Abstract 664: Microbial and inflammatory response to electronic cigarette and cigarette use
Authors: Kevin L. Ying, Min-Ae Song, Daniel Y. Weng, Quentin A. Nickerson, Joseph P. McElroy, Theodore M. Brasky, Mark D. Wewers, Ewy Mathé, Jo L. Freudenheim, Peter G. Shields
Journal: Cancer Research (2019)

Abstract Background: As electronic cigarette (e-cig) use increases in the US, investigation of their effects are critical. Alteration of the lung microbiome, oral microbiome, and inflammation are well established effects of cigarettes; however the effects of e-cigs are yet unknown. Individuals with smoking-related lung disease have alterations in their lung microbiome compared to healthy individuals and their lung microbiomes appear more similar to their oral microbiomes when compared to healthy individuals. To our knowledge, only one study has examined smoking tobacco’s concurrent effects in the oral and lung microbiome and none have examined e-cig use. Further, none have studied e-cigs’ effect on the lung microbiome and inflammation. We hypothesized that e-cig use would affect the lung microbiome, and that the effects are different from smokers and never-smokers; alteration of the lung microbiome will also affect inflammatory gene expression in the lungs. Methods: A cross-sectional study of bronchoscopy with bronchoalveolar lavage (BAL) of 10 never-smokers, 8 cigarette smokers, and 10 e-cig users was conducted. RNA was extracted from BAL samples for total transcriptome RNA-seq analysis, allowing measurement of the microbiome and human gene expression. Differences in the microbiome by smoking status were determined by the Kruskal-Wallis test. Pairwise Wilcoxon rank sum tests with Holm correction was used. Effect size (fold change &amp;gt;1.5) and adjusted P-value cutoffs (&amp;lt;0.05) were used to identify microbes of potential interest. The limma-voom package in R was used to determine associations with human gene expression. Results: We identified 53 differentially-abundant bacterial species in BAL samples by smoking group. Among them, the majority were less abundant in the lung of smokers and ~20 are normally found in the oral microbiome. While there were significant differences in differentially-abundant microbes between e-cig users and smokers and between smokers and never-smokers, the microbiome of e-cig users did not differ from that of never-smokers. In preliminary analyses of gene expression, there were 2,400 differentially-expressed human genes among the three groups, of which 58 are inflammatory pathway genes. Conclusion: The majority of differentially-abundant microbes observed by smoking group are largely due to smokers. The microbiome of e-cig users is more similar to that of never-smokers. Interestingly, nearly half of microbes that are altered in the lung microbiome due to smoking use are bacterial species normally found in the oral microbiome. These findings suggest that the alterations in the oral microbiome associated with smoking cigarettes may also be reflected in the lung microbiome. Citation Format: Kevin L. Ying, Min-Ae Song, Daniel Y. Weng, Quentin A. Nickerson, Joseph P. McElroy, Theodore M. Brasky, Mark D. Wewers, Ewy Mathé, Jo L. Freudenheim, Peter G. Shields. Microbial and inflammatory response to electronic cigarette and cigarette use [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 664.