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      Causal effects of relative fat, protein, and carbohydrate intake on chronic kidney disease: a Mendelian randomization study

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          ABSTRACT

          Background

          The effects of specific macronutrients on kidney function independent of total calorie intake have rarely been studied, although the composition of macronutrient intake has been reported to affect health outcomes.

          Objectives

          We aimed to investigate the effects of macronutrient intake ratios on the risk of chronic kidney disease (CKD) by Mendelian randomization (MR) analysis.

          Methods

          The study was an observational cohort study mainly based on the UK Biobank and including MR analysis. First, we evaluated the relative baseline macronutrient composition—that is, the number of calories from each macronutrient divided by total calorie intake—of the diets of UK Biobank participants, and we used Cox regression to assess the incidence of end-stage kidney disease (ESKD) in 65,164 participants with normal kidney function [estimated glomerular filtration rate (eGFR) ≥60 mL/min/1.73 m2]. We implemented a genetic instrument for relative fat, protein, and carbohydrate intake developed by a previous genome-wide association study (GWAS) and performed MR analysis. Two-sample MR was performed with the summary statistics from independent CKDGen GWAS for kidney function traits (n = 567,460), including CKD (eGFR <60 mL/min/1.73 m2) and log-transformed eGFR.

          Results

          The median relative macronutrient intake composition at baseline was 35% fats, 15% protein, and 50% carbohydrates. Higher relative protein intake in subjects with normal kidney function was significantly associated with a lower risk of incident ESKD (HR: 0.54; 95% CI: 0.30, 0.95) in the observational investigation. Two-sample MR indicated that increased relative fat intake causally increased the risk of kidney function impairment [CKD (OR: 1.94; 95% CI: 1.39, 2.71); log eGFR (β: −0.036; 95% CI: −0.048, −0.024)] and that higher relative protein intake was causally linked to a lower CKD risk [CKD (OR: 0.50; 95% CI: 0.35, 0.72); log eGFR (β: 0.044; 95% CI: 0.030, 0.058)].

          Conclusions

          A desirable macronutrient composition, including high relative protein intake and low relative fat intake, may causally reduce the risk of CKD in the general population.

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          Most cited references39

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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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            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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              Second-generation PLINK: rising to the challenge of larger and richer datasets

              PLINK 1 is a widely used open-source C/C++ toolset for genome-wide association studies (GWAS) and research in population genetics. However, the steady accumulation of data from imputation and whole-genome sequencing studies has exposed a strong need for even faster and more scalable implementations of key functions. In addition, GWAS and population-genetic data now frequently contain probabilistic calls, phase information, and/or multiallelic variants, none of which can be represented by PLINK 1's primary data format. To address these issues, we are developing a second-generation codebase for PLINK. The first major release from this codebase, PLINK 1.9, introduces extensive use of bit-level parallelism, O(sqrt(n))-time/constant-space Hardy-Weinberg equilibrium and Fisher's exact tests, and many other algorithmic improvements. In combination, these changes accelerate most operations by 1-4 orders of magnitude, and allow the program to handle datasets too large to fit in RAM. This will be followed by PLINK 2.0, which will introduce (a) a new data format capable of efficiently representing probabilities, phase, and multiallelic variants, and (b) extensions of many functions to account for the new types of information. The second-generation versions of PLINK will offer dramatic improvements in performance and compatibility. For the first time, users without access to high-end computing resources can perform several essential analyses of the feature-rich and very large genetic datasets coming into use.
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                Author and article information

                Contributors
                Journal
                The American Journal of Clinical Nutrition
                Oxford University Press (OUP)
                0002-9165
                1938-3207
                February 10 2021
                February 10 2021
                Affiliations
                [1 ]Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea
                [2 ]Department of Internal Medicine, Armed Forces Capital Hospital, Gyeonggi-do, Korea
                [3 ]Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea
                [4 ]Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea
                [5 ]Department of Internal Medicine, Keimyung University School of Medicine, Daegu, Korea
                [6 ]Transdisciplinary Department of Medicine & Advanced Technology, Seoul National University Hospital, Seoul, Korea
                [7 ]Kidney Research Institute, Seoul National University, Seoul, Korea
                [8 ]Department of Internal Medicine, Seoul National University Boramae Medical Center, Seoul, Korea
                Article
                10.1093/ajcn/nqaa379
                33564816
                55081230-1874-4ac3-ab2c-33202efe5eb5
                © 2021

                https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model

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