Analysis of genetic polymorphism associations with cardiometabolic risk factors and phenotypic age in individuals without significant pathology

BACKGROUND: Against the background of significant achievements in the treatment and prevention of various diseases, the direction of “medicine for the healthy” currently does not adequately meet the public demand for active longevity. Developing age assessment systems (epigenetic, biochemical and other “clocks”) allow us to get closer to the assessment of biological age, which is an important step towards finding technologies that can slow down aging. AIM: To identify the relationship between clinical characteristics, phenotypic age and genetic factors in a cohort of people without clinically significant pathology who lead a healthy lifestyle. METHODS: A single-center, cross-sectional study was conducted. A retrospective analysis of clinical, laboratory and instrumental examination results of participants in wellness programs at the “First Line” preventive medicine resort was performed. Genetic polymorphism was determined using commercially developed biochip technology. Gene polymorphisms (222 single nucleotide variants) potentially associated with cardiometabolic risks according to published scientific data were analyzed. RESULTS: In a cohort of 29 patients aged 27 to 68 years, 14 single nucleotide variants were identified, associated with changes in systolic (rs6920220 of the TNFAIP3 gene, rs1137101 of the LEPR gene) and diastolic (rs1137101 of the LEPR gene, rs7903146 of the TCF7L2 gene, rs12255372 of the TCF7L2 gene) blood pressure, dyslipidemia (rs266729 of the ADIPOQ gene, rs1045642 of the ABCB1 gene, rs1815739 of the ACTN3 gene), increased body weight (rs4961 of the ADD1 gene), as well as with decreased phenotypic age (rs17553719 of the AQP3 gene, rs1801197 of the CALCR gene, rs2470152 of the CYP19A1 gene, rs1800955 of the DRD4 gene, rs17782313 of the MC4R gene). Most of these associations have not been previously studied or have been reported in only a few publications. CONCLUSION: The assessment of the influence of a wide range of genetic polymorphisms seems to be a promising direction for the future choice of effective strategies for prolonging life in the absence of diseases. The success of new technologies and methods to slow down aging largely depends on the introduction of a multidisciplinary approach that combines various fields: clinical, genetic, “multi-omic” (including metabolomic), microbiomic, immune, psychological and others.