Identification of <i>OCA2</i> as a novel locus for the co‐morbidity of asthma‐plus‐eczema
Bibliographic record
Abstract
BACKGROUND: Numerous genes have been associated with the three most common allergic diseases (asthma, allergic rhinitis or eczema) but these genes explain only a part of the heritability. In the vast majority of genetic studies, complex phenotypes such as co-morbidity of two of these diseases, have not been considered. This may partly explain missing heritability. OBJECTIVE: To identify genetic variants specifically associated with the co-morbidity of asthma-plus-eczema. METHODS: We first conducted a meta-analysis of four GWAS (Genome-Wide Association Study) of the combined asthma-plus-eczema phenotype (total of 8807 European-ancestry subjects of whom 1208 subjects had both asthma and eczema). To assess whether the association with SNP(s) was specific to the co-morbidity, we also conducted a meta-analysis of homogeneity test of association according to disease status ("asthma-plus-eczema" vs. the presence of only one disease "asthma only or eczema only"). We then used a joint test by combining the two test statistics from the co-morbidity-SNP association and the phenotypic heterogeneity of SNP effect meta-analyses. RESULTS: Seven SNPs were detected for specific association to the asthma-plus-eczema co-morbidity, two with significant and five with suggestive evidence using the joint test after correction for multiple testing. The two significant SNPs are located in the OCA2 gene (Oculocutaneous Albinism II), a new locus never detected for significant evidence of association with any allergic disease. This gene is a promising candidate gene, because of its link to skin and lung diseases, and to epithelial barrier and immune mechanisms. CONCLUSION: Our study underlines the importance of studying sub-phenotypes as co-morbidities to detect new susceptibility genes.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".