectively, the physiological and genetic data provide strong evidence of the neural contribution to sarcopenia development, and suggest NMJ and axonal integrity to be of central importance. Finally, the normative data and diagnostic thresholds established in this thesis may help inform the clinical interpretation of muscle health across the entire adult age-span. Importantly, the diagnostic thresholds were proficient in identifying those with poor performance across a myriad of clinically relevant health domains, and suggest the cut-points currently in widespread use, may be too stringent.
Type of Material
Doctoral Thesis
Publisher
University College Dublin. School of Public Health, Physiotherapy and Sports Science
Qualification Name
Ph.D.
Copyright (Published Version)
2022 the Author
Language
English
Status of Item
Peer reviewed
This item is made available under a Creative Commons License
File(s)
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Name
7294601-1.pdf
Size
11.77 MB
Format
Adobe PDF
Checksum (MD5)
676954e3b8a51ded438ebc90466255a9
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