Associations Between Three <i>CTLA-4</i> Polymorphisms and Hashimoto's Thyroiditis Risk: An Updated Meta-Analysis with Trial Sequential Analysis
Bibliographic record
Abstract
AIMS: In this article, we conducted an updated meta-analysis with trial sequential analysis (TSA) to refine the associations between three common single nucleotide polymorphisms (SNPs) in the CTLA-4 gene (+49A/G, CT60, and -318C/T) and Hashimoto's thyroiditis (HT). METHODS: Statistical association analyses were performed using four genetic models, including the allelic, codominant, dominant, and recessive models with the Revman 5.3, Stata 14.0, and TSA 0.9 software. For quality evaluation, the Newcastle-Ottawa Scale was used. RESULTS: Our meta-analysis included 29 independent studies with low risk of bias that involved 3614 cases and 8839 controls. The pooled results indicated a significant association between the +49A/G polymorphism and an increased risk of HT in all four genetic models. Furthermore, the TSA demonstrated that the evidence of this association was robust and credible. Subgroup analysis revealed a significantly higher risk of HT in Asians compared with Caucasians associated with the +49A/G polymorphism. Surprisingly, in contrast to the results with adults, we did not find any significant association when analyzing the pediatric subgroup. For the CT60 polymorphism, a significant association with risk of HT was detected overall, and subgroup analysis revealed that this association was significant in the Asian subgroup, but not in the Caucasian subgroup. No statistically significant associations were detected in any of the investigated genetic models for the -318C/T polymorphism. However, the results of the TSA suggested that the sample sizes used for the CTLA-4 CT60 and -318C/T SNPs were insufficient. CONCLUSION: Our meta-analysis showed significant associations between the risk of HT and both the +49A/G and CT60 polymorphisms, but not the -318C/T polymorphism. In addition, the TSA results indicated that CTLA-4 +49A/G should be considered as a biomarker for HT, whereas both the CT60 and -318C/T SNPs warrant confirmation by further studies.
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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 | 0.017 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.044 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".