Biomarker signatures of aging.
Biomarker signatures of aging.
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DOI：
10.1111/acel.12557
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发表时间：
2017-04
期刊：
影响因子：
7.8
通讯作者：
Perls TT
中科院分区：
文献类型：
--
作者：
Sebastiani P;Thyagarajan B;Sun F;Schupf N;Newman AB;Montano M;Perls TT
由于人们的年龄不同，年龄并不是残疾、发病率和死亡率易感性的充分标志。我们测量了19种血液生物标志物，包括标准血液学指标的成分，脂质生物标志物，以及4704名长寿家庭研究（LLFS）参与者的炎症和虚弱标志物，年龄范围为30-110岁，并使用凝聚算法将LLFS参与者分组为集群，从而产生26种不同的生物标志物特征。为了测试这些特征是否与生物老化的差异相关，我们使用LLFS中收集的纵向数据将其与生理功能的纵向变化以及癌症，心血管疾病，2型糖尿病和死亡率的事件风险相关联。与LLFS中最常见的生物标志物特征相比，特征2与显著降低的死亡率、发病率和更好的身体功能相关，而其他9个特征与不太成功的衰老相关，其特征是虚弱、发病率和死亡率的风险较高。七个特征的预测值在来自心脏研究的独立数据集中重复，具有可比的显著效果，另外三个特征显示出一致的效果。该分析表明，存在各种生物标志物特征，并且它们与身体功能、发病率和死亡率的显著关联表明这些模式代表生物老化的差异。这些特征表明，单一生物标志物的失调可以随其他生物标志物的模式而变化，单独的个体生物标志物的年龄相关变化不一定表明疾病或功能下降。
Because people age differently, age is not a sufficient marker of susceptibility to disabilities, morbidities, and mortality. We measured nineteen blood biomarkers that include constituents of standard hematological measures, lipid biomarkers, and markers of inflammation and frailty in 4704 participants of the Long Life Family Study (LLFS), age range 30–110 years, and used an agglomerative algorithm to group LLFS participants into clusters thus yielding 26 different biomarker signatures. To test whether these signatures were associated with differences in biological aging, we correlated them with longitudinal changes in physiological functions and incident risk of cancer, cardiovascular disease, type 2 diabetes, and mortality using longitudinal data collected in the LLFS. Signature 2 was associated with significantly lower mortality, morbidity, and better physical function relative to the most common biomarker signature in LLFS, while nine other signatures were associated with less successful aging, characterized by higher risks for frailty, morbidity, and mortality. The predictive values of seven signatures were replicated in an independent data set from the Framingham Heart Study with comparable significant effects, and an additional three signatures showed consistent effects. This analysis shows that various biomarker signatures exist, and their significant associations with physical function, morbidity, and mortality suggest that these patterns represent differences in biological aging. The signatures show that dysregulation of a single biomarker can change with patterns of other biomarkers, and age‐related changes of individual biomarkers alone do not necessarily indicate disease or functional decline.