健康人生物学衰老标志物的个体化评价及衰老程度判定

Estimation of individual biological aging and individualized evaluation of biomarkers of aging in healthy people

目的（1）应用已建立的生物学年龄积分公式对健康人群进行生物学年龄的个体化评价及衰老程度判定。（2）观察不同衰老程度生物学标志物的差异，为临床进行衰老干预提供靶点。方法2003年对沈阳、北京、大连地区2876名30～98岁受试者进行筛选，最终人选健康人852名，按年龄分为4组：青年组（〈45岁），中年组（45—59岁），年轻老人组（60～74岁），老年组（1〉75岁）。利用已构建的生物学年龄积分公式进行个体化生物学年龄积分计算，以生物学年龄积分为因变量，时序年龄为自变量作线性回归将852人分为延缓衰老，正常衰老和提前衰老。按衰老程度和时序年龄分组对构建生物学年龄积分的7个生物学标志物[颈动脉舒张期最大前向血流速度（EDV）、脉压（PP）、颈动脉内膜中层厚度（IMT）、二尖瓣环侧壁充盈早期峰流速度（MVEL）、二尖瓣E／A比值（E／A）、胱蛋白酶抑制剂（CYSC）、纤维蛋白原（FIB）]进行双因素方差分析。同时观察，在不同年龄组不同衰老程度间的差异。结果（1）按衰老程度分组后，相同年龄组内的时序年龄比较差异无统计学意义，但生物学年龄积分比较差异有统计学意义（青年组：F=91．8，P〈0．01；中年组：F=134．5，P〈0．01；年轻老人组：F=199．5，P〈0．01；老年组：F=82．0，P〈0．01）。（2）7项生物学标志物在衰老程度分组和时序年龄分组的双因素方差分析中，不同年龄组间及不同衰老程度间差异均有统计学意义。（3）PP在提前衰老均较正常衰老和延缓衰老有显著增加[青年组：（49．0±6．9）、（37．6±6．4）、（30．8±7．6）mmHg，F=93．2，P〈0．01；中年组：（52．9±7．3）、（44．3±5．9）、（32．7±8．4）mmHg，F=125．7，P〈0．01；年轻老人组：（61．9±7．6）、（51．6±6．6）、（37．1±8．7）mmHg，F=196．5，P〈0．01；老年组（72．2±13．7）、（61．1±6．8）、（43．8±10．8）mmHg，F=60．2，P〈0．01]。EDV在提前衰老均较正常衰老和延缓衰老显著降低。IMT、MVEL、E／A、CYSC及FIB在不同年龄组内的衰老程度间比较差异有统计学意义。结论（1）生物学年龄积分在衰老评价中具有重要作用，为临床进行衰老干预提供了目标人群。（2）IMT、EDV、E／A、MVEL、PP、FIB、CYSC7项生物学标志物可用于构建衰老生物学年龄积分公式，为衰老干预提供靶点。

Objective To estimate the degree of biological aging for healthy people by the biological age score equation and observe the differences of various aging biomarkers so as to provide targets for clinical anti-aging intervention. Methods A total of 2876 subjects aged 30 - 98 years old were recruited from 3 Chinese cities in 2003. After screening, 852 healthy subjects were finally selected and assigned into 4 groups according to ages： young group （ 〈 45 yr）, middle-aged group （45 -59 yr）, young-elder group （60 -74 yr） and elder group （≥75 yr）. They received a total of 108 physical, morphological, physiologic and biochemical examinations. The biological age score equation was employed to compute the individual biological age scores for all subjects. Then the biological age score was taken as a dependent variable and the chronological age as an independent variable for linear regression. Based on the confidence interval with ± 1 standard deviation of regression line, they were divided into 3 groups （ delayed aging, normal aging and early aging）. According to the chronological ages and degrees of aging, two-way analysis of variance was conducted for the following 7 biomarkers ： end diastolic velocity （ EDV）, intima-media thickness （ IMT）, ratio of peak velocity of early filling to atrial filling （ E/A）, mitral valve annulus lateral wall of peak velocity of early filling （MVEL）, arterial pulse pressure （PP）, fibrinogen （FIB） and cystatin C （CYSC）. At the same time, the differences of 7 biomarkers were observed in different aging groups in 4 age groups. Results （ 1 ） A comparison of biological age score ： there were no significant differences in chronological age among 3 biological aging groups in same chronological age groups. However, there were some significant differences in biological age score （ young group ： F = 91.8, P 〈 0. 01 ; middle-aged group ： F = 134.5, P 〈 0.01 ; young-elder group： F=199.5, P 〈0.01; eider group： F =82. 1, P 〈0.01）. （2） Two-way analysis of variance （ aging groups and chronological age groups for biomarkers） ： there were significant differences of 7 biomarkers in different chronological age groups and different aging groups. （3） A comparison of biomarkers among aging groups： there were significant differences in PP among 3 aging groups in 4 age groups. PP increased significantly in early aging group to normal aging group and delayed aging group （young group： 49.0±6.9, 37.6±6.4, 30.8±7.6 mm Hg, F=93.2, P〈0.01; middle-aged group： 52.9±7.3, 44.3 ± 5.9, 32.7 ±8.4 mm Hg, F=125.7, P〈0.01; young-elder group： 61.9 ±7.6, 51.6 ±6.6, 37. 1 ±8.7 mm Hg, F=196.5, P〈0.01; elder group： 72.2±13.7, 61.1 ±6.8, 43.8 ±10.8 mm Hg, F =60.2, P 〈 0.01 ）. There were significant differences in EDV among 3 aging groups in 4 age groups. EDV increased significantly in early aging group to normal aging group and delayed aging group. There were significant changes in IMT, MVEL, E/A, CYSC and FIB among aging groups in different age groups. Conclusion （ 1 ） Biological age score plays an essential role in the evaluation of aging. Based on individual evaluation of biological age score, the degrees of aging can be categorized by grouping so that a clinician may provide clinical anti-aging interventions within the target groups. （2） The above 7 biomarkers are competent for the evaluation of aging. They can not only be used to construct biological age score equation, but also provide clinical targeted interventions for aging.