ReviewVeterinary research communications2026
Biomarkers of equine asthma: A review of the current literature.
Review in Veterinary research communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
5 authors.
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Abstract
Equine Asthma (EA) is a common, lower airway disease. Yet current diagnostic standards rely on bronchoalveolar lavage fluid (BALF) cytology, which is moderately invasive and not always feasible in field conditions. This review aimed to synthesize current evidence on candidate biomarkers of EA, with a primary focus on blood-based matrices and BALF, while also including data on biomarkers measured in tracheal wash (TW), saliva and exhaled breath condensate (EBC), where available. Searches were performed in PubMed, Scopus and Google Scholar, and original studies in horses with mild-to-moderate or severe EA reporting potential biomarkers were included. Across 57 unique studies, a broad spectrum of candidate biomarkers was evaluated. Blood-derived biomarkers, including surfactant protein D (SP-D), secretoglobin (SCGB), haptoglobin showed variable but generally limited specificity when assessed individually, although several combinations improved diagnostic accuracy. BALF-derived biomarkers more consistently reflected local airway inflammation and disease severity. Among these, neutrophil extracellular traps (NETs) related markers, neutrophil gelatinase-associated lipocalin (NGAL) and allergen-specific IgE profiles emerged as the most promising candidates, particularly in multimarker panels and phenotype-stratified analyses. Overall, current evidence supports the potential of integrated biomarker panels, especially those derived from BALF and complemented by blood-based markers, to refine the diagnosis and monitoring of EA, but robust validation in large, well-characterised study group is still required before routine clinical implementation.
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