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Statins have contributed to the prevention of numerous atherosclerotic cardiovascular (CV) events and cardiovascular deaths in the past three decades. The benefit of statins is mainly mediated by the lowering of LDLc. According to scientific evidence, the current international guidelines recommend very low LDLc goals in patients at high/very high cardiovascular risk because they are associated with fewer CV events and improvements in atherosclerotic plaques. However, these goals often cannot be obtained with statins alone. Recent RCTs have demonstrated that these CV benefits can also be obtained with nonstatin LDLc-lowering drugs such as PCSK9 inhibitors (alirocumab and evolocumab), ezetimibe and bempedoic acid, while evidence with inclisiran is upcoming. Icosapent ethyl, a lipid metabolism modifier, has also shown an effect on event reduction. Physicians should take advantage of the currently available lipid-lowering therapies, choosing the drug or combination of drugs that is most appropriate for each patient according to his or her CV risk and baseline LDLc concentration. Strategies implementing combination therapies from early stages or even from the outset may increase the number of patients attaining LDLc goals, thereby preventing new CV episodes and improving existing atherosclerotic lesions.

Background: Brief interventions (BI) for risky drinkers in primary healthcare have been demonstrated to be cost-effective but they are still poorly implemented. Digital BI seems to be a complementary strategy to overcome some barriers to implementation but there is a scarcity of studies in clinical environments. We present the results of a randomized controlled non-inferiority trial which tests the non-inferiority of facilitated access to a digital intervention (experimental condition) for risky drinkers against a face-to-face BI (control condition) provided by primary healthcare professionals. Method: In a non-inferiority randomized controlled trial, unselected primary healthcare patients (≥ 18 years old) were given a brief introduction and asked to log on to the study website to fill in the 3-item version of the Alcohol Use Disorders Identification Test. Positively screened patients (4+ for women and 5+ for men) received further online assessment (AUDIT, socio-demographic characteristics and EQ-5D-5L) and were automatically randomized to either face-to-face or digital BI (1:1). The primary outcome was the proportion of patients classified as risky drinkers by the digitally administered AUDIT at month 3. A multiple imputation approach for the missing data was performed. Results: Of the 4499 patients approached by 115 healthcare professionals, 1521 completed the AUDIT-C. Of the 368 positively screened patients, 320 agreed to participate and were randomized to either intervention. At month 3, there were more risky drinkers in the experimental group (59.8%) than in the control group (52%), which was similar to the distribution at baseline and less than the pre-specified margin of 10%. The difference was not significant when accounting for possible confounders. Conclusion: Digital BI was not inferior to face-to-face BI, in line with previous findings and the a priori hypothesis. However, the low power of the final sample, due to the low recruitment and loss to follow-up, limits the interpretation of the findings. New approaches in this field are required to ensure the effective implementation of digital interventions in actual practice.

Determination of lipoprotein particle size and number using advanced lipoprotein tests (ALTs) is of particular importance to improve cardiovascular risk prediction. Here we present the Liposcale test, a novel ALT based on 2D diffusion-ordered 1H NMR spectroscopy. Our method uses diffusion coefficients to provide a direct measure of the mean particle sizes and numbers. Using 177 plasma samples from healthy individuals and the concentration of ApoB and ApoA from isolated lipoprotein fractions, our test showed a stronger correlation between the NMR-derived lipoprotein particle numbers and apolipoprotein concentrations than the LipoProfile® test commercialized by Liposcience. We also converted LDL particle numbers to ApoB equivalents (milligrams per deciliter) and our test yielded similar values of LDL-ApoB to the LipoProfile® test (absolute mean bias of 8.5 and 7.4 mg/dl, respectively). In addition, our HDL particle number values were more concordant with the calibrated values determined recently using ion mobility. Finally, principal component analysis distinguished type 2 diabetic patients with and without atherogenic dyslipidemia (AD) on a second cohort of 307 subjects characterized using the Liposcale test (area under the curve = 0.88) and showed concordant relationships between variables explaining AD. Altogether, our method provides reproducible and reliable characterization of lipoprotein particles and it is applicable to pathological states such as AD.

The lipid profile of familial combined hyperlipidemia (FCHL) shares some characteristics with atherogenic dyslipidemia seen in diabetes, metabolic syndrome, and obesity. Adipocyte fatty acid-binding protein 4 (FABP4) appears to be a determinant of atherogenic dyslipidemia. We examined relationships between FABP4 plasma concentrations, dyslipidemia, and metabolic variables in patients with FCHL. We studied 273 unrelated FCHL patients and 118 control subjects. FABP4 was higher in FCHL than controls, with mean levels of 21.8 (10.1) μg/l and 19.2 (9.2) μg/l, respectively (adjusted P= 0.012). In FCHL, FABP4 correlated to body mass index (BMI), waist circumference, insulin levels, and homeostasis model assessment (HOMA) index (all P< 0.05), but not to lipid levels, whereas in obese patients, FABP4 correlated to triglyceride levels (r = 0.303, P= 0.014) and very low density lipoprotein size (r = 0.502, P = 0.001), as determined by nuclear magnetic resonance. Associations of FABP4 with BMI and waist circumference, but not with insulin levels, persisted in this subgroup. Plasma FABP4 does not influence the lipid phenotype of FCHL. In a small subgroup of obese FCHL, FABP4 levels were associated with triglyceride-rich lipoproteins independent of insulin resistance. These results support a hyperlipidemic mechanism of FCHL different from similar metabolic conditions where fat mass is strongly related to FABP4 and hypertriglyceridemia.

The aim of this study was to evaluate the impact of adipocyte fatty acid binding protein 4 (FABP4) on the lipid profile in type 2 diabetic subjects. Plasma levels of FABP4 and adiponectin and an extensive lipid profile were analyzed in 169 type 2 diabetic subjects and 105 controls. Type 2 diabetic subjects were categorized according the presence of atherogenic dyslipidemia. Univariate statistical analyses, partial correlation tests, and binary logistic regression models were applied. In type 2 diabetic subjects, FABP4 was positively correlated with plasma triglycerides (P = 0.007), apolipoprotein C-III (apoC-III) (P = 0.009), and all the components of triglyceride-rich lipoproteins, including VLDL triglycerides (P = 0.002), VLDL-cholesterol (P = 0.001), and VLDL apoB (P = 0.001). FABP4 was inversely correlated with apoA-I (P = 0.038), HDL-cholesterol (P = 0.002), and HDL apoA-I (P = 0.010) in type 2 diabetic subjects. These correlations are not significantly affected by age, gender, body mass index, adiponectin, insulin, or any pharmacological treatment. The associations are even stronger when the FABP4/adiponectin ratio is considered. None of these associations were observed in controls. High FABP4 and low adiponectin levels are independent predictors of atherogenic dyslipidemia. In conclusion, FABP4 plasma concentrations hold strong potential for development as a clinical biomarker for atherogenic dyslipidemia, independent of obesity and insulin resistance, in type 2 diabetic subjects.