PROJECT SUMMARY
Despite the prevalence of advanced age as a risk factor for many diseases, its features are rarely replicated in
experimental modeling of these diseases. Mimicking elements of aging is particularly rare in the in vitro
context, even though in vitro approaches can offer a degree of tunability and control that enable pursuit of
unique mechanistic, biological questions. Many diseases also present with sexual dimorphism, wherein men
exhibit different disease characteristics than women. Again, this element of sex-specific behavior is rarely
examined in the in vitro environment.
In aortic valve stenosis (AVS), advanced age and male sex are the top two risk factors; AVS also exhibits
sexual dimorphism in its presentation. The only approved treatment for this prevalent disease is surgical valve
replacement, a shortfall that is, in large part, due to our relatively poor understanding of its pathogenesis and
progression. Current platforms are not set up to query why aging is the strongest risk factor for this disease, or
why men exhibit difference pathology than women. Thus, we propose to create in vitro tissue-engineered
models that incorporate both age-related and sex-specific features in order to elucidate mechanisms
responsible for the onset of AVS hallmarks.
Specifically, we will: 1) Characterize age-related changes in valve structure and hemodynamics and create
corresponding engineered environments, 2) Evaluate the roles of cellular aging vs. environment aging in
sensitizing the valve to pathological stimuli, and 3) Determine how age-related sex hormone changes (and
cellular memory thereof) influence the valvular response to pathological stimuli.
This study will yield multiple advancements, particularly with respect to in vitro modeling of aging and
pathologies, and identification of the most influential age-related features that guide the responsiveness of
valve tissues to pathological stimuli. Such work has the potential to identify specific age-related changes and
signaling pathways that may be targets for intervention strategies to reduce AVS risk.
