Molecular signatures and the study of gene expression profiles in inflammatory heart diseases

Department of Internal Medicine - Cardiology, Biomedical Research Center, University Hospital Giessen and Marburg and Philipps-University Marburg, Hans-Meerwein-Str., 35043, Marburg, Germany, .
Herz (Impact Factor: 0.91). 08/2012; 37(6):619-626. DOI: 10.1007/s00059-012-3662-5
Source: PubMed

ABSTRACT Myocarditis, a common heart disease pathologically defined as an inflammatory reaction of the myocardium, is most frequently caused by infectious agents, including viruses and bacteria, and may develop in later stages into dilated cardiomyopathy (DCM). Several studies have identified inflammatory components engaged in the transition from acute myocarditis to chronic DCM, and there is growing evidence that myocarditis and DCM are closely related. Novel technological advances in genomic screening have gained insight into molecular and cellular mechanisms involved the pathogenesis of inflammatory heart disease and, in particular, in the development of systolic dysfunction resulting from DCM. Detection of differential gene expression profiles have become valid tools in the study of inflammatory heart disease. Molecular signatures are defined as individual sets of genes, mRNA transcripts, proteins, genetic variations or other variables, which can be used as markers for a particular phenotype. These signatures may be useful for clinical diagnosis or risk assessment and, in addition, may help to identify molecules not previously known to be involved in the pathogenesis of these disease conditions.Microarray analyses have dramatically refined our knowledge about tissue-specific gene expression patterns, simply by being able to study thousands of genes simultaneously in a single experiment. In the field of cardiovascular research, microarrays are increasingly used in the study of end-stage cardiomyopathies, such as DCM, that ultimately lead to symptoms of heart failure. By means of microarray analysis, a set of differentially expressed genes can be detected, among them are transcripts coding for sarcomeric and extracellular matrix proteins, stress response and inflammatory proteins as well as transcription factors and translational regulators. Expression profiling may be particularly helpful to improve the differential diagnosis of heart failure and enable novel insight into selected molecular pathways.

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