Previous studies have shown significant differences in the health status of the population depending on the place of residence. Despite the ongoing preventive measures, there is no improvement in the epidemiological situation in relation to noncommunicable diseases, including due to unfavorable living conditions. This study is a continuation of the following earlier studies: Epidemiology of Cardiovascular Diseases in Regions of Russian Federation (ESSE-RF) and ESSE-RF-2.Aim. To assess the prevalence of cardiovascular diseases, various risk factors (RFs) of these diseases and their association in Russian regions with different economic, climate and geographic characteristics to determine the risk profile of the region and develop approaches to targeted prevention programs specific to the regions.Material and methods. The study selected 30 regions representing each federal district of the Russian Federation. The survey of participants is carried out in three stages as follows: survey using an original modular questionnaire; measurements, including anthropometry, hand grip strength test, blood pressure and heart rate assessment; blood sampling, followed by biobanking and laboratory tests.Conclusion. The results obtained will allow deepening knowledge about the RF profile specific to a particular region, evaluating the effectiveness of preventive programs, and planning new ones taking into account regional and socio-demographic characteristics. This will become the basis for a better understanding of the socio-economic burden of noncommunicable diseases and the economic damage of RFs.

Aim. To analyze the structure of clinical data, as well as the principles of collecting and storing related data of the biobank of the National Medical Research Center for Therapy and Preventive Medicine (hereinafter Biobank).Material and methods. The analysis was carried out using the documentation available in the Biobank, as well as the databases used in its work. The paper presents clinical data on biosamples available in the Biobank as of August 18, 2021.Results. At the time of analysis, the Biobank had 373547 samples collected from 54192 patients within 37 research projects. The article presents the analysis of data representation and quantitative assessment of the presence/absence of common diagnoses in clinical projects. Approaches to documenting clinical information associated with biological samples stored in the Biobank were assessed. The methods and tools used for standardization and automation of processes used in the Biobank were substantiated.Conclusion. The Biobank of the National Medical Research Center for Therapy and Preventive Medicine is the largest research biobank in Russia, which meets all modern international requirements and is one of the key structures that improve the research quality and intensify their conduct both within the one center and in cooperation with other biobanks and scientific institutions. The collection and systematic storage of clinical abstracts of biological samples is an integral and most important part of the Biobank’s work.

Aim. To study the relationship between the abundance of the genera in the gut microbiota (GM) and levels of serum biomarkers of chronic systemic inflammation and endotoxemia in patients with HFpEF.Material and methods. The composition of GM among 42 patients with HFpEF (men, 57,1%) was assessed by 16S rRNA sequencing. The median age was 67,0 years, interquartile range [64,0; 71,5] years. Correlation and multivariate regression analysis (with adjustments for sex and age) of relationships between the relative abundance of intestinal bacteria and the concentrations of serum biomarkers including high-sensitivity C-reactive protein (hsCRP), interleukins (IL) 1β and 6, the soluble suppressor of tumorigenicity (sST2), and the level of lipopolysaccharide (LPS) was carried out.Results. According to multivariate regression analysis, the relative abundance of Haemophilus was directly related to the concentration of IL-1β (odds ratio (ОR) 32,37, 95% confidence interval (CI) 2,071237,69, p=0,025), Coriobacteriaceae (unclassified) — with IL-6 (ОR 6,27, (1,42-36,74), p=0,024), Porphyromonadaceae (unclassified) — with sST2 (ОR 5,96, (1,33-34,39), p=0,028), and the relative abundance of the genera Pseudomonas (ОR 7,09, (1,45-42,39), p=0,020), Parasutterella (ОR 4,55, (1,07-22,76), p=0,047) and Clostridiaceae (unclassified) (ОR 4,85, (1,06-24,7), p=0,045) was directly associated with LPS levels.Conclusion. In patients with HFpEF, the relative abundance of some GM genera (e.g., Haemophilus, Coriobacteriaceae (unclassified), Porphyromonadaceae (unclassified), Pseudomonas, Parasutterella, Clostridiaceae (unclassified)) is statistically significantly associated with the concentration of biomarkers of chronic systemic inflammation and endotoxemia.

Biosample preservation for future research is a fundamental component of translational medicine. At the same time, the value of stored biosamples is largely determined by the presence of related clinical data and other information. Electronic medical records are a unique source of a large amount of information received over a long period of time. In this regard, genetic and other types of data obtained from the biosample analysis can be associated with phenotypic and other types of information stored in electronic medical records, which pushes the boundaries in large-scale genetic research and improves healthcare. The aim of this review was to analyze the literature on the potential of combining electronic medical records and biobank databases in research and clinical practice.

Aim. To create and validate an algorithm for automatic aliquoting of serum and plasma samples for biobanking as part of a large-scale study.Material and methods. Biobank of the National Medical Research Center for Therapy and Preventive Medicine is equipped with a Tecan automated aliquoting system. When compiling the aliquoting program (script), the following parameters were selected: the time spent on spotting one complete cryobox, with a capacity of 96 cryotubes, the optimal number of vacutainers and tips for a single loading of the device. The program was created to receive 12 aliquots of 0,5 ml of blood serum, plasma with ethylenediaminetetraacetic acid and plasma with sodium citrate in cryotubes per 1 ml from eight participants in total from each in one cycle of device loading. Automatic and manual spotting was assessed in terms of the time spent on sample preparation and the quality of the aliquots obtained.Results. A methodology for conducting the preanalytical phase of a  large-scale study based on the automation of biosample aliquoting has been developed and validated. We created scripts for aliquoting serum and blood plasma at the automated Tecan Freedom EVO system. An experiment conducted on biomaterial from 64 participants showed, that with an expected flow of 32 participants per day, it took more than 2 hours for manual aliquoting, and for automatic aliquoting (4 launches of the aliquot robot for 24 vacutainers from 8 participants) — less than 1,5 hours with the complete exclusion of human errors.Conclusion. Automated aliquoting has a following number of advantages in comparison with manual: it allows to guarantee standardization and efficiency of sample preparation, reduce the time and increase the accuracy of aliquoting of biomaterial, save space in long-term storage freezers due to the use of smaller cryotubes. The developed algorithm for creating aliquoting programs and calculating the optimal use of consumables can be used in other projects.