The effect of smoking on DNA methylation of peripheral blood mononuclear cells from African American women

Role of epigenetic mechanisms in the pathogenesis of chronic respiratory diseases and response to inhaled exposures: From basic concepts to clinical applications

Epigenetic modifications are chemical groups in our DNA (and chromatin) that determine which genes are active and which are shut off. Importantly, they integrate environmental signals to direct cellular function. Upon chronic environmental exposures, the epigenetic signature of lung cells gets altered, triggering aberrant gene expression programs that can lead to the development of chronic lung diseases. In addition to driving disease, epigenetic marks can serve as attractive lung disease biomarkers, due to early onset, disease specificity, and stability, warranting the need for more epigenetic research in the lung field. Despite substantial progress in mapping epigenetic alterations (mostly DNA methylation) in chronic lung diseases, the molecular mechanisms leading to their establishment are largely unknown. This review is meant as a guide for clinicians and lung researchers interested in epigenetic regulation with a focus on DNA methylation. It provides a short introduction to the main epigenetic mechanisms (DNA methylation, histone modifications and non-coding RNA) and the machinery responsible for their establishment and removal. It presents examples of epigenetic dysregulation across a spectrum of chronic lung diseases and discusses the current state of epigenetic therapies. Finally, it introduces the concept of epigenetic editing, an exciting novel approach to dissecting the functional role of epigenetic modifications. The promise of this emerging technology for the functional study of epigenetic mechanisms in cells and its potential future use in the clinic is further discussed.

A comprehensive lifestyle index and its associations with DNA methylation and type 2 diabetes among Ghanaian adults: the rodam study

BACKGROUND

A series of modifiable lifestyle factors, such as diet quality, physical activity, alcohol intake, and smoking, may drive the rising burden of type 2 diabetes (T2DM) among sub-Saharan Africans globally. It is unclear whether epigenetic changes play a mediatory role in the associations between these lifestyle factors and T2DM. We assessed the associations between a comprehensive lifestyle index, DNA methylation and T2DM among Ghanaian adults.

METHODS

We used whole-blood Illumina 450 k DNA methylation data from 713 Ghanaians from the Research on Obesity and Diabetes among African Migrants (RODAM) study. We constructed a comprehensive lifestyle index based on established cut-offs for diet quality, physical activity, alcohol intake, and smoking status. In the T2DM-free discovery cohort (n = 457), linear models were fitted to identify differentially methylated positions (DMPs) and differentially methylated regions (DMRs) associated with the lifestyle index after adjustment for age, sex, body mass index (BMI), and technical covariates. Associations between the identified DMPs and the primary outcome (T2DM), as well as secondary outcomes (fasting blood glucose (FBG) and HbA1c), were determined via logistic and linear regression models, respectively.

RESULTS

In the present study population (mean age: 52 ± 10 years; male: 42.6%), the comprehensive lifestyle index showed a significant association with one DMP annotated to an intergenic region on chromosome 7 (false discovery rate (FDR) = 0.024). Others were annotated to ADCY7, SMARCE1, AHRR, LOXL2, and PTBP1 genes. One DMR was identified and annotated to the GFPT2 gene (familywise error rate (FWER) from bumphunter bootstrap = 0.036). None of the DMPs showed significant associations with T2DM; directions of effect were positive for the DMP in the AHRR and inverse for all the other DMPs. Higher methylation of the ADCY7 DMP was associated with higher FBG (p = 0.024); LOXL2 DMP was associated with lower FBG (p = 0.023) and HbA1c (p = 0.049); and PTBP1 DMP was associated with lower HbA1c (p = 0.002).

CONCLUSIONS

In this explorative epigenome-wide association study among Ghanaians, we identified one DMP and DMR associated with a comprehensive lifestyle index not previously associated with individual lifestyle factors. Based on our findings, we infer that lifestyle factors in combination, affect DNA methylation, thereby influencing the risk of T2DM among Ghanaian adults living in different contexts.

Greater methylation of the IL-6 promoter region is associated with decreased integrity of the corpus callosum in schizophrenia

BACKGROUND

Schizophrenia is associated with chronic subclinical inflammation and decreased integrity of the corpus callosum (CC). Our previous study showed associations between peripheral IL-6 levels and the integrity of the CC. Epigenetic studies show associations between methylation of the genes related to immunological processes and integrity of the CC.

AIM

To investigate correlations between methylation status of IL-6 promotor and peripheral IL-6 levels and the integrity of the CC in schizophrenia.

MATERIAL AND METHODS

The participants were 29 chronic schizophrenia patients (SCH) and 29 controls. Decreased integrity of the CC was understood as increased mean diffusivity (MD) and/or decreased fractional anisotropy (FA) in diffusion tensor imaging. Peripheral IL-6 concentrations were measured in serum samples and IL-6 promoter methylation status of 6 CpG sites was analyzed in peripheral leukocytes by pyrosequencing.

RESULTS

Moderate positive correlations were found between CpG1 methylation and the MD of proximal regions of the CC (CCR1-CCR3) and between CpGmean and MD of CCR1 in SCH. Weaker positive correlations were found for CpGmean with CCR2 and CCR3 and negative correlations were found for CpG1 and FA of CCR3 in SCH. Multivariate regression showed that methylation of CpG1, type of antipsychotic treatment, and their interaction were significant independent predictors of MD of CCR1 in SCH. Methylation of CpG2 was negatively correlated with serum IL-6 in SCH.

CONCLUSIONS

The methylation level of the IL-6 promotor region in peripheral leukocytes is associated with the integrity of the CC in schizophrenia and this association may depend on the type of antipsychotic treatment. Further studies are necessary to explain the mechanisms of the observed associations.

Genome-wide DNA methylation analysis of cannabis use disorder in a veteran cohort enriched for posttraumatic stress disorder

Cannabis use has been increasing over the past decade, not only in the general US population, but particularly among military veterans. With this rise in use has come a concomitant increase in cannabis use disorder (CUD) among veterans. Here, we performed an epigenome-wide association study for lifetime CUD in an Iraq/Afghanistan era veteran cohort enriched for posttraumatic stress disorder (PTSD) comprising 2,310 total subjects (1,109 non-Hispanic black and 1,201 non-Hispanic white). We also investigated CUD interactions with current PTSD status and examined potential indirect effects of DNA methylation (DNAm) on the relationship between CUD and psychiatric diagnoses. Four CpGs were associated with lifetime CUD, even after controlling for the effects of current smoking (AHRR cg05575921, LINC00299 cg23079012, VWA7 cg22112841, and FAM70A cg08760398). Importantly, cg05575921, a CpG strongly linked to smoking, remained associated with lifetime CUD even when restricting the analysis to veterans who reported never smoking cigarettes. Moreover, CUD interacted with current PTSD to affect cg05575921 and cg23079012 such that those with both CUD and PTSD displayed significantly lower DNAm compared to the other groups. Finally, we provide preliminary evidence that AHRR cg05575921 helps explain the association between CUD and any psychiatric diagnoses, specifically mood disorders.

The Influence of Smoking and Occupational Risk Factors on DNA Methylation in the AHRR and F2RL3 Genes

BACKGROUND

AHRR and F2RL3 hypomethylation has been associated with lung cancer. In this study, we investigated the cross-sectional association between smoking and occupational exposures, and AHRR and F2RL3 methylation.

METHODS

A case-control study was nested in CARTaGENE to examine the association between AHRR and F2RL3 methylation and lung cancer risk (200 cases; 400 controls). A secondary analysis was conducted using the data collected from this nested study; namely, baseline information on participants' smoking behavior and longest-held job was obtained. A cumulative smoking index summarized information on the number of cigarettes smoked, duration of smoking, and time since cessation. Exposure to 13 occupational agents was estimated using the Canadian Job Exposure Matrix. In baseline blood samples, methylation ratios of 40 CpG sites in the AHRR and F2RL3 genes were measured using Sequenom EpiTYPER. Separate least squares regression models were used to estimate the associations between smoking and occupational exposures, and average AHRR and F2RL3 methylation levels, while adjusting for confounders identified from directed acyclic graphs.

RESULTS

In both genes, smoking was associated with lower average methylation levels. Occupational exposure to aromatic amines, cadmium, and formaldehyde were associated with lower AHRR methylation while, only benzene was associated with F2RL3 hypomethylation; these associations were stronger among ever smokers.

CONCLUSIONS

Our findings support that smoking and occupational exposures to some agents are associated with AHRR and F2RL3 hypomethylation.

IMPACT

Our results inform on mechanisms underlying environmental exposures in lung cancer etiology; future studies should prioritize studying joint exposures.

Accelerated epigenetic age, inflammation, and gene expression in lung: comparisons of smokers and vapers with non-smokers

BACKGROUND

Cigarette smoking and aging are the main risk factors for pulmonary diseases, including cancer. Epigenetic aging may explain the relationship between smoking, electronic cigarette vaping, and pulmonary health. No study has examined smoking and vaping-related epigenetic aging in relation to lung biomarkers.

METHODS

Lung epigenetic aging measured by DNA methylation (mAge) and its acceleration (mAA) was assessed in young (age 21-30) electronic cigarette vapers (EC, n = 14, including 3 never-smoking EC), smokers (SM, n = 16), and non-EC/non-SM (NS, n = 39). We investigated relationships of mAge estimates with chronological age (Horvath-mAge), lifespan/mortality (Grim-mAge), telomere length (TL-mAge), smoking/EC history, urinary biomarkers, lung cytokines, and transcriptome.

RESULTS

Compared to NS, EC and SM had significantly older Grim-mAge, shorter TL-mAge, significantly accelerated Grim-mAge and decelerated TL-mAge. Among SM, Grim-mAA was associated with nicotine intake and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL). For EC, Horvath-mAA was significantly correlated with puffs per day. Overall, cytokines (IL-1β, IL-6, and IL-8) and 759 transcripts (651 unique genes) were significantly associated with Grim-mAA. Grim-mAA-associated genes were highly enriched in immune-related pathways and genes that play a role in the morphology and structures of cells/tissues.

CONCLUSIONS

Faster lung mAge for SM is consistent with prior studies of blood. Faster lung mAge for EC compared to NS indicates possible adverse pulmonary effects of EC on biological aging. Our findings support further research, particularly on epigenetic markers, on effects of smoking and vaping on pulmonary health. Given that most EC are former smokers, further study is needed to understand unique effects of electronic cigarettes on biological aging.

AHRR Hypomethylation mediates the association between maternal smoking and metabolic profiles in children

BACKGROUND

Tobacco smoking during pregnancy is associated with metabolic dysfunction in children, but mechanistic insights remain limited. Hypomethylation of cg05575921 in the aryl hydrocarbon receptor repressor (AHRR) gene is associated with in utero tobacco smoke exposure. In this study, we evaluated whether AHRR hypomethylation mediates the association between maternal smoking and metabolic dysfunction in children.

METHODS

We assessed metabolic dysfunction using liver fat content (LFC), serum, and clinical data in children aged 7-12 years (n=78) followed since birth. Maternal smoking was self-reported at 12 weeks gestation. Methylation was measured by means of pyrosequencing at 3 sequential CpG sites, including cg05575921, at birth and at ages 7-12. Regression models were used to evaluate whether AHRR methylation mediated the association between maternal smoking and child metabolic dysfunction.

RESULTS

Average AHRR methylation at birth was significantly higher among children of nonsmoking mothers compared with children of mothers who smoked (69.8% ± 4.4% vs. 63.5% ± 5.5, p=0.0006). AHRR hypomethylation at birth was associated with higher liver fat content (p=0.01), triglycerides (p=0.01), and alanine aminotransferase levels (p=0.03), and lower HDL cholesterol (p=0.01) in childhood. AHRR hypomethylation significantly mediated associations between maternal smoking and liver fat content (indirect effect=0.213, p=0.018), triglycerides (indirect effect=0.297, p=0.044), and HDL cholesterol (indirect effect = -0.413, p=0.007). AHRR methylation in childhood (n=78) was no longer significantly associated with prenatal smoke exposure or child metabolic parameters (p>0.05).

CONCLUSIONS

AHRR hypomethylation significantly mediates the association between prenatal tobacco smoke exposure and features of childhood metabolic dysfunction, despite the lack of persistent hypomethylation of AHRR into childhood. Further studies are needed to replicate these findings and to explore their causal and long-term significance.

Short-term smoking cessation leads to a universal decrease in whole blood genomic DNA methylation in patients with a smoking history

BACKGROUND

Epigenetics is involved in various human diseases. Smoking is one of the most common environmental factors causing epigenetic changes. The DNA methylation changes and mechanisms after quitting smoking have yet to be defined. The present study examined the changes in DNA methylation levels before and after short-term smoking cessation and explored the potential mechanism.

METHODS

Whole blood and clinical data were collected from 8 patients before and after short-term smoking cessation, DNA methylation was assessed, and differentially methylated sites were analyzed, followed by a comprehensive analysis of the differentially methylated sites with clinical data. GO/KEGG enrichment and protein-protein interaction (PPI) network analyses identified the hub genes. The differentially methylated sites between former and current smokers in GSE50660 from the GEO database were detected by GEO2R. Then, a Venn analysis was carried out using the differentially methylated sites. GO/KEGG enrichment analysis was performed on the genes corresponding to the common DNA methylation sites, the PPI network was constructed, and hub genes were predicted. The enriched genes associated with the cell cycle were selected, and the pan-cancer gene expression and clinical significance in lung cancer were analyzed based on the TCGA database.

RESULTS

Most genes showed decreased DNA methylation levels after short-term smoking cessation; 694 upregulated methylation CpG sites and 3184 downregulated methylation CpG sites were identified. The DNA methylation levels were altered according to the clinical data (body weight, expiratory, and tobacco dependence score). Enrichment analysis, construction of the PPI network, and pan-cancer analysis suggested that smoking cessation may affect various biological processes.

CONCLUSIONS

Smoking cessation leads to epigenetic changes, mainly decreased in the decline of most DNA methylation levels. Bioinformatics further identified the biologically relevant changes after short-term smoking cessation.

Emerging roles of a chemoattractant receptor GPR15 and ligands in pathophysiology

Chemokine receptors play a central role in the maintenance of immune homeostasis and development of inflammation by directing leukocyte migration to tissues. GPR15 is a G protein-coupled receptor (GPCR) that was initially known as a co-receptor for human immunodeficiency virus (HIV) and simian immunodeficiency virus (SIV), with structural similarity to other members of the chemoattractant receptor family. Since the discovery of its novel function as a colon-homing receptor of T cells in mice a decade ago, GPR15 has been rapidly gaining attention for its involvement in a variety of inflammatory and immune disorders. The recent identification of its natural ligand C10orf99, a chemokine-like polypeptide strongly expressed in gastrointestinal tissues, has established that GPR15-C10orf99 is a novel signaling axis that controls intestinal homeostasis and inflammation through the migration of immune cells. In addition, it has been demonstrated that C10orf99-independent functions of GPR15 and GPR15-independent activities of C10orf99 also play significant roles in the pathophysiology. Therefore, GPR15 and its ligands are potential therapeutic targets. To provide a basis for the future development of GPR15- or GPR15 ligand-targeted therapeutics, we have summarized the latest advances in the role of GPR15 and its ligands in human diseases as well as the molecular mechanisms that regulate GPR15 expression and functions.

Development and validation of a simple general population lung cancer risk model including AHRR-methylation

INTRODUCTION

Screening reduces lung cancer mortality of high-risk populations. Currently proposed screening eligibility criteria only identify half of those individuals, who later develop lung cancer. This study aimed to develop and validate a sensitive and simple model for predicting 10-year lung cancer risk.

METHODS

Using the 1991-94 examination of The Copenhagen City Heart Study in Denmark, 6,820 former or current smokers from the general population were followed for lung cancer within 10 years after examination. Logistic regression of baseline variables (age, sex, education, chronic obstructive pulmonary disease, family history of lung cancer, smoking status and cumulative smoking, secondhand smoking, occupational exposures to dust and fume, body mass index, lung function, plasma C-reactive protein, and AHRR(cg05575921) methylation) identified the best predictive model. The model was validated among 3,740 former or current smokers from the 2001-03 examination, also followed for 10 years. A simple risk chart was developed with Poisson regression.

RESULTS

Age, sex, education, smoking status, cumulative smoking, and AHRR(cg05575921) methylation identified 65 of 88 individuals who developed lung cancer in the validation cohort. The highest risk group, consisting of less educated men aged >65 with current smoking status and cumulative smoking >20 pack-years, had absolute 10-year risks varying from 4% to 16% by AHRR(cg05575921) methylation.

CONCLUSION

A simple risk chart including age, sex, education, smoking status, cumulative smoking, and AHRR(cg05575921) methylation, identifies individuals with 10-year lung cancer risk from below 1% to 16%. Including AHRR(cg05575921) methylation in the eligibility criteria for screening identifies smokers who would benefit the most from screening.

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.

Life factors acting on systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is a highly heterogeneous autoimmune disease that primarily affects women. Currently, in the search for the mechanisms of SLE pathogenesis, the association of lifestyle factors such as diet, cigarette smoking, ultraviolet radiation exposure, alcohol and caffeine-rich beverage consumption with SLE susceptibility has been systematically investigated. The cellular and molecular mechanisms mediating lifestyle effects on SLE occurrence, including interactions between genetic risk loci and environment, epigenetic changes, immune dysfunction, hyper-inflammatory response, and cytotoxicity, have been proposed. In the present review of the reports published in reputable peer-reviewed journals and government websites, we consider the current knowledge about the relationships between lifestyle factors and SLE incidence and outline directions of future research in this area. Formulation of practical measures with regard to the lifestyle in the future will benefit SLE patients and may provide potential therapy strategies.

Smoking and Its Consequences on Male and Female Reproductive Health

Smoking contributes to the death of around one in 10 adults worldwide. Specifically, cigarettes are known to contain around 4000 toxins and chemicals that are hazardous in nature. The negative effects of smoking on human health and interest in smoking-related diseases have a long history. Among these concerns are the harmful effects of smoking on reproductive health. Thirteen percent of female infertility is due to smoking. Female smoking can lead to gamete mutagenesis, early loss of reproductive function, and thus advance the time to menopause. It has been also associated with ectopic pregnancy and spontaneous abortion. Even when it comes to assisted reproductive technologies cycles, smokers require more cycles, almost double the number of cycles needed to conceive as non-smokers. Male smoking is shown to be correlated with poorer semen parameters and sperm DNA fragmentation. Not only active smokers but also passive smokers, when excessively exposed to smoking, can have reproductive problems comparable to those seen in smokers. In this book chapter, we will approach the effect of tobacco, especially tobacco smoking, on male and female reproductive health. This aims to take a preventive approach to infertility by discouraging smoking and helping to eliminate exposure to tobacco smoke in both women and men.

Association of lipid metabolism-related gene promoter methylation with risk of coronary artery disease

BACKGROUND

Coronary artery disease (CAD) is a complex disease that is influenced by environmental and genetic factors. Lipid levels are regarded as a major risk factor for CAD, and epigenetic mechanisms might be involved in the regulation of CAD development. This study was designed to investigate the association between the DNA methylation status of 8 lipid metabolism-related genes and the risk of CAD in the Chinese Han population.

METHODS

A total of 260 individuals were sampled in this study, including 120 CAD cases and 140 normal healthy controls. DNA methylation status was tested via targeted bisulfite sequencing.

RESULTS

The results indicated a significant association between hypomethylation of the APOC3, CETP and APOC1 gene promoters and the risk of CAD. Individuals with higher methylation levels of the APOA5 and LIPC gene promoters had increased risks for CAD. In addition, ANGPTL4 methylation level was significantly associated with CAD in males but not females. There were no significant differences in the methylation levels of the APOB and PCSK9 gene promoters between CAD patients and controls.

CONCLUSIONS

The methylation status of the APOC3, APOA5, LIPC, CETP and APOC1 gene promoters may be associated with the development of CAD.

Current Therapeutic Landscape and Safety Roadmap for Targeting the Aryl Hydrocarbon Receptor in Inflammatory Gastrointestinal Indications

Target modulation of the AhR for inflammatory gastrointestinal (GI) conditions holds great promise but also the potential for safety liabilities both within and beyond the GI tract. The ubiquitous expression of the AhR across mammalian tissues coupled with its role in diverse signaling pathways makes development of a “clean” AhR therapeutically challenging. Ligand promiscuity and diversity in context-specific AhR activation further complicates targeting the AhR for drug development due to limitations surrounding clinical translatability. Despite these concerns, several approaches to target the AhR have been explored such as small molecules, microbials, PROTACs, and oligonucleotide-based approaches. These various chemical modalities are not without safety liabilities and require unique de-risking strategies to parse out toxicities. Collectively, these programs can benefit from in silico and in vitro methodologies that investigate specific AhR pathway activation and have the potential to implement thresholding parameters to categorize AhR ligands as “high” or “low” risk for sustained AhR activation. Exploration into transcriptomic signatures for AhR safety assessment, incorporation of physiologically-relevant in vitro model systems, and investigation into chronic activation of the AhR by structurally diverse ligands will help address gaps in our understanding regarding AhR-dependent toxicities. Here, we review the role of the AhR within the GI tract, novel therapeutic modality approaches to target the AhR, key AhR-dependent safety liabilities, and relevant strategies that can be implemented to address drug safety concerns. Together, this review discusses the emerging therapeutic landscape of modalities targeting the AhR for inflammatory GI indications and offers a safety roadmap for AhR drug development.

FeCO3, constructing the network biomarkers using the inter-feature correlation coefficients and its application in detecting high-order breast cancer biomarkers

Aims:

This study aims to formulate the inter-feature correlation as the engineered features.

Background:

Modern biotechnologies tend to generate a huge number of characteristics of a sample, while an OMIC dataset usually has a few dozens or hundreds of samples due to the high costs of generating the OMIC data. So many bio-OMIC studies assumed the inter-feature independence and selected a feature with a high phenotype-association.

Objective:

However, many features are closely associated with each other due to their physical or functional interactions, which may be utilized as a new view of features.

Method:

This study proposed a feature engineering algorithm based on the correlation coefficients (FeCO3) by utilizing the correlations between a given sample and a few reference samples. A comprehensive evaluation was carried out for the proposed FeCO3 network features using 24 bio-OMIC datasets.

Result:

The experimental data suggested that the newly calculated FeCO3 network features tended to achieve better classification performances than the original features, using the same popular feature selection and classification algorithms. The FeCO3 network features were also consistently supported by the literature. FeCO3 was utilized to investigate the high-order engineered biomarkers of breast cancer, and detected the PBX2 gene (Pre-B-Cell Leukemia Transcription Factor 2) as one of the candidate breast cancer biomarkers. Although the two methylated residues cg14851325 (Pvalue=8.06e-2) and cg16602460 (Pvalue=1.19e-1) within PBX2 did not have statistically significant association with breast cancers, the high-order inter-feature correlations showed a significant association with breast cancers.

Conclusion:

The proposed FeCO3 network features calculated the high-order inter-feature correlations as novel features, and may facilitate the investigations of complex diseases from this new perspective. The source code is available in FigShare at 10.6084/m9.figshare.13550051 or the web site http://www.healthinformaticslab.org/supp/ .

Effect of Environmental Stressors, Xenobiotics, and Oxidative Stress on Male Reproductive and Sexual Health

This article examines the environmental factor-induced oxidative stress (OS) and their effects on male reproductive and sexual health. There are several factors that induce OS, i.e. radition, metal contamination, xenobiotic compounds, and cigarette smoke and lead to cause toxicity in the cells through metabolic or bioenergetic processes. These environmental factors may produce free radicals and enhance the reactive oxygen species (ROS). Free radicals are molecules that include oxygen and disbalance the amount of electrons that can create major chemical chains in the body and cause oxidation. Oxidative damage to cells may impair male fertility and lead to abnormal embryonic development. Moreover, it does not only cause a vast number of health issues such as ageing, cancer, atherosclerosis, insulin resistance, diabetes mellitus, cardiovascular diseases, ischemia-reperfusion injury, and neurodegenerative disorders but also decreases the motility of spermatozoa while increasing sperm DNA damage, impairing sperm mitochondrial membrane lipids and protein kinases. This chapter mainly focuses on the environmental stressors with further discussion on the mechanisms causing congenital impairments due to poor sexual health and transmitting altered signal transduction pathways in male gonadal tissues.

Zoo: Selecting Transcriptomic and Methylomic Biomarkers by Ensembling Animal-Inspired Swarm Intelligence Feature Selection Algorithms

Biological omics data such as transcriptomes and methylomes have the inherent “large p small n” paradigm, i.e., the number of features is much larger than that of the samples. A feature selection (FS) algorithm selects a subset of the transcriptomic or methylomic biomarkers in order to build a better prediction model. The hidden patterns in the FS solution space make it challenging to achieve a feature subset with satisfying prediction performances. Swarm intelligence (SI) algorithms mimic the target searching behaviors of various animals and have demonstrated promising capabilities in selecting features with good machine learning performances. Our study revealed that different SI-based feature selection algorithms contributed complementary searching capabilities in the FS solution space, and their collaboration generated a better feature subset than the individual SI feature selection algorithms. Nine SI-based feature selection algorithms were integrated to vote for the selected features, which were further refined by the dynamic recursive feature elimination framework. In most cases, the proposed Zoo algorithm outperformed the existing feature selection algorithms on transcriptomics and methylomics datasets.

The relationship of smoking to cg05575921 methylation in blood and saliva DNA samples from several studies

Numerous studies have shown that cg05575921 methylation decreases in response to smoking. However, secondary to methodological issues, the magnitude and dose dependency of that response is as of yet unclear. This lack of certainty is a barrier to the use of DNA methylation clinically to assess and monitor smoking status. To better define this relationship, we conducted a joint analysis of methylation sensitive PCR digital (MSdPCR) assessments of cg05575921 methylation in whole blood and/or saliva DNA to smoking using samples from 421 smokers and 423 biochemically confirmed non-smokers from 4 previously published studies. We found that cg05575921 methylation manifested a curvilinear dose dependent decrease in response to increasing cigarette consumption. In whole blood DNA, the Receiver Operating Characteristic (ROC) Area Under the Curve (AUC) of cg05575921 methylation for predicting daily smoking status was 0.98. In saliva DNA, the gross AUC was 0.91 with correction for cellular heterogeneity improving the AUC to 0.94. Methylation status was significantly associated with the Fagerstrom Test for Nicotine Dependence score, but with significant sampling heterogeneity. We conclude that MSdPCR assessments of cg05575921 methylation are a potentially powerful, clinically implementable tool for the assessment and management of smoking.

Ten Years of EWAS

Epigenome-wide association study (EWAS) has been applied to analyze DNA methylation variation in complex diseases for a decade, and epigenome as a research target has gradually become a hot topic of current studies. The DNA methylation microarrays, next-generation, and third-generation sequencing technologies have prepared a high-quality platform for EWAS. Here, the progress of EWAS research is reviewed, its contributions to clinical applications, and mainly describe the achievements of four typical diseases. Finally, the challenges encountered by EWAS and make bold predictions for its future development are presented.

2dFDR: a new approach to confounder adjustment substantially increases detection power in omics association studies

One challenge facing omics association studies is the loss of statistical power when adjusting for confounders and multiple testing. The traditional statistical procedure involves fitting a confounder-adjusted regression model for each omics feature, followed by multiple testing correction. Here we show that the traditional procedure is not optimal and present a new approach, 2dFDR, a two-dimensional false discovery rate control procedure, for powerful confounder adjustment in multiple testing. Through extensive evaluation, we demonstrate that 2dFDR is more powerful than the traditional procedure, and in the presence of strong confounding and weak signals, the power improvement could be more than 100%.

DNA Methylation in Babies Born to Nonsmoking Mothers Exposed to Secondhand Smoke during Pregnancy: An Epigenome-Wide Association Study

BACKGROUND

Maternal smoking during pregnancy is related to altered DNA methylation in infant umbilical cord blood. The extent to which low levels of smoke exposure among nonsmoking pregnant women relates to offspring DNA methylation is unknown.

OBJECTIVE

This study sought to evaluate relationships between maternal prenatal plasma cotinine levels and DNA methylation in umbilical cord blood in newborns using the Infinium HumanMethylation 450K BeadChip.

METHODS

Participants from the Newborn Epigenetics Study cohort who reported not smoking during pregnancy had verified low levels of cotinine from maternal prenatal plasma (0 ng / mL to < 4  ng / mL ), and offspring epigenetic data from umbilical cord blood were included in this study (n = 79 ). Multivariable linear regression models were fit to the data, controlling for cell proportions, age, race, education, and parity. Estimates represent changes in response to any 1 -ng / mL unit increase in exposure.

RESULTS

Multivariable linear regression models yielded 29,049 CpGs that were differentially methylated in relation to increases in cotinine at a 5% false discovery rate. Top CpGs were within or near genes involved in neuronal functioning (PRKG1, DLGAP2, BSG), carcinogenesis (FHIT, HSPC157) and inflammation (AGER). Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses suggest cotinine was related to methylation of gene pathways controlling neuronal signaling, metabolic regulation, cell signaling and regulation, and cancer. Further, enhancers associated with transcription start sites were enriched in altered CpGs. Using an independent sample from the same study population (n = 115 ), bisulfite pyrosequencing was performed with infant cord blood DNA for two genes within our top 20 hits (AGER and PRKG1). Results from pyrosequencing replicated epigenome results for PRKG1 (cg17079497, estimate = - 1.09 , standard error  ( SE ) = 0.45 , p = 0.018 ) but not for AGER (cg09199225; estimate = - 0.16 , SE = 0.21 , p = 0.44 ).

DISCUSSION

Secondhand smoke exposure among nonsmoking women may alter DNA methylation in regions involved in development, carcinogenesis, and neuronal functioning. These novel findings suggest that even low levels of smoke exposure during pregnancy may be sufficient to alter DNA methylation in distinct sites of mixed umbilical cord blood leukocytes in pathways that are known to be altered in cord blood from pregnant active smokers. https://doi.org/10.1289/EHP8099.

Prediction of biological age and evaluation of genome-wide dynamic methylomic changes throughout human aging

The use of DNA methylation signatures to predict chronological age and aging rate is of interest in many fields, including disease prevention and treatment, forensics, and anti-aging medicine. Although a large number of methylation markers are significantly associated with age, most age-prediction methods use a few markers selected based on either previously published studies or datasets containing methylation information. Here, we implemented reproducing kernel Hilbert spaces (RKHS) regression and a ridge regression model in a Bayesian framework that utilized phenotypic and methylation profiles simultaneously to predict chronological age. We used over 450,000 CpG sites from the whole blood of a large cohort of 4,409 human individuals with a range of 10-101 years of age. Models were fitted using adjusted and un-adjusted methylation measurements for cell heterogeneity. Un-adjusted methylation scores delivered a significantly higher prediction accuracy than adjusted methylation data, with a correlation between age and predicted age of 0.98 and a root-mean-square error (RMSE) of 3.54 years in un-adjusted data, and 0.90 (correlation) and 7.16 (RMSE) years in adjusted data. Reducing the number of predictors (CpG sites) through subset selection improved predictive power with a correlation of 0.98 and an RMSE of 2.98 years in the RKHS model. We found distinct global methylation patterns, with a significant increase in the proportion of methylated cytosines in CpG islands and a decreased proportion in other CpG types, including CpG shore, shelf, and open sea (p < 5e-06). Epigenetic drift seemed to be a widespread phenomenon as more than 97% of the age-associated methylation sites had heteroscedasticity. Apparent methylomic aging rate (AMAR) had a sex-specific pattern, with an increase in AMAR in females with age related to males.

Mining the Selective Remodeling of DNA Methylation in Promoter Regions to Identify Robust Gene-Level Associations With Phenotype

Epigenetics is an essential biological frontier linking genetics to the environment, where DNA methylation is one of the most studied epigenetic events. In recent years, through the epigenome-wide association study (EWAS), researchers have identified thousands of phenotype-related methylation sites. However, the overlaps of identified phenotype-related DNA methylation sites between various studies are often quite small, and it might be due to the fact that methylation remodeling has a certain degree of randomness within the genome. Thus, the identification of robust gene-phenotype associations is crucial to interpreting pathogenesis. How to integrate the methylation values of different sites on the same gene and to mine the DNA methylation at the gene level remains a challenge. A recent study found that the DNA methylation difference of the gene body and promoter region has a strong correlation with gene expression. In this study, we proposed a Statistical difference of DNA Methylation between Promoter and Other Body Region (SIMPO) algorithm to extract DNA methylation values at the gene level. First, by choosing to smoke as an environmental exposure factor, our method led to significant improvements in gene overlaps (from 5 to 17%) between different datasets. In addition, the biological significance of phenotype-related genes identified by SIMPO algorithm is comparable to that of the traditional probe-based methods. Then, we selected two disease contents (e.g., insulin resistance and Parkinson's disease) to show that the biological efficiency of disease-related gene identification increased from 15.43 to 44.44% (p-value = 1.20e-28). In summary, our results declare that mining the selective remodeling of DNA methylation in promoter regions can identify robust gene-level associations with phenotype, and the characteristic remodeling of a given gene's promoter region can reflect the essence of disease.

Cigarette smoke-induced alterations in blood: A review of research on DNA methylation and gene expression

Worldwide, smoking remains a threat to public health, causing preventable diseases and premature mortality. Cigarette smoke is a powerful inducer of DNA methylation and gene expression alterations, which have been associated with negative health consequences. Here, we review the current knowledge on smoking-related changes in DNA methylation and gene expression in human blood samples. We identified 30 studies focused on the association between active smoking, DNA methylation modifications, and gene expression alterations. Overall, we identified 1,758 genes with differentially methylated sites (DMS) and differentially expressed genes (DEG) between smokers and nonsmokers, of which 261 were detected in multiple studies (≥4). The most frequently (≥10 studies) reported genes were AHRR, GPR15, GFI1, and RARA. Functional enrichment analysis of the 261 genes identified the aryl hydrocarbon receptor repressor and T cell pathways (T helpers 1 and 2) as influenced by smoking status. These results highlight specific genes for future mechanistic and translational research that may be associated with cigarette smoke exposure and smoking-related diseases. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

A dynamic recursive feature elimination framework (dRFE) to further refine a set of OMIC biomarkers

MOTIVATION

A feature selection algorithm may select the subset of features with the best associations with the class labels. The recursive feature elimination (RFE) is a heuristic feature screening framework and has been widely used to select the biological OMIC biomarkers. This study proposed a dynamic recursive feature elimination (dRFE) framework with more flexible feature elimination operations. The proposed dRFE was comprehensively compared with 11 existing feature selection algorithms and five classifiers on the eight difficult transcriptome datasets from a previous study, the ten newly collected transcriptome datasets and the five methylome datasets.

RESULTS

The experimental data suggested that the regular RFE framework did not perform well, and dRFE outperformed the existing feature selection algorithms in most cases. The dRFE-detected features achieved Acc=1.0000 for the two methylome datasets GSE53045 and GSE66695. The best prediction accuracies of the dRFE-detected features were 0.9259, 0.9424, and 0.8601 for the other three methylome datasets GSE74845, GSE103186, and GSE80970, respectively. Four transcriptome datasets received Acc=1.0000 using the dRFE-detected features, and the prediction accuracies for the other six newly collected transcriptome datasets were between 0.6301 and 0.9917.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Epigenetic signatures underlying inflammation: an interplay of nutrition, physical activity, metabolic diseases, and environmental factors for personalized nutrition

AIM AND OBJECTIVE

Emerging translational evidence suggests that epigenetic alterations (DNA methylation, miRNA expression, and histone modifications) occur after external stimuli and may contribute to exacerbated inflammation and the risk of suffering several diseases including diabetes, cardiovascular diseases, cancer, and neurological disorders. This review summarizes the current knowledge about the harmful effects of high-fat/high-sugar diets, micronutrient deficiencies (folate, manganese, and carotenoids), obesity and associated complications, bacterial/viral infections, smoking, excessive alcohol consumption, sleep deprivation, chronic stress, air pollution, and chemical exposure on inflammation through epigenetic mechanisms. Additionally, the epigenetic phenomena underlying the anti-inflammatory potential of caloric restriction, n-3 PUFA, Mediterranean diet, vitamin D, zinc, polyphenols (i.e., resveratrol, gallic acid, epicatechin, luteolin, curcumin), and the role of systematic exercise are discussed.

METHODS

Original and review articles encompassing epigenetics and inflammation were screened from major databases (including PubMed, Medline, Science Direct, Scopus, etc.) and analyzed for the writing of the review paper.

CONCLUSION

Although caution should be exercised, research on epigenetic mechanisms is contributing to understand pathological processes involving inflammatory responses, the prediction of disease risk based on the epigenotype, as well as the putative design of therapeutic interventions targeting the epigenome.

Sex-specific effects of in utero and adult tobacco smoke exposure

Tobacco smoke has harmful effects on a multiorgan level. Exposure to smoke, whether in utero or environmental, significantly increases susceptibility. This susceptibility has been identified to be divergent between males and females. However, there remains a distinct lack of thorough research into the relationship between sex and exposure to tobacco. Females tend to generate a more significant response than males during adulthood exposure. The intrauterine environment is meticulously controlled, and exposure to tobacco presents a significant factor that contributes to poor health outcomes and susceptibility later in life. Analysis of these effects in relation to the sex of the offspring is yet to be holistically reviewed and summarized. In this review, we will delineate the time-dependent relationship between tobacco smoke exposure and sex-specific disease susceptibility. We further outline possible biological mechanisms that may contribute to the identified pattern.

DNA Methylation Markers in Lung Cancer

Lung cancer is the most common cancer and the leading cause of cancer-related morbidity and mortality worldwide. As early symptoms of lung cancer are minimal and non-specific, many patients are diagnosed at an advanced stage. Despite a concerted effort to diagnose lung cancer early, no biomarkers that can be used for lung cancer screening and prognosis prediction have been established so far. As global DNA demethylation and gene-specific promoter DNA methylation are present in lung cancer, DNA methylation biomarkers have become a major area of research as potential alternative diagnostic methods to detect lung cancer at an early stage. This review summarizes the emerging DNA methylation changes in lung cancer tumorigenesis, focusing on biomarkers for early detection and their potential clinical applications in lung cancer.

A comprehensive comparison of residue-level methylation levels with the regression-based gene-level methylation estimations by ReGear

MOTIVATION

DNA methylation is a biological process impacting the gene functions without changing the underlying DNA sequence. The DNA methylation machinery usually attaches methyl groups to some specific cytosine residues, which modify the chromatin architectures. Such modifications in the promoter regions will inactivate some tumor-suppressor genes. DNA methylation within the coding region may significantly reduce the transcription elongation efficiency. The gene function may be tuned through some cytosines are methylated.

METHODS

This study hypothesizes that the overall methylation level across a gene may have a better association with the sample labels like diseases than the methylations of individual cytosines. The gene methylation level is formulated as a regression model using the methylation levels of all the cytosines within this gene. A comprehensive evaluation of various feature selection algorithms and classification algorithms is carried out between the gene-level and residue-level methylation levels.

RESULTS

A comprehensive evaluation was conducted to compare the gene and cytosine methylation levels for their associations with the sample labels and classification performances. The unsupervised clustering was also improved using the gene methylation levels. Some genes demonstrated statistically significant associations with the class label, even when no residue-level methylation features have statistically significant associations with the class label. So in summary, the trained gene methylation levels improved various methylome-based machine learning models. Both methodology development of regression algorithms and experimental validation of the gene-level methylation biomarkers are worth of further investigations in the future studies. The source code, example data files and manual are available at http://www.healthinformaticslab.org/supp/.

Smoking-Related DNA Methylation is Differentially Associated with Cadmium Concentration in Blood

Tobacco smoking, a risk factor for several human diseases, can lead to alterations in DNA methylation. Smoking is a key source of cadmium exposure; however, there are limited studies examining DNA methylation alterations following smoking-related cadmium exposure. To identify such cadmium exposure-related DNA methylation, we performed genome-wide DNA methylation profiling using DNA samples from 50 smokers and 50 non-smokers. We found that a total of 136 CpG sites (including 70 unique genes) were significantly differentially methylated in smokers as compared to that in non-smokers. The CpG site cg05575921 in the AHRR gene was hypomethylated (Δ ß >  - 0.2) in smokers, which was in accordance with previous studies. The rs951295 (within RNA gene LOC105370802) and cg00587941 sites were under-methylated by > 15% in smokers, whereas cg11314779 (within CELF6) and cg02126896 were over-methylated by ≥ 15%. We analyzed the association between blood cadmium concentration and DNA methylation level for 50 smokers and 50 non-smokers. DNA methylation rates of 307 CpG sites (including 207 unique genes) were significantly correlated to blood cadmium concentration (linear regression P value < 0.001). The four significant loci (cg05575921 and cg23576855 in AHRR, cg03636183 in F2RL3, and cg21566642) were under-methylated by > 10% in smokers compared to that in non-smokers. In conclusion, our study demonstrated that DNA methylation levels of rs951295, cg00587941, cg11314779, and cg02126896 sites may be new putative indicators of smoking status. Furthermore, we showed that these four loci may be differentially methylated by cadmium exposure due to smoking.

Epigenetic measures of ageing predict the prevalence and incidence of leading causes of death and disease burden

BACKGROUND

Individuals of the same chronological age display different rates of biological ageing. A number of measures of biological age have been proposed which harness age-related changes in DNA methylation profiles. These measures include five 'epigenetic clocks' which provide an index of how much an individual's biological age differs from their chronological age at the time of measurement. The five clocks encompass methylation-based predictors of chronological age (HorvathAge, HannumAge), all-cause mortality (DNAm PhenoAge, DNAm GrimAge) and telomere length (DNAm Telomere Length). A sixth epigenetic measure of ageing differs from these clocks in that it acts as a speedometer providing a single time-point measurement of the pace of an individual's biological ageing. This measure of ageing is termed DunedinPoAm. In this study, we test the association between these six epigenetic measures of ageing and the prevalence and incidence of the leading causes of disease burden and mortality in high-income countries (n ≤ 9537, Generation Scotland: Scottish Family Health Study).

RESULTS

DNAm GrimAge predicted incidence of clinically diagnosed chronic obstructive pulmonary disease (COPD), type 2 diabetes and ischemic heart disease after 13 years of follow-up (hazard ratios = 2.22, 1.52 and 1.41, respectively). DunedinPoAm predicted the incidence of COPD and lung cancer (hazard ratios = 2.02 and 1.45, respectively). DNAm PhenoAge predicted incidence of type 2 diabetes (hazard ratio = 1.54). DNAm Telomere Length associated with the incidence of ischemic heart disease (hazard ratio = 0.80). DNAm GrimAge associated with all-cause mortality, the prevalence of COPD and spirometry measures at the study baseline. These associations were present after adjusting for possible confounding risk factors including alcohol consumption, body mass index, deprivation, education and tobacco smoking and surpassed stringent Bonferroni-corrected significance thresholds.

CONCLUSIONS

Our data suggest that epigenetic measures of ageing may have utility in clinical settings to complement gold-standard methods for disease assessment and management.

Multi-method genome- and epigenome-wide studies of inflammatory protein levels in healthy older adults

BACKGROUND

The molecular factors which control circulating levels of inflammatory proteins are not well understood. Furthermore, association studies between molecular probes and human traits are often performed by linear model-based methods which may fail to account for complex structure and interrelationships within molecular datasets.

METHODS

In this study, we perform genome- and epigenome-wide association studies (GWAS/EWAS) on the levels of 70 plasma-derived inflammatory protein biomarkers in healthy older adults (Lothian Birth Cohort 1936; n = 876; Olink® inflammation panel). We employ a Bayesian framework (BayesR+) which can account for issues pertaining to data structure and unknown confounding variables (with sensitivity analyses using ordinary least squares- (OLS) and mixed model-based approaches).

RESULTS

We identified 13 SNPs associated with 13 proteins (n = 1 SNP each) concordant across OLS and Bayesian methods. We identified 3 CpG sites spread across 3 proteins (n = 1 CpG each) that were concordant across OLS, mixed-model and Bayesian analyses. Tagged genetic variants accounted for up to 45% of variance in protein levels (for MCP2, 36% of variance alone attributable to 1 polymorphism). Methylation data accounted for up to 46% of variation in protein levels (for CXCL10). Up to 66% of variation in protein levels (for VEGFA) was explained using genetic and epigenetic data combined. We demonstrated putative causal relationships between CD6 and IL18R1 with inflammatory bowel disease and between IL12B and Crohn's disease.

CONCLUSIONS

Our data may aid understanding of the molecular regulation of the circulating inflammatory proteome as well as causal relationships between inflammatory mediators and disease.

Array-Based Epigenetic Aging Indices May Be Racially Biased

Epigenetic aging (EA) indices are frequently used as predictors of mortality and other important health outcomes. However, each of the commonly used array-based indices has significant heritable components which could tag ethnicity and potentially confound comparisons across racial and ethnic groups. To determine if this was possible, we examined the relationship of DNA methylation in cord blood from 203 newborns (112 African American (AA) and 91 White) at the 513 probes from the Levine PhenoAge Epigenetic Aging index to ethnicity. Then, we examined all sites significantly associated with race in the newborn sample to determine if they were also associated with an index of ethnic genetic heritage in a cohort of 505 AA adults. After Bonferroni correction, methylation at 50 CpG sites was significantly associated with ethnicity in the newborn cohort. The five most significant sites predicted ancestry with a receiver operator characteristic area under the curve of 0.97. Examination of the top 50 sites in the AA adult cohort showed that methylation status at 11 of those sites was also associated with percentage European ancestry. We conclude that the Levine PhenoAge Index is influenced by cryptic ethnic-specific genetic influences. This influence may extend to similarly constructed EA indices and bias cross-race comparisons.

Smoking May Affect Pulmonary Function through DNA Methylation: an Epigenome-Wide Association Study in Korean Men

Smoking is a risk factor for various disease outcomes and is one of the modifiers of DNA methylation. We aimed to identify smoking-related DNA methylation sites (CpG-sites) and test whether one identified CpG-site is associated with smoking-related traits and pulmonary function. We obtained DNA methylation data of 209 men from the Korean Genome and Epidemiology Study analyzed by Illumina's HumanMethylation450 array. To identify smoking-related DNA methylation sites, epigenome-wide association analysis of smoking status was conducted, adjusting for age, area, current drinking status, and body mass index. We assessed the association between smoking intensity and DNA methylation of cg05951221 (AHRR), the CpG showing the strongest largest difference in DNA methylation among the 5 hypomethylated CpGs in current smokers compared to never smokers. The association between DNA methylation and pulmonary function was examined longitudinally resulting in a positive association between DNA methylation and forced expiratory volume in 1 second/forced vital capacity, regardless of adjustment for smoking status. This suggests that DNA methylation associates with long-term pulmonary function. Our study contributes to explaining the relationship between smoking and pulmonary function via DNA methylation.

DNA Methylation Signature for EZH2 Functionally Classifies Sequence Variants in Three PRC2 Complex Genes

Weaver syndrome (WS), an overgrowth/intellectual disability syndrome (OGID), is caused by pathogenic variants in the histone methyltransferase EZH2, which encodes a core component of the Polycomb repressive complex-2 (PRC2). Using genome-wide DNA methylation (DNAm) data for 187 individuals with OGID and 969 control subjects, we show that pathogenic variants in EZH2 generate a highly specific and sensitive DNAm signature reflecting the phenotype of WS. This signature can be used to distinguish loss-of-function from gain-of-function missense variants and to detect somatic mosaicism. We also show that the signature can accurately classify sequence variants in EED and SUZ12, which encode two other core components of PRC2, and predict the presence of pathogenic variants in undiagnosed individuals with OGID. The discovery of a functionally relevant signature with utility for diagnostic classification of sequence variants in EZH2, EED, and SUZ12 supports the emerging paradigm shift for implementation of DNAm signatures into diagnostics and translational research.

Patterns of Reliability: Assessing the Reproducibility and Integrity of DNA Methylation Measurement

DNA methylation plays an important role in both normal human development and risk of disease. The most utilized method of assessing DNA methylation uses BeadChips, generating an epigenome-wide “snapshot” of >450,000 observations (probe measurements) per assay. However, the reliability of each of these measurements is not equal, and little consideration is paid to consequences for research. We correlated repeat measurements of the same DNA samples using the Illumina HumanMethylation450K and the Infinium MethylationEPIC BeadChips in 350 blood DNA samples. Probes that were reliably measured were more heritable and showed consistent associations with environmental exposures, gene expression, and greater cross-tissue concordance. Unreliable probes were less replicable and generated an unknown volume of false negatives. This serves as a lesson for working with DNA methylation data, but the lessons are equally applicable to working with other data: as we advance toward generating increasingly greater volumes of data, failure to document reliability risks harming reproducibility.

•

Measurements of DNA methylation made using BeadChip probes are differentially reliable

•

Unreliable probes were less heritable, less replicable, and less functionally relevant

•

This has serious implications for reporting and evaluating DNA methylation findings

•

Reliability joins replicability and reproducibility to make three fundamental Rs of STEM

Although DNA methylation data are used widely by researchers in many fields, the reliability of these data are surprisingly variable. Our findings remind us that, in an age of increasingly big data, research is only as robust as its foundations. We hope that our findings will improve the integrity of DNA methylation studies. We also hope that our findings serve as a cautionary reminder for those generating and implementing big data of any type: reliability is a fundamental aspect of replicability. Conducting analysis with reliable data will improve chances of replicable findings, which might lead to more actionable targets for further research. To the extent that reliable data improve replicability, the knock-on effect will be more public confidence in research and less effort spent trying to replicate findings that are bound to fail.

Smoking and blood DNA methylation: an epigenome-wide association study and assessment of reversibility

We conducted a genome-wide association study of blood DNA methylation and smoking, attempted replication of previously discovered associations, and assessed the reversibility of smoking-associated methylation changes. DNA methylation was measured in baseline peripheral blood samples for 5,044 participants in the Melbourne Collaborative Cohort Study. For 1,032 participants, these measures were repeated using blood samples collected at follow-up, a median of 11 years later. A cross-sectional analysis of the association between smoking and DNA methylation and a longitudinal analysis of changes in smoking status and changes in DNA methylation were conducted. We used our cross-sectional analysis to replicate previously reported associations for current (N = 3,327) and former (N = 172) smoking. A comprehensive smoking index accounting for the biological half-life of smoking compounds and several aspects of smoking history was constructed to assess the reversibility of smoking-induced methylation changes. This measure of lifetime exposure to smoking allowed us to detect more associations than comparing current with never smokers. We identified 4,496 cross-sectional associations at P < 10-7, including 3,296 annotated to 1,326 genes that were not previously implicated in smoking-associated DNA methylation changes at this significance threshold. We replicated the majority of previously reported associations (P < 10-7) for current and former smokers. In our data, we observed for former smokers a substantial degree of return to the methylation levels of never smokers, compared with current smokers (median: 74%, IQR = 63-86%), corresponding to small values (median: 2.75, IQR = 1.5-5.25) for the half-life parameter of the comprehensive smoking index. Longitudinal analyses identified 368 sites at which methylation changed upon smoking cessation. Our study demonstrates the usefulness of the comprehensive smoking index to detect associations between smoking and DNA methylation at CpGs across the genome, replicates the vast majority of previously reported associations, and quantifies the reversibility of smoking-induced methylation changes.

The Effect of Tobacco Smoking Differs across Indices of DNA Methylation-Based Aging in an African American Sample: DNA Methylation-Based Indices of Smoking Capture These Effects

Smoking is one of the leading preventable causes of morbidity and mortality worldwide, prompting interest in its association with DNA methylation-based measures of biological aging. Considerable progress has been made in developing DNA methylation-based measures that correspond to self-reported smoking status. In addition, assessment of DNA methylation-based aging has been expanded to better capture individual differences in risk for morbidity and mortality. Untested to date, however, is whether smoking is similarly related to older and newer indices of DNA methylation-based aging, and whether DNA methylation-based indices of smoking can be used in lieu of self-reported smoking to examine effects on DNA methylation-based aging measures. In the current investigation we examine mediation of the impact of self-reported cigarette consumption on accelerated, intrinsic DNA methylation-based aging using indices designed to predict chronological aging, phenotypic aging, and mortality risk, as well as a newly developed DNA methylation-based measure of telomere length. Using a sample of 500 African American middle aged smokers and non-smokers, we found that a) self-reported cigarette consumption was associated with accelerated intrinsic DNA methylation-based aging on some but not all DNA methylation-based aging indices, b) for those aging outcomes associated with self-reported cigarette consumption, DNA methylation-based indicators of smoking typically accounted for greater variance than did self-reported cigarette consumption, and c) self-reported cigarette consumption effects on DNA methylation-based aging indices typically were fully mediated by DNA methylation-based indicators of smoking (e.g., PACKYRS from GrimAge; or cg05575921 CpG site). Results suggest that when DNA methylation-based indices of smoking are substituted for self-reported assessments of smoking, they will typically fully reflect the varied impact of cigarette smoking on intrinsic, accelerated DNA methylation-based aging.

Cigarette and Cannabis Smoking Effects on GPR15+ Helper T Cell Levels in Peripheral Blood: Relationships with Epigenetic Biomarkers

Background: Smoking causes widespread epigenetic changes that have been linked with an increased risk of smoking-associated diseases and elevated mortality. Of particular interest are changes in the level of T cells expressing G-protein-coupled receptor 15 (GPR15), a chemokine receptor linked with multiple autoimmune diseases, including inflammatory bowel disease, multiple sclerosis and psoriasis. Accordingly, a better understanding of the mechanisms by which smoking influences variation in the GPR15+ helper T cell subpopulation is of potential interest. Methods: In the current study, we used flow cytometry and digital PCR assays to measure the GPR15+CD3+CD4+ populations in peripheral blood from a cohort of n = 62 primarily African American young adults (aged 27–35 years) with a high rate of tobacco and cannabis use. Results: We demonstrated that self-reported tobacco and cannabis smoking predict GPR15⁺CD3⁺CD4⁺ helper T cell levels using linear regression models. Further, we demonstrated that methylation of two candidate CpGs, cg19859270, located in GPR15, and cg05575921, located in the gene Aryl Hydrocarbon Receptor Repressor (AHRR), were both significant predictors of GPR15⁺CD3⁺CD4⁺ cell levels, mediating the relationship between smoking habits and increases in GPR15⁺CD3⁺CD4⁺ cells. As hypothesized, the interaction between cg05575921 and cg19859270 was also significant, indicating that low cg05575921 methylation was more strongly predictive of GPR15⁺CD3⁺CD4⁺ cell levels for those who also had lower cg19859270 methylation. Conclusions: Smoking leads changes in two CpGs, cg05575921 and cg19859270, that mediate 38.5% of the relationship between tobacco and cannabis smoking and increased GPR15⁺ T_h levels in this sample. The impact of cg19859270 in amplifying the association between cg05575921 and increased GPR15⁺ T_h levels is of potential theoretical interest given the possibility that it reflects a permissive interaction between different parts of the adaptive immune system.

Relationship of Cigarette Smoking and Alcohol Consumption to Incidence of Systemic Lupus Erythematosus in a Prospective Cohort Study of Black Women

OBJECTIVE

Systemic lupus erythematosus (SLE) affects black women more frequently than other racial/gender groups. In past studies, largely consisting of white and Asian cohorts, cigarette smoking was associated with increased SLE risk, and moderate alcohol consumption was associated with decreased SLE risk. The aim of this study was to assess associations of smoking and alcohol consumption with the risk of incident SLE among black women, using data from a long-term, prospective, follow-up study.

METHODS

The Black Women's Health Study enrolled 59,000 black women in 1995 and collected data on demographics, health status, and medical and lifestyle variables. Follow-up questionnaires that were given every 2 years identified incident disease and updated risk factors. Cases of incident SLE that met the American College of Rheumatology revised criteria for SLE as updated in 1997 were confirmed through medical record review. Cox regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (95% CI) for associations of cigarette smoking and alcohol intake with incidence of SLE.

RESULTS

A total of 127 incident SLE cases from 1995 to 2015 (mean age 43 years at diagnosis) were confirmed. Compared to never smokers, the risk of SLE among ever smokers was elevated, but not significantly (HR 1.45 [95% CI 0.97-2.18]). Risk was similar for current and past smoking and increased nonsignificantly with increasing pack-years. The HR was 0.71 (95% CI 0.45-1.12) for current drinking relative to never drinking, with a HR of 0.43 (95% CI 0.19-0.96) for ≥4 drinks/week.

CONCLUSION

Findings from this large study of SLE risk among black women are consistent with previous results from studies in other populations of increased risk of SLE associated with cigarette smoking and decreased risk with moderate alcohol consumption.

AHRR methylation predicts smoking status and smoking intensity in both saliva and blood DNA

Many existing DNA repositories do not have robust characterizations of smoking, while for many currently ongoing studies, the advent of vaping has rendered traditional cotinine-based methods of determining smoking status unreliable. Previously, we have shown that methylation status at cg05575921 in whole blood DNA can reliably predict cigarette consumption. However, whether methylation status in saliva can be used similarly has yet to be established. Herein, we use DNA from 418 biochemically confirmed smokers or nonsmokers to compare and contrast the utility of cg05575921 in classifying and quantifying cigarette smoking. Using whole blood DNA, a model incorporating age, gender, and methylation status had a receiver operating characteristic (ROC) area under the curve (AUC) for predicting smoking status of 0.995 with a nonlinear demethylation response to smoking. Using saliva DNA, the ROC AUC for predicting smoking was 0.971 with the plot of the relationship of DNA methylation to daily cigarette consumption being very similar to that seen for whole blood DNA. The addition of information from another methylation marker designed to correct for cellular heterogeneity improved the AUC for saliva DNA to 0.981. Finally, in 31 subjects who reported quitting smoking 10 or more years previously, cg05575921 methylation was nonsignificantly different from controls. We conclude that DNA methylation status at cg05575921 in DNA from whole blood or saliva predicts smoking status and daily cigarette consumption. We suggest these epigenetic assessments for objectively ascertaining smoking status will find utility in research, clinical, and civil applications.

The role of cigarette smoke-induced epigenetic alterations in inflammation

Background

Exposure to cigarette smoke (CS) is a major threat to human health worldwide. It is well established that smoking increases the risk of respiratory diseases, cardiovascular diseases and different forms of cancer, including lung, liver, and colon. CS-triggered inflammation is considered to play a central role in various pathologies by a mechanism that stimulates the release of pro-inflammatory cytokines. During this process, epigenetic alterations are known to play important roles in the specificity and duration of gene transcription.

Main text

Epigenetic alterations include three major modifications: DNA modifications via methylation; various posttranslational modifications of histones, namely, methylation, acetylation, phosphorylation, and ubiquitination; and non-coding RNA sequences. These modifications work in concert to regulate gene transcription in a heritable fashion. The enzymes that regulate these epigenetic modifications can be activated by smoking, which further mediates the expression of multiple inflammatory genes. In this review, we summarize the current knowledge on the epigenetic alterations triggered by CS and assess how such alterations may affect smoking-mediated inflammatory responses.

Conclusion

The recognition of the molecular mechanisms of the epigenetic changes in abnormal inflammation is expected to contribute to the understanding of the pathophysiology of CS-related diseases such that novel epigenetic therapies may be identified in the near future.

AHRR Methylation is a Significant Predictor of Mortality Risk in Framingham Heart Study

Background.-The ability to predict mortality is useful to clinicians, policy makers and insurers. At the current time, prediction of future mortality is still an inexact process with some proposing that epigenetic assessments could play a role in improving prognostics. In past work, we and others have shown that DNA methylation status at cg05575921, a well-studied measure of smoking intensity, is also a predictor of mortality. However, the exact extent of that predictive capacity and its independence of other commonly measured mortality risk factors are unknown. Objective.-To determine the capacity of methylation to predict mortality. Method.-We analyzed the relationship of methylation at cg05575921 and cg04987734, a recently described quantitative marker of heavy alcohol consumption, to mortality in the Offspring Cohort of the Framingham Heart Study using proportional hazards survival analysis. Results.-In this group of participants (n = 2278) whose average age was 66 ± 9 years, we found that the inclusion of both cg05575921 and cg04987734 methylation to a base model consisting of age and sex only, or to a model containing 11 commonly used mortality risk factors, improved risk prediction. What is more, prediction accuracy for the base model plus methylation data was increased compared to the base model plus known predictors of mortality (CHD, COPD, or stroke). Conclusion.-Cg05575921, and to a smaller extent cg04987734, are strong predictors of mortality risk in older Americans and that incorporation of DNA methylation assessments to these and other loci may be useful to population scientists, actuaries and policymakers to better understand the relationship of environmental risk factors, such as smoking and drinking, to mortality.

Epigenetic signatures of smoking associate with cognitive function, brain structure, and mental and physical health outcomes in the Lothian Birth Cohort 1936

Recent advances in genome-wide DNA methylation (DNAm) profiling for smoking behaviour have given rise to a new, molecular biomarker of smoking exposure. It is unclear whether a smoking-associated DNAm (epigenetic) score has predictive value for ageing-related health outcomes which is independent of contributions from self-reported (phenotypic) smoking measures. Blood DNA methylation levels were measured in 895 adults aged 70 years in the Lothian Birth Cohort 1936 (LBC1936) study using the Illumina 450K assay. A DNA methylation score based on 230 CpGs was used as a proxy for smoking exposure. Associations between smoking variables and health outcomes at age 70 were modelled using general linear modelling (ANCOVA) and logistic regression. Additional analyses of smoking with brain MRI measures at age 73 (n = 532) were performed. Smoking-DNAm scores were positively associated with self-reported smoking status (P < 0.001, eta-squared ɳ2 = 0.63) and smoking pack years (r = 0.69, P < 0.001). Higher smoking DNAm scores were associated with variables related to poorer cognitive function, structural brain integrity, physical health, and psychosocial health. Compared with phenotypic smoking, the methylation marker provided stronger associations with all of the cognitive function scores, especially visuospatial ability (P < 0.001, partial eta-squared ɳp2 = 0.022) and processing speed (P < 0.001, ɳp2 = 0.030); inflammatory markers (all P < 0.001, ranges from ɳp2 = 0.021 to 0.030); dietary patterns (healthy diet (P < 0.001, ɳp2 = 0.052) and traditional diet (P < 0.001, ɳp2 = 0.032); stroke (P = 0.006, OR 1.48, 95% CI 1.12, 1.96); mortality (P < 0.001, OR 1.59, 95% CI 1.42, 1.79), and at age 73; with MRI volumetric measures (all P < 0.001, ranges from ɳp2 = 0.030 to 0.052). Additionally, education was the most important life-course predictor of lifetime smoking tested. Our results suggest that a smoking-associated methylation biomarker typically explains a greater proportion of the variance in some smoking-related morbidities in older adults, than phenotypic measures of smoking exposure, with some of the accounted-for variance being independent of phenotypic smoking status.

A systematic review of smoking-related epigenetic alterations

The aim of this study is to provide a systematic review of the known epigenetic alterations caused by cigarette smoke; establish an evidence-based perspective of their clinical value for screening, diagnosis, and treatment of smoke-related disorders; and discuss the challenges and ethical concerns associated with epigenetic studies. A well-defined, reproducible search strategy was employed to identify relevant literature (clinical, cellular, and animal-based) between 2000 and 2019 based on AMSTAR guidelines. A total of 80 studies were identified that reported alterations in DNA methylation, histone modifications, and miRNA expression following exposure to cigarette smoke. Changes in DNA methylation were most extensively documented for genes including AHRR, F2RL3, DAPK, and p16 after exposure to cigarette smoke. Likewise, miR16, miR21, miR146, and miR222 were identified to be differentially expressed in smokers and exhibit potential as biomarkers for determining susceptibility to COPD. We also identified 22 studies highlighting the transgenerational effects of maternal and paternal smoking on offspring. This systematic review lists the epigenetic events/alterations known to occur in response to cigarette smoke exposure and identifies the major genes and miRNAs that are potential targets for translational research in associated pathologies. Importantly, the limitations and ethical concerns related to epigenetic studies are also highlighted, as are the effects on the ability to address specific questions associated with exposure to tobacco/cigarette smoke. In the future, improved interpretation of epigenetic signatures will lead to their increased use as biomarkers and/or in drug development.

Validated inference of smoking habits from blood with a finite DNA methylation marker set

Inferring a person’s smoking habit and history from blood is relevant for complementing or replacing self-reports in epidemiological and public health research, and for forensic applications. However, a finite DNA methylation marker set and a validated statistical model based on a large dataset are not yet available. Employing 14 epigenome-wide association studies for marker discovery, and using data from six population-based cohorts (N = 3764) for model building, we identified 13 CpGs most suitable for inferring smoking versus non-smoking status from blood with a cumulative Area Under the Curve (AUC) of 0.901. Internal fivefold cross-validation yielded an average AUC of 0.897 ± 0.137, while external model validation in an independent population-based cohort (N = 1608) achieved an AUC of 0.911. These 13 CpGs also provided accurate inference of current (average AUC_{crossvalidation} 0.925 ± 0.021, AUC_{externalvalidation}0.914), former (0.766 ± 0.023, 0.699) and never smoking (0.830 ± 0.019, 0.781) status, allowed inferring pack-years in current smokers (10 pack-years 0.800 ± 0.068, 0.796; 15 pack-years 0.767 ± 0.102, 0.752) and inferring smoking cessation time in former smokers (5 years 0.774 ± 0.024, 0.760; 10 years 0.766 ± 0.033, 0.764; 15 years 0.767 ± 0.020, 0.754). Model application to children revealed highly accurate inference of the true non-smoking status (6 years of age: accuracy 0.994, N = 355; 10 years: 0.994, N = 309), suggesting prenatal and passive smoking exposure having no impact on model applications in adults. The finite set of DNA methylation markers allow accurate inference of smoking habit, with comparable accuracy as plasma cotinine use, and smoking history from blood, which we envision becoming useful in epidemiology and public health research, and in medical and forensic applications.