The quality, uniqueness, and causality of NMR-based prediction models for low-density lipoprotein cholesterol subfractions in human blood plasma

Abstract

Low-density lipoprotein (LDL) cholesterol (chol) subfractions are risk biomarkers for cardiovascular diseases (CVD). A reference analysis, ultracentrifugation (UC), is laborious and may be replaced with a rapid prediction using proton NMR spectra of human blood plasma. However, the quality and uniqueness of these prediction models of biologically related subfractions remains unknown. This study, using two independent cohorts (n = 277), investigates the inter-correlations between LDL cholesterol in the main fraction and five subfractions, as well as the independence of their NMR-based prediction models. The results reveal that the prediction models utilize both shared and unique spectral information from the NMR spectra to determine concentrations of LDL subfractions. Analysis of variance contributions for prediction and causality assessments demonstrate that the NMR spectra contain unique predictive information for the LDL1chol, LDL2chol, and LDL5chol subfractions. In contrast, the spectral signatures for LDL3chol and LDL4chol are either insufficient or confounded. Our findings indicate that these five CVD biomarkers represent two independent clusters, reflecting their biosynthetic pathways, and confirm the presence of causal relationships between certain LDL chol subfractions. This highlights the importance of employing caution when interpreting the concentrations of specific LDL subfractions as standalone biomarkers for CVD risk.