Svetlana Vladimirovna Mustafina

In recent years, the theory of metabolic phenotyping has been actively studied, which is based on the identification of metabolically healthy (MHP) and unhealthy phenotypes (MUHP) people with different body mass index (BMI). According to the literature, the basis for the formation of MUHP is insulin resistance (IR). One of the most practically accessible tools for assessing IR is the TyG index and its derivatives. However, there is still insufficient information about the features of IR indicators in individuals with different metabolic phenotypes. Aim is to study the indices of insulin resistance based on the TyG index in a sample of women aged 25–44 in Novosibirsk. Material and methods. A representative sample of women aged 25–44 years living in Novosibirsk was examined, the final sample included 651 women. Study design: a single-stage population-based study. An anthropometric and laboratory examination was performed. The criteria of metabolic syndrome IDF, 2005, were considered as definitions of a metabolically unhealthy phenotype. Statistical processing of the results was carried out in the SPSS for Windows program. Results. Young women with MUHP had significantly higher TyG, TyG-BMI, TyG-WC, TyG-WC/height indices than those with MHP both in the entire sample and when divided into groups by BMI ( p < 0.05). With an increase in BMI from normal body weight to obesity, a significant increase in TyG-BMI, TyGWC, TyG-WC/height ( p < 0.0001) was revealed, but not the TyG index. When evaluating the ability of the studied indices to recognize the presence of MUHP, models of good (TyG) and excellent quality (TyG-BMI, TyG-WC, TyG-WC/height) were obtained for all indices. The highest quality of the model was obtained for the TyG-WC index (AUC = 0.930, p < 0.0001), the cut-off value for MUHP recognition was 368.3 (Se = 93.8 %, S p = 79.1 %). Conclusions. Higher TyG-based insulin resistance indices were found in women with MUHP compared with MHP at any body mass index value, the TyG-WC index showed the greatest ability to recognize MUHP in young women.

ABCC8-MODY is caused by variants in the ATP-binding cassette transporter subfamily C member 8 (ABCC8) gene, which encodes sulfonylurea receptor 1 (SUR1), a subunit of the ATP-sensitive potassium channel (K-ATP) found in β-cell membranes. ABCC8 is responsible for the secretion of insulin, which controls blood sugar levels. We report on a 35-year-old female patient with diabetes regarding a likely pathogenic variant NM_001287174.3: c.970G>A, p. V324M (rs1328072266) in the ABCC8 gene. Based on the genetic test results, the patient was diagnosed with MODY12. Conclusions . A personalized approach to diagnosis and treatment is especially important in identifying the “non-classical” course of diabetes in young people. The presented case demonstrates the features of the clinical course and difficulties in treating a rare form of monogenic diabetes – ABCC8-MODY.

This review analyzes the prevalence of childhood and adolescent obesity in the Russian Federation. Data from various regional studies are provided. In some regions, long-term obesity dynamics were studied. The history of studying the epidemiology of obesity in Russia spans more than thirty years. According to the data obtained, the prevalence of childhood obesity throughout the country remains high and continues to increase. In all regions where long-term trends were assessed, the prevalence of obesity has increased (maximum 15.8% in the Tyumen Region). Among children, obesity is recorded among boys more often (maximum 38.3% in St. Petersburg) compared to girls (maximum 37.4% in St. Petersburg).

Objective. To analyze the associations of resting heart rate with the risk of all-cause death in the Siberian cohort of persons aged 45—69 years with type 2 diabetes mellitus. Material and methods. The follow-up group included 571 patients with type 2 diabetes mellitus (T2DM): 205 males (35.9%) and 366 females (64.1%). The follow-up period—from 2003—2005 to December 31, 2019—averaged 13.6±3.9 years, with a median of 15.0 years. Fatal events were recorded based on information from the medical certificate of death (form No. 106/y) according to the registry office. Univariate and multivariate Cox regression analyses were used to determine the independent association of heart rate (HR) with a fatal event over a 15-year follow-up period. The studied associations were adjusted for a wide range of «traditional» cardiovascular risk factors. Statistical data were processed using the SPSS software package (v.13.0; v.23.0). Results. In the sex-combined cohort with T2DM, the hazard ratio of overall death within 15 years was positively associated with a heart rate ≥80/min. In the sex- and age-controlled model, the hazard ratio (HR) was 3.286 (95% CI 1.911—5.651), and in the multiple covariate model, it was 1.543 (95% CI 1.116—2.133). For males with T2DM, a heart rate ≥80 bpm was a significant risk factor for all-cause death, HR=2.773 (1.739—4.423). For females with T2DM, this association was not identified. Conclusion. Heart rate ≥80 bpm in males with type 2 diabetes mellitus is a significant risk factor for all-cause death.

Эпидемиологические исследования йодного дефицита у подростков в г. Новосибирске: данные 15-летнего наблюдения

Aim. To study the clinical and laboratory characteristics of the endocrine phenotype of post-COVID syndrome. Design. A one-stage observational study. Materials and methods. A sample of 270 COVID-19 convalescents was examined. Based on the criteria of the World Health Organization, a group with post-COVID syndrome was identified, comprising 208 convalescents, of whom 98 had the endocrine phenotype. The study included the assessment of medical history, analysis of medical records, anthropometric measurements, and a range of clinical and biochemical blood parameters. All patients were evaluated by an internist and relevant specialist physicians. Results Individuals with the endocrine phenotype of post-COVID syndrome had higher values of the following parameters compared to patients with other phenotypes: age (p < 0.001), body mass index (p < 0.001), waist circumference (p < 0.001), systolic blood pressure (p = 0.010), triglyceride levels (p = 0.002), and uric acid levels (p < 0.001). They also demonstrated lower levels of high-density (p = 0.031) and low-density (p = 0.049) lipoprotein cholesterol, as well as a reduced glomerular filtration rate (p < 0.001). In the endocrine phenotype, the following conditions were more frequently diagnosed: obesity (based on body mass index) (p = 0.010), abdominal obesity (p < 0.001), arterial hypertension (p < 0.001), hypertriglyceridemia (p = 0.026), hyperuricemia (p < 0.001), and a decreased glomerular filtration rate < 90 mL/min/1.73 m2 (p = 0.016). Multivariate regression analysis showed that, in men older than 45 years, the presence of the endocrine phenotype of post-COVID syndrome was directly associated with a reduced glomerular filtration rate < 90 mL/min/1.73 m2 (odds ratio (OR) = 8.311; 95% confidence interval (CI): 1.628–42.442; p = 0.011), whereas in women older than 45 years it was associated with an increase in uric acid level by 1 µmol/L (OR = 1.010; 95% CI: 1.002–1.019; p = 0.014). Conclusion. The prevalence of the endocrine phenotype of post-COVID syndrome was 47.1% (52.0% in men and 48.0% in women). Individuals with the endocrine phenotype more frequently had a history of severe COVID-19 and glucocorticoid therapy. In men older than 45 years, the likelihood of having the endocrine phenotype of post-COVID syndrome was associated with reduced glomerular filtration rate, whereas in women older than 45 years it was associated with increased uric acid levels. Keywords: convalescences of COVID-19, post-COVID syndrome, endocrine phenotype.

Aim. According to the literature study the effectiveness and accuracy of models for predicting the risk of developing type 2 diabetes mellitus T2DM, including genetic markers. Key points. The article presents the results of foreign studies on the development of models for predicting the risk of developing T2DM using various clinical characteristics, biochemical indicators and genetic markers. Thematic sources from the PubMed database were analyzed. According to the literature genetic markers are useful risk factors for developing T2DM, which are not affected by reverse causality. Early studies based on a small number of nucleotide variants found small additional predictive value for genetic markers compared with clinical risk factors. Recent studies based on a larger number of variants have shown significant predictive value. Conclusion. Overall, additional research is need to better understanding the genetic mechanisms and potential causal links between nucleotide variants and the risk of developing of T2DM. This research could provide more insight into personalized therapy options for patients with a higher risk of developing T2DM. Keywords: type 2 diabetes mellitus, genetic markers, predicting the risk

The purpose of this study was to create a scoring scale for assessing the 10-year risk of cardiovascular events for middle-aged and elderly people with type 2 diabetes mellitus (DM).Material and methods. The analysis included data from 314 people with T2DM: 142 men, 242 women, the average age for both sexes was 60.81 ± 6.38 years. The baseline survey was carried out within the framework of the HAPIEE project; the observation period lasted from 2003–2005. to December 31, 2013 and averaged 10 years. Persons who had myocardial infarction and/or cerebral stroke before the examination were excluded from the analysis. Non-fatal cardiovascular (CV) diseases and CV death were established in accordance with the codes of the International Classification of Diseases, 10th revision. As part of the study, two groups were formed: the main group, which included people with T2DM who “developed CV events” over 10 years of observation – 50 (15.9 %) people, and a comparison group – people with T2DM who “did not develop CV events” during the observation period (264 people). Anthropometric indicators, blood pressure, socio-demographic data, and some biochemical parameters were determined. To analyze the association of the studied factors with the risk of CV events, multivariate stepwise Cox regression analysis was used.Results. As a result of multivariate Cox regression analysis, associations with the risk of developing CV diseases were obtained for the following factors: gender (men), age (≥ 55 years), heart rate (≥ 80 beats/min), SBP (≥ 150 mmHg), marital status single, education (not higher). Individuals with a score above 9 are considered to be at high 10-year risk of cardiovascular events.Conclusions. A model has been created that predicts the risk of developing CV events in relation to individuals with T2DM living in a large industrial city in Western Siberia. Based on the data obtained, it will be possible to select priority preventive areas and therapeutic interventions.

Cardiovascular diseases (CVD) occupy a leading position in the structure of all-cause mortality. Prospective and interventional studies have identified the major risk factors for CVD and shown their associations with the risk of cardiovascular outcomes and all-cause death. The impact on the individual risk of death may vary by age, sex, study design, and may be population-specific. We aimed to study the contribution of major CVD risk factors to the 15-year risk of all-cause death in the Russian (Siberian) population cohort aged 45–69 years.Material and methods. A random population sample (men and women 45–69 years old, n = 9360) was examined at baseline in 2003–2005 (Novosibirsk, Russian branch of the HAPIEE project) and re-examined twice in 2006–2008 and 2015–2018. Current analysis included individuals without baseline CVD (n = 8087), the average follow-up period – 15.6 (SD 0.69) years. The fatal events were registered based on death certificates from the Population Registration Bureau (ZAGS), and using the data received at serial examinations and postal interview. We analyzed the association between CVD risk factors and all-cause death using multivariate Cox regression.Results. In a cohort aged 45–69, in the adjusted model, 15-year risk of all-cause death was positively associated with age (HR = 1.08; 95 % CI 1.07–1.09), male sex (HR = 1.46; 95 % CI 1.24–1.71), hypertension (HT) (HR = 1.39; 95 % CI 1.25–1.55), smoking (HR = 2.37; 95 % CI 2.08–2.70), high WHR (HR = 1.19; 95 % CI 1.06–1.33), and type 2 diabetes (T2DM) (HR = 1.52; 95 % CI 1.34–1.73), and it was negatively associated with elevated total cholesterol (TC) or LDL-C in blood. In age- and sex-adjusted model, the risk was additionally associated with high triglycerides (HTG), obesity and elevated fasting plasma glucose (FPG). In men, the risk of death was independently associated with age, HT, smoking, low HDL-C, high WHR, and T2DM. In women, the risk of death was independently associated with age, HT, T2DM smoking, and, in age-standardized models, obesity, high WHR, and hyperglycemia.Conclusions. In a population cohort of 45 years and older, among CVD risk factors male sex, HT, smoking, central obesity, and T2DM independently contributed to the risk of all-cause death. Among lipid parameters, low HDL-C and high TG levels increased the risk of death in men. Associations between cardiovascular risk factors and the risk of all-cause death in older people have the patterns specific for older age; these features are important to take into account in a strategy to reduce mortality in the population.

It has now been shown that overweight and obesity are associated with the development of at least 13 types of cancer, including cancer of the breast, colon and rectum, endometrium, esophagus (adenocarcinoma), gallbladder, stomach, kidney (renal cell), liver, ovaries, pancreas and thyroid glands, as well as multiple myeloma. Obesity-related cancers account for about 40% of all cancers. Thus, obesity is ahead of smoking as the most common modifiable risk factor for carcinogenesis. This review collects the latest data on the impact of obesity phenotypes on the risk of developing cancer, including a discussion of the contribution of the metabolically healthy obesity phenotype (MHO) to tumorigenesis. Possible mechanisms contributing to the emergence and progression of cancer are analyzed, for example: stimulation of cell proliferation, evasion of growth suppressors, inhibition of apoptosis and provision of replicative immortality, induction of angiogenesis, activation of invasion and metastasis, influence on genome instability, as well as chronic low-grade inflammation that contributes to the development of cancer. Understanding how obesity influences the above mechanisms may facilitate the development of new cancer prevention and treatment strategies for obese populations.