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Repositioning drugs by targeting network modules: a Parkinson's disease case study
Zongliang Yue1,2, Itika Arora2, Eric Y Zhang2
1Center for Biomedical Big Data, Wenzhou Medical University First Affiliated Hospital, Wenzhou, Zhejiang Province, China.
BMC Bioinformatics
|January 4, 2018
Summary
This study introduces a novel systems pharmacology approach for Parkinson's Disease (PD) drug discovery by integrating genetic data and gene expression modules. The method identifies potential PD treatments by targeting gene expression modules, offering a promising strategy for complex polygenic diseases.
Area of Science:
- Systems pharmacology
- Genomics
- Neuroscience
Background:
- Complex diseases like Parkinson's Disease (PD) involve intricate biological networks, making single-target drug discovery challenging.
- Genome-wide association studies (GWAS) and gene expression data offer insights into PD's genetic architecture and transcriptional profiles.
- Targeting dysregulated pathways or processes, rather than single genes, may be more effective for complex polygenic diseases.
Purpose of the Study:
- To develop and validate a systems pharmacology framework for drug repositioning in PD.
- To integrate GWAS and gene expression data to identify PD-specific gene co-expression modules.
- To discover novel therapeutic agents by targeting these identified modules.
Main Methods:
- Integrated GWAS data with gene co-expression modules from PD patient brain tissues using weighted gene correlation network analysis (WGCNA).
- Performed enrichment analysis to identify PD-specific gene modules (Brown and Turquoise) and their associated functional pathways.
- Utilized drug-protein regulatory databases and developed a Drug Effect Sum Score (DESS) to evaluate drug efficacy for module restoration.
Main Results:
- Identified two significant PD-specific gene co-expression modules: the Brown Module (449 genes) and the Turquoise Module (905 genes).
- Discovered key functional pathways within these modules, including cellular respiration, intracellular transport, and M-phase.
- Evaluated numerous candidate drugs, with 5 already reported for PD and 6 showing potential for repositioning based on high DESS scores.
Conclusions:
- The developed systems pharmacology framework effectively integrates genetic and transcriptomic data for PD drug repositioning.
- A modular approach targeting gene expression modules shows promise for overcoming limitations in single-gene targeting for polygenic diseases.
- This strategy offers a novel direction for discovering effective therapeutics for complex diseases like PD.