Comorbidity Analysis between Alzheimer's Disease and Type 2 Diabetes Mellitus (T2DM) Based on Shared Pathways and the Role of T2DM Drugs.
Comorbidity Analysis between Alzheimer's Disease and Type 2 Diabetes Mellitus (T2DM) Based on Shared Pathways and the Role of T2DM Drugs.
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DOI：
10.3233/jad-170440
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
Hofmann-Apitius M
中科院分区：
文献类型：
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作者：
Karki R;Kodamullil AT;Hofmann-Apitius M
多项研究表明阿尔茨海默病（AD）和2型糖尿病（T2DM）之间存在共病关联，表明两者可能存在共同的潜在病理生理机制。本研究旨在从分子水平对相关知识进行系统建模，以寻找解释AD与T2DM之间存在共病关联的机制基础。我们使用基于知识的建模方法，利用生物表达语言（BEL）建立了AD和T2DM的两个网络模型，该模型能够从各种知识资源中捕获和表示分子和临床水平上的因果关系和相关关系。通过比较分析，我们确定了几种假定的“共享路径”。我们在机制水平上证明了胰岛素信号通路如何与其他重要的阿尔茨海默病信号通路（如神经营养因子信号通路、PI3K/AKT信号通路、MTOR信号通路和MAPK信号通路）相关，以及这些信号通路如何在阿尔茨海默病和T2DM中相互交叉。此外，我们提出了一个机制假说，解释了抗糖尿病药物二甲双胍对AD的有利和不利影响。本文介绍的两个可计算模型提供了一个强大的框架，以确定AD和T2DM之间共享的合理机制联系，从而确定新治疗的靶向途径。我们的方法也可以用来为为什么某些T2DM治疗似乎会增加AD风险的问题提供机制上的答案。
Various studies suggest a comorbid association between Alzheimer’s disease (AD) and type 2 diabetes mellitus (T2DM) indicating that there could be shared underlying pathophysiological mechanisms. This study aims to systematically model relevant knowledge at the molecular level to find a mechanistic rationale explaining the existing comorbid association between AD and T2DM. We have used a knowledge-based modeling approach to build two network models for AD and T2DM using Biological Expression Language (BEL), which is capable of capturing and representing causal and correlative relationships at both molecular and clinical levels from various knowledge resources. Using comparative analysis, we have identified several putative “shared pathways”. We demonstrate, at a mechanistic level, how the insulin signaling pathway is related to other significant AD pathways such as the neurotrophin signaling pathway, PI3K/AKT signaling, MTOR signaling, and MAPK signaling and how these pathways do cross-talk with each other both in AD and T2DM. In addition, we present a mechanistic hypothesis that explains both favorable and adverse effects of the anti-diabetic drug metformin in AD. The two computable models introduced here provide a powerful framework to identify plausible mechanistic links shared between AD and T2DM and thereby identify targeted pathways for new therapeutics. Our approach can also be used to provide mechanistic answers to the question of why some T2DM treatments seem to increase the risk of AD.