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      Serum Phosphate, BMI, and Body Composition of Middle-Aged and Older Adults: A Cross-Sectional Association Analysis and Bidirectional Mendelian Randomization Study

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          ABSTRACT

          Background

          Observational studies have reported associations between serum phosphate and BMI in specific clinical settings, but the nature of this relation in the general population is unclear.

          Objectives

          The aim of this study was twofold: to investigate the association between serum phosphate and BMI and body composition, as well as to explore evidence of causality through a bidirectional one-sample Mendelian randomization (MR) in the population-based Rotterdam Study (RS).

          Methods

          Observational associations between phosphate (mg/dL) and BMI, lean mass, and fat percentage (fat%), estimated by DXA, were analyzed using multivariable regression models in 9202 participants aged 45–100 y from 3 RS cohorts. The role of serum leptin was examined in a subgroup of 1089 participants. For MR analyses, allele scores with 6 single-nucleotide polymorphisms (SNPs) for phosphate and 905 SNPs for BMI were constructed in 7983 participants.

          Results

          Phosphate was inversely associated with BMI in the total population (β: –0.89; 95% CI: –1.17, –0.62), and stronger in women (β: –1.92; 95% CI: –2.20, –1.65) than in men (β: –0.37; 95% CI: –0.68, –0.06) ( P-interaction < 0.05). Adjustment for leptin did not change results in men. In women, adjustment for leptin attenuated the association, but it was not abolished (β: –0.94; 95% CI: –1.45, –0.42). Phosphate was inversely associated with fat%, but not with lean mass, in both sexes. MR analyses suggested a causal effect of BMI on serum phosphate (β: –0.01; 95% CI: –0.02, 0.00) but not vice versa.

          Conclusions

          Serum phosphate was inversely associated with BMI and fat% in a population-based study of middle-aged and older adults, with a stronger effect in women than in men. Adjusting for leptin attenuated this relation in women only. MR results suggest a causal effect of BMI on phosphate but not vice versa. An underlying sex dimorphism in phosphate homeostasis should be further explored.

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          Most cited references64

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          A new equation to estimate glomerular filtration rate.

          Equations to estimate glomerular filtration rate (GFR) are routinely used to assess kidney function. Current equations have limited precision and systematically underestimate measured GFR at higher values. To develop a new estimating equation for GFR: the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation. Cross-sectional analysis with separate pooled data sets for equation development and validation and a representative sample of the U.S. population for prevalence estimates. Research studies and clinical populations ("studies") with measured GFR and NHANES (National Health and Nutrition Examination Survey), 1999 to 2006. 8254 participants in 10 studies (equation development data set) and 3896 participants in 16 studies (validation data set). Prevalence estimates were based on 16,032 participants in NHANES. GFR, measured as the clearance of exogenous filtration markers (iothalamate in the development data set; iothalamate and other markers in the validation data set), and linear regression to estimate the logarithm of measured GFR from standardized creatinine levels, sex, race, and age. In the validation data set, the CKD-EPI equation performed better than the Modification of Diet in Renal Disease Study equation, especially at higher GFR (P < 0.001 for all subsequent comparisons), with less bias (median difference between measured and estimated GFR, 2.5 vs. 5.5 mL/min per 1.73 m(2)), improved precision (interquartile range [IQR] of the differences, 16.6 vs. 18.3 mL/min per 1.73 m(2)), and greater accuracy (percentage of estimated GFR within 30% of measured GFR, 84.1% vs. 80.6%). In NHANES, the median estimated GFR was 94.5 mL/min per 1.73 m(2) (IQR, 79.7 to 108.1) vs. 85.0 (IQR, 72.9 to 98.5) mL/min per 1.73 m(2), and the prevalence of chronic kidney disease was 11.5% (95% CI, 10.6% to 12.4%) versus 13.1% (CI, 12.1% to 14.0%). The sample contained a limited number of elderly people and racial and ethnic minorities with measured GFR. The CKD-EPI creatinine equation is more accurate than the Modification of Diet in Renal Disease Study equation and could replace it for routine clinical use. National Institute of Diabetes and Digestive and Kidney Diseases.
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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
                Journal
                J Nutr
                J Nutr
                jn
                The Journal of Nutrition
                Oxford University Press
                0022-3166
                1541-6100
                January 2022
                09 November 2021
                09 November 2021
                : 152
                : 1
                : 276-285
                Affiliations
                Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam , Rotterdam, The Netherlands
                Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam , Rotterdam, The Netherlands
                Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam , Rotterdam, The Netherlands
                Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam , Rotterdam, The Netherlands
                Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam , Rotterdam, The Netherlands
                Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam , Rotterdam, The Netherlands
                Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam , Rotterdam, The Netherlands
                Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam , Rotterdam, The Netherlands
                Author notes
                Address correspondence to MCZ (e-mail: m.c.zillikens@ 123456erasmusmc.nl )

                AB and NC-O contributed equally to this work.

                Author information
                https://orcid.org/0000-0002-7466-1472
                https://orcid.org/0000-0001-7999-5538
                https://orcid.org/0000-0003-2830-6813
                https://orcid.org/0000-0002-7276-3387
                Article
                nxab351
                10.1093/jn/nxab351
                8754515
                34601595
                65655b4f-169a-4b43-8373-9771078d5527
                © The Author(s) 2021. Published by Oxford University Press on behalf of the American Society for Nutrition.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License ( https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@ 123456oup.com

                History
                : 01 July 2021
                : 20 August 2021
                : 24 September 2021
                Page count
                Pages: 10
                Funding
                Funded by: Netherlands Organisation for Scientific Research, DOI 10.13039/501100003246;
                Award ID: 175.010.2005.011
                Award ID: 911-03-012
                Funded by: Genetic Laboratory of the Department of Internal Medicine;
                Funded by: Erasmus MC, DOI 10.13039/501100003061;
                Award ID: 014-93-015
                Funded by: Netherlands Genomics Initiative;
                Funded by: Netherlands Consortium for Healthy Aging;
                Award ID: 050-060-810
                Categories
                Nutritional Epidemiology
                AcademicSubjects/MED00060
                AcademicSubjects/SCI00960

                Nutrition & Dietetics
                phosphate,bmi,mendelian randomization,fat mass,lean mass,population-based cohort
                Nutrition & Dietetics
                phosphate, bmi, mendelian randomization, fat mass, lean mass, population-based cohort

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