The term “equine asthma” has been proposed as a unifying descriptor of inflammatory airway disease (IAD), recurrent airway obstruction (RAO), and summer pasture-associated obstructive airway disease. Whilst the term will increase comprehensibility for both the lay and scientific communities, its biologic relevance must be compared and contrasted to asthma in human medicine, recognizing the limited availability of peer-reviewed equine-derived data, which are largely restricted to clinical signs, measures of airway obstruction and inflammation and response to therapy. Such limitations constrain meaningful comparisons with human asthma phenotypes. Suggested minimum inclusion criteria supporting the term asthma, as well as similarities and differences between IAD, RAO, and multiple human asthma phenotypes are discussed. Furthermore, differences between phenotype and severity are described, and typical features for equine asthma subcategories are proposed. Based on shared features, we conclude that mild/moderate (IAD) and severe (RAO) equine asthma are biologically appropriate models for both allergic and non-allergic human asthma, with RAO (severe equine asthma) also being an appropriate model for late-onset asthma. With the development of new biologic treatments in humans and the application of more targeted therapeutic approaches in the horse, it would appear appropriate to further investigate the allergic (Th-2) and non-allergic (non-Th-2) phenotypes of equine asthma. Further research is required to more fully determine the potential clinical utility of phenotype classification.

The microbial composition of the equine respiratory tract, and differences due to mild equine asthma (also called Inflammatory Airway Disease (IAD)) have not been reported. The primary treatment for control of IAD in horses are corticosteroids. The objectives were to characterize the upper and lower respiratory tract microbiota associated with respiratory health and IAD, and to investigate the effects of dexamethasone on these bacterial communities using high throughput sequencing. The respiratory microbiota of horses was dominated by four major phyla, Proteobacteria (43.85%), Actinobacteria (21.63%), Firmicutes (16.82%), and Bacteroidetes (13.24%). Fifty genera had a relative abundance > 0.1%, with Sphingomonas and Pantoea being the most abundant. The upper and lower respiratory tract microbiota differed in healthy horses, with a decrease in richness in the lower airways, and 2 OTUs that differed in abundance. There was a separation between bacterial communities in the lower respiratory tract of healthy and IAD horses; 6 OTUs in the tracheal community had different abundance with disease status, with Streptococcus being increased in IAD horses. Treatment with dexamethasone had an effect on the lower respiratory tract microbiota of both heathy and IAD horses, with 8 OTUs increasing in abundance (including Streptococcus) and 1 OTU decreasing. The lower respiratory tract microbiota differed between healthy and IAD horses. Further research on the role of Streptococcus in IAD is warranted. Dexamethasone treatment affected the lower respiratory tract microbiota, which suggests that control of bacterial overgrowth in IAD horses treated with dexamethasone could be part of the treatment strategy.

Background: The stability of reference genes has a tremendous effect on the results of relative quantification of genes expression by quantitative polymerase chain reaction. Equine Inflammatory Airway Disease (IAD) is a common condition often treated with corticosteroids. The diagnosis of IAD is based on clinical signs and bronchoalveolar lavage (BAL) fluid cytology. The aim of this study was to identify reference genes with the most stable mRNA expression in the BAL cells of horses with IAD irrespective of corticosteroids treatment. Results: The expression stability of seven candidate reference genes (B2M, HPRT, GAPDH, ACTB, UBB, RPL32, SDHA) was determined by qRT-PCR in BAL samples taken pre- and post- treatment with dexamethasone and fluticasone propionate for two weeks in 7 horses with IAD. Primers' efficiencies were calculated using LinRegPCR. NormFinder, GeNorm and qBasePlus softwares were used to rank the genes according to their stability. GeNorm was also used to determine both the ideal number and the best combination of reference genes. GAPDH was found to be the most stably expressed gene with the three softwares. GeNorm ranked B2M as the least stable gene. Based on the pair-wise variation cut-off value determined with GeNorm, the number of genes required for optimal normalization was four and included GAPDH, SDHA, HPRT and RPL32. Conclusion: The geometric mean of GAPDH, HPRT, SDHA and RPL32 is recommended for accurate normalization of quantitative PCR data in BAL cells of horses with IAD treated with corticosteroids. If only one reference gene can be used, then GAPDH is recommended.

Background: Comprehensive endoscopic scoring of the upper and lower airways for inflammation has not been critically assessed among a large population of horses. The relationship between upper and lower airways described in humans by the “one airway, one disease” concept might also apply to horses. Hypothesis/Objectives: To evaluate if an association exists between endoscopic inflammatory scores and mucus scores of upper and lower airways and to investigate if endoscopic findings correlate with the lower airway inflammation measured by bronchoalveolar lavage (BAL) cytology. Methods: Prospective field study. Pharyngitis, pharyngeal mucus, tracheal mucus, tracheal septum thickness, and bronchial mucus were scored using new and previously described scoring systems on a convenience sample of 128 horses with and without lung inflammation. Based on BAL fluid cytology, horses were categorized as having normal, moderate, or severe inflammation of the lower airways. Results: All 5 endoscopy scores showed excellent interobserver agreement. Tracheal mucus (P < .001), tracheal septum thickness (P = .036), and bronchial mucus (P = .037) were significantly increased in horses with severe inflammation BALs and were correlated among themselves but not with upper airways scores. BAL neutrophils percentage was correlated with tracheal mucus (r_s = 0.41, P < .001), bronchial mucus (r_s = 0.27, P = .003), and had a weak negative correlation with pharyngitis (r_s = −0.25, P = .004). Conclusions and Clinical Importance: Lower airway endoscopy scores are reflective of lower airway inflammation; however, upper and lower airways are independent in terms of severity of inflammation. Therefore, observing upper airway inflammation is not an indication to test for lower airway inflammation.