Combining experimental and mathematical modeling to reveal mechanisms of macrophage-dependent left ventricular remodeling

Modelling the Effect of Matrix Metalloproteinases in Dermal Wound Healing

With over 2 million people in the UK suffering from chronic wounds, understanding the biochemistry and pharmacology that underpins these wounds and wound healing is of high importance. Chronic wounds are characterised by high levels of matrix metalloproteinases (MMPs), which are necessary for the modification of healthy tissue in the healing process. Overexposure of MMPs, however, adversely affects healing of the wound by causing further destruction of the surrounding extracellular matrix. In this work, we propose a mathematical model that focuses on the interaction of MMPs with dermal cells using a system of partial differential equations. Using biologically realistic parameter values, this model gives rise to travelling waves corresponding to a front of healthy cells invading a wound. From the arising travelling wave analysis, we observe that deregulated apoptosis results in the emergence of chronic wounds, characterised by elevated MMP concentrations. We also observe hysteresis effects when both the apoptotic rate and MMP production rate are varied, providing further insight into the management (and potential reversal) of chronic wounds.

The Microenvironment of the Pathogenesis of Cardiac Hypertrophy

Pathological cardiac hypertrophy is a key risk factor for the development of heart failure and predisposes individuals to cardiac arrhythmia and sudden death. While physiological cardiac hypertrophy is adaptive, hypertrophy resulting from conditions comprising hypertension, aortic stenosis, or genetic mutations, such as hypertrophic cardiomyopathy, is maladaptive. Here, we highlight the essential role and reciprocal interactions involving both cardiomyocytes and non-myocardial cells in response to pathological conditions. Prolonged cardiovascular stress causes cardiomyocytes and non-myocardial cells to enter an activated state releasing numerous pro-hypertrophic, pro-fibrotic, and pro-inflammatory mediators such as vasoactive hormones, growth factors, and cytokines, i.e., commencing signaling events that collectively cause cardiac hypertrophy. Fibrotic remodeling is mediated by cardiac fibroblasts as the central players, but also endothelial cells and resident and infiltrating immune cells enhance these processes. Many of these hypertrophic mediators are now being integrated into computational models that provide system-level insights and will help to translate our knowledge into new pharmacological targets. This perspective article summarizes the last decades' advances in cardiac hypertrophy research and discusses the herein-involved complex myocardial microenvironment and signaling components.

Intercellular model predicts mechanisms of inflammation-fibrosis coupling after myocardial infarction

After myocardial infarction (MI), cardiac cells work together to regulate wound healing of the infarct. The pathological response to MI yields cardiac remodelling comprising inflammatory and fibrosis phases, and the interplay of cellular dynamics that underlies these phases has not been elucidated. This study developed a computational model to identify cytokine and cellular dynamics post-MI to predict mechanisms driving post-MI inflammation, resolution of inflammation, and scar formation. Additionally, this study evaluated the interdependence between inflammation and fibrosis. Our model bypassed limitations of in vivo approaches in achieving cellular specificity and performing specific perturbations such as global knockouts of chemical factors. The model predicted that inflammation is a graded response to initial infarct size that is amplified by a positive feedback loop between neutrophils and interleukin 1β (IL-1β). Resolution of inflammation was driven by degradation of IL-1β, matrix metalloproteinase 9, and transforming growth factor β (TGF-β), as well as apoptosis of neutrophils. Inflammation regulated TGFβ secretion directly through immune cell recruitment and indirectly through upregulation of macrophage phagocytosis. Lastly, we found that mature collagen deposition was an ultrasensitive switch in response to inflammation, which was amplified primarily by cardiac fibroblast proliferation. These findings describe the relationship between inflammation and fibrosis and highlight how the two responses work together post-MI. This model revealed that post-MI inflammation and fibrosis are dynamically coupled, which provides rationale for designing novel anti-inflammatory, pro-resolving or anti-fibrotic therapies that may improve the response to MI. KEY POINTS: Inflammation and matrix remodelling are two processes involved in wound healing after a heart attack. Cardiac cells work together to facilitate these processes; this is done by secreting cytokines that then regulate the cells themselves or other cells surrounding them. This study developed a computational model of the dynamics of cardiac cells and cytokines to predict mechanisms through which inflammation and matrix remodelling is regulated. We show the roles of various cytokines and signalling motifs in driving inflammation, resolution of inflammation and fibrosis. The novel concept of inflammation-fibrosis coupling, based on the model prediction that inflammation and fibrosis are dynamically coupled, provides rationale for future studies and for designing therapeutics to improve the response after a heart attack.

Organized Chaos: Deciphering Immune Cell Heterogeneity's Role in Inflammation in the Heart

During homeostasis, immune cells perform daily housekeeping functions to maintain heart health by acting as sentinels for tissue damage and foreign particles. Resident immune cells compose 5% of the cellular population in healthy human ventricular tissue. In response to injury, there is an increase in inflammation within the heart due to the influx of immune cells. Some of the most common immune cells recruited to the heart are macrophages, dendritic cells, neutrophils, and T-cells. In this review, we will discuss what is known about cardiac immune cell heterogeneity during homeostasis, how these cell populations change in response to a pathology such as myocardial infarction or pressure overload, and what stimuli are regulating these processes. In addition, we will summarize technologies used to evaluate cell heterogeneity in models of cardiovascular disease.

Iterative community-driven development of a SARS-CoV-2 tissue simulator

The 2019 novel coronavirus, SARS-CoV-2, is a pathogen of critical significance to international public health. Knowledge of the interplay between molecular-scale virus-receptor interactions, single-cell viral replication, intracellular-scale viral transport, and emergent tissue-scale viral propagation is limited. Moreover, little is known about immune system-virus-tissue interactions and how these can result in low-level (asymptomatic) infections in some cases and acute respiratory distress syndrome (ARDS) in others, particularly with respect to presentation in different age groups or pre-existing inflammatory risk factors. Given the nonlinear interactions within and among each of these processes, multiscale simulation models can shed light on the emergent dynamics that lead to divergent outcomes, identify actionable "choke points" for pharmacologic interventions, screen potential therapies, and identify potential biomarkers that differentiate patient outcomes. Given the complexity of the problem and the acute need for an actionable model to guide therapy discovery and optimization, we introduce and iteratively refine a prototype of a multiscale model of SARS-CoV-2 dynamics in lung tissue. The first prototype model was built and shared internationally as open source code and an online interactive model in under 12 hours, and community domain expertise is driving regular refinements. In a sustained community effort, this consortium is integrating data and expertise across virology, immunology, mathematical biology, quantitative systems physiology, cloud and high performance computing, and other domains to accelerate our response to this critical threat to international health. More broadly, this effort is creating a reusable, modular framework for studying viral replication and immune response in tissues, which can also potentially be adapted to related problems in immunology and immunotherapy.

Using models to advance medicine: mathematical modeling of post-myocardial infarction left ventricular remodeling

The heart is an organ with limited capacity for regeneration and repair. The irreversible cell death and corresponding diminished ability of the heart to repair after myocardial infarction (MI), is a leading cause of morbidity and mortality worldwide. In this paper, a new mathematical model is presented to study the left ventricular (LV) remodeling and associated events after MI. The model accurately describes and predicts the interactions among heart cells and the immune system post-MI in the absence of medical interventions. The resulting system of nonlinear ordinary differential equations is studied both analytically and numerically in order to demonstrate the functionality and performance of the new model. To the best of our knowledge, this model is the only one of its kind to consider and correctly apply all of the known factors in diseased heart LV modeling. This model has the potential to provide researchers with a predictive computational tool to better understand the MI pathology and develop various cell-based treatment options, with benefits of lowering the cost and reducing the development time.

A computational bio-chemo-mechanical model of in vivo tissue-engineered vascular graft development

Stenosis is the primary complication of current tissue-engineered vascular grafts used in pediatric congenital cardiac surgery. Murine models provide considerable insight into the possible mechanisms underlying this situation, but they are not efficient for identifying optimal changes in scaffold design or therapeutic strategies to prevent narrowing. In contrast, computational modeling promises to enable time- and cost-efficient examinations of factors leading to narrowing. Whereas past models have been limited by their phenomenological basis, we present a new mechanistic model that integrates molecular- and cellular-driven immuno- and mechano-mediated contributions to in vivo neotissue development within implanted polymeric scaffolds. Model parameters are inferred directly from in vivo measurements for an inferior vena cava interposition graft model in the mouse that are augmented by data from the literature. By complementing Bayesian estimation with identifiability analysis and simplex optimization, we found optimal parameter values that match model outputs with experimental targets and quantify variability due to measurement uncertainty. Utility is illustrated by parametrically exploring possible graft narrowing as a function of scaffold pore size, macrophage activity, and the immunomodulatory cytokine transforming growth factor beta 1 (TGF-β1). The model captures salient temporal profiles of infiltrating immune and synthetic cells and associated secretion of cytokines, proteases, and matrix constituents throughout neovessel evolution, and parametric studies suggest that modulating scaffold immunogenicity with early immunomodulatory therapies may reduce graft narrowing without compromising compliance.

Infarct in the Heart: What's MMP-9 Got to Do with It?

Over the past three decades, numerous studies have shown a strong connection between matrix metalloproteinase 9 (MMP-9) levels and myocardial infarction (MI) mortality and left ventricle remodeling and dysfunction. Despite this fact, clinical trials using MMP-9 inhibitors have been disappointing. This review focuses on the roles of MMP-9 in MI wound healing. Infiltrating leukocytes, cardiomyocytes, fibroblasts, and endothelial cells secrete MMP-9 during all phases of cardiac repair. MMP-9 both exacerbates the inflammatory response and aids in inflammation resolution by stimulating the pro-inflammatory to reparative cell transition. In addition, MMP-9 has a dual effect on neovascularization and prevents an overly stiff scar. Here, we review the complex role of MMP-9 in cardiac wound healing, and highlight the importance of targeting MMP-9 only for its detrimental actions. Therefore, delineating signaling pathways downstream of MMP-9 is critical.

Immune regulation of cardiac fibrosis post myocardial infarction

Pathological changes resulting from myocardial infarction (MI) include extracellular matrix alterations of the left ventricle, which can lead to cardiac stiffness and impair systolic and diastolic function. The signals released from necrotic tissue initiate the immune cascade, triggering an extensive inflammatory response followed by reparative fibrosis of the infarct area. Immune cells such as neutrophils, monocytes, macrophages, mast cells, T-cells, and dendritic cells play distinct roles in orchestrating this complex pathological condition, and regulate the balance between pro-fibrotic and anti-fibrotic responses. This review discusses how molecular signals between fibroblasts and immune cells mutually regulate fibrosis post-MI, and outlines the emerging pharmacological targets and therapies for modulating inflammation and cardiac fibrosis associated with MI.

Human fibroblast-macrophage tissue spheroids demonstrate ratio-dependent fibrotic activity for in vitro fibrogenesis model development

Fibrosis is a pathological accumulation of excessive collagen that underlies many of the most common diseases, representing dysfunction of the essential processes of normal tissue healing. Fibrosis research aims to limit this response without ameliorating the essential role of fibrogenesis in organ function. However, the absence of a realistic in vitro model has hindered investigation into mechanisms and potential interventions because the standard 2D monolayer culture of fibroblasts has limited applicability. We sought to develop and optimize fibrosis spheroids: a scaffold-free three-dimensional human fibroblast-macrophage spheroid system representing an improved benchtop model of human fibrosis. We created, characterized and optimized human fibroblast-only spheroids, demonstrating increased collagen deposition compared to monolayer fibroblasts, while spheroids larger than 300 μm suffered from progressively increasing apoptosis. Next, we improved the spheroid system with the addition of human macrophages to more precisely recapitulate the environment during fibrogenesis, creating a hybrid spheroid system with different ratios of fibroblasts and macrophages ranging from 2 : 1 to 64 : 1. We found that in the hybrid spheroids (particularly the 16 : 1 [F16] ratio) more fibroblasts were activated, with greater macrophage polarization towards a pro-inflammatory M1 phenotype. Hybrid spheroids containing higher ratios of macrophages showed greater macrophage heterogeneity and less fibrogenesis, while low macrophage ratios limited macrophage-induced effects and yielded less collagen deposition. The F16 group also had the highest expression levels of fibrosis-related genes (Col-1a1, Col-3a1 and TGF-β) and inflammation-related genes (TNF, IL1β and IL6). IF staining demonstrated that F16 spheroids had the highest levels of αSMA, collagen-1 and collagen-3 deposition among all groups as well as formation of a dense collagen rim surrounding the spheroid. Future studies exploring the greater fibrotic activity of F16 spheroids may provide new mechanistic insights into diseases involving excessive fibrotic activity. Microtissue fibrosis models capable of achieving greater clinical fidelity have the potential to combine the relevance of animal models with the scale, cost and throughput of in vitro testing.

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

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.

Biomechanics of infarcted left ventricle: a review of modelling

Mathematical modelling in biomechanics of infarcted left ventricle (LV) serves as an indispensable tool for remodelling mechanism exploration, LV biomechanical property estimation and therapy assessment after myocardial infarction (MI). However, a review of mathematical modelling after MI has not been seen in the literature so far. In the paper, a systematic review of mathematical models in biomechanics of infarcted LV was established. The models include comprehensive cardiovascular system model, essential LV pressure-volume and stress-stretch models, constitutive laws for passive myocardium and scars, tension models for active myocardium, collagen fibre orientation optimization models, fibroblast and collagen fibre growth/degradation models and integrated growth-electro-mechanical model after MI. The primary idea, unique characteristics and key equations of each model were identified and extracted. Discussions on the models were provided and followed research issues on them were addressed. Considerable improvements in the cardiovascular system model, LV aneurysm model, coupled agent-based models and integrated electro-mechanical-growth LV model are encouraged. Substantial attention should be paid to new constitutive laws with respect to stress-stretch curve and strain energy function for infarcted passive myocardium, collagen fibre orientation optimization in scar, cardiac rupture and tissue damage and viscoelastic effect post-MI in the future.

Multiscale Coupling of an Agent-Based Model of Tissue Fibrosis and a Logic-Based Model of Intracellular Signaling

Wound healing and fibrosis following myocardial infarction (MI) is a dynamic process involving many cell types, extracellular matrix (ECM), and inflammatory cues. As both incidence and survival rates for MI increase, management of post-MI recovery and associated complications are an increasingly important focus. Complexity of the wound healing process and the need for improved therapeutics necessitate a better understanding of the biochemical cues that drive fibrosis. To study the progression of cardiac fibrosis across spatial and temporal scales, we developed a novel hybrid multiscale model that couples a logic-based differential equation (LDE) model of the fibroblast intracellular signaling network with an agent-based model (ABM) of multi-cellular tissue remodeling. The ABM computes information about cytokine and growth factor levels in the environment including TGFβ, TNFα, IL-1β, and IL-6, which are passed as inputs to the LDE model. The LDE model then computes the network signaling state of individual cardiac fibroblasts within the ABM. Based on the current network state, fibroblasts make decisions regarding cytokine secretion and deposition and degradation of collagen. Simulated fibroblasts respond dynamically to rapidly changing extracellular environments and contribute to spatial heterogeneity in model predicted fibrosis, which is governed by many parameters including cell density, cell migration speeds, and cytokine levels. Verification tests confirmed that predictions of the coupled model and network model alone were consistent in response to constant cytokine inputs and furthermore, a subset of coupled model predictions were validated with in vitro experiments with human cardiac fibroblasts. This multiscale framework for cardiac fibrosis will allow for systematic screening of the effects of molecular perturbations in fibroblast signaling on tissue-scale extracellular matrix composition and organization.

Agent-based modeling and bifurcation analysis reveal mechanisms of macrophage polarization and phenotype pattern distribution

Macrophages play a key role in tissue regeneration by polarizing to different destinies and generating various phenotypes. Recognizing the underlying mechanisms is critical in designing therapeutic procedures targeting macrophage fate determination. Here, to investigate the macrophage polarization, a nonlinear mathematical model is proposed in which the effect of IL4, IFNγ and LPS, as external stimuli, on STAT1, STAT6, and NFκB is studied using bifurcation analysis. The existence of saddle-node bifurcations in these internal key regulators allows different combinations of steady state levels which are attributable to different fates. Therefore, we propose dynamic bifurcation as a crucial built-in mechanism of macrophage polarization. Next, in order to investigate the polarization of a population of macrophages, bifurcation analysis is employed aligned with agent-based approach and a two-layer model is proposed in which the information from single cells is exploited to model the behavior in tissue level. Also, in this model, a partial differential equation describes the diffusion of secreted cytokines in the medium. Finally, the model was validated against a set of experimental data. Taken together, we have here developed a cell and tissue level model of macrophage polarization behavior which can be used for designing therapeutic interventions.

Coupled Immunological and Biomechanical Model of Emphysema Progression

Chronic Obstructive Pulmonary Disease (COPD) is a disabling respiratory pathology, with a high prevalence and a significant economic and social cost. It is characterized by different clinical phenotypes with different risk profiles. Detecting the correct phenotype, especially for the emphysema subtype, and predicting the risk of major exacerbations are key elements in order to deliver more effective treatments. However, emphysema onset and progression are influenced by a complex interaction between the immune system and the mechanical properties of biological tissue. The former causes chronic inflammation and tissue remodeling. The latter influences the effective resistance or appropriate mechanical response of the lung tissue to repeated breathing cycles. In this work we present a multi-scale model of both aspects, coupling Finite Element (FE) and Agent Based (AB) techniques that we would like to use to predict the onset and progression of emphysema in patients. The AB part is based on existing biological models of inflammation and immunological response as a set of coupled non-linear differential equations. The FE part simulates the biomechanical effects of repeated strain on the biological tissue. We devise a strategy to couple the discrete biological model at the molecular /cellular level and the biomechanical finite element simulations at the tissue level. We tested our implementation on a public emphysema image database and found that it can indeed simulate the evolution of clinical image biomarkers during disease progression.

Proteomic analysis of the cardiac extracellular matrix: clinical research applications

INTRODUCTION

The cardiac extracellular matrix (ECM) provides anatomical, biochemical, and physiological support to the left ventricle. ECM proteins are difficult to detect using unbiased proteomic approaches due to solubility issues and a relatively low abundance compared to cytoplasmic and mitochondrial proteins present in highly prevalent cardiomyocytes. Areas covered: Proteomic capabilities have dramatically improved over the past 20 years, due to enhanced sample preparation protocols and increased capabilities in mass spectrometry (MS), database searching, and bioinformatics analysis. This review summarizes technological advancements made in proteomic applications that make ECM proteomics highly feasible. Expert commentary: Proteomic analysis of the ECM provides an important contribution to our understanding of the molecular and cellular processes associated with cardiovascular disease. Using results generated from proteomics approaches in basic science applications and integrating proteomics templates into clinical research protocols will aid in efforts to personalize medicine.

Cardiac macrophage biology in the steady-state heart, the aging heart, and following myocardial infarction

Macrophages play critical roles in homeostatic maintenance of the myocardium under normal conditions and in tissue repair after injury. In the steady-state heart, resident cardiac macrophages remove senescent and dying cells and facilitate electrical conduction. In the aging heart, the shift in macrophage phenotype to a proinflammatory subtype leads to inflammaging. Following myocardial infarction (MI), macrophages recruited to the infarct produce both proinflammatory and anti-inflammatory mediators (cytokines, chemokines, matrix metalloproteinases, and growth factors), phagocytize dead cells, and promote angiogenesis and scar formation. These diverse properties are attributed to distinct macrophage subtypes and polarization status. Infarct macrophages exhibit a proinflammatory M1 phenotype early and become polarized toward an anti-inflammatory M2 phenotype later post-MI. Although this classification system is oversimplified and needs to be refined to accommodate the multiple different macrophage subtypes that have been recently identified, general concepts on macrophage roles are independent of subtype classification. This review summarizes current knowledge about cardiac macrophage origins, roles, and phenotypes in the steady state, with aging, and after MI, as well as highlights outstanding areas of investigation.

Extracellular Matrix for Myocardial Repair

Multiple strategies have been investigated to restore functional myocardium following injury or disease including the local administration of cytokines or chemokines, stem/progenitor cell therapy, mechanical circulatory support, pharmacologic use, and the use of inductive biomaterials. The use of xenogeneic biologic scaffolds composed of extracellular matrix (ECM) has been shown to facilitate functional restoration of several tissues and organs including the esophagus, skeletal muscle, skin, and myocardium, among others. The present chapter describes the current understanding of specific components of biologic scaffolds composed of ECM, the mechanisms by which ECM bioscaffolds promote constructive cardiac remodeling after injury, determinants of remodeling outcome, and the versatility of ECM as a potential cardiac therapeutic.

Platelet-Specific p38α Deficiency Improved Cardiac Function After Myocardial Infarction in Mice

OBJECTIVE

MAPKs (mitogen-activated protein kinases), especially p38, play detrimental roles in cardiac diseases and cardiac remodeling post-myocardial infarction. However, the activation and function of MAPKs in coronary thrombosis in vivo and its relationship with clinical outcomes remain poorly understood.

APPROACH AND RESULTS

Here, we showed that p38α was the major isoform expressed in human and mouse platelets. Platelet-specific p38α-deficient mice presented impaired thrombosis and hemostasis but had improved cardiac function, reduced infarct size, decreased inflammatory response, and microthrombus in a left anterior descending artery ligation model. Signaling analysis revealed that p38 activation was one of the earliest events in platelets after treatment with receptor agonists or reactive oxygen species. p38α/MAPK-activated protein kinase 2/heat shock protein 27 and p38α/cytosolic phospholipases A2 were the major pathways regulating receptor-mediated or hydrogen peroxide-induced platelet activation in an ischemic environment. Moreover, the distinct roles of ERK1/2 (extracellular signal-regulated kinase) in receptor- or reactive oxygen species-induced p38-mediated platelet activation reflected the complicated synergistic relationships among MAPKs. Analysis of clinical samples revealed that MAPKs were highly phosphorylated in platelets from preoperative patients with ST-segment-elevation myocardial infarction, and increased phosphorylation of p38 was associated with no-reflow outcomes.

CONCLUSIONS

We conclude that p38α serves as a critical regulator of platelet activation and potential indicator of highly thrombotic lesions and no-reflow, and inhibition of platelet p38α may improve clinical outcomes in subjects with ST-segment-elevation myocardial infarction.

Knowledge gaps to understanding cardiac macrophage polarization following myocardial infarction

Following myocardial infarction (MI), macrophages coordinate both pro-inflammatory and reparative responses of the left ventricle (LV) by reacting to and secreting cytokines, chemokines, and growth factors and by stimulating endothelial cells and fibroblasts to modulate neovascularization and scar formation. Healing of the infarcted LV can be divided into three distinct, but overlapping phases: inflammatory, proliferative, and maturation. Macrophages are involved in all phases. Despite macrophages being a major leukocyte cell type in the post-MI LV, how this cell type regulates LV remodeling over the post-MI time continuum is not completely understood. In this review, we summarize the current literature as a foundation to discuss the major knowledge gaps that remain. Defining the post-MI temporal macrophage phenotypes to establish a classification system is the first step in exploring how macrophage phenotypes are regulated, how temporal stimulation and secretion profiles evolve, and how best to modify stimuli to yield predictable cell responses. This article is part of a Special Issue entitled: The role of post-translational protein modifications on heart and vascular metabolism edited by Jason R.B. Dyck & Jan F.C. Glatz.

Mathematical modeling of cardiac growth and remodeling

This review provides an overview of the current state of mathematical models of cardiac growth and remodeling (G&R). We concisely describe the experimental observations associated with cardiac G&R and discuss existing mathematical models that describe this process. To facilitate the discussion, we have organized the G&R models in terms of (1) the physical focus (biochemical vs mechanical) and (2) the process that they describe (myocyte hypertrophy vs extracellular matrix remodeling). The review concludes with a discussion of some possible directions that can advance the existing state of cardiac G&R mathematical modeling. WIREs Syst Biol Med 2016, 8:211-226. doi: 10.1002/wsbm.1330 For further resources related to this article, please visit the WIREs website.

Computational modeling of cardiac fibroblasts and fibrosis

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.

Monocyte and macrophage contributions to cardiac remodeling

The mammalian heart contains a population of resident macrophages that expands in response to myocardial infarction and hemodynamic stress. This expansion occurs likely through both local macrophage proliferation and monocyte recruitment. Given the role of macrophages in tissue remodeling, their contribution to adaptive processes in the heart is conceivable but currently poorly understood. In this review, we discuss monocyte and macrophage heterogeneity associated with cardiac stress, the cell's potential contribution to the pathogenesis of cardiac fibrosis, and describe different tools to study and characterize these innate immune cells. Finally, we highlight their potential role as therapeutic targets.

Computational Identification of Mechanistic Factors That Determine the Timing and Intensity of the Inflammatory Response

Timely resolution of inflammation is critical for the restoration of homeostasis in injured or infected tissue. Chronic inflammation is often characterized by a persistent increase in the concentrations of inflammatory cells and molecular mediators, whose distinct amount and timing characteristics offer an opportunity to identify effective therapeutic regulatory targets. Here, we used our recently developed computational model of local inflammation to identify potential targets for molecular interventions and to investigate the effects of individual and combined inhibition of such targets. This was accomplished via the development and application of computational strategies involving the simulation and analysis of thousands of inflammatory scenarios. We found that modulation of macrophage influx and efflux is an effective potential strategy to regulate the amount of inflammatory cells and molecular mediators in both normal and chronic inflammatory scenarios. We identified three molecular mediators − tumor necrosis factor-α (TNF-α), transforming growth factor-β (TGF-β), and the chemokine CXCL8 − as potential molecular targets whose individual or combined inhibition may robustly regulate both the amount and timing properties of the kinetic trajectories for neutrophils and macrophages in chronic inflammation. Modulation of macrophage flux, as well as of the abundance of TNF-α, TGF-β, and CXCL8, may improve the resolution of chronic inflammation.

A recent approach to quantitatively characterize the timing and intensity of the inflammatory response relies on the use of four quantities termed inflammation indices. The values of the inflammation indices may reflect the differences between normal and pathological inflammation, and may be used to gauge the effects of therapeutic interventions aimed to control inflammation. Yet, the specific inflammatory mechanisms that can be targeted to selectively control these indices remain unknown. Here, we developed and applied a computational strategy to identify potential target mechanisms to regulate such indices. We used our recently developed model of local inflammation to simulate thousands of inflammatory scenarios. We then subjected the corresponding inflammation index values to sensitivity and correlation analysis. We found that the inflammation indices may be significantly influenced by the macrophage influx and efflux rates, as well as by the degradation rates of three specific molecular mediators. These results suggested that the indices can be effectively regulated by individual or combined inhibition of those molecular mediators, which we confirmed by computational experiments. Taken together, our results highlight possible targets of therapeutic intervention that can be used to control both the timing and the intensity of the inflammatory response.

Biomechanics of Cardiac Function

The heart pumps blood to maintain circulation and ensure the delivery of oxygenated blood to all the organs of the body. Mechanics play a critical role in governing and regulating heart function under both normal and pathological conditions. Biological processes and mechanical stress are coupled together in regulating myocyte function and extracellular matrix structure thus controlling heart function. Here, we offer a brief introduction to the biomechanics of left ventricular function and then summarize recent progress in the study of the effects of mechanical stress on ventricular wall remodeling and cardiac function as well as the effects of wall mechanical properties on cardiac function in normal and dysfunctional hearts. Various mechanical models to determine wall stress and cardiac function in normal and diseased hearts with both systolic and diastolic dysfunction are discussed. The results of these studies have enhanced our understanding of the biomechanical mechanism in the development and remodeling of normal and dysfunctional hearts. Biomechanics provide a tool to understand the mechanism of left ventricular remodeling in diastolic and systolic dysfunction and guidance in designing and developing new treatments.

Transformative Impact of Proteomics on Cardiovascular Health and Disease: A Scientific Statement From the American Heart Association

The year 2014 marked the 20th anniversary of the coining of the term proteomics. The purpose of this scientific statement is to summarize advances over this period that have catalyzed our capacity to address the experimental, translational, and clinical implications of proteomics as applied to cardiovascular health and disease and to evaluate the current status of the field. Key successes that have energized the field are delineated; opportunities for proteomics to drive basic science research, facilitate clinical translation, and establish diagnostic and therapeutic healthcare algorithms are discussed; and challenges that remain to be solved before proteomic technologies can be readily translated from scientific discoveries to meaningful advances in cardiovascular care are addressed. Proteomics is the result of disruptive technologies, namely, mass spectrometry and database searching, which drove protein analysis from 1 protein at a time to protein mixture analyses that enable large-scale analysis of proteins and facilitate paradigm shifts in biological concepts that address important clinical questions. Over the past 20 years, the field of proteomics has matured, yet it is still developing rapidly. The scope of this statement will extend beyond the reaches of a typical review article and offer guidance on the use of next-generation proteomics for future scientific discovery in the basic research laboratory and clinical settings.

Unraveling the exercise-related proteome signature in heart

Exercise training is a well-known non-pharmacological strategy for the prevention and treatment of cardiovascular diseases. Despite the established phenotypic knowledge, the molecular signature of exercise-induced cardiac remodeling remains poorly characterized. The great majority of studies dedicated to this topic use conventional reductionist methods, which only allow analyzing individual protein candidates. Nowadays, several methodologies based on mass spectrometry are available and have been successfully applied for the characterization of heart proteome, representing an attractive approach for the wide characterization of the complex molecular networks that underlie exercise-induced cardiac remodeling. Still, few studies have used these methodologies to understand the impact of exercise training on the remodeling of cardiac proteome. The present study analyzes the few available data obtained from mass spectrometry (MS)-based proteomic studies assessing the impact of distinct types of exercise training on the protein profile of heart (left ventricle and isolated mitochondria) and the potential cross-tolerance between exercise training and diseases as myocardial infarction and obesity. Network analysis was performed with bioinformatics to integrate data from distinct research papers, based on distinct exercise training protocols, animal models and methodological approaches applied in the characterization of heart proteome. The analysis revealed that exercise training confers a unique proteome signature characterized by the up-regulation of lipid and organic metabolic processes, vasculogenesis and tissue regeneration. Data retrieved from this analysis also suggested that cardiac mitochondrial proteome is highly dynamic in response to exercise training due, in part, to the action of specific kinases as PKA and PKG. Regarding to the type of exercise, treadmill training seems to have a greater effect on the modulation of cardiac proteome than swimming. Data from the present review will certainly open new perspectives on cardiac proteomics and will help to envisage future studies targeting the identification of the regulatory mechanisms underlying cardiac adaptive and maladaptive remodeling.

Using systems biology approaches to understand cardiac inflammation and extracellular matrix remodeling in the setting of myocardial infarction

Inflammation and extracellular matrix (ECM) remodeling are important components regulating the response of the left ventricle to myocardial infarction (MI). Significant cellular- and molecular-level contributors can be identified by analyzing data acquired through high-throughput genomic and proteomic technologies that provide expression levels for thousands of genes and proteins. Large-scale data provide both temporal and spatial information that need to be analyzed and interpreted using systems biology approaches in order to integrate this information into dynamic models that predict and explain mechanisms of cardiac healing post-MI. In this review, we summarize the systems biology approaches needed to computationally simulate post-MI remodeling, including data acquisition, data analysis for biomarker classification and identification, data integration to build dynamic models, and data interpretation for biological functions. An example for applying a systems biology approach to ECM remodeling is presented as a reference illustration.

A model to determine the effect of collagen fiber alignment on heart function post myocardial infarction

BACKGROUND

Adverse remodeling of the left ventricle (LV) following myocardial infarction (MI) leads to heart failure. Recent studies have shown that scar anisotropy is a determinant of cardiac function post-MI, however it remains unclear how changes in extracellular matrix (ECM) organization and structure contribute to changes in LV function. The objective of this study is to develop a model to identify potential mechanisms by which collagen structure and organization affect LV function post-MI.

METHODS

A four-region, multi-scale, cylindrical model of the post-MI LV was developed. The mechanical properties of the infarct region are governed by a constitutive equation based on the uncrimping of collagen fibers. The parameters of this constitutive equation include collagen orientation, angular dispersion, fiber stiffness, crimp angle, and density. Parametric variation of these parameters was used to elucidate the relationship between collagen properties and LV function.

RESULTS

The mathematical model of the LV revealed several factors that influenced cardiac function post-MI. LV function was maximized when collagen fibers were aligned longitudinally. Increased collagen density was also found to improve stroke volume for longitudinal alignments while increased fiber stiffness decreased stroke volume for circumferential alignments.

CONCLUSIONS

The results suggest that cardiac function post-MI is best preserved through increased circumferential compliance. Further, this study identifies several collagen fiber-level mechanisms that could potentially regulate both infarct level and organ level mechanics. Improved understanding of the multi-scale relationships between the ECM and LV function will be beneficial in the design of new diagnostic and therapeutic technologies.

Computational approach to characterize causative factors and molecular indicators of chronic wound inflammation

Chronic inflammation is rapidly becoming recognized as a key contributor to numerous pathologies. Despite detailed investigations, understanding of the molecular mechanisms regulating inflammation is incomplete. Knowledge of such critical regulatory processes and informative indicators of chronic inflammation is necessary for efficacious therapeutic interventions and diagnostic support to clinicians. We used a computational modeling approach to elucidate the critical factors responsible for chronic inflammation and to identify robust molecular indicators of chronic inflammatory conditions. Our kinetic model successfully captured experimentally observed cell and cytokine dynamics for both acute and chronic inflammatory responses. Using sensitivity analysis, we identified macrophage influx and efflux rate modulation as the strongest inducing factor of chronic inflammation for a wide range of scenarios. Moreover, our model predicted that, among all major inflammatory mediators, IL-6, TGF-β, and PDGF may generally be considered the most sensitive and robust indicators of chronic inflammation, which is supported by existing, but limited, experimental evidence.

Mathematical modeling of left ventricular dimensional changes in mice during aging

Cardiac aging is characterized by diastolic dysfunction of the left ventricle (LV), which is due in part to increased LV wall stiffness. In the diastolic phase, myocytes are relaxed and extracellular matrix (ECM) is a critical determinant to the changes of LV wall stiffness. To evaluate the effects of ECM composition on cardiac aging, we developed a mathematical model to predict LV dimension and wall stiffness changes in aging mice by integrating mechanical laws and our experimental results. We measured LV dimension, wall thickness, LV mass, and collagen content for wild type (WT) C57/BL6J mice of ages ranging from 7.3 months to those of 34.0 months. The model was established using the thick wall theory and stretch-induced tissue growth to an isotropic and homogeneous elastic composite with mixed constituents. The initial conditions of the simulation were set based on the data from the young mice. Matlab simulations of this mathematical model demonstrated that the model captured the major features of LV remodeling with age and closely approximated experimental results. Specifically, the temporal progression of the LV interior and exterior dimensions demonstrated the same trend and order-of-magnitude change as our experimental results. In conclusion, we present here a validated mathematical model of cardiac aging that applies the thick-wall theory and stretch-induced tissue growth to LV remodeling with age.

Mathematical modeling and stability analysis of macrophage activation in left ventricular remodeling post-myocardial infarction

Background

About 6 million Americans suffer from heart failure and 70% of heart failure cases are caused by myocardial infarction (MI). Following myocardial infarction, increased cytokines induce two major types of macrophages: classically activated macrophages which contribute to extracellular matrix destruction and alternatively activated macrophages which contribute to extracellular matrix construction. Though experimental results have shown the transitions between these two types of macrophages, little is known about the dynamic progression of macrophages activation. Therefore, the objective of this study is to analyze macrophage activation patterns post-MI.

Results

We have collected experimental data from adult C57 mice and built a framework to represent the regulatory relationships among cytokines and macrophages. A set of differential equations were established to characterize the regulatory relationships for macrophage activation in the left ventricle post-MI based on the physical chemistry laws. We further validated the mathematical model by comparing our computational results with experimental results reported in the literature. By applying Lyaponuv stability analysis, the established mathematical model demonstrated global stability in homeostasis situation and bounded response to myocardial infarction.

Conclusions

We have established and validated a mathematical model for macrophage activation post-MI. The stability analysis provided a possible strategy to intervene the balance of classically and alternatively activated macrophages in this study. The results will lay a strong foundation to understand the mechanisms of left ventricular remodelling post-MI.

Mechanical regulation of fibroblast migration and collagen remodelling in healing myocardial infarcts

Effective management of healing and remodelling after myocardial infarction is an important problem in modern cardiology practice. We have recently shown that the level of infarct anisotropy is a critical determinant of heart function following a large anterior infarction, which suggests that therapeutic gains may be realized by controlling infarct anisotropy. However, factors regulating infarct anisotropy are not well understood. Mechanical, structural and chemical guidance cues have all been shown to regulate alignment of fibroblasts and collagen in vitro, and prior studies have proposed that each of these cues could regulate anisotropy of infarct scar tissue, but understanding of fibroblast behaviour in the complex environment of a healing infarct is lacking. We developed an agent-based model of infarct healing that accounted for the combined influence of these cues on fibroblast alignment, collagen deposition and collagen remodelling. We pooled published experimental data from several sources in order to determine parameter values, then used the model to test the importance of each cue for predicting collagen alignment measurements from a set of recent cryoinfarction experiments. We found that although chemokine gradients and pre-existing matrix structures had important effects on collagen organization, a response of fibroblasts to mechanical cues was critical for correctly predicting collagen alignment in infarct scar. Many proposed therapies for myocardial infarction, such as injection of cells or polymers, alter the mechanics of the infarct region. Our modelling results suggest that such therapies could change the anisotropy of the healing infarct, which could have important functional consequences. This model is therefore a potentially important tool for predicting how such interventions change healing outcomes.

Monocytes as a diagnostic marker of cardiovascular diseases

Inflammation is an important pathogenic factor of cardiovascular diseases. Inflammatory processes induce the organism systemic changes that are sensed by the cells of innate immune system. These systemic changes include increased concentrations of soluble factors capable of activating monocytes in the blood circulation therefore monocytes represent highly attractive cell population for diagnostic use. To date various parameters of circulating monocytes were associated with cardiovascular diseases. These comprise monocyte count, increased adhesive properties, alteration of lipid metabolism, phagocytosis and endocytosis of LDL. Search for markers, better suitable for clinical use led to identification of monocyte population heterogeneity. One of the best studied markers for identification of monocyte subpopulation is CD16. Although there is no consensus regarding the origin and composition of various monocyte subpopulations, association of increased size of CD16+ monocyte population with atherosclerosis is well established. Further surface markers of monocytes found to be associated with cardiovascular diseases are CD18, CD11b, CXCR1, CD36 and STAB1. Functional studies performed on primary human monocytes support the importance of these molecules for the pathogenesis of cardiovascular diseases. Continuous research on monocyte biology leads to identification of perspective markers that show significant potential of clinical use. These include analysis of monocyte response to a challenge and level of mitochondrial DNA heteroplasmy. Further research involving genomic, proteomic and cell biology techniques supplemented with systems biology approaches for data analysis and computer simulations are required for defining molecular and functional parameters of monocytes to be used as a diagnostic tool or therapeutic target.