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Inhalation Toxicology
International Forum for Respiratory Research
Volume 32, 2020 - Issue 13-14
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Research Articles

Effect of E-Cigarette aerosol exposure on airway inflammation in a murine model of asthma

, , ORCID Icon & ORCID Icon
Pages 503-511 | Received 22 Sep 2020, Accepted 20 Nov 2020, Published online: 09 Dec 2020
 

Abstract

Objective

The popularity of electronic cigarettes (E-Cigs) smoking is increasing worldwide including patients with asthma. In this study, the effects of E-Cigs aerosol exposure on airway inflammation in an allergen-driven murine model of asthma were investigated.

Materials and methods

Balb/c mice were randomly assigned to; control group (received fresh air, Ovalbumin (Ova) sensitization and saline challenge), E-Cig group (received E-Cig aerosol, Ova sensitization, and saline challenge), Ova S/C group (received fresh air, Ova sensitization and Ova challenge) and E-Cig + Ova S/C group. Bronchoalveolar lavage fluid (BALF) and lung tissue were evaluated for inflammatory cells and inflammatory mediators, respectively.

Results

Exposure to E-Cig aerosol significantly increased the number of all types of inflammatory cells in BALF (p < 0.05). Further, E-Cig aerosol reduced levels of transforming growth factor (TGF)-β1 and matrix metalloproteinase (MMP)-2 in lung tissue homogenate (p < 0.05). Combined E-Cig aerosol and Ova S/C increased the airway recruitment of inflammatory cells, especially neutrophils, eosinophils, and lymphocytes (p < 0.05), increased the level of interleukin (IL)-13, and reduced the level of TGF-β1 (p < 0.05).

Conclusions

E-Cig aerosol exposure induced airway inflammation in both control mice and allergen-driven murine model of asthma. The inflammatory response induced by E-Cig was slightly higher in allergen-driven murine model of asthma than in healthy animals.

Acknowledgments

The authors thank Laila Abu Hawieleh, MSc and We’am Yacoub, BSc for their technical assistance.

Disclosure statement

The authors report no conflict of interest.

Additional information

Funding

This work was supported by the Deanship of Research at Jordan University of Science and Technology [grant number 333/2019].

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