Association of genetic variations in <i>FoxP3</i> gene with Graves' disease in a Southwest Chinese Han population
Bibliographic record
Abstract
Abstract Background Graves' disease (GD) is a T cell‐mediated organ‐specific autoimmune disease. Forkhead box P3 (FoxP3) is an excellent marker for the induction and development of regulatory T cells (Tregs). Recent studies showed that single‐nucleotide polymorphisms (SNPs) in the FoxP3 gene were associated with the increased susceptibility to several autoimmune diseases. In the present study, we investigated the association of FoxP3 gene polymorphisms with GD in a Southwest Chinese Han population. Methods A two‐stage case‐control study was performed in 890 healthy controls (male, 282; female, 608) and 503 patients with GD (male, 138; female, 365). Four SNPs (rs3761548, rs3761549, rs3761547, and rs2280883) were genotyped by the polymerase chain reaction‐restriction fragment length polymorphism assay. The χ2 test was used to compare the genotype distributions and allele frequencies between GD patients and healthy controls. Results In the first stage, the significantly increased frequencies of the A allele (p = .031, odds ratio [OR] = 1.635) and AA genotype (p = .023, OR = 3.257), together with a significantly decreased frequency of the C allele (p = .031, OR = 0.611) of FoxP3/rs3761548 were found in female patients with GD. None of the other FoxP3 SNPs was associated with GD susceptibility. Subsequent validation and combination of data confirmed the association between FoxP3/rs3761548 and the female patients with GD (A allele: p < .001, OR = 1.672; AA genotype: p = .005, OR = 2.488; CC genotype: p = .001, OR = 0.622; C allele: p < .001, OR = 0.615, respectively). Conclusion Our findings suggest that FoxP3/rs3761548 is significantly associated with female GD patients in a Southwest Chinese Han population.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".