Genome-Wide Association Study Identifies Novel Loci Associated With Diisocyanate-Induced Occupational Asthma
Bibliographic record
Abstract
Diisocyanates, reactive chemicals used to produce polyurethane products, are the most common causes of occupational asthma. The aim of this study is to identify susceptibility gene variants that could contribute to the pathogenesis of diisocyanate asthma (DA) using a Genome-Wide Association Study (GWAS) approach. Genome-wide single nucleotide polymorphism (SNP) genotyping was performed in 74 diisocyanate-exposed workers with DA and 824 healthy controls using Omni-2.5 and Omni-5 SNP microarrays. We identified 11 SNPs that exceeded genome-wide significance; the strongest association was for the rs12913832 SNP located on chromosome 15, which has been mapped to the HERC2 gene (p = 6.94 × 10(-14)). Strong associations were also found for SNPs near the ODZ3 and CDH17 genes on chromosomes 4 and 8 (rs908084, p = 8.59 × 10(-9) and rs2514805, p = 1.22 × 10(-8), respectively). We also prioritized 38 SNPs with suggestive genome-wide significance (p < 1 × 10(-6)). Among them, 17 SNPs map to the PITPNC1, ACMSD, ZBTB16, ODZ3, and CDH17 gene loci. Functional genomics data indicate that 2 of the suggestive SNPs (rs2446823 and rs2446824) are located within putative binding sites for the CCAAT/Enhancer Binding Protein (CEBP) and Hepatocyte Nuclear Factor 4, Alpha transcription factors (TFs), respectively. This study identified SNPs mapping to the HERC2, CDH17, and ODZ3 genes as potential susceptibility loci for DA. Pathway analysis indicated that these genes are associated with antigen processing and presentation, and other immune pathways. Overlap of 2 suggestive SNPs with likely TF binding sites suggests possible roles in disruption of gene regulation. These results provide new insights into the genetic architecture of DA and serve as a basis for future functional and mechanistic 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".