The extracellular matrix in myocardial injury, repair, and remodeling

Frangogiannis, Nikolaos G.

doi:10.1172/jci87491

Cited by 402 publications

(353 citation statements)

References 182 publications

Supporting

Mentioning

343

Contrasting

Unclassified

Order By: Relevance

“…Moreover, examination of the predicted transcriptional regulatory networks for each specific cell-state comparison identifies well-defined MI-associated gene expression differences in human Fibroblasts (upregulation of Col1a1,Col1a2,Col3a1,Col4a2,Col5a1,Col5a2 [Collagen scar] Fn1, Thbs1, Mmp14) along with novel implicated regulators which agree with prior literature (Fig. 4F) (van Dijk et al 2008;Spinale et al 2013;Frangogiannis 2017;Mouton et al 2019). While the two central transcriptional nodes in this network, Hif1a and Runx1, have been previously implicated in MI and even as possible targets for therapy, these markers have not been explicitly associated with the MI fibroblasts (Kido et al 2005;Semenza 2014;McCarroll et al 2018).…”

Section: Computing Disease-level Impacts In Diverse Tissue Cell-typessupporting

confidence: 87%

cellHarmony: Cell-level matching and holistic comparison of single-cell transcriptomes

DePasquale

Dexheimer

Schnell

et al. 2018

Preprint

View full text Add to dashboard Cite

To understand the molecular pathogenesis of human disease, precision analyses to define molecular alterations within (and between) disease-associated cell populations are desperately needed.Single-cell genomics represents an ideal platform to enable the identification and comparison of normal and diseased transcriptional cell states. We note that disease-associated perturbations usually retain cellular-identity programs (core genes), providing an appropriate reference for secondary comparison analyses. Thus, we created cellHarmony, an integrated solution for the unsupervised analysis and classification of cell types from diverse scRNA-Seq datasets. cellHarmony is an automated and easy-touse tool that efficiently matches single-cell transcriptomes using a community clustering and alignment strategy. Utilizing core genes and community clustering to reveal disease and cell-state systems-level insights overcomes bias toward donor and disease effects that can be imposed by joint-alignment approaches. Moreover, cellHarmony directly compares cell frequencies and gene expression in a celltype-specific manner, then produces a holistic representation of these differences across potentially dozens of cell populations and impacted regulatory networks. Using this approach, we identify gene regulatory programs that are selectively impacted in distinct hematopoietic and heart cell populations that suggest novel disease mechanisms and drug targets. Thus, this approach holds tremendous promise in revealing the molecular and cellular origins of complex diseases.

show abstract

Section: Computing Disease-level Impacts In Diverse Tissue Cell-typessupporting

confidence: 87%

cellHarmony: Cell-level matching and holistic comparison of single-cell transcriptomes

DePasquale

Dexheimer

Schnell

et al. 2018

Preprint

View full text Add to dashboard Cite

show abstract

“…Mouse models of myocardial disease have been extensively used to study the pathophysiology of myocardial infarction and heart failure (14),(15),(16),(17),(18),(19),(20). Although sophisticated imaging modalities, histopathologic studies and molecular approaches are used to study remodeling of the left ventricle, atrial pathology is often ignored.…”

Section: Introductionmentioning

confidence: 99%

Left atrial remodeling, hypertrophy, and fibrosis in mouse models of heart failure

Hanif¹,

Alex²,

Su³

et al. 2017

Cardiovascular Pathology

Self Cite

View full text Add to dashboard Cite

Left ventricular dysfunction increases left atrial pressures and causes atrial remodeling. In human subjects, increased left atrial size is a powerful predictor of mortality and adverse events in a broad range of cardiac pathologic conditions. Moreover, structural remodeling of the atrium plays an important role in the pathogenesis of atrial tachyarrhythmias. Despite the potential value of the atrium in assessment of functional endpoints in myocardial disease, atrial pathologic alterations in mouse models of left ventricular disease have not been systematically investigated. Our study describes the geometric, morphologic and structural changes in experimental mouse models of cardiac pressure overload (induced through transverse aortic constriction), myocardial infarction and diabetes. Morphometric and histological analysis showed that pressure overload was associated with left atrial dilation, increased left atrial mass, loss of myofibrillar content in a subset of atrial cardiomyocytes, atrial cardiomyocyte hypertrophy, and atrial fibrosis. In mice undergoing non-reperfused myocardial infarction protocols, marked left ventricular systolic dysfunction was associated with left atrial enlargement, atrial cardiomyocyte hypertrophy and atrial fibrosis. Both infarcted animals and pressure overloaded mice exhibited attenuation and perturbed localization of atrial connexin-43 immunoreactivity, suggesting gap junctional remodeling. In the absence of injury, obese diabetic db/db mice had diastolic dysfunction, associated with atrial dilation, atrial cardiomyocyte hypertrophy and mild atrial fibrosis. Considering the challenges in assessment of clinically relevant functional endpoints in mouse models of heart disease, study of atrial geometry and morphology may serve as an important new tool for evaluation of ventricular function.

show abstract

“…Collagens I and III are the most common ECM components, and they respectively account for 85–90% and 5–11% of collagens in the cardiac ECM [20]. These collagens compose a fibrillar network in cardiac tissue and provide both structural stability and take part in cellular signaling.…”

Section: Collagen Fibrosis and Other Biological Targets For Ecm Imamentioning

confidence: 99%

“…The cardiac ECM is a dynamic environment that varies in organization and composition throughout the course of cardiac disease and during normal cardiac development. Knowledge of these changes can help researchers and clinicians understand, detect, and treat cardiac disease [20, 62]. Biomedical imaging is one of the main tools for measuring the cardiac extracellular matrix (ECM), encompassing a range of research and clinical imaging methods that are capable of visualizing different ECM properties and components.…”

Section: Introductionmentioning

confidence: 99%

Imaging the Cardiac Extracellular Matrix

Pinkert

Hortensius

Ogle

et al. 2018

Advances in Experimental Medicine and Biology

View full text Add to dashboard Cite

Cardiovascular disease is the global leading cause of death. One route to address this problem is using biomedical imaging to measure the molecules and structures that surround cardiac cells. This cellular microenvironment, known as the cardiac extracellular matrix, changes in composition and organization during most cardiac diseases and in response to many cardiac treatments. Measuring these changes with biomedical imaging can aid in understanding, diagnosing, and treating heart disease. This chapter supports those efforts by reviewing representative methods for imaging the cardiac extracellular matrix. It first describes the major biological targets of ECM imaging, including the primary imaging target of fibrillar collagen. Then it discusses the imaging methods, describing their current capabilities and limitations. It categorizes the imaging methods into two main categories: organ-scale noninvasive methods and cellular-scale invasive methods. Noninvasive methods can be used on patients, but only a few are clinically available, and others require further development to be used in the clinic. Invasive methods are the most established and can measure a variety of properties, but they cannot be used on live patients. Finally, the chapter concludes with a perspective on future directions and applications of biomedical imaging technologies.

show abstract

The extracellular matrix in myocardial injury, repair, and remodeling

Cited by 402 publications

References 182 publications

cellHarmony: Cell-level matching and holistic comparison of single-cell transcriptomes

cellHarmony: Cell-level matching and holistic comparison of single-cell transcriptomes

Left atrial remodeling, hypertrophy, and fibrosis in mouse models of heart failure

Imaging the Cardiac Extracellular Matrix

Contact Info

Product

Resources

About