Three components of glucose dynamics – value, variability, and autocorrelation – are independently associated with coronary plaque vulnerability

Abstract

SUMMARYImpaired glucose homeostasis leads to many complications, with coronary artery disease (CAD) being a major contributor to healthcare costs. However, current CAD screening methods lack efficacy. Here, we predicted CAD using easy-to-measure indices, including continuous glucose monitoring (CGM)-derived indices. We found that CGM-derived indices, particularly ADRR and AC_Var, exhibited stronger predictive capabilities for CAD compared to commonly used diabetes diagnostic indices such as fasting blood glucose (FBG), hemoglobin A1C (HbA1c), and plasma glucose level at 120 min during oral glucose tolerance tests (PG120). Factor analysis identified three distinct components underlying glucose dynamics – value, variability, and autocorrelation – each independently associated with CAD. Remarkably, ADRR was influenced by the first two components, and AC_Var was influenced by the third component. FBG, HbA1c, and PG120 were influenced only by the value component, making them insufficient for CAD prediction. CGM-derived indices reflecting the three components can outperform traditional diabetes diagnostic methods in CAD prediction. (150/150 words)