Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1214875 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR32103929_1.fastq.gz | Fastqsanger.gz | |||
| SRR32103930_1.fastq.gz | Fastqsanger.gz | |||
| SRR32103931_1.fastq.gz | Fastqsanger.gz | |||
| SRR32103932_1.fastq.gz | Fastqsanger.gz | |||
| SRR32103933_1.fastq.gz | Fastqsanger.gz |
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Similar Datasets
Project description:Subgingival Microbiome of Electronic Cigarette Users
| PRJNA544061 | ENA
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.
2024-07-10 | GSE253603 | GEO
Project description:Background: The microbiome is increasingly being linked to cancer risk. Little is known about the lung and oral cavity microbiomes in healthy smokers (SM), and even less for electronic cigarette (EC) users, compared healthy never-smokers (NS). Methods: In a cross-sectional pilot study of SM (N=8), EC users (N=10) and NS (N=10) saliva and bronchoscopy-collected bronchoalveolar lavage samples were collected. Bacteria species were identified through metatranscriptome profiling by RNA-sequencing to study associations with the lung and oral microbiome. Pairwise comparisons and linear modeling was assessed with false discovery rates <0.1. Results: Total bacterial load was similar for the SM, EC users and NS, and there was no differences in the bacterial diversity across groups. In the lung, there were 44 bacterial species that were statistically significantly different for SM/NS, 80% of which were decreased in the SM. There were 12 bacterial species that were different for SM/EC users, all of which were decreased, 10 of which were also identified in the SM/NS comparison. The 2 bacterial species unique to SM/EC comparison were Neisseria sp. KEM232 and Curvibacter sp. AEP1-3. From the top 5 decreased species in SM/EC, 3 were also identified in the SM/NS comparison (Neisseria elongata, Neisseria sicca, and Haemophilus parainfluenzae) and 2 of these were unique to the SM/EC comparison (Neisseria zoodegmatis and Ottowia sp. oral taxon 894). There were 8 species increased in SM compared to NS, none of which are known to be clinically significant. In the oral microbiome, 152 bacteria species were differentially abundant for the SM/NS analysis, and only 17 for the EC/NS comparison, all which were also present in SM/NS comparisons. There were 21 bacteria that were differentially abundant in both the lung and oral cavity for SM and NS, 95% also were decreased in the SM. Conclusion: Smoking and EC use do not appear to materially affect the lung microbiome, although differences are noted of unclear clinical significance. Most differentially abundant bacteria decreased, which may be due to a toxic effect of cigarette smoke, including a change in humidity or heating. Given the low number of overlapping oral and lung microbes, the oral microbiome does not appear to be a good surrogate for smoking-related effects in the lung.
2022-07-13 | GSE180785 | GEO
Project description:In this paper, we first report that EC smoking significantly increases the odds of gingival inflammation. Then, we seek to identify and explain the mechanism that underlies the relationship between EC smoking and gingival inflammation via the oral microbiome. We performed mediation analyses to assess if EC smoking affects the oral microbiome, which in turn affects gingival inflammation. For this, we collected saliva and subgingival samples from EC users and non-users and profiled their microbial compositions via 16S rRNA amplicon sequencing. We then performed α-diversity, β-diversity, and taxonomic differential analyses to survey the disparity in microbial composition between EC users and non-users. We found significant increases in α-diversity in EC users and disparities in β-diversity between EC users and non-users.
2022-12-09 | GSE201949 | GEO
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.
2016-10-12 | GSE82137 | GEO
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.
2023-07-05 | GSE227547 | GEO
Project description:Gene Expression Alterations in Bronchial Epithelium of Electronic Cigarette Users
| PRJNA439243 | ENA
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.
2019-10-09 | GSE112073 | GEO