Copper-driven risk of coronary artery calcification: Multi-metal mixture analysis and threshold identification

The relationship between metal exposure and coronary artery calcification (CAC) remains limited with inconsistent conclusions.

In this case-control study conducted at Aerospace Wuxi Health Management Centre, blood metal concentrations were measured in 909 participants. CAC scores were measured through unenhanced electrocardiographically gated multi-slice CT (uCT 710). The associations with CAC risk were assessed using logistic regression, restricted cubic splines (RCS), and mixture models including Weighted quantile sum (WQS) regression, Quantile g-computation (QGC), and Bayesian kernel machine regression (BKMR). A derivative method based on the RCS model was used to identify effect thresholds.

Multi-model analysis revealed copper (Cu) as the principal metal associated with CAC, contributing a weight of 0.52 in the metal mixture. A critical dose-response threshold was identified at 12.5 μmol/L, below which each unit increase in Cu concentration raised CAC risk by 50.8 % (odds ratio = 1.51). Participants with Cu levels in the highest quartile (≥16.6 μmol/L) had a 2.13-fold greater risk of CAC compared to those in the lowest quartile. These findings were consistent across WQS regression, BKMR, and fully adjusted logistic models, all confirming the significant and predominant role of Cu.

Exposure to the mixture of Mg, Ca, Zn, Cu, and Fe was positively associated with CAC risk, largely attributable to Cu.