Obesity is a growing health problem worldwide. It is associated with an increased cardiovascular risk on the one hand of obesity itself and on the other hand of associated medical conditions (hypertension, diabetes, insulin resistance, and sleep apnoea syndrome). Obesity has an important role in atherosclerosis and coronary artery disease. Obesity leads to structural and functional changes of the heart, which causes heart failure. The altered myocardial structure increases the risk of atrial fibrillation and sudden cardiac death. However, obesity also has a protective effect on the clinical outcome of underlying cardiovascular disease, the phenomenon called obesity paradox. The improved cardiac imaging techniques allow the early detection of altered structure and function of the heart in obese patients. In this review, we attempt to summarize the relationship between obesity and cardiovascular diseases and outline the underlying mechanisms. The demonstrated new techniques of cardiac diagnostic procedures allow for the early detection and treatment of subclinical medical conditions and, therefore, the prevention of cardiovascular events.

Margatoxin (MgTx), an alpha-KTx scorpion toxin, is considered a selective inhibitor of the Kv1.3K + channel. This peptide is widely used in ion channel research; however, a comprehensive study of its selectivity with electrophysiological methods has not been published yet. The lack of selectivity might lead to undesired side effects upon therapeutic application or may lead to incorrect conclusion regarding the role of a particular ion channel in a physiological or pathophysiological response either in vitro or in vivo. Using the patch-clamp technique we characterized the selectivity profile of MgTx using L929 cells expressing mKv1.1 channels, human peripheral lymphocytes expressing Kv1.3 channels and transiently transfected tsA201 cells expressing hKv1.1, hKv1.2, hKv1.3, hKv1.4-IR, hKv1.5, hKv1.6, hKv1.7, rKv2.1, Shaker-IR, hERG, hKCa1.1, hKCa3.1 and hNav1.5 channels. MgTx is indeed a high affinity inhibitor of Kv1.3 (Kd = 11.7 pM) but is not selective, it inhibits the Kv1.2 channel with similar affinity (Kd = 6.4 pM) and Kv1.1 in the nanomolar range (Kd = 4.2 nM). Based on our comprehensive data MgTX has to be considered a non-selective Kv1.3 inhibitor, and thus, experiments aiming at elucidating the significance of Kv1.3 in in vitro or in vivo physiological responses have to be carefully evaluated.

Adult growth hormone deficiency (AGHD) is considered a rare endocrine disorder involving patients with childhood-onset and adult-onset growth hormone deficiency (AoGHD) and characterized by adverse cardiometabolic risk profile. Besides traditional cardiovascular risk factors, endothelial dysfunction, low-grade inflammation, impaired adipokine profile, oxidative stress and hypovitaminosis D may also contribute to the development of premature atherosclerosis and higher cardiovascular risk in patients with AGHD. Growth hormone replacement has been proved to exert beneficial effects on several cardiovascular risk factors, but it is also apparent that hormone substitution in itself does not eliminate all cardiometabolic abnormalities associated with the disease. Novel biomarkers and diagnostic techniques discussed in this review may help to evaluate individual cardiovascular risk and identify patients with adverse cardiometabolic risk profile. In the absence of disease-specific guidelines detailing how to assess the cardiovascular status of these patients, we generally recommend close follow-up of the cardiovascular status as well as low threshold for a more detailed evaluation.

Background. The elevated level of plasminogen activator inhibitor-1 (PAI-1) in obese subjects with metabolic syndrome and in patients with type 2 diabetes is well established. The association of plasma PAI-1 and lipid metabolism is still unclear. The aim of the present study was to determine the relationship between plasma PAI-1 levels and the distribution of lipoprotein subfractions in obese and lean nondiabetic individuals.Subjects and Methods. We enrolled fifty nondiabetic obese patients and thirty-two healthy volunteers. Lipoprotein subfractions were detected with Lipoprint System. Plasma PAI-1, tumor necrosis factor-α(TNF-α), interleukin-6 (IL-6), and myeloperoxidase (MPO) concentrations were determined with enzyme-linked immunosorbent assay (ELISA), while serum paraoxonase-1 (PON1) activities were measured by spectrophotometry.Results. The TNF-α, IL-6, oxidized low-density lipoprotein (oxLDL), and MPO levels were found to be significantly higher, while PON1 paraoxonase and arylesterase activities were nonsignificantly lower in the obese patients. Strong significant negative correlations were found between plasma PAI-1 concentration and mean LDL size, as well as between PAI-1 concentrations and the levels of the large and intermediate high-density lipoprotein (HDL) subfractions. In multiple regression analysis, PAI-1 was predicted by waist circumference and intermediate HDL subfraction.Conclusion. The significant correlations between PAI-1 levels and lipoprotein subfractions indicate the link between PAI-1 and lipid metabolism in obesity.

Background: Afamin is a liver-produced bioactive protein and features α- and γ-tocopherol binding sites. Afamin levels are elevated in metabolic syndrome and obesity and correlate well with components of metabolic syndrome. Afamin concentrations, correlations between afamin and vitamin E, afamin and lipoprotein subfractions in non-diabetic, obese patients have not been fully examined. Methods: Fifty non-diabetic, morbidly obese patients and thirty-two healthy, normal-weight individuals were involved in our study. The afamin concentrations were measured by ELISA. Lipoprotein subfractions were determined with gel electrophoresis. Gas chromatography–mass spectrometry was used to measure α- and γ tocopherol levels. Results: Afamin concentrations were significantly higher in the obese patients compared to the healthy control (70.4 ± 12.8 vs. 47.6 ± 8.5 μg/mL, p < 0.001). Positive correlations were found between afamin and fasting glucose, HbA1c, hsCRP, triglyceride, and oxidized LDL level, as well as the amount and ratio of small HDL subfractions. Negative correlations were observed between afamin and mean LDL size, as well as the amount and ratio of large HDL subfractions. After multiple regression analysis, HbA1c levels and small HDL turned out to be independent predictors of afamin. Conclusions: Afamin may be involved in the development of obesity-related oxidative stress via the development of insulin resistance and not by affecting α- and γ-tocopherol levels.

Metabolomics strategies are widely used to examine obesity and type 2 diabetes (T2D). Patients with obesity (n = 31) or T2D (n = 26) and sex- and age-matched controls (n = 28) were recruited, and serum and tear samples were collected. The concentration of 23 amino acids and 10 biogenic amines in serum and tear samples was analyzed. Statistical analysis and Pearson correlation analysis along with network analysis were carried out. Compared to controls, changes in the level of 6 analytes in the obese group and of 10 analytes in the T2D group were statistically significant. For obesity, the energy generation, while for T2D, the involvement of NO synthesis and its relation to insulin signaling and inflammation, were characteristic. We found that BCAA and glutamine metabolism, urea cycle, and beta-oxidation make up crucial parts of the metabolic changes in T2D. According to our data, the retromer-mediated retrograde transport, the ethanolamine metabolism, and, consequently, the endocannabinoid signaling and phospholipid metabolism were characteristic of both conditions and can be relevant pathways to understanding and treating insulin resistance. By providing potential therapeutic targets and new starting points for mechanistic studies, our results emphasize the importance of complex data analysis procedures to better understand the pathomechanism of obesity and diabetes.