HDL quality features revealed by proteome-lipidome connectivity are associated with atherosclerotic disease

Lipoprotein, especially high-density lipoprotein (HDL), particles are composed of multiple heterogeneous subgroups containing various proteins and lipids. The molecular distribution among these subgroups is closely related to cardiovascular disease (CVD). Here, we established high-resolution proteomics and lipidomics (HiPL) methods to depict the molecular profiles across lipoprotein (Lipo-HiPL) and HDL (HDL-HiPL) subgroups by optimizing the resolution of anion-exchange chromatography and comprehensive quantification of proteins and lipids on the omics level. Furthermore, based on the Pearson correlation coefficient analysis of molecular profiles across high-resolution subgroups, we achieved the relationship of proteome-lipidome connectivity (PLC) for lipoprotein and HDL particles. By application of these methods to high-fat, high-cholesterol diet-fed rabbits and acute coronary syndrome (ACS) patients, we uncovered the delicate dynamics of the molecular profile and reconstruction of lipoprotein and HDL particles. Of note, the PLC features revealed by the HDL-HiPL method discriminated ACS from healthy individuals better than direct proteome and lipidome quantification or PLC features revealed by the Lipo-HiPL method, suggesting their potential in ACS diagnosis. Together, we established HiPL methods to trace the dynamics of the molecular profile and PLC of lipoprotein and even HDL during the development of CVD.

Automated summary

By establishing high-resolution proteomics and lipidomics methods, researchers were able to characterize the molecular profiles of lipoprotein and HDL particles, potentially aiding in the diagnosis of cardiovascular disease by quantifying proteins and lipids across subgroups.