[An epigenetic clock model for assessing the human biological age of healthy aging]

Objective: To construct an epigenetic clock model for assessing and calibrating human biological age. Methods: Convenience sampling was used to select 186 subjects from the longevity cohort of Guangxi Zhuang Antonornous Region from July 1 to November 30, 2019, and 124 subjects from the physical examination population of the Seventh Medical Center of the PLA General Hospital from October 1 to December 31, 2020. Self-designed questionnaire was applied to collect demographic characteristics and family history of disease. Physical examination was applied to determine heart rate and blood pressure. Fasting peripheral venous blood was drawn for determination of fasting plasma glucose, plasma total cholesterol, triglyceride, plasma high-density lipoprotein cholesterol, plasma low-density lipoprotein cholesterol and telomere length. Methylation levels of EDARADD cg09809672, IPO8 cg19722847, NHLRC1 cg22736354, P2RX6 cg05442902 and SCGN cg06493994 were detected by targeted methylation site sequencing. A total of 54 subjects with unqualified quality control of DNA methylation and telomere length were excluded, and 256 subjects' data were finally analyzed. Trend test was used for the change of methylation level among different ages groups, multiple linear regression method was used to build prediction models of biological age. Kendal rank correlation analysis was used to evaluate the correlation of age gap (Gregorian calendar age minus biological age) with telomere length. Independent sample t-test was used to compare the health-related indicators between subjects with different age gap within different age groups. Results: The M(Q₁, Q₃)of age of subjects were 67 (51, 91) years old, including 166 females (64.84%). With increase of age, the methylation levels of gene loci were decreased (EDARADD cg09809672, IPO8 cg19722847 and P2RX6 cg05442902) and increased (NHLRC1 cg22736354 and SCGN cg06493994) (all P values<0.05). The established biological age prediction model was as follows: Y=-53.121×EDARADD cg09809672-137.564×IPO8 cg19722847+141.040×NHLRC1 cg22736354-67.893×P2RX6 cg05442902+149.547×SCGNcg06493994+4.592×sex+64.185 (R²=0.86, P<0.001), where Y was the biological age, and the items in the equation were methylation level, sex (male =1, female =2) and intercept in sequence. The Kendall rank correlation coefficient between age gap and telomere length was 0.731 (P<0.001). Compared with the subjects whose age gaP<0, the subjects with age gaP≥0 had higher systolic blood pressure in adolescence [(88.50±8.89) and (109.83±9.48) mmHg, respectively, 1 mmHg=0.133 kPa]; lower TC [(5.48±0.23) and (3.98±0.54) mmol/L, respectively, ] and TG [(3.51±0.32) and (3.41±0.20) mmol/L] in young adults; lower fasting blood glucose in middle age [(6.17±0.67) and (5.37±0.79) mmol/L, respectively, ] and higher diastolic blood pressure in nonagenarian age [(76.99±6.78) and (83.97±9.36) mmHg, respectively, ] (all P values<0.05). Conclusion: The constructed epigenetic clock model can be used to evaluate and calibrate human biological age.