Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, Germany; Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn-Aachen International Center for IT, Bonn, Germany.
Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, Germany.
Alzheimers Dement. 2015 Nov;11(11):1329-39. doi: 10.1016/j.jalz.2015.02.006. Epub 2015 Apr 4.
The discovery and development of new treatments for Alzheimer's disease (AD) requires a profound mechanistic understanding of the disease. Here, we propose a model-driven approach supporting the systematic identification of putative disease mechanisms.
We have created a model for AD and a corresponding model for the normal physiology of neurons using biological expression language to systematically model causal and correlative relationships between biomolecules, pathways, and clinical readouts. Through model-model comparison we identify "chains of causal relationships" that lead to new insights into putative disease mechanisms.
Using differential analysis of our models we identified a new mechanism explaining the effect of amyloid-beta on apoptosis via both the neurotrophic tyrosine kinase receptor, type 2 and nerve growth factor receptor branches of the neurotrophin signaling pathway. We also provide the example of a model-guided interpretation of genetic variation data for a comorbidity analysis between AD and type 2 diabetes mellitus.
The two computable, literature-based models introduced here provide a powerful framework for the generation and validation of rational, testable hypotheses across disease areas.
阿尔茨海默病（AD）新疗法的发现和开发需要深入了解疾病的机制。在这里，我们提出了一种模型驱动的方法，支持系统地识别潜在的疾病机制。
我们使用生物表达语言为 AD 建立了一个模型和一个相应的神经元正常生理学模型，以系统地模拟生物分子、途径和临床结果之间的因果和相关关系。通过模型-模型比较，我们确定了导致潜在疾病机制新见解的“因果关系链”。
通过对我们模型的差异分析，我们确定了一个新的机制，通过神经营养酪氨酸激酶受体 2 型和神经生长因子受体分支的神经营养因子信号通路，解释了淀粉样蛋白-β对细胞凋亡的影响。我们还提供了一个模型指导的遗传变异数据分析示例，用于 AD 和 2 型糖尿病之间的合并症分析。
这里介绍的两个可计算的、基于文献的模型为跨疾病领域生成和验证合理的、可测试的假设提供了一个强大的框架。
