No abstract

Coronary heart disease (CHD) is one of the most common causes of death worldwide. The pharmacokinetic properties of drugs used to treat coronary heart disease depend on genetic factors, including the genotype of CYP2C19, CYP2C9 and CYP4F2. However, existing studies of the genetic basis of the response to treatment in patients with acute coronary syndrome (ACS) have contradictory results, requiring a more detailed study. Goal. In this study, we studied the distribution of the genotypes of CYP2C19*2, CYP2C9*2 and CYP4F2*3 among 59 patients diagnosed with ACS who received dual antiplatelet therapy. Methods. The polymerase chain reaction (PCR) method was used to determine the genotypes of CYP2C19, CYP2C9 and CYP4F2. A correlation analysis of the results of genotype carriage and clinical and laboratory parameters of patients was carried out. Results. The distribution of CYP2C9*2 genotypes was as follows: wild genotype (CC) was found with a frequency of 78 % (45 patients), heterozygotes (CT) — 22 % (12 patients), homozygotes (TT) were not detected. The CYP4F2*3 genotype was distributed as follows: 56.14 % (32 patients) had a wild genotype (CC), 31.5 % (18 patients) were heterozygotes with reduced enzyme activity (CT), 12.36 % (7 patients) were homozygotes for the T (TT) allele. The distribution of alleles and genotypes of CYP2C9 did not correspond to the Hardy-Weinberg equation (χ2 = 21.55; p = 0.044), while the distribution of alleles and genotypes of CYP4F2 corresponded to it (χ2 = 3.61; p = 0.0574). Conclusion. The study showed a high prevalence of the genotypes CYP2C9*2 (CT) and CYP4F2*3 (CT and TT) among patients with acute coronary syndrome. The carriage of CYP2C19*2 was significantly associated with adverse cardiovascular events in patients. These results suggest that genetic testing can provide valuable information for risk stratification and personalized treatment of patients with acute coronary syndrome

Cardiovascular disease is the leading cause of death in the population. Unfortunately, cardiovascular disease and its associated risks are often difficult to diagnose due to the many factors associated with age and other comorbidities that lead to significant uncertainty in diagnostic classification and therapeutic decision making. Therefore, there is a great need to find new biomarkers for more accurate diagnosis, risk assessment and treatment recommendations for both acute and chronic cardiovascular disease. This article presents an analysis of metabolomic and genomic markers used for the diagnosis of cardiovascular disease. The study of the metabolome in combination with the genome and proteome can provide important information about both the pathogenesis of cardiovascular disease and the ability to search for and identify new cardiovascular disease biomarkers. Along with the fundamental data on new cardiovascular disease biomarkers, there is an urgent need for further research confirming their great potential for practical health care.

An additional informative tool in the diagnosis of cardiovascular diseases in the early stages can be the analysis of changes in the fatty acid profile, which can be considered as a marker of various pathological conditions. The study of the effects of fatty acids and the mechanisms of changes in the fatty acid profile in connection with cardiovascular diseases remains relevant. We have analyzed modern data from foreign and domestic literature on issues related to the importance of fatty acids as possible markers in the diagnosis of cardiovascular diseases. Basic information about the structure of fatty acids, their functions in the human body, the relationship between the level of free fatty acids and indicators of the development of pathological processes of the cardiovascular system is presented. The factors influencing the dynamics of fatty acid concentrations both in normal conditions and during the development of pathological processes are reflected. The processes of biochemical modification of the fatty acid composition of the lipid matrix of the cell membrane are considered. The expediency of using fatty acids, together with some protein markers in the diagnosis of diseases of the cardiovascular system, has been shown. The collection and analysis of the accumulated information on the role of fatty acids helps to optimize the use of laboratory markers to determine the stages of pathogenesis of circulatory organ damage, to develop a system for evaluating the effectiveness of therapy for cardiovascular diseases, and to create a set of laboratory and instrumental tests for monitoring the condition of patients.

At present, metabolomics is an intensively developing approach to the specific diagnosis of cardiovascular diseases. Metabolic analysis allows the study of complete metabolomic profiles and their deviations resulting from changes, for example, gene and RNA expression, protein activity, or environmental factors. Analysis of the metabolomic blood profile helps in solving a large number of scientific and clinical problems, one of which is the search for markers of diseases, in particular, cardiovascular diseases (CVD). Aim of the study was to investigate metabolomic markers used for the diagnosis of cardiovascular diseases on the basis of literature data. Material and methods. The literature data was analyzed for key words: cardiovascular diseases, metabolomics, metabolic profile, metabolomic markers in da- tabases PubMed, Scopus, Web of Science, CyberLeninka, PatentDB, Science Direct Open Access, eLibrary. Results. Analysis of literature data and patent search confirms the high importance of metabolomic markers in the diagnosis of CVD. In the patent literature, BNP/NT-proBNP is most common used as a metabolic marker of CVD (11.27 %). The use of CRP (8.99 %) and troponin (8.49 %) is also common. PICP (0.02 %), sVCAM-1 (0.09 %), stimulating growth factor ST-2 (0.12 %) and thrombomodulin (0.12 %) as metabolic markers of CVD. Conclusions. Against the backdrop of analytical methods, metabolomics is the most important diagnostic area. At the same time, it should be noted that by combining the results of the analysis of metabolic studies with others, for example, genomic and proteomic, one can get a complete picture of the pathogenesis of diseases, assess the risk of complications, and also determine the effectiveness of the treatment.