A network-based systems genetics framework identifies pathobiology and drug repurposing in Parkinson’s disease
Abstract Parkinson’s disease (PD) is the second most prevalent neurodegenerative disorder. However, current treatments only manage symptoms and lack the ability to slow or prevent disease progression. We utilized a systems genetics approach to identify potential risk genes and repurposable drugs for...
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Nature Portfolio
2025-01-01
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| Series: | npj Parkinson's Disease |
| Online Access: | https://doi.org/10.1038/s41531-025-00870-y |
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| author | Lijun Dou Zhenxing Xu Jielin Xu Chengxi Zang Chang Su Andrew A. Pieper James B. Leverenz Fei Wang Xiongwei Zhu Jeffrey Cummings Feixiong Cheng |
| author_facet | Lijun Dou Zhenxing Xu Jielin Xu Chengxi Zang Chang Su Andrew A. Pieper James B. Leverenz Fei Wang Xiongwei Zhu Jeffrey Cummings Feixiong Cheng |
| author_sort | Lijun Dou |
| collection | DOAJ |
| description | Abstract Parkinson’s disease (PD) is the second most prevalent neurodegenerative disorder. However, current treatments only manage symptoms and lack the ability to slow or prevent disease progression. We utilized a systems genetics approach to identify potential risk genes and repurposable drugs for PD. First, we leveraged non-coding genome-wide association studies (GWAS) loci effects on five types of brain-specific quantitative trait loci (xQTLs, including expression, protein, splicing, methylation and histone acetylation) under the protein–protein interactome (PPI) network. We then prioritized 175 PD likely risk genes (pdRGs), such as SNCA, CTSB, LRRK2, DGKQ, and CD44, which are enriched in druggable targets and differentially expressed genes across multiple human brain-specific cell types. Integrating network proximity-based drug repurposing and patient electronic health record (EHR) data observations, we identified Simvastatin as being significantly associated with reduced incidence of PD (hazard ratio (HR) = 0.91 for fall outcome, 95% confidence interval (CI): 0.87–0.94; HR = 0.88 for dementia outcome, 95% CI: 0.86–0.89) after adjusting for 267 covariates. In summary, our network-based systems genetics framework identifies potential risk genes and repurposable drugs for PD and other neurodegenerative diseases if broadly applied. |
| format | Article |
| id | doaj-art-34f70baf7be2443f8418c481839c18d4 |
| institution | Kabale University |
| issn | 2373-8057 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Parkinson's Disease |
| spelling | doaj-art-34f70baf7be2443f8418c481839c18d42025-01-26T12:21:27ZengNature Portfolionpj Parkinson's Disease2373-80572025-01-0111111610.1038/s41531-025-00870-yA network-based systems genetics framework identifies pathobiology and drug repurposing in Parkinson’s diseaseLijun Dou0Zhenxing Xu1Jielin Xu2Chengxi Zang3Chang Su4Andrew A. Pieper5James B. Leverenz6Fei Wang7Xiongwei Zhu8Jeffrey Cummings9Feixiong Cheng10Cleveland Clinic Genome Center, Lerner Research Institute, Cleveland ClinicDepartment of Population Health Sciences, Weill Cornell Medical College, Cornell UniversityCleveland Clinic Genome Center, Lerner Research Institute, Cleveland ClinicDepartment of Population Health Sciences, Weill Cornell Medical College, Cornell UniversityDepartment of Population Health Sciences, Weill Cornell Medical College, Cornell UniversityDepartment of Psychiatry, Case Western Reserve UniversityDepartment of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve UniversityDepartment of Population Health Sciences, Weill Cornell Medical College, Cornell UniversityDepartment of Pathology, Case Western Reserve University, School of MedicineChambers-Grundy Center for Transformative Neuroscience, Department of Brain Health, Kirk Kerkorian School of Medicine, UNLVCleveland Clinic Genome Center, Lerner Research Institute, Cleveland ClinicAbstract Parkinson’s disease (PD) is the second most prevalent neurodegenerative disorder. However, current treatments only manage symptoms and lack the ability to slow or prevent disease progression. We utilized a systems genetics approach to identify potential risk genes and repurposable drugs for PD. First, we leveraged non-coding genome-wide association studies (GWAS) loci effects on five types of brain-specific quantitative trait loci (xQTLs, including expression, protein, splicing, methylation and histone acetylation) under the protein–protein interactome (PPI) network. We then prioritized 175 PD likely risk genes (pdRGs), such as SNCA, CTSB, LRRK2, DGKQ, and CD44, which are enriched in druggable targets and differentially expressed genes across multiple human brain-specific cell types. Integrating network proximity-based drug repurposing and patient electronic health record (EHR) data observations, we identified Simvastatin as being significantly associated with reduced incidence of PD (hazard ratio (HR) = 0.91 for fall outcome, 95% confidence interval (CI): 0.87–0.94; HR = 0.88 for dementia outcome, 95% CI: 0.86–0.89) after adjusting for 267 covariates. In summary, our network-based systems genetics framework identifies potential risk genes and repurposable drugs for PD and other neurodegenerative diseases if broadly applied.https://doi.org/10.1038/s41531-025-00870-y |
| spellingShingle | Lijun Dou Zhenxing Xu Jielin Xu Chengxi Zang Chang Su Andrew A. Pieper James B. Leverenz Fei Wang Xiongwei Zhu Jeffrey Cummings Feixiong Cheng A network-based systems genetics framework identifies pathobiology and drug repurposing in Parkinson’s disease npj Parkinson's Disease |
| title | A network-based systems genetics framework identifies pathobiology and drug repurposing in Parkinson’s disease |
| title_full | A network-based systems genetics framework identifies pathobiology and drug repurposing in Parkinson’s disease |
| title_fullStr | A network-based systems genetics framework identifies pathobiology and drug repurposing in Parkinson’s disease |
| title_full_unstemmed | A network-based systems genetics framework identifies pathobiology and drug repurposing in Parkinson’s disease |
| title_short | A network-based systems genetics framework identifies pathobiology and drug repurposing in Parkinson’s disease |
| title_sort | network based systems genetics framework identifies pathobiology and drug repurposing in parkinson s disease |
| url | https://doi.org/10.1038/s41531-025-00870-y |
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