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      Genetic insights into the relationship between immune cell characteristics and ischemic stroke: A bidirectional Mendelian randomization study

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          Abstract

          Background and purpose

          Ischemic stroke, a major contributor to global disability and mortality, is underpinned by intricate pathophysiological mechanisms, notably neuroinflammation and immune cell dynamics. Prior research has identified a nuanced and often paradoxical link between immune cell phenotypes and ischemic stroke susceptibility. The aim of this study was to elucidate the potential causal links between the median fluorescence intensity (MFI) and morphological parameters (MP) of 731 immune cell types and ischemic stroke risk.

          Methods

          By analyzing extensive genetic datasets, we conducted comprehensive Mendelian randomization (MR) analyses to discern the genetic correlations between diverse immune cell attributes (MFI and MP) and ischemic stroke risk.

          Results

          Our study identified key immune cell signatures linked to ischemic stroke risk. Both B cells and T cells, among other immune cell types, have a bidirectional influence on stroke risk. Notably, the regulatory T‐cell phenotype demonstrates significant neuroprotective properties, with all odds ratio (OR) values and confidence intervals (CIs) being less than 1. Furthermore, CD39 phenotype immune cells, particularly CD39+ CD8+ T cells (inverse variance weighting [IVW] OR 0.92, 95% CI 0.87–0.97; p = 0.002) and CD39+ activated CD4 regulatory T cells (IVW OR 0.93, 95% CI 0.90–0.97; p < 0.001), show notable neuroprotection against ischemic stroke.

          Conclusion

          This investigation provides new genetic insights into the interplay between various immune cells and ischemic stroke, underscoring the complex role of immune processes in stroke pathogenesis. These findings lay a foundation for future research, which may confirm and expand upon these links, potentially leading to innovative immune‐targeted therapies for stroke prevention and management.

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          Most cited references54

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          Mendelian Randomization Analysis With Multiple Genetic Variants Using Summarized Data

          Genome-wide association studies, which typically report regression coefficients summarizing the associations of many genetic variants with various traits, are potentially a powerful source of data for Mendelian randomization investigations. We demonstrate how such coefficients from multiple variants can be combined in a Mendelian randomization analysis to estimate the causal effect of a risk factor on an outcome. The bias and efficiency of estimates based on summarized data are compared to those based on individual-level data in simulation studies. We investigate the impact of gene–gene interactions, linkage disequilibrium, and ‘weak instruments’ on these estimates. Both an inverse-variance weighted average of variant-specific associations and a likelihood-based approach for summarized data give similar estimates and precision to the two-stage least squares method for individual-level data, even when there are gene–gene interactions. However, these summarized data methods overstate precision when variants are in linkage disequilibrium. If the P-value in a linear regression of the risk factor for each variant is less than , then weak instrument bias will be small. We use these methods to estimate the causal association of low-density lipoprotein cholesterol (LDL-C) on coronary artery disease using published data on five genetic variants. A 30% reduction in LDL-C is estimated to reduce coronary artery disease risk by 67% (95% CI: 54% to 76%). We conclude that Mendelian randomization investigations using summarized data from uncorrelated variants are similarly efficient to those using individual-level data, although the necessary assumptions cannot be so fully assessed.
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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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              Reading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians

              Mendelian randomisation uses genetic variation as a natural experiment to investigate the causal relations between potentially modifiable risk factors and health outcomes in observational data. As with all epidemiological approaches, findings from Mendelian randomisation studies depend on specific assumptions. We provide explanations of the information typically reported in Mendelian randomisation studies that can be used to assess the plausibility of these assumptions and guidance on how to interpret findings from Mendelian randomisation studies in the context of other sources of evidence
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                Author and article information

                Contributors
                ytyhy_1009@126.com
                chpwang@wfmc.edu.cn
                Journal
                Eur J Neurol
                Eur J Neurol
                10.1111/(ISSN)1468-1331
                ENE
                European Journal of Neurology
                John Wiley and Sons Inc. (Hoboken )
                1351-5101
                1468-1331
                07 February 2024
                May 2024
                : 31
                : 5 ( doiID: 10.1111/ene.v31.5 )
                : e16226
                Affiliations
                [ 1 ] Shandong Second Medical University Weifang China
                [ 2 ] Department II of Neurology Affiliated Hospital of Shandong Second Medical University Weifang China
                [ 3 ] Emergency Department Yantaishan hospital Yantai China
                Author notes
                [*] [* ] Correspondence

                Haiyan Yang, Yantaishan hospital, No. 10087, Science and Technology Avenue, Laishan District, Yantai, Shandong 264003, China.

                Email: ytyhy_1009@ 123456126.com

                Chunping Wang, Shandong Second Medical University, No. 7166, Baotong West Street, Weicheng District, Weifang, Shandong 261053, China.

                Email: chpwang@ 123456wfmc.edu.cn

                Author information
                https://orcid.org/0009-0002-0751-8278
                Article
                ENE16226 EJoN-23-2501.R1
                10.1111/ene.16226
                11236043
                38323746
                24e45abd-50c5-475c-8e44-24b78fa5d518
                © 2024 The Authors. European Journal of Neurology published by John Wiley & Sons Ltd on behalf of European Academy of Neurology.

                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
                : 10 January 2024
                : 14 December 2023
                : 15 January 2024
                Page count
                Figures: 3, Tables: 0, Pages: 8, Words: 5162
                Funding
                Funded by: The Key Research and Development Program of Shandong Province
                Award ID: 2023RKY07003
                Categories
                Original Article
                Stroke
                Custom metadata
                2.0
                May 2024
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.4.5 mode:remove_FC converted:08.07.2024

                Neurology
                causal inference,immunity,ischemic stroke,mr analysis,neuroinflammation
                Neurology
                causal inference, immunity, ischemic stroke, mr analysis, neuroinflammation

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