Microarray molecular mapping of horses with severe asthma

Autor: Samuel J. White, Laurent Couetil, Eric A. Richard, Eliane Marti, Philippe B. Wilson
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Journal of Veterinary Internal Medicine, Vol 38, Iss 1, Pp 477-484 (2024)
Druh dokumentu: article
ISSN: 1939-1676
0891-6640
DOI: 10.1111/jvim.16951
Popis: Abstract Background Severe asthma (SA) in horses, resembling human asthma, is a prevalent, debilitating allergic respiratory condition marked by elevated allergen‐specific immunoglobulin E (IgE) against environmental proteins; however, research exploring the exposome's influence on IgE profiles is currently limited but holds paramount significance for diagnostic and therapeutic developments. Animals Thirty‐five sports horses were analyzed, consisting of environmentally matched samples from France (5 SA; 6 control), the United States (6 SA; 6 control), and Canada (6 SEA; 6 control). Methods This intentional cross‐sectional study investigated the sensitization profiles of SA‐affected and healthy horses via serological antigen microarray profiling. Partial least square‐discriminant analysis (PLS‐DA) was used to identify and rank the importance of allergens for class separation (ie, affected/non‐affected) as variable influence of projection (VIP), and allergen with commonality internationally established via frequency analysis. Results PLS‐DA models showed high discriminatory power in predicting SA in horses from Canada (area under the curve [AUC] 0.995) and France (AUC 0.867) but poor discriminatory power in horses from the United States (AUC 0.38). Hev b 5.0101, Cyn D, Der p 2, and Rum cr were the only shared allergens across all geographical groups. Conclusions and Clinical Importance Microarray profiling can identify specific allergenic components associated with SA in horses, while mathematical modeling of this data can be used for disease classification, highlighting the variability of sensitization profiles between geographical locations and emphasizing the importance of local exposure to the prevalence of different allergens. Frequency scoring analysis can identify important variables that contribute to the classification of SA across different geographical regions.
Databáze: Directory of Open Access Journals
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