Can non-cholesterol sterols and lipoprotein subclasses distribution predict different patterns of cholesterol metabolism and statin therapy response?

Abstract

Cholesterol homeostasis disorders may cause dyslipidemia, atherosclerosis progression and coronary artery disease (CAD) development. Evaluation of non-cholesterol sterols (NCSs) as synthesis and absorption markers, and lipoprotein particles quality may indicate the dyslipidemia early development. This study investigates associations of different cholesterol homeostasis patterns with low-density (LDL) and high-density lipoproteins (HDL) subclasses distribution in statin-treated and statin-untreated CAD patients, and potential use of aforementioned markers for CAD treatment optimization. The study included 78 CAD patients (47 statin-untreated and 31 statin-treated) and 31 controls (CG). NCSs concentrations were quantified using gas chromatography- flame ionization detection (GC-FID). Lipoprotein subclasses were separated by gradient gel electrophoresis. In patients, cholesterol-synthesis markers were significantly higher comparing to CG. Cholesterol-synthesis markers were inversely associated with LDL size in all groups. For cholesterol homeostasis estimation, each group was divided to good and/or poor synthetizers and/or absorbers according to desmosterol and β-sitosterol median values. In CG, participants with reduced cholesterol absorption, the relative proportion of small, dense LDL was higher in those with increased cholesterol synthesis compared to those with reduced synthesis (p<0.01). LDL I fraction was significantly higher in poor synthetizers/poor absorbers subgroup compared to poor synthetizers/good absorbers (p<0.01), and good synthetizers/poor absorbers (p<0.01). Statin-treated patients with increased cholesterol absorption had increased proportion of LDL IVB (p<0.05). The results suggest the existence of different lipoprotein abnormalities according to various patterns of cholesterol homeostasis. Desmosterol/β-sitosterol ratio could be used for estimating individual propensity toward dyslipidemia development and direct the future treatment. © 2017 Walter de Gruyter GmbH, Berlin/Boston.