Date of Completion
Influenza, Aging, Skeletal Muscle, Vaccination, RNA-Sequencing
Field of Study
Doctor of Philosophy
The goal of this dissertation is to expand our understanding of how influenza (flu) infection negatively impacts skeletal muscle and leads to future disability with aging. We hypothesize that flu infection triggers prolonged inflammation and increased immune cell presence in skeletal muscle leading to skeletal muscle atrophy and impaired muscle function accompanied by diminished regenerative capacity in aged mice. We first determined that despite lack of direct flu infection, flu led to skeletal muscle atrophic gene expression and impaired muscle function which was prolonged and heightened in aged mice (Chapter 2). Next, we determined that muscle atrophy primarily occurs in MyHC type IIB muscle fibers (Chapter 3). This occurred concomitantly with disrupted architecture, fibrosis, and increased nuclei in aged muscle IHC staining. Importantly, protective immunity via vaccination mitigated these effects. These studies culminated into a hypothesis generating transcriptomic project, which has painted a fully unbiased look into aged muscle processes during flu infection (Chapter 4). Interestingly, these experiments point to an immune-mediated, primarily T cell, driven myopathy during flu infection in aged muscle. The studies in this thesis are the first to examine in depth how flu impacts skeletal muscle with aging and leads to muscle dysfunction and disability. While many questions remain, this research has laid the ground work for others to test pathways/genes as mechanism(s) of flu-induced muscle atrophy with aging as the first step of developing prevention and treatment options. Indeed, development of prophylactic and therapeutic treatments for flu-induced myopathies could save lives of countless older adults, prevent catastrophic disability, and increase overall resilience and healthspan.
Keilich, Spencer Ryan, "Influenza-induced Muscle Degradation: Mechanisms of Flu-induced Disability with Aging" (2020). Doctoral Dissertations. 2450.