© 2006 European Society of Cardiology
Aetiology-specific patterns in end-stage heart failure patients identified by functional annotation and classification of microarray data
a Department of Circulation and Medical Imaging, Norwegian University of Science and Technology Trondheim, Norway
b Department of Information Technology and Computer Science, Norwegian University of Science and Technology Trondheim, Norway
c Department of Cardiology Rikshospitalet, Oslo, Norway
d Department of Thorax Surgery Rikshospitalet, Oslo, Norway
e Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology Trondheim, Norway
f Department of Medicine, St. Olav's Hospital Trondheim, Norway
g The Linnaeus Centre for Bioinformatics, Uppsala University Uppsala, Sweden
h Department of Cardiology, St. Olav's Hospital Trondheim, Norway
* Corresponding author. Department of Circulation and Imaging, Faculty of Medicine, NTNU, Medical Research Centre, N-7489 Trondheim, Norway. Tel.: +47 7359 8888. E-mail address: vidar.beisvag{at}ntnu.no
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Abstract |
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Background: The objective of the present study was to use gene expression profiling, functional annotations and classification to identify aetiology-specific biological processes and potential molecular markers for different aetiologies of end-stage heart failure.
Methods and results: Individual left ventricular myocardial samples from eleven coronary artery disease and nine dilated cardiomyopathy transplant patients were co-hybridized with pooled RNA from four non-failing hearts on custom-made arrays of 7000 human genes. Significance analysis identified differential expression of 153 and 147 genes, respectively, in coronary artery disease or dilated cardiomyopathy versus non-failing hearts. Analysis of Gene Ontology biological process annotations indicated aetiology-specific patterns, primarily related to genes involved in catabolism and in regulation of protein kinase activity. Gene expression classifiers were obtained and used for class prediction of random samples of coronary artery diseased and dilated cardiomyopathic hearts. Best classifiers frequently included matrix metalloproteinase 3, fibulin 1, ATP-binding cassette, sub-family B member 1 and iroquois homeobox protein 5.
Conclusion: Combining functional annotation from microarray data and classification analysis constitutes a potent strategy to identify disease-specific biological processes and gene expression markers in e.g. end-stage coronary artery disease and dilated cardiomyopathy.
Key Words: Coronary artery disease • Cardiomyopathy • Gene expression • Functional annotation • Classification
Received December 6, 2005; Revised March 7, 2006; Accepted May 9, 2006
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