Rhinovirus Species–Specific Antibodies Differentially Reflect Clinical Outcomes in Health and Asthma
Bibliographic record
Abstract
Abstract Rationale Rhinoviruses (RVs) are major triggers of common cold and acute asthma exacerbations. RV species A, B, and C may have distinct clinical impact; however, little is known regarding RV species–specific antibody responses in health and asthma. Objectives To describe and compare total and RV species–specific antibody levels in healthy children and children with asthma, away from an acute event. Methods Serum samples from 163 preschool children with mild to moderate asthma and 72 healthy control subjects from the multinational Predicta cohort were analyzed using the recently developed PreDicta RV antibody chip. Measurements and Main Results RV antibody levels varied, with RV-C and RV-A being higher than RV-B in both groups. Compared with control subjects, asthma was characterized by significantly higher levels of antibodies to RV-A and RV-C, but not RV-B. RV antibody levels positively correlated with the number of common colds over the previous year in healthy children, and wheeze episodes in children with asthma. Antibody levels also positively correlated with asthma severity but not with current asthma control. Conclusions The variable humoral response to RV species in both groups suggests a differential infectivity pattern between RV species. In healthy preschoolers, RV antibodies accumulate with colds. In asthma, RV-A and RV-C antibodies are much higher and further increase with disease severity and wheeze episodes. Higher antibody levels in asthma may be caused by a compromised innate immune response, leading to increased exposure of the adaptive immune response to the virus. Importantly, there is no apparent protection with increasing levels of antibodies.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".