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      Women's reproductive traits and ischemic stroke: a two‐sample Mendelian randomization study

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          Abstract

          Objective

          We conducted a Mendelian randomization (MR) study to disentangle causal associations between women's reproductive behaviors and ischemic stroke (IS) and investigate the roles of two modifiable risk factors (body mass index (BMI) and educational attainment (EA)) in these associations.

          Methods

          Using summary‐level data from large‐scale genome‐wide association studies, we performed univariable MR to examine whether there is genetic evidence that women's reproductive traits are causally associated with IS and its subtypes. Multivariable MR and MR mediation analysis were used to investigate whether BMI and EA are common mechanisms or mediators for these associations. A set of sensitivity analyses were conducted to test valid MR assumptions.

          Results

          We observed consistent and statistically significant associations across female and sex‐combined analyses for earlier age at first birth (AFB) and age at first sexual intercourse (AFS) with a higher risk of IS and large‐artery atherosclerotic stroke (LAS) risk in the primary analysis. The odds ratios of IS per 1 SD increase in genetically predicted early AFB and AFS were 0.93 (95% CI, 0.86–0.99; p = 0.046) and 0.83 (95% CI, 0.70–0.97, p = 0.020), respectively. Further analyses indicated that BMI played a shared role in AFS and IS/LAS while EA played a shared role in AFS/AFB and IS/LAS as well as a mediator in the path from AFS to IS/LAS.

          Interpretation

          These findings may inform prevention strategies and interventions directed toward relative women's reproductive behaviors and IS. Future studies are warranted to explore other factors related to EA which are responsible for these causalities.

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          Most cited references53

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          UK Biobank: An Open Access Resource for Identifying the Causes of a Wide Range of Complex Diseases of Middle and Old Age

          Cathie Sudlow and colleagues describe the UK Biobank, a large population-based prospective study, established to allow investigation of the genetic and non-genetic determinants of the diseases of middle and old age.
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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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              The MR-Base platform supports systematic causal inference across the human phenome

              Results from genome-wide association studies (GWAS) can be used to infer causal relationships between phenotypes, using a strategy known as 2-sample Mendelian randomization (2SMR) and bypassing the need for individual-level data. However, 2SMR methods are evolving rapidly and GWAS results are often insufficiently curated, undermining efficient implementation of the approach. We therefore developed MR-Base (http://www.mrbase.org): a platform that integrates a curated database of complete GWAS results (no restrictions according to statistical significance) with an application programming interface, web app and R packages that automate 2SMR. The software includes several sensitivity analyses for assessing the impact of horizontal pleiotropy and other violations of assumptions. The database currently comprises 11 billion single nucleotide polymorphism-trait associations from 1673 GWAS and is updated on a regular basis. Integrating data with software ensures more rigorous application of hypothesis-driven analyses and allows millions of potential causal relationships to be efficiently evaluated in phenome-wide association studies.
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                Author and article information

                Contributors
                zhangjiedoctor@csu.edu.cn
                Journal
                Ann Clin Transl Neurol
                Ann Clin Transl Neurol
                10.1002/(ISSN)2328-9503
                ACN3
                Annals of Clinical and Translational Neurology
                John Wiley and Sons Inc. (Hoboken )
                2328-9503
                17 November 2022
                January 2023
                : 10
                : 1 ( doiID: 10.1002/acn3.v10.1 )
                : 70-83
                Affiliations
                [ 1 ] School of Public Health (Shenzhen) Sun Yat‐sen University Shenzhen Guangdong 518107 China
                [ 2 ] Department of Neurology, The Second Xiangya Hospital Central South University Changsha Hunan 410011 China
                [ 3 ] School of Public Health Fudan University Shanghai 200032 China
                Author notes
                [*] [* ] Correspondence

                Jie Zhang, Department of Neurology, The Second Xiangya Hospital of Central South University, No. 139, Renmin Middle Road, Furong District, Changsha, Hunan, China. Tel: +86 18673111288; Fax: 073185292112; E‐mail: zhangjiedoctor@ 123456csu.edu.cn

                [ a ]

                These authors contributed equally to the manuscript as co‐first authors.

                Author information
                https://orcid.org/0000-0001-8700-0836
                Article
                ACN351702 ACN3-2022-09-0462
                10.1002/acn3.51702
                9852390
                36398399
                b67110d0-2125-4a31-92b5-64a7c3061d92
                © 2022 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                : 08 November 2022
                : 17 September 2022
                : 08 November 2022
                Page count
                Figures: 3, Tables: 3, Pages: 83, Words: 9342
                Categories
                Research Article
                Research Articles
                Custom metadata
                2.0
                January 2023
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.2.3 mode:remove_FC converted:19.01.2023

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