The metabolic syndrome (MetS) has become one of the most important clinical issues in the cardiovascular field for this decade because of the marked increase in cardiovascular (CV) risk associated with a clustering of risk factors. The aim of the current study was to evaluate the relationship between MetS and its components and cardiovascular disease (CVD). This population-based cross-sectional study was based on data from two studies carried out in Russia (ESSE-RF) and Italy (PLIC). One sample from each cohort was selected, matching individuals by sex and age. A comparison between samples of MetS components distribution and CV risk, according to SCORE chart, has been conducted. A total of 609 individuals (mean [SD] age 55 [8] years, about 39% males) for each cohort were selected. Almost half of PLIC cohort participants belonged to the moderate CV risk group (47% vs 27%), while in ESSE-RF cohort a relatively higher prevalence of individuals classified in the high and very high risk group was observed (19% vs 11%, 21% vs 6%, respectively). Overall, 43% of ESSE-RF participants were diagnosed with MetS, compared with the 27% of PLIC members (the difference in prevalence becomes 37% vs 21%, considering a more conservative cut-off for waist circumference). Both cohorts showed a trend towards the increase of MetS components moving from the lowest to the highest CV risk class, with a high prevalence of patients with four or five MetS determinants allocated in the high/very high CV risk group. Developing effective public health strategies for the prevention, detection and treatment of MetS should be an urgent priority to reduce the burden of CVD, not only in subjects at high/very high CV risk, but also in those characterized by a lower risk, as even rare CV events that come from low risk group bring a tangible burden to healthcare systems.

Lipoprotein (a) (Lp(a)) is considered a genetic factor for cardiovascular disease playing an important role in atherogenesis and thrombosis, but the evidence about its association with sleep duration is controversial. We evaluated the relation between self-reported sleep duration and Lp(a). Among 1600 participants of the population-based sample, we selected 1427 subjects without previously known cardiovascular events, who answered the questions about their sleep duration; had valid lipid profile results (total cholesterol, low- and high-density lipoproteins, Lp(a), apolipoprotein AI (ApoAI), ApoB, and ApoB/ApoAI); and did not take lipid-lowering drugs (mean age 46 ± 12 years). We performed a structured interview, which included questions about lifestyle, medical history, complaints, and sleep duration (How long have you been sleeping per night during the last month?). Sleep duration was classified as follows: <6 h/night—short, 6–9 h/night—normal, and ≥10 h/night—long. Overall, 73 respondents (5.2%) were short-sleepers and 69 (4.8%) long-sleepers. Males were slightly more prevalent among short-sleepers. The groups matched by age, body mass index, blood pressure, diabetes mellitus, and hypertension rate. Short-sleepers had lower rates of high total cholesterol (≥5.0 mmol/L), lower Lp(a) levels and lower rates of increased Lp(a) ≥0.5 g/L, and higher insulin and insulin resistance (assessed by the homeostatic model assessment for insulin resistance (HOMA-IR)). ApoAI, ApoB, their ratio, and other lab tests were similar in the groups. The multinomial logistic regression demonstrated that only the short sleep duration was independently (odds ratio (OR) 0.29, 95% confidence interval (CI) (0.09–0.91), p = 0.033) associated with Lp(a) (χ² = 41.58, p = 0.003). Other influencing factors were smoking and HOMA-IR. Such an association was not found for long-sleepers. In conclusion, a short-sleep duration is associated with Lp(a). The latter might mediate the higher insulin resistance and higher cardiometabolic risks in short-sleepers.

Background: In developed countries there are significant gender differences in lifetime expectancy that can be explained by behavioral risk factors (RF). Objective: The aim of our study was to estimate gender features of behavioral RF in general population of Saint-Petersburg, Russia. Methods: As a part of all-Russian epidemiology survey ESSE-RF a random sampling of 1600 Saint-Petersburg inhabitants (25-64 y.o.) stratified by age and sex was performed. All participants filled in the questionnaire. Anthropometry (weight, height, body-mass index (BMI), waist circumference (WC)) and fasting blood-tests (lipids, glucose by Abbott Architect 8000 (USA)) were performed. Results: There were examined 573 (36%) men and 1027 (64%) women. No gender differences in obesity were found according to BMI criteria — in 178 (31.2%) women and 352 (35.1%) men. Obesity was more often detected in females according to WC criteria: АТРIII — 44.1 vs 30.3%; IDF 51.2 vs 66.4% (p <0.001 for both). Linear regression analysis was performed and age was associated with BMI — 1.6 kg/m2/decade, WC in women — 5,2 cm/decade and WC in men — 2.8 cm/decade, р <0.001 for all anthropometric parameters. Optimal level of physical activity was equally documented in both genders — 540 (61.2%) women and 286 (58.9%) men. Daily intake of sweets was lower in men — 228 (39.8%) vs 539 (52.5%) in women (p <0.001). 810 (50,6%) of trial subjects were non-smokers, 395 (24,7%) were former smokers, and 395 (24,7%) were smokers at the moment of trial. The higher number of female smokers was observed — 194 (19.1%). Conclusion: A high prevalence of obesity is observed in sample of Saint-Petersburg inhabitants — it is higher among women according to WC criteria regardless of menopause, possibly due to bigger sweets consumption. Males smoke more often and consume less fresh fruits and vegetables which is accompanied by a higher prevalence of hyperglycemia and hypertriglyceridemia.

Genetic analysis of patients with lipid metabolism disorders is becoming increasingly prevalent in clinical practice. In particular, researchers are directing considerable attention toward studying familial hypercholesterolemia (FH). Despite its high population frequency (heterozygous FH occurs in approximately 1 in 250–300 individuals, with even higher prevalence reported in some regions of the world), the heterogeneity of this condition presents major obstacles to its diagnosis. Owing to the advancement of molecular methods and laboratory technologies, it has become possible to establish the genetic basis of metabolic disorders. In the present study, using next-generation sequencing (NGS), a cohort of 261 patients with a confirmed clinical diagnosis of familial hypercholesterolemia was investigated. Among the 82 variants identified in FH-associated genes (LDLR, APOB, PCSK9, LDLRAP1), the most prevalent was the LDLR NP_000518.3:p.Leu401His variant, which was detected in 21 patients. The second most frequent variant in our cohort (19 patients) was APOB NP_000433.2:p.Arg3527Gln. Overall, 56.1% of patients with a DLCN score of 3–5 (possible FH) carried pathogenic variants, demonstrating the insufficient sensitivity of clinical criteria alone. The presence of early coronary heart disease in 22.73% of genotype-negative patients, together with the considerable number of individuals displaying a pronounced clinical FH phenotype despite negative genetic testing, underscores the importance of further exploring the genetic architecture of FH across different populations.