G-Protein–coupled Receptor Polymorphisms Are Associated with Asthma in a Large German Population
Bibliographic record
Abstract
RATIONALE: Recently, a new asthma susceptibility gene, GPRA (G-protein-related receptor for asthma), has been identified by positional cloning. Initial association studies in a Finnish and Canadian population suggested an association with asthma and elevated serum IgE levels. OBJECTIVE: In a large, nested case-control study, associations between GPRA polymorphisms, asthma, and serum IgE levels were analyzed. METHODS: Using matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) technology, 1,872 German children aged 9 to 11 years (including 624 children with asthma and/or bronchial hyperresponsiveness) were genotyped for seven polymorphisms in the GPRA gene. MEASUREMENTS: Hardy-Weinberg equilibrium was assessed, and association studies with single nucleotide polymorphisms (SNPs) and haplotypes were performed. MAIN RESULTS: SNP 546333 increased the risk for asthma (odds ratio [OR], 1.40; 95% confidence interval [CI], 1.04-1.88; p = 0.025) and concomitant asthma and bronchial hyperresponsiveness (BHR; OR, 2.38; 95% CI, 1.22-4.66; p = 0.009). Also, SNP 585883 was associated with asthma (OR, 1.34; 95% CI, 1.04-1.72; p = 0.022) and asthma in combination with BHR (OR, 2.71; 95% CI, 1.45-5.09; p = 0.001). Furthermore, SNP 585883 was associated with elevated serum IgE levels (OR, 1.63; 95% CI, 1.10-2.42; p = 0.015). Haplotype combinations of risk alleles increased the OR for asthma to 1.83 (95% CI, 1.08-3.08; p = 0.024) and for asthma and concomitant BHR to OR 3.51 (95% CI, 1.08-11.37; p = 0.036). CONCLUSIONS: These results indicate that GPRA polymorphisms increase the susceptibility for asthma and BHR, and to a lesser degree for the elevation of serum IgE, in a German population, confirming initial observations in other white populations.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".