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衰老与稳态应变:使用贝叶斯网络分析在衰老背景下探索和评估稳态应变标志物。

Aging and Allostasis: Using Bayesian Network Analytics to Explore and Evaluate Allostatic Markers in the Context of Aging.

作者信息

Kallen Victor, Tahir Muhammad, Bedard Andrew, Bongers Bart, van Riel Natal, van Meeteren Nico

机构信息

Department of Microbiology & Systems Biology, Netherlands Organization for Applied Scientific Research (TNO), PO Box 360, 3700 AJ Zeist, The Netherlands.

The Physical Activity and Nutrition INfluences In Ageing (PANINI) Consortium: School of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK.

出版信息

Diagnostics (Basel). 2021 Jan 21;11(2):157. doi: 10.3390/diagnostics11020157.

DOI:10.3390/diagnostics11020157
PMID:33494482
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7912325/
Abstract

Allostatic load reflects the cumulative strain on organic functions that may gradually evolve into overt disease. Our aim was to evaluate the allostatic parameters in the context of aging, and identify the parameters that may be suitable for an allostatic load index for elderly people (>60 years). From previously published studies, 11 allostatic (bio)markers could be identified that sustain sufficient variability with aging to capture meaningful changes in health status. Based on reported statistics (prevalence of a biomarker and its associated outcome, and/or an odds/risk ratio relating these two), seven of these could be adopted in a Bayesian Belief Network (BBN), providing the probability of "disturbed" allostasis in any given elder. Additional statistical analyses showed that changes in IL-6 and BMI contributed the most to a "disturbed" allostasis, indicating their prognostic potential in relation to deteriorating health in otherwise generally healthy elderly. In this way, and despite the natural decline in variance that irrevocably alters the prognostic relevance of most allostatic (bio)markers with aging, it appeared possible to outline an allostatic load index specifically for the elderly. The allostatic parameters here identified might consequently be considered a useful basis for future quantitative modelling in the context of (healthy) aging.

摘要

应激负荷反映了机体功能的累积性应变,这种应变可能会逐渐发展为显性疾病。我们的目的是在衰老的背景下评估应激参数,并确定可能适用于老年人(>60岁)应激负荷指数的参数。从先前发表的研究中,可以确定11种应激(生物)标志物,它们随着年龄增长具有足够的变异性,以反映健康状况的有意义变化。根据报告的统计数据(生物标志物的患病率及其相关结果,和/或两者之间的比值比/风险比),其中七种可以纳入贝叶斯信念网络(BBN),以提供任何给定老年人“紊乱”应激的概率。额外的统计分析表明,白细胞介素-6(IL-6)和体重指数(BMI)的变化对应激“紊乱”的影响最大,表明它们在一般健康的老年人健康状况恶化方面具有预后潜力。通过这种方式,尽管随着年龄增长方差自然下降不可避免地改变了大多数应激(生物)标志物的预后相关性,但似乎有可能专门为老年人勾勒出一个应激负荷指数。这里确定的应激参数因此可能被认为是未来在(健康)衰老背景下进行定量建模的有用基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/06b9/7912325/a510d779d4a3/diagnostics-11-00157-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/06b9/7912325/d2ee21543359/diagnostics-11-00157-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/06b9/7912325/0712c1b4ce6b/diagnostics-11-00157-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/06b9/7912325/5afc7cdada1f/diagnostics-11-00157-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/06b9/7912325/280391dad013/diagnostics-11-00157-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/06b9/7912325/a510d779d4a3/diagnostics-11-00157-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/06b9/7912325/d2ee21543359/diagnostics-11-00157-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/06b9/7912325/0712c1b4ce6b/diagnostics-11-00157-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/06b9/7912325/5afc7cdada1f/diagnostics-11-00157-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/06b9/7912325/280391dad013/diagnostics-11-00157-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/06b9/7912325/a510d779d4a3/diagnostics-11-00157-g005.jpg

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