Eosinophilic airway inflammation in patients with atopic dermatitis
Bibliographic record
Abstract
Eosinophilic airway inflammation in patients with atopic dermatitisTo the Editor,Atopic dermatitis (AD) is a chronic inflammatory skin disorder described as the first clinical manifestation of the atopic march leading to allergic asthma (AA) then allergic rhinitis (AR). AD, however, is not limited to childhood onset1, with some patients developing asthma first2. Most AD patients are reported to have airway hyperresponsiveness (AHR)3,4 airway eosinophilia5, and concurrent asthma. The Hamilton Integrated Research Ethics Board approved this study. In cohort 1 we evaluated AHR and sputum eosinophils in AD patients (6 mild, 6 moderate-severe) but with no history of asthma, to determine if undiagnosed asthma was present in this population. AD patients were characterized using skin prick test (SPT) Eczema Area and Severity Index (EADI), Asthma Control (ACQ-5) and Leicester Cough (LSQ) questionnaires, spirometry, AHR, and sputum eosinophils, and compared to mild AA (n=14) with no history of AD. Refer to supplement for eligibility and methods. Neither group had used parenteral or oral anti-inflammatory therapy for >1 month. Twenty-one of the 26 patients had a history of AR with 9/21 (43%) reporting AR first in a ‘reverse atopic march’ sequence. AD had a significantly higher EASI score and methacholine PC20, and lower ACQ-5 score compared to AA (all p<0.01) (Table 1). Despite having no history or clinical diagnosis of asthma, 3/12 (25%) AD demonstrated AHR defined by methacholine PC20 <16mg/ml, with data from all AD patients showing negative correlations between methacholine PC20 versus blood eosinophils (r = -0.81, p = <0.01), EASI score (r = -0.74, p = <0.01), and a trend versus IgE (r = -0.53, p = 0.07). When AD patients were grouped by AHR present/absent, those with AHR had significantly higher EASI score (p = 0.02) and blood eosinophils (p<0.001) (Table 1). Furthermore, when AD patients were grouped as mild (n=6) or moderate-severe (n=6) by EASI score, those with AHR were all classified as moderate-severe. The difference in AHR was not explained by allergen sensitivity because the number of positive SPT for animal, mould, house dust mite, or pollen was similar between AD subgroups when divided by AHR present/absent, or by AD severity. Nine of 12 (75%) AD patients demonstrated sputum eosinophilia, as defined by ≥3%6, with levels similar to AA. In AD there was no relationship between sputum eosinophils versus methacholine PC20 or EASI score. We measured cough by LCQ to determine if sputum eosinophils in AD could be explained by eosinophilic bronchitis, however we found no relationship between LCQ score versus sputum eosinophils or blood eosinophils, and additionally there was no relationship between LCQ versus methacholine PC20 or EASI score. To further interrogate the concept of reverse atopic march, in cohort 2 we obtained biopsies of unaffected skin from the lower back of patients with moderate to severe AD (n=17), AA with no history of AD (n=14) and healthy controls (HC, n=15) to measure histological features common to AD. Internal controls showed lesional skin of AD had greater lymphocytic infiltration, epidermal thickening (both p<0.01) and spongiosis compared to their unaffected skin (p=0.04). (Table 2). In unaffected skin, lymphocytic infiltrate was significantly higher in AD versus AA (p=0.03) and HC (p = <0.01), with no difference between any groups for spongiosis, neutrophilic infiltration, vacuole numbers, or epidermal thickening. Eosinophils in unaffected skin were too infrequent for analysis. Notably, skin from AA was histologically similar to HC. Taken together, our observations from this small study suggest that allergic disorders can occur independently or in reverse order to that described by the atopic march. Furthermore, a significant proportion of patients with AD have AHR and eosinophilic airway inflammation indicating potential development of airways inflammatory disease including asthma.References1. Burgess JA, Dharmage SC, Byrnes GB, Matheson MC, Gurrin LC, Wharton CL, et al. Childhood eczema and asthma incidence and persistence: a cohort study from childhood to middle age. J Allergy Clin Immunol . 2008;122(2):280-5.2. Barberio G, Pajno G, Vita D, Caminiti L, Canonica G, Passalacqua G. Does a ‘reverse’atopic march exist? Allergy . 2008;63(12):1630-2.3. Corbo G, Ferrante E, Macciocchi B, Foresi A, De Angelis V, Fabrizi G, et al. Bronchial hyperresponsiveness in atopic dermatitis.Allergy . 1989;44(8):595-8.4. Barker AF, Hirshman CA, D’Silva R, Hanifin JM. Airway responsiveness in atopic dermatitis. J Allergy Clin Immunol . 1991;87(4):780-3.5. Kyllönen H, Malmberg P, Remitz A, Rytilä P, Metso T, Helenius I, et al. Respiratory symptoms, bronchial hyper‐responsiveness, and eosinophilic airway inflammation in patients with moderate‐to‐severe atopic dermatitis. Clinical & Experimental Allergy . 2006;36(2):192-7.6. Belda J, Leigh R, Parameswaran K, O’Byrne PM, Sears MR, Hargreave FE. Induced sputum cell counts in healthy adults. Am J Resp Crit Care Med . 2000;161(2):475-8.Cusack RP,Whetstone CE,Alsaji N,Howie KJ,Stevens C,Wattie J,Wiltshire L,Howran J,O’Byrne PM,Sehmi R,Lima H,Gauvreau GMDepartment of Medicine, McMaster University, Hamilton, Ontario, CanadaConflict of InterestThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.No funding to report* Correspondence: Gail M GauvreauAddress: McMaster University, 1200 Main St W., HSC 3U31E, Hamilton, Ontario Canada L8N 3Z5Phone: 1-905-525-9140 ext 22791Email: gauvreau@mcmaster.caKeywords: asthma, atopic dermatitis, airway hyperresponsiveness, eosinophils, skin, inflammation
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".