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Abstract
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. 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.
Highlights
Along with previous traditional epidemiological data, these findings suggest that coffee and caffeine consumption may prevent kidney stone disease
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 per genetically predicted 50% greater coffee consumption and 0.86 per genetically predicted 80 mg greater caffeine consumption
Summary
Study DesignMR analysis is an instrumental variable analysis with the use of genetic variants as instrumental variables.[11]. 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.[10] The present study was based on publicly available summary-level data from large genome-wide association studies and consortia. Fifteen single-nucleotide polymorphisms (SNPs) associated with coffee consumption at the genome-wide significance level (P < 5 × 10−8) were obtained from a metaanalysis 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).[12] Twelve independent SNPs (r2 < 0.01 and clump distance > 10,000 kb) were used as instrumental variables for coffee consumption.
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