Lipoprotein Sub-Fractions by Ion-Mobility Analysis and Its Association with Subclinical Coronary Atherosclerosis in High-Risk Individuals

Aims: There is limited knowledge about the association of lipoprotein particles and markers of coronary atherosclerosis such as coronary artery calcification (CAC) in relatively young high-risk persons. This study examines the association of lipoprotein subfractions and CAC in high cardiometabolic risk individuals. Methods: The study presents analysis from baseline data of a randomized trial targeted at high-risk workers. Employees of Baptist Health South Florida with metabolic syndrome or diabetes were recruited. At baseline, all 182 participants had lipoprotein subfraction analysis using the ion mobility technique and participants above 35 years (N = 170) had CAC test done. Principal components (PC) were computed for the combination of lipoprotein subclasses. Multiple bootstrapped regression analyses (BSA) were conducted to assess the relationship between lipoprotein subfractions and CAC. Results: The study population (N = 170) was largely female (84%) with a mean age of 58 years. Three PCs accounted for 88% variation in the sample. PC2, with main contributions from VLDL partides in the positive direction and large LDL particles in the negative direction was associated with a 22% increase in CAC odds (P value < 0.05 in 100% of BSA). PC3, with main contributions from HDL lipoprotein particles in the positive direction and small/medium LDL and large IDL particles in the negative direction, was associated with a 9% reduction in CAC odds (P < 0.05 in 88% of BSA). PC1, which had approximately even contributions from HDL, LDL, IDL and VLDL lipoprotein subfractions in the positive direction, was not associated with CAC. Conclusion: In a relatively young but high-risk population, a lipoprotein profile predominated by triglyceride-rich lipoproteins was associated with increased risk of CAC, while one predominated by HDL lipoproteins offered modest protection. Lipoprotein sub-fraction analysis may help to further discriminate patients who require more intensive cardiovascular work-up and treatment.