Mouse models of anti-neutrophil cytoplasmic antibody-associated vasculitis.

Curr Pharm Des

Centre for Inflammatory Diseases, Monash University, Department of Medicine, Monash Medical Centre, 246 Clayton Road, Clayton, VIC 3168, Australia.

Published: May 2016

Inflammation of blood vessels (vasculitis) results from many pathological processes and is found in many different diseases. However, in most situations, the pathological processes inducing vasculitis are unknown. The discovery of anti-neutrophil cytoplasmic autoantibodies (ANCAs) in the 1980s opened the door for studies that eventually led to the description of a new previously undescribed disease, ANCA-associated vasculitis (AAV). Unravelling the immunopathogenesis of this new disease resulted largely from the development of animal models. The major breakthroughs were the description of ANCA, its association with small vessel vasculitis and the discovery of its target autoantigens (myeloperoxidase and Proteinase 3). Three major disease syndromes comprise the AAVs, microscopic polyangiitis, granulomatosis with polyangiitis and eosinophilic granulomatosis with polyangiitis (EGPA). Recent human studies suggest that proteinase 3 and myeloperoxidase associated vasculitis are two separate but related diseases. The ability to induce murine autoimmunity to myeloperoxidase including ANCA (with the same immune staining patterns as human ANCA) and the capacity of this anti-myeloperoxidase autoimmunity to induce disease with many of the characteristic features of human AAV are well developed. However, the development of animal models of anti-proteinase 3 ANCA and EGPA is much less well developed. Animal models are important in understanding the human disease and in particular in defining potential therapeutic targets and in early stage therapeutic testing of potential drugs. Clearly the relevance of animal models depends on how closely they mimic human diseases. The current status of animal models of vasculitis will be described in detail with reference to these criteria.

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http://dx.doi.org/10.2174/1381612821666150316121029DOI Listing

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