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      Systemic lupus erythematosus and epilepsy: A Mendelian randomization study

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          Abstract

          Objective

          Numerous observational studies have found a relationship between systemic lupus erythematosus (SLE) and epilepsy; however, their causal relationship remains unclear. This study aimed to investigate the causal role of SLE in epilepsy or any of its subtypes using a two‐sample Mendelian randomization (MR) analysis.

          Methods

          Single nucleotide polymorphisms (SNPs) linked to SLE were utilized as instrumental variables in MR analysis to assess their causal impact on epilepsy. The primary MR findings were derived using the inverse variance weighted (IVW) method, which was further supported by the weighted median and MR‐Egger regression techniques. Additionally, sensitivity analyses, including Cochran's Q test and pleiotropy tests, were conducted to evaluate the influence of these SNPs on epilepsy, particularly looking for signs of horizontal pleiotropy and heterogeneity.

          Results

          We selected 43 SNPs that reached genome‐wide significance from genome‐wide association studies (GWASs) on SLE to serve as instrumental variables in this study. The IVW method showed no evidence to support a causal association between SLE and epilepsy (all epilepsy: odds ratio (OR) = 1.006, 95% confidence interval (CI) = 0.994–1.018; focal epilepsy: OR = 1.006, 95% CI = 0.994–1.019; generalized epilepsy: OR = 1.015, 95% CI = 0.996–1.035). Other MR complementary methods revealed consistent results. Furthermore, there was no evidence indicating heterogeneity or horizontal pleiotropy.

          Significance

          The findings of MR analysis did not support a genetically predicted causal relationship between SLE and epilepsy, but emphasized the need for further research on shared pathophysiological mechanisms, particularly the role of immune system abnormalities and potential influences such as chronic inflammation and therapeutic interventions.

          Plain Language Summary

          The etiology of epilepsy is complex and diverse, including immune factors. Through a Mendelian randomization analysis, we did not find evidence of a genetic causal relationship between systemic lupus erythematosus and epilepsy. However, this does not invalidate epidemiological evidence, and further exploration is needed to investigate factors influencing the relationship between the two.

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          Most cited references31

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          Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression

          Background: The number of Mendelian randomization analyses including large numbers of genetic variants is rapidly increasing. This is due to the proliferation of genome-wide association studies, and the desire to obtain more precise estimates of causal effects. However, some genetic variants may not be valid instrumental variables, in particular due to them having more than one proximal phenotypic correlate (pleiotropy). Methods: We view Mendelian randomization with multiple instruments as a meta-analysis, and show that bias caused by pleiotropy can be regarded as analogous to small study bias. Causal estimates using each instrument can be displayed visually by a funnel plot to assess potential asymmetry. Egger regression, a tool to detect small study bias in meta-analysis, can be adapted to test for bias from pleiotropy, and the slope coefficient from Egger regression provides an estimate of the causal effect. Under the assumption that the association of each genetic variant with the exposure is independent of the pleiotropic effect of the variant (not via the exposure), Egger’s test gives a valid test of the null causal hypothesis and a consistent causal effect estimate even when all the genetic variants are invalid instrumental variables. Results: We illustrate the use of this approach by re-analysing two published Mendelian randomization studies of the causal effect of height on lung function, and the causal effect of blood pressure on coronary artery disease risk. The conservative nature of this approach is illustrated with these examples. Conclusions: An adaption of Egger regression (which we call MR-Egger) can detect some violations of the standard instrumental variable assumptions, and provide an effect estimate which is not subject to these violations. The approach provides a sensitivity analysis for the robustness of the findings from a Mendelian randomization investigation.
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            Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator

            ABSTRACT Developments in genome‐wide association studies and the increasing availability of summary genetic association data have made application of Mendelian randomization relatively straightforward. However, obtaining reliable results from a Mendelian randomization investigation remains problematic, as the conventional inverse‐variance weighted method only gives consistent estimates if all of the genetic variants in the analysis are valid instrumental variables. We present a novel weighted median estimator for combining data on multiple genetic variants into a single causal estimate. This estimator is consistent even when up to 50% of the information comes from invalid instrumental variables. In a simulation analysis, it is shown to have better finite‐sample Type 1 error rates than the inverse‐variance weighted method, and is complementary to the recently proposed MR‐Egger (Mendelian randomization‐Egger) regression method. In analyses of the causal effects of low‐density lipoprotein cholesterol and high‐density lipoprotein cholesterol on coronary artery disease risk, the inverse‐variance weighted method suggests a causal effect of both lipid fractions, whereas the weighted median and MR‐Egger regression methods suggest a null effect of high‐density lipoprotein cholesterol that corresponds with the experimental evidence. Both median‐based and MR‐Egger regression methods should be considered as sensitivity analyses for Mendelian randomization investigations with multiple genetic variants.
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              A framework for the investigation of pleiotropy in two‐sample summary data Mendelian randomization

              Mendelian randomization (MR) uses genetic data to probe questions of causality in epidemiological research, by invoking the Instrumental Variable (IV) assumptions. In recent years, it has become commonplace to attempt MR analyses by synthesising summary data estimates of genetic association gleaned from large and independent study populations. This is referred to as two‐sample summary data MR. Unfortunately, due to the sheer number of variants that can be easily included into summary data MR analyses, it is increasingly likely that some do not meet the IV assumptions due to pleiotropy. There is a pressing need to develop methods that can both detect and correct for pleiotropy, in order to preserve the validity of the MR approach in this context. In this paper, we aim to clarify how established methods of meta‐regression and random effects modelling from mainstream meta‐analysis are being adapted to perform this task. Specifically, we focus on two contrastin g approaches: the Inverse Variance Weighted (IVW) method which assumes in its simplest form that all genetic variants are valid IVs, and the method of MR‐Egger regression that allows all variants to violate the IV assumptions, albeit in a specific way. We investigate the ability of two popular random effects models to provide robustness to pleiotropy under the IVW approach, and propose statistics to quantify the relative goodness‐of‐fit of the IVW approach over MR‐Egger regression. © 2017 The Authors. Statistics in Medicine Published by JohnWiley & Sons Ltd
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                Author and article information

                Contributors
                yqzhang@cqmu.edu.cn
                ligongbo@hospital.cqmu.edu.cn
                Journal
                Epilepsia Open
                Epilepsia Open
                10.1002/(ISSN)2470-9239
                EPI4
                Epilepsia Open
                John Wiley and Sons Inc. (Hoboken )
                2470-9239
                28 September 2024
                December 2024
                : 9
                : 6 ( doiID: 10.1002/epi4.v9.6 )
                : 2274-2282
                Affiliations
                [ 1 ] Department of Neurology The Second Affiliated Hospital of Chongqing Medical University Chongqing China
                [ 2 ] Department of Neurology Zhongshan Hospital of Traditional Chinese Medicine Guangdong China
                Author notes
                [*] [* ] Correspondence

                Yuqing Zhang and Gongbo Li, Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, No. 74 Linjiang Road, Yuzhong District, Chongqing, China.

                Email: yqzhang@ 123456cqmu.edu.cn and ligongbo@ 123456hospital.cqmu.edu.cn

                Author information
                https://orcid.org/0000-0003-0451-4597
                Article
                EPI413058 EPI4-0357-2023.R2
                10.1002/epi4.13058
                11633673
                39340433
                b71d3502-063f-4acc-b1ee-9d4bb1e2cc91
                © 2024 The Author(s). Epilepsia Open published by Wiley Periodicals LLC on behalf of International League Against Epilepsy.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 29 August 2024
                : 19 December 2023
                : 30 August 2024
                Page count
                Figures: 5, Tables: 2, Pages: 9, Words: 4000
                Funding
                Funded by: Kuanren Talents Program of the second affiliated Hospital of Chongqing Medical University
                Award ID: kryc‐yq‐2215
                Funded by: Natural Science Foundation of Chongqing , doi 10.13039/501100005230;
                Award ID: cstc2020jcyj‐msxmX0149
                Award ID: CSTB2023NSCQ‐MSX0176
                Funded by: China Postdoctoral Science Foundation , doi 10.13039/501100002858;
                Award ID: 2022M710562
                Funded by: Natural Science Foundation of China , doi 10.13039/501100001809;
                Award ID: 82001434
                Categories
                Original Article
                Original Article
                Custom metadata
                2.0
                December 2024
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.5.1 mode:remove_FC converted:11.12.2024

                epilepsy,mendelian randomization,systemic lupus erythematosus

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