Transcriptomic epidemiology of smoking: the effect of smoking on gene expression in lymphocytes

Novel epigenetic changes unveiled by monozygotic twins discordant for smoking habits

Exposure to cigarette smoking affects the epigenome and could increase the risk of developing diseases such as cancer and cardiovascular disorders. Changes in DNA methylation associated with smoking may help to identify molecular pathways that contribute to disease etiology. Previous studies are not completely concordant in the identification of differentially methylated regions in the DNA of smokers. We performed an epigenome-wide DNA methylation study in a group of monozygotic (MZ) twins discordant for smoking habits to determine the effect of smoking on DNA methylation. As MZ twins are considered genetically identical, this model allowed us to identify smoking-related DNA methylation changes independent from genetic components. We investigated the whole blood genome-wide DNA methylation profiles in 20 MZ twin pairs discordant for smoking habits by using the Illumina HumanMethylation450 BeadChip. We identified 22 CpG sites that were differentially methylated between smoker and non-smoker MZ twins by intra-pair analysis. We confirmed eight loci already described by other groups, located in AHRR, F2RL3, MYOG1 genes, at 2q37.1 and 6p21.33 regions, and also identified several new loci. Moreover, pathway analysis showed an enrichment of genes involved in GTPase regulatory activity. Our study confirmed the evidence of smoking-related DNA methylation changes, emphasizing that well-designed MZ twin models can aid the discovery of novel DNA methylation signals, even in a limited sample population.

Dynamics of smoking-induced genome-wide methylation changes with time since smoking cessation

Several studies have recently identified strong epigenetic signals related to tobacco smoking. However, an aspect that did not receive much attention is the evolution of epigenetic changes with time since smoking cessation. We conducted a series of epigenome-wide association studies to capture the dynamics of smoking-induced epigenetic changes after smoking cessation, using genome-wide methylation profiles obtained from blood samples in 745 women from 2 European populations. Two distinct classes of CpG sites were identified: sites whose methylation reverts to levels typical of never smokers within decades after smoking cessation, and sites remaining differentially methylated, even more than 35 years after smoking cessation. Our results suggest that the dynamics of methylation changes following smoking cessation are driven by a differential and site-specific magnitude of the smoking-induced alterations (with persistent sites being most affected) irrespective of the intensity and duration of smoking. Analyses of the link between methylation and expression levels revealed that methylation predominantly and remotely down-regulates gene expression. Among genes whose expression was associated with our candidate CpG sites, LRRN3 appeared to be particularly interesting as it was one of the few genes whose methylation and expression were directly associated, and the only gene in which both methylation and gene expression were found associated with smoking. Our study highlights persistent epigenetic markers of smoking, which can potentially be detected decades after cessation. Such historical signatures are promising biomarkers to refine individual risk profiling of smoking-induced chronic disease such as lung cancer.

Tobacco smoking-response genes in blood and buccal cells

Tobacco smoking is a well-known cause of various diseases, however, its toxic mechanisms for diseases are not completely understood, yet. Therefore, we performed biological monitoring to find tobacco smoking-responsive mechanisms including oxidative stress in Korean men (N=36). Whole genome microarray analyses were performed with peripheral blood from smokers and age-matched nonsmokers. We also performed qRT-PCR to confirm the microarray results and compared the gene expression of blood to those of buccal cells. To assess the effects of tobacco smoking on oxidative stress, we analyzed urinary levels of malondialdehyde (MDA), a lipid peroxidation marker, and performed PCR-based arrays on reactive oxygen species (ROS)-related genes. As results, 34 genes were differently expressed in blood between smokers and nonsmokers (ps<0.01 and >1.5-fold change). Particularly, the genes involved in immune responsive pathways, e.g., the Fcγ-receptor mediated phagocytosis and the leukocyte transendothelial migration pathways, were differentially expressed between smokers and nonsmokers. Among the above genes, the ACTG1, involved in the maintenance of actin cytoskeleton, cell migration and cancer metastasis, was highly expressed by smoking in both blood and buccal cells. Concerning oxidative stress, smokers showed high levels of urinary MDA and down-regulation of expressions of antioxidant related genes including TPO, MPO, GPX2, PTGR1, and NUDT1 as compared to nonsmokers (ps<0.05). In conclusion, these results suggest that systemically altered immune response and oxidative stress can be tobacco-responsive mechanisms for the related diseases. Based on consistent results in blood and buccal cells, expression of the ACTG1 can be a tobacco smoking-responsive biomarker.

CpG sites associated with cigarette smoking: analysis of epigenome-wide data from the Sister Study

BACKGROUND

Smoking increases the risk of many diseases, and it is also linked to blood DNA methylation changes that may be important in disease etiology.

OBJECTIVES

We sought to identify novel CpG sites associated with cigarette smoking.

METHODS

We used two epigenome-wide data sets from the Sister Study to identify and confirm CpG sites associated with smoking. One included 908 women with methylation measurements at 27,578 CpG sites using the HumanMethylation27 BeadChip; the other included 200 women with methylation measurements for 473,844 CpG sites using the HumanMethylation450 BeadChip. Significant CpGs from the second data set that were not included in the 27K assay were validated by pyrosequencing in a subset of 476 samples from the first data set.

RESULTS

Our study successfully confirmed smoking associations for 9 previously established CpGs and identified 2 potentially novel CpGs: cg26764244 in GNG12 (p = 9.0 × 10-10) and cg22335340 in PTPN6 (p = 2.9 × 10-05). We also found strong evidence of an association between smoking status and cg02657160 in CPOX (p = 7.3 × 10-7), which has not been previously reported. All 12 CpGs were undermethylated in current smokers and showed an increasing percentage of methylation in former and never-smokers.

CONCLUSIONS

We identified 2 potentially novel smoking related CpG sites, and provided independent replication of 10 previously reported CpGs sites related to smoking, one of which is situated in the gene CPOX. The corresponding enzyme is involved in heme biosynthesis, and smoking is known to increase heme production. Our study extends the evidence base for smoking-related changes in DNA methylation.

Tobacco smoking increases immune activation and impairs T-cell function in HIV infected patients on antiretrovirals: a cross-sectional pilot study

Background

The influence of tobacco smoking on the immune system of HIV infected individuals is largely unknown. We investigated the impact of tobacco smoking on immune activation, microbial translocation, immune exhaustion and T-cell function in HIV infected individuals.

Method

HIV infected smokers and non-smokers (n = 25 each) with documented viral suppression on combination antiretroviral therapy and HIV uninfected smokers and non-smokers (n = 15 each) were enrolled. Markers of immune activation (CD38 and HLA-DR) and immune exhaustion (PD1, Tim3 and CTLA4) were analyzed in peripheral blood mononuclear cells (PBMCs) by flow cytometry. Plasma markers of microbial translocation (soluble-CD14 - sCD14 and lipopolysaccharide - LPS) were measured. Antigen specific functions of CD4+ and CD8+ T-cells were measured, by flow cytometry, in PBMCs after 6 hours stimulation with Cytomegalovirus, Epstein-Barr virus and Influenza Virus (CEF) peptide pool.

Results

Compared to non-smokers, smokers of HIV infected and uninfected groups showed significantly higher CD4+ and CD8+ T-cell activation with increased frequencies of CD38+HLA-DR+ cells with a higher magnitude in HIV infected smokers. Expressions of immune exhaustion markers (PD1, Tim3 and CTLA4) either alone or in combinations were significantly higher in smokers, especially on CD4+ T-cells. Compared to HIV uninfected non-smokers, microbial translocation (sCD14 and LPS) was higher in smokers of both groups and directly correlated with CD4+ and CD8+ T-cell activation. Antigen specific T-cell function showed significantly lower cytokine response of CD4+ and CD8+ T-cells to CEF peptide-pool stimulation in smokers of both HIV infected and uninfected groups.

Conclusions

Our results suggest that smoking and HIV infection independently influence T-cell immune activation and function and together they present the worst immune profile. Since smoking is widespread among HIV infected individuals, studies are warranted to further evaluate the cumulative effect of smoking on impairment of the immune system and accelerated disease progression.

Differential Effect of Active Smoking on Gene Expression in Male and Female Smokers

Smoking is the second leading cause of preventable death in the United States. Cohort epidemiological studies have demonstrated that women are more vulnerable to cigarette-smoking induced diseases than their male counterparts, however, the molecular basis of these differences has remained unknown. In this study, we explored if there were differences in the gene expression patterns between male and female smokers, and how these patterns might reflect different sex-specific responses to the stress of smoking. Using whole genome microarray gene expression profiling, we found that a substantial number of oxidant related genes were expressed in both male and female smokers, however, smoking-responsive genes did indeed differ greatly between male and female smokers. Gene set enrichment analysis (GSEA) against reference oncogenic signature gene sets identified a large number of oncogenic pathway gene-sets that were significantly altered in female smokers compared to male smokers. In addition, functional annotation with Ingenuity Pathway Analysis (IPA) identified smoking-correlated genes associated with biological functions in male and female smokers that are directly relevant to well-known smoking related pathologies. However, these relevant biological functions were strikingly overrepresented in female smokers compared to male smokers. IPA network analysis with the functional categories of immune and inflammatory response gene products suggested potential interactions between smoking response and female hormones. Our results demonstrate a striking dichotomy between male and female gene expression responses to smoking. This is the first genome-wide expression study to compare the sex-specific impacts of smoking at a molecular level and suggests a novel potential connection between sex hormone signaling and smoking-induced diseases in female smokers.

Protein-protein interaction networks (PPI) and complex diseases

The physical interaction of proteins which lead to compiling them into large densely connected networks is a noticeable subject to investigation. Protein interaction networks are useful because of making basic scientific abstraction and improving biological and biomedical applications. Based on principle roles of proteins in biological function, their interactions determine molecular and cellular mechanisms, which control healthy and diseased states in organisms. Therefore, such networks facilitate the understanding of pathogenic (and physiologic) mechanisms that trigger the onset and progression of diseases. Consequently, this knowledge can be translated into effective diagnostic and therapeutic strategies. Furthermore, the results of several studies have proved that the structure and dynamics of protein networks are disturbed in complex diseases such as cancer and autoimmune disorders. Based on such relationship, a novel paradigm is suggested in order to confirm that the protein interaction networks can be the target of therapy for treatment of complex multi-genic diseases rather than individual molecules with disrespect the network.

Systems biology approach to stage-wise characterization of epigenetic genes in lung adenocarcinoma

Background

Epigenetics refers to the reversible functional modifications of the genome that do not correlate to changes in the DNA sequence. The aim of this study is to understand DNA methylation patterns across different stages of lung adenocarcinoma (LUAD).

Results

Our study identified 72, 93 and 170 significant DNA methylated genes in Stages I, II and III respectively. A set of common 34 significant DNA methylated genes located in the promoter section of the true CpG islands were found across stages, and these were: HOX genes, FOXG1, GRIK3, HAND2, PRKCB, etc. Of the total significant DNA methylated genes, 65 correlated with transcription function. The epigenetic analysis identified the following novel genes across all stages: PTGDR, TLX3, and POU4F2. The stage-wise analysis observed the appearance of NEUROG1 gene in Stage I and its re-appearance in Stage III. The analysis showed similar epigenetic pattern across Stage I and Stage III. Pathway analysis revealed important signaling and metabolic pathways of LUAD to correlate with epigenetics. Epigenetic subnetwork analysis identified a set of seven conserved genes across all stages: UBC, KRAS, PIK3CA, PIK3R3, RAF1, BRAF, and RAP1A. A detailed literature analysis elucidated epigenetic genes like FOXG1, HLA-G, and NKX6-2 to be known as prognostic targets.

Conclusion

Integrating epigenetic information for genes with expression data can be useful for comprehending in-depth disease mechanism and for the ultimate goal of better target identification.

Smoke-related DNA methylation changes in the etiology of human disease

Exposure to environmental and lifestyle factors, such as cigarette smoking, affect the epigenome and might mediate risk for diseases and cancers. We have performed a genome-wide DNA methylation study to determine the effect of smoke and snuff (smokeless tobacco) on DNA methylation. A total of 95 sites were differentially methylated [false discovery rate (FDR) q-values < 0.05] in smokers and a subset of the differentially methylated loci were also differentially expressed in smokers. We found no sites, neither any biological functions nor molecular processes enriched for smoke-less tobacco-related differential DNA methylation. This suggests that methylation changes are not caused by the basic components of the tobacco but from its burnt products. Instead, we see a clear enrichment (FDR q-value < 0.05) for genes, including CPOX, CDKN1A and PTK2, involved in response to arsenic-containing substance, which agrees with smoke containing small amounts of arsenic. A large number of biological functions and molecular processes with links to disease conditions are also enriched (FDR q-value < 0.05) for smoke-related DNA methylation changes. These include 'insulin receptor binding', and 'negative regulation of glucose import' which are associated with diabetes, 'positive regulation of interleukin-6-mediated signaling pathway', 'regulation of T-helper 2 cell differentiation', 'positive regulation of interleukin-13 production' which are associated with the immune system and 'sertoli cell fate commitment' which is important for male fertility. Since type 2 diabetes, repressed immune system and infertility have previously been associated with smoking, our results suggest that this might be mediated by DNA methylation changes.

Peripheral blood mononuclear cell gene expression in chronic obstructive pulmonary disease

Although most cases of chronic obstructive pulmonary disease (COPD) occur in smokers, only a fraction of smokers develop the disease. We hypothesized distinct molecular signatures for COPD and emphysema in the peripheral blood mononuclear cells (PBMCs) of current and former smokers. To test this hypothesis, we identified and validated PBMC gene expression profiles in smokers with and without COPD. We generated expression data on 136 subjects from the COPDGene study, using Affymetrix U133 2.0 microarrays (Affymetrix, Santa Clara, CA). Multiple linear regression with adjustment for covariates (gender, age, body mass index, family history, smoking status, and pack-years) was used to identify candidate genes, and ingenuity pathway analysis was used to identify candidate pathways. Candidate genes were validated in 149 subjects according to multiplex quantitative real-time polymerase chain reaction, which included 75 subjects not previously profiled. Pathways that were differentially expressed in subjects with COPD and emphysema included those that play a role in the immune system, inflammatory responses, and sphingolipid (ceramide) metabolism. Twenty-six of the 46 candidate genes (e.g., FOXP1, TCF7, and ASAH1) were validated in the independent cohort. Plasma metabolomics was used to identify a novel glycoceramide (galabiosylceramide) as a biomarker of emphysema, supporting the genomic association between acid ceramidase (ASAH1) and emphysema. COPD is a systemic disease whose gene expression signatures in PBMCs could serve as novel diagnostic or therapeutic targets.

Analysis of the transcriptome in molecular epidemiology studies

The human transcriptome is complex, comprising multiple transcript types, mostly in the form of non-coding RNA (ncRNA). The majority of ncRNA is of the long form (lncRNA, ≥ 200 bp), which plays an important role in gene regulation through multiple mechanisms including epigenetics, chromatin modification, control of transcription factor binding, and regulation of alternative splicing. Both mRNA and ncRNA exhibit additional variability in the form of alternative splicing and RNA editing. All aspects of the human transcriptome can potentially be dysregulated by environmental exposures. Next-generation RNA sequencing (RNA-Seq) is the best available methodology to measure this although it has limitations, including experimental bias. The third phase of the MicroArray Quality Control Consortium project (MAQC-III), also called Sequencing Quality Control (SeQC), aims to address these limitations through standardization of experimental and bioinformatic methodologies. A limited number of toxicogenomic studies have been conducted to date using RNA-Seq. This review describes the complexity of the human transcriptome, the application of transcriptomics by RNA-Seq or microarray in molecular epidemiology studies, and limitations of these approaches including the type of cell or tissue analyzed, experimental variation, and confounding. By using good study designs with precise, individual exposure measurements, sufficient power and incorporation of phenotypic anchors, studies in human populations can identify biomarkers of exposure and/or early effect and elucidate mechanisms of action underlying associated diseases, even at low doses. Analysis of datasets at the pathway level can compensate for some of the limitations of RNA-Seq and, as more datasets become available, will increasingly elucidate the exposure-disease continuum.

Making sense of OMICS data in population-based environmental health studies

Although experience from the application of OMICS technologies in population-based environmental health studies is still relatively limited, the accumulated evidence shows that it can allow the identification of features (genes, proteins, and metabolites), or sets of such features, which are targeted by particular exposures or correlate with disease risk. Such features or profiles can therefore serve as biomarkers of exposure or disease risk. Blood-based OMIC profiles appear to reflect to some extent events occurring in target tissues and are associated with toxicity or disease and therefore have the potential to facilitate the elucidation of exposure-disease relationships. Further progress in this direction requires better understanding of the significance of exposure-induced network perturbations for disease initiation and progression and the development of a framework that combines agnostic searches with the utilization of prior knowledge, taking account of particular elements which characterize the structure and evolution of complex systems and brings in principles of systems biology.

A comprehensive analysis of adiponectin QTLs using SNP association, SNP cis-effects on peripheral blood gene expression and gene expression correlation identified novel metabolic syndrome (MetS) genes with potential role in carcinogenesis and systemic inflammation

BACKGROUND

Metabolic syndrome (MetS) is an aberration associated with increased risk for cancer and inflammation. Adiponectin, an adipocyte-produced abundant protein hormone, has countering effect on the diabetogenic and atherogenic components of MetS. Plasma levels of adiponectin are negatively correlated with onset of cancer and cancer patient mortality. We previously performed microsatellite linkage analyses using adiponectin as a surrogate marker and revealed two QTLs on chr5 (5p14) and chr14 (14q13).

METHODS

Using individuals from 85 extended families that contributed to the linkage and who were measured for 42 clinical and biologic MetS phenotypes, we tested QTL-based SNP associations, peripheral white blood cell (PWBC) gene expression, and the effects of cis-acting SNPs on gene expression to discover genomic elements that could affect the pathophysiology and complications of MetS.

RESULTS

Adiponectin levels were found to be highly intercorrelated phenotypically with the majority of MetS traits. QTL-specific haplotype-tagging SNPs associated with MetS phenotypes were annotated to 14 genes whose function could influence MetS biology as well as oncogenesis or inflammation. These were mechanistically categorized into four groups: cell-cell adhesion and mobility, signal transduction, transcription and protein sorting. Four genes were highly prioritized: cadherin 18 (CDH18), myosin X (MYO10), anchor protein 6 of AMPK (AKAP6), and neuronal PAS domain protein 3 (NPAS3). PWBC expression was detectable only for the following genes with multi-organ or with multi-function properties: NPAS3, MARCH6, MYO10 and FBXL7. Strong evidence of cis-effects on the expression of MYO10 in PWBC was found with SNPs clustered near the gene's transcription start site. MYO10 expression in PWBC was marginally correlated with body composition (p = 0.065) and adipokine levels in the periphery (p = 0.064). Variants of genes AKAP6, NPAS3, MARCH6 and FBXL7 have been previously reported to be associated with insulin resistance, inflammatory markers or adiposity studies using genome-wide approaches whereas associations of CDH18 and MYO10 with MetS traits have not been reported before.

CONCLUSIONS

Adiponectin QTLs-based SNP association and mRNA expression identified genes that could mediate the association between MetS and cancer or inflammation.

Blood transcriptomics: applications in toxicology

The number of new chemicals that are being synthesized each year has been steadily increasing. While chemicals are of immense benefit to mankind, many of them have a significant negative impact, primarily owing to their inherent chemistry and toxicity, on the environment as well as human health. In addition to chemical exposures, human exposures to numerous non-chemical toxic agents take place in the environment and workplace. Given that human exposure to toxic agents is often unavoidable and many of these agents are found to have detrimental human health effects, it is important to develop strategies to prevent the adverse health effects associated with toxic exposures. Early detection of adverse health effects as well as a clear understanding of the mechanisms, especially at the molecular level, underlying these effects are key elements in preventing the adverse health effects associated with human exposure to toxic agents. Recent developments in genomics, especially transcriptomics, have prompted investigations into this important area of toxicology. Previous studies conducted in our laboratory and elsewhere have demonstrated the potential application of blood gene expression profiling as a sensitive, mechanistically relevant and practical surrogate approach for the early detection of adverse health effects associated with exposure to toxic agents. The advantages of blood gene expression profiling as a surrogate approach to detect early target organ toxicity and the molecular mechanisms underlying the toxicity are illustrated and discussed using recent studies on hepatotoxicity and pulmonary toxicity. Furthermore, the important challenges this emerging field in toxicology faces are presented in this review article.

Graphical modeling of gene expression in monocytes suggests molecular mechanisms explaining increased atherosclerosis in smokers

Smoking is a risk factor for atherosclerosis with reported widespread effects on gene expression in circulating blood cells. We hypothesized that a molecular signature mediating the relation between smoking and atherosclerosis may be found in the transcriptome of circulating monocytes. Genome-wide expression profiles and counts of atherosclerotic plaques in carotid arteries were collected in 248 smokers and 688 non-smokers from the general population. Patterns of co-expressed genes were identified by Independent Component Analysis (ICA) and network structure of the pattern-specific gene modules was inferred by the PC-algorithm. A likelihood-based causality test was implemented to select patterns that fit models containing a path “smoking→gene expression→plaques”. Robustness of the causal inference was assessed by bootstrapping. At a FDR ≤0.10, 3,368 genes were associated to smoking or plaques, of which 93% were associated to smoking only. SASH1 showed the strongest association to smoking and PPARG the strongest association to plaques. Twenty-nine gene patterns were identified by ICA. Modules containing SASH1 and PPARG did not show evidence for the “smoking→gene expression→plaques” causality model. Conversely, three modules had good support for causal effects and exhibited a network topology consistent with gene expression mediating the relation between smoking and plaques. The network with the strongest support for causal effects was connected to plaques through SLC39A8, a gene with known association to HDL-cholesterol and cellular uptake of cadmium from tobacco, while smoking was directly connected to GAS6, a gene reported to have anti-inflammatory effects in atherosclerosis and to be up-regulated in the placenta of women smoking during pregnancy. Our analysis of the transcriptome of monocytes recovered genes relevant for association to smoking and atherosclerosis, and connected genes that before, were only studied in separate contexts. Inspection of correlation structure revealed candidates that would be missed by expression-phenotype association analysis alone.

Perturbation of cellular immune functions in cigarette smokers and protection by palm oil vitamin E supplementation

Background

Cigarette smoke contains free radicals and an have adverse effect to the immune system. Supplementation of palm oil vitamin E (palmvitee), is known has antioxidant properties is thought to be beneficial for system immune protection against free radicals activity. The objective of the study was to determine the effect of palmvitee supplementation on immune response in smokers.

Methods

This study involved a group of smokers and nonsmokers who received 200 mg/day palmvitee and placebo for the control group. Blood samples were taken at 0, 12 and 24 weeks of supplementation. Plasma tocopherol and tocotrienol were determined by HPLC, lymphocyte proliferation by lymphocyte transformation test (LTT) and enumeration of lymphocytes T and B cells by flow cytometry. Statistical analysis was performed by Mann–Whitney U-test for non-parametric data distribution and correlation among the variables was examined by Spearman.

Results

Plasma tocopherol and tocotrienol were increased in vitamin E supplemented group as compared to placebo group. Urine cotinine levels and serum α₁-antitrypsin were significantly higher in smokers compared to nonsmokers. Lymphocyte proliferation induced by PHA showed an increasing trend with palmvitee supplementation in both smokers and nonsmokers. Natural killer cells were decreased; CD4⁺ cells and B cells were increased in smokers compared to nonsmokers but were unaffected with vitamin E supplementation except in the percentage of B cells which were increased in nonsmokers supplemented palmvitee compared to placebo. CD4⁺/CD8⁺ ratio was increased in smokers compared to nonsmokers. The high TWBC count observed in smokers correlated with the increased CD4⁺ and B cells.

Conclusions

Smoking caused alterations in certain immune parameters and palmvitee supplementation tended to cause an increase in lymphocytes transformation test but had no effect on CD3⁺, CD4⁺, CD8⁺, NK cells and B cells except B cells percentage in nonsmokers.

Chapter 4: Protein interactions and disease

Proteins do not function in isolation; it is their interactions with one another and also with other molecules (e.g. DNA, RNA) that mediate metabolic and signaling pathways, cellular processes, and organismal systems. Due to their central role in biological function, protein interactions also control the mechanisms leading to healthy and diseased states in organisms. Diseases are often caused by mutations affecting the binding interface or leading to biochemically dysfunctional allosteric changes in proteins. Therefore, protein interaction networks can elucidate the molecular basis of disease, which in turn can inform methods for prevention, diagnosis, and treatment. In this chapter, we will describe the computational approaches to predict and map networks of protein interactions and briefly review the experimental methods to detect protein interactions. We will describe the application of protein interaction networks as a translational approach to the study of human disease and evaluate the challenges faced by these approaches.

A whole blood gene expression-based signature for smoking status

Background

Smoking is the leading cause of preventable death worldwide and has been shown to increase the risk of multiple diseases including coronary artery disease (CAD). We sought to identify genes whose levels of expression in whole blood correlate with self-reported smoking status.

Methods

Microarrays were used to identify gene expression changes in whole blood which correlated with self-reported smoking status; a set of significant genes from the microarray analysis were validated by qRT-PCR in an independent set of subjects. Stepwise forward logistic regression was performed using the qRT-PCR data to create a predictive model whose performance was validated in an independent set of subjects and compared to cotinine, a nicotine metabolite.

Results

Microarray analysis of whole blood RNA from 209 PREDICT subjects (41 current smokers, 4 quit ≤ 2 months, 64 quit > 2 months, 100 never smoked; NCT00500617) identified 4214 genes significantly correlated with self-reported smoking status. qRT-PCR was performed on 1,071 PREDICT subjects across 256 microarray genes significantly correlated with smoking or CAD. A five gene (CLDND1, LRRN3, MUC1, GOPC, LEF1) predictive model, derived from the qRT-PCR data using stepwise forward logistic regression, had a cross-validated mean AUC of 0.93 (sensitivity=0.78; specificity=0.95), and was validated using 180 independent PREDICT subjects (AUC=0.82, CI 0.69-0.94; sensitivity=0.63; specificity=0.94). Plasma from the 180 validation subjects was used to assess levels of cotinine; a model using a threshold of 10 ng/ml cotinine resulted in an AUC of 0.89 (CI 0.81-0.97; sensitivity=0.81; specificity=0.97; kappa with expression model = 0.53).

Conclusion

We have constructed and validated a whole blood gene expression score for the evaluation of smoking status, demonstrating that clinical and environmental factors contributing to cardiovascular disease risk can be assessed by gene expression.

Genotype×age interaction in human transcriptional ageing

Individual differences in biological ageing (i.e., the rate of physiological response to the passage of time) may be due in part to genotype-specific variation in gene action. However, the sources of heritable variation in human age-related gene expression profiles are largely unknown. We have profiled genome-wide expression in peripheral blood mononuclear cells from 1240 individuals in large families and found 4472 human autosomal transcripts, representing ~4349 genes, significantly correlated with age. We identified 623 transcripts that show genotype by age interaction in addition to a main effect of age, defining a large set of novel candidates for characterization of the mechanisms of differential biological ageing. We applied a novel SNP genotype × age interaction test to one of these candidates, the ubiquilin-like gene UBQLNL, and found evidence of joint cis-association and genotype by age interaction as well as trans-genotype by age interaction for UBQLNL expression. Both UBQLNL expression levels at recruitment and cis genotype are associated with longitudinal cancer risk in our study cohort.

Relationship of environmental tobacco smoke to otitis media (OM) in children

INTRODUCTION

Many, but not all, studies have found a correlation between environmental tobacco smoke (ETS) and acute otitis media (AOM) and other adverse otologic outcomes. Given its high personal and societal costs and the divergent findings of the effect of ETS on middle ear disease, the aim of the current study was to assess the impact and possible determinant factors of ETS on recurrent (two or more) episodes of AOM.

METHODS

The study was performed at Heim Pal Children's Hospital, Ear, Nose and Throat (ENT) Department, Budapest, Hungary. Caregivers of a convenience sample of 412 children attending the ENT outpatient clinic were surveyed via a 22-item questionnaire regarding demographics, socioeconomics, and smoking behaviours of the child's family; as well as care-givers' self report of the number of AOM episodes of the child.

RESULTS

Of the 412 participants, 155 (38%) children's parents smoked. In bivariate analysis, two or more episodes of AOM correlated with reported hearing problems, day care enrolment, parental employment and increased age of the child. In multivariate logistic regression, parental smoking more than doubled a child's risk for recurrent AOM while increased maternal employment (e.g. part-time or full-time versus unemployed) boosted risk up to fourfold. Among children whose parents smoked, half-packs of cigarettes smoked per day and day care attendance doubled or nearly tripled, respectively, the risk of recurrent AOM episodes.

CONCLUSIONS

Childhood exposure to ETS is high among an ENT clinic population of Hungarian children. Such exposure correlates with AOM episodes, ENT operations and conductive hearing loss. Data such as these argue for strict laws smoke-free laws not only in Hungary, but also in Europe and around the world.

Molecular signature of smoking in human lung tissues

Cigarette smoking is the leading risk factor for lung cancer. To identify genes deregulated by smoking and to distinguish gene expression changes that are reversible and persistent following smoking cessation, we carried out genome-wide gene expression profiling on nontumor lung tissue from 853 patients with lung cancer. Gene expression levels were compared between never and current smokers, and time-dependent changes in gene expression were studied in former smokers. A total of 3,223 transcripts were differentially expressed between smoking groups in the discovery set (n = 344, P < 1.29 × 10(-6)). A substantial number of smoking-induced genes also were validated in two replication sets (n = 285 and 224), and a gene expression signature of 599 transcripts consistently segregated never from current smokers across all three sets. The expression of the majority of these genes reverted to never-smoker levels following smoking cessation, although the time course of normalization differed widely among transcripts. Moreover, some genes showed very slow or no reversibility in expression, including SERPIND1, which was found to be the most consistent gene permanently altered by smoking in the three sets. Our findings therefore indicate that smoking deregulates many genes, many of which reverse to normal following smoking cessation. However, a subset of genes remains altered even decades following smoking cessation and may account, at least in part, for the residual risk of lung cancer among former smokers. Cancer Res; 72(15); 3753-63. ©2012 AACR.

Cigarette smoking behaviors and time since quitting are associated with differential DNA methylation across the human genome

The impact of cigarette smoking can persist for extended periods following smoking cessation and may involve epigenetic reprogramming. Changes in DNA methylation associated with smoking may help to identify molecular pathways that contribute to the latency between exposure and disease onset. Cross-sectional cohort data from subjects in the International COPD Genetics Network (n = 1085) and the Boston Early-Onset COPD study (n = 369) were analyzed as the discovery and replication cohorts, respectively. Genome-wide methylation data on 27 578 CpG sites in 14 475 genes were obtained on DNA from peripheral blood leukocytes using the Illumina HumanMethylation27K Beadchip in both cohorts. We identified 15 sites significantly associated with current smoking, 2 sites associated with cumulative smoke exposure, and, within the subset of former smokers, 3 sites associated with time since quitting cigarettes. Two loci, factor II receptor-like 3 (F2RL3) and G-protein-coupled receptor 15 (GPR15), were significantly associated in all three analyses and were validated by pyrosequencing. These findings (i) identify a novel locus (GPR15) associated with cigarette smoking and (ii) suggest the existence of dynamic, site-specific methylation changes in response to smoking which may contribute to the extended risks associated with cigarette smoking that persist after cessation.

Paternal smoking and risk of childhood acute lymphoblastic leukemia: systematic review and meta-analysis

Objective. To investigate the association between paternal smoking and childhood acute lymphoblastic leukemia (ALL). Method. We identified 18 published epidemiologic studies that reported data on both paternal smoking and childhood ALL risk. We performed a meta-analysis and analyzed dose-response relationships on ALL risk for smoking during preconception, during pregnancy, after birth, and ever smoking. Results. The summary odds ratio (OR) of childhood ALL associated with paternal smoking was 1.11 (95% Confidence Interval (CI): 1.05-1.18, I(2) = 18%) during any time period, 1.25 (95% CI: 1.08-1.46, I(2) = 53%) preconception; 1.24 (95% CI: 1.07-1.43, I(2) = 54%) during pregnancy, and 1.24 (95% CI: 0.96-1.60, I(2) = 64%) after birth, with a dose-response relationship between childhood ALL and paternal smoking preconception or after birth. Conclusion. The evidence supports a positive association between childhood ALL and paternal ever smoking and at each exposure time period examined. Future epidemiologic studies should assess paternal smoking during well-defined exposure windows and should include biomarkers to assess smoking exposure and toxicological mechanisms.

Blood gene expression profiling detects silica exposure and toxicity

Blood gene expression profiling was investigated as a minimally invasive surrogate approach to detect silica exposure and resulting pulmonary toxicity. Rats were exposed by inhalation to crystalline silica (15 mg/m³, 6 h/day, 5 days), and pulmonary damage and blood gene expression profiles were determined after latency periods (0-16 weeks). Silica exposure resulted in pulmonary toxicity as evidenced by histological and biochemical changes in the lungs. The number of significantly differentially expressed genes in the blood, identified by microarray analysis, correlated with the severity of silica-induced pulmonary toxicity. Functional analysis of the differentially expressed genes identified activation of inflammatory response as the major biological signal. Induction of pulmonary inflammation, as suggested by the blood gene expression data, was supported by significant increases in the number of macrophages and infiltrating neutrophils as well as the activity of pro-inflammatory chemokines observed in the lungs of the silica-exposed rats. A gene expression signature developed using the blood gene expression data predicted the exposure of rats to lower, minimally toxic and nontoxic concentrations of silica. Taken together, our findings suggest the potential application of peripheral blood gene expression profiling as a minimally invasive surrogate approach to detect pulmonary toxicity induced by silica in the rat. However, further research is required to determine the potential application of our findings specifically to monitor human exposure to silica and the resulting pulmonary effects.