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      Age-specific effects of weight-based body size on fracture risk in later life: a lifecourse Mendelian randomisation study

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          Abstract

          Musculoskeletal conditions, including fractures, can have severe and long-lasting consequences. Higher body mass index in adulthood is widely acknowledged to be protective for most fracture sites. However, sources of bias induced by confounding factors may have distorted previous findings. Employing a lifecourse Mendelian randomisation (MR) approach by using genetic instruments to separate effects at different life stages, this investigation aims to explore how prepubertal and adult body size independently influence fracture risk in later life.

          Using data from a large prospective cohort, univariable and multivariable MR were conducted to simultaneously estimate the effects of age-specific genetic proxies for body size (n = 453,169) on fracture risk (n = 416,795). A two-step MR framework was additionally applied to elucidate potential mediators. Univariable and multivariable MR indicated strong evidence that higher body size in childhood reduced fracture risk (OR, 95% CI: 0.89, 0.82 to 0.96, P = 0.005 and 0.76, 0.69 to 0.85, P = 1 × 10 − 6, respectively). Conversely, higher body size in adulthood increased fracture risk (OR, 95% CI: 1.08, 1.01 to 1.16, P = 0.023 and 1.26, 1.14 to 1.38, P = 2 × 10 − 6, respectively). Two-step MR analyses suggested that the effect of higher body size in childhood on reduced fracture risk was mediated by its influence on higher estimated bone mineral density (eBMD) in adulthood.

          This investigation provides novel evidence that higher body size in childhood reduces fracture risk in later life through its influence on increased eBMD. From a public health perspective, this relationship is complex since obesity in adulthood remains a major risk factor for co-morbidities. Results additionally indicate that higher body size in adulthood is a risk factor for fractures. Protective effect estimates previously observed are likely attributed to childhood effects.

          Supplementary Information

          The online version contains supplementary material available at 10.1007/s10654-023-00986-6.

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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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              The UK Biobank resource with deep phenotyping and genomic data

              The UK Biobank project is a prospective cohort study with deep genetic and phenotypic data collected on approximately 500,000 individuals from across the United Kingdom, aged between 40 and 69 at recruitment. The open resource is unique in its size and scope. A rich variety of phenotypic and health-related information is available on each participant, including biological measurements, lifestyle indicators, biomarkers in blood and urine, and imaging of the body and brain. Follow-up information is provided by linking health and medical records. Genome-wide genotype data have been collected on all participants, providing many opportunities for the discovery of new genetic associations and the genetic bases of complex traits. Here we describe the centralized analysis of the genetic data, including genotype quality, properties of population structure and relatedness of the genetic data, and efficient phasing and genotype imputation that increases the number of testable variants to around 96 million. Classical allelic variation at 11 human leukocyte antigen genes was imputed, resulting in the recovery of signals with known associations between human leukocyte antigen alleles and many diseases.
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                Author and article information

                Contributors
                grace.power@bristol.ac.uk
                Journal
                Eur J Epidemiol
                Eur J Epidemiol
                European Journal of Epidemiology
                Springer Netherlands (Dordrecht )
                0393-2990
                1573-7284
                3 May 2023
                3 May 2023
                2023
                : 38
                : 7
                : 795-807
                Affiliations
                [1 ]GRID grid.5337.2, ISNI 0000 0004 1936 7603, MRC Integrative Epidemiology Unit, , University of Bristol, ; Bristol, UK
                [2 ]GRID grid.5337.2, ISNI 0000 0004 1936 7603, Population Health Sciences, Bristol Medical School, , University of Bristol, ; Oakfield House, Oakfield Grove, Bristol, BS8 2BN UK
                [3 ]GRID grid.5337.2, ISNI 0000 0004 1936 7603, Musculoskeletal Research Unit, Translational Health Sciences, Bristol Medical School, , University of Bristol, ; Bristol, UK
                [4 ]GRID grid.8391.3, ISNI 0000 0004 1936 8024, Genetics of Complex Traits, College of Medicine and Health, , University of Exeter, ; Exeter, UK
                [5 ]GRID grid.5337.2, ISNI 0000 0004 1936 7603, NIHR Bristol Biomedical Research Centre Bristol, , University Hospitals Bristol and Weston NHS Foundation Trust, University of Bristol, ; Bristol, UK
                Author information
                http://orcid.org/0000-0002-5702-7728
                Article
                986
                10.1007/s10654-023-00986-6
                10276076
                37133737
                d9c830b3-5f7e-432c-a562-dc84873710a3
                © The Author(s) 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 6 October 2022
                : 2 March 2023
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000265, Medical Research Council;
                Award ID: MC_UU_00011/1
                Award ID: MR/N0137941/1
                Award ID: MR/T002239/1
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100014013, UK Research and Innovation;
                Award ID: MR/S003886/1
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000691, Academy of Medical Sciences;
                Award ID: SBF004\1079
                Award Recipient :
                Categories
                Locomotor Diseases
                Custom metadata
                © Pietro Paolo Sanna 2023

                Public health
                bone health,fracture risk,weight,body size,mendelian randomisation,lifecourse
                Public health
                bone health, fracture risk, weight, body size, mendelian randomisation, lifecourse

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