Two genes do most of the inherited work here, and both of them are plumbing: one moves urate out through the kidney, the other out through the gut. Neither is a reason to test, and one of them is a reason to be careful with a drug.
Solid lines are connections this site curates. Dashed lines mean the two ends share a research paper — worth knowing, and not a claim that one explains the other.
Gout is arthritis caused by a crystal. When urate — the end product of purine breakdown — rises past what blood can hold, it can come out of solution as needle-shaped crystals in a joint. The immune system attacks the crystals, and the result is one of the most violently painful things a joint can do: usually the base of the big toe, usually overnight, red and hot and untouchable.
It has a reputation as a disease of excess, and diet does matter. It matters less than most people are told, and rather less than inheritance does.
Urate is not made in an unusual way in people who get gout. It is removed in an unusual way. Both major genes here are transporters — proteins that carry urate across a membrane and out.
rs4475146 is in SLC2A9, which reabsorbs urate in the kidney: it decides how much of what is filtered out gets pulled back in. It has the largest effect on blood urate of any common variant known, in either direction.
rs1481012 is in ABCG2, which pumps urate out into the intestine. When it works less well, a route of disposal narrows.
The scale of these effects is unusual for common variants. In a 2008 study, the missense variant in SLC2A9 reached a p-value of 7 × 10⁻¹⁶⁸ for blood urate and was associated with gout at an odds ratio of 0.59 per copy of the protective allele; the missense variant in ABCG2 was associated with gout at OR 1.74. Those are not the fractional shifts common-variant genetics usually delivers.
A 2013 study of more than 140,000 people found 28 loci affecting blood urate — 18 of them new — and checked each one against gout itself and against how much urate the kidney excretes. Effects were of similar size in several non-European groups, which is not something that can be assumed.
The pathways the analysis pointed at were not only transport: glucose metabolism turned up too, which is part of why gout keeps company with obesity, diabetes and high blood pressure rather than arriving alone.
The two genes above are not the whole story. Sixteen more positions on this page come from five further studies of blood urate specifically, and SLC2A9 keeps turning out to be the strongest common-variant hit for the trait, study after study.
The discovery came first: rs6855911, in what was then called simply "GLUT9" — the same gene now known as SLC2A9 — was identified in 2007 in Sardinian and Tuscan cohorts, one of the earliest genome-wide scans to implicate this gene at all.
A 2010 CHARGE Consortium study of 28,283 people, replicated in 22,054 more, built an eight-locus "genetic urate score" — including three more of this page's variants, rs13129697 (also SLC2A9), rs675209 (RREB1) and rs1106766 (INHBC) — and used it as a natural experiment. The score was strongly associated with both urate and gout, but showed no association at all with blood pressure, glucose, kidney function or coronary heart disease. That is genetic evidence against, not for, the idea that urate itself damages the heart — gout and cardiovascular disease keep company for other reasons, not because one straightforwardly causes the other.
A larger 2021 UK Biobank study of 363,228 people, covering 35 different blood and urine biomarkers at once, contributed 56 of this page's variants in total. Using the same genetic-instrument logic as the CHARGE score above, at far greater scale, it confirmed a causal effect of urate on gout specifically — one of 51 such causal relationships the study established across all 35 biomarkers together.
The same study put that causal finding to practical use: it built a combined "multi-PRS" model, one polygenic risk score per biomarker used together rather than a single urate score alone, and tested it in an independent cohort of 135,500 people. For gout specifically, that combined model improved genetic risk stratification beyond what the urate score alone could manage — evidence that gout's genetic risk is not fully captured by urate genetics in isolation, even though urate is the proximate, causal driver described above.
The remaining loci come from a Japanese biochemical-trait GWAS (three variants, including further hits in ABCG2, SLC2A9 and SLC22A12) and a Scottish cohort study that used deeper genotype imputation to find two rarer variants, near FAM134B and ZNF160 — a reminder that even a trait mapped this thoroughly still has loci too rare for most studies to catch.
High urate is necessary for gout and nowhere near sufficient: most people with raised urate never have an attack. And of the variation in blood urate between people, diet accounts for a strikingly small share compared with these transporters.
That is not permission, and it is not blame either. It is a correction to a story in which gout is something a person did to themselves.
Not these two. A different position, in HLA-B, does: the allele HLA-B*58:01 raises the risk of a rare but severe skin reaction to allopurinol, the most-prescribed urate-lowering drug. Prescribing guidance recommends testing before starting allopurinol in the populations where that allele is common — see the allopurinol page.
That is the reverse of the usual direction. It is not a genotype telling somebody to take something; it is a genotype telling a prescriber to look before they do.
Positions joined since this page was written
What this is The text above discusses the variants this page was written around. Since then the catalogue has joined 643 more positions to it, by shared trait or shared paper. They are listed here by the paper each came from; the text does not describe them, and each variant page carries that study's own record.
Sinnott-Armstrong N et al. 2021, Nature genetics rs36095412 (RNF186), rs79091515 (RNF2), rs2955742 (TMEM266), rs55653892 (near ANP32BP1), rs72925159 (MTX2), rs34355135 (LRP2), rs4916009 (JAK1), rs932046 (near RCN2), rs11626364 (MIDEAS), rs9887921 (TCEA3), rs72768728 (TBC1D24), rs10494326 (near CRPP1) and 495 more — PMID:33462484
Major TJ et al. 2024, Nature genetics rs2581817 (SFMBT1), rs9426886 (TRIM46), rs7675964 (SLC2A9), rs17298067 (NFAT5), rs75312918 (FBRSL1), rs12251238 (TCF7L2), rs62252461 (CADM2), rs489837 (APCDD1), rs190676167 (RUVBL2), rs17767183 (IL1R1), rs6031601 (HNF4A), rs1991371 (BMPR2) and 100 more — PMID:39406924
Verma A et al. 2024, Science (New York, N.Y.) rs725686 (AKAP13), rs2941470 (HNF4G), rs2728109 (PKD2), rs2611336 (ZNF318), rs9666878 (near KAT5), rs10763558 (BICC1), rs1896246 (BICC1), rs75614137 (SFMBT1), rs6760274 (near TMEM18), rs532582234 (near RNU6-983P), rs4962696 (EEF1AKMT2), rs10799945 (near U3) — PMID:39024449
Zhou W et al. 2022, Cell genomics rs16856530 (LRP2), rs2728099 (PKD2), rs4515883 (SHLD2) — PMID:36777996
Folkersen L et al. 2020, Nature metabolism rs142444346 (LRRC36), rs4894192 (LINC01117) — PMID:33067605
Suhre K et al. 2017, Nature communications rs7184253 (LRRC36), rs8051517 (SMPD3) — PMID:28240269
Sumpter NA et al. 2023, Arthritis & rheumatology (Hoboken, N.J.) rs6811287 (near WDR1), rs853685 (near SMIM15P2) — PMID:36281732
Pietzner M et al. 2021, Science (New York, N.Y.) rs3892816 (ATP6V0D1) — PMID:34648354
Sun BB et al. 2018, Nature rs60697456 (CTCF-DT) — PMID:29875488
Jiang L et al. 2021, Nature genetics rs544648171 (near FLJ46284) — PMID:34737426
2026-07-31 · Genome-wide association study identifies toll-like receptor four protein-mediated metabolic remodelling affecting gout pathogenesis. Journal of Global Health. 2026. DOI:10.7189/jogh.16.04268
Why does obesity cause gout? Genetic evidence points to TLR4, not just extra uric acid
Obesity is a well-established risk factor for gout, but this study asked what genetically links the two beyond simply generating more uric acid. Combining observational data from 9,700 NHANES adults with two-sample Mendelian randomization on genome-wide association summary statistics, it confirmed a dose-dependent relationship between BMI and gout (OR=1.97), then systematically screened 113 druggable genes for a genetic mediator. Toll-like receptor 4 (TLR4) emerged as a genetically supported candidate: Bayesian colocalization found shared causal variants between BMI and gout risk at the TLR4 locus (posterior probability >0.75), and multivariable Mendelian randomization showed TLR4 affects gout risk independently of BMI itself (beta=0.23, P=0.011) -- evidence for a specific metabolic-immune pathway, not just 'more weight, more uric acid, more gout.' This site's own gout page carries 59 variants; TLR4 is not currently among them, and this study reports gene-level Mendelian randomization evidence rather than a single lead rsID with a GWAS Catalog-style p-value, so this entry adds context to the condition page rather than a new variant page.
2026-01-28 · Namba S, et al., Nature 2026, PMID:41606330
A cross-population compendium of gene-environment interactions
An atlas of gene-environment interactions — where a variant's effect size differs by age, sex or lifestyle — built from 440,210 people of European and Japanese ancestry and replicated in 539,794 more from diverse populations. Decomposing the contributions of age, sex and lifestyle exposed the aetiology of these interactions, including reverse causality from disease-driven changes in diet, and showed that they affect polygenic prediction accuracy and how well scores transfer across populations. Omics-level analyses found sex-discordant genetic effects in lipid metabolism, which the authors connect to failures of genetically supported drug trials. The variant that dominates this catalogue's overlap with the study is rs671 in ALDH2 — the alcohol flush variant — whose effects on liver enzymes (AST, ALT), HDL cholesterol and red-cell indices differ by sex, ever-drinking and smoking; also on this site from the study: rs145954970 (SLC22A11, uric acid, gout), rs11066015 (ACAD10, red-cell count by drinking), rs730154 (CYP19A1, height by sex) and rs35747824 (PDILT, creatinine by age). PMID:41606330.
Sources. Köttgen et al. (Nat Genet 2013) combined data from more than 140,000 individuals of European ancestry within the Global Urate Genetics Consortium and identified and replicated 28 genome-wide significant loci for serum urate concentration, 18 of them novel. The loci were further characterised for association with gout, for transcript expression and for the fractional excretion of urate; associations for many were of similar magnitude in individuals of non-European ancestry. Network analysis implicated inhibin–activin signalling and glucose metabolism in systemic urate control. This is the study the collector recorded as the source for both positions listed on this page.
Effect sizes at the two major loci. Dehghan et al. (Lancet 2008), in genome-wide analyses of the Framingham and Rotterdam cohorts with replication in ARIC, reported the missense variant rs16890979 in SLC2A9 at p = 7.0 × 10⁻¹⁶⁸ for serum urate in white participants and OR 0.59 per T allele (95% CI 0.52–0.68) for gout, and the missense variant rs2231142 in ABCG2 (Q141K) at p = 2.5 × 10⁻⁶⁰ for urate and OR 1.74 (95% CI 1.51–1.99) for gout, direction-consistent in black participants. rs16890979 is now on this page — the collector filed it under Urate levels rather than under Gout itself, and it is linked here on the strength of the gout odds ratio Dehghan et al. reported directly. The ABCG2 missense position, rs2231142, is still not in our variant table; the ABCG2 positions listed here mark the same gene, not the same marker.
Diagnosis. Definitive diagnosis is the identification of monosodium urate crystals in synovial fluid under polarised light. Serum urate measured during an acute attack can be normal and does not exclude the diagnosis. No genotype is used diagnostically.
Pharmacogenomics. HLA-B*58:01 is associated with allopurinol-induced severe cutaneous adverse reactions, including Stevens–Johnson syndrome, toxic epidermal necrolysis and DRESS. CPIC published a guideline for HLA-B genotype and allopurinol dosing in 2013 and confirmed in its 2015 update that the recommendation was unchanged. Allele frequency is markedly population-dependent, and testing recommendations are framed accordingly.
What a 23andMe/AncestryDNA export or raw VCF can and can't tell you about Gout comes down to these specific, well-studied positions — not a diagnosis. 782 positions are linked to this page; the ones this page's own text discusses are shown first.
The studies behind these variants recruited participants from different ancestries — a result found in one population doesn't always transfer to another. Based on 639 of 782 linked studies with a resolved discovery ancestry.
Research-derived gene–drug associations only — not a prescription, dosing guide, or medical advice. Always follow your prescriber's guidance.
| Gene | Drug | What the research shows |
|---|---|---|
| HLA-B | Allopurinol | The HLA-B*58:01 allele is associated with a substantially increased risk of severe cutaneous adverse reactions to allopurinol — Stevens–Johnson syndrome, toxic epidermal necrolysis and DRESS. CPIC published a guideline for HLA-B genotype and allopurinol dosing and confirmed in its 2015 update that the original recommendation stands. Allele frequency varies widely between populations, which is why testing guidance is population-specific rather than universal. This is a safety check before prescribing, not a dosing adjustment and not something to act on from a raw data file. (CPIC guidelines for HLA-B genotype and allopurinol dosing: 2015 update (Clin Pharmacol Ther 2016, PMID 26094938).) |
| HPRT1 | Mycophenolic acid | Mycophenolic acid, an immunosuppressant used after organ transplant and for some autoimmune conditions, carries an FDA label warning specifically for people with confirmed HPRT1 deficiency — the enzyme defect behind Lesch-Nyhan syndrome and its milder form, Kelley-Seegmiller syndrome, both of which cause a severe genetic form of gout through uric acid overproduction, the same biology this whole page is about. The drug is not metabolized by HPRT1; the concern runs the other way — mycophenolic acid blocks a separate, parallel route of purine synthesis (via IMPDH), and in someone whose HPRT1-dependent salvage pathway is already broken, that additional block can worsen the same uric acid overproduction already driving their gout, kidney stones and kidney disease. This is why the label recommends avoiding the drug in confirmed HPRT1 deficiency rather than adjusting the dose. (FDA prescribing information for mycophenolic acid delayed-release tablets (Myfortic); GeneReviews, "HPRT1 Disorders".) |
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Gout. MyGeneLog™. https://www.mygenelog.com/conditions/gout
Diet contributes and does not explain most of it. The variation in blood urate between people is dominated by how urate is transported out of the body — through the kidney and through the gut — and those transporters are inherited. High urate is also necessary but not sufficient: most people with raised urate never have an attack.
No. Neither position is used to diagnose gout, to predict an attack or to choose a treatment. Gout is diagnosed by finding urate crystals in joint fluid. If you have had an attack, that is a conversation with a doctor, and your genotype will not be part of it.
That one is real and it is a safety check rather than a result to act on alone. Carrying the allele raises the risk of a severe skin reaction to allopurinol, and prescribing guidance recommends testing beforehand where the allele is common. It is ordered by the prescriber, from a clinical laboratory — a consumer raw data file is not the right instrument for it.
Partly because the same pathways turn up. The 2013 analysis of urate loci implicated glucose metabolism as well as transport, which is one reason gout tends to arrive in company rather than on its own.
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