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Physiol. Genomics 31: 367-373, 2007. First published August 21, 2007; doi:10.1152/physiolgenomics.00144.2007
1094-8341/07 $8.00
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Received 10 July 2007; accepted in final form 9 August 2007.
Physiological Genomics 31:367-373 (2007)
1094-8341/06 $8.00 © 2007 American Physiological Society

Editorial Focus

Altered microRNA expression in human heart disease

Sadakatsu Ikeda 1,*, Sek Won Kong 1,*, Jun Lu 2, Egbert Bisping 3, Hao Zhang 2, Paul D. Allen 4, Todd R. Golub 2,5, Burkert Pieske 3 and William T. Pu 1

1 Department of Cardiology, Children's Hospital Boston, and Department of Genetics, Harvard Medical School, Boston;
2 Department of Pediatric Oncology, Dana Farber Cancer Institute, Harvard Medical School, Boston, and the Broad Institute of Harvard and MIT, Cambridge, Massachusetts;
3 Department of Cardiology and Pneumology, Georg August University, Göttingen, Germany;
4 Department of Anesthesia, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts;
5 Department of Medicine, Children's Hospital Boston, Boston, Massachusetts, and Howard Hughes Medical Institute, Chevy Chase, Maryland

ABSTRACT

MicroRNAs are recently discovered regulators of gene expression and are becoming increasingly recognized as important regulators of heart function. Genome-wide profiling of microRNAs in human heart failure has not been reported previously. We measured expression of 428 microRNAs in 67 human left ventricular samples belonging to control (n = 10), ischemic cardiomyopathy (ICM, n = 19), dilated cardiomyopathy (DCM, n = 25), or aortic stenosis (AS, n = 13) diagnostic groups. miRNA expression between disease and control groups was compared by ANOVA with Dunnett's post hoc test. We controlled for multiple testing by estimating the false discovery rate. Out of 428 microRNAs measured, 87 were confidently detected; 43 were differentially expressed in at least one disease group. In supervised clustering, microRNA expression profiles correctly grouped samples by their clinical diagnosis, indicating that microRNA expression profiles are distinct between diagnostic groups. This was further supported by class prediction approaches, in which the class (control, ICM, DCM, AS) predicted by a microRNA-based classifier matched the clinical diagnosis 69% of the time (P < 0.001). These data show that expression of many microRNAs is altered in heart disease and that different types of heart disease are associated with distinct changes in microRNA expression. These data will guide further studies of the contribution of microRNAs to heart disease pathogenesis.

heart failure; gene expression; expression profiling




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