A network-based systems genetics framework identifies pathobiology and drug repurposing in Parkinson's disease

Area of Science:

• Neurogenetics
• Systems Biology
• Pharmacogenomics

Background:

• Parkinson's disease (PD) is a prevalent neurodegenerative disorder with limited disease-modifying treatments.
• Current PD therapies manage symptoms but do not alter disease progression.
• Genome-wide association studies (GWAS) have identified genetic loci associated with PD, offering potential therapeutic targets.

Purpose of the Study:

• To identify potential Parkinson's disease (PD) risk genes using a systems genetics approach.
• To discover repurposable drugs for PD treatment by integrating network proximity and electronic health record (EHR) data.
• To leverage multi-omics data and GWAS findings for novel PD therapeutic strategies.

Main Methods:

• Integrated non-coding GWAS loci effects with brain-specific quantitative trait loci (xQTLs) within a protein-protein interaction (PPI) network.
• Prioritized PD likely risk genes (pdRGs) by combining five molecular xQTL types: expression (eQTLs), protein (pQTLs), splicing (sQTLs), methylation (meQTLs), and histone acetylation (haQTLs).
• Employed network proximity-based drug repurposing and validated candidates using patient EHR data.

Main Results:

• Identified 175 pdRGs, including known genes like SNCA and LRRK2, through QTL-regulated GWAS.
• Validated pdRGs as druggable targets, differentially expressed across cell types, impacting parkin and alpha-synuclein pathways.
• Discovered simvastatin's association with reduced PD incidence (fall and dementia outcomes) via EHR data analysis.

Conclusions:

• The systems genetics framework successfully identified potential PD risk genes and repurposable drugs.
• Simvastatin shows promise as a potential PD therapeutic, warranting further investigation.
• This approach can be broadly applied to identify targets and treatments for other neurodegenerative diseases.