Physicochemical Properties of Lipoproteins Assessed by Nuclear Magnetic Resonance as a Predictor of Premature Cardiovascular Disease. PRESARV-SEA Study.

Some lipoprotein disorders related to the residual risk of premature cardiovascular disease (PCVD) are not detected by the conventional lipid profile. In this case-control study, the predictive power of PCVD of serum sdLDL-C, measured using a lipoprotein precipitation method, and of the physicochemical properties of serum lipoproteins, analyzed by nuclear magnetic resonance (NMR) techniques, were evaluated. We studied a group of patients with a first PCVD event (n = 125) and a group of control subjects (n = 190). Conventional lipid profile, the size and number of Very Low Density Lipoproteins (VLDL), Low Density Lipoproteins (LDL), High Density Lipoproteins (HDL) particles, and the number of particles of their subclasses (large, medium, and small) were measured. Compared to controls, PCVD patients had lower concentrations of all LDL particles, and smaller and larger diameter of LDL and HDL particles, respectively. PCVD patients also showed higher concentrations of small dense LDL-cholesterol (sdLDL), and triglycerides (Tg) in LDL and HDL particles (HDL-Tg), and higher concentrations of large VLDL particles. Multivariate logistic regression showed that sdLDL-C, HDL-Tg, and large concentrations of LDL particles were the most powerful predictors of PCVD. A strong relationship was observed between increased HDL-Tg concentrations and PCVD. This study demonstrates that beyond the conventional lipid profile, PCVD patients have other atherogenic lipoprotein alterations that are detected by magnetic resonance imaging (MRI) analysis.

GlycA Levels during the Earliest Stages of Rheumatoid Arthritis: Potential Use as a Biomarker of Subclinical Cardiovascular Disease.

This study aimed at evaluating the clinical relevance of glycoprotein profiles during the earliest phases of rheumatoid arthritis (RA) as biomarkers of cardiovascular (CV) risk and treatment response. Then, GlycA and GlycB serum levels were measured using 1H-nuclear magnetic resonance in 82 early RA patients, 14 clinically-suspect arthralgia (CSA), and 28 controls. Serum glycosyltransferase activity was assessed by a colorimetric assay. Subclinical CV disease was assessed by Doppler-ultrasound. We found that GlycA and GlycB serum levels were increased in RA (both p < 0.001), but not in CSA, independently of cardiometabolic risk factors. Increased serum glycosyltransferase activity paralleled GlycA (r = 0.405, p < 0.001) and GlycB levels (r = 0.327, p = 0.005) in RA. GlycA, but not GlycB, was associated with atherosclerosis occurrence (p = 0.012) and severity (p = 0.001). Adding GlycA to the mSCORE improved the identification of patients with atherosclerosis over mSCORE alone, increasing sensitivity (29.7 vs. 68.0%) and accuracy (55.8 vs. 76.6%) and allowing reclassification into more appropriate risk categories. GlycA-reclassification identified patients with impaired lipoprotein metabolism. Finally, baseline GlycA levels predicted poor clinical response upon anti-rheumatic treatment at 6 and 12 months in univariate and multivariate analysis. In sum, increased GlycA levels during the earliest stage of RA can be considered a powerful biomarker for CV risk stratification and treatment response.