Ni X L, Yuan H P, Jiao J, Wang Z P, Su H B, Lyu Y, Pang G F, Zhang W, Sun L, Hu C Y, Yang Z
The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology of National Health Commission, Beijing 100730, China.
Clinical Lab, the Seventh Medical Center of Chinese People's Liberation Army General Hospital, Beijing 100700, China.
Zhonghua Yi Xue Za Zhi. 2022 Jan 11;102(2):119-124. doi: 10.3760/cma.j.cn112137-20210817-01862.
To construct an epigenetic clock model for assessing and calibrating human biological age. 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 -test was used to compare the health-related indicators between subjects with different age gap within different age groups. The (, )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 values<0.05). The established biological age prediction model was as follows: =-53.121×EDARADD cg09809672-137.564×IPO8 cg19722847+141.040×NHLRC1 cg22736354-67.893×P2RX6 cg05442902+149.547×SCGNcg06493994+4.592×sex+64.185 (=0.86, <0.001), where 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 (<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 values<0.05). The constructed epigenetic clock model can be used to evaluate and calibrate human biological age.
构建用于评估和校准人类生物学年龄的表观遗传时钟模型。采用便利抽样法,于2019年7月1日至11月30日从广西壮族自治区长寿队列中选取186名受试者,并于2020年10月1日至12月31日从中国人民解放军总医院第七医学中心体检人群中选取124名受试者。应用自行设计的问卷收集人口统计学特征和疾病家族史。进行体格检查以测定心率和血压。抽取空腹外周静脉血以测定空腹血糖、血浆总胆固醇、甘油三酯、血浆高密度脂蛋白胆固醇、血浆低密度脂蛋白胆固醇和端粒长度。通过靶向甲基化位点测序检测EDARADD基因cg09809672、IPO8基因cg19722847、NHLRC1基因cg22736354、P2RX6基因cg05442902和SCGN基因cg06493994的甲基化水平。共排除54例DNA甲基化和端粒长度质量控制不合格的受试者,最终分析256名受试者的数据。采用趋势检验分析不同年龄组甲基化水平的变化,采用多元线性回归方法建立生物学年龄预测模型。采用肯德尔等级相关分析评估年龄差(公历年龄减去生物学年龄)与端粒长度的相关性。采用独立样本t检验比较不同年龄组中不同年龄差受试者的健康相关指标。受试者年龄为67(51,91)岁,其中女性166例(64.84%)。随着年龄增长,基因位点的甲基化水平呈下降趋势(EDARADD基因cg09809672、IPO8基因cg19722847和P2RX6基因cg05442902)和上升趋势(NHLRC1基因cg22736354和SCGN基因cg06493994)(所有P值<0.05)。建立的生物学年龄预测模型如下:生物学年龄=-53.121×EDARADD基因cg09809672-137.564×IPO8基因cg19722847+141.040×NHLRC1基因cg22736354-67.893×P2RX6基因cg05442902+149.547×SCGN基因cg06493994+4.592×性别+64.185(R²=0.86,P<0.001),其中生物学年龄为生物学年龄,方程中的各项依次为甲基化水平、性别(男性=1,女性=2)和截距。年龄差与端粒长度的肯德尔等级相关系数为0.731(P<0.001)。与年龄差<0的受试者相比,年龄差≥0的受试者在青春期收缩压较高[分别为(88.50±8.89)和(109.83±9.48)mmHg,1mmHg=0.133kPa];在青年期总胆固醇较低[分别为(5.48±0.23)和(3.98±0.54)mmol/L]和甘油三酯较低[分别为(3.51±0.32)和(3.41±0.20)mmol/L];在中年期空腹血糖较低[分别为(6.17±0.67)和(5.37±0.79)mmol/L],在九十岁年龄段舒张压较高[分别为(76.99±6.78)和(83.97±9.36)mmHg](所有P值<0.05)。构建的表观遗传时钟模型可用于评估和校准人类生物学年龄。