Literature DB >> 20428444

Extracellular matrix alterations in cardiomyopathy: The possible crucial role in the dilative form.

V I Kapelko1.   

Abstract

The collagen network, part of the myocardial extracellular matrix (EM), and other EM proteins transmit mechanical forces generated by cardiomyocytes to cardiac cavities. Network rearrangement and enlargement - fibrosis - is an essential component of cardiac remodelling at various pathological stages. In particular, similarly abundant fibrosis occurs in dilated, hypertrophic and restrictive cardiomyopathy, and it is unclear how this relates to respective changes in ventricular cavities and size. Recent studies of hereditary forms have provided evidence that, in hypertrophic cardiomyopathy, the primary changes occur within cardiomyocytes that are subjected to either necrosis or mutations in genes that code for contractile proteins, while gene mutations of EM proteins have not been found. In contrast, in dilative cardiomyopathy, gene mutations of dystrophin, merosin and other proteins connecting the collagen matrix to cardiomyocyte membranes and actin filaments have been found. A distortion of the mechanical link between the contractile apparatus and the collagen matrix may disturb force transmission in both directions and lead to decreased developed pressure and increased end-systolic volume, provoking cardiac dilation. Profound alterations in the EM have also been induced acutely by alcohol, adriamycin or a high pacing rate, resulting in the development of dilative cardiomyopathy. Thus, EM alterations may be the primary factor in the pathogenesis of dilative cardiomyopathy.

Entities:  

Keywords:  Cardiomyopathy; Extracellular matrix; Fibrosis; Heart; Remodelling

Year:  2001        PMID: 20428444      PMCID: PMC2858965     

Source DB:  PubMed          Journal:  Exp Clin Cardiol        ISSN: 1205-6626


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8.  Losing Regulation of the Extracellular Matrix is Strongly Predictive of Unfavorable Prognostic Outcome after Acute Myocardial Infarction.

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10.  Network-based computational approach to identify genetic links between cardiomyopathy and its risk factors.

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