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      Potential causal association of diabetes mellitus and blood glucose related indexes with the onset of epilepsy: a two-sample Mendelian randomization study

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          Abstract

          Aim

          Diabetes mellitus (DM) may promote the occurrence of epilepsy through mechanisms, such as inflammation, immune imbalance, and cerebrovascular injury, caused by metabolic abnormalities. However, evidence for the effects of DM and blood glucose (BG) on the risk of epilepsy is limited. Herein, this study used the Mendelian randomization (MR) method to investigate the potential causal associations of DM and BG-related indexes with epilepsy.

          Methods

          In this two-sample MR study, summary statistics data of the genome-wide association studies (GWASs) on exposures, including type 1 diabetes mellitus (T1DM), T2DM, fasting glucose, and glycated hemoglobin (HbAlc), were extracted from the MRC-Integrative Epidemiology Unit (MRC-IEU). The GWAS data on study outcomes, including epilepsy, focal epilepsy, and generalized epilepsy, were obtained from the FinnGen consortium. MR-Egger regression was used to examine horizontal pleiotropism of instrumental variables (IVs), and Cochran's Q statistics was used to quantify the heterogeneity. MR analysis methods including inverse variance weighted (IVW) tests, weighted median, and MR-Egger were utilized to investigate the causal associations between DM and BG-related indexes with epilepsy. The evaluation indexes were odds ratios (ORs) and 95% confidence intervals (CIs). Reverse causal association analyses were also performed. In addition, IVW-radial and leave-one-out tests were utilized for sensitivity analyses.

          Results

          IVW estimates suggested that T1DM has potential causal associations with epilepsy (OR = 1.057, 95% CI: 1.031–1.084) and generalized epilepsy (OR = 1.066, 95% CI: 1.018–1.116). No significant reverse causal associations of T1DM with epilepsy or generalized epilepsy were found (all P > 0.05). In addition, sensitivity analysis results identified no outlier, indicating that the associations of T1DM with epilepsy and generalized epilepsy were relatively robust.

          Conclusion

          Patients with T1DM had a potential risk of developing epilepsy, and prompt treatment of DM and dynamic monitoring may be beneficial to prevent epilepsy in this high-risk population. However, the causal associations of DM and BG with epilepsy may warrant further verification.

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          Most cited references30

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          Interpreting findings from Mendelian randomization using the MR-Egger method

          Mendelian randomization-Egger (MR-Egger) is an analysis method for Mendelian randomization using summarized genetic data. MR-Egger consists of three parts: (1) a test for directional pleiotropy, (2) a test for a causal effect, and (3) an estimate of the causal effect. While conventional analysis methods for Mendelian randomization assume that all genetic variants satisfy the instrumental variable assumptions, the MR-Egger method is able to assess whether genetic variants have pleiotropic effects on the outcome that differ on average from zero (directional pleiotropy), as well as to provide a consistent estimate of the causal effect, under a weaker assumption—the InSIDE (INstrument Strength Independent of Direct Effect) assumption. In this paper, we provide a critical assessment of the MR-Egger method with regard to its implementation and interpretation. While the MR-Egger method is a worthwhile sensitivity analysis for detecting violations of the instrumental variable assumptions, there are several reasons why causal estimates from the MR-Egger method may be biased and have inflated Type 1 error rates in practice, including violations of the InSIDE assumption and the influence of outlying variants. The issues raised in this paper have potentially serious consequences for causal inferences from the MR-Egger approach. We give examples of scenarios in which the estimates from conventional Mendelian randomization methods and MR-Egger differ, and discuss how to interpret findings in such cases. Electronic supplementary material The online version of this article (doi:10.1007/s10654-017-0255-x) contains supplementary material, which is available to authorized users.
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            Mendelian randomization: genetic anchors for causal inference in epidemiological studies

            Observational epidemiological studies are prone to confounding, reverse causation and various biases and have generated findings that have proved to be unreliable indicators of the causal effects of modifiable exposures on disease outcomes. Mendelian randomization (MR) is a method that utilizes genetic variants that are robustly associated with such modifiable exposures to generate more reliable evidence regarding which interventions should produce health benefits. The approach is being widely applied, and various ways to strengthen inference given the known potential limitations of MR are now available. Developments of MR, including two-sample MR, bidirectional MR, network MR, two-step MR, factorial MR and multiphenotype MR, are outlined in this review. The integration of genetic information into population-based epidemiological studies presents translational opportunities, which capitalize on the investment in genomic discovery research.
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              Epilepsy in adults

              Epilepsy is one of the most common serious brain conditions, affecting over 70 million people worldwide. Its incidence has a bimodal distribution with the highest risk in infants and older age groups. Progress in genomic technology is exposing the complex genetic architecture of the common types of epilepsy, and is driving a paradigm shift. Epilepsy is a symptom complex with multiple risk factors and a strong genetic predisposition rather than a condition with a single expression and cause. These advances have resulted in the new classification of epileptic seizures and epilepsies. A detailed clinical history and a reliable eyewitness account of a seizure are the cornerstones of the diagnosis. Ancillary investigations can help to determine cause and prognosis. Advances in brain imaging are helping to identify the structural and functional causes and consequences of the epilepsies. Comorbidities are increasingly recognised as important aetiological and prognostic markers. Antiseizure medication might suppress seizures in up to two-thirds of all individuals but do not alter long-term prognosis. Epilepsy surgery is the most effective way to achieve long-term seizure freedom in selected individuals with drug-resistant focal epilepsy, but it is probably not used enough. With improved understanding of the gradual development of epilepsy, epigenetic determinants, and pharmacogenomics comes the hope for better, disease-modifying, or even curative, pharmacological and non-pharmacological treatment strategies. Other developments are clinical implementation of seizure detection devices and new neuromodulation techniques, including responsive neural stimulation.
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                Author and article information

                Contributors
                URI : http://loop.frontiersin.org/people/2682807/overviewRole: Role: Role: Role: Role: Role:
                Role: Role: Role: Role: Role:
                Journal
                Front Neurol
                Front Neurol
                Front. Neurol.
                Frontiers in Neurology
                Frontiers Media S.A.
                1664-2295
                19 June 2024
                2024
                : 15
                : 1399504
                Affiliations
                Department of Neurology, The Fifth People's Hospital of Wujiang District, Suzhou , Jiangsu, China
                Author notes

                Edited by: Pranav Kumar Prabhakar, Lovely Professional University, India

                Reviewed by: Shikha Grover, Pace Analytical Labs, United States

                Nidhi Kundu, National Institutes of Health (NIH), United States

                Sudha Varadaraj, University of Texas Southwestern Medical Center, United States

                *Correspondence: Mengting Zhu zmtshuizujingling@ 123456outlook.com
                Article
                10.3389/fneur.2024.1399504
                11221190
                38962478
                4adb6e37-2232-4613-b738-d55b67eed97a
                Copyright © 2024 Zhu and Ling.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 12 March 2024
                : 14 May 2024
                Page count
                Figures: 3, Tables: 5, Equations: 0, References: 30, Pages: 9, Words: 4610
                Funding
                The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.
                Categories
                Neurology
                Original Research
                Custom metadata
                Epilepsy

                Neurology
                diabetes mellitus,blood pressure,epilepsy,mendelian randomization study,causal association

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