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J Am Coll Cardiol, 2006; 48:1610-1617, doi:10.1016/j.jacc.2006.07.026
(Published online 26 September 2006). © 2006 by the American College of Cardiology Foundation |


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* Department of Medicine I, University Hospital Grosshadern, Munich, Germany
Department of Cardiac Surgery, University Hospital Grosshadern, Munich, Germany
Department of Medical Informatics, Biometrics and Epidemiology, Ludwig-Maximilians-University, Munich, Germany
Division of Molecular Genome Analysis, German Cancer Research Center, Heidelberg, Germany
|| Department of Medical Informatics and Biomathematics, University of Münster, Münster, Germany
Manuscript received December 18, 2005; revised manuscript received April 14, 2006, accepted June 6, 2006.
* Reprint requests and correspondence: Dr. Andreas S. Barth, Department of Medicine I, University Hospital Grosshadern, Munich, Marchioninistrasse 15, 81377 Munich, Germany (Email: andreas.barth{at}med.uni-muenchen.de).
OBJECTIVES: This study was designed to identify a common gene expression signature in dilated cardiomyopathy (DCM) across different microarray studies.
BACKGROUND: Dilated cardiomyopathy is a common cause of heart failure in Western countries. Although gene expression arrays have emerged as a powerful tool for delineating complex disease patterns, differences in platform technology, tissue heterogeneity, and small sample sizes obscure the underlying pathophysiologic events and hamper a comprehensive interpretation of different microarray studies in heart failure.
METHODS: We accounted for tissue heterogeneity and technical aspects by performing 2 genome-wide expression studies based on cDNA and short-oligonucleotide microarray platforms which comprised independent septal and left ventricular tissue samples from nonfailing (NF) (n = 20) and DCM (n = 20) hearts.
RESULTS: Concordant results emerged for major gene ontology classes between cDNA and oligonucleotide microarrays. Notably, immune response processes displayed the most pronounced down-regulation on both microarray types, linking this functional gene class to the pathogenesis of end-stage DCM. Furthermore, a robust set of 27 genes was identified that classified DCM and NF samples with >90% accuracy in a total of 108 myocardial samples from our cDNA and oligonucleotide microarray studies as well as 2 publicly available datasets.
CONCLUSIONS: For the first time, independent microarray datasets pointed to significant involvement of immune response processes in end-stage DCM. Moreover, based on 4 independent microarray datasets, we present a robust gene expression signature of DCM, encouraging future prospective studies for the implementation of disease biomarkers in the management of patients with heart failure.
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