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J Mol Cell Cardiol. 2016 Apr;93:73-83. doi: 10.1016/j.yjmcc.2015.11.020. Epub 2015 Dec 1.

Computational modeling of cardiac fibroblasts and fibrosis.

Author information

1
University of Virginia, Biomedical Engineering Department, 415 Lane Road, Charlottesville, VA 22903, USA. Electronic address: acz4nr@virginia.edu.
2
University of Virginia, Biomedical Engineering Department, 415 Lane Road, Charlottesville, VA 22903, USA. Electronic address: wjr2n@virginia.edu.
3
University of Virginia, Biomedical Engineering Department, 415 Lane Road, Charlottesville, VA 22903, USA. Electronic address: holmes@virginia.edu.
4
University of Virginia, Biomedical Engineering Department, 415 Lane Road, Charlottesville, VA 22903, USA. Electronic address: jjs3g@virginia.edu.

Abstract

Altered fibroblast behavior can lead to pathologic changes in the heart such as arrhythmia, diastolic dysfunction, and systolic dysfunction. Computational models are increasingly used as a tool to identify potential mechanisms driving a phenotype or potential therapeutic targets against an unwanted phenotype. Here we review how computational models incorporating cardiac fibroblasts have clarified the role for these cells in electrical conduction and tissue remodeling in the heart. Models of fibroblast signaling networks have primarily focused on fibroblast cell lines or fibroblasts from other tissues rather than cardiac fibroblasts, specifically, but they are useful for understanding how fundamental signaling pathways control fibroblast phenotype. In the future, modeling cardiac fibroblast signaling, incorporating -omics and drug-interaction data into signaling network models, and utilizing multi-scale models will improve the ability of in silico studies to predict potential therapeutic targets against adverse cardiac fibroblast activity.

KEYWORDS:

Cardiac fibroblast; Computational modeling; Fibrosis; Systems biology

PMID:
26608708
PMCID:
PMC4846515
DOI:
10.1016/j.yjmcc.2015.11.020
[Indexed for MEDLINE]
Free PMC Article

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