Human HDL containing a novel apoC-I isoform induces smooth muscle cell apoptosis.

AIMS: We discovered that some adults with coronary heart disease (CHD) have a high density lipoprotein (HDL) subclass which induces human aortic smooth muscle cell (ASMC) apoptosis in vitro. The purpose of this investigation was to determine what properties differentiate apoptotic and non-apoptotic HDL subclasses in adults with and without CHD. METHODS AND RESULTS: Density gradient ultracentrifugation was used to measure the particle density distribution and to isolate two HDL subclass fractions, HDL2 and HDL3, from 21 individuals, including 12 without CHD. The HDL fractions were incubated with ASMCs for 24 h; apoptosis was quantitated relative to C2-ceramide and tumour necrosis factor-alpha (TNF-α). The observed effect of some HDL subclasses on apoptosis was ∼6-fold greater than TNF-α and ∼16-fold greater than the cell medium. We observed that apoptotic HDL was (i) predominately associated with the HDL2 subclass; (ii) almost exclusively found in individuals with a higher apoC-I serum level and a novel, higher molecular weight isoform of apoC-I; and (iii) more common in adults with CHD, the majority of whom had high (>60 mg/dL) HDL-C levels. CONCLUSIONS: Some HDL subclasses enriched in a novel isoform of apoC-I induce extensive ASMC apoptosis in vitro. Individuals with this apoptotic HDL phenotype generally have higher apoC-I and HDL-C levels consistent with an inhibitory effect of apoC-I on cholesteryl ester transfer protein activity. The association of this phenotype with processes that can promote plaque rupture may explain a source of CHD risk not accounted for by the classical risk factors.

Developing high performance lipoprotein density profiling for use in clinical studies relating to cardiovascular disease.

Early detection of the beginning stage of cardiovascular disease (CVD) is an approach to prevention because the process is reversible at this stage. Consequently, several methods for screening for CVD have been introduced in recent years incorporating different analytical methods for characterizing the population of blood-borne lipoprotein subclasses. The gold standard method for lipoprotein subclassification is based on lipoprotein density measured by sedimentation equilibrium using the ultracentrifuge. However, this method has not been adopted for clinical studies because of difficulties in achieving the precision required for distinguishing individuals with and without CVD particularly when statistical classification methods are used. The objective of this study was to identify and improve the major factors that influence the precision of measurement of lipoprotein density profile by sedimentation equilibrium analysis and labeling with a fluorescent probe. The study has two phases, each contributing to precision. The first phase focuses on the ultracentrifugation-related variables, and the second phase addresses those factors involved in converting the fluorescent lipoprotein density profile to a digital format compatible with statistical analysis. The overall improvement in precision was on the order of a factor of 5, sufficient to be effectively applied to ongoing classification studies relating to CVD risk assessment.