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Alzheimers Dement. 2015 Nov;11(11):1329-39. doi: 10.1016/j.jalz.2015.02.006. Epub 2015 Apr 4.

Computable cause-and-effect models of healthy and Alzheimer's disease states and their mechanistic differential analysis.

Author information

1
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.
2
Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, Germany.
3
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. Electronic address: martin.hofmann-apitius@scai.fraunhofer.de.

Abstract

INTRODUCTION:

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.

METHODS:

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.

RESULTS:

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.

DISCUSSION:

The two computable, literature-based models introduced here provide a powerful framework for the generation and validation of rational, testable hypotheses across disease areas.

KEYWORDS:

APP; Alzheimer's disease; Alzheimer's disease model; Neurotrophin signaling; OpenBEL; Type 2 diabetes mellitus

PMID:
25849034
DOI:
10.1016/j.jalz.2015.02.006
[Indexed for MEDLINE]
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