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      Effects of ulcerative colitis and Crohn’s disease on neurodegenerative diseases: A Mendelian randomization study

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          Abstract

          Background: Both ulcerative colitis (UC) and Crohn’s disease (CD) are associated with neurodegenerative diseases (NDs) in observational studies, but the causality remains controversial. We aimed to use Mendelian randomization (MR) analysis to explore causal associations between UC and CD and NDs.

          Methods: We used single nucleotide polymorphisms (SNPs) associated ( p < 5 × 10 −8) with UC and CD as instrumental variables (IVs) to perform the MR analysis on the risks of three NDs, namely, Alzheimer’s Disease (AD), Parkinson’s Disease (PD), and Amyotrophic Lateral Sclerosis (ALS). The inverse variance weighted (IVW) was the primary method and supplement with the weighted median and MR-Egger regression. Moreover, the MR-Egger intercept test, Cochran’s Q test, and “leave one out” sensitivity analysis were implemented to assess the horizontal pleiotropy, heterogeneities, and stability of these SNPs on NDs. To verify the stability of the results, we re-run the MR analysis by using another set of IVs of UC and CD. A reverse causality analysis was conducted to test whether NDs were causally associated with UC or CD. The significance threshold was set at p < 0.05/6 = 0.008.

          Results: In the primary MR analysis, the IVW method yielded no evidence to support a causal association between UC and PD ( OR: 1.01, 95% CI: 0.96–1.06, p = 0.65), AD ( OR: 1.00, 95% CI: 0.99–1.00, p = 0.57), or ALS ( OR: 0.98, 95% CI: 0.96–1.01, p = 0.24), and neither did the MR-Egger and weighted median methods. Our MR analysis also suggested no definitively causal effect of the genetically predicted CD on PD ( OR: 1.01, 95% CI: 0.97–1.05, p = 0.54), AD ( OR: 1.00, 95% CI: 0.99–1.00, p = 0.26), or ALS ( OR: 0.99, 95% CI: 0.96–1.02, p = 0.41), as well as MR-Egger and weighted median methods. Consistent results were found in validation analyses. We did not find a significant causal effect of NDs on UC or CD in the reverse MR analysis.

          Conclusion: No evidence indicated an association between the risks of NDs and genetically predicted UC or CD. The MR results did not support a causal association between UC or CD and three NDs.

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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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            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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                Author and article information

                Contributors
                Journal
                Front Genet
                Front Genet
                Front. Genet.
                Frontiers in Genetics
                Frontiers Media S.A.
                1664-8021
                15 August 2022
                2022
                : 13
                : 846005
                Affiliations
                [1] 1 Department of Medical Administration , Minzu Hospital of Guangxi Zhuang Autonomous Region , Nanning, China
                [2] 2 Department of Epidemiology , School of Public Health , Guangxi Medical University , Nanning, China
                Author notes

                Edited by: Leonid Padyukov, Karolinska Institutet (KI), Sweden

                Reviewed by: Ayse Demirkan, University of Surrey, United Kingdom

                Nidan Qiao, Fudan University, China

                *Correspondence: Zheng Wen, zheng.wen_gxmu@ 123456foxmail.com

                This article was submitted to Neurogenomics, a section of the journal Frontiers in Genetics

                Article
                846005
                10.3389/fgene.2022.846005
                9421062
                36046231
                cd0aee95-b16c-471f-9755-5ec030943ad4
                Copyright © 2022 Li and Wen.

                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
                : 30 December 2021
                : 11 July 2022
                Categories
                Genetics
                Original Research

                Genetics
                ulcerative colitis,crohn’s disease,parkinson’s disease,alzheimer’s disease,amyotrophic lateral sclerosis,mendelian randomization,causal association

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