Study Title:

N-acetylcysteine (NAC) ameliorates Epstein-Barr virus latent membrane protein 1 induced chronic inflammation.

Study Abstract

Chronic inflammation results when the immune system responds to trauma, injury or infection and the response is not resolved. It can lead to tissue damage and dysfunction and in some cases predispose to cancer. Some viruses (including Epstein-Barr virus (EBV)) can induce inflammation, which may persist even after the infection has been controlled or cleared. The damage caused by inflammation, can itself act to perpetuate the inflammatory response. The latent membrane protein 1 (LMP1) of EBV is a pro-inflammatory factor and in the skin of transgenic mice causes a phenotype of hyperplasia with chronic inflammation of increasing severity, which can progress to pre-malignant and malignant lesions. LMP1 signalling leads to persistent deregulated expression of multiple proteins throughout the mouse life span, including TGFα S100A9 and chitinase-like proteins. Additionally, as the inflammation increases, numerous chemokines and cytokines are produced which promulgate the inflammation. Deposition of IgM, IgG, IgA and IgE and complement activation form part of this process and through genetic deletion of CD40, we show that this contributes to the more tissue-destructive aspects of the phenotype. Treatment of the mice with N-acetylcysteine (NAC), an antioxidant which feeds into the body's natural redox regulatory system through glutathione synthesis, resulted in a significantly reduced leukocyte infiltrate in the inflamed tissue, amelioration of the pathological features and delay in the inflammatory signature measured by in vivo imaging. Reducing the degree of inflammation achieved through NAC treatment, had the knock on effect of reducing leukocyte recruitment to the inflamed site, thereby slowing the progression of the pathology. These data support the idea that NAC could be considered as a treatment to alleviate chronic inflammatory pathologies, including post-viral disease. Additionally, the model described can be used to effectively monitor and accurately measure therapies for chronic inflammation.

Study Information

PLoS One. 2017 Dec 11;12(12):e0189167. doi: 10.1371/journal.pone.0189167. eCollection 2017.

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