Amy J. Sehnert

Correlation of peripheral-blood gene expression with the extent of coronary artery stenosis.

Background—The molecular pathophysiology of coronary artery disease (CAD) includes cytokine release and a localized inflammatory response within the vessel wall. The extent to which CAD and its severity is reflected by gene expression in circulating cells is unknown. Methods and Results—From an initial coronary catheterization cohort we identified 41 patients, comprising 27 cases with angiographically significant CAD and 14 controls without coronary stenosis. Whole-genome microarray analysis performed on peripheral-blood mononuclear cells yielded 526 genes with >1.3-fold differential expression (P<0.05) between cases and controls. Real-time polymerase chain reaction on 106 genes (the 50 most significant microarray genes and 56 additional literature genes) in an independent subset of 95 patients (63 cases, 32 controls) from the same cohort yielded 14 genes (P<0.05) that independently discriminated CAD state in a multivariable analysis that included clinical and demographic factors. From an independent second catheterization cohort, 215 patients were selected for real-time polymerase chain reaction–based replication. A case:control subset of 107 patients (86 cases, 21 controls) replicated 11 of the 14 multivariably significant genes from the first cohort. An analysis of the 14 genes in the entire set of 215 patients demonstrated that gene expression was proportional to maximal coronary artery stenosis (P<0.001 by ANOVA). Conclusions—Gene expression in peripheral-blood cells reflects the presence and extent of CAD in patients undergoing angiography.

Multicenter Validation of the Diagnostic Accuracy of a Blood-Based Gene Expression Test for Assessing Obstructive Coronary Artery Disease in Nondiabetic Patients

BACKGROUND Diagnosing obstructive coronary artery disease (CAD) in at-risk patients can be challenging and typically requires both noninvasive imaging methods and coronary angiography, the gold standard. Previous studies have suggested that peripheral blood gene expression can indicate the presence of CAD. OBJECTIVE To validate a previously developed 23-gene, expression-based classification test for diagnosis of obstructive CAD in nondiabetic patients. DESIGN Multicenter prospective trial with blood samples obtained before coronary angiography. (ClinicalTrials.gov registration number: NCT00500617) SETTING: 39 centers in the United States. PATIENTS An independent validation cohort of 526 nondiabetic patients with a clinical indication for coronary angiography. MEASUREMENTS Receiver-operating characteristic (ROC) analysis of classifier score measured by real-time polymerase chain reaction, additivity to clinical factors, and reclassification of patient disease likelihood versus disease status defined by quantitative coronary angiography. Obstructive CAD was defined as 50% or greater stenosis in 1 or more major coronary arteries by quantitative coronary angiography. RESULTS The area under the ROC curve (AUC) was 0.70 ± 0.02 (P < 0.001); the test added to clinical variables (Diamond-Forrester method) (AUC, 0.72 with the test vs. 0.66 without; P = 0.003) and added somewhat to an expanded clinical model (AUC, 0.745 with the test vs. 0.732 without; P = 0.089). The test improved net reclassification over both the Diamond-Forrester method and the expanded clinical model (P < 0.001). At a score threshold that corresponded to a 20% likelihood of obstructive CAD (14.75), the sensitivity and specificity were 85% and 43% (yielding a negative predictive value of 83% and a positive predictive value of 46%), with 33% of patient scores below this threshold. LIMITATION Patients with chronic inflammatory disorders, elevated levels of leukocytes or cardiac protein markers, or diabetes were excluded. CONCLUSION A noninvasive whole-blood test based on gene expression and demographic characteristics may be useful for assessing obstructive CAD in nondiabetic patients without known CAD. PRIMARY FUNDING SOURCE CardioDx.

A VALIDATED, PERIPHERAL BLOOD GENE EXPRESSION PATTERN CORRELATES WITH CORONARY ARTERIAL PLAQUE BURDEN BY QUANTITATIVE CORONARY ANGIOGRAPHY AND CORONARY ARTERY CALCIUM SCORING

Category: 48. Genetics and Clinical Outcomes Presentation Number: 924-4 Citation: J. Am. Coll. Cardiol. 2011;57;E1157 Authors: Szilard Voros, Michael R. Elashoff, Amy J. Sehnert, Hsiao D. Lieu, James A. Wingrove, Susan E. Daniels, Steven Rosenberg, Alexandra Lansky, Robert S. Schwartz, William E. Kraus, Eric J. Topol, Piedmont Heart Institute, Atlanta, GA, CardioDx Inc, Palo Alto, CA Abstract: Background: Coronary plaque burden can be measured indirectly by quantitative coronary angiography (QCA) and by coronary artery calcium (CAC) scoring by CT. We previously validated a real-time-PCR-based 23-geneexpression test, Corus CAD, to predict obstructive CAD using QCA (≥50% stenosis). Background: Coronary plaque burden can be measured indirectly by quantitative coronary angiography (QCA) and by coronary artery calcium (CAC) scoring by CT. We previously validated a real-time-PCR-based 23-geneexpression test, Corus CAD, to predict obstructive CAD using QCA (≥50% stenosis). Methods: In the validation cohort of the PREDICT study (NCT 00500617), 526 patients had gene expression score and QCA-derived plaque burden available and in 79 patients (49 cases, 30 controls), CAC score also. Plaque burden was defined as the sum of occluded luminal volumes for all QCA lesions; occluded volume is calculated from lesion length and reference and minimal vessel luminal diameter, assuming a symmetrical hourglass shape. Linear regression analysis was used to evaluate relationships. Results: In the 526 patients, there was significant correlation between gene expression score and QCA-derived plaque burden (p=1.4x10-8, R=0.38). In the CT subset, gene expression and CAC scores (range 0-3189; median=270) were correlated with R=0.63 (p=3x10-10). ROC analysis for the prediction of non-zero CAC by gene expression score showed an AUC 0.92. Both scores were significantly associated with disease burden by QCA (R=0.57 and 0.51,