Tubular Urate Transporter Gene Polymorphisms Differentiate Patients with Gout Who Have Normal and Decreased Urinary Uric Acid Excretion
Bibliographic record
Abstract
OBJECTIVE: Primary gout has been associated with single-nucleotide polymorphisms (SNP) in several tubular urate transporter genes. No study has assessed the association of reabsorption and secretion urate transporter gene SNP with gout in a single cohort of documented primary patients with gout carefully subclassified as normoexcretors or underexcretors. METHODS: Three reabsorption SNP (SLC22A12/URAT1, SLC2A9/GLUT9, and SLC22A11/OAT4) and 2 secretion transporter SNP (SLC17A1/NPT1 and ABCG2/BRCP) were studied in 104 patients with primary gout and in 300 control subjects. The patients were subclassified into normoexcretors and underexcretors according to their serum and 24-h urinary uric acid levels under strict conditions of dietary control. RESULTS: Compared with control subjects, patients with gout showed different allele distributions of the 5 SNP analyzed. However, the diagnosis of underexcretor was only positively associated with the presence of the T allele of URAT1 rs11231825, the G allele of GLUT9 rs16890979, and the A allele of ABCG2 rs2231142. The association of the A allele of ABCG2 rs2231142 in normoexcretors was 10 times higher than in underexcretors. The C allele of NPT1 rs1165196 was only significantly associated with gout in patients with normal uric acid excretion. CONCLUSION: Gout with uric acid underexcretion is associated with transporter gene SNP related mainly to tubular reabsorption, whereas uric acid normoexcretion is associated only with tubular secretion SNP. This finding supports the concept of distinctive mechanisms to account for hyperuricemia in patients with gout with reduced or normal uric acid excretion.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".