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      The causal effect of cytokine cycling levels on osteoarthritis: a bidirectional Mendelian randomized study

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          Abstract

          Objective

          Osteoarthritis (OA) is the most prevalent joint disease globally, serving as a primary cause of pain and disability. However, the pathological processes underlying OA remain incompletely understood. Several studies have noted an association between cytokines and OA, yet the causal link between them remains ambiguous. This study aims to identify cytokines potentially causally related to OA using Mendelian randomization (MR) analysis, informing early clinical diagnosis and treatment decisions.

          Methods

          We conducted a genome-wide association study (GWAS) on 12 OA traits involving 177,517 cases and 649,173 controls from 9 international cohorts. For discovery MR analysis, we used 103 cytokines from two European populations as instrumental variables (IVs). Concurrently, another European population OA GWAS database (36,185 cases and 135,185 controls) was used to replicate MR analysis, employing the inverse variance weighted (IVW) method as the primary analytic approach. Additional methods tested included MR Egger, Weighted median, and Weighted mode. We merged the MR findings through meta-analysis. Heterogeneity testing, level pleiotropy testing (MR Egger intercept test and MRPRESSO), and sensitivity analysis via Leave One Out (LOO) were conducted to verify result robustness. Lastly, reverse MR analysis was performed.

          Results

          The meta-analysis merger revealed a correlation between CX3CL1 cycle levels and increased OA risk (OR=1.070, 95% CI: 1.040-1.110; P<0.010). We also observed associations between MCP4 (OR=0.930, 95% CI: 0.890-0.970; P<0.010) and CCL25 (OR=0.930, 95% CI: 0.890-0.970; P<0.010) with reduced OA risk. The sensitivity analysis results corroborate the robustness of these findings.

          Conclusion

          Our MR analysis indicates a potential causal relationship between CX3CL1, MCP4, CCL25, and OA risk changes. Further research is warranted to explore the influence of cytokines on OA development.

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          Most cited references61

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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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            ‘Mendelian randomization’: can genetic epidemiology contribute to understanding environmental determinants of disease?*

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              MendelianRandomization: an R package for performing Mendelian randomization analyses using summarized data

              Abstract MendelianRandomization is a software package for the R open-source software environment that performs Mendelian randomization analyses using summarized data. The core functionality is to implement the inverse-variance weighted, MR-Egger and weighted median methods for multiple genetic variants. Several options are available to the user, such as the use of robust regression, fixed- or random-effects models and the penalization of weights for genetic variants with heterogeneous causal estimates. Extensions to these methods, such as allowing for variants to be correlated, can be chosen if appropriate. Graphical commands allow summarized data to be displayed in an interactive graph, or the plotting of causal estimates from multiple methods, for comparison. Although the main method of data entry is directly by the user, there is also an option for allowing summarized data to be incorporated from the PhenoScanner database of genotype—phenotype associations. We hope to develop this feature in future versions of the package. The R software environment is available for download from [https://www.r-project.org/]. The MendelianRandomization package can be downloaded from the Comprehensive R Archive Network (CRAN) within R, or directly from [https://cran.r-project.org/web/packages/MendelianRandomization/]. Both R and the MendelianRandomization package are released under GNU General Public Licenses (GPL-2|GPL-3).
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                Author and article information

                Contributors
                URI : https://loop.frontiersin.org/people/1959004Role: Role: Role: Role:
                URI : https://loop.frontiersin.org/people/2300218Role: Role: Role: Role:
                URI : https://loop.frontiersin.org/people/2575158Role: Role: Role: Role:
                Role: Role: Role:
                Role: Role: Role: Role:
                Role: Role: Role: Role: Role:
                Role: Role: Role: Role:
                URI : https://loop.frontiersin.org/people/1354533Role: Role: Role: Role: Role:
                Role: Role: Role: Role:
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                Journal
                Front Immunol
                Front Immunol
                Front. Immunol.
                Frontiers in Immunology
                Frontiers Media S.A.
                1664-3224
                11 January 2024
                2023
                : 14
                : 1334361
                Affiliations
                [1] 1 Second Clinical Medical College, Guizhou University of Traditional Chinese Medicine , Guiyang, China
                [2] 2 Department of Rheumatology and Immunology, The First People's Hospital Of Guiyang , Guiyang, China
                [3] 3 Department of Rheumatology and Immunology, The Second Affiliated Hospital of Guizhou University of Traditional Chinese Medicine , Guiyang, China
                Author notes

                Edited by: Zhong Zheng, University of California, Los Angeles, United States

                Reviewed by: Xue Xu, Capital Medical University, China

                Yao Chen, University of California, Los Angeles, United States

                Kresimir Duric, University Hospital Centre Zagreb, Croatia

                *Correspondence: Fang Tang, 64550932@ 123456qq.com ; Wukai Ma, walker55@ 123456163.com

                †These authors have contributed equally to this work

                Article
                10.3389/fimmu.2023.1334361
                10808687
                38274820
                7f8990d9-6a8b-40e9-b2a3-3f0ad0067a2d
                Copyright © 2024 Jiang, Cai, Yao, Zhang, Lan, Jin, Tang, Ma, Yao, Chen and Lan

                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
                : 07 November 2023
                : 27 December 2023
                Page count
                Figures: 5, Tables: 0, Equations: 0, References: 61, Pages: 10, Words: 3589
                Funding
                The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This research was funded by Guizhou Provincial Clinical Research Center for Rheumatism and Immunology (Qian Kehe Platform Talent No. 2202); Guizhou Provincial Basic Research Program(Natural Science)(Fundamentals of Qian Kehe-ZK General 436); Guizhou Provincial Department of Education Youth Science and Technology Talent Growth Project (Qian Jiaohe-KY Word No. 262); Guizhou University of Traditional Chinese Medicine Graduate Education Innovation Program Project (YCXZRB202201); Guizhou Province College Student Innovation and Entrepreneurship Training Program Project (S202310662064).
                Categories
                Immunology
                Original Research
                Custom metadata
                Inflammation

                Immunology
                cytokines,osteoarthritis,mendelian randomization,bidirectional,meta analysis
                Immunology
                cytokines, osteoarthritis, mendelian randomization, bidirectional, meta analysis

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