Allostatic Load as a Complex Clinical Construct: A Case-Based Computational Modeling Approach.
Allostatic Load as a Complex Clinical Construct: A Case-Based Computational Modeling Approach.
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DOI：
10.1002/cplx.21743
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发表时间：
2016-09
期刊：
影响因子：
2.3
通讯作者：
Seeman T
中科院分区：
文献类型：
--
作者：
Buckwalter JG;Castellani B;McEwen B;Karlamangla AS;Rizzo AA;John B;O'Donnell K;Seeman T
非稳态负荷（AL）是一个复杂的临床结构，提供了一个独特的窗口，累积的压力的影响。然而，由于其固有的复杂性，AL提出了两个主要的测量挑战，传统的统计建模（该领域的主导方法）：它是由一个复杂的因果网络的bioallostatic系统，由一组更大的动态生物标志物表示;和，它是位于一个网络的先行社会生态系统，连接AL的健康结果和差距的差异。为了应对这些挑战，我们采用了基于案例的计算建模（CBM），这使我们能够取得四个进展：（1）我们开发了一个多系统，7因素（2）使用它来创建九种不同临床AL概况的目录（因果路径）;（3）将每个临床特征与23种健康结果的类型学联系起来;（4）探索我们的结果（事后）作为性别的函数，这是一个关键的社会生态因素。就重点而言，（a）健康的临床特征几乎没有健康风险;（B）与高血压和糖尿病相关的促炎特征;（c）与心脏病、TIA/中风、糖尿病和循环问题相关的低应激激素;以及（d）与心脏病和高血压相关的高应激激素。事后分析还发现，男性在高血压（61.2%）、代谢综合征（63.2%）、高应激激素（66.4%）和高血糖（57.1%）方面的代表性过高;而女性在健康（81.9%）、低应激激素（66.3%）和低应激拮抗剂（应激缓冲剂）（95.4%）方面的代表性过高。
Allostatic load (AL) is a complex clinical construct, providing a unique window into the cumulative impact of stress. However, due to its inherent complexity, AL presents two major measurement challenges to conventional statistical modeling (the field’s dominant methodology): it is comprised of a complex causal network of bioallostatic systems, represented by an even larger set of dynamic biomarkers; and, it is situated within a web of antecedent socioecological systems, linking AL to differences in health outcomes and disparities. To address these challenges, we employed case-based computational modeling (CBM), which allowed us to make four advances: (1) we developed a multisystem, 7-factor (20 biomarker) model of AL’s network of allostatic systems; (2) used it to create a catalog of nine different clinical AL profiles (causal pathways); (3) linked each clinical profile to a typology of 23 health outcomes; and (4) explored our results (post hoc) as a function of gender, a key socioecological factor. In terms of highlights, (a) the Healthy clinical profile had few health risks; (b) the pro-inflammatory profile linked to high blood pressure and diabetes; (c) Low Stress Hormones linked to heart disease, TIA/Stroke, diabetes, and circulation problems; and (d) high stress hormones linked to heart disease and high blood pressure. Post hoc analyses also found that males were overrepresented on the High Blood Pressure (61.2%), Metabolic Syndrome (63.2%), High Stress Hormones (66.4%), and High Blood Sugar (57.1%); while females were overrepresented on the Healthy (81.9%), Low Stress Hormones (66.3%), and Low Stress Antagonists (stress buffers) (95.4%) profiles.