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M Mazidi et al, 2022. The association between coffee and caffeine consumption and renal function: insight from individual-level data, Mendelian randomization, and meta-analysis, Archives of Medical Science.

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

M Mazidi et al, 2022
Archives of Medical Science
July 20, 2022

ABSTRACT

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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