Principal component analysis of gene expression data: The case of atrial fibrillation

Abstract

Atrial fibrillation (AF) is the most common persistent cardiac arrhythmia. AF is also associated with extensive structural, contractile, and electrophysiological remodeling, which can sustain AF itself. The understanding of the molecular events of these remodeling processes is essential for the development of new targeted therapeutic interventions. In this paper microarray data related to permanent AF patients and controls were analyzed using the principal components extracted from a matrix having gene expression values as statistical units and patients as variables. The data were obtained from the public functional genomics data repository of the National Institute of Health (called Gene Expression Omnibus, GEO). Data from record #GSE2240 have been analyzed, consisting of samples of right atrial myocardium (appendage). Data were related to two Affymetrix platforms U133A and U133B. Right atrial appendages were obtained from 30 patients undergoing open heart surgery for valve repair or coronary artery bypass grafting. Of these, 10 patients had permanent AF and 20 patients had no history of AF. The differences in gene expression profiles between permanent AF patients and controls are related to a very small part of the data variability. However, the analysis of such a small difference in terms of factor loadings and scores, succeed in discriminating patients from controls and in offering a mechanistic view relating AF condition to both cardiac muscle organization and inflammatory processes.