Genetic risk factor identification for common epilepsies guided by integrative omics data analysis
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Wiley Open Access
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| Natura: | Artículo Open Access |
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Wiley
2025
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| author | Ashwini Mushunuri Oluyomi Adesoji Roland Krause Patrick May Holger Lerche Albert Becker Daniela Grimm Michael Nothnagel Herbert Schulz |
| author_facet | Ashwini Mushunuri Oluyomi Adesoji Roland Krause Patrick May Holger Lerche Albert Becker Daniela Grimm Michael Nothnagel Herbert Schulz Ashwini Mushunuri Oluyomi Adesoji Roland Krause Patrick May Holger Lerche Albert Becker Daniela Grimm Michael Nothnagel Herbert Schulz |
| collection | Wiley Open Access |
| contents | Genetic risk factor identification for common epilepsies guided by integrative omics data analysis Ashwini Mushunuri Oluyomi Adesoji Roland Krause Patrick May Holger Lerche Albert Becker Daniela Grimm Michael Nothnagel Herbert Schulz Epilepsia Abstract Objective Genetic generalized epilepsies (GGEs) comprise the most common genetically determined epilepsy syndromes, following a complex mode of inheritance. Although many important common and rare genetic factors causing or contributing to these epilepsies have been identified in the past decades, many features of the genetic architecture are still insufficiently understood. This study integrates genome‐wide association study (GWAS) data from the International League Against Epilepsy Consortium on Complex Epilepsies with transcriptome‐wide association studies to identify genes whose genetically regulated expression levels are associated with epilepsy. Methods To achieve this, we used multiple computational approaches, including MAGMA, a tool for gene analysis of GWAS data, and its derivatives E‐MAGMA and H‐MAGMA, to improve gene mapping accuracy by utilizing tissue‐specific expression and chromatin interaction data. Furthermore, we developed ME‐MAGMA to incorporate methylation quantitative trait loci data, providing insights into epigenetic factors. Results We identified a total of 897 false discovery rate‐corrected (<.05) candidates. These include voltage‐gated calcium channels, voltage‐gated potassium channels, and other genes such as NPRL2 , CACNB2 , and KCNT1 associated with epilepsy pathogenesis that act as key players in neuronal communication and signaling in the brain. Significance In this study, we propose new candidate genes to expand the dataset of potential epilepsy‐causing genes. Further research on these genes may enhance our understanding of the complex regulatory mechanisms underlying GGE and other types of epilepsy, potentially revealing targets for therapeutic intervention. 10.1111/epi.70021 http://creativecommons.org/licenses/by/4.0/ |
| doi_str_mv | 10.1111/epi.70021 |
| format | Artículo Open Access |
| id | wiley_oa_10_1111_epi_70021 |
| institution | Wiley Open Access |
| license_str_mv | http://creativecommons.org/licenses/by/4.0/ |
| publishDate | 2025 |
| publisher | Wiley |
| record_format | wiley_oa |
| spellingShingle | Genetic risk factor identification for common epilepsies guided by integrative omics data analysis Ashwini Mushunuri Oluyomi Adesoji Roland Krause Patrick May Holger Lerche Albert Becker Daniela Grimm Michael Nothnagel Herbert Schulz Epilepsia Genetic risk factor identification for common epilepsies guided by integrative omics data analysis Ashwini Mushunuri Oluyomi Adesoji Roland Krause Patrick May Holger Lerche Albert Becker Daniela Grimm Michael Nothnagel Herbert Schulz Epilepsia Abstract Objective Genetic generalized epilepsies (GGEs) comprise the most common genetically determined epilepsy syndromes, following a complex mode of inheritance. Although many important common and rare genetic factors causing or contributing to these epilepsies have been identified in the past decades, many features of the genetic architecture are still insufficiently understood. This study integrates genome‐wide association study (GWAS) data from the International League Against Epilepsy Consortium on Complex Epilepsies with transcriptome‐wide association studies to identify genes whose genetically regulated expression levels are associated with epilepsy. Methods To achieve this, we used multiple computational approaches, including MAGMA, a tool for gene analysis of GWAS data, and its derivatives E‐MAGMA and H‐MAGMA, to improve gene mapping accuracy by utilizing tissue‐specific expression and chromatin interaction data. Furthermore, we developed ME‐MAGMA to incorporate methylation quantitative trait loci data, providing insights into epigenetic factors. Results We identified a total of 897 false discovery rate‐corrected (<.05) candidates. These include voltage‐gated calcium channels, voltage‐gated potassium channels, and other genes such as NPRL2 , CACNB2 , and KCNT1 associated with epilepsy pathogenesis that act as key players in neuronal communication and signaling in the brain. Significance In this study, we propose new candidate genes to expand the dataset of potential epilepsy‐causing genes. Further research on these genes may enhance our understanding of the complex regulatory mechanisms underlying GGE and other types of epilepsy, potentially revealing targets for therapeutic intervention. 10.1111/epi.70021 http://creativecommons.org/licenses/by/4.0/ |
| title | Genetic risk factor identification for common epilepsies guided by integrative omics data analysis |
| topic | Epilepsia |
| url | https://onlinelibrary.wiley.com/doi/10.1111/epi.70021 |