Association of Urokinase-type Plasminogen Activator with Asthma and Atopy
Bibliographic record
Abstract
RATIONALE: Urokinase plasminogen activator (uPA) interacts with its receptor on inflammatory and migrating cells to regulate extracellular matrix degradation, cell adhesion, and inflammatory cell activation. It is necessary for the development of an appropriate immune response and is involved in tissue remodeling. The PLAU gene codes for this enzyme, and is located on 10q24. This region has demonstrated evidence for linkage in a genome scan for asthma in a sample from northeastern Quebec. Here, we hypothesized that uPA may function as a regulator of asthma susceptibility. OBJECTIVES: To test for association between asthma and genetic variants of PLAU. METHODS: We sequenced PLAU and tested for genetic association between identified variants and asthma-related traits in a French-Canadian familial collection (231 families, 1,139 subjects). Additional association studies were performed in two other family-based Canadian cohorts (Canadian Asthma Primary Prevention Study [CAPPS], 238 trios; and Study of Asthma Genes and the Environment [SAGE], 237 trios). MEASUREMENTS AND MAIN RESULTS: In the original sample, under the dominant model, the common alleles, rs2227564C (P141) and rs2227566T, were associated with asthma (p = 0.011 and 0.045, respectively) and with airway hyperresponsiveness (AHR) (p = 0.026 and 0.038, respectively). Analysis of the linkage disequilibrium pattern also revealed association of the common haplotype for asthma, atopy, and AHR (p = 0.031, 0.043, and 0.006, respectively). Whereas no significant association was detected for PLAU single-nucleotide polymorphisms in the CAPPS cohort, association was observed in the SAGE cohort between the rs4065C allele and atopy under additive (p = 0.005) and dominant (p = 0.0001) genetic models. CONCLUSIONS: This suggests a role for the uPA pathway in the pathogenesis of the disease.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".