Prediction of Ischemic Events on the Basis of Transcriptomic and Genomic Profiling in Patients Undergoing Carotid Endarterectomy

TL;DRAbstract

Classic risk factors, including age, smoking, serum cholesterol, diabetes and blood pressure, constitute the basis of present risk prediction models but fail to identify all individuals at risk. The objective of this study was to investigate if genomic and transcriptional patterns improve prediction of ischemic events in patients with established carotid artery disease. Genotype and gene expression profiles were obtained from carotid plaque tissue (n = 126) and peripheral blood mononuclear cells (n = 97) of patients undergoing carotid endarterectomy. Patients were followed for an average of 44 months, and 25 ischemic events occurred (18 ischemic strokes and 7 myocardial infarctions). Blinded leave-one-out cross-validation on Cox regression coefficients was used to assign gene expression-based risk scores to each patient. When compared with classic risk factors, addition of carotid plaque gene expression-based risk score improved the prediction of future ischemic events from an area und

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