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      Investigating a possible causal relationship between maternal serum urate concentrations and offspring birthweight: a Mendelian randomization study

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          Abstract

          Background

          Higher urate levels are associated with higher systolic blood pressure (SBP) in adults, and in pregnancy with lower offspring birthweight. Mendelian randomization (MR) analyses suggest a causal effect of higher urate on higher SBP and of higher maternal SBP on lower offspring birthweight. If urate causally reduces birthweight, it might confound the effect of SBP on birthweight. We therefore tested for a causal effect of maternal urate on offspring birthweight.

          Methods

          We tested the association between maternal urate levels and offspring birthweight using multivariable linear regression in the Exeter Family Study of Childhood Health (EFSOCH; n = 872) and UK Biobank (UKB; n = 133 187). We conducted two-sample MR to test for a causal effect of maternal urate [114 single-nucleotide polymorphisms (SNPs); n = 288 649 European ancestry] on offspring birthweight ( n = 406 063 European ancestry; maternal SNP effect estimates adjusted for fetal effects). We assessed a causal relationship between urate and SBP using one-sample MR in UKB women ( n = 199 768).

          Results

          Higher maternal urate was associated with lower offspring birthweight with similar confounder-adjusted magnitudes in EFSOCH [22 g lower birthweight per 1-SD higher urate (95% CI: –50, 6); P = 0.13] and UKB [–28 g (95% CI: –31, –25); P = 1.8  × 10 –75]. The MR causal effect estimate was directionally consistent, but smaller [–11 g (95% CI: –25, 3); P IVW = 0.11]. In women, higher urate was causally associated with higher SBP [1.7 mmHg higher SBP per 1-SD higher urate (95% CI: 1.4, 2.1); P = 7.8  × 10 –22], consistent with that previously published in women and men.

          Conclusion

          The marked attenuation of the MR result of maternal urate on offspring birthweight compared with the multivariable regression result suggests previous observational associations may be confounded. The 95% CIs of the MR result included the null but suggest a possible small effect on birthweight. Maternal urate levels are unlikely to be an important contributor to offspring birthweight.

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          Most cited references44

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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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            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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                Author and article information

                Contributors
                Journal
                Int J Epidemiol
                Int J Epidemiol
                ije
                International Journal of Epidemiology
                Oxford University Press
                0300-5771
                1464-3685
                February 2023
                03 October 2022
                03 October 2022
                : 52
                : 1
                : 178-189
                Affiliations
                Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter , Exeter, UK
                University of Queensland Diamantina Institute, University of Queensland , Brisbane, Queensland, Australia
                Institute for Molecular Bioscience, University of Queensland , Brisbane, Queensland, Australia
                Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter , Exeter, UK
                Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter , Exeter, UK
                Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter , Exeter, UK
                Medical Research Council Integrative Epidemiology Unit, University of Bristol , Bristol, UK
                Population Health Science, Bristol Medical School, University of Bristol , Bristol, UK
                Bristol NIHR Biomedical Research Centre , Bristol, UK
                University of Queensland Diamantina Institute, University of Queensland , Brisbane, Queensland, Australia
                Institute for Molecular Bioscience, University of Queensland , Brisbane, Queensland, Australia
                K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology , Trondheim, Norway
                University of Queensland Diamantina Institute, University of Queensland , Brisbane, Queensland, Australia
                Institute for Molecular Bioscience, University of Queensland , Brisbane, Queensland, Australia
                Medical Research Council Integrative Epidemiology Unit, University of Bristol , Bristol, UK
                Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter , Exeter, UK
                Medical Research Council Integrative Epidemiology Unit, University of Bristol , Bristol, UK
                Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter , Exeter, UK
                Author notes
                Corresponding author. Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter EX1 2LU, UK. E-mail: r.beaumont@ 123456exeter.ac.uk

                Joint senior authors.

                Author information
                https://orcid.org/0000-0003-0663-4621
                https://orcid.org/0000-0003-0750-8248
                Article
                dyac186
                10.1093/ije/dyac186
                9908052
                36191079
                f623f0a2-3d12-4aec-a888-c31d19f060d5
                © The Author(s) 2022. Published by Oxford University Press on behalf of the International Epidemiological Association.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 23 January 2022
                : 30 August 2022
                : 14 September 2022
                Page count
                Pages: 12
                Funding
                Funded by: QUEX Institute;
                Funded by: University of Exeter, DOI 10.13039/501100000737;
                Funded by: University of Queensland, DOI 10.13039/501100001794;
                Funded by: Wellcome Trust, DOI 10.13039/100010269;
                Funded by: Royal Society, DOI 10.13039/501100000288;
                Award ID: WT104150
                Funded by: Wellcome Senior Research Fellowship;
                Award ID: WT220390
                Funded by: University of Exeter, DOI 10.13039/501100000737;
                Funded by: British Heart Foundation, DOI 10.13039/501100000274;
                Award ID: AA/18/7/34219
                Funded by: European Research Council, DOI 10.13039/100010663;
                Award ID: 669545
                Funded by: National Institute of Health;
                Award ID: DK10324
                Funded by: University of Bristol, DOI 10.13039/501100000883;
                Funded by: Medical Research Council, DOI 10.13039/501100000265;
                Award ID: MC_UU_00011/6
                Funded by: British Heart Foundation Professor;
                Award ID: CH/F/20/90003
                Categories
                Perinatal Epidemiology
                AcademicSubjects/MED00860

                Public health
                birthweight,serum urate,mendelian randomization,blood pressure,genetics
                Public health
                birthweight, serum urate, mendelian randomization, blood pressure, genetics

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