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The association between coffee and caffeine consumption and renal function: insight from individual-level data, Mendelian randomization, and meta-analysis

INTRODUCTION: The reported relationship between coffee intake and renal function is poorly understood. By applying two-sample Mendelian randomization (MR) and systematic review and meta-analysis we investigated the association of caffeine and coffee intake with prevalent CKD and markers of renal fun...

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Autores principales: Mazidi, Mohsen, Mikhailidis, Dimitri P., Dehghan, Abbas, Jóźwiak, Jacek, Covic, Adrian, Sattar, Naveed, Banach, Maciej
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Termedia Publishing House 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9266873/
https://www.ncbi.nlm.nih.gov/pubmed/35832703
http://dx.doi.org/10.5114/aoms/144905
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author Mazidi, Mohsen
Mikhailidis, Dimitri P.
Dehghan, Abbas
Jóźwiak, Jacek
Covic, Adrian
Sattar, Naveed
Banach, Maciej
author_facet Mazidi, Mohsen
Mikhailidis, Dimitri P.
Dehghan, Abbas
Jóźwiak, Jacek
Covic, Adrian
Sattar, Naveed
Banach, Maciej
author_sort Mazidi, Mohsen
collection PubMed
description INTRODUCTION: The reported relationship between coffee intake and renal function is poorly understood. By applying two-sample Mendelian randomization (MR) and systematic review and meta-analysis we investigated the association of caffeine and coffee intake with prevalent CKD and markers of renal function. MATERIAL AND METHODS: For the individual data analysis we analyzed the National Health and Nutrition Examination Surveys (NHANES) data on renal function markers and caffeine intake. MR was implemented by using summary-level data from the largest ever genome-wide association studies (GWAS) conducted on coffee intake (N = 91,462) and kidney function (N = 133,413). The inverse variance weighted method (IVW), weighted median-based method, MR-Egger, MR-RAPS, and MR-PRESSO were applied. Random effects models and generic inverse variance methods were used to synthesize quantitative and pooled data for the meta-analysis, followed by a leave-one-out method for sensitivity analysis. RESULTS: Finally, we included the data of 18,436 participants; 6.9% had prevalent CKD (based on eGFR). Caffeine intake for the general population was 131.1 ±1.1 mg. The percentage of participants with CKD, by caffeine quartile, was 16.6% in the first (lowest) quartile, 13.9% in the second, 12.2% in the third and 11.0% in the top quartile (p < 0.001). After adjustment, for increasing quartiles for caffeine consumption, mean urine albumin, albumin-creatinine ratio and estimated glomerular filtration rate (GFR) did not change significantly (p > 0.234). In fully adjusted logistic regression models, there was no significant difference in chances of CKD prevalence (p-trend = 0.745). In the same line, the results of MR showed no impact of coffee intake on CKD (IVW: β = –0.0191, SE = 0.069, p = 0.781) or on eGFR (overall = IVW: β = –0.0005, SE = 0.005, p = 0.926) either in diabetic (IVW: β = –0.006, SE = 0.009, p = 0.478) or non-diabetic patients (IVW: β = –6.772, SE = 0.006, p = 0.991). Results from the meta-analysis indicated that coffee consumption was not significantly associated with CKD (OR = 0.85, 95% CI: 0.71–1.02, p = 0.090, n = 6 studies, I (2) = 0.32). These findings were robust in sensitivity analyses. CONCLUSIONS: Implementing different strategies, we detected no significant association between coffee consumption and renal function or risk of CKD.
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spelling pubmed-92668732022-07-12 The association between coffee and caffeine consumption and renal function: insight from individual-level data, Mendelian randomization, and meta-analysis Mazidi, Mohsen Mikhailidis, Dimitri P. Dehghan, Abbas Jóźwiak, Jacek Covic, Adrian Sattar, Naveed Banach, Maciej Arch Med Sci Systematic review/Meta-analysis INTRODUCTION: The reported relationship between coffee intake and renal function is poorly understood. By applying two-sample Mendelian randomization (MR) and systematic review and meta-analysis we investigated the association of caffeine and coffee intake with prevalent CKD and markers of renal function. MATERIAL AND METHODS: For the individual data analysis we analyzed the National Health and Nutrition Examination Surveys (NHANES) data on renal function markers and caffeine intake. MR was implemented by using summary-level data from the largest ever genome-wide association studies (GWAS) conducted on coffee intake (N = 91,462) and kidney function (N = 133,413). The inverse variance weighted method (IVW), weighted median-based method, MR-Egger, MR-RAPS, and MR-PRESSO were applied. Random effects models and generic inverse variance methods were used to synthesize quantitative and pooled data for the meta-analysis, followed by a leave-one-out method for sensitivity analysis. RESULTS: Finally, we included the data of 18,436 participants; 6.9% had prevalent CKD (based on eGFR). Caffeine intake for the general population was 131.1 ±1.1 mg. The percentage of participants with CKD, by caffeine quartile, was 16.6% in the first (lowest) quartile, 13.9% in the second, 12.2% in the third and 11.0% in the top quartile (p < 0.001). After adjustment, for increasing quartiles for caffeine consumption, mean urine albumin, albumin-creatinine ratio and estimated glomerular filtration rate (GFR) did not change significantly (p > 0.234). In fully adjusted logistic regression models, there was no significant difference in chances of CKD prevalence (p-trend = 0.745). In the same line, the results of MR showed no impact of coffee intake on CKD (IVW: β = –0.0191, SE = 0.069, p = 0.781) or on eGFR (overall = IVW: β = –0.0005, SE = 0.005, p = 0.926) either in diabetic (IVW: β = –0.006, SE = 0.009, p = 0.478) or non-diabetic patients (IVW: β = –6.772, SE = 0.006, p = 0.991). Results from the meta-analysis indicated that coffee consumption was not significantly associated with CKD (OR = 0.85, 95% CI: 0.71–1.02, p = 0.090, n = 6 studies, I (2) = 0.32). These findings were robust in sensitivity analyses. CONCLUSIONS: Implementing different strategies, we detected no significant association between coffee consumption and renal function or risk of CKD. Termedia Publishing House 2021-12-14 /pmc/articles/PMC9266873/ /pubmed/35832703 http://dx.doi.org/10.5114/aoms/144905 Text en Copyright: © 2022 Termedia & Banach https://creativecommons.org/licenses/by-nc-sa/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) License, allowing third parties to copy and redistribute the material in any medium or format and to remix, transform, and build upon the material, provided the original work is properly cited and states its license.
spellingShingle Systematic review/Meta-analysis
Mazidi, Mohsen
Mikhailidis, Dimitri P.
Dehghan, Abbas
Jóźwiak, Jacek
Covic, Adrian
Sattar, Naveed
Banach, Maciej
The association between coffee and caffeine consumption and renal function: insight from individual-level data, Mendelian randomization, and meta-analysis
title The association between coffee and caffeine consumption and renal function: insight from individual-level data, Mendelian randomization, and meta-analysis
title_full The association between coffee and caffeine consumption and renal function: insight from individual-level data, Mendelian randomization, and meta-analysis
title_fullStr The association between coffee and caffeine consumption and renal function: insight from individual-level data, Mendelian randomization, and meta-analysis
title_full_unstemmed The association between coffee and caffeine consumption and renal function: insight from individual-level data, Mendelian randomization, and meta-analysis
title_short The association between coffee and caffeine consumption and renal function: insight from individual-level data, Mendelian randomization, and meta-analysis
title_sort association between coffee and caffeine consumption and renal function: insight from individual-level data, mendelian randomization, and meta-analysis
topic Systematic review/Meta-analysis
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9266873/
https://www.ncbi.nlm.nih.gov/pubmed/35832703
http://dx.doi.org/10.5114/aoms/144905
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