National Heart, Lung, and Blood Institute's and Boston University's Framingham Heart Study, Framingham, Massachusetts.
Department of Public Health Solutions, National Institute for Health and Welfare, Turku, Finland.
J Gerontol A Biol Sci Med Sci. 2019 Oct 4;74(11):1778-1785. doi: 10.1093/gerona/gly249.
Comprehensive conjoint characterization of long-term trajectories representing several biological systems is lacking.
We measured serially indicators representing 14 distinct biological systems in up to 3,453 participants attending four Framingham Study examinations: bone mineral density, body mass index (BMI), C-reactive protein, glomerular filtration rate, forced vital capacity (FVC), 1 second forced expiratory volume/FVC ratio (FEV1/FVC), gait speed, grip strength, glycosylated hemoglobin (HbA1c), heart rate, left ventricular mass, Mini-Mental State Examination (MMSE), pulse pressure, and total/high-density lipoprotein cholesterol ratio (TC/HDL).
We observed that correlations among the 14 sex-specific trajectories were modest (r < .30 for 169 of 182 sex-specific correlations). During follow-up (median 8 years), 232 individuals experienced a cardiovascular disease (CVD) event and 393 participants died. In multivariable regression models, CVD incidence was positively related to trajectories of BMI, HbA1c, TC/HDL, gait time, and pulse pressure (p < .06); mortality risk was related directly to trajectories of gait time, C-reactive protein, heart rate, and pulse pressure but inversely to MMSE and FEV1/FVC (p < .006). A unit increase in the trajectory risk score was associated with a 2.80-fold risk of CVD (95% confidence interval [CI], 2.04-3.84; p < .001) and a 2.71-fold risk of death (95% CI, 2.30-3.20; p < .001). Trajectory risk scores were suggestive of a greater increase in model c-statistic compared with single occasion measures (delta-c compared with age- and sex-adjusted models: .032 vs .026 for CVD; .042 vs .030 for mortality).
Biological systems age differentially over the life course. Longitudinal data on a parsimonious set of biomarkers reflecting key biological systems may facilitate identification of high-risk individuals.
缺乏对代表多个生物系统的长期轨迹进行综合联合特征描述的研究。
我们对参加四项弗雷明汉研究检查的多达 3453 名参与者的 14 个不同生物系统的指标进行了连续测量:骨矿物质密度、体重指数(BMI)、C 反应蛋白、肾小球滤过率、用力肺活量(FVC)、1 秒用力呼气量/FVC 比值(FEV1/FVC)、步态速度、握力、糖化血红蛋白(HbA1c)、心率、左心室质量、简易精神状态检查(MMSE)、脉压和总/高密度脂蛋白胆固醇比值(TC/HDL)。
我们观察到 14 个性别特异性轨迹之间的相关性较弱(182 个性别特异性相关性中 169 个相关系数<0.30)。在随访期间(中位 8 年),232 人发生心血管疾病(CVD)事件,393 人死亡。在多变量回归模型中,CVD 发病率与 BMI、HbA1c、TC/HDL、步态时间和脉压的轨迹呈正相关(p < 0.06);死亡率与步态时间、C 反应蛋白、心率和脉压的轨迹直接相关,与 MMSE 和 FEV1/FVC 的轨迹呈负相关(p < 0.006)。轨迹风险评分每增加一个单位,CVD 的风险增加 2.80 倍(95%置信区间 [CI],2.04-3.84;p < 0.001),死亡的风险增加 2.71 倍(95% CI,2.30-3.20;p < 0.001)。轨迹风险评分与单一时刻测量相比,提示模型 C 统计量有更大的增加(与年龄和性别调整模型相比,C 增加 0.032 比 0.026 用于 CVD;C 增加 0.042 比 0.030 用于死亡率)。
生物系统在生命过程中会以不同的速度衰老。关于反映关键生物系统的一组简单生物标志物的纵向数据可能有助于识别高危个体。