Epigenetic age and role of factors of the metabolic-associated diseases in accelerating of aging rates

Abstract

The aim of the study was to establish the relationship between factors of metabolic‑associated diseases and markers of premature aging and biological age in patients of different age groups.
 Materials and methods. The study included 151 patients with metabolic disorders but without clinical signs of cardiovascular disease, who were hospitalized or obtained outpatient treatment in the L. T. Mala National Therapy Institute of NAMS of Ukraine during the period of 2019 to 2021 years. The average age of the surveyed was 51.4 ± 12.1 years, women accounted for 62.3 % (n = 94). All patients were divided into groups depending on age: group 1 included subjects aged less than 40 years (n = 22), group 2 consisted of 40 to 49 years old (n = 46), group 3 — from 50 to 59 years (n = 49), group 4 — from 60 to 69 years (n = 21), group 5 — from 70 to 79 years (n = 13). All subjects underwent anthropometric measurements, clinical and biochemical analyses. Serum levels of insulin, C‑reactive protein (CRP), sirtuin 1 (SIRT1) and the percentage of global methylation based on the level of 5‑methylcytosine (5‑mc) were determined by enzyme immunoassay. Activity of total superoxide dismutase (T‑SOD) in blood serum was determined by colorimetric method. The prooxidant‑antioxidant balance of blood serum was calculated as the ratio of the levels of total hydroperoxides (THP) and total antioxidant activity (TAA). Molecular genetic studies included the determination of the relative telomere length of blood leukocytes by real‑time PCR. The epigenetic age was calculated using the DNAm PhenoAge epigenetic clock. Comparison of statistical characteristics between groups and over the course of observation was carried out using parametric and nonparametric criteria, depending on the type of data. Method of logistic regression was used to assess the prognostic value of the observed factors. For all types of analysis, differences were considered statistically significant at p < 0.05.
 Results. The greatest amount of metabolic pathology and the least amount of isolated pathology were observed in patients aged 50 — 59 years. In this group of patients an analysis of age‑related features of metabolic disorders established a non‑linear parabolic dependence with a maximum of manifestations. Correlation analysis revealed a significant relationship between the percentage of global methylation and anthropometric indicators (body mass index, waist and hip volume, visceral fat percentage), platelet levels and glomerular filtration rate. Factors associated with the accelerated aging included insulin resistance index, total cholesterol, SIRT1, glycohemoglobin, and blood telomere length.
 Conclusions. The acceleration of aging processes is associated with both metabolic and molecular genetic factors, this finding opens opportunities for predicting and timely prevention of age‑related diseases.