Signature genes in human heart failure based on gene expression analysis: Can we identify a unique set?

Dilated Cardiomyopathy is one of leading courses of heart failure. Recent advances in microarray technology have promised significant advantages in understanding the molecular mechanisms underlying dilated cardiomyopathy and heart failure. Several microarray studies have successfully yielded a set of signature genes associated with heart failure. However, it has been found that the overlap of these heart failure associated genes derived from different experiments is very small. Based on the analysis of two publicly available microarray datasets associated with heart failure with three types of machine learning and statistical prediction models, this paper explores this phenomenon. We found that there is no unique set of genes associated with heart failure. Many sets of genes can achieve very high prediction accuracy. In order to identify biomarkers in human heart failure, it may not be sufficient to just focus a certain number of top genes. Such main candidates should be chosen from the much longer list of genes.