Smoking-mediated up-regulation of GAD67 expression in the human airway epithelium

<p>Abstract</p> <p>Background</p> <p>The production of gamma-amino butyric acid (GABA) is dependent on glutamate decarboxylases (GAD65 and GAD67), the enzymes that catalyze the decarboxylation of glutamate to GABA. Based on studies suggesting a role of the airway epithelial GABAergic system in asthma-related mucus overproduction, we hypothesized that cigarette smoking, another disorder associated with increased mucus production, may modulate GABAergic system-related gene expression levels in the airway epithelium.</p> <p>Methods</p> <p>We assessed expression of the GABAergic system in human airway epithelium obtained using bronchoscopy to sample the epithelium and microarrays to evaluate gene expression. RT-PCR was used to confirm gene expression of GABAergic system gene in large and small airway epithelium from heathy nonsmokers and healthy smokers. The differences in the GABAergic system gene was further confirmed by TaqMan, immunohistochemistry and Western analysis.</p> <p>Results</p> <p>The data demonstrate there is a complete GABAergic system expressed in the large and small human airway epithelium, including glutamate decarboxylase, GABA receptors, transporters and catabolism enzymes. Interestingly, of the entire GABAergic system, smoking modified only the expression of GAD67, with marked up-regulation of GAD67 gene expression in both large (4.1-fold increase, p < 0.01) and small airway epithelium of healthy smokers (6.3-fold increase, p < 0.01). At the protein level, Western analysis confirmed the increased expression of GAD67 in airway epithelium of healthy smokers compared to healthy nonsmokers (p < 0.05). There was a significant positive correlation between GAD67 and MUC5AC gene expression in both large and small airway epithelium (p < 0.01), implying a link between GAD67 and mucin overproduction in association with smoking.</p> <p>Conclusions</p> <p>In the context that GAD67 is the rate limiting enzyme in GABA synthesis, the correlation of GAD67 gene expression with MUC5AC expressions suggests that the up-regulation of airway epithelium expression of GAD67 may contribute to the increase in mucus production observed in association with cigarette smoking.</p> <p>Trial registration</p> <p>NCT00224198; NCT00224185</p

The Human Airway Epithelial Basal Cell Transcriptome

The human airway epithelium consists of 4 major cell types: ciliated, secretory, columnar and basal cells. During natural turnover and in response to injury, the airway basal cells function as stem/progenitor cells for the other airway cell types. The objective of this study is to better understand human airway epithelial basal cell biology by defining the gene expression signature of this cell population.. The basal cell signature displayed overlap with genes expressed in basal-like cells from other human tissues and with that of murine airway basal cells. Consistent with self-modulation as well as signaling to other airway cell types, the human airway basal cell signature was characterized by genes encoding extracellular matrix components, growth factors and growth factor receptors, including genes related to the EGF and VEGF pathways. Interestingly, while the basal cell signature overlaps that of basal-like cells of other organs, the human airway basal cell signature has features not previously associated with this cell type, including a unique pattern of genes encoding extracellular matrix components, G protein-coupled receptors, neuroactive ligands and receptors, and ion channels.The human airway epithelial basal cell signature identified in the present study provides novel insights into the molecular phenotype and biology of the stem/progenitor cells of the human airway epithelium

RNA-Seq quantification of the human small airway epithelium transcriptome

<p>Abstract</p> <p>Background</p> <p>The small airway epithelium (SAE), the cell population that covers the human airway surface from the 6^thgeneration of airway branching to the alveoli, is the major site of lung disease caused by smoking. The focus of this study is to provide quantitative assessment of the SAE transcriptome in the resting state and in response to chronic cigarette smoking using massive parallel mRNA sequencing (RNA-Seq).</p> <p>Results</p> <p>The data demonstrate that 48% of SAE expressed genes are ubiquitous, shared with many tissues, with 52% enriched in this cell population. The most highly expressed gene, SCGB1A1, is characteristic of Clara cells, the cell type unique to the human SAE. Among other genes expressed by the SAE are those related to Clara cell differentiation, secretory mucosal defense, and mucociliary differentiation. The high sensitivity of RNA-Seq permitted quantification of gene expression related to infrequent cell populations such as neuroendocrine cells and epithelial stem/progenitor cells. Quantification of the absolute smoking-induced changes in SAE gene expression revealed that, compared to ubiquitous genes, more SAE-enriched genes responded to smoking with up-regulation, and those with the highest basal expression levels showed most dramatic changes. Smoking had no effect on SAE gene splicing, but was associated with a shift in molecular pattern from Clara cell-associated towards the mucus-secreting cell differentiation pathway with multiple features of cancer-associated molecular phenotype.</p> <p>Conclusions</p> <p>These observations provide insights into the unique biology of human SAE by providing quantit-ative assessment of the global transcriptome under physiological conditions and in response to the stress of chronic cigarette smoking.</p

Increased power of mixed models facilitates association mapping of 10 loci for metabolic traits in an isolated population

The potential benefits of using population isolates in genetic mapping, such as reduced genetic, phenotypic and environmental heterogeneity, are offset by the challenges posed by the large amounts of direct and cryptic relatedness in these populations confounding basic assumptions of independence. We have evaluated four representative specialized methods for association testing in the presence of relatedness; (i) within-family (ii) within- and between-family and (iii) mixed-models methods, using simulated traits for 2906 subjects with known genome-wide genotype data from an extremely isolated population, the Island of Kosrae, Federated States of Micronesia. We report that mixed models optimally extract association information from such samples, demonstrating 88% power to rank the true variant as among the top 10 genome-wide with 56% achieving genome-wide significance, a >80% improvement over the other methods, and demonstrate that population isolates have similar power to non-isolate populations for observing variants of known effects. We then used the mixed-model method to reanalyze data for 17 published phenotypes relating to metabolic traits and electrocardiographic measures, along with another 8 previously unreported. We replicate nine genome-wide significant associations with known loci of plasma cholesterol, high-density lipoprotein, low-density lipoprotein, triglycerides, thyroid stimulating hormone, homocysteine, C-reactive protein and uric acid, with only one detected in the previous analysis of the same traits. Further, we leveraged shared identity-by-descent genetic segments in the region of the uric acid locus to fine-map the signal, refining the known locus by a factor of 4. Finally, we report a novel associations for height (rs17629022, P< 2.1 × 10−8

Biologic Phenotyping of the Human Small Airway Epithelial Response to Cigarette Smoking

BACKGROUND: The first changes associated with smoking are in the small airway epithelium (SAE). Given that smoking alters SAE gene expression, but only a fraction of smokers develop chronic obstructive pulmonary disease (COPD), we hypothesized that assessment of SAE genome-wide gene expression would permit biologic phenotyping of the smoking response, and that a subset of healthy smokers would have a "COPD-like" SAE transcriptome. METHODOLOGY/PRINCIPAL FINDINGS: SAE (10th-12th generation) was obtained via bronchoscopy of healthy nonsmokers, healthy smokers and COPD smokers and microarray analysis was used to identify differentially expressed genes. Individual responsiveness to smoking was quantified with an index representing the % of smoking-responsive genes abnormally expressed (I(SAE)), with healthy smokers grouped into "high" and "low" responders based on the proportion of smoking-responsive genes up- or down-regulated in each smoker. Smokers demonstrated significant variability in SAE transcriptome with I(SAE) ranging from 2.9 to 51.5%. While the SAE transcriptome of "low" responder healthy smokers differed from both "high" responders and smokers with COPD, the transcriptome of the "high" responder healthy smokers was indistinguishable from COPD smokers. CONCLUSION/SIGNIFICANCE: The SAE transcriptome can be used to classify clinically healthy smokers into subgroups with lesser and greater responses to cigarette smoking, even though these subgroups are indistinguishable by clinical criteria. This identifies a group of smokers with a "COPD-like" SAE transcriptome

Genome-Wide Association Studies in an Isolated Founder Population from the Pacific Island of Kosrae

It has been argued that the limited genetic diversity and reduced allelic heterogeneity observed in isolated founder populations facilitates discovery of loci contributing to both Mendelian and complex disease. A strong founder effect, severe isolation, and substantial inbreeding have dramatically reduced genetic diversity in natives from the island of Kosrae, Federated States of Micronesia, who exhibit a high prevalence of obesity and other metabolic disorders. We hypothesized that genetic drift and possibly natural selection on Kosrae might have increased the frequency of previously rare genetic variants with relatively large effects, making these alleles readily detectable in genome-wide association analysis. However, mapping in large, inbred cohorts introduces analytic challenges, as extensive relatedness between subjects violates the assumptions of independence upon which traditional association test statistics are based. We performed genome-wide association analysis for 15 quantitative traits in 2,906 members of the Kosrae population, using novel approaches to manage the extreme relatedness in the sample. As positive controls, we observe association to known loci for plasma cholesterol, triglycerides, and C-reactive protein and to a compelling candidate loci for thyroid stimulating hormone and fasting plasma glucose. We show that our study is well powered to detect common alleles explaining ≥5% phenotypic variance. However, no such large effects were observed with genome-wide significance, arguing that even in such a severely inbred population, common alleles typically have modest effects. Finally, we show that a majority of common variants discovered in Caucasians have indistinguishable effect sizes on Kosrae, despite the major differences in population genetics and environment

Altered lung biology of healthy never smokers following acute inhalation of E-cigarettes

Abstract Background Little is known about health risks associated with electronic cigarette (EC) use although EC are rising in popularity and have been advocated as a means to quit smoking cigarettes. Methods Ten never-smokers, without exposure history to tobacco products or EC, were assessed at baseline with questionnaire, chest X-ray, lung function, plasma levels of endothelial microparticles (EMP), and bronchoscopy to obtain small airway epithelium (SAE) and alveolar macrophages (AM). One week later, subjects inhaled 10 puffs of “Blu” brand EC, waited 30 min, then another 10 puff; n = 7 were randomized to EC with nicotine and n = 3 to EC without nicotine to assess biological responses in healthy, naive individuals. Results Two hr. post-EC exposure, subjects were again assessed as at baseline. No significant changes in clinical parameters were observed. Biological changes were observed compared to baseline, including altered transcriptomes of SAE and AM for all subjects and elevated plasma EMP levels following inhalation of EC with nicotine. Conclusions This study provides in vivo human data demonstrating that acute inhalation of EC aerosols dysregulates normal human lung homeostasis in a limited cohort of healthy naïve individuals. These observations have implications to new EC users, nonsmokers exposed to secondhand EC aerosols and cigarette smokers using EC to quit smoking. Trial registration ClinicalTrials.gov NCT01776398 (registered 10/12/12), NCT02188511 (registered 7/2/14)

Additional file 1: of Altered lung biology of healthy never smokers following acute inhalation of E-cigarettes

Supplemental Methods. Inclusion / exclusion criteria for heathy never smokers. Table S1. E-cigarette Effects Scale. Table S2A. Initiation of E-cigarette Vital Signs. Table S2B. Time point Differences of E-cigarette Vital Signs. Table S3. Urine Nicotine Metabolites Pre- and Post-Exposure to E-Cigarette Aerosols. Table S4. Small Airway Epithelium Differentially Expressed Genes Following Acute Inhalation of E-cigarettes with Nicotine. Table S5. Small Airway Epithelium Differentially Expressed Genes Following Acute Inhalation of E-cigarettes without Nicotine. Table S6. Alveolar Macrophage Differentially Expressed Genes Following Acute In-halation of E-cigarettes with Nicotine. Table S7. Alveolar Macrophage Differentially Expressed Genes Following Acute Inhalation of E-cigarettes without Nicotine. (PDF 199 kb