Multiscale computational model predicts how environmental changes and treatments affect microvascular remodeling in fibrotic disease
Year: 2024
Type: article
Abstract: Investigating the molecular, cellular, and tissue-level changes caused by disease, and the effects of pharmacological treatments across these biological scales, necessitates the use of multiscale computational modeling in combination with experimentation. Many diseases dynamically alter the tissue microenvironment in ways that trigger microvascular network remodeling, which leads to the expansion or regression of microvessel networks. When microvessels undergo remodeling in idiopathic pulmonary fibrosis (IPF), functional gas exchange is impaired and lung function declines. We integrated a multiscale computational model with independent experiments to investigate how combinations of biomechanical and biochemical cues in IPF alter cell fate decisions leading to microvascular remodeling. Our computational model predicted that extracellular matrix (ECM) stiffening reduced microvessel area, which was accompanied by physical uncoupling of endothelial cell (EC) and pericytes, the cells that comprise microvessels. Nintedanib, an Food and Drug Administration-approved drug for treating IPF, was predicted to further potentiate microvessel regression by decreasing the percentage of quiescent pericytes while increasing the percentage of pericytes undergoing pericyte-myofibroblast transition in high ECM stiffnesses. Importantly, the model suggested that YAP/TAZ inhibition may overcome the deleterious effects of nintedanib by promoting EC-pericyte coupling and maintaining microvessel homeostasis. Overall, our combination of computational and experimental modeling can predict and explain how cell decisions affect tissue changes during disease and in response to treatments.
Source: PNAS Nexus
Institution: University of Virginia
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $4,202
Awards: Multi-scale, model-driven exploration of sub-generational gene expression in bacteria: individual consequences, population benefits, EAGER/Collaborative Research: High-throughput, Autonomous Real-time Monitoring of Tissue Mechanical Property Change via Impedimetric Sensor Arrays, Systems Pharmacology Model for Spatial Control of Cardiac Fibrosis, G575101006, G7014720030, Modeling to Design Treatments for Idiopathic Lung Fibrosis, G9000154035, Basic Cardiovascular Research Training Grant, Interdisciplinary Training in Systems & Biomolecular Data Science
OpenAlex ID: W4405222615
