Smoking effect on DNA methylation in human blood CD8T cells
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE147430 | GEO | 2021/01/28
REPOSITORIES: GEO
Similar Datasets
Project description:To better characterize smoking–associated methylation changes in whole blood, we used Illumina HumanMethylation450 BeadChip to assess DNA samples from current (SM, n=172) and never smokers (NS, n=81).
2017-02-14 | GSE85210 | 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: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:Smoking effect on DNA methylation in human blood CD8T cells
| PRJNA614542 | ENA
Project description:Cigarette smoking is a major cause of preventable morbidity and mortality. While quitting smoking is the best option, switching from cigarettes to non-combustible alternatives (NCAs) such as e-vapor products is a viable harm reduction approach for smokers who would otherwise continue to smoke. A key challenge for the clinical assessment of NCAs is that self-reported product use can be unreliable, compromising the proper evaluation of their risk reduction potential. In this cross-sectional study with 205 healthy volunteers, we combined comprehensive exposure characterization with in-depth multi-omics profiling to compare effects across four study groups: cigarette smokers (CS), e-vapor users (EV), former smokers (FS) and never smokers (NS). Multi-omics analyses included metabolomics, transcriptomics, DNA methylomics, proteomics, and lipidomics. Comparison of the molecular effects between CS and NS recapitulated several previous observations, such as increases in inflammatory markers in CS. Generally, FS and EV demonstrated intermediate molecular effects between the NS and CS groups. Stratification of the FS and EV by combustion exposure markers suggested that this positioning on the scale between CS and NS was partially driven by non-compliance / dual use. Overall, this study highlights the importance of in-depth exposure characterization before biological effect characterization for any NCA assessment study.
2024-02-22 | E-MTAB-12751 | biostudies-arrayexpress
Project description:While tobacco smoke exposure strongly influences DNA methylation and is causative in numerous human diseases, the underlying mechanistic links are obscure. Here we investigated genome-wide smoking-associated differentially methylated regions (SM-DMRs) using CD14 monocytes of smokers (n=47) and nonsmokers (n=46) from two independently recruited populations, the Multi-Ethnic Study of Atherosclerosis (MESA) and Clinical Research Unit (CRU) at NIEHS. We found that SM-DMRs preferentially occur at genomic regions with the characteristics of putative enhancer, open chromatin, and the enrichment of TF binding indicated by ENCODE/Roadmap Epigenome/BLUEPRINT datasets. Most of our selected candidate SM-DMRs identified in the two populations were also observed in other hematopoietic cell types (CD15 granulocytes, CD19 B cells, CD4 T cells, CD8 T cells, CD56 NK cells) and were successfully validated using a second method in an independently recruited group of subjects. Aryl-Hydrocarbon Receptor Repressor (AHRR) SM-DMR, located at an intragenic enhancer, was the most significantly affected DMR and we have previously reported that a methylation level of a CpG in this gene was associated with subclinical atherosclerosis. The AHRR DMR was also detected in saliva DNA and these results were highly correlated with effects in monocytes (r2 = 0.90), suggesting that saliva may provide a potential alternative, noninvasive source for biomarkers that use DNA. Mechanistically, our results suggested that AHRR SM-DMR upregulated AHRR mRNA through activating AHRR enhancer in monocytes of smokers but not in granulocytes, indicated by increased noncoding RNA. Taken together, our study suggests that cell type-specific activation of enhancers at SM-DMRs may represent a mechanism driving smoking-related disease.
2017-12-19 | GSE104700 | GEO
Project description:A tissue like buccal mucosa (from cheek swabs) would be an ideal sample material for rapid, easy collection for testing of biomarkers as an alternative to blood. A limited number of studies, primarily in the smoker/oral cancer literature, address this tissue's efficacy for quantitative PCR or microarray gene expression analysis. In this study both qPCR and microarray analyses were used to evaluate gene expression in buccal cells. An initial study comparing blood and buccal cells from the same individuals looked at relative amounts of four genes. The RNA isolated from buccal cells was degraded but was of sufficient quality to be used with RT-qPCR to detect expression of specific genes. Second, buccal cell RNA was used for microarray-based differential gene expression studies by comparing gene expression between smokers and nonsmokers. The isolation and amplification protocol allowed use of 150-fold less buccal cell RNA than had been reported previously with human microarrays. We report here the finding of a small number of significant gene expression differences between smokers and nonsmokers, using buccal cells as target material. Additionally, Gene Set Enrichment Analysis confirmed that these genes were changing expression in the same pattern as seen in an earlier buccal cell study performed by another group. Our results suggest that in spite of a high degree of RNA degradation, buccal cells from cheek mucosa could be used to detect differential gene expression between smokers and nonsmokers. However the RNA degradation, increase in sample variability and microarray failure rate show that buccal samples should be used with caution as source material in expression studies. Samples were collected from eight subjects, four smokers (Sm)and four nonsmokers (NS). Each cheek was sampled creating an a and b sample for each subject which is reflected in the array name. All samples were isolated separately for total RNA. Each was hybridzed to microarrays to examine for differential gene expression between smokers and nonsmokers. There are 14 total samples in the main dataset (Set 2). One cheek sample failed in microarray analysis for two individuals, 08BCNS23 a and 08BCSm27 a, and so are not included here. A sample set (Set 1) was created which contains the four samples shown in this file. They represent repeated sampling of both cheeks for two individuals to test for reproducibility. There is a separate RMA file and metadata file (this file) for these data. These included samples 08BC11Sm a and b, a smoker, and 08BC12NSa and b a nonsmoker.
2010-03-07 | E-GEOD-16149 | biostudies-arrayexpress
Project description:Cigarette smoke is associated with the majority of lung cancers: however, 25% of lung cancer patients are non-smokers, and half of all newly diagnosed lung cancer patients are former smokers. Lung tumors exhibit distinct epidemiological, clinical, pathological, and molecular features depending on smoking status, suggesting divergent mechanisms underlie tumorigenesis in smokers and non-smokers. MicroRNAs (miRNAs) are integral contributors to tumorigenesis and mediate biological responses to smoking. Based on the hypothesis that smoking-specific miRNA differences in lung adenocarcinomas reflect distinct tumorigenic processes selected by different smoking and non-smoking environments, we investigated the contribution of miRNA disruption to lung tumor biology and patient outcome in the context of smoking status. Results: We discovered novel and distinct smoking-status-specific patterns of miRNA and miRNA-mediated gene networks, and identified miRNAs that were prognostically significant in a smoking-dependent manner. Conclusions: We conclude that miRNAs disrupted in a smoking-status-dependent manner affect distinct cellular pathways and differentially influence lung cancer patient prognosis in current, former and never smokers. Our findings may represent promising biologically relevant markers for lung cancer prognosis or therapeutic intervention. We applied a whole transcriptome sequencing based approach to interrogate miRNA levels in 94 patient-matched lung adenocarcinoma and non-malignant lung parenchymal tissue pairs from current [CS], former [FS] and never smokers [NS].
2014-10-30 | E-GEOD-62182 | biostudies-arrayexpress
Project description:Pre-processing method comparison on Illumina HumanMethylation450 BeadChips array
| PRJNA329483 | ENA
Project description:DNA methylation classification reference set (1077) and validation set (428) of 1505 sarcoma samples using Illumina HumanMethylation450 BeadChips or Illumina Infinium HumanMethylation850 BeadChips
2020-03-01 | GSE140686 | GEO