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Towards a Pathway Inventory of the Human Brain for Modeling Disease Mechanisms Underlying Neurodegeneration
Anandhi Iyappan1,2, Michaela Gündel1,2, Mohammad Shahid3
1Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Schloss Birlinghoven, Sankt Augustin, Germany.
Abstract:
Molecular signaling pathways have been long used to demonstrate interactions among upstream causal molecules and downstream biological effects. They show the signal flow between cell compartments, the majority of which are represented as cartoons. These are often drawn manually by scanning through the literature, which is time-consuming, static, and non-interoperable. Moreover, these pathways are often devoid of context (condition and tissue) and biased toward certain disease conditions. Mining the scientific literature creates new possibilities to retrieve pathway information at higher contextual resolution and specificity. To address this challenge, we have created a pathway terminology system by combining signaling pathways and biological events to ensure a broad coverage of the entire pathway knowledge domain. This terminology was applied to mining biomedical papers and patents about neurodegenerative diseases with focus on Alzheimer's disease. We demonstrate the power of our approach by mapping literature-derived signaling pathways onto their corresponding anatomical regions in the human brain under healthy and Alzheimer's disease states. We demonstrate how this knowledge resource can be used to identify a putative mechanism explaining the mode-of-action of the approved drug Rasagiline, and show how this resource can be used for fingerprinting patents to support the discovery of pathway knowledge for Alzheimer's disease. Finally, we propose that based on next-generation cause-and-effect pathway models, a dedicated inventory of computer-processable pathway models specific to neurodegenerative diseases can be established, which hopefully accelerates context-specific enrichment analysis of experimental data with higher resolution and richer annotations.
Insights
We developed a new pathway terminology system to extract detailed molecular signaling pathway information from scientific literature. This approach enhances understanding of neurodegenerative diseases like Alzheimer's disease.
Area of Science:
- Biochemistry
- Computational Biology
- Neuroscience
Background:
- Molecular signaling pathways are crucial for understanding biological processes but are often manually curated, static, and lack contextual information.
- Existing pathway representations are frequently context-devoid (condition, tissue) and biased towards specific diseases, limiting their utility.
- Automated mining of scientific literature offers potential for higher resolution and specificity in pathway information retrieval.
Purpose of the Study:
- To develop a novel pathway terminology system integrating signaling pathways and biological events for comprehensive knowledge domain coverage.
- To apply this system for mining biomedical literature and patents related to neurodegenerative diseases, with a focus on Alzheimer's disease.
- To demonstrate the utility of literature-derived pathways in understanding disease mechanisms and drug actions.
Main Methods:
- Created a pathway terminology system by combining signaling pathways and biological events.
- Applied the terminology to mine biomedical papers and patents concerning neurodegenerative diseases, particularly Alzheimer's disease.
- Mapped literature-derived signaling pathways to human brain anatomical regions for healthy and Alzheimer's disease states.
Main Results:
- Successfully mapped literature-derived signaling pathways onto specific brain regions in healthy and Alzheimer's disease contexts.
- Identified a potential mechanism for the drug Rasagiline's mode-of-action.
- Demonstrated the use of the resource for patent fingerprinting to discover Alzheimer's disease pathway knowledge.
Conclusions:
- The developed pathway terminology system enables high-resolution, context-specific pathway information extraction from literature.
- This approach facilitates the discovery of disease mechanisms and drug actions, particularly for neurodegenerative diseases like Alzheimer's disease.
- Proposes the establishment of a dedicated inventory of computer-processable pathway models for neurodegenerative diseases to accelerate data analysis.
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