Association of Four Genetic Loci with Uric Acid Levels and Reduced Renal Function: The J-SHIPP Suita Study
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Recent genome-wide association studies have identified several genetic variants as susceptibility loci for serum uric acid (UA) levels. We also identified a common nonsense mutation, W258X, responsible for renal hypouricemia. Here, we investigated clinical implications of these genetic variants by cross-sectional and longitudinal genetic epidemiological analysis. METHODS: The study enrolled 5,165 Japanese subjects aged 64 ± 12 years from the general population. Clinical parameters were obtained from the personal health records, evaluated at medical checkups. RESULTS: Serum UA levels were significantly different between the SLC22A12 rs11231825 (CC/CT/TT: 4.5 ± 1.6, 5.0 ± 1.4, 5.3 ± 1.4 mg/dl; p = 7.6 × 10(-20)), SLC2A9 rs1014290 (TT/TG/GG: 4.9 ± 1.4, 5.1 ± 1.4, 5.3 ± 1.4 mg/dl; p = 3.1 × 10(-11)) and ABCG2 rs2231142 (TT/TG/GG: 5.3 ± 1.5, 5.2 ± 1.4, 5.1 ± 1.4 mg/dl; p = 2.0 × 10(-5)) genotypes. During 9.4 years of follow-up, 87 new cases of hyperuricemia were diagnosed. Multiple logistic regression analysis identified the accumulation of risk alleles as a significant determinant of future development of hyperuricemia (OR = 7.94; 95% CI: 1.97-53.6). In contrast, subjects with nonsense mutation predominantly showed lower UA levels (XX/XW/WW: 1.3 ± 1.7, 3.6 ± 1.0, 5.2 ± 1.4 mg/dl; p = 9.3 × 10(-82)). However, these subjects showed significantly reduced renal function (β = -0.111; p < 0.001) independently of possible covariates. CONCLUSION: Accumulation of risk genotypes was an independent risk factor for future development of hyperuricemia. Genetically developed hypouricemia was an independent risk factor for decreased renal function.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it