Project description:Background: While electronic cigarette (ECIG) use is rapidly rising, their safety profile remains uncertain. The effects of tobacco cigarette (TCIG) smoke on bronchial airway epithelial gene-expression have provided insights into tobacco-related disease pathogenesis. Understanding the impact of electronic cigarettes (ECIGs) on airway gene-expression could provide insights into their potential long-term health effects. Objectives: We sought to compare the bronchial airway gene-expression profiles of former TCIG smokers now using ECIGs with the profiles of former and current TCIG smokers. Methods: We performed gene-expression profiling of bronchial epithelial cells collected from TCIG smokers not using ECIGs (n=21), former smokers using ECIGs (n=15), and current TCIG smokers not using ECIGs (n=9). We then compared our findings with previous studies of the effects of TCIG use on bronchial epithelium, as well an in vitro model of ECIG exposure. Results: Amongst 3,165 genes whose expression varied between the three study groups (q < 0.05), we identified 468 genes significantly altered in ECIG users relative to former smokers (p < 0.05). 79 of these genes were up or down-regulated concordantly between ECIG and TCIG. We did not detect ECIG-associated gene expression changes in known pathways associated with TCIG usage. Genes downregulated in ECIG users are enriched among the genes most downregulated by exposure of airway epithelium to ECIG vapor in vitro. Conclusions: TCIG exposure was associated with a larger number of airway gene-expression changes than with ECIG exposures. ECIGs induce both distinct and shared patterns of gene expression relative to TCIGs in the bronchial airway epithelium.
Project description:Analysis of primary human bronchial epithelial cells grown in air liquid interface, exposed in vitro to whole tobacco cigarette smoke (48 puffs, 48 minutes) and electronic cigarette aerosol (400 puffs, 200 minutes). Electronic cigarette exposures included two flavors (menthol, tobacco) both with, and without nicotine.
Project description:Exposure to electronic cigarette (e-cigarette) aerosol has been linked to a number of health concerns, including DNA damage, elevated oxidative stress, release of inflammatory cytokine, and dysfunctions in epithelial barriers. However, little is known about the effect of exclusive e-cigarette use on expression profiles of exosomal miRNAs, which play critical regulatory roles in many inflammatory responses and disease process including cancer. We aim to compare the exosomal microRNAs expression profile between exclusive e-cigarette users and normal controls without any tobacco product use (non-users). Using blood and urine samples from exclusive e-cigarette users and non-users in the Population Assessment of Tobacco and Health (PATH) Wave 1 study (2013-2014), we examined exosomal microRNAs expression levels through Illumina NextSeq 500/550 sequencing. We identified microRNAs that have significantly higher expression levels in exclusive e-cigarette users than non-users. Gene enrichment analysis of these significant exosomal microRNAs showed their involvement in cancer related pathways, which might indicate a potential elevated risk of cancer among exclusive e-cigarette users.
Project description:Electronic cigarettes (EC) are increasing in popularity, but there is only little information on their biologic effects on the oral epithelium, the initial site exposed to EC smoke. We assessed the oral epithelium response to EC by comparing the histology and RNA transcriptome (mRNA and miRNA) of healthy EC vapers to nonsmokers (NS). mRNA was assessed based on: (1) genome-wide; (2) genes previously identified as dysregulated in the oral epithelium of EC vapers vs NS; (3) immune and inflammatory-related genes previously identified as dysregulated in the nasal epithelium of EC vapers compared to NS; (4) genes previously identified as dysregulated in the small airway epithelium of NS following an acute exposure to EC; and (5) genes related to the initial steps of COVID-19 infection. In addition, miRNA was assessed genome-wide. Comparisons were performed using ANOVA, and Benajmini-Hochberg corrected p <0.05 was considered significant. The histology of the epithelium, lamina propria and basal layer in EC vapers appeared normal. Assessment of mRNA and miRNA, based on all gene lists, did not identify any genes significantly modified in the oral epithelium of EC vapers. Assessment of the oral epithelium of healthy EC vapers by histology, mRNA and miRNA demonstrated no abnormalities in response to EC smoke.
Project description: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.
Project description:Electronic cigarettes, also known as ecig-s, have been widely used in recent years, especially among younger populations. Cytotoxic and carcinogenic substances can be present in their composition, but little is known about the risks associated with their use. The purpose of this study was to evaluate the proteome profile of saliva from users of electronic cigarettes. Participants were divided into two groups: the Electronic Cigarette Group (EG), consisting of 25 regular and exclusive e-cig users, and the Control Group (CG), comprising 25 non-smokers and non-e-cig users, matched by sex and age to the EG. All participants underwent clinical examination and unstimulated saliva collection for evaluation of the salivary proteome. Shotgun proteomics resulted in the identification of 168 proteins, including 48 exclusive to EG, 28 exclusive to CG, and 92 shared by both groups. Statistical comparison (t-test) between EG and CG revealed four differentially expressed proteins: Fatty acid binding protein 5, Calgranulin-B, and Cornifin-A in the CG, and cytostatin-D in the EG. Additionally, a higher abundance of proteins was observed, including glutathione S-transferase P, Immunoglobulin J chain and Acetyl-CoA dehydrogenase, in the EG group. These findings suggest an organismal response to increased oxidative stress, the presence of inflammatory components, and altered salivary microbiome, which can predispose individuals to the development of future pathological conditions.
Project description:Electronic cigarette (EC) use has grown substantially since entry into the US market, particularly among adolescents and combustible tobacco users. Despite growing popularity and claims of harm reduction, the health effects of these products outside the lung is poorly understood. Several constituents of cigarette smoke (CS) with known neurovascular and inflammatory effects are present in EC liquids or formed during the generation of vapor. The present study characterizes the impact of EC exposure on neuroinflammation and blood-brain barrier (BBB) function, and provides comparison of outcomes with reference cigarette exposure normalized to comparable levels of nicotine delivery. Additionally, the contribution of nicotine to observed effects is elucidated through comparison with EC liquids which are verified to be nicotine-free. C57BL/6 mice are exposed to 2 hrs of daily EC vapor or CS, beginning at 8 wks of age. Changes in BBB gene expression are first characterized by whole exome sequencing of isolated brain microvessels following chronic (2 month) EC exposure.
Project description:Electronic cigarettes (e-cigarettes) have gained their popularity as a substitute for cigarettes or cigars. Despite the widespread use of flavoring chemicals in e-cigarettes, the health impacts of the flavoring compounds, in particular their effects on critical cellular function in the lung, remain largely unknown. The goal of this study was to identify transcriptomic changes and impacted biological pathways in primary human bronchial epithelial cells (HBECs) exposed to flavoring chemicals (diacetyl or 2,3-pentanedione) and to flavored e-cigarette smoke. An airway-liquid interface culturing method was used to differentiate primary human bronchial epithelial cells (HBECs) into mature epithelial cells, which were then treated with 25 ppm diacetyl, 100 ppm 2,3 pentanedione, or e-cigarette smoke solution containing 2 ppm diacetyl. Poly(A)-selected RNA-Seq libraries were prepared with the PrepX RNA-Seq for Illumina Library kit. An Illumina HiSeq 2500 instrument was used to generate 50 base pair single-end reads. STAR was used to align sequencing reads to the hg38 reference genome, and HTSeq was used to quantify transcript levels. DESeq2 was used to perform differential expression analysis.