Anti-APOB monoclonal antibody, clone 7H7

Atherogenic LDL particles are physicochemically and metabolically heterogeneous. Can bioactive lipid cargo differentiate LDL subclasses, and thus potential atherogenicity? What is the effect of statin treatment? Obese hypertriglyceridemic hypercholesterolemic males [n = 12; lipoprotein (a) <10 mg/dl] received pitavastatin calcium (4 mg/day) for 180 days in a single-phase unblinded study. The lipidomic profiles (23 lipid classes) of five LDL subclasses fractionated from baseline and post-statin plasmas were determined by LC-MS. At baseline and on statin treatment, very small dense LDL (LDL5) was preferentially enriched (up to 3-fold) in specific lysophospholipids {LPC, lysophosphatidylinositol (LPI), lysoalkylphosphatidylcholine [LPC(O)]; 9, 0.2, and 0.14 mol per mole of apoB, respectively; all P < 0.001 vs. LDL1-4}, suggesting elevated inflammatory potential per particle. In contrast, lysophosphatidylethanolamine was uniformly distributed among LDL subclasses. Statin treatment markedly reduced absolute plasma concentrations of all LDL subclasses (up to 33.5%), including LPC, LPI, and LPC(O) contents (up to -52%), consistent with reduction in cardiovascular risk. Despite such reductions, lipotoxic ceramide load per particle in LDL1-5 (1.5-3 mol per mole of apoB; 3-7 mmol per mole of PC) was either conserved or elevated. Bioactive lipids may constitute biomarkers for the cardiometabolic risk associated with specific LDL subclasses in atherogenic dyslipidemia at baseline, and with residual risk on statin therapy.

Background LDL-C lowering is the main measure in cardiovascular disease prevention but a residual risk of ischemic events still remains. Alterations of lipoproteins, specially, increase in small dense LDL (sdLDL) particles are related to this risk. Objective To investigate the potential use of sdLDL cholesterol concentration (sdLDL-C) isolated by an easy precipitation method and to assess the impact of a set of clinical and biochemical variables determined by NMR on sdLDL concentration. Methods sdLDL-C and NMR lipid profile were performed in 85 men samples. Association among them was evaluated using Pearson coefficients (r(xy)). A multivariate regression was performed to identify the influence of NMR variables on sdLDL-C. Results A strong association between sdLDL-C and LDLLDL-P (r(xy) = 0.687) and with LDL-Z (r(xy) = -0.603) was found. The multivariate regression explained a 56.8% in sdLDL-C variation (P = 8.77.10-12). BMI, ApoB, triglycerides, FFA, and LDL-Z showed a significant contribution. The most important ones were ApoB and LDL-Z; a 1nm increase (LDL-Z) leads to decrease 126 nmol/L in sdLDL-C. Conclusion The association between sdLDL-C, LDL-Z, and LDL-P is clear. From a large number of variables, especially LDL-Z and apoB influence on sdLDL-C. Results show that the smaller the LDL size, the higher their cholesterol concentration. Therefore, sdLDL-C determination by using this easy method would be useful to risk stratification and to uncover cardiovascular residual risk.