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Aetiology‐specific patterns in end‐stage heart failure patients identified by functional annotation and classification of microarray data
Author(s) -
Beisvag Vidar,
Lehre Per Kristian,
Midelfart Herman,
Aass Halfdan,
Geiran Odd,
Sandvik Arne Kristian,
Lægreid Astrid,
Komorowski Jan,
Ellingsen Øyvind
Publication year - 2006
Publication title -
european journal of heart failure
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.149
H-Index - 133
eISSN - 1879-0844
pISSN - 1388-9842
DOI - 10.1016/j.ejheart.2006.05.004
Subject(s) - medicine , heart failure , dilated cardiomyopathy , coronary artery disease , microarray , gene expression profiling , cardiomyopathy , microarray analysis techniques , gene expression , ischemic cardiomyopathy , gene , cardiology , bioinformatics , genetics , biology , ejection fraction
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.