No Evidence of Causal Association between Atopic Dermatitis and Primary Open-Angle Glaucoma: A Bidirectional Two-Sample Mendelian Randomization Study
Bibliographic record
Abstract
Abstract: Background: Atopic dermatitis (AD) can present with open-angle glaucoma, but powerful evidence to support their causal relationship is absent. Objective: To investigate the causal association of AD with primary open-angle glaucoma (POAG). Methods: A bidirectional 2-sample Mendelian randomization (MR) study was performed with the software R. Results: Eighteen single nucleotide polymorphisms (SNPs) were used in the forward MR analysis with AD as exposure. The inverse-variance weighted (IVW) method produced a result that genetically predicted AD was not associated with POAG (odds ratio [OR] = 1.10, 95% confidence interval [CI]: 0.95–1.27, P = 0.215). Fifty-one SNPs were used in the reverse MR analysis with POAG as exposure. The IVW method yielded a result that genetically predicted POAG was not correlated with AD (OR = 0.98, 95% CI: 0.95–1.01, P = 0.191). The bidirectional causal effect estimates were consistent with supplementary MR methods (MR-Egger, weighted median, simple mode, and weighted mode). The sensitivity analysis showed stable results. Conclusions: This bidirectional 2-sample MR study did not give evidence of causal association between AD and POAG.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.037 | 0.077 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".