BackgroundLevels of LDL (low‐density lipoprotein) cholesterol in the population are declining, and increasing attention is being focused on residual lipid‐related pathways of atherosclerotic cardiovascular disease risk beyond LDL cholesterol. Among individuals with low (<130 mg/dL) LDL cholesterol, we undertook detailed profiling of circulating atherogenic lipoproteins in relation to incident cardiovascular disease in 2 populations.Methods and ResultsWe performed proton nuclear magnetic resonance spectroscopy to quantify concentrations of LDL and VLDL (very low‐density lipoprotein) particle subclasses in 11 984 JUPITER trial participants (NCT00239681). Adjusted Cox models examined cardiovascular disease risk associated with lipoprotein measures according to treatment allocation. Risk (adjusted hazard ratio [95%CI] per SD increment) among placebo‐allocated participants was associated with total LDL particles (1.19 [1.02, 1.38]) and total VLDL particles (1.21 [1.04, 1.41]), as well as apolipoprotein B, non–high‐density lipoprotein cholesterol, and triglycerides, but not LDL‐c. Rosuvastatin reduced LDL measures but had variable effects on triglyceride and VLDL measures. On‐statin levels of the smallest VLDL particle subclass were associated with a 68% per‐SD (adjusted hazard ratio 1.68 [1.28, 2.22]) increase in residual risk—this risk was related to VLDL cholesterol and not triglyceride or larger VLDL particles. There was evidence that residual risk prediction during statin therapy could be significantly improved through the inclusion of key VLDL measures (Harrell C‐index 0.780 versus 0.712; P<0.0001). In an independent, prospective cohort of 4721 individuals referred for cardiac catheterization (CATHGEN), similar patterns of lipoprotein‐related risk were observed.ConclusionsAtherogenic lipoprotein particle concentrations were associated with cardiovascular disease risk when LDL cholesterol was low. VLDL lipoproteins, particularly the smallest remnant subclass, may represent unused targets for risk prediction and potential therapeutic intervention for reducing residual risk.Clinical Trial Registration URL: http://www.clinicaltrials.gov. Unique identifier: NCT00239681.
Background Raising the cholesterol of HDL particles is targeted as a cardiovascular disease prevention strategy. However, HDL particles are heterogeneous in composition and structure, which may relate to differences in antiatherogenic potential. We prospectively evaluated the association of HDL subclasses, defined by a recently proposed nomenclature, with incident coronary heart disease (CHD). Methods and Results Baseline HDL particle concentrations were measured by nuclear magnetic resonance spectroscopy and categorized into five subclasses (very large, large, medium, small, and very small) among 26,332 initially healthy women. During a median follow-up of 17 years, 969 cases of incident CHD (myocardial infarction, revascularization, and CHD death) were ascertained. In Cox models that adjusted for age, race/ethnicity, blood pressure, smoking, postmenopausal status, and hormone therapy, associations with incident CHD were inverse (p-trend<0.0001) for concentrations of very large (hazard ratio [HR] for top versus bottom quartile 0.49, 95% confidence interval [CI] 0.41–0.60), large (0.54, 0.45–0.64), and medium (0.69, 0.58–0.83) HDL subclasses. Conversely, HRs (95% CIs) for small and very small HDL were 1.22 (1.01–1.46, p-trend=0.08) and 1.67 (1.39–2.02, p-trend<0.0001), respectively. However, after additionally adjusting for metabolic and lipoprotein variables, associations for the spectrum of large, medium, and small HDL subclasses were inverse (p-trend<0.05 for large and small, and 0.07 for medium), while subclasses at either end of the spectrum were not associated with CHD (p-trend=0.97 for very large and 0.21 for very small HDL). Conclusion In this prospective study, associations with incident CHD differed by HDL particle subclass, which may be relevant for developing HDL-modulating therapies.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.