Kidney disease
Does high blood uric acid actually cause kidney disease?
Open access · cc by · source: Europe PMC
People whose genes give them lifelong higher uric acid do not have worse kidney function, suggesting the familiar link between uric acid and kidney disease is not causal.
Study at a glance
- Design
- Mendelian randomisation — Two-sample MR using 26 urate-raising genetic variants as instruments against published GWAS summary statistics for eGFR and CKD, analysed with 7 pleiotropy-robust methods; replicated in UK Biobank and by a genetic risk score in 4 US population cohorts, with gout as a positive control.
- N
- No single N: the urate GWAS had 110,347 people; CKD summary data had 12,385 cases and 104,780 controls; UK Biobank added 335,212 people (5,615 CKD cases); the individual-level cohorts totalled 13,425.
- Population
- Adults of European ancestry in genetic consortia, UK Biobank, and the ARIC, CARDIA, CHS and Framingham cohorts.
- Outcome
- Estimated glomerular filtration rate (eGFR) and chronic kidney disease (eGFR below 60 or clinical diagnosis codes); gout as a positive-control outcome.
Structured fields used in claim comparison tables when every cited study has a complete layer.
Key findings
None of the 7 methods found a causal effect of urate on eGFR or on CKD, and the UK Biobank and cohort analyses were also null (genetic risk score and CKD: odds ratio 1.05, not significant). The same variants clearly raised gout risk, showing the instruments worked. In contrast, ordinary observational analysis of the same cohorts found that each 1 mg/dl of urate went with 1.48 times the odds of CKD. The study had over 99% power to detect an effect as large as the observational one.
Methodology
The researchers used Mendelian randomization, treating 26 genetic variants that raise serum urate as a natural experiment assigned at conception. They tested whether these variants predicted kidney function (eGFR) or chronic kidney disease in large genome-wide datasets, using 7 different methods designed to cope with variants that might affect the kidney through other pathways. They repeated the test in UK Biobank using hospital diagnosis codes, and in 4 US population cohorts using each person's genetic risk score, and checked that the same variants did predict gout, which urate is known to cause.
Limitations
Mendelian randomization estimates the effect of lifelong, genetically raised urate, which may not match the effect of lowering urate with a drug later in life, and it cannot rule out benefits of xanthine oxidase inhibitors that act through reduced oxidative stress rather than lower urate. All participants were of European ancestry, so the result may not generalise to other populations. The genetic instruments showed substantial pleiotropy, and some GWAS participants may have been on urate-lowering drugs; the authors addressed both with robust methods and sensitivity analyses, but these remain assumptions rather than proofs.
How this study connects
Role on claims
Each row is a claim on a concept or method page where this paper supports, challenges, or qualifies the statement. Roles are hand-checked — not a model guess.
The uric acid-CKD link seen in ordinary studies is probably not causal.
Mendelian randomization using 26 urate-raising variants found no causal effect of serum urate on eGFR or CKD, although the same variants raised gout risk and observational analysis of the same cohorts showed 1.48 times the odds of CKD per 1 mg/dl urate.
Evidence for the claim as stated.
Observational data link higher urate to CKD, but genetic (Mendelian randomization) evidence does not support a causal effect. Both designs were applied to overlapping cohorts; the conflict is between an association and a causal estimate.
Evidence for the claim as stated.
Open questions
Tensions this paper is part of
From concept pages' “where studies disagree.” Disagreement means the same question; scope means different assays, populations, or outcomes.
Observational data link higher urate to CKD, but genetic (Mendelian randomization) evidence does not support a causal effect. Both designs were applied to overlapping cohorts; the conflict is between an association and a causal estimate.
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