Abstract 1231: Using oral and lung microbiome to assess microbial dysbiosis and inflammatory response to electronic cigarettes and to cigarettes

Abstract

Abstract Background: Alteration of the oral microbiome (microbial dysbiosis) with cigarette smoking is well established. However, the effect of electronic cigarettes (e-cigs) use on the oral microbiome is unknown, although there are emerging data that e-cigs induce microbial changes similar to smoking. In smoking-related diseases, such as chronic obstructive pulmonary disease, there are changes in the oral microbiome and in the expression of genes involved in inflammatory pathways. Similar to the oral microbiome, it is feasible that smoking tobacco and e-cig use could also affect the lung microbiome. To the best of our knowledge, there is only one published study investigating smoking tobacco effects on the oral and lung microbiome. No published studies have evaluated concurrent effects of e-cigs in the oral and lung microbiome. Aims: We hypothesize that microbial dysbiosis and expression of inflammatory cytokines in the oral cavity and lung will differ between smokers and nonsmokers, and that e-cig users will have microbial dysbiosis more similar to smokers. To accomplish this, we propose 1) to examine the association of oral and lung microbiome in nonsmokers, smokers and e-cig users, 2) to determine if the oral microbiome and the lung microbiome differ among these groups, and 3) to determine correlation of the microbiota with host expression of inflammation-related genes. Methods: A cross-sectional study using bronchoscopy and oral rinse collection of 10 never-smokers, 8 cigarette smokers, and 10 e-cig users was conducted. For each study participant, RNA was extracted from saliva and bronchoalveolar lavage (BAL) samples for total transcriptome analysis using RNA-seq; facilitating this approach allows measurement of bacterial communities and human inflammatory cytokine expression in the same assay. To determine microbial dysbiosis by smoking status, the Mann Whitney U-test and Kruskal-Wallis H-test were used with Bonferroni correction for multiple comparisons. Both effect size (fold change >1.5) and adjusted p-value cutoffs (<0.05) were used to identify statistical significance. Results: In preliminary analyses we identified 2,257 bacterial strains in saliva samples and 1592 in BAL samples. We found a lack of concordance of highly abundant bacteria in the oral cavity and lungs. The top twenty expressed human genes were associated with RNA splicing, RNA elongation and miRNAs. Comparisons of microbial dysbiosis by smoking status are currently under way. Conclusion: The composition of the microbiome for saliva is different from that of BAL. Comparison of the metatranscriptome and transcriptome between the lung and oral cavity, as well as between smokers, nonsmokers and e-cigarette users, will allow us to observe how e-cig use compares with cigarette smoking and never smoking in terms of microbial dysbiosis and inflammatory cytokines. Citation Format: Kevin L. Ying, Min-Ae Song, Daniel Y. Weng, Quentin A. Nickerson, Joseph P. McElroy, David Frankhouser, Pearlly S. Yan, Ralf Bundschuh, Theodore M. Brasky, Mark D. Wewers, Ewy Mathé, Jo L. Freudenheim, Peter G. Shields. Using oral and lung microbiome to assess microbial dysbiosis and inflammatory response to electronic cigarettes and to cigarettes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1231.