Potential Pleiotropic Genes and Shared Biological Pathways in Epilepsy and Depression Based on GWAS Summary Statistics. (12th April 2022)

• Record Type: Journal Article
• Authors: Lin, Han; Lin, Wan-Hui; Lin, Feng; Liu, Chang-Yun; Che, Chun-Hui; Huang, Hua-Pin
• Other Names: Khan Rahim Academic Editor.
• Is Part Of: Computational intelligence and neuroscience. Volume 2022(2022)
• Publication Date: 2022-04-12
• Subjects: Neurosciences -- Data processing -- Periodicals; Computational intelligence -- Periodicals; Computational neuroscience -- Periodicals; 612.80285
• DOI: 10.1155/2022/6799285
• Languages: English
• ISSNs: 1687-5265

Abstract

Abstract : Current epidemiological and experimental studies have indicated the overlapping genetic foundation of epilepsy and depression. However, the detailed pleiotropic genetic etiology and neurobiological pathways have not been well understood, and there are many variants with underestimated effect on the comorbidity of the two diseases. Utilizing genome-wide association study (GWAS) summary statistics of epilepsy (15, 212 cases and 29, 677 controls) and depression (170, 756 cases and 329, 443 controls) from large consortia, we assessed the integrated gene-based association with both diseases by Multimarker Analysis of Genomic Annotation (MAGMA) and Fisher's meta-analysis. On the one hand, shared genes with significantly altered transcripts in Gene Expression Omnibus (GEO) data sets were considered as possible pleiotropic genes. On the other hand, the pathway enrichment analysis was conducted based on the gene lists with nominal significance in the gene-based association test of each disease. We identified a total of two pleiotropic genes ( CD3G and SLCO3A1 ) with gene expression analysis validated and interpreted twenty-five common biological process supported with literature mining. This study indicates the potentially shared genes associated with both epilepsy and depression based on gene expression, meta-data analysis, and pathway enrichment strategy along with traditional GWAS and provides insights into the possible intersecting pathways that were not previously reported.