rs10865331 in 2p15 increases susceptibility to ankylosing spondylitis: a HuGE review and meta-analysis.
Bibliographic record
Abstract
OBJECTIVES: 2p15 polymorphisms have been reported to increase ankylosing spondylitis (AS) susceptibility in several studies; however, when it comes to whether and how much of this risk exists, the results are inconclusive. The aim of this study is to investigate the correlation between rs10865331 in 2p15 and the risk of AS. METHODS: We conducted a HuGE review and meta-analysis of studies published through September 2019. Studies were identified in PubMed, Scopus, HuGE Navigator, Embase, and Web of Science databases. Odds ratios (ORs) and 95% confidence intervals (CIs) for risk estimations were calculated. Sensitivity analysis, subgroup analysis and analysis for potential publication bias were also estimated. RESULTS: Eleven studies with 18555 AS patients and 43777 unrelated healthy individuals, each with a score greater than 6 on the Newcastle-Ottawa Scale (NOS), that investigated the association between rs10865331 in 2p15 and AS were included in our meta-analysis. Data were classified into the genotype analysis cohort, the OR-value cohort, and the pooled analysis cohort, and then a meta-analysis was performed. The OR value of the recessive model in the genotype analysis cohort was 1.376 (95% CI=1.204-1.572, p<0.001, I²=56.30%), and the OR value of the pooled analysis cohort was 1.295 (95% CI=1.228-1.365, p<0.001, I²=73.70%). These findings suggest that individual who carries this single nucleotide polymorphism (SNP) are about 30% more susceptible to developing AS. CONCLUSIONS: Our results suggest that rs10865331 is associated with a significantly higher risk of AS in all race and country subgroups that we have evaluated. Therefore, rs10865331 may be a useful genetic marker for predicting AS susceptibility. However, further studies are needed to confirm our findings.
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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 | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.032 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".