Biological Sex Is an Effect Modifier of Allergen-Mediated Alteration of the Lung Proteome
Bibliographic record
Abstract
Asthma exhibits a distinct sex bias in the disease prevalence, severity, and response to therapy. However, sex-related differences in alterations of the lung proteome mediated by aeroallergens critical in asthma, such as house dust mites (HDM), remain unknown. In this study, we define sex-related differences in the lung proteome using an HDM-challenged mouse model by 1D LC-MS/MS. Sex-disaggregated data analysis showed that 406 proteins were uniquely altered in females, 273 proteins were uniquely altered in males, and 414 proteins were altered in both females and males in response to HDM. In a linear mixed model analysis, sex modified the HDM exposure effect for 163 proteins, i.e., a significant sex:exposure interaction was identified in 84 proteins in females and 35 proteins in males. Of these, 12 proteins showed a significant sex effect in both female and male lungs. We further selected 3 proteins Tjp1, Lamtor1, and G3BP2 for independent confirmation studies. Our findings detail the sex-specific lung proteome in response to an aeroallergen critical in asthma and demonstrate that sex is a significant effect modifier of HDM response. These results will serve as a valuable resource for delineating sex-specific mechanisms in aeroallergen-driven responses in asthma research.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".