Li Qing, Wang Shengrui, Milot Emmanuel, Bergeron Patrick, Ferrucci Luigi, Fried Linda P, Cohen Alan A
Groupe de recherche PRIMUS, Department of Family Medicine, University of Sherbrooke, 3001 12e Ave N, Sherbrooke, Quebec, Canada, J1H 5N4.
Department of Computer Science, University of Sherbrooke, 2500 boulevard de l'Université, Sherbrooke, Quebec, Canada, J1K 2R1.
Aging Cell. 2015 Dec;14(6):1103-12. doi: 10.1111/acel.12402. Epub 2015 Sep 29.
An increasing number of aging researchers believes that multi-system physiological dysregulation may be a key biological mechanism of aging, but evidence of this has been sparse. Here, we used biomarker data on nearly 33, 000 individuals from four large datasets to test for the presence of multi-system dysregulation. We grouped 37 biomarkers into six a priori groupings representing physiological systems (lipids, immune, oxygen transport, liver function, vitamins, and electrolytes), then calculated dysregulation scores for each system in each individual using statistical distance. Correlations among dysregulation levels across systems were generally weak but significant. Comparison of these results to dysregulation in arbitrary 'systems' generated by random grouping of biomarkers showed that a priori knowledge effectively distinguished the true systems in which dysregulation proceeds most independently. In other words, correlations among dysregulation levels were higher using arbitrary systems, indicating that only a priori systems identified distinct dysregulation processes. Additionally, dysregulation of most systems increased with age and significantly predicted multiple health outcomes including mortality, frailty, diabetes, heart disease, and number of chronic diseases. The six systems differed in how well their dysregulation scores predicted health outcomes and age. These findings present the first unequivocal demonstration of integrated multi-system physiological dysregulation during aging, demonstrating that physiological dysregulation proceeds neither as a single global process nor as a completely independent process in different systems, but rather as a set of system-specific processes likely linked through weak feedback effects. These processes--probably many more than the six measured here--are implicated in aging.
越来越多的衰老研究人员认为，多系统生理失调可能是衰老的关键生物学机制，但这方面的证据一直很少。在此，我们使用了来自四个大型数据集的近33000名个体的生物标志物数据，以测试多系统失调的存在情况。我们将37种生物标志物分为六个代表生理系统的先验分组（脂质、免疫、氧运输、肝功能、维生素和电解质），然后使用统计距离计算每个个体中每个系统的失调分数。各系统失调水平之间的相关性总体较弱但显著。将这些结果与通过生物标志物随机分组产生的任意“系统”中的失调情况进行比较表明，先验知识有效地区分了失调最独立发生的真正系统。换句话说，使用任意系统时，失调水平之间的相关性更高，这表明只有先验系统识别出了不同的失调过程。此外，大多数系统的失调随年龄增长而增加，并显著预测了多种健康结局，包括死亡率、衰弱、糖尿病、心脏病和慢性病数量。这六个系统在其失调分数预测健康结局和年龄的能力方面存在差异。这些发现首次明确证明了衰老过程中存在综合的多系统生理失调，表明生理失调既不是作为一个单一的全局过程发生，也不是在不同系统中作为一个完全独立的过程发生，而是作为一组可能通过微弱反馈效应联系起来的系统特异性过程发生。这些过程——可能比这里测量的六个过程多得多——与衰老有关。
