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Computational model predicts paracrine and intracellular drivers of fibroblast phenotype after myocardial infarction.

ABSTRACT: The fibroblast is a key mediator of wound healing in the heart and other organs, yet how it integrates multiple time-dependent paracrine signals to control extracellular matrix synthesis has been difficult to study in vivo. Here, we extended a computational model to simulate the dynamics of fibroblast signaling and fibrosis after myocardial infarction (MI) in response to time-dependent data for nine paracrine stimuli. This computational model was validated against dynamic collagen expression and collagen area fraction data from post-infarction rat hearts. The model predicted that while many features of the fibroblast phenotype at inflammatory or maturation phases of healing could be recapitulated by single static paracrine stimuli (interleukin-1 and angiotensin-II, respectively), mimicking the reparative phase required paired stimuli (e.g. TGFβ and endothelin-1). Virtual overexpression screens simulated with either static cytokine pairs or post-MI paracrine dynamic predicted phase-specific regulators of collagen expression. Several regulators increased (Smad3) or decreased (Smad7, protein kinase G) collagen expression specifically in the reparative phase. NADPH oxidase (NOX) overexpression sustained collagen expression from reparative to maturation phases, driven by TGFβ and endothelin positive feedback loops. Interleukin-1 overexpression had mixed effects, both enhancing collagen via the TGFβ positive feedback loop and suppressing collagen via NFκB and BAMBI (BMP and activin membrane-bound inhibitor) incoherent feed-forward loops. These model-based predictions reveal network mechanisms by which the dynamics of paracrine stimuli and interacting signaling pathways drive the progression of fibroblast phenotypes and fibrosis after myocardial infarction.

SUBMITTER: Zeigler AC

PROVIDER: S-EPMC7434705 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Both skin wound healing and the cardiac response to myocardial infarction (MI) progress through similar pathways involving inflammation, resolution, tissue repair, and scar formation. Due to the similarities, we hypothesized that the healing response to skin wounding would predict future response to MI. Mice were given a 3-mm skin wound using a disposable biopsy punch and the skin wound was imaged daily until closure. The same set of animals was given MI by permanent coronary artery ligation 28 days later and followed for 7 days. Cardiac physiology was measured by echocardiography at baseline and MI days 3 and 7. Animals that survived until day 7 were grouped as survivors, and animals that died from MI were grouped as nonsurvivors. Survivors had faster skin wound healing than nonsurvivors. Faster skin wound healing predicted MI survival better than commonly used cardiac functional variables (e.g., infarct size, fractional shortening, and end diastolic dimension). N-glycoproteome profiling of MI day 3 plasma revealed α2-macroglobulin and ELL-associated factor 1 as strong predictors of future MI death and progression to heart failure. A second cohort of MI mice validated these findings. To investigate the clinical relevance of α2-macroglobulin, we mapped the plasma glycoproteome in patients with MI 48 h after admission and in healthy controls. In patients, α2-macroglobulin was increased 48 h after MI. Apolipoprotein D, another plasma glycoprotein, detrimentally regulated both skin and cardiac wound healing in male but not female mice by promoting inflammation. Our results reveal that the skin is a mirror to the heart and common pathways link wound healing across organs.NEW & NOTEWORTHY Faster skin wound healers had more efficient cardiac healing after myocardial infarction (MI). Two plasma proteins at D3 MI, EAF1 and A2M, predicted MI death in 66% of cases. ApoD regulated both skin and cardiac wound healing in male mice by promoting inflammation. The skin was a mirror to the heart and common pathways linked wound healing across organs.

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Computational model predicts paracrine and intracellular drivers of fibroblast phenotype after myocardial infarction.

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