Molecular signatures and the study of gene expression profiles in inflammatory heart diseases
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.
Herz 11/2012; DOI:10.1007/s00059-012-3721-y · 0.78 Impact Factor
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ABSTRACT: -Myocarditis is an inflammatory disease of the cardiac muscle and is mainly caused by viral infections. Viral myocarditis has been proposed to be divided into three phases; the acute viral phase, the subacute immune phase, and the chronic cardiac remodeling phase. Although individualized therapy should be applied depending on the phase, no clinical or experimental studies have found biomarkers that distinguish between the three phases. Theiler's murine encephalomyelitis virus (TMEV) belongs to the genus Cardiovirus, and can cause myocarditis in susceptible mouse strains.Circulation Cardiovascular Genetics 07/2014; 7(4). DOI:10.1161/CIRCGENETICS.114.000505 · 6.73 Impact Factor
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ABSTRACT: Development of innovative high throughput technologies has enabled a variety of molecular landscapes to be interrogated with an unprecedented degree of detail. Emergence of next generation nucleotide sequencing methods, advanced proteomic techniques, and metabolic profiling approaches continue to produce a wealth of biological data that captures molecular frameworks underlying phenotype. The advent of these novel technologies has significant translational applications, as investigators can now explore molecular underpinnings of developmental states with a high degree of resolution. Application of these leading-edge techniques to patient samples has been successfully used to unmask nuanced molecular details of disease vs healthy tissue, which may provide novel targets for palliative intervention. To enhance such approaches, concomitant development of algorithms to reprogram differentiated cells in order to recapitulate pluripotent capacity offers a distinct advantage to advancing diagnostic methodology. Bioinformatic deconvolution of several "-omic" layers extracted from reprogrammed patient cells, could, in principle, provide a means by which the evolution of individual pathology can be developmentally monitored. Significant logistic challenges face current implementation of this novel paradigm of patient treatment and care, however, several of these limitations have been successfully addressed through continuous development of cutting edge in silico archiving and processing methods. Comprehensive elucidation of genomic, transcriptomic, proteomic, and metabolomic networks that define normal and pathological states, in combination with reprogrammed patient cells are thus poised to become high value resources in modern diagnosis and prognosis of patient disease.Croatian Medical Journal 08/2013; 54(4):319-329. DOI:10.3325//cmj.2013.54.319 · 1.25 Impact FactorThis article is viewable in ResearchGate's enriched formatRG Format enables you to read in context with side-by-side figures, citations, and feedback from experts in your field.