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Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, SwedenUnit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
Coffee and caffeine consumption have been associated with a lower risk of kidney stones in observational studies. We conducted a Mendelian randomization study to assess the causal nature of these associations.
Mendelian randomization analysis.
Setting & Participants
Independent genetic variants associated with coffee and caffeine consumption at the genome-wide significance level were selected from previously published meta-analyses as instrumental variables. Summary-level data for kidney stones were obtained from the UK Biobank study (6,536 cases and 388,508 noncases) and the FinnGen consortium (3,856 cases and 172,757 noncases).
Genetically predicted coffee and caffeine consumption.
Clinically diagnosed kidney stones.
Mendelian randomization methods were used to calculate causal estimates. Estimates from the 2 sources were combined using the fixed-effects meta-analysis methods.
Genetically predicted coffee and caffeine consumption was associated with a lower risk of kidney stones in the UK Biobank study, and the associations were directionally similar in the FinnGen consortium. The combined odds ratio of kidney stones was 0.60 (95% CI, 0.46-0.79; P < 0.001) per a genetically predicted 50% increase in coffee consumption and 0.81 (95% CI, 0.69-0.94; P = 0.005) per a genetically predicted 80-mg increase in caffeine consumption.
Genetic influence on kidney stone risk via pathways not involving coffee or caffeine.
Using genetic data, this study provides evidence that higher coffee and caffeine consumption may cause a reduction in kidney stones.
This Mendelian randomization study based on genetic data from 2 large studies found evidence to support causal associations between higher coffee and caffeine consumption and lower risk of kidney stones. Along with previous traditional epidemiological data, these findings suggest that coffee and caffeine consumption may prevent kidney stone disease.
consumption have been associated with a reduced risk of kidney stones in a large body of observational studies. Nevertheless, whether these associations are causal has not been established due to the possibility of confounding in observational studies and the lack of data from randomized controlled trials.
Employing genetic variants as instrumental variables for an exposure (eg, coffee consumption), the Mendelian randomization design can strengthen the causal inference.
The approach can minimize residual confounding because genetic variants are randomly allocated at conception and thus generally unrelated to confounders, such as environmental and self-adopted factors.
The random allocation of effect allele in the Mendelian randomization design resembles the randomization process in randomized controlled trials. In addition, the method can diminish reverse causation because genetic variants used to proxy the effect of the exposure cannot be modified by the onset and progression of the outcome.
There are 3 important assumptions of MR analysis (Fig 1). The first assumption is that the genetic variants proposed as instrumental variables should be robustly associated with the exposure; the second assumption indicates that the used genetic variants should not be associated with any confounders; and the third assumption is that the selected genetic variants should affect the risk of the outcome merely through the risk factor, not via alternative pathways.
The present study was based on publicly available summary-level data from large genome-wide association studies and consortia.
Genetic Instrument Selection
Fifteen single-nucleotide polymorphisms (SNPs) associated with coffee consumption at the genome-wide significance level (P < 5 × 10−8) were obtained from a meta-analysis of 4 genome-wide association studies (GWAS) on coffee consumption with up to 375,833 individuals of European ancestry (~89% from the UK Biobank study).
Twelve independent SNPs (r2< 0.01 and clump distance > 10,000 kb) were used as instrumental variables for coffee consumption. The effect sizes for the SNP-coffee associations were scaled to a 50% increase (eg, an increase from 1 cup to 1.5 cups). Two variants associated with caffeine consumption at P < 5 × 10−8 were used as instrumental variables for caffeine consumption from a meta-analysis of 6 GWAS including 9,876 individuals of European ancestry.
In UK Biobank, cases with kidney stones were defined by the International Classification of Diseases, 10th Revision (ICD-10), Office of Population and Censuses Surveys, and self-reported operation codes. GWAS was performed on 6,536 cases and 388,508 controls of European ancestry with the adjustment for sex, age, and the genotyping platform.
In FinnGen, cases were defined by N20 in ICD-10 and 592 in ICD-8 and ICD-9. The fourth release of the FinnGen consortium data was used with 3,856 cases and 172,757 noncases after the removal of individuals with ambiguous gender, high genotype missingness (>5%), excess heterozygosity (±4 SD), and non-Finnish ancestry. Association tests had been adjusted for age, sex, genetic principal components, and genotyping batch. Individuals who had withdrawn consent were excluded in both data sources.
The inverse-variance weighted (IVW) method was used as the main statistical model.
We used the IVW with random effects method to estimate the associations for genetically predicted coffee consumption and the IVW fixed-effects method (for analysis with <3 SNPs) to estimate the associations for genetically predicted caffeine consumption. The causal estimates were calculated by meta-analyzing SNP-specific Wald ratio estimates (ie, the beta coefficient for the effect of the SNP on the outcome divided by the beta coefficient for the effect of the SNP on the exposure) using a random- or fixed-effects inverse variance method that weights each ratio by its standard error.
All studies included in the GWAS cited here were approved by a relevant review board. The present MR analyses were approved by the Swedish Ethical Review Authority (2019-02793).
The F statistic was 159 for the association for coffee consumption in the UK Biobank. Genetically predicted coffee and caffeine consumption was inversely associated with a risk of kidney stones in the UK Biobank study, and the associations were directionally similar in the FinnGen consortium (Fig 2). After meta-analysis of the 2 data sources, the odds ratio of kidney stone disease was 0.57 (95% CI, 0.39-0.82; P = 0.003) per genetically predicted 50% greater coffee consumption and 0.86 (95% CI, 0.77-0.96; P = 0.008) per genetically predicted 80 mg greater caffeine consumption. The results for coffee consumption in relation to kidney stones remained consistent in sensitivity analyses (Table 2). We detected mild heterogeneity but no evidence of pleiotropy in the MR-Egger regression (P for the intercept > 0.2). MR-PRESSO analyses detected 2 outliers in the FinnGen consortium, respectively. The association remained after outlier removal (Table 2).
Table 2Association of Genetically Predicted Coffee Consumption With Risk of Kidney Stones in Sensitivity Analyses
Weighted median method
OR, 0.68 (95% CI, 0.50-0.93)
OR, 0.71 (95% CI, 0.38-1.34)
Intercept in MR-Egger regression
Weighted median method
OR, 0.71 (95% CI, 0.44-1.15)
OR, 0.96 (95% CI, 0.33-2.78)
OR, 0.65 (95% CI, 0.44-0.98)
Intercept in MR-Egger regression
Two outliers were detected in the MR-PRESSO analysis in FinnGen. No outlier was observed in the MR-PRESSO analysis in UKBB. Abbreviations: CI, confidence interval; FinnGen, FinnGen Consortium; OR, odds ratio; MR, Mendelian randomization; NA, not applicable; UKBB, UK Biobank.
The present MR study revealed inverse associations of genetically predicted coffee and caffeine consumption with risk of kidney stones in a combined sample of 7,396 cases and 530,411 noncases, which supported findings from most but not all observational studies.
In a recent systematic review, large-scale, population-based studies found that coffee consumption was associated with a lower risk of urinary stones, with similar associations for caffeinated and decaffeinated coffee consumption.
Furthermore, a cohort study including 194,095 participants reported an approximately 26% lower risk of developing kidney stones in individuals who consumed ≥1 serving per day of caffeinated coffee compared with those who consumed <1 serving per week.
Adequately compensated by water intake, the caffeine contained in coffee beverages results in an increase in urine flow, which represents an important protective factor against the development of kidney stones. Caffeine can also reduce calcium oxalate crystal adhesion on the apical surface of renal tubular epithelial cells.
There are strengths and limitations in this study. The major merit is the MR design, which strengthened the causal inference in the associations of coffee and caffeine consumption with risk of kidney stones. Additionally, we examined these associations in 2 independent populations, and the consistent results guaranteed the robustness of findings. We confined the studied population to individuals of European ancestry, which limited the population bias, whereas this might on the other side limit the generalizability of our findings to other populations. There was a large overlap in sample between exposure and outcome data, which might make the model overfitting and the causal estimates toward observational associations.
However, the F statistic > 10 indicated that the bias caused by sample overlap was likely to be minimal.
The important limitation is possible horizontal pleiotropy, which means that genetic instruments influence risk of kidney stones not via coffee or caffeine consumption but via other pathways. However, traits that are genetically correlated with coffee consumption, such as obesity and smoking, appear to increase risk of kidney stone disease
and are therefore unlikely to bias inverse associations between coffee consumption and kidney stone formation. Another pleiotropic factor may be daily fluid intake, which is likely to be positively correlated with coffee and caffeine consumption and inversely associated with risk of kidney stone disease.
In conclusion, this MR study provides genetic evidence in support of causal inverse associations of coffee and caffeine consumption with kidney stones. Increasing coffee and caffeine consumption may be a prevention strategy for kidney stones.
Authors’ Full Names and Academic Degrees
Shuai Yuan, BMed, MMedSc, and Susanna C. Larsson, PhD.
Study design: SCL; data analysis: SY. Each author contributed important intellectual content during manuscript drafting or revision and accepts accountability for the overall work by ensuring that questions pertaining to the accuracy or integrity of any portion of the work are appropriately investigated and resolved.
This study is supported by the Swedish Research Council for Health, Working Life and Welfare (Forte; grant no. 2018-00123) and the Swedish Research Council (Vetenskapsrådet; grant no. 2019-00977). The funders did not have a role in study design, data collection, analysis, reporting, or the decision to submit for publication.
The authors declare that they have no relevant financial interests.
Genetic instruments for coffee consumption and caffeine were obtained from the cited meta-analyses of genome-wide association studies. Genetic association estimates for kidney stones were obtained from the UK Biobank study and the FinnGen consortium. The authors thank all investigators for sharing these data.
All data analyzed in this study are listed in Table 1.
Received March 12, 2021. Evaluated by 2 external peer reviewers, with direct editorial input from a Statistics/Methods Editor, an Associate Editor, and the Editor-in-Chief. Accepted in revised form April 26, 2021.
Kidney stones: a global picture of prevalence, incidence, and associated risk factors.