Multiscale Computational Tool to Reduce the Prevalence of Age-Related Tendinopathy by Resolving the Key Mechanisms of Tendon Dynamics Project Summary The long term goal of this work is to alter the clinical paradigm for age-related tendinopathy and to rationally design strategies to impede degeneration and improve healing by identifying the key mechanisms of tendon dynamics before and after injury. Age-related tendinopathy is a physically debilitating and painful disorder wherein tendon structural integrity and mechanical performance decline, increasing the risk of rupture. Existing treatments often fail to restore tendon strength and functionality, contributing to significant healthcare costs and negatively impacting quality of life for up to one in three adults over fifty. Nevertheless, the key mechanisms of age-related tendon changes and healing deficiencies are not well-understood. We seek to determine the key mechanisms of tendon dynamics to effectively focus clinical intervention. To accomplish this we propose to leverage a computational tool, informed and validated by experimental data in the murine patellar tendon, to identify the key mechanisms that diminish the preservation and restoration of dynamic homeostasis with age. Our central hypothesis is that tendon cells respond to daily motions by producing or removing load-bearing tendon components to maintain a homeostatic state. Further, we hypothesize that age-related disruptions to the balance of the production and removal of these components increase susceptibility to degeneration and/or tears by decreasing mechanical performance and healing potential.
In Aim 1 of this proposal, we will evaluate the age-specific sensitivity of tendon mechanical homeostasis to different declining production mechanisms.
In Aim 2, we will determine the age-specific bounds of tendon growth potential by evaluating the effect of altered mechanical loading on homeostasis.
In Aim 3, we will delineate the age-specific tendon component adaptations which hinder the restoration of mechanical homeostasis following injury. Successful completion of this study will provide a fundamental understanding of the critical mechanisms of tendon dynamics with increasing age. Further, it will provide a vital step towards the development of predictive computational models to aid in the rational design of patient-specific treatment plans and interventions, improving the clinical care of age-related tendinopathy.
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