Air pollution exposure is estimated to contribute to approximately seven million early deaths every year worldwide and more than 3% of disability-adjusted life years lost. Air pollution has numerous harmful effects on health and contributes to the development and morbidity of cardiovascular disease, metabolic disorders, and a number of lung pathologies, including asthma and chronic obstructive pulmonary disease (COPD). Emerging data indicate that air pollution exposure modulates the epigenetic mark, DNA methylation (DNAm), and that these changes might in turn influence inflammation, disease development, and exacerbation risk. Several traffic-related air pollution (TRAP) components, including particulate matter (PM), black carbon (BC), ozone (O 3 ), nitrogen oxides (NO x ), and polyaromatic hydrocarbons (PAHs), have been associated with changes in DNAm; typically lowering DNAm after exposure. Effects of air pollution on DNAm have been observed across the human lifespan, but it is not yet clear whether early life developmental sensitivity or the accumulation of exposures have the most significant effects on health. Air pollution exposure-associated DNAm patterns are often correlated with long-term negative respiratory health outcomes, including the development of lung diseases, a focus in this review. Recently, interventions such as exercise and B vitamins have been proposed to reduce the impact of air pollution on DNAm and health. Ultimately, improved knowledge of how exposure-induced change in DNAm impacts health, both acutely and chronically, may enable preventative and remedial strategies to reduce morbidity in polluted environments. Electronic supplementary material The online version of this article (10.1186/s13148-019-0713-2) contains supplementary material, which is available to authorized users.

In asthma and chronic obstructive pulmonary disease, activation of G q -protein-coupled receptors causes bronchoconstriction. In each case, the management of moderate-to-severe disease uses inhaled corticosteroid (glucocorticoid)/long-acting β 2 -adrenoceptor agonist (LABA) combination therapies, which are more efficacious than either monotherapy alone. In primary human airway smooth muscle cells, glucocorticoid/LABA combinations synergistically induce the expression of regulator of G-protein signaling 2 (RGS2), a GTPaseactivating protein that attenuates G q signaling. Functionally, RGS2 reduced intracellular free calcium flux elicited by histamine, methacholine, leukotrienes, and other spasmogens. Furthermore, protection against spasmogen-increased intracellular free calcium, following treatment for 6 h with LABA plus corticosteroid, was dependent on RGS2. Finally, Rgs2-deficient mice revealed enhanced bronchoconstriction to spasmogens and an absence of LABA-induced bronchoprotection. These data identify RGS2 gene expression as a genomic mechanism of bronchoprotection that is induced by glucocorticoids plus LABAs in human airway smooth muscle and provide a rational explanation for the clinical efficacy of inhaled corticosteroid (glucocorticoid)/LABA combinations in obstructive airways diseases.adrenoreceptor | beta-2-adrenergic receptor | protein kinase A | glucocorticoid receptor | NR3C1

BackgroundThe capacity of technologies measuring DNA methylation (DNAm) is rapidly evolving, as are the options for applicable bioinformatics methods. The most commonly used DNAm microarray, the Illumina Infinium HumanMethylation450 (450K array), has recently been replaced by the Illumina Infinium HumanMethylationEPIC (EPIC array), nearly doubling the number of targeted CpG sites. Given that a subset of 450K CpG sites is absent on the EPIC array and that several tools for both data normalization and analyses were developed on the 450K array, it is important to assess their utility when applied to EPIC array data. One of the most commonly used 450K tools is the pan-tissue epigenetic clock, a multivariate predictor of biological age based on DNAm at 353 CpG sites. Of these CpGs, 19 are missing from the EPIC array, thus raising the question of whether EPIC data can be used to accurately estimate DNAm age. We also investigated a 71-CpG epigenetic age predictor, referred to as the Hannum method, which lacks 6 probes on the EPIC array. To evaluate these epigenetic clocks in EPIC data properly, a prior assessment of the effects of data preprocessing methods on DNAm age is also required.MethodsDNAm was quantified, on both the 450K and EPIC platforms, from human primary monocytes derived from 172 individuals. We calculated DNAm age from raw, and three different preprocessed data forms to assess the effects of different processing methods on the DNAm age estimate. Using an additional cohort, we also investigated DNAm age of peripheral blood mononuclear cells, bronchoalveolar lavage, and bronchial brushing samples using the EPIC array.ResultsUsing monocyte-derived data from subjects on both the 450K and EPIC, we found that DNAm age was highly correlated across both raw and preprocessing methods (r > 0.91). Thus, the correlation between chronological age and the DNAm age estimate is largely unaffected by platform differences and normalization methods. However, we found that the choice of normalization method and measurement platform can lead to a systematic offset in the age estimate which in turn leads to an increase in the median error. Comparing the 450K and EPIC DNAm age estimates, we observed that the median absolute difference was 1.44–3.10 years across preprocessing methods.ConclusionsHere, we have provided evidence that the epigenetic clock is resistant to the lack of 19 CpG sites missing from the EPIC array as well as highlighted the importance of considering the technical variance of the epigenetic when interpreting group differences below the reported error. Furthermore, our study highlights the utility of epigenetic age acceleration measure, the residuals from a linear regression of DNAm age on chronological age, as the resulting values are robust with respect to normalization methods and measurement platforms.Electronic supplementary materialThe online version of this article (10.1186/s13148-018-0556-2) contains supplementary material, which is available to authorized users.

Binding of glucocorticoid to the glucocorticoid receptor (GR/NR3C1) may repress inflammatory gene transcription via direct, protein synthesis-independent processes (transrepression), or by activating transcription (transactivation) of multiple anti-inflammatory/repressive factors. Using human pulmonary A549 cells, we showed that 34 out of 39 IL-1β-inducible mRNAs were repressed to varying degrees by the synthetic glucocorticoid, dexamethasone. Whilst these repressive effects were GR-dependent, they did not correlate with either the magnitude of IL-1β-inducibility or the NF-κB-dependence of the inflammatory genes. This suggests that induction by IL-1β and repression by dexamethasone are independent events. Roles for transactivation were investigated using the protein synthesis inhibitor, cycloheximide. However, cycloheximide reduced the IL-1β-dependent expression of 13 mRNAs, which, along with the 5 not showing repression by dexamethasone, were not analysed further. Of the remaining 21 inflammatory mRNAs, cycloheximide significantly attenuated the dexamethasone-dependent repression of 11 mRNAs that also showed a marked time-dependence to their repression. Such effects are consistent with repression occurring via the de novo synthesis of a new product, or products, which subsequently cause repression (i.e., repression via a transactivation mechanism). Conversely, 10 mRNAs showed completely cycloheximide-independent, and time-independent, repression by dexamethasone. This is consistent with direct GR transrepression. Importantly, the inflammatory mRNAs showing attenuated repression by dexamethasone in the presence of cycloheximide also showed a significantly greater extent of repression and a higher potency to dexamethasone compared to those mRNAs showing cycloheximide-independent repression. This suggests that the repression of inflammatory mRNAs by GR transactivation-dependent mechanisms accounts for the greatest levels of repression and the most potent repression by dexamethasone. In conclusion, our data indicate roles for both transrepression and transactivation in the glucocorticoid-dependent repression of inflammatory gene expression. However, transactivation appears to account for the more potent and efficacious mechanism of repression by glucocorticoids on these IL-1β-induced genes.

Although inhaled glucocorticoids, or corticosteroids (ICS), are generally effective in asthma, understanding their anti‐inflammatory actions in vivo remains incomplete. To characterize glucocorticoid‐induced modulation of gene expression in the human airways, we performed a randomized placebo‐controlled crossover study in healthy male volunteers. Six hours after placebo or budesonide inhalation, whole blood, bronchial brushings, and endobronchial biopsies were collected. Microarray analysis of biopsy RNA, using stringent (≥2‐fold, 5% false discovery rate) or less stringent (≥1.25‐fold, P ≤ 0.05) criteria, identified 46 and 588 budesonide‐induced genes, respectively. Approximately two third of these genes are transcriptional regulators (KLF9, PER1, TSC22D3, ZBTB16), receptors (CD163, CNR1, CXCR4, LIFR, TLR2), or signaling genes (DUSP1, NFKBIA, RGS1, RGS2, ZFP36). Listed genes were qPCR verified. Expression of anti‐inflammatory and other potentially beneficial genes is therefore confirmed and consistent with gene ontology (GO) terms for negative regulation of transcription and gene expression. However, GO terms for transcription, signaling, metabolism, proliferation, inflammatory responses, and cell movement were also associated with the budesonide‐induced genes. The most enriched functional cluster indicates positive regulation of proliferation, locomotion, movement, and migration. Moreover, comparison with the budesonide‐induced expression profile in primary human airway epithelial cells shows considerable cell type specificity. In conclusion, increased expression of multiple genes, including the transcriptional repressor, ZBTB16, that reduce inflammatory signaling and gene expression, occurs in the airways and blood and may contribute to the therapeutic efficacy of ICS. This provides a previously lacking insight into the in vivo effects of ICS and should promote strategies to improve glucocorticoid efficacy in inflammatory diseases.