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Physiol Genomics. 2013 Jul 15;45(14):597-605. doi: 10.1152/physiolgenomics.00013.2013. Epub 2013 May 21.

Detection of differentially methylated gene promoters in failing and nonfailing human left ventricle myocardium using computation analysis.

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1
Department of Pathology, Emory University, Atlanta, Georgia, USA.

Abstract

Human dilated cardiomyopathy (DCM) is characterized by congestive heart failure and altered myocardial gene expression. Epigenetic changes, including DNA methylation, are implicated in the development of DCM but have not been studied extensively. Clinical human DCM and nonfailing control left ventricle samples were individually analyzed for DNA methylation and expressional changes. Expression microarrays were used to identify 393 overexpressed and 349 underexpressed genes in DCM (GEO accession number: GSE43435). Gene promoter microarrays were utilized for DNA methylation analysis, and the resulting data were analyzed by two different computational methods. In the first method, we utilized subtractive analysis of DNA methylation peak data to identify 158 gene promoters exhibiting DNA methylation changes that correlated with expression changes. In the second method, a two-stage approach combined a particle swarm optimization feature selection algorithm and a discriminant analysis via mixed integer programming classifier to identify differentially methylated gene promoters. This analysis identified 51 hypermethylated promoters and six hypomethylated promoters in DCM with 100% cross-validation accuracy in the group assignment. Generation of a composite list of genes identified by subtractive analysis and two-stage computation analysis revealed four genes that exhibited differential DNA methylation by both methods in addition to altered gene expression. Computationally identified genes (AURKB, BTNL9, CLDN5, and TK1) define a central set of differentially methylated gene promoters that are important in classifying DCM. These genes have no previously reported role in DCM. This study documents that rigorous computational analysis applied to microarray analysis of healthy and diseased human heart samples helps to define clinically relevant DNA methylation and expressional changes in DCM.

KEYWORDS:

DAMIP; DNA methylation; computational analysis; heart; heart failure

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