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Record W4283771466 · doi:10.1183/13993003.00442-2022

Airway autoantibodies are determinants of asthma severity

2022· article· en· W4283771466 on OpenAlexafffund
Brittany Salter, Nan Zhao, Kiho Son, Nadia Suray Tan, Anna Dvorkin‐Gheva, Katherine Radford, Nicola LaVigne, Chynna Huang, Melanie Kjarsgaard, Quan‐Zhen Li, Konstantinos Tselios, Hui Fang Lim, Nader Khalidi, Parameswaran Nair, Manali Mukherjee

Bibliographic record

VenueEuropean Respiratory Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsMcMaster University Medical CentreMcGill UniversityJewish General HospitalMcMaster UniversitySt. Joseph’s Healthcare Hamilton
FundersInstitute of Circulatory and Respiratory HealthCanadian Institutes of Health Research
KeywordsMedicineAsthmaAutoantibodyAirwayImmunologyIntensive care medicineAntibodySurgery

Abstract

fetched live from OpenAlex

Background Local airway autoimmune responses may contribute to steroid dependence and persistent eosinophilia in severe asthma. Auto-IgG antibodies directed against granule proteins such as eosinophil peroxidase (EPX), macrophage scavenger receptor with collagenous structure (MARCO) and nuclear/extranuclear antigens (antinuclear antibodies (ANAs)) have been reported. Our objective was to describe the prevalence and clinical characteristics of asthmatic patients with airway autoreactivity, and to assess if this could be predicted from clinical history of autoreactivity. Methods We analysed anti-EPX, anti-MARCO and ANAs in 218 sputum samples collected prospectively from 148 asthmatic patients, and evaluated their association with lung function parameters, blood/airway inflammation, severity indices and exacerbations. Additionally, 107 of these patients consented to fill out an autoimmune checklist to determine personal/family history of systemic autoimmune disease and symptoms. Results Out of the 148 patients, 59 (40%) were anti-EPX IgG+, 53 (36%) were anti-MARCO IgG+and 64 out of 129 (50%) had ≥2 nuclear/extranuclear autoreactivities. A composite airway autoreactivity score (CAAS) demonstrated that 82 patients (55%) had ≥2 airway autoreactivities (considered as CAAS+). Increased airway eosinophil degranulation (OR 15.1, 95% CI 1.1–199.4), increased blood leukocytes (OR 3.5, 95% CI 1.3–10.1) and reduced blood lymphocytes (OR 0.19, 95% CI 0.04–0.84) predicted CAAS+. A third of CAAS+patients reported an exacerbation, associated with increased anti-EPX and/or anti-MARCO IgG (p<0.05). While no association was found between family history or personal diagnosis of autoimmune disease, 30% of CAAS+asthmatic patients reported sicca symptoms (p=0.02). Current anti-inflammatory (inhaled/oral corticosteroids and/or adjunct anti-interleukin-5 biologics) treatment does not attenuate airway autoantibodies, irrespective of eosinophil suppression. Conclusion We report 55% of moderate–severe asthmatic patients to have airway autoreactivity that persists despite anti-inflammatory treatment and is associated with exacerbations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.024
GPT teacher head0.281
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations28
Published2022
Admission routes2
Has abstractyes

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