# Dynamic Modeling of Mechanotransduction in the Bicuspid Aortic Valve: Separating the Effects of Altered VICs and Mechanics

> **NIH NIH F32** · UNIVERSITY OF TEXAS AT AUSTIN · 2021 · $70,458

## Abstract

The bicuspid aortic valve (BAV) anomaly is characterized by the presence of two (rather than three) leaflets and
is the most common congenital heart anomaly, affecting~ 1.4% of the population. It is estimated that ~30-50%
of individuals with BAV will require surgical intervention for aortic stenosis and a BAV is present in virtually all
aortic valve replacement patients under age 50. The presence of a BAV in asymptomatic, young patients is often
detected early due to widespread availability and routine use of screening echocardiography. However, early
diagnosis only leads to closer monitoring as there are no pharmaceutical interventions for delaying/preventing
disease progression in the BAV. The rational design of pharmaceutical interventions warrants a more complete
understanding of the underlying cellular processes responsible for disease progression in the BAV. The resident
valve interstitial cells (VICs) are responsible for maintaining the mechanical environment of the heart valves,
primarily through synthesis and remodeling of the extracellular matrix (ECM). Altered ECM content and organization
has been documented prior to calcification in the BAV; thus, valve degeneration is a potential risk
factor for the eventual development of AS in the BAV. However, the complex mechanotransduction networks
responsible for VIC activation and subsequent pathological ECM synthesis/remodeling has made it difficult
to determine the systems-level properties underlying the progression to symptomatic disease through purely
experimental means. We hypothesize that VICs from BAVs are more sensitive to increases in mechanical stiffness
than their tricuspid aortic valve (TAV) counterparts and the altered mechanics of the BAV exacerbates these
altered mechanotransduction cascades. However, separating the effects of the altered mechanical environment
from intrinsic VIC differences in the presence of intimate feedback loops requires a systems-level experimental/
computational approach. Thus, we propose to integrate proteomcis data with the first computational model
of VIC cell signaling to address this research question. In Aim 1, the altered signaling networks in diseased
human BAVs and TAVs extracted during for aortic valve replacement will be compared via quantitative proteomics
with normal TAVs. In Aim 2, human VICs will be extracted from BAVs and TAVs, cultured on mechanoresponsive
hydrogels, and assessed via protoemics and confocal microscopy. This data will be integrated with
computational models of mechanotransduction to evaluate key differences in the mechanotransduction cascade
between BAV- and TAV-derived VICs and predict the effects of perturbing key components of Bav- and TAV-mechanotransduction.
In Aim 3, BAV- and TAV-derived mechanical waveforms will be used to stimulate VICs
on a high throuput mechanobiology screening platform to evaluate the effects of altered mechanical loads on
BAV- and TAV-mechanotransduction. Successful completion of this proposed ...

## Key facts

- **NIH application ID:** 10328481
- **Project number:** 5F32HL149210-02
- **Recipient organization:** UNIVERSITY OF TEXAS AT AUSTIN
- **Principal Investigator:** Daniel Paul Howsmon
- **Activity code:** F32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $70,458
- **Award type:** 5
- **Project period:** 2020-09-01 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10328481

## Citation

> US National Institutes of Health, RePORTER application 10328481, Dynamic Modeling of Mechanotransduction in the Bicuspid Aortic Valve: Separating the Effects of Altered VICs and Mechanics (5F32HL149210-02). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/10328481. Licensed CC0.

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