AHRR methylation in heavy smokers: associations with smoking, lung cancer risk, and lung cancer mortality

DNA methylation at AHRR as a master predictor of smoke exposure and a biomarker for sleep and exercise

BACKGROUND

DNA methylation profiling may provide a more accurate measure of the smoking status than self-report and may be useful in guiding clinical interventions and forensic investigations. In the current study, blood DNA methylation profiles of nearly 800 Polish individuals were assayed using Illuminia EPIC and the inference of smoking from epigenetic data was explored. In addition, we focused on the role of the AHRR gene as a top marker for smoking and investigated its responsiveness to other lifestyle behaviors.

RESULTS

We found > 450 significant CpGs associated with cigarette consumption, and overrepresented in various biological functions including cell communication, response to stress, blood vessel development, cell death, and atherosclerosis. The model consisting of cg05575921 in AHRR (p = 4.5 × 10-32) and three additional CpGs (cg09594361, cg21322436 in CNTNAP2 and cg09842685) was able to predict smoking status with a high accuracy of AUC = 0.8 in the test set. Importantly, a gradual increase in the probability of smoking was observed, starting from occasional smokers to regular heavy smokers. Furthermore, former smokers displayed the intermediate DNA methylation profiles compared to current and never smokers, and thus our results indicate the potential reversibility of DNA methylation after smoking cessation. The AHRR played a key role in a predictive analysis, explaining 21.5% of the variation in smoking. In addition, the AHRR methylation was analyzed for association with other modifiable lifestyle factors, and showed significance for sleep and physical activity. We also showed that the epigenetic score for smoking was significantly correlated with most of the epigenetic clocks tested, except for two first-generation clocks.

CONCLUSIONS

Our study suggests that a more rapid return to never-smoker methylation levels after smoking cessation may be achievable in people who change their lifestyle in terms of physical activity and sleep duration. As cigarette smoking has been implicated in the literature as a leading cause of epigenetic aging and AHRR appears to be modifiable by multiple exogenous factors, it emerges as a promising target for intervention and investment.

Probabilistic inference of epigenetic age acceleration from cellular dynamics

The emergence of epigenetic predictors was a pivotal moment in geroscience, propelling the measurement and concept of biological aging into a quantitative era; however, while current epigenetic clocks show strong predictive power, they are data-driven in nature and are not based on the underlying biological mechanisms driving methylation dynamics. We show that predictions of these clocks are susceptible to several confounding non-age-related phenomena that make interpretation of these estimates and associations difficult. To address these limitations, we developed a probabilistic model describing methylation transitions at the cellular level. Our approach reveals two measurable components, acceleration and bias, which directly reflect perturbations of the underlying cellular dynamics. Acceleration is the proportional increase in the speed of methylation transitions across CpG sites, whereas bias corresponds to global changes in methylation levels. Using data from 15,900 participants from the Generation Scotland study, we develop a robust inference framework and show that these are two distinct processes confounding current epigenetic predictors. Our results show improved associations of acceleration and bias with physiological traits known to impact healthy aging, such as smoking and alcohol consumption, respectively. Furthermore, a genome-wide association study of epigenetic age acceleration identified seven genomic loci.

Epigenome-Wide Association Studies of Chronic Obstructive Pulmonary Disease and Lung Function: A Systematic Review

Rationale: Chronic obstructive pulmonary disease (COPD) results from gene-environment interactions over the lifetime. These interactions are captured by epigenetic changes, such as DNA methylation. Objectives: To systematically review the evidence form epigenome-wide association studies related to COPD and lung function. Methods: A systematic literature search performed on PubMed, Embase, and Cumulative Index to Nursing and Allied Health Literature (CINAHL) databases identified 1,947 articles that investigated epigenetic changes associated with COPD and/or lung function; 17 of them met our eligibility criteria, from which data were manually extracted. Differentially methylated positions (DMPs) and/or annotated genes were considered replicated if identified by two or more studies with a P < 1 × 10-4. Measurements and Main Results: Ten studies profiled DNA methylation changes in blood and seven in respiratory samples, including surgically resected lung tissue (n = 3), small airway epithelial brushings (n = 2), BAL (n = 1), and sputum (n = 1). Main results showed: 1) high variability in study design, covariates, and effect sizes, which prevented a formal meta-analysis; 2) in blood samples, 51 DMPs were replicated in relation to lung function and 12 related to COPD; 3) in respiratory samples, 42 DMPs were replicated in relation to COPD but none in relation to lung function; and 4) in COPD versus control studies, 123 genes (2.6% of total) were shared between one or more blood and one or more respiratory samples and associated with chronic inflammation, ion transport, and coagulation. Conclusions: There is high heterogeneity across published COPD and/or lung function epigenome-wide association studies. A few genes (n = 123; 2.6%) were replicated in blood and respiratory samples, suggesting that blood can recapitulate some changes in respiratory tissues. These findings have implications for future research. Systematic Review [protocol] registered with Open Science Framework (OSF).

Differential Impact of Smoking on Methylome and Transcriptome in Crohn's Disease and Ulcerative Colitis

BACKGROUND

Smoking is an environmental factor that differentially impacts Crohn's disease (CD) and ulcerative colitis (UC). The mechanism of impact of smoking on disease risk and clinical outcomes remains to be established.

METHODS

This study used a prospective cohort of patients with CD or UC. Self-reported smoking status was validated using serum cotinine measurement. We profiled methylation changes in peripheral blood using the Illumina Methylation BeadChip. Transcriptomic profiling was performed on ileal and colonic tissue using an Illumina TruSeq platform. We compared the methylation and transcriptional changes in current, former, and never smokers stratified by disease type.

RESULTS

Our cohort included 200 patients with CD or UC with methylation profiles and 160 with transcriptomic data. The mean serum cotinine level was higher in current compared with former or never smokers. Epigenetic changes common to both CD and UC included hypomethylation at AHRR. Smoking-associated MGAT3 hypomethylation was associated with severe disease course only in UC, while IER3 hypomethylation was associated with worse course only in CD. Smoking downregulated several inflammatory pathways in UC. Current smoking in CD but not in UC was associated with upregulation of several genes mediating Paneth cell function. Genes with opposite direction of effects in CD and UC include HSD3B2 and GSTA1.

CONCLUSIONS

Our findings suggest both common and differential effects of cigarette smoking on CD and UC. Paneth cell dysfunction may mediate adverse impact of smoking on CD. Bile acid and oxidative stress pathways may be relevant for the differential effect of smoking on CD and UC.

Expression of AhR-regulated miRNAs in non-small cell lung cancer in smokers and never smokers

Smoking is a risk factor for non-small cell lung cancer (NSCLC). The most common subtypes of NSCLC are lung adenocarcinoma (LAC) and squamous cell carcinoma (SCC). The cigarette smoke contains aryl hydrocarbon receptor (AhR) ligands, such as benzo(a)pyrene (BaP). By activating the AhR, BaP can change the expression of many genes, including miRNA-encoding genes. In this study, we have evaluated the expression of few miRNAs potentially regulated by AhR (miR-21, -342, -93, -181a, -146a), as well as CYP1A1, a known AhR target gene, in lung tumor samples from smoking (n=40) and non-smoking (n=30) patients with LAC and from smoking patients with SCC (n=40). We have also collected macroscopically normal lung tissue >5 cm from the tumor margin. We compared the obtained data on the miRNA expression in tumors with data from The Cancer Genome Atlas (TCGA). We found that in 76.7% of non-smoking LAC patients, CYP1A1 mRNA was not detected in tumor and normal lung tissues, while in smoking patients, CYP1A1 expression was detected in tumors in almost half of the cases (47.5% for SCC and 42.5% for LAC). The expression profile of AhR-regulated miRNAs differed between LAC and SCC and depended on the smoking status. In LAC patients, the expression of oncogenic miRNA-21 and miRNA-93 in tumors was higher than in normal lung tissue from the same patients. However, in SCC patients from our sample, the levels of these miRNAs in tumor and non-transformed lung tissue did not differ significantly. The results of our studies and TCGA data indicate that the expression levels of miRNA-181a and miRNA-146a in LAC are associated with smoking: expression of these miRNAs was significantly lower in tumors of smokers. It is possible that their expression is regulated by AhR and AhRR (AhR repressor), and inhibition of AhR by AhRR leads to a decrease in miRNA expression in tumors of smoking patients. Overall, these results confirm that smoking has an effect on the miRNA expression profile. This should be taken into account when searching for new diagnostic and therapeutic targets for NSCLC.

High-dimensional quantile mediation analysis with application to a birth cohort study of mother-newborn pairs

MOTIVATION

There has been substantial recent interest in developing methodology for high-dimensional mediation analysis. Yet, the majority of mediation statistical methods lean heavily on mean regression, which limits their ability to fully capture the complex mediating effects across the outcome distribution. To bridge this gap, we propose a novel approach for selecting and testing mediators throughout the full range of the outcome distribution spectrum.

RESULTS

The proposed high-dimensional quantile mediation model provides a comprehensive insight into how potential mediators impact outcomes via their mediation pathways. This method's efficacy is demonstrated through extensive simulations. The study presents a real-world data application examining the mediating effects of DNA methylation on the relationship between maternal smoking and offspring birthweight.

AVAILABILITY AND IMPLEMENTATION

Our method offers a publicly available and user-friendly function qHIMA(), which can be accessed through the R package HIMA at https://CRAN.R-project.org/package=HIMA.

Blood DNA methylation signature of diet quality and association with cardiometabolic traits

AIMS

Diet quality might influence cardiometabolic health through epigenetic changes, but this has been little investigated in adults. Our aims were to identify cytosine-phosphate-guanine (CpG) dinucleotides associated with diet quality by conducting an epigenome-wide association study (EWAS) based on blood DNA methylation (DNAm) and to assess how diet-related CpGs associate with inherited susceptibility to cardiometabolic traits: body mass index (BMI), systolic blood pressure (SBP), triglycerides, type 2 diabetes (T2D), and coronary heart disease (CHD).

METHODS AND RESULTS

Meta-EWAS including 5274 participants in four cohorts from Spain, the USA, and the UK. We derived three dietary scores (exposures) to measure adherence to a Mediterranean diet, to a healthy plant-based diet, and to the Dietary Approaches to Stop Hypertension. Blood DNAm (outcome) was assessed with the Infinium arrays Human Methylation 450K BeadChip and MethylationEPIC BeadChip. For each diet score, we performed linear EWAS adjusted for age, sex, blood cells, smoking and technical variables, and BMI in a second set of models. We also conducted Mendelian randomization analyses to assess the potential causal relationship between diet-related CpGs and cardiometabolic traits. We found 18 differentially methylated CpGs associated with dietary scores (P < 1.08 × 10-7; Bonferroni correction), of which 12 were previously associated with cardiometabolic traits. Enrichment analysis revealed overrepresentation of diet-associated genes in pathways involved in inflammation and cardiovascular disease. Mendelian randomization analyses suggested that genetically determined methylation levels corresponding to lower diet quality at cg02079413 (SNORA54), cg02107842 (MAST4), and cg23761815 (SLC29A3) were causally associated with higher BMI and at cg05399785 (WDR8) with greater SBP, and methylation levels associated with higher diet quality at cg00711496 (PRMT1) with lower BMI, T2D risk, and CHD risk and at cg0557921 (AHRR) with lower CHD risk.

CONCLUSION

Diet quality in adults was related to differential methylation in blood at 18 CpGs, some of which related to cardiometabolic health.

The complex biology of aryl hydrocarbon receptor activation in cancer and beyond

The aryl hydrocarbon receptor (AHR) signaling pathway is a complex regulatory network that plays a critical role in various biological processes, including cellular metabolism, development, and immune responses. The complexity of AHR signaling arises from multiple factors, including the diverse ligands that activate the receptor, the expression level of AHR itself, and its interaction with the AHR nuclear translocator (ARNT). Additionally, the AHR crosstalks with the AHR repressor (AHRR) or other transcription factors and signaling pathways and it can also mediate non-genomic effects. Finally, posttranslational modifications of the AHR and its interaction partners, epigenetic regulation of AHR and its target genes, as well as AHR-mediated induction of enzymes that degrade AHR-activating ligands may contribute to the context-specificity of AHR activation. Understanding the complexity of AHR signaling is crucial for deciphering its physiological and pathological roles and developing therapeutic strategies targeting this pathway. Ongoing research continues to unravel the intricacies of AHR signaling, shedding light on the regulatory mechanisms controlling its diverse functions.

Blood Leukocyte AHRR Methylation and Risk of Non-smoking-associated Cancer: A Case-cohort Study of Non-Hodgkin Lymphoma

Aryl-hydrocarbon receptor repressor (AHRR) hypomethylation in peripheral blood is tightly linked with tobacco smoking and lung cancer. Here, we investigated AHRR methylation in non-Hodgkin lymphoma (NHL), a non-smoking-associated cancer. In a case-cohort study within the population-based Danish Diet, Cancer and Health cohort, we measured AHRR (cg23576855) methylation in prediagnostic blood from 161 participants who developed NHL within 13.4 years of follow-up (median: 8.5 years), with a comparison group of 164 randomly chosen participants. We measured DNA-methylation levels using bisulfite pyrosequencing and estimated incidence rate ratios (IRR) using Cox proportional hazards models with adjustment for baseline age, sex, educational level, smoking status, body mass index, alcohol intake, physical activity, and diet score. Global DNA-methylation levels were assessed by long interspersed nucleotide element 1 (LINE-1) analysis. Overall, the IRR for AHRR hypomethylation (lowest vs. other quartiles) was 2.52 [95% confidence interval (CI), 1.24-5.15]. When stratified according to time between blood draw and diagnosis, low AHRR methylation levels were associated with a future diagnosis of NHL [IRR: 4.50 (95% CI, 1.62-12.50) at 0-<5 years, 7.04 (95% CI, 2.36-21.02) at 5-<10 years, and 0.56 (95% CI, 0.21-1.45) at ≥10 years]. There was no association between global DNA-methylation levels and risk of NHL. Our results show that AHRR hypomethylation in blood leukocytes is associated with a higher risk of NHL in a time-dependent manner, suggesting that it occurs as a response to tumor development.

Significance

Our population-based study demonstrated that lower AHRR methylation levels in peripheral blood leukocytes were associated with an increased risk of NHL. This association was independent of tobacco smoking, sex, and lifestyle characteristics, but was highly dependent on time to diagnosis. These findings highlight the potential of AHRR methylation as a biomarker for NHL risk, effective up to 10 years after blood draw.

Polymorphisms in Glutathione S-Transferase (GST) Genes Modify the Effect of Exposure to Maternal Smoking Metabolites in Pregnancy and Offspring DNA Methylation

Maternal smoking in pregnancy (MSP) affects the offspring's DNA methylation (DNAm). There is a lack of knowledge regarding individual differences in susceptibility to exposure to MSP. Glutathione S-transferase (GST) genes are involved in protection against harmful oxidants such as those found in cigarette smoke. This study aimed to test whether polymorphisms in GST genes influence the effect of MSP on offspring DNAm. Using data from the Isle of Wight birth cohort, we assessed the association of MSP and offspring DNAm in 493 mother-child dyads (251 male, 242 female) with the effect-modifying role of GST gene polymorphism (at rs506008, rs574344, rs12736389, rs3768490, rs1537234, and rs1695). MSP was assessed by levels of nicotine and its downstream metabolites (cotinine, norcotinine, and hydroxycotinine) in maternal sera. In males, associations of hydroxycotinine with DNAm at cg18473733, cg25949550, cg11647108, and cg01952185 and norcotinine with DNAm at cg09935388 were modified by GST gene polymorphisms (p-values < 0.05). In females, associations of hydroxycotinine with DNAm at cg12160087 and norcotinine with DNAm at cg18473733 were modified by GST gene polymorphisms (p-values < 0.05). Our study emphasizes the role of genetic polymorphism in GST genes in DNAm's susceptibility to MSP.

Deciphering the roles of aryl hydrocarbon receptor (AHR) in regulating carcinogenesis

Aryl hydrocarbon receptor (AHR) is a ligand-dependent receptor that belongs to the superfamily of basic helix-loop-helix (bHLH) transcription factors. The activation of the canonical AHR signaling pathway is known to induce the expression of cytochrome P450 enzymes, facilitating the detoxification metabolism in the human body. Additionally, AHR could interact with various signaling pathways such as epidermal growth factor receptor (EGFR), signal transducer and activator of transcription 3 (STAT3), hypoxia-inducible factor-1α (HIF-1α), nuclear factor ekappa B (NF-κβ), estrogen receptor (ER), and androgen receptor (AR) signaling pathways. Over the past 30 years, several studies have reported that various chemical, physical, or biological agents, such as tobacco, hydrocarbon compounds, industrial and agricultural chemical wastes, drugs, UV, viruses, and other toxins, could affect AHR expression or activity, promoting cancer development. Thus, it is valuable to overview how these factors regulate AHR-mediated carcinogenesis. Current findings have reported that many compounds could act as AHR ligands to drive the expressions of AHR-target genes, such as CYP1A1, CYP1B1, MMPs, and AXL, and other targets that exert a pro-proliferation or anti-apoptotic effect, like XIAP. Furthermore, some other physical and chemical agents, such as UV and 3-methylcholanthrene, could promote AHR signaling activities, increasing the signaling activities of a few oncogenic pathways, such as the phosphatidylinositol 3-kinase/protein kinase B (PI3K/AKT) and mitogen-activated protein kinase/extracellular signal-regulated kinase (MAPK/ERK) pathways. Understanding how various factors regulate AHR-mediated carcinogenesis processes helps clinicians and scientists plan personalized therapeutic strategies to improve anti-cancer treatment efficacy. As many studies that have reported the roles of AHR in regulating carcinogenesis are preclinical or observational clinical studies that did not explore the detailed mechanisms of how different chemical, physical, or biological agents promote AHR-mediated carcinogenesis processes, future studies should focus on conducting large-scale and functional studies to unravel the underlying mechanism of how AHR interacts with different factors in regulating carcinogenesis processes.

Changing Smoking Behavior and Epigenetics: A Longitudinal Study of 4,432 Individuals From the General Population

BACKGROUND

Hypomethylation of the aryl hydrocarbon receptor repressor (AHRR) gene indicates long-term smoking exposure and might therefore be a monitor for smoking-induced disease risk. However, studies of individual longitudinal changes in AHRR methylation are sparse.

RESEARCH QUESTION

How does the recovery of AHRR methylation depend on change in smoking behaviors and demographic variables?

STUDY DESIGN AND METHODS

This study included 4,432 individuals from the Copenhagen City Heart Study, with baseline and follow-up blood samples and smoking information collected approximately 10 years apart. AHRR methylation at the cg05575921 site was measured in bisulfite-treated leukocyte DNA. Four smoking groups were defined: participants who never smoked (Never-Never), participants who formerly smoked (Former-Former), participants who quit during the study period (Current-Former), and individuals who smoked at both baseline and follow-up (Current-Current). Methylation recovery was defined as the increase in AHRR methylation between baseline and follow-up examination.

RESULTS

Methylation recovery was highest among participants who quit, with a median methylation recovery of 5.58% (interquartile range, 1.79; 9.15) vs 1.64% (interquartile range, -1.88; 4.96) in the Current-Current group (P < .0001). In individuals who quit smoking, older age was associated with lower methylation recovery (P < .0001). In participants who quit aged > 65 years, methylation recovery was 5.9% at 5.6 years after quitting; methylation recovery was 8.5% after 2.8 years for participants who quit aged < 55 years.

INTERPRETATION

AHRR methylation recovered after individuals quit smoking, and recovery was more pronounced and occurred faster in younger compared with older interim quitters.

Targeted DNA methylation analysis and prediction of smoking habits in blood based on massively parallel sequencing

Tobacco smoking is a frequent habit sustained by > 1.3 billion people in 2020 and the leading preventable factor for health risk and premature mortality worldwide. In the forensic context, predicting smoking habits from biological samples may allow broadening DNA phenotyping. In this study, we aimed to implement previously published smoking habit classification models based on blood DNA methylation at 13 CpGs. First, we developed a matching lab tool based on bisulfite conversion and multiplex PCR followed by amplification-free library preparation and targeted paired-end massively parallel sequencing (MPS). Analysis of six technical duplicates revealed high reproducibility of methylation measurements (Pearson correlation of 0.983). Artificially methylated standards uncovered marker-specific amplification bias, which we corrected via bi-exponential models. We then applied our MPS tool to 232 blood samples from Europeans of a wide age range, of which 90 were current, 71 former and 71 never smokers. On average, we obtained 189,000 reads/sample and 15,000 reads/CpG, without marker drop-out. Methylation distributions per smoking category roughly corresponded to previous microarray analysis, showcasing large inter-individual variation but with technology-driven bias. Methylation at 11 out of 13 smoking-CpGs correlated with daily cigarettes in current smokers, while solely one was weakly correlated with time since cessation in former smokers. Interestingly, eight smoking-CpGs correlated with age, and one displayed weak but significant sex-associated methylation differences. Using bias-uncorrected MPS data, smoking habits were relatively accurately predicted using both two- (current/non-current) and three- (never/former/current) category model, but bias correction resulted in worse prediction performance for both models. Finally, to account for technology-driven variation, we built new, joint models with inter-technology corrections, which resulted in improved prediction results for both models, with or without PCR bias correction (e.g. MPS cross-validation F₁-score > 0.8; 2-categories). Overall, our novel assay takes us one step closer towards the forensic application of viable smoking habit prediction from blood traces. However, future research is needed towards forensically validating the assay, especially in terms of sensitivity. We also need to further shed light on the employed biomarkers, particularly on the mechanistics, tissue specificity and putative confounders of smoking epigenetic signatures.

The complexity in DNA methylation analysis of allergic diseases

PURPOSE OF REVIEW

This review aims to report all the recent studies that are implicated in DNA methylation analysis in the field of allergy and to underline the complexity of the study methodologies and results.

RECENT FINDINGS

Although the growing number of DNA methylation studies have yet to point to a specific mechanism, herein we provide an overview of the majority of pathways considered to be implicated and highlight particular genes, like KNH2 , ATPAF2 and ZNF385A , for their potential as biomarkers.

SUMMARY

The epigenetic profile of respiratory allergic diseases, and particularly DNA methylation, has been investigated in various populations, so as to gain a better understanding of its role in pathogenesis. Through our analysis, multiple links are presented between differential DNA methylation loci and IgE sensitization, lung functionality and severity of the disease. Additionally, associations of this epigenetic change with maternal asthma, age, sex and environmental factors are described, thus uncovering specific gene families that, after further examination could be used as methylation biomarkers in cases of allergic disease.

A generalization of moderated statistics to data adaptive semiparametric estimation in high-dimensional biology

The widespread availability of high-dimensional biological data has made the simultaneous screening of many biological characteristics a central problem in computational and high-dimensional biology. As the dimensionality of datasets continues to grow, so too does the complexity of identifying biomarkers linked to exposure patterns. The statistical analysis of such data often relies upon parametric modeling assumptions motivated by convenience, inviting opportunities for model misspecification. While estimation frameworks incorporating flexible, data adaptive regression strategies can mitigate this, their standard variance estimators are often unstable in high-dimensional settings, resulting in inflated Type-I error even after standard multiple testing corrections. We adapt a shrinkage approach compatible with parametric modeling strategies to semiparametric variance estimators of a family of efficient, asymptotically linear estimators of causal effects, defined by counterfactual exposure contrasts. Augmenting the inferential stability of these estimators in high-dimensional settings yields a data adaptive approach for robustly uncovering stable causal associations, even when sample sizes are limited. Our generalized variance estimator is evaluated against appropriate alternatives in numerical experiments, and an open source R/Bioconductor package, biotmle, is introduced. The proposal is demonstrated in an analysis of high-dimensional DNA methylation data from an observational study on the epigenetic effects of tobacco smoking.

DNA-Methylation Signatures of Tobacco Smoking in a High Cardiovascular Risk Population: Modulation by the Mediterranean Diet

Biomarkers based on DNA methylation are relevant in the field of environmental health for precision health. Although tobacco smoking is one of the factors with a strong and consistent impact on DNA methylation, there are very few studies analyzing its methylation signature in southern European populations and none examining its modulation by the Mediterranean diet at the epigenome-wide level. We examined blood methylation smoking signatures on the EPIC 850 K array in this population (n = 414 high cardiovascular risk subjects). Epigenome-wide methylation studies (EWASs) were performed analyzing differential methylation CpG sites by smoking status (never, former, and current smokers) and the modulation by adherence to a Mediterranean diet score was explored. Gene-set enrichment analysis was performed for biological and functional interpretation. The predictive value of the top differentially methylated CpGs was analyzed using receiver operative curves. We characterized the DNA methylation signature of smoking in this Mediterranean population by identifying 46 differentially methylated CpGs at the EWAS level in the whole population. The strongest association was observed at the cg21566642 (p = 2.2 × 10-32) in the 2q37.1 region. We also detected other CpGs that have been consistently reported in prior research and discovered some novel differentially methylated CpG sites in subgroup analyses. In addition, we found distinct methylation profiles based on the adherence to the Mediterranean diet. Particularly, we obtained a significant interaction between smoking and diet modulating the cg5575921 methylation in the AHRR gene. In conclusion, we have characterized biomarkers of the methylation signature of tobacco smoking in this population, and suggest that the Mediterranean diet can increase methylation of certain hypomethylated sites.

The role of the oral microbiome in smoking-related cardiovascular risk: a review of the literature exploring mechanisms and pathways

Cardiovascular disease is a leading cause of morbidity and mortality. Oral health is associated with smoking and cardiovascular outcomes, but there are gaps in knowledge of many mechanisms connecting smoking to cardiovascular risk. Therefore, the aim of this review is to synthesize literature on smoking and the oral microbiome, and smoking and cardiovascular risk/disease, respectively. A secondary aim is to identify common associations between the oral microbiome and cardiovascular risk/disease to smoking, respectively, to identify potential shared oral microbiome-associated mechanisms. We identified several oral bacteria across varying studies that were associated with smoking. Atopobium, Gemella, Megasphaera, Mycoplasma, Porphyromonas, Prevotella, Rothia, Treponema, and Veillonella were increased, while Bergeyella, Haemophilus, Lautropia, and Neisseria were decreased in the oral microbiome of smokers versus non-smokers. Several bacteria that were increased in the oral microbiome of smokers were also positively associated with cardiovascular outcomes including Porphyromonas, Prevotella, Treponema, and Veillonella. We review possible mechanisms that may link the oral microbiome to smoking and cardiovascular risk including inflammation, modulation of amino acids and lipids, and nitric oxide modulation. Our hope is this review will inform future research targeting the microbiome and smoking-related cardiovascular disease so possible microbial targets for cardiovascular risk reduction can be identified.

TNF-α and NF-κB signaling play a critical role in cigarette smoke-induced epithelial-mesenchymal transition of retinal pigment epithelial cells in proliferative vitreoretinopathy

Proliferative vitreoretinopathy (PVR) is characterized by the growth and contraction of cellular membranes within the vitreous cavity and on both surfaces of the retina, resulting in recurrent retinal detachments and poor visual outcomes. Proinflammatory cytokines like tumor necrosis factor alpha (TNFα) have been associated with PVR and the epithelial-mesenchymal transition (EMT) of retinal pigment epithelial (RPE) cells. Cigarette smoke is the only known modifiable risk factor for PVR, but the mechanisms are unclear. The purpose of this study was to examine the impact of cigarette smoke on the proinflammatory TNFα/NF-κB/Snail pathway in RPE cells to better understand the mechanisms through which cigarette smoke increases the risk of PVR. Human ARPE-19 cells were exposed to cigarette smoke extract (CSE), for 4 to 24-hours and TNFα, Snail, IL-6, IL-8, and α-SMA levels were analyzed by qPCR and/or Western blot. The severity of PVR formation was assessed in a murine model of PVR after intravitreal injection of ARPE-19 cells pre-treated with CSE or not. Fundus imaging, OCT imaging, and histologic analysis 4 weeks after injection were used to examine PVR severity. ARPE-19 cells exposed to CSE expressed higher levels of TNFα, SNAIL, IL6 and IL8 mRNA as well as SNAIL, Vimentin and α-SMA protein. Inhibition of TNFα and NF-κB pathways blocked the effect of CSE. In vivo, intravitreal injection of ARPE-19 cells treated with CSE resulted in more severe PVR compared to mice injected with untreated RPE cells. These studies suggest that the TNFα pathway is involved in the mechanism whereby cigarette smoke increases PVR. Further investigation into the role of TNFα/NF-κB/Snail in driving PVR and pharmacological targeting of these pathways in disease are warranted.

Multidimensional Mutational Profiling of the Indian HNSCC Sub-Population Provides IRAK1, a Novel Driver Gene and Potential Druggable Target

Head and neck squamous cell carcinomas (HNSCC) include heterogeneous group of tumors, classified according to their anatomical site. It is the sixth most prevalent cancer globally. Among South Asian countries, India accounts for 40% of HNC malignancies with significant morbidity and mortality. In the present study, we have performed exome sequencing and analysis of 51 Head and Neck squamous cell carcinoma samples. Besides known mutations in the oncogenes and tumour suppressors, we have identified novel gene signatures differentiating buccal, alveolar, and tongue cancers. Around 50% of the patients showed mutation in tumour suppressor genes TP53 and TP63. Apart from the known mutations, we report novel mutations in the genes AKT1, SPECC1, and LRP1B, which are linked with tumour progression and patient survival. A highly curated process was developed to identify survival signatures. 36 survival-related genes were identified based on the correlation of functional impact of variants identified using exome-seq with gene expression from transcriptome data (GEPIA database) and survival. An independent LASSO regression analysis was also performed. Survival signatures common to both the methods led to identification of 4 dead and 3 alive gene signatures, the accuracy of which was confirmed by performing a ROC analysis (AUC=0.79 and 0.91, respectively). Also, machine learning-based driver gene prediction tool resulted in the identification of IRAK1 as the driver (p-value = 9.7 e-08) and also as an actionable mutation. Modelling of the IRAK1 mutation showed a decrease in its binding to known IRAK1 inhibitors.

Epigenetic modelling of former, current and never smokers

BACKGROUND

DNA methylation (DNAm) performs excellently in the discrimination of current and former smokers from never smokers, where AUCs > 0.9 are regularly reported using a single CpG site (cg05575921; AHRR). However, there is a paucity of DNAm models which attempt to distinguish current, former and never smokers as individual classes. Derivation of a robust DNAm model that accurately distinguishes between current, former and never smokers would be particularly valuable to epidemiological research (as a more accurate smoking definition vs. self-report) and could potentially translate to clinical settings. Therefore, we appraise 4 DNAm models of ternary smoking status (that is, current, former and never smokers): methylation at cg05575921 (AHRR model), weighted scores from 13 CpGs created by Maas et al. (Maas model), weighted scores from a LASSO model of candidate smoking CpGs from the literature (candidate CpG LASSO model), and weighted scores from a LASSO model supplied with genome-wide 450K data (agnostic LASSO model). Discrimination is assessed by AUC, whilst classification accuracy is assessed by accuracy and kappa, derived from confusion matrices.

RESULTS

We find that DNAm can classify ternary smoking status with reasonable accuracy, including when applied to external data. Ternary classification using only DNAm far exceeds the classification accuracy of simply assigning all classes as the most prevalent class (63.7% vs. 36.4%). Further, we develop a DNAm classifier which performs well in discriminating current from former smokers (agnostic LASSO model AUC in external validation data: 0.744). Finally, across our DNAm models, we show evidence of enrichment for biological pathways and human phenotype ontologies relevant to smoking, such as haemostasis, molybdenum cofactor synthesis, body fatness and social behaviours, providing evidence of the generalisability of our classifiers.

CONCLUSIONS

Our findings suggest that DNAm can classify ternary smoking status with close to 65% accuracy. Both the ternary smoking status classifiers and current versus former smoking status classifiers address the present lack of former smoker classification in epigenetic literature; essential if DNAm classifiers are to adequately relate to real-world populations. To improve performance further, additional focus on improving discrimination of current from former smokers is necessary.

Disease-related blood-based differential methylation in cystic fibrosis and its representation in lung cancer revealed a regulatory locus in PKP3 in lung epithelial cells

Cystic fibrosis (CF) is a monogenic disease, characterized by massive chronic lung inflammation. The observed variability in clinical phenotypes in monozygotic CF twins is likely associated with the extent of inflammation. This study sought to investigate inflammation-related aberrant DNA methylation in CF twins and to determine to what extent acquired methylation changes may be associated with lung cancer.

Blood-based genome-wide DNA methylation analysis was performed to compare the DNA methylomes of monozygotic twins, from the European CF Twin and Sibling Study with various degrees of disease severity. Putatively inflammation-related and differentially methylated positions were selected from a large lung cancer case-control study and investigated in blood by targeted bisulphite next-generation-sequencing. An inflammation-related locus located in the Plakophilin-3 (PKP3) gene was functionally analysed regarding promoter and enhancer activity in presence and absence of methylation using luciferase reporter assays.

We confirmed in a unique cohort that monozygotic twins, even if clinically discordant, have only minor differences in global DNA methylation patterns and blood cell composition. Further, we determined the most differentially methylated positions, a high proportion of which are blood cell-type-specific, whereas others may be acquired and thus have potential relevance in the context of inflammation as lung cancer risk factors. We identified a sequence in the gene body of PKP3 which is hypermethylated in blood from CF twins with severe phenotype and highly variably methylated in lung cancer patients and controls, independent of known clinical parameters, and showed that this region exhibits methylation-dependent promoter activity in lung epithelial cells.

A cross-tissue transcriptome-wide association study identifies novel susceptibility genes for lung cancer in Chinese populations

Although dozens of susceptibility loci have been identified for lung cancer in genome-wide association studies (GWASs), the susceptibility genes and underlying mechanisms remain unclear. In this study, we conducted a cross-tissue transcriptome-wide association study (TWAS) with UTMOST based on summary statistics from 13 327 lung cancer cases and 13 328 controls and the genetic-expression matrix over 44 human tissues in the Genotype-Tissue Expression (GTEx) project. After further evaluating the associations in each tissue, we revealed 6 susceptibility genes in known loci and identified 12 novel ones. Among those, five novel genes, including DCAF16 (Pcross-tissue = 2.57 × 10-5, PLung = 2.89 × 10-5), CBL (Pcross-tissue = 5.08 × 10-7, PLung = 1.82 × 10-4), ATR (Pcross-tissue = 1.45 × 10-5, PLung = 9.68 × 10-5), GYPE (Pcross-tissue = 1.45 × 10-5, PLung = 2.17 × 10-3) and PARD3 (Pcross-tissue = 5.79 × 10-6, PLung = 4.05 × 10-3), were significantly associated with the risk of lung cancer in both cross-tissue and lung tissue models. Further colocalization analysis indicated that rs7667864 (C > A) and rs2298650 (G > T) drove the GWAS association signals at 4p15.31-32 (OR = 1.09, 95%CI: 1.04-1.12, PGWAS = 5.54 × 10-5) and 11q23.3 (OR = 1.08, 95%CI: 1.04-1.13, PGWAS = 5.55 × 10-5), as well as the expression of DCAF16 (βGTEx = 0.24, PGTEx = 9.81 × 10-15; βNJLCC = 0.29, PNJLCC = 3.84 × 10-8) and CBL (βGTEx = -0.17, PGTEx = 2.82 × 10-8; βNJLCC = -0.32, PNJLCC = 2.61 × 10-7) in lung tissue. Functional annotations and phenotype assays supported the carcinogenic effect of these novel susceptibility genes in lung carcinogenesis.

POU2F2 promotes the proliferation and motility of lung cancer cells by activating AGO1

Background

To detect and investigate the expression of POU domain class 2 transcription factor 2 (POU2F2) in human lung cancer tissues, its role in lung cancer progression, and the potential mechanisms.

Methods

Immunohistochemical (IHC) assays were conducted to assess the expression of POU2F2 in human lung cancer tissues. Immunoblot assays were performed to assess the expression levels of POU2F2 in human lung cancer tissues and cell lines. CCK-8, colony formation, and transwell-migration/invasion assays were conducted to detect the effects of POU2F2 and AGO1 on the proliferaion and motility of A549 and H1299 cells in vitro. CHIP and luciferase assays were performed for the mechanism study. A tumor xenotransplantation model was used to detect the effects of POU2F2 on tumor growth in vivo.

Results

We found POU2F2 was highly expressed in human lung cancer tissues and cell lines, and associated with the lung cancer patients’ prognosis and clinical features. POU2F2 promoted the proliferation, and motility of lung cancer cells via targeting AGO1 in vitro. Additionally, POU2F2 promoted tumor growth of lung cancer cells via AGO1 in vivo.

Conclusion

We found POU2F2 was highly expressed in lung cancer cells and confirmed the involvement of POU2F2 in lung cancer progression, and thought POU2F2 could act as a potential therapeutic target for lung cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-021-01476-9.