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Systems Biology of Fibroblast Activation Following Myocardial Infarction

心肌梗塞后成纤维细胞激活的系统生物学

基本信息

批准号：
9463789
负责人：
MERRY L LINDSEY
金额：
$ 38.13万
依托单位：
UNIVERSITY OF MISSISSIPPI MED CTR
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-05-01 至 2019-01-18
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9463789
关键词：
American Cardiac Cell model Cell physiology Cells Cicatrix Classification Collagen Computer Simulation Congestive Heart Failure Coupled Data Development Diagnosis Evolution Extracellular Matrix Extracellular Matrix Proteins Fibroblasts Fibronectins Flow Cytometry Foundations Goals Grant Growth Factor Heart Heart Rate Heart failure In Vitro Infarction Inflammation Inflammatory Integrins Interleukin-1 Knowledge Left Ventricular Remodeling Left ventricular structure Leukocytes Matrix Metalloproteinases Mediator of activation protein Modeling Molecular Myocardial Infarction Myofibroblast Outcome Outcome Study Output Patients Pattern Phase Phenotype Production Regulation Role Running Series Signal Pathway Signal Transduction Stimulus Structure System Systems Biology TGFB1 gene Testing Therapeutic Thrombospondins Time Transforming Growth Factor beta Wound Healing base cardiogenesis cell type chemokine computerized tools cytokine experimental study glycoproteomics healing high risk improved outcome in vivo innovation mathematical model mortality new therapeutic target next generation sequencing periostin predicting response predictive marker predictive modeling prevent public health relevance response simulation therapy development transcriptomics

项目摘要

DESCRIPTION (provided by applicant): About one in four myocardial infarction (MI) patients progress to develop congestive heart failure, which has a 50% 5-year mortality rate. The goal of this project is to understand post-MI roles of the fibroblast by establishing and validating an in silico computational model of the temporal evolution of fibroblast activation. Our preliminary results demonstrate that fibroblasts proceed through a series of activation profiles over the first 28 days post-MI and that modifying fibroblast responses can alter remodeling of the left ventricle (LV). We hypothesize that fibroblasts undergo a temporal phenotype evolution to coordinate the post-MI LV remodeling phenotype. Our specific aims are: 1) construct an in silico computational model that simulates fibroblast activation patterns over the post-MI time course; 2) Perturb endogenous cytokine and growth factor signaling pathways to evaluate the system and optimize model robustness.; and 3) Examine endogenous ECM influences to evaluate model predictability. The innovation of this proposal lies in both the concept that fibroblasts regulate remodeling as a continuum of phenotypes and that integration of experimental and computational approaches will allow us to establish a predictive computational tool. The potential outcome of these studies will be 1) the development of a computational tool to simulate fibroblast activation post-MI; 2) the identification of fibroblast activation markers that predict V remodeling outcomes; and 3) recognition of key fibrotic mechanisms that can be therapeutically modulated to regulate fibroblast activation.