Transcriptomal analysis of failing and nonfailing human hearts

Author:

Steenman M.1,Chen Y.-W.2,Le Cunff M.1,Lamirault G.1,Varró A.3,Hoffman E.2,Léger J. J.1

Affiliation:

1. Institut National de la Santé et de la Recherche Médicale U533, 44035 Nantes, France

2. Children’s National Medical Center, Washington, District of Columbia 20010

3. Department of Pharmacology and Pharmacotherapy, University of Szeged, H-6701 Szeged, Hungary

Abstract

Heart failure is a multifactorial disease that may result from different initiating events. To contribute to an improved comprehension of normal cardiac function and the molecular events leading to heart failure, we performed large-scale gene expression analysis of failing and nonfailing human ventricle. Our aim was to define and compare expression profiles of 4 specific pathophysiological cardiac situations: 1) left ventricle (LV) from nonfailing heart; 2) LV from failing hearts affected by dilated cardiomyopathy (DCM); 3) LV from failing hearts affected by ischemic CM (ICM); 4) right ventricle (RV) from failing hearts affected by DCM or ICM. We used oligonucleotide arrays representing ∼12,000 human genes. After stringent numerical analyses using several statistical tests, we identified 1,306 genes with a similar expression profile in all 4 cardiac situations, therefore representative of part of the human cardiac expression profile. A total of 95 genes displayed differential expression between failing and nonfailing heart samples, reflecting a reversal to developmental gene expression, dedifferentiation of failing cardiomyocytes, and involvement of apoptosis. Twenty genes were differentially expressed between failing LV and failing RV, identifying possible candidates for different functioning of both ventricles. Finally, no genes were found to be significantly differentially expressed between failing DCM and failing ICM LV, emphasizing that transcriptomal analysis of explanted hearts results mainly in identification of expression profiles of end-stage heart failure and less in determination of expression profiles of the underlying etiology. Taken together, our data resulted in identification of putative transcriptomal landmarks for normal and disturbed cardiac function.

Publisher

American Physiological Society

Subject

Genetics,Physiology

Reference47 articles.

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