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Rare Models: Use of a Novel Translational Model for Diffuse Alveolar Haemorrhage
Journal article   Open access   Peer reviewed

Rare Models: Use of a Novel Translational Model for Diffuse Alveolar Haemorrhage

Karan R. Chadda, Savithri Sathivelu, Susan K. Armstrong, Charlotte Edling and Kamalan Jeevaratnam
International journal of molecular sciences, Vol.27(10), p.4157
07/05/2026
PMID: 42196142

Abstract

diffuse alveolar haemorrhage pulmonary arterial hypertension exercise-induced pulmonary haemorrhage translational model equine
Diffuse alveolar haemorrhage (DAH) is rare but associated with high morbidity and mortality. It is underpinned by mechanisms of endothelial dysfunction, inflammation, and vascular remodelling, yet its pathogenesis remains incompletely understood. Progress in translational research is currently limited by the absence of robust animal models of this condition. Equine exercise-induced pulmonary haemorrhage (EIPH), a common and progressive disorder in racehorses, may represent a novel and underutilised translational model for studying DAH, which can be a complication of or associated with other cardiopulmonary conditions, such as pulmonary arterial hypertension (PAH). EIPH occurs spontaneously in up to 95% of thoroughbreds after repeated strenuous exercise and is characterised by haemorrhage into the alveoli, capillary stress failure, inflammatory infiltration, and subsequent parenchymal remodelling. These processes closely parallel the vascular injury and immune activation observed in DAH. Horses further offer distinct advantages as models for human respiratory disease, including large lung size, long lifespan, and comparable pulmonary architecture. The regional distribution of haemorrhage in equine lungs additionally enables within-animal control studies. By leveraging the mechanistic overlaps between equine and human pulmonary pathology, EIPH provides a unique opportunity for biomarker discovery, mechanistic insight, and therapeutic testing in pulmonary vascular disease.
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https://doi.org/10.3390/ijms27104157View
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