title: Gene expression patterns in peripheral blood correlate with the extent of coronary artery disease.
abstract: Systemic and local inflammation plays a prominent role in the pathogenesis of atherosclerotic coronary artery disease, but the relationship of whole blood gene expression changes with coronary disease remains unclear. We have investigated whether gene expression patterns in peripheral blood correlate with the severity of coronary disease and whether these patterns correlate with the extent of atherosclerosis in the vascular wall. Patients were selected according to their coronary artery disease index (CADi), a validated angiographical measure of the extent of coronary atherosclerosis that correlates with outcome. RNA was extracted from blood of 120 patients with at least a stenosis greater than 50% (CADi > or = 23) and from 121 controls without evidence of coronary stenosis (CADi = 0). 160 individual genes were found to correlate with CADi (rho > 0.2, P<0.003). Prominent differential expression was observed especially in genes involved in cell growth, apoptosis and inflammation. Using these 160 genes, a partial least squares multivariate regression model resulted in a highly predictive model (r(2) = 0.776, P<0.0001). The expression pattern of these 160 genes in aortic tissue also predicted the severity of atherosclerosis in human aortas, showing that peripheral blood gene expression associated with coronary atherosclerosis mirrors gene expression changes in atherosclerotic arteries. In conclusion, the simultaneous expression pattern of 160 genes in whole blood correlates with the severity of coronary artery disease and mirrors expression changes in the atherosclerotic vascular wall.
authors.affiliation: Duke University Medical Center and Duke Clinical Research Institute, Duke University, Durham, North Carolina, United States of America. peter.sinnaeve@uzleuven.be
authors.forename: Peter R
authors.initials: PR
authors.lastname: Sinnaeve
authors.forename: Mark P
authors.initials: MP
authors.lastname: Donahue
authors.forename: Peter
authors.initials: P
authors.lastname: Grass
authors.forename: David
authors.initials: D
authors.lastname: Seo
authors.forename: Jacky
authors.initials: J
authors.lastname: Vonderscher
authors.forename: Salah-Dine
authors.initials: SD
authors.lastname: Chibout
authors.forename: William E
authors.initials: WE
authors.lastname: Kraus
authors.forename: Michael
authors.initials: M
authors.lastname: Sketch
authors.forename: Charlotte
authors.initials: C
authors.lastname: Nelson
authors.forename: Geoffrey S
authors.initials: GS
authors.lastname: Ginsburg
authors.forename: Pascal J
authors.initials: PJ
authors.lastname: Goldschmidt-Clermont
authors.forename: Christopher B
authors.initials: CB
authors.lastname: Granger
mesh_terms: D000328:Adult; D000368:Aged; D001011:Aorta / Q000378:metabolism; D016022:Case-Control Studies; D015331:Cohort Studies; D003324:Coronary Artery Disease / Q000097:blood* / Q000378:metabolism; D005260:Female; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation; D006801:Humans; D007249:Inflammation; D008297:Male; D008875:Middle Aged; D020411:Oligonucleotide Array Sequence Analysis; D012307:Risk Factors