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Risk of epilepsy in rheumatoid arthritis: a meta-analysis of population based studies and bioinformatics analysis

BACKGROUND: An increasing number of studies support an association between rheumatoid arthritis (RA) and brain disorders. This study aims to determine the association between RA and epilepsy. METHODS: A comprehensive search of databases in both English and Chinese was performed. Data from the select...

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Autores principales: Zhao, Huawei, Li, Shan, Xie, Meijuan, Chen, Rongrong, Lu, Haimei, Wen, Chengping, Filiano, Anthony J., Xu, Zhenghao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7011323/
https://www.ncbi.nlm.nih.gov/pubmed/32095225
http://dx.doi.org/10.1177/2040622319899300
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author Zhao, Huawei
Li, Shan
Xie, Meijuan
Chen, Rongrong
Lu, Haimei
Wen, Chengping
Filiano, Anthony J.
Xu, Zhenghao
author_facet Zhao, Huawei
Li, Shan
Xie, Meijuan
Chen, Rongrong
Lu, Haimei
Wen, Chengping
Filiano, Anthony J.
Xu, Zhenghao
author_sort Zhao, Huawei
collection PubMed
description BACKGROUND: An increasing number of studies support an association between rheumatoid arthritis (RA) and brain disorders. This study aims to determine the association between RA and epilepsy. METHODS: A comprehensive search of databases in both English and Chinese was performed. Data from the selected studies were extracted and analyzed independently by two authors. Genes associated with epilepsy and RA were also collected and analyzed. RESULTS: We included six nationwide population based studies (n = 7,094,113 cases in total) for the meta-analysis. The risk of epilepsy was increased in RA patients [risk ratio (RR) = 1.601; 95% confidence interval (CI): 1.089–2.354; p = 0.017; n = 3,803,535 cases] and children born to mothers with RA (RR = 1.475; 95% CI: 1.333–1.633; p < 0.001, n = 3,290,578 cases). Subgroup analysis and meta-regression showed the RR of epilepsy in RA was negatively correlated with age. Furthermore, we found that 433 identified genes in a coexpression network from the hippocampi of 129 epileptic patients were enriched in the RA and related Kyoto Encyclopedia of Genes and Genomes pathways, while 13 genes (mainly related to inflammatory cytokines and chemokines) were identified as potential key genes bridging the RA and epilepsy. CONCLUSIONS: Our study, utilizing meta-analysis and bioinformatical data, highlights a close association between epilepsy and RA. Further studies are still warranted to expand these findings, especially for a population that is exposed to RA during fetal and childhood periods.
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spelling pubmed-70113232020-02-24 Risk of epilepsy in rheumatoid arthritis: a meta-analysis of population based studies and bioinformatics analysis Zhao, Huawei Li, Shan Xie, Meijuan Chen, Rongrong Lu, Haimei Wen, Chengping Filiano, Anthony J. Xu, Zhenghao Ther Adv Chronic Dis Meta-Analysis BACKGROUND: An increasing number of studies support an association between rheumatoid arthritis (RA) and brain disorders. This study aims to determine the association between RA and epilepsy. METHODS: A comprehensive search of databases in both English and Chinese was performed. Data from the selected studies were extracted and analyzed independently by two authors. Genes associated with epilepsy and RA were also collected and analyzed. RESULTS: We included six nationwide population based studies (n = 7,094,113 cases in total) for the meta-analysis. The risk of epilepsy was increased in RA patients [risk ratio (RR) = 1.601; 95% confidence interval (CI): 1.089–2.354; p = 0.017; n = 3,803,535 cases] and children born to mothers with RA (RR = 1.475; 95% CI: 1.333–1.633; p < 0.001, n = 3,290,578 cases). Subgroup analysis and meta-regression showed the RR of epilepsy in RA was negatively correlated with age. Furthermore, we found that 433 identified genes in a coexpression network from the hippocampi of 129 epileptic patients were enriched in the RA and related Kyoto Encyclopedia of Genes and Genomes pathways, while 13 genes (mainly related to inflammatory cytokines and chemokines) were identified as potential key genes bridging the RA and epilepsy. CONCLUSIONS: Our study, utilizing meta-analysis and bioinformatical data, highlights a close association between epilepsy and RA. Further studies are still warranted to expand these findings, especially for a population that is exposed to RA during fetal and childhood periods. SAGE Publications 2020-02-07 /pmc/articles/PMC7011323/ /pubmed/32095225 http://dx.doi.org/10.1177/2040622319899300 Text en © The Author(s), 2020 https://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Meta-Analysis
Zhao, Huawei
Li, Shan
Xie, Meijuan
Chen, Rongrong
Lu, Haimei
Wen, Chengping
Filiano, Anthony J.
Xu, Zhenghao
Risk of epilepsy in rheumatoid arthritis: a meta-analysis of population based studies and bioinformatics analysis
title Risk of epilepsy in rheumatoid arthritis: a meta-analysis of population based studies and bioinformatics analysis
title_full Risk of epilepsy in rheumatoid arthritis: a meta-analysis of population based studies and bioinformatics analysis
title_fullStr Risk of epilepsy in rheumatoid arthritis: a meta-analysis of population based studies and bioinformatics analysis
title_full_unstemmed Risk of epilepsy in rheumatoid arthritis: a meta-analysis of population based studies and bioinformatics analysis
title_short Risk of epilepsy in rheumatoid arthritis: a meta-analysis of population based studies and bioinformatics analysis
title_sort risk of epilepsy in rheumatoid arthritis: a meta-analysis of population based studies and bioinformatics analysis
topic Meta-Analysis
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7011323/
https://www.ncbi.nlm.nih.gov/pubmed/32095225
http://dx.doi.org/10.1177/2040622319899300
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