Novel antidiabetic drugs introduced in the last decade have not only revolutionized the treatment of type 2 diabetes mellitus but have also changed our cardiovascular risk reduction strategy. Glucagon-like peptide-1 (GLP-1) receptor agonists reduce the risk of atherosclerotic diseases primarily through their complex anti-atherosclerotic effect due to their endothelial function-improving, anti-inflammatory, anti-thrombotic, and plaque-stabilizing effects. Sodium–glucose cotransporter 2 (SGLT2) inhibitors, on the other hand, have a favorable cardiovascular effect, mainly by increasing sodium excretion, reducing plasma volume, enhancing the use of ketone bodies as metabolic substrates in heart and kidney tissues, and reducing oxidative stress and uric acid serum levels. However, when using these two groups of drugs, important questions arise. What criteria should be used to decide on the administration of one or the other class of drugs? Which group of agents can be used more effectively to reduce our patients’ cardiovascular risk? What are the possible adverse effects? What can be gained by combining the two drugs? Our objective was to provide a current literature-based and comparative summary on the mechanisms of action, cardiovascular-risk-reducing efficacy, and safety profiles of these two drug classes, with an emphasis on identifying key factors influencing everyday clinical decision-making.

High-density lipoprotein (HDL)-bound apolipoprotein M/sphingosine 1-phosphate (ApoM/S1P) complex in cardiovascular diseases serves as a bridge between HDL and endothelial cells, maintaining a healthy endothelial barrier. To date, S1P and ApoM in patients with untreated heterozygous familial hypercholesterolemia (HeFH) have not been extensively studied. Eighty-one untreated patients with HeFH and 32 healthy control subjects were included in this study. Serum S1P, ApoM, sCD40L, sICAM-1, sVCAM-1, oxLDL, and TNFα concentrations were determined by ELISA. PON1 activities were measured spectrophotometrically. Lipoprotein subfractions were detected by Lipoprint. We diagnosed FH using the Dutch Lipid Clinic Network criteria. Significantly higher serum S1P and ApoM levels were found in HeFH patients compared to controls. S1P negatively correlated with large HDL and positively with small HDL subfractions in HeFH patients and the whole study population. S1P showed significant positive correlations with sCD40L and MMP-9 levels and PON1 arylesterase activity, while we found significant negative correlation between sVCAM-1 and S1P in HeFH patients. A backward stepwise multiple regression analysis showed that the best predictors of serum S1P were large HDL subfraction and arylesterase activity. Higher S1P and ApoM levels and their correlations with HDL subfractions and inflammatory markers in HeFH patients implied their possible role in endothelial protection.

Background: Familial hypercholesterolemia (FH) is an autosomal dominant trait characterized by elevated LDL-C concentrations and is associated with an increased risk of premature atherosclerosis. Progranulin (PGRN) is a multifunctional protein that is known to have various anti-atherogenic effects. To date, the use of serum PGRN in patients with FH has not been studied. Methods: In total, 81 untreated patients with heterozygous FH (HeFH) and 32 healthy control subjects were included in this study. Serum PGRN, sICAM-1, sVCAM-1, oxLDL and TNFα concentrations were determined by ELISA. Lipoprotein subfractions were detected by Lipoprint. We diagnosed FH using the Dutch Lipid Clinic Network criteria. Results: We could not find a significant difference between the PGRN concentrations of the HeFH patients and controls (37.66 ± 9.75 vs. 38.43 ± 7.74 ng/mL, ns.). We found significant positive correlations between triglyceride, TNFα, sVCAM-1, the ratio of small HDL subfraction and PGRN, while significant negative correlations were found between the ratio of large HDL subfraction and PGRN both in the whole study population and in FH patients. PGRN was predicted by sVCAM-1, logTNFα and the ratio of small HDL subfraction. Conclusions: The strong correlations between HDL subfractions, inflammatory markers and PGRN suggest that PGRN may exert its anti-atherogenic effect in HeFH through the alteration of HDL composition and the amelioration of inflammation rather than through decreasing oxidative stress.

Background: Systemic lupus erythematosus (SLE) is an autoimmune disorder associated with premature atherosclerosis and vascular impairment. However, the role of endocan, a biomarker of glycocalyx injury, is not completely clarified in the detection of vascular damage. Therefore, our aim was to investigate serum endocan in comparison with conventional inflammatory markers, arterial stiffness parameters, and carotid ultrasound findings in a cohort of young patients with SLE. Methods: We enrolled 47 clinically active young SLE patients (40 females and 7 males) in the study. Arterial stiffness indicated by augmentation index and pulse wave velocity (PWV) was measured by arteriography. Brachial artery flow-mediated dilatation and common carotid intima-media thickness were detected by ultrasonography. The serum concentrations of endocan, IL-6, MPO, MCP-1, MMP-3, -7, and -9, as well as TNFα, were measured by an enzyme-linked immunosorbent assay (ELISA). Results: We found significant negative correlations between serum endocan and both CH50 and C3. Serum endocan was higher in active SLE patients compared to inactive patients, however, the difference was not statistically significant (241.4 (183–295) vs. 200.3 (167–278) pg/mL; p = 0.313). Serum TNFα and hsCRP significantly correlated with PWV. However, we did not detect significant correlations between vascular diagnostic tests and serum endocan levels. Conclusions: Based on our results, serum endocan is associated with disease activity; however, further studies are needed to clarify the value of serum endocan in the cardiovascular risk estimation of SLE patients. Measurement of serum endocan, as well as the routine assessment of arterial stiffness parameters, should be integrated into the comprehensive management plans of young patients with SLE.

Stromal cell-derived factor-1 (SDF-1) is a chemokine that exerts multifaceted roles in atherosclerosis. However, its association with hyperlipidemia is contradictory. To date, serum SDF-1 and its correlations with lipid fractions and subfractions in heterozygous familial hypercholesterolemia (HeFH) have not been investigated. Eighty-one untreated patients with HeFH and 32 healthy control subjects were enrolled in the study. Serum SDF-1, oxidized LDL (oxLDL) and myeloperoxidase (MPO) were determined by ELISA. Lipoprotein subfractions were detected by Lipoprint. We diagnosed FH using the Dutch Lipid Clinic Network criteria. Significantly lower serum SDF-1 was found in HeFH patients compared to healthy controls. Significant negative correlations were detected between serum total cholesterol, triglycerides, LDL-cholesterol (LDL-C), apolipoprotein B100 (ApoB100) and SDF-1. Furthermore, serum SDF-1 negatively correlated with VLDL and IDL, as well as large LDL and large and intermediate HDL subfractions, while there was a positive correlation between mean LDL-size, small HDL and SDF-1. SDF-1 negatively correlated with oxLDL and MPO. A backward stepwise multiple regression analysis showed that the best predictors of serum SDF-1 were VLDL and oxLDL. The strong correlation of SDF-1 with lipid fractions and subfractions highlights the potential common pathways of SDF-1 and lipoprotein metabolism, which supports the role of SDF-1 in atherogenesis.

Background/Objectives: The clinical presentation of homozygous familial hypercholesterolemia (HoFH) and severe heterozygous familial hypercholesterolemia (sHeFH) often demonstrates substantial overlap, as low-density lipoprotein cholesterol (LDL-C) levels may fall within similar ranges in both conditions. Methods: In this single-center 10-year retrospective study at the University of Debrecen, Hungary, we present the clinical characteristics of patients with 6 HoFH and 6 sHeFH diagnosed by genetic testing, discuss the diagnostic limitations encountered in clinical practice, and outline the key components of therapeutic management. Results: The mean age at diagnosis was lower in the HoFH group (31.83 ± 19.5 vs. 41.83 ± 15.9 years). The differences in total cholesterol (13.48 ± 7.4 vs. 11.02 ± 3.5 mmol/L) and LDL-C levels (10.89 ± 6.6 vs. 8.58 ± 3.26 mmol/L) between the groups were not statistically significant. Interestingly, vascular complications were more frequent in sHeFH group as well (4 vs. 1 patients). In neither the HoFH nor the sHeFH group were we able to achieve the target LDL-C levels, due in part to the specific features of the reimbursement system, patient and parental preferences, the extremely high baseline LDL-C levels, and certain genetic characteristics. Conclusions: Our findings highlight the importance of genetic testing-based personalized therapy in these specific patient subpopulations. We emphasize that serum LDL-C alone is insufficient to distinguish between HoFH and sHeFH patients, and that therapeutic challenges should be anticipated in both groups arising partly from limited patient adherence as well as from financial constraints.