Airway Hyperresponsiveness, but Not Bronchoalveolar Inflammatory Cytokines Profiles, Is Modified at the Subclinical Onset of Severe Equine Asthma.
Thibault FrippiatTatiana ArtIrene TosiPublished in: Animals : an open access journal from MDPI (2023)
Airway hyperresponsiveness (AHR) and inflammation are both observed in human and equine asthma. The aim of this study was to assess the timeline and relationship of both features at the subclinical onset of severe equine asthma (SEA). First, the repeatability of the pulmonary function test (PFT) using impulse oscillometry system, and the methacholine bronchoprovocation test (BPT) were assessed at a 1-day interval on six SEA horses in clinical remission and six control horses. Then, clinical and ancillary tests were performed before and after a 1-week low-dust environmental challenge, including weighted clinical score, respiratory endoscopy, bronchoalveolar fluid cytology, PFT, and BPT. Both PFT and BPT showed acceptable repeatability. No test allowed SEA horses in clinical remission to be distinguished from control, unlike in human patients. Because of the low-dust environment, no significant difference was observed in the results of clinical and conventional ancillary examinations after the challenge. However, SEA horses showed increased AHR after the environmental challenge. At that stage, no signs of inflammation or changes in pro-inflammatory cytokines profiles (quantification and gene expression) were observed, suggesting AHR is present at an earlier stage of equine asthma than airway inflammation. This feature indicates SEA could present in a different disease pathway than neutrophilic human asthma.
Keyphrases
- chronic obstructive pulmonary disease
- gene expression
- endothelial cells
- lung function
- oxidative stress
- allergic rhinitis
- magnetic resonance imaging
- randomized controlled trial
- clinical trial
- magnetic resonance
- machine learning
- systemic lupus erythematosus
- induced pluripotent stem cells
- cystic fibrosis
- disease activity
- climate change
- air pollution
- deep learning
- drinking water
- polycyclic aromatic hydrocarbons
- ultrasound guided
- fine needle aspiration