scholarly journals Peripheral blood microbial signatures in current and former smokers

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jarrett D. Morrow ◽  
Peter J. Castaldi ◽  
Robert P. Chase ◽  
Jeong H. Yun ◽  
Sool Lee ◽  
...  
Keyword(s):  
Peripheral Blood ◽  
Interaction Analysis ◽  
Smoking Status ◽  
Meta Analysis ◽  
Human Microbiome ◽  
Independent Set ◽  
Chronic Obstructive ◽  
Obstructive Pulmonary Disease ◽  
Dyspnea Score ◽  
Former Smokers

AbstractThe human microbiome has a role in the development of multiple diseases. Individual microbiome profiles are highly personalized, though many species are shared. Understanding the relationship between the human microbiome and disease may inform future individualized treatments. We hypothesize the blood microbiome signature may be a surrogate for some lung microbial characteristics. We sought associations between the blood microbiome signature and lung-relevant host factors. Based on reads not mapped to the human genome, we detected microbial nucleic acids through secondary use of peripheral blood RNA-sequencing from 2,590 current and former smokers with and without chronic obstructive pulmonary disease (COPD) from the COPDGene study. We used the Genome Analysis Toolkit (GATK) microbial pipeline PathSeq to infer microbial profiles. We tested associations between the inferred profiles and lung disease relevant phenotypes and examined links to host gene expression pathways. We replicated our analyses using a second independent set of blood RNA-seq data from 1,065 COPDGene study subjects and performed a meta-analysis across the two studies. The four phyla with highest abundance across all subjects were Proteobacteria, Actinobacteria, Firmicutes and Bacteroidetes. In our meta-analysis, we observed associations (q-value < 0.05) between Acinetobacter, Serratia, Streptococcus and Bacillus inferred abundances and Modified Medical Research Council (mMRC) dyspnea score. Current smoking status was associated (q < 0.05) with Acinetobacter, Serratia and Cutibacterium abundance. All 12 taxa investigated were associated with at least one white blood cell distribution variable. Abundance for nine of the 12 taxa was associated with sex, and seven of the 12 taxa were associated with race. Host-microbiome interaction analysis revealed clustering of genera associated with mMRC dyspnea score and smoking status, through shared links to several host pathways. This study is the first to identify a bacterial microbiome signature in the peripheral blood of current and former smokers. Understanding the relationships between systemic microbial signatures and lung-related phenotypes may inform novel interventions and aid understanding of the systemic effects of smoking.

scholarly journals Peripheral blood microbial signatures in COPD

2020 ◽  
Author(s):  
Jarrett D. Morrow ◽  
Peter J. Castaldi ◽  
Robert P. Chase ◽  
Jeong H. Yun ◽  
Sool Lee ◽  
...  
Keyword(s):  
Lung Disease ◽  
Peripheral Blood ◽  
Interaction Analysis ◽  
Airway Remodeling ◽  
Human Microbiome ◽  
Chronic Obstructive ◽  
Obstructive Pulmonary Disease ◽  
Bacterial Microbiome ◽  
Former Smokers ◽  
Expression Pathways

AbstractBackgroundThe human microbiome has a role in the development of human diseases. Individual microbiome profiles are highly personalized, though many species are shared. Understanding the relationship between the human microbiome and disease may inform future individualized treatments. Specifically, the blood microbiome, once believed sterile, may be a surrogate for some lung and gut microbial characteristics. We sought associations between the blood microbiome and lung-relevant host factors.MethodsBased on reads not mapped to the human genome, we detected microbial nucleic acid signatures in peripheral blood RNA-sequencing for 2,590 current and former smokers with and without chronic obstructive pulmonary disease (COPD) from the COPDGene study. We used the GATK microbial pipeline PathSeq to infer microbial profiles. We tested associations between the inferred profiles and lung disease relevant phenotypes and examined links to host gene expression pathways.ResultsThe four phyla with highest abundance across all subjects were Proteobacteria, Actinobacteria, Firmicutes and Bacteroidetes. We observed associations between exacerbation phenotypes and the relative abundance of Staphylococcus, Acidovorax and Cupriavidus. The genus Flavobacterium was associated with emphysema and change in emphysema. Our host-microbiome interaction analysis revealed clustering of genera associated with emphysema, systemic inflammation, airway remodeling and exacerbations, through links to lung-relevant host pathways.ConclusionsThis study is the first to identify a bacterial microbiome signature in the peripheral blood of current and former smokers. Understanding the relationships between the systemic microbial populations and lung disease severity may inform novel interventions and aid in the understanding of exacerbation phenotypes.

scholarly journals Widespread Sexual Dimorphism in the Transcriptome of Human Airway Epithelium in Response to Smoking

2019 ◽  
Author(s):  
Chen Xi Yang ◽  
Henry Shi ◽  
Irving Ding ◽  
Cheng Wei Tony Yang ◽  
Edward Kyoo-Hoon Kim ◽  
...  
Keyword(s):  
Airway Epithelium ◽  
Molecular Mechanisms ◽  
Smoking Status ◽  
Epidemiological Studies ◽  
Chronic Obstructive ◽  
Obstructive Pulmonary Disease ◽  
Human Airway ◽  
Human Airway Epithelium ◽  
Increased Risk ◽  
Former Smokers

ABSTRACTEpidemiological studies have shown that female smokers are at higher risk of chronic obstructive pulmonary disease (COPD). Female patients have worse symptoms and health status and increased risk of exacerbations. We determined the differences in the transcriptome of the airway epithelium between males and females at baseline and in response to smoking. We processed public gene expression data of human airway epithelium into a discovery cohort of 211 subjects (never smokers n=68; current smokers n=143) and two replication cohorts of 104 subjects (21 never, 52 current, and 31 former smokers) and 238 subjects (99 current and 139 former smokers. We analyzed gene differential expression with smoking status, sex, and smoking-by-sex interaction and used network approaches for modules’ level analyses. We identified and replicated two differentially expressed modules between the sexes in response to smoking with genes located throughout the autosomes and not restricted to sex chromosomes. The two modules were enriched in autophagy (up-regulated in female smokers) and response to virus and type 1 interferon signaling pathways which were down-regulated in female smokers compared to males. The results offer insights into the molecular mechanisms of the sexually dimorphic COPD risk and presentation potentially enabling a precision medicine approach to COPD.

scholarly journals Widespread Sexual Dimorphism in the Transcriptome of Human Airway Epithelium in Response to Smoking

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Chen Xi Yang ◽  
Henry Shi ◽  
Irving Ding ◽  
Stephen Milne ◽  
Ana I. Hernandez Cordero ◽  
...  
Keyword(s):  
Airway Epithelium ◽  
Molecular Mechanisms ◽  
Smoking Status ◽  
Epidemiological Studies ◽  
Chronic Obstructive ◽  
Obstructive Pulmonary Disease ◽  
Human Airway ◽  
Human Airway Epithelium ◽  
Increased Risk ◽  
Former Smokers

AbstractEpidemiological studies have shown that female smokers are at higher risk of chronic obstructive pulmonary disease (COPD). Female patients have worse symptoms and health status and increased risk of exacerbations. We determined the differences in the transcriptome of the airway epithelium between males and females, as well the sex-by-smoking interaction. We processed public gene expression data of human airway epithelium into a discovery cohort of 211 subjects (never smokers n = 68; current smokers n = 143) and two replication cohorts of 104 subjects (21 never, 52 current, and 31 former smokers) and 238 subjects (99 current and 139 former smokers. We analyzed gene differential expression with smoking status, sex, and smoking-by-sex interaction and used network approaches for modules’ level analyses. We identified and replicated two differentially expressed modules between the sexes in response to smoking with genes located throughout the autosomes and not restricted to sex chromosomes. The two modules were enriched in autophagy (up-regulated in female smokers) and response to virus and type 1 interferon signaling pathways which were down-regulated in female smokers compared to males. The results offer insights into the molecular mechanisms of the sexually dimorphic effect of smoking, potentially enabling a precision medicine approach to smoking related lung diseases.

scholarly journals Meta-analysis of Gene Expression Microarray Datasets in Chronic Obstructive Pulmonary Disease

2019 ◽  
Author(s):  
Lavida R. K. Rogers ◽  
Madison Verlinde ◽  
George I. Mias
Keyword(s):  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Smoking Status ◽  
Meta Analysis ◽  
Differentially Expressed ◽  
Chronic Obstructive ◽  
P Value ◽  
Obstructive Pulmonary Disease ◽  
Microarray Datasets ◽  
Microarray Expression

AbstractChronic obstructive pulmonary disease (COPD) was classified by the Centers for Disease Control and Prevention in 2014 as the 3rd leading cause of death in the United States (US). The main cause of COPD is exposure to tobacco smoke and air pollutants. Problems associated with COPD include under-diagnosis of the disease and an increase in the number of smokers worldwide. The goal of our study is to identify disease variability in the gene expression profiles of COPD subjects compared to controls. We used pre-existing, publicly available microarray expression datasets to conduct a meta-analysis. Our inclusion criteria for microarray datasets selected for smoking status, age and sex of blood donors reported. Our datasets used Affymetrix, Agilent microarray platforms (7 datasets, 1,262 samples). We re-analyzed the curated raw microarray expression data using R packages, and used Box-Cox power transformations to normalize datasets. To identify significant differentially expressed genes we ran an analysis of variance with a linear model with disease state, age, sex, smoking status and study as effects that also included binary interactions. We found 1,513 statistically significant (Benjamini-Hochberg-adjusted p-value <0.05) differentially expressed genes with respect to disease state (COPD or control). We further filtered these genes for biological effect using results from a Tukey test post-hoc analysis (Benjamini-Hochberg-adjusted p-value <0.05 and 10% two-tailed quantiles of mean differences between COPD and control), to identify 304 genes. Through analysis of disease, sex, age, and also smoking status and disease interactions we identified differentially expressed genes involved in a variety of immune responses and cell processes in COPD. We also trained a logistic regression model using the 304 genes as features, which enabled prediction of disease status with 84% accuracy. Our results give potential for improving the diagnosis of COPD through blood and highlight novel gene expression disease signatures.

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