Multicenter validation of the diagnostic accuracy of a blood-based gene expression test for assessing obstructive...

Area of Science:

• Cardiovascular disease research
• Molecular diagnostics
• Biomarker discovery

Background:

• Diagnosing obstructive coronary artery disease (CAD) is challenging, often requiring invasive procedures.
• Peripheral blood gene expression has emerged as a potential noninvasive biomarker for CAD.
• Current diagnostic methods necessitate a combination of noninvasive imaging and coronary angiography.

Purpose of the Study:

• To validate a 23-gene expression-based classification test for diagnosing obstructive CAD.
• To assess the test's diagnostic performance in nondiabetic patients.
• To determine if the test improves upon existing clinical risk assessment models.

Main Methods:

• A multicenter prospective trial involving 526 nondiabetic patients undergoing coronary angiography.
• Blood samples were analyzed using real-time polymerase chain reaction to measure gene expression.
• Receiver-operating characteristic (ROC) analysis was used to evaluate the classifier's accuracy.
• The test's ability to add diagnostic value to clinical factors was assessed.

Main Results:

• The gene expression test demonstrated an area under the ROC curve (AUC) of 0.70 ± 0.02.
• The test improved obstructive CAD prediction when added to the Diamond-Forrester method (AUC 0.72 vs. 0.66) and an expanded clinical model (AUC 0.745 vs. 0.732).
• Significant net reclassification improvement was observed (P < 0.001).

Conclusions:

• A noninvasive, whole-blood gene expression test shows potential for assessing obstructive CAD in select patients.
• The test may aid in identifying nondiabetic patients without known CAD who require further investigation.
• Exclusion criteria included diabetes, chronic inflammatory disorders, and elevated cardiac markers.