Association of CD4 Enhancer Gene Polymorphisms with Rheumatoid Arthritis and Systemic Lupus Erythematosus in Taiwan
Bibliographic record
Abstract
UNLABELLED: It has been found that changes in CD4 expression and CD4+ T cell activity may influence tolerance or tissue destruction in autoimmune diseases and contribute to their risk. We examined whether an association of CD4 enhancer gene polymorphisms with rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) exists. METHODS: For study of the CD4 -11743A/C polymorphism, 192 patients with RA, 141 patients with SLE, and 96 normal controls participated. For the CD4 -10845A/G polymorphism, 191 patients with RA, 127 patients with SLE, and 92 controls participated. The polymorphism of the CD4 enhancer was examined with the polymerase chain reaction-restriction fragment length polymorphism method. Genotypic and allelic frequencies of the 3 groups of participants were compared. Genotype groups were also compared according to different clinical variables among the patients with RA and SLE. RESULTS: For the CD4 -11743A/C polymorphism, patients with RA demonstrated significantly higher frequency of the C allele (p = 0.048); patients with SLE had significantly higher frequency of the CC genotype (p = 0.026), and lower frequency of the AC genotype (p = 0.013) compared with controls. For the CD4 -10845A/G polymorphism, patients with RA had significantly higher frequencies of the AA genotype (p = 0.047) and the A allele (p = 0.026); patients with SLE had significantly higher frequency of the AA genotype (p = 0.011) and A allele (p = 0.001), and lower frequency of the GG genotype (p = 0.003) compared with controls. A comparison of genotype groups according to different clinical variables revealed the association of the respective polymorphisms with mucosal ulcer lesions among patients with SLE. CONCLUSION: . Our results suggest that the genetic polymorphisms at the CD4 enhancer gene are associated with the risk of development of RA and SLE. They are also associated with mucosal ulcer lesions in patients with SLE.
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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 | 0.000 | 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) | 0.003 | 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".