Exploring the pathogenesis of canine epilepsy using a systems genetics method and implications for anti-epilepsy drug discovery
Metrics: PDF 674 views | HTML 1308 views | ?
Ze-Jia Cui1,*, Ye-Mao Liu1,*, Qiang Zhu1, Jingbo Xia1 and Hong-Yu Zhang1
1Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Hubei, Wuhan, China
*These authors contributed equally to this work
Jingbo Xia, email: email@example.com
Keywords: canine; systems genetics; pathogenic factors; drug combinations
Received: July 05, 2017 Accepted: November 10, 2017 Published: December 27, 2017
Epilepsy is a common neurological disorder in domestic dogs. However, its complex mechanism involves multiple genetic and environmental factors that make it challenging to identify the real pathogenic factors contributing to epilepsy, particularly for idiopathic epilepsy. Conventional genome-wide association studies (GWASs) can detect various genes associated with epilepsy, although they primarily detect the effects of single-site mutations in epilepsy while ignoring their interactions. In this study, we used a systems genetics method combining both GWAS and gene interactions and obtained 26 significantly mutated subnetworks. Among these subnetworks, seven genes were reported to be involved in neurological disorders. Combined with gene ontology enrichment analysis, we focused on 4 subnetworks that included traditional GWAS-neglected genes. Moreover, we performed a drug enrichment analysis for each subnetwork and identified significantly enriched candidate anti-epilepsy drugs using a hypergeometric test. We discovered 22 potential drug combinations that induced possible synergistic effects for epilepsy treatment, and one of these drug combinations has been confirmed in the Drug Combination database (DCDB) to have beneficial anti-epileptic effects. The method proposed in this study provides deep insight into the pathogenesis of canine epilepsy and implications for anti-epilepsy drug discovery.
All site content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 License.