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Gene expression patterns in peripheral blood correlate with the extent of coronary artery disease

ABSTRACT: Gene expression profile in circulating leukocytes identifies patients with coronary artery disease Peter Sinnaeve, Mark Donahue, Peter Grass, Jacky Vonderscher, David Seo, Pascal Goldschmidt, Christopher Granger Department of Medicine, Duke University, Durham, NC, USA, Novartis Institute for Biomedical Research, Cambridge, Boston, MA, USA Introduction Systemic and local inflammation plays a prominent pathogenetic role in atherosclerotic coronary artery disease (CAD), but the relationship of phenotypic changes in circulating leukocytes and extent of CAD remains unclear. We have investigated whether gene expression patterns in circulating leukocytes are associated with presence and extent of CAD. Methods Patients undergoing coronary angiography were selected according to their Duke CAD index (CADi), a validated angiographical measure of the extent of coronary atherosclerosis that correlates with outcome. RNA was extracted from 110 patients with CAD (CADi>23) and from 112 partially matched controls without CAD (CADi=0). Gene expression was assessed using Affymetrix U133A chips. Genes correlating with CAD were identified using Spearman’s rank correlation, and predictive gene expression patterns were identified using a partial least squares (PLS) regression analysis. Results 160 individual genes were found to significantly correlate with CADi (rho>0.2, P<0.0027), although changes in individual gene expression were relatively small (1.2 to 1.5 fold). Using these 160 genes, the PLS multivariate regression resulted in a highly predictive model (r2=0.764, P<0.001). Cross-validation showed that most of the predictive model was carried by only 8 genes (r2=0.752) (table 1). Conclusion Simultaneous expression pattern of 8 genes appears to be highly predictive for CAD. Peripheral leukocyte gene expression pattern could be a novel non-invasive biomarker for CAD and lead to new pathophysiologic insights.

ORGANISM(S): Homo sapiens

PROVIDER: GSE12288 | GEO | 2008/10/31

SECONDARY ACCESSION(S): PRJNA113575

REPOSITORIES: GEO

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Project description:Monocytes and T-cells play an important role in the development of atherosclerotic coronary artery disease (CAD). Differences in transcriptional activity of these cells might reflect the individual's atherosclerotic burden. Transcriptome analysis of circulating mononuclear cells from carefully matched atherosclerotic and control patients will potentially provide insights into the pathophysiology of atherosclerosis and supply biomarkers for diagnostic purposes. From patients undergoing coronary angiography because of anginal symptoms, we carefully matched 18 patients with severe triple-vessel CAD to 13 control patients without signs of CAD on angiography. All patients were on statin and aspirin treatment. RNA from circulating CD4+ T-cells, CD14+ monocytes, lipopolysaccharide-stimulated monocytes, macrophages and CD34+ progenitor cells was subjected to genome-wide expression analysis. Only CD14+ monocytes demonstrated that a small number of genes involved in activation was overexpressed in control patients, which was verified by real-time polymerase-chain reaction. In this pilot study, cautious matching of patients with severe atherosclerotic CAD with control patients without angiographic signs of coronary atherosclerosis did not reveal differences in transcriptional activity in four out of five different mononuclear cell types. In resting monocytes from patients without overt CAD some inflammatory genes were overexpressed as compared to patients with severe CAD. Large inter-individual variability prevented the use of single differentially expressed genes as biomarkers. Keywords: disease-state analysis In total 153 arrays were analyzed with 6 technical replicates (147 biological samples). CD34+ stem cells, CD4+ T-cells, resting CD14+ monocytes, stimulated monocytes and macrophages were analyzed, all from patient with severe coronary atherosclerosis or controls that had no coronary atherosclerosis as determined angiographically, and which were carefully matched for age and gender.

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Gene expression patterns in peripheral blood correlate with the extent of coronary artery disease

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