A Pilot Study Of Immunological and Microbiome Profiling Reveals Distinct Inflammatory Profiles For Smokers and Electronic Cigarette Users [re-analysis]
Background: Smoking increases pulmonary inflammation, but an effect by electronic cigarette (EC) vaping is less understood. We previously reported smokers (SM) had increased lung immune cell counts and inflammatory gene expression in bronchial epithelial cells compared to EC users and never-smokers (NS). Here we report association of smoking and vaping with immune cell subtypes and gene expression in bronchoalveolar lavage. Methods: SM, EC users, and NS underwent bronchoscopy (n=28).  RNASeq and the CIBERSORT computational algorithm were used to determine immune cell subtypes, along with inflammatory gene expression and microbiome metatranscriptomics. Correlations and associations were assessed across and within the tobacco-use groups, corrected for false discovery rates. Results: Classification of macrophage subtypes revealed a 2-fold increase in M0 macrophages for smokers and EC users relative to never-smokers, with a concordant decrease in M2 macrophages. There were 68, 19, and 1 significantly differentially expressed inflammatory genes (DEG) (FDR<0.05; log2-fold change>1) between SM/NS, SM/EC users, and EC users/NS respectively. CSF-1 and GATA3 expression correlated positively and inversely with M0 and M2 macrophages respectively. Correlation profiling for DEG showed distinct lung profiles for each participant group. There were 3 bacteria genera-DEG correlations and 3 bacteria genera-macrophage subtype correlations (Diffcorr>0.5 and FDR<0.1). Conclusions:  In this pilot study, smoking and EC use were associated with an increase in undifferentiated M0 macrophages, but smokers differed from EC users and NS for inflammatory gene expression. The preliminary data support the hypothesis that smoking and EC use have toxic lung effects  influencing inflammatory responses, but not via changes in the microbiome. Overall design: Inflammatory gene expression profiling by high throughput sequencing (RNA-seq) The re-analyzed GSE180785 Samples (28 out of 54) have been re-accessioned for the convenient retrieval of the complete raw data from SRA. Please note that, during the lung microbiome analysis, one subject (102B(T2351_PS16)) was removed from the analysis for being an outlier, and thus the bacteria genus csv only contains 27 data column.