High-Density Lipoprotein and Long-Term Incidence and Progression of Aortic Valve Calcification: The Multi-Ethnic Study of Atherosclerosis.

Abstract

Aortic valve calcification (AVC) shares pathological features with atherosclerosis. Lipoprotein components have been detected in aortic valve tissue, including HDL (high-density lipoprotein). HDL measures have inverse associations with cardiovascular disease, but relationships with long-term AVC progression are unclear. We investigated associations of HDL cholesterol, HDL-particle number and size, apoC3-defined HDL subtypes, and, secondarily, CETP (cholesteryl ester transfer protein) mass and activity, with long-term incidence and progression of AVC. We used linear mixed-effects models to evaluate the associations of baseline HDL indices with AVC. AVC was quantified by Agatston scoring of up to 3 serial computed tomography scans over a median of 8.9 (maximum 11.2) years of follow-up in the Multi-Ethnic Study of Atherosclerosis (n=6784). After adjustment, higher concentrations of HDL-C (high-density lipoprotein cholesterol), HDL-P (HDL particles), large HDL-P, and apoC3-lacking HDL-C were significantly associated with lower incidence/progression of AVC. Neither small or medium HDL-P nor apoC3-containing HDL-C was significantly associated with AVC incidence/progression. When included together, a significant association was observed only for HDL-C, but not for HDL-P. Secondary analyses showed an inverse relationship between CETP mass, but not activity, and AVC incidence/progression. In exploratory assessments, inverse associations for HDL-C, HDL-P, large HDL-P, and apoC3-lacking HDL with AVC incidence/progression were more pronounced for older, male, and White participants. ApoC3-containing HDL-C only showed a positive association with AVC in these subgroups. In a multiethnic population, HDL-C, HDL-P, large HDL-P, and apoC3-lacking HDL-C were inversely associated with long-term incidence and progression of AVC. Further investigation of HDL composition and mechanisms could be useful in understanding pathways that slow AVC.