Appraising the causal relevance of DNA methylation for risk of lung cancer

IARC Workshop on the Key Characteristics of Carcinogens: Assessment of End Points for Evaluating Mechanistic Evidence of Carcinogenic Hazards

BACKGROUND

The 10 key characteristics (KCs) of carcinogens form the basis of a framework to identify, organize, and evaluate mechanistic evidence relevant to carcinogenic hazard identification. The 10 KCs are related to mechanisms by which carcinogens cause cancer. The International Agency for Research on Cancer (IARC) Monographs programme has successfully applied the KCs framework for the mechanistic evaluation of different types of exposures, including chemicals, metals, and complex exposures, such as environmental, occupational, or dietary exposures. The use of this framework has significantly enhanced the identification and organization of relevant mechanistic data, minimized bias in evaluations, and enriched the knowledge base regarding the mechanisms of known and suspected carcinogens.

OBJECTIVES

We sought to report the main outcomes of an IARC Scientific Workshop convened by the IARC to establish appropriate, transparent, and uniform application of the KCs in future IARC Monographs evaluations.

METHODS

A group of experts from different disciplines reviewed the IARC Monographs experience with the KCs of carcinogens, discussing three main themes: a) the interpretation of end points forming the evidence base for the KCs, b) the incorporation of data from novel assays on the KCs, and c) the integration of the mechanistic evidence as part of cancer hazard identification. The workshop participants assessed the relevance and the informativeness of multiple KCs-associated end points for the evaluation of mechanistic evidence in studies of exposed humans and experimental systems.

DISCUSSION

Consensus was reached on how to enhance the use of in silico, molecular, and cellular high-output and high-throughput data. In addition, approaches to integrate evidence across the KCs and opportunities to improve methodologies of mechanistic evaluation of cancer hazards were explored. The findings described herein and in a forthcoming IARC technical report will support future working groups of experts in reporting and interpreting results under the KCs framework within the IARC Monographs or in other contexts. https://doi.org/10.1289/EHP15389.

Proteome-Wide Multicenter Mendelian Randomization Analysis to Identify Novel Therapeutic Targets for Lung Cancer

INTRODUCTION

Lung cancer (LC) remains a leading cause of cancer mortality worldwide, underscoring the urgent need for novel therapeutic targets. The integration of Mendelian randomization (MR) with proteomic data presents a novel approach to identifying potential targets for LC treatment.

METHODS

This study utilized a proteome-wide MR analysis, leveraging publicly available data from genome-wide association studies (GWAS) and protein quantitative trait loci (pQTL) studies. We analyzed genetic association data for LC from the TRICL-ILCCO Consortium and proteomic data from the Decode cohort. The MR framework was employed to estimate the causal effects of specific proteins on LC risk, supplemented by external validation, co-localization analyses, and exploration of protein-protein interaction (PPI) networks.

RESULTS

Our analysis identified five proteins (TFPI, ICAM5, SFTPB, COL6A3, EPHB1) with significant associations to LC risk. External validation confirmed the potential therapeutic relevance of ICAM5 and SFTPB. Co-localization analyses and PPI network exploration provided further insights into the biological pathways involved and their potential mechanistic roles in LC pathogenesis.

CONCLUSION

The study highlights the power of integrating genomic and proteomic data through MR analysis to uncover novel therapeutic targets for lung cancer. The identified proteins, particularly ICAM5 and SFTPB, offer promising directions for future research and development of targeted therapies, demonstrating the potential to advance personalized medicine in lung cancer treatment.

A novel hypothesis-generating approach for detecting phenotypic associations using epigenetic data

Aim: Hypotheses about what phenotypes to include in causal analyses, that in turn can have clinical and policy implications, can be guided by hypothesis-free approaches leveraging the epigenome, for example.Materials & methods: Minimally adjusted epigenome-wide association studies (EWAS) using ALSPAC data were performed for example conditions, dysmenorrhea and heavy menstrual bleeding (HMB). Differentially methylated CpGs were searched in the EWAS Catalog and associated traits identified. Traits were compared between those with and without the example conditions in ALSPAC.Results: Seven CpG sites were associated with dysmenorrhea and two with HMB. Smoking and adverse childhood experience score were associated with both conditions in the hypothesis-testing phase.Conclusion: Hypothesis-generating EWAS can help identify associations for future analyses.

Blood-based DNA methylation markers for lung cancer prediction

Objective

Screening high-risk individuals with low-dose CT reduces mortality from lung cancer, but many lung cancers occur in individuals who are not eligible for screening. Risk biomarkers may be useful to refine risk models and improve screening eligibility criteria. We evaluated if blood-based DNA methylation markers can improve a traditional lung cancer prediction model.

Methods and analysis

This study used four prospective cohorts with blood samples collected prior to lung cancer diagnosis. The study was restricted to participants with a history of smoking, and one control was individually matched to each lung cancer case using incidence density sampling by cohort, sex, date of blood collection, age and smoking status. To train a DNA methylation-based risk score, we used participants from Melbourne Collaborative Cohort Study-Australia (n=648) and Northern Sweden Health and Disease Study-Sweden (n=380) based on five selected CpG sites. The risk discriminative performance of the methylation score was subsequently validated in participants from European Investigation into Cancer and Nutrition-Italy (n=267) and Norwegian Women and Cancer-Norway (n=185) and compared with that of the questionnaire-based PLCOm2012 lung cancer risk model.

Results

The area under the receiver operating characteristic curve (AUC) for the PLCOm2012 model in the validation studies was 0.70 (95% CI: 0.65 to 0.75) compared with 0.73 (95% CI: 0.68 to 0.77) for the methylation score model (P difference=0.07). Incorporating the methylation score with the PLCOm2012 model did not improve the risk discrimination (AUC: 0.73, 95% CI: 0.68 to 0.77, P difference=0.73).

Conclusions

This study suggests that the methylation-based risk prediction score alone provides similar lung cancer risk-discriminatory performance as the questionnaire-based PLCOm2012 risk model.

Associations between immune cell phenotypes and lung cancer subtypes: insights from mendelian randomization analysis

INTRODUCTION

Lung cancer is a common malignant tumor, and different types of immune cells may have different effects on the occurrence and development of lung cancer subtypes, including lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD). However, the causal relationship between immune phenotype and lung cancer is still unclear.

METHODS

This study utilized a comprehensive dataset containing 731 immune phenotypes from the European Bioinformatics Institute (EBI) to evaluate the potential causal relationship between immune phenotypes and LUSC and LUAD using the inverse variance weighted (IVW) method in Mendelian randomization (MR). Sensitivity analyses, including MR-Egger intercept, Cochran Q test, and others, were conducted for the robustness of the results. The study results were further validated through meta-analysis using data from the Transdisciplinary Research Into Cancer of the Lung (TRICL) data. Additionally, confounding factors were excluded to ensure the robustness of the findings.

RESULTS

Among the final selection of 729 immune cell phenotypes, three immune phenotypes exhibited statistically significant effects with LUSC. CD28 expression on resting CD4 regulatory T cells (OR 1.0980, 95% CI: 1.0627-1.1344, p < 0.0001) and CD45RA + CD28- CD8 + T cell %T cell (OR 1.0011, 95% CI: 1.0007; 1.0015, p < 0.0001) were associated with increased susceptibility to LUSC. Conversely, CCR2 expression on monocytes (OR 0.9399, 95% CI: 0.9177-0.9625, p < 0.0001) was correlated with a decreased risk of LUSC. However, no significant causal relationships were established between any immune cell phenotypes and LUAD.

CONCLUSION

This study demonstrates that specific immune cell types are associated with the risk of LUSC but not with LUAD. While these findings are derived solely from European populations, they still provide clues for a deeper understanding of the immunological mechanisms underlying lung cancer and may offer new directions for future therapeutic strategies and preventive measures.

Identification of genetically predicted DNA methylation markers associated with non-small cell lung cancer risk among 34,964 cases and 448,579 controls

BACKGROUND

Although the associations between genetic variations and lung cancer risk have been explored, the epigenetic consequences of DNA methylation in lung cancer development are largely unknown. Here, the genetically predicted DNA methylation markers associated with non-small cell lung cancer (NSCLC) risk by a two-stage case-control design were investigated.

METHODS

The genetic prediction models for methylation levels based on genetic and methylation data of 1595 subjects from the Framingham Heart Study were established. The prediction models were applied to a fixed-effect meta-analysis of screening data sets with 27,120 NSCLC cases and 27,355 controls to identify the methylation markers, which were then replicated in independent data sets with 7844 lung cancer cases and 421,224 controls. Also performed was a multi-omics functional annotation for the identified CpGs by integrating genomics, epigenomics, and transcriptomics and investigation of the potential regulation pathways.

RESULTS

Of the 29,894 CpG sites passing the quality control, 39 CpGs associated with NSCLC risk (Bonferroni-corrected p ≤ 1.67 × 10-6 ) were originally identified. Of these, 16 CpGs remained significant in the validation stage (Bonferroni-corrected p ≤ 1.28 × 10-3 ), including four novel CpGs. Multi-omics functional annotation showed nine of 16 CpGs were potentially functional biomarkers for NSCLC risk. Thirty-five genes within a 1-Mb window of 12 CpGs that might be involved in regulatory pathways of NSCLC risk were identified.

CONCLUSIONS

Sixteen promising DNA methylation markers associated with NSCLC were identified. Changes of the methylation level at these CpGs might influence the development of NSCLC by regulating the expression of genes nearby.

PLAIN LANGUAGE SUMMARY

The epigenetic consequences of DNA methylation in lung cancer development are still largely unknown. This study used summary data of large-scale genome-wide association studies to investigate the associations between genetically predicted levels of methylation biomarkers and non-small cell lung cancer risk at the first time. This study looked at how well larotrectinib worked in adult patients with sarcomas caused by TRK fusion proteins. These findings will provide a unique insight into the epigenetic susceptibility mechanisms of lung cancer.

Integrated genetic and epigenetic analyses uncovered GLP1R association with metabolically healthy obesity

BACKGROUND

Both genetic and epigenetic variations of GLP1R influence the development and progression of obesity. However, the underlying mechanism remains elusive. This study aims to explore the mediation roles of obesity-related methylation sites in GLP1R gene variants-obesity association.

METHODS

A total of 300 Chinese adult participants were included in this study and classified into two groups: 180 metabolically healthy obesity (MHO) cases and 120 metabolically healthy normal-weight (MHNW) controls. Questionnaire investigation, physical measurement and laboratory examination were assessed in all participants. 18 single nucleotide polymorphisms (SNPs) and 31 CpG sites were selected for genotype and methylation assays. Causal inference test (CIT) was performed to evaluate the associations between GLP1R genetic variation, DNA methylation and MHO.

RESULTS

The study found that rs4714211 polymorphism of GLP1R gene was significantly associated with MHO. Additionally, methylation sites in the intronic region of GLP1R (GLP1R-68-CpG 7.8.9; GLP1R-68-CpG 12.13; GLP1R-68-CpG 17; GLP1R-68-CpG 21) were associated with MHO, and two of these methylation sites (GLP1R-68-CpG 7.8.9; GLP1R-68-CpG 17) partially mediated the association between genotypes and MHO.

CONCLUSIONS

Not only the gene polymorphism, but also the DNA methylation of GLP1R was associated with MHO. Epigenetic changes in the methylome may in part explain the relationship between genetic variants and MHO.

Dietary and supplemental intake of vitamins C and E is associated with altered DNA methylation in an epigenome-wide association study meta-analysis

BACKGROUND

Dietary intake of antioxidants such as vitamins C and E protect against oxidative stress, and may also be associated with altered DNA methylation patterns.

METHODS

We meta-analysed epigenome-wide association study (EWAS) results from 11,866 participants across eight population-based cohorts to evaluate the association between self-reported dietary and supplemental intake of vitamins C and E with DNA methylation. EWAS were adjusted for age, sex, BMI, caloric intake, blood cell type proportion, smoking status, alcohol consumption, and technical covariates. Significant results of the meta-analysis were subsequently evaluated in gene set enrichment analysis (GSEA) and expression quantitative trait methylation (eQTM) analysis.

RESULTS

In meta-analysis, methylation at 4,656 CpG sites was significantly associated with vitamin C intake at FDR ≤ 0.05. The most significant CpG sites associated with vitamin C (at FDR ≤ 0.01) were enriched for pathways associated with systems development and cell signalling in GSEA, and were associated with downstream expression of genes enriched in the immune response in eQTM analysis. Furthermore, methylation at 160 CpG sites was significantly associated with vitamin E intake at FDR ≤ 0.05, but GSEA and eQTM analysis of the top most significant CpG sites associated with vitamin E did not identify significant enrichment of any biological pathways investigated.

CONCLUSIONS

We identified significant associations of many CpG sites with vitamin C and E intake, and our results suggest that vitamin C intake may be associated with systems development and the immune response.

Environment factors, DNA methylation, and cancer

Today, the rapid development of science and technology and the rapid change in economy and society are changing the way of life of human beings and affecting the natural, living, working, and internal environment on which human beings depend. At the same time, the global incidence of cancer has increased significantly yearly, and cancer has become the number one killer that threatens human health. Studies have shown that diet, living habits, residential environment, mental and psychological factors, intestinal flora, genetics, social factors, and viral and non-viral infections are closely related to human cancer. However, the molecular mechanisms of the environment and cancer development remain to be further explored. In recent years, DNA methylation has become a key hub and bridge for environmental and cancer research. Some environmental factors can alter the hyper/hypomethylation of human cancer suppressor gene promoters, proto-oncogene promoters, and the whole genome, causing low/high expression or gene mutation of related genes, thereby exerting oncogenic or anticancer effects. It is expected to develop early warning markers of cancer environment based on DNA methylation, thereby providing new methods for early detection of cancers, diagnosis, and targeted therapy. This review systematically expounds on the internal mechanism of environmental factors affecting cancer by changing DNA methylation, aiming to help establish the concept of cancer prevention and improve people's health.

Exploring the cross-cancer effect of smoking and its fingerprints in blood DNA methylation on multiple cancers: A Mendelian randomization study

Aberrant smoking-related DNA methylation has been widely investigated as a carcinogenesis mechanism, but whether the cross-cancer epigenetic pathways exist remains unclear. We conducted two-sample Mendelian randomization (MR) analyses respectively on smoking behaviors (age of smoking initiation, smoking initiation, smoking cessation, and lifetime smoking index [LSI]) and smoking-related DNA methylation to investigate their effect on 15 site-specific cancers, based on a genome-wide association study (GWAS) of 1.2 million European individuals and an epigenome-WAS (EWAS) of 5907 blood samples of Europeans for smoking and 15 GWASs of European ancestry for multiple site-specific cancers. Significantly identified CpG sites were further used for colocalization analysis, and those with cross-cancer effect were validated by overlapping with tissue-specific eQTLs. In the genomic MR, smoking measurements of smoking initiation, smoking cessation and LSI were suggested to be casually associated with risk of seven types of site-specific cancers, among which cancers at lung, cervix and colorectum were provided with strong evidence. In the epigenetic MR, methylation at 75 CpG sites were reported to be significantly associated with increased risks of multiple cancers. Eight out of 75 CpG sites were observed with cross-cancer effect, among which cg06639488 (EFNA1), cg12101586 (CYP1A1) and cg14142171 (HLA-L) were validated by eQTLs at specific cancer sites, and cg07932199 (ATXN2) had strong evidence to be associated with cancers of lung (coefficient, 0.65, 95% confidence interval [CI], 0.31-1.00), colorectum (0.90 [0.61, 1.18]), breast (0.31 [0.20, 0.43]) and endometrium (0.98 [0.68, 1.27]). These findings highlight the potential practices targeting DNA methylation-involved cross-cancer pathways.

Smoking, blood DNA methylation sites and lung cancer risk

Altered DNA methylation (DNAm) might be a biological intermediary in the pathway from smoking to lung cancer. In this study, we investigated the contribution of differential blood DNAm to explain the association between smoking and lung cancer incidence. Blood DNAm was measured in 2321 Strong Heart Study (SHS) participants. Incident lung cancer was assessed as time to event diagnoses. We conducted mediation analysis, including validation with DNAm and paired gene expression data from the Framingham Heart Study (FHS). In the SHS, current versus never smoking and pack-years single-mediator models showed, respectively, 29 and 21 differentially methylated positions (DMPs) for lung cancer with statistically significant mediated effects (14 of 20 available, and five of 14 available, positions, replicated, respectively, in FHS). In FHS, replicated DMPs showed gene expression downregulation largely in trans, and were related to biological pathways in cancer. The multimediator model identified that DMPs annotated to the genes AHRR and IER3 jointly explained a substantial proportion of lung cancer. Thus, the association of smoking with lung cancer was partly explained by differences in baseline blood DNAm at few relevant sites. Experimental studies are needed to confirm the biological role of identified eQTMs and to evaluate potential implications for early detection and control of lung cancer.

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

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

Significance

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

The Association of Methylation Level in the CYP39A1 Gene with High Altitude Pulmonary Edema in the Chinese Population

Background

High altitude pulmonary edema (HAPE) is still the most common fatal disease at high altitudes. DNA methylation proceeds with an important role in HAPE progression. This study was designed to investigate the association between CYP39A1 methylation and HAPE.

Methods

Peripheral blood samples were enrolled from 106 participants (53 HAPE patients and 53 healthy subjects) to study the association of CYP39A1 methylation with HAPE. DNA methylation site in the promoter region of CYP39A1 was detected by Sequenom MassARRAY EpiTYPER platform.

Results

Probability analysis showed that the methylation probabilities of CYP39A1_1_CpG_5 and CYP39A1_3_CpG_21 are significant differences between the cases and controls (p< 0.05). The methylation level analysis indicated that CYP39A1_1_CpG_2.3.4, CYP39A1_5_CpG_6.7, and CYP39A1_5_CpG_9.10 were higher methylation in HAPE compared to the controls (p< 0.05). CYP39A1_3_CpG_21 and CYP39A1_4_CpG_3 exhibited a lower methylation level in HAPE than that in the controls (p< 0.05). The association analysis given that CYP39A1_1_CpG_2.3.4 (OR 2.56, p= 0.035), CYP39A1_5_CpG_6.7 (OR 3.99, p= 0.003), CYP39A1_5_CpG_9.10 (OR 3.99, p= 0.003), CYP39A1_5_CpG_16.17.18 (OR 2.53, p= 0.033), and CYP39A1_5_CpG_20 (OR 3.05, p= 0.031) are associated with an increased risk of HAPE. Whereas CYP39A1_1_CpG_5 (OR 0.33, p= 0.016) and CYP39A1_3_CpG_21 (OR 0.18, p= 0.005) have a protective role in HAPE. Besides, age-stratification analysis showed that CYP39A1_1_CpG_5 (OR 0.16, p= 0.014) and CYP39A1_3_CpG_21 (OR 0.08, p= 0.023) had a protective impact on HAPE in people aged ≤32 years. CYP39A1_5_CpG_6.7 (OR 6.70, p= 0.008) and CYP39A1_5_CpG_9.10 (OR 6.70, p= 0.008) were related to an increased susceptibility to HAPE aged >32 years. Moreover, the diagnostic value of CYP39A1_3_CpG_21 (AUC = 0.712, p< 0.001) was significantly better than other CpG sites.

Conclusion

The methylation level of CYP39A1 was associated with a risk of HAPE in the Chinese population, which provided new perspective for preventing and diagnosing of HAPE.

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

BACKGROUND

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

RESEARCH QUESTION

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

STUDY DESIGN AND METHODS

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

RESULTS

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

INTERPRETATION

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

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

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

Epigenome-wide DNA methylation in externalizing behaviours: A review and combined analysis

DNA methylation (DNAm) is one of the most frequently studied epigenetic mechanisms facilitating the interplay of genomic and environmental factors, which can contribute to externalizing behaviours and related psychiatric disorders. Previous epigenome-wide association studies (EWAS) for externalizing behaviours have been limited in sample size, and, therefore, candidate genes and biomarkers with robust evidence are still lacking. We 1) performed a systematic literature review of EWAS of attention-deficit/hyperactivity disorder (ADHD)- and aggression-related behaviours conducted in peripheral tissue and cord blood and 2) combined the most strongly associated DNAm sites observed in individual studies (p < 10^-3) to identify candidate genes and biological systems for ADHD and aggressive behaviours. We observed enrichment for neuronal processes and neuronal cell marker genes for ADHD. Astrocyte and granulocytes cell markers among genes annotated to DNAm sites were relevant for both ADHD and aggression-related behaviours. Only 1 % of the most significant epigenetic findings for ADHD/ADHD symptoms were likely to be directly explained by genetic factors involved in ADHD. Finally, we discuss how the field would greatly benefit from larger sample sizes and harmonization of assessment instruments.

WDR74 rs11231247 contributes to the susceptibility and prognosis of non-small cell lung cancer

OBJECTIVES

WD repeat-containing protein 74 (WDR74) has been linked with the development of lung cancer. This study aims to investigate the relationship between WDR74 rs11231247 and non-small cell lung cancer (NSCLC) susceptibility and the prognosis of NSCLC patients.

METHODS

UALCAN, MethPrimer, ensembl and Pancan meQTL databases were used for bioinformatics analysis. The case-control study included 462 NSCLC patients and 462 health controls. WDR74 rs11231247 genotype was determined by PCR-RFLP. Logistic regression model was used to calculate odds ratio (OR) and 95% confidence interval (95% CI) for analyzing the association of WDR74 SNP with the risk of NSCLC. Log-rank test and Cox regression analysis were used to evaluate the effect of WDR74 genetic variation on the prognosis of NSCLC.

RESULTS

Compared with normal tissues, WDR74 expression level was higher and methylation level was lower in LUAD tissues. There were two CpG islands presented in the promoter of WDR74. And rs11231247 was in the second CpG island. We then discovered that rs11231247 CC and CT were more likely modified by methylation. LUAD case-control study demonstrated that rs11231247 CC genotype was associated with NSCLC risk with OR (95%CI) of 5.29 (2.59-10.79). Stratified analysis showed that rs11231247 T > C polymorphism could increase NSCLC risk in younger subjects (age≤58) (OR = 1.64, 95%CI = 1.06-2.54, P = 0.027). Survival analysis and Cox regression analysis showed rs11231247 CC genotype contributed to a poor prognosis of NSCLC patients (MST=21, HR=2.09, 95%CI=1.17-3.75).

CONCLUSION

WDR74 rs11231247 polymorphism affected the risk and prognosis of NSCLC.

A comparison of the genes and genesets identified by GWAS and EWAS of fifteen complex traits

Identifying genomic regions pertinent to complex traits is a common goal of genome-wide and epigenome-wide association studies (GWAS and EWAS). GWAS identify causal genetic variants, directly or via linkage disequilibrium, and EWAS identify variation in DNA methylation associated with a trait. While GWAS in principle will only detect variants due to causal genes, EWAS can also identify genes via confounding, or reverse causation. We systematically compare GWAS (N > 50,000) and EWAS (N > 4500) results of 15 complex traits. We evaluate if the genes or gene ontology terms flagged by GWAS and EWAS overlap, and find substantial overlap for diastolic blood pressure, (gene overlap P = 5.2 × 10^-6; term overlap P = 0.001). We superimpose our empirical findings against simulated models of varying genetic and epigenetic architectures and observe that in most cases GWAS and EWAS are likely capturing distinct genesets. Our results indicate that GWAS and EWAS are capturing different aspects of the biology of complex traits.

Elucidating the genetic architecture of DNA methylation to identify promising molecular mechanisms of disease

DNA methylation commonly occurs at cytosine-phosphate-guanine sites (CpGs) that can serve as biomarkers for many diseases. We analyzed whole genome sequencing data to identify DNA methylation quantitative trait loci (mQTLs) in 4126 Framingham Heart Study participants. Our mQTL mapping identified 94,362,817 cis-mQTLvariant-CpG pairs (for 210,156 unique autosomal CpGs) at P < 1e-7 and 33,572,145 trans-mQTL variant-CpG pairs (for 213,606 unique autosomal CpGs) at P < 1e-14. Using cis-mQTL variants for 1258 CpGs associated with seven cardiovascular disease (CVD) risk factors, we found 104 unique CpGs that colocalized with at least one CVD trait. For example, cg11554650 (PPP1R18) colocalized with type 2 diabetes, and was driven by a single nucleotide polymorphism (rs2516396). We performed Mendelian randomization (MR) analysis and demonstrated 58 putatively causal relations of CVD risk factor-associated CpGs to one or more risk factors (e.g., cg05337441 [APOB] with LDL; MR P = 1.2e-99, and 17 causal associations with coronary artery disease (e.g. cg08129017 [SREBF1] with coronary artery disease; MR P = 5e-13). We also showed that three CpGs, e.g., cg14893161 (PM20D1), are putatively causally associated with COVID-19 severity. To assist in future analyses of the role of DNA methylation in disease pathogenesis, we have posted a comprehensive summary data set in the National Heart, Lung, and Blood Institute's BioData Catalyst.

Identification of novel susceptibility methylation loci for pancreatic cancer in a two-phase epigenome-wide association study

The role of DNA methylation and its interplay with gene expression in the susceptibility to pancreatic cancer (PanC) remains largely unexplored. To fill in this gap, we conducted an integrative two-phase epigenome-wide association study (EWAS) of PanC using genomic DNA from 44 cases and 556 controls (20 local controls and 536 public controls in the Framingham Heart Study) in phase 1 and 23 cases and 22 controls in phase 2. We validated the findings using pre-diagnostic blood samples from 13 cases and 26 controls in the Women's Health Initiative (WHI) Study. We further examined gene expression in peripheral leukocytes of 47 cases and 31 controls involved in the methylation study using RNA sequencing and performed bidirectional Mendelian randomization (MR) analysis using existing single nucleotide polymorphism (SNP) data. In phase 1, we identified 2776 significantly differentially methylated CpG sites (DMPs) and 154 significantly differentially methylated regions (DMRs). In phase 2, we validated six DMPs (in or near AIM2, DGKA, STK39, and TNFSF8) and three DMRs (in or near nc886, LY6G5C, and HLA-DPB1). The DMR near nc886 was further validated in the WHI samples (P = 6.69 × 10-5). MR analysis suggested that the CpG sites cg00308130 and cg16684184 for nc886 and cg16875057 for STK39 were causally related to PanC susceptibility and that PanC influenced methylation of cg15354065 for DGKA. This first integrative EWAS of PanC provides novel insights into the role of DNA methylation and its interplay with SNPs and gene expression in the disease susceptibility.

Epigenetic mechanisms of lung carcinogenesis involve differentially methylated CpG sites beyond those associated with smoking

Smoking-related epigenetic changes have been linked to lung cancer, but the contribution of epigenetic alterations unrelated to smoking remains unclear. We sought for a sparse set of CpG sites predicting lung cancer and explored the role of smoking in these associations. We analysed CpGs in relation to lung cancer in participants from two nested case-control studies, using (LASSO)-penalised regression. We accounted for the effects of smoking using known smoking-related CpGs, and through conditional-independence network. We identified 29 CpGs (8 smoking-related, 21 smoking-unrelated) associated with lung cancer. Models additionally adjusted for Comprehensive Smoking Index-(CSI) selected 1 smoking-related and 49 smoking-unrelated CpGs. Selected CpGs yielded excellent discriminatory performances, outperforming information provided by CSI only. Of the 8 selected smoking-related CpGs, two captured lung cancer-relevant effects of smoking that were missed by CSI. Further, the 50 CpGs identified in the CSI-adjusted model complementarily explained lung cancer risk. These markers may provide further insight into lung cancer carcinogenesis and help improving early identification of high-risk patients.

DNA methylation patterns reflect individual's lifestyle independent of obesity

OBJECTIVE

Obesity is driven by modifiable lifestyle factors whose effects may be mediated by epigenetics. Therefore, we investigated lifestyle effects on blood DNA methylation in participants of the LIFE-Adult study, a well-characterised population-based cohort from Germany.

RESEARCH DESIGN AND METHODS

Lifestyle scores (LS) based on diet, physical activity, smoking and alcohol intake were calculated in 4107 participants of the LIFE-Adult study. Fifty subjects with an extremely healthy lifestyle and 50 with an extremely unhealthy lifestyle (5th and 95th percentiles LS) were selected for genome-wide DNA methylation analysis in blood samples employing Illumina Infinium® Methylation EPIC BeadChip system technology.

RESULTS

Differences in DNA methylation patterns between body mass index groups (<25 vs. >30 kg/m² ) were rather marginal compared to inter-lifestyle differences (0 vs. 145 differentially methylated positions [DMPs]), which identified 4682 differentially methylated regions (DMRs; false discovery rate [FDR <5%) annotated to 4426 unique genes. A DMR annotated to the glutamine-fructose-6-phosphate transaminase 2 (GFPT2) locus showed the strongest hypomethylation (∼6.9%), and one annotated to glutamate rich 1 (ERICH1) showed the strongest hypermethylation (∼5.4%) in healthy compared to unhealthy lifestyle individuals. Intersection analysis showed that diet, physical activity, smoking and alcohol intake equally contributed to the observed differences, which affected, among others, pathways related to glutamatergic synapses (adj. p < .01) and axon guidance (adj. p < .05). We showed that methylation age correlates with chronological age and waist-to-hip ratio with lower DNA methylation age (DNAmAge) acceleration distances in participants with healthy lifestyles. Finally, two identified top DMPs for the alanyl aminopeptidase (ANPEP) locus also showed the strongest expression quantitative trait methylation in blood.

CONCLUSIONS

DNA methylation patterns help discriminate individuals with a healthy versus unhealthy lifestyle, which may mask subtle methylation differences derived from obesity.

Applying Mendelian randomization to appraise causality in relationships between nutrition and cancer

Dietary factors are assumed to play an important role in cancer risk, apparent in consensus recommendations for cancer prevention that promote nutritional changes. However, the evidence in this field has been generated predominantly through observational studies, which may result in biased effect estimates because of confounding, exposure misclassification, and reverse causality. With major geographical differences and rapid changes in cancer incidence over time, it is crucial to establish which of the observational associations reflect causality and to identify novel risk factors as these may be modified to prevent the onset of cancer and reduce its progression. Mendelian randomization (MR) uses the special properties of germline genetic variation to strengthen causal inference regarding potentially modifiable exposures and disease risk. MR can be implemented through instrumental variable (IV) analysis and, when robustly performed, is generally less prone to confounding, reverse causation and measurement error than conventional observational methods and has different sources of bias (discussed in detail below). It is increasingly used to facilitate causal inference in epidemiology and provides an opportunity to explore the effects of nutritional exposures on cancer incidence and progression in a cost-effective and timely manner. Here, we introduce the concept of MR and discuss its current application in understanding the impact of nutritional factors (e.g., any measure of diet and nutritional intake, circulating biomarkers, patterns, preference or behaviour) on cancer aetiology and, thus, opportunities for MR to contribute to the development of nutritional recommendations and policies for cancer prevention. We provide applied examples of MR studies examining the role of nutritional factors in cancer to illustrate how this method can be used to help prioritise or deprioritise the evaluation of specific nutritional factors as intervention targets in randomised controlled trials. We describe possible biases when using MR, and methodological developments aimed at investigating and potentially overcoming these biases when present. Lastly, we consider the use of MR in identifying causally relevant nutritional risk factors for various cancers in different regions across the world, given notable geographical differences in some cancers. We also discuss how MR results could be translated into further research and policy. We conclude that findings from MR studies, which corroborate those from other well-conducted studies with different and orthogonal biases, are poised to substantially improve our understanding of nutritional influences on cancer. For such corroboration, there is a requirement for an interdisciplinary and collaborative approach to investigate risk factors for cancer incidence and progression.

Methylome-wide association study of antidepressant use in Generation Scotland and the Netherlands Twin Register implicates the innate immune system

Antidepressants are an effective treatment for major depressive disorder (MDD), although individual response is unpredictable and highly variable. Whilst the mode of action of antidepressants is incompletely understood, many medications are associated with changes in DNA methylation in genes that are plausibly linked to their mechanisms. Studies of DNA methylation may therefore reveal the biological processes underpinning the efficacy and side effects of antidepressants. We performed a methylome-wide association study (MWAS) of self-reported antidepressant use accounting for lifestyle factors and MDD in Generation Scotland (GS:SFHS, N = 6428, EPIC array) and the Netherlands Twin Register (NTR, N = 2449, 450 K array) and ran a meta-analysis of antidepressant use across these two cohorts. We found ten CpG sites significantly associated with self-reported antidepressant use in GS:SFHS, with the top CpG located within a gene previously associated with mental health disorders, ATP6V1B2 (β = -0.055, pcorrected = 0.005). Other top loci were annotated to genes including CASP10, TMBIM1, MAPKAPK3, and HEBP2, which have previously been implicated in the innate immune response. Next, using penalised regression, we trained a methylation-based score of self-reported antidepressant use in a subset of 3799 GS:SFHS individuals that predicted antidepressant use in a second subset of GS:SFHS (N = 3360, β = 0.377, p = 3.12 × 10-11, R2 = 2.12%). In an MWAS analysis of prescribed selective serotonin reuptake inhibitors, we showed convergent findings with those based on self-report. In NTR, we did not find any CpGs significantly associated with antidepressant use. The meta-analysis identified the two CpGs of the ten above that were common to the two arrays used as being significantly associated with antidepressant use, although the effect was in the opposite direction for one of them. Antidepressants were associated with epigenetic alterations in loci previously associated with mental health disorders and the innate immune system. These changes predicted self-reported antidepressant use in a subset of GS:SFHS and identified processes that may be relevant to our mechanistic understanding of clinically relevant antidepressant drug actions and side effects.

Systematic review of Mendelian randomization studies on risk of cancer

BACKGROUND

We aimed to map and describe the current state of Mendelian randomization (MR) literature on cancer risk and to identify associations supported by robust evidence.

METHODS

We searched PubMed and Scopus up to 06/10/2020 for MR studies investigating the association of any genetically predicted risk factor with cancer risk. We categorized the reported associations based on a priori designed levels of evidence supporting a causal association into four categories, namely robust, probable, suggestive, and insufficient, based on the significance and concordance of the main MR analysis results and at least one of the MR-Egger, weighed median, MRPRESSO, and multivariable MR analyses. Associations not presenting any of the aforementioned sensitivity analyses were not graded.

RESULTS

We included 190 publications reporting on 4667 MR analyses. Most analyses (3200; 68.6%) were not accompanied by any of the assessed sensitivity analyses. Of the 1467 evaluable analyses, 87 (5.9%) were supported by robust, 275 (18.7%) by probable, and 89 (6.1%) by suggestive evidence. The most prominent robust associations were observed for anthropometric indices with risk of breast, kidney, and endometrial cancers; circulating telomere length with risk of kidney, lung, osteosarcoma, skin, thyroid, and hematological cancers; sex steroid hormones and risk of breast and endometrial cancer; and lipids with risk of breast, endometrial, and ovarian cancer.

CONCLUSIONS

Despite the large amount of research on genetically predicted risk factors for cancer risk, limited associations are supported by robust evidence for causality. Most associations did not present a MR sensitivity analysis and were thus non-evaluable. Future research should focus on more thorough assessment of sensitivity MR analyses and on more transparent reporting.

DNA Methylation in Peripheral Blood: Providing Novel Biomarkers of Exposure and Immunity to Examine Cancer Risk

DNA methylation is an epigenetic phenomenon that can alter and control gene expression. Because methylation plays a key role in cell differentiation, methylation markers have been identified that are unique to a given cell type; these markers are stable and can be measured in tissue or whole blood. The article by Katzke and colleagues, published in this issue, uses methylation markers to estimate proportions of immune cell subtypes in peripheral blood samples that were collected prior to diagnosis, thus allowing them to directly examine associations with pancreatic cancer risk. Given that immune-cell counts cannot be measured from archived blood, and that retrospective case-control studies rely on blood that is collected after cancer diagnosis, few studies have been able to examine the role of the systemic immune response in cancer risk. Measurement of DNA methylation in peripheral blood, primarily through development of whole-genome approaches, has also opened new doors to examining cancer etiology.See related article by Katzke et al., p. 2179.

A functional methylation signature to predict the prognosis of Chinese lung adenocarcinoma based on TCGA

Background

Lung cancer is the leading cause of cancer morbidity and mortality worldwide, however, the individualized treatment is still unsatisfactory. DNA methylation can affect gene regulation and may be one of the most valuable biomarkers in predicting the prognosis of lung adenocarcinoma. This study was aimed to identify methylation CpG sites that may be used to predict lung adenocarcinoma prognosis.

Methods

The Cancer Genome Atlas (TCGA) database was used to detect methylation CpG sites associated with lung adenocarcinoma prognosis and construct a methylation signature model. Then, a Chinese cohort was carried out to estimate the association between methylation and lung adenocarcinoma prognosis. Biological function studies, including demethylation treatment, cell proliferative capacity, and gene expression changes in lung adenocarcinoma cell lines, were further performed.

Results

In the TCGA set, three methylation CpG sites were selected that were associated with lung adenocarcinoma prognosis (cg14517217, cg15386964, and cg18878992). The risk of mortality was increased in lung adenocarcinoma patients with the gradual increase level of methylation signature based on three methylation sites levels (HR = 45.30, 95% CI = 26.69–66.83; p < 0.001). The C‐statistic value increased to 0.77 when age, gender, and other clinical variables were added to the signature to prediction model. A similar situation was confirmed in Chinese lung adenocarcinoma cohort. In the biological function studies, the proliferative capacity of cell lines was inhibited when the cells were demethylated with 5‐aza‐2'‐deoxycytidine (5‐aza‐2dC). The mRNA and protein expression levels of SEPT9 and HIST1H2BH (cg14517217 and cg15386964) were downregulated with different concentrations of 5‐aza‐2dC treatment, while cg18878992 showed the opposite result.

Conclusion

This study is the first to develop a three‐CpG‐based model for lung adenocarcinoma, which is a practical and useful tool for prognostic prediction that has been validated in a Chinese population.

Assessing the role of genome-wide DNA methylation between smoking and risk of lung cancer using repeated measurements: the HUNT study

BACKGROUND

It is unclear if smoking-related DNA methylation represents a causal pathway between smoking and risk of lung cancer. We sought to identify novel smoking-related DNA methylation sites in blood, with repeated measurements, and to appraise the putative role of DNA methylation in the pathway between smoking and lung cancer development.

METHODS

We derived a nested case-control study from the Trøndelag Health Study (HUNT), including 140 incident patients who developed lung cancer during 2009-13 and 140 controls. We profiled 850 K DNA methylation sites (Illumina Infinium EPIC array) in DNA extracted from blood that was collected in HUNT2 (1995-97) and HUNT3 (2006-08) for the same individuals. Epigenome-wide association studies (EWAS) were performed for a detailed smoking phenotype and for lung cancer. Two-step Mendelian randomization (MR) analyses were performed to assess the potential causal effect of smoking on DNA methylation as well as of DNA methylation (13 sites as putative mediators) on risk of lung cancer.

RESULTS

The EWAS for smoking in HUNT2 identified associations at 76 DNA methylation sites (P < 5 × 10-8), including 16 novel sites. Smoking was associated with DNA hypomethylation in a dose-response relationship among 83% of the 76 sites, which was confirmed by analyses using repeated measurements from blood that was collected at 11 years apart for the same individuals. Two-step MR analyses showed evidence for a causal effect of smoking on DNA methylation but no evidence for a causal link between DNA methylation and the risk of lung cancer.

CONCLUSIONS

DNA methylation modifications in blood did not seem to represent a causal pathway linking smoking and the lung cancer risk.

Investigating the DNA methylation profile of e-cigarette use

BACKGROUND

Little evidence exists on the health effects of e-cigarette use. DNA methylation may serve as a biomarker for exposure and could be predictive of future health risk. We aimed to investigate the DNA methylation profile of e-cigarette use.

RESULTS

Among 117 smokers, 117 non-smokers and 116 non-smoking vapers, we evaluated associations between e-cigarette use and epigenome-wide methylation from saliva. DNA methylation at 7 cytosine-phosphate-guanine sites (CpGs) was associated with e-cigarette use at p < 1 × 10-5 and none at p < 5.91 × 10-8. 13 CpGs were associated with smoking at p < 1 × 10-5 and one at p < 5.91 × 10-8. CpGs associated with e-cigarette use were largely distinct from those associated with smoking. There was strong enrichment of known smoking-related CpGs in the smokers but not the vapers. We also tested associations between e-cigarette use and methylation scores known to predict smoking and biological ageing. Methylation scores for smoking and biological ageing were similar between vapers and non-smokers. Higher levels of all smoking scores and a biological ageing score (GrimAge) were observed in smokers. A methylation score for e-cigarette use showed poor prediction internally (AUC 0.55, 0.41-0.69) and externally (AUC 0.57, 0.36-0.74) compared with a smoking score (AUCs 0.80) and was less able to discriminate lung squamous cell carcinoma from adjacent normal tissue (AUC 0.64, 0.52-0.76 versus AUC 0.73, 0.61-0.85).

CONCLUSIONS

The DNA methylation profile for e-cigarette use is largely distinct from that of cigarette smoking, did not replicate in independent samples, and was unable to discriminate lung cancer from normal tissue. The extent to which methylation related to long-term e-cigarette use translates into chronic effects requires further investigation.

Hypomethylation of AHRR (cg05575921) Is Related to Smoking Status in the Mexican Mestizo Population

Tobacco smoking results in a multifactorial disease involving environmental and genetic factors; epigenome-wide association studies (EWAS) show changes in DNA methylation levels due to cigarette consumption, partially reversible upon tobacco smoking cessation. Therefore, methylation levels could predict smoking status. This study aimed to evaluate the DNA methylation level of cg05575921 (AHRR) and cg23771366 (PRSS23) and their correlation with lung function variables, cigarette consumption, and nicotine addiction in the Mexican smoking population. We included 114 non-smokers (NS) and 102 current tobacco smokers (TS); we then further subclassified them as heavy smokers (HS) (n = 53) and light smokers (LS) (n = 49). We used restriction enzymes (MspI/HpaII) and qPCR to determine the DNA methylation level. We observed significant hypomethylation of cg05575921 in smokers compared to NS (p = 0.003); further analysis found a difference between HS and NS (p = 0.02). We did not observe differences between other groups or a positive correlation between methylation levels and age, BMI, cigarette consumption, nicotine addiction, or lung function. In conclusion, the cg05575921 site of AHRR is significantly hypomethylated in Mexican smokers, especially in HS (≥20 cigarettes per day).

Epigenome-wide DNA methylation signature of benzo[a]pyrene exposure and their mediation roles in benzo[a]pyrene-associated lung cancer development

Benzo[a]pyrene (B[a]P) is a typical carcinogen associated with increased lung cancer risk, but the underlying mechanisms remain unclear. This study aimed to investigate epigenome-wide DNA methylation associated with B[a]P exposure and their mediation effects on B[a]P-lung cancer association in two lung cancer case-control studies of 462 subjects. Their plasma levels of benzo[a]pyrene diol epoxide-albumin (BPDE-Alb) adducts and genome-wide DNA methylations were separately detected in peripheral blood by using enzyme-linked immunosorbent assay (ELISA) and genome-wide methylation arrays. The epigenome-wide meta-analysis was performed to analyze the associations between BPDE-Alb adducts and DNA methylations. Mediation analysis was applied to assess effect of DNA methylation on the B[a]P-lung cancer association. We identified 15 CpGs associated with BPDE-Alb adducts (P_-meta < 1.0 × 10^-5), among which the methylation levels at five loci (cg06245338, cg24256211, cg15107887, cg02211741, and cg04354393 annotated to UBE2O, SAMD4A, ACBD6, DGKZ, and SLFN13, respectively) mediated a separate 38.5%, 29.2%, 41.5%, 47.7%, 56.5%, and a joint 58.2% of the association between BPDE-Alb adducts and lung cancer risk. Compared to the traditional factors [area under the curve (AUC) = 0.788], addition of these CpGs exerted improved discriminations for lung cancer, with AUC ranging 0.828-0.861. Our results highlight DNA methylation alterations as potential mediators in lung tumorigenesis induced by B[a]P exposure.

The increased expression and aberrant methylation of SHC1 in non-small cell lung cancer: Integrative analysis of clinical and bioinformatics databases

Despite the previous evidence showing that SHC adaptor protein 1 (SHC1) could encode three distinct isoforms (p46SHC, p52SHC and p66SHC) that function in different activities such as regulating life span and Ras activation, the precise underlying role of SHC1 in lung cancer also remains obscure. In this study, we firstly found that SHC1 expression was up‐regulated both in lung adenocarcinoma (LUAD) and in lung squamous cell carcinoma (LUSC) tissues. Furthermore, compared to patients with lower SHC1 expression, LUAD patients with higher expression of SHC1 had poorer overall survival (OS). Moreover, higher expression of SHC1 was also associated with worse OS in patients with stages 1 and 2 but not stage 3 lung cancer. Significantly, the analysis showed that SHC1 methylation level was associated with OS in lung cancer patients. It seemed that the methylation level at specific probes within SHC1 showed negative correlations with SHC1 expression both in LUAD and in LUSC tissues. The LUAD and LUSC patients with hypermethylated SHC1 at cg12473916 and cg19356022 probes had a longer OS. Therefore, it is reasonable to conclude that SHC1 has a potential clinical significance in LUAD and LUSC patients.

Methylation marks of prenatal exposure to maternal smoking and risk of cancer in adulthood

BACKGROUND

Prenatal exposure to maternal smoking is detrimental to child health but its association with risk of cancer has seldom been investigated. Maternal smoking induces widespread and long-lasting DNA methylation changes, which we study here for association with risk of cancer in adulthood.

METHODS

Eight prospective case-control studies nested within the Melbourne Collaborative Cohort Study were used to assess associations between maternal-smoking-associated methylation marks in blood and risk of several cancers: breast (n = 406 cases), colorectal (n = 814), gastric (n = 166), kidney (n = 139), lung (n = 327), prostate (n = 847) and urothelial (n = 404) cancer and B-cell lymphoma (n = 426). We used conditional logistic regression models to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for associations between cancer and five methylation scores calculated as weighted averages for 568, 19, 15, 28 and 17 CpG sites. Models were adjusted for confounders, including personal smoking history (smoking status, pack-years, age at starting and quitting) and methylation scores for personal smoking.

RESULTS

All methylation scores for maternal smoking were strongly positively associated with risk of urothelial cancer. Risk estimates were only slightly attenuated after adjustment for smoking history, other potential confounders and methylation scores for personal smoking. Potential negative associations were observed with risk of lung cancer and B-cell lymphoma. No associations were observed for other cancers.

CONCLUSIONS

We found that methylation marks of prenatal exposure to maternal smoking are associated with increased risk of urothelial cancer. Our study demonstrates the potential for using DNA methylation to investigate the impact of early-life, unmeasured exposures on later-life cancer risk.

Methylation Regulation of TLR3 on Immune Parameters in Lung Adenocarcinoma

This study aims to analyze the methylation regulation of TLR3 in lung adenocarcinoma (LUAD) and to explore the association of TLR3 expression with immune microenvironment. TLR3 has a decreased expression in LUAD tissues and low expression of TLR3 is not only associated with poor prognosis in patients with LUAD, but also can be used as a diagnostic marker. Bisulfite sequencing PCR (BSP) results showed that the methylation level in the promoter of TLR3 was negatively correlated with the level of TLR3 mRNA in LUAD tissues. TIMER analysis showed that TLR3 was negatively correlated with the tumor purity of LUAD and positively with immune cell infiltration to some extent. ESTIMATE analysis also suggested that TLR3 expression and its methylation had significant correlation with immune score. The lower immune scores were associated with the late stage of LUAD and poor prognosis. The high expression of TLR3 might inhibit the development of LUAD by activating apoptosis pathway. The proteins interacted with TLR3 were mainly involved in the apoptosis pathway and positively correlated with the key genes (MYD88, Caspase 8, BIRC3, PIK3R1) in this pathway. Therefore, TLR3 as a key biomarker for prognosis and diagnosis in LUAD, might be considered as a potential epigenetic and immunotherapeutic target.

Epigenome-wide scan identifies differentially methylated regions for lung cancer using pre-diagnostic peripheral blood

BACKGROUND

DNA methylation markers have been associated with lung cancer risk and may identify aetiologically relevant genomic regions, or alternatively, be markers of disease risk factors or biological processes associated with disease development.

METHODS

In a nested case-control study, we measured blood leukocyte DNA methylation levels in pre-diagnostic samples collected from 430 participants (208 cases; 222 controls) in the 1989 CLUE II cohort. We compared DNA methylation levels with case/control status to identify novel genomic regions, both single CpG sites and differentially methylated regions (DMRs), while controlling for known DNA methylation changes associated with smoking using a previously described pack-years-based smoking methylation score. Stratification analyses were conducted over time from blood draw to diagnosis, histology, and smoking status.

RESULTS

We identified 16 single CpG sites and 40 DMRs significantly associated with lung cancer risk (q < 0.05). The identified genomic regions were associated with genes including H19, HOXA3/HOXA4, RUNX3, BRICD5, PLXNB2, and RP13. For the single CpG sites, the strongest association was noted for cg09736286 in the DIABLO gene (OR [for 1 SD] = 2.99, 95% CI: 1.95-4.59, P-value = 4.81 × 10-7). We found that CpG sites in the HOXA3/HOXA4 region were hypermethylated in cases compared to controls.

CONCLUSION

The single CpG sites and DMRs that we identified represented significant measurable differences in lung cancer risk, providing potential biomarkers for lung cancer risk stratification. Future studies will need to examine whether these regions are causally related to lung cancer.

Genetic impacts on DNA methylation: research findings and future perspectives

Multiple recent studies highlight that genetic variants can have strong impacts on a significant proportion of the human DNA methylome. Methylation quantitative trait loci, or meQTLs, allow for the exploration of biological mechanisms that underlie complex human phenotypes, with potential insights for human disease onset and progression. In this review, we summarize recent milestones in characterizing the human genetic basis of DNA methylation variation over the last decade, including heritability findings and genome-wide identification of meQTLs. We also discuss challenges in this field and future areas of research geared to generate insights into molecular processes underlying human complex traits.

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

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

A region-based method for causal mediation analysis of DNA methylation data

Exposure to environmental factors can affect DNA methylation at a 5'-cytosine-phosphate-guanine-3' (CpG) site or a genomic region, which can then affect an outcome. In other words, environmental effects on an outcome could be mediated by DNA methylation. To date, single CpG-site-based mediation analysis has been employed extensively. More recently, however, there has been considerable interest in studying differentially methylated regions (DMRs), both because DMRs are more likely to have functional effects than single CpG sites and because testing DMRs reduces multiple testing. In this report, we propose a novel causal mediation approach under the counterfactual framework to test the significance of total (TE), direct (DE), and indirect effects (IE) of predictors on response variable with a methylated region (MR) as the mediator (denoted as MR-Mediation). Functional linear transformation is used to reduce the possible high dimension of the CpG sites in a predefined MR and to account for their location information. In our simulation studies, MR-Mediation retained the desired Type I error rates for TE, DE, and IE tests. Furthermore, MR-Mediation had better power performance than testing mean methylation level as the mediator in most considered scenarios, especially for IE (i.e., mediated effect) test, which could be more interesting than the other two effect tests. We further illustrate our proposed method by analysing the methylation mediated effect of exposure to gun violence on total immunoglobulin E or atopic asthma among participants in the Epigenetic Variation and Childhood Asthma in Puerto Ricans study.

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.

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

BACKGROUND

A low level of methylation at cg05575921 in the aryl-hydrocarbon receptor repressor (AHRR) gene is robustly associated with smoking, and some studies have observed associations between cg05575921 methylation and increased lung cancer risk and mortality. To prospectively examine whether decreased methylation at cg05575921 may identify high risk subpopulations for lung cancer screening among heavy smokers, and mortality in cases, we evaluated associations between cg05575921 methylation and lung cancer risk and mortality, by histotype, in heavy smokers.

METHODS

The β-Carotene and Retinol Efficacy Trial (CARET) included enrollees ages 45-69 with ≥ 20 pack-year smoking histories and/or occupational asbestos exposure. A subset of CARET participants had cg05575921 methylation available from HumanMethylationEPIC assays of blood collected on average 4.3 years prior to lung cancer diagnosis in cases. Cg05575921 methylation β-values were treated continuously for a 10% methylation decrease and as quintiles, where quintile 1 (Q1, referent) represents high methylation and Q5, low methylation. We used conditional logistic regression models to examine lung cancer risk overall and by histotype in a nested case-control study including 316 lung cancer cases (diagnosed through 2005) and 316 lung cancer-free controls matched on age (±5 years), sex, race/ethnicity, enrollment year, current/former smoking, asbestos exposure, and follow-up time. Mortality analyses included 372 lung cancer cases diagnosed between 1985 and 2013 with available methylation data. We used Cox proportional hazards models to examine mortality overall and by histotype.

RESULTS

Decreased cg05575921 methylation was strongly associated with smoking, even in our population of heavy smokers. We did not observe associations between decreased pre-diagnosis cg05575921 methylation and increased lung cancer risk, overall or by histotype. We observed linear increasing trends for lung cancer-specific mortality across decreasing cg05575921 methylation quintiles for adenocarcinoma and small cell carcinoma (P-trends = 0.01 and 0.04, respectively).

CONCLUSIONS

In our study of heavy smokers, decreased cg05575921 methylation was strongly associated with smoking but not increased lung cancer risk. The observed association between cg05575921 methylation and increased mortality in adenocarcinoma and small cell histotypes requires further examination. Our results do not support using decreased cg05575921 methylation as a biomarker for lung cancer screening risk stratification.

A cell-type deconvolution meta-analysis of whole blood EWAS reveals lineage-specific smoking-associated DNA methylation changes

Highly reproducible smoking-associated DNA methylation changes in whole blood have been reported by many Epigenome-Wide-Association Studies (EWAS). These epigenetic alterations could have important implications for understanding and predicting the risk of smoking-related diseases. To this end, it is important to establish if these DNA methylation changes happen in all blood cell subtypes or if they are cell-type specific. Here, we apply a cell-type deconvolution algorithm to identify cell-type specific DNA methylation signals in seven large EWAS. We find that most of the highly reproducible smoking-associated hypomethylation signatures are more prominent in the myeloid lineage. A meta-analysis further identifies a myeloid-specific smoking-associated hypermethylation signature enriched for DNase Hypersensitive Sites in acute myeloid leukemia. These results may guide the design of future smoking EWAS and have important implications for our understanding of how smoking affects immune-cell subtypes and how this may influence the risk of smoking related diseases.

Smoking-associated DNA methylation changes in whole blood have been reported by many EWAS. Here, the authors use a cell-type deconvolution algorithm to identify cell-type specific DNA methylation signals in seven EWAS, identifying lineage-specific smoking-associated DNA methylation changes.

AHRR hypomethylation as an epigenetic marker of smoking history predicts risk of myocardial infarction in former smokers

BACKGROUND AND AIMS

Smoking causes cardiovascular disease. AHRR hypomethylation at the cg05575921 site is associated with active and former smoking status at baseline, and cumulative amount of tobacco smoked. We tested the hypothesis that AHRR cg05575921 hypomethylation as an epigenetic marker of smoking history predicts the risk of myocardial infarction in former smokers.

METHODS

We included 10,510 individuals with methylation extent measurements and information on smoking status from the Copenhagen City Heart Study (CCHS), a prospective, cohort study of the general population carried out from 1991 to 2003. The endpoint myocardial infarction was retrieved from the national Danish Patient Registry and the national Danish Causes of Death Registry.

RESULTS

For individuals in the 1st (lowest) quartile of AHRR cg05575921 methylation (≤49% methylation extent), 99% were ever smokers at baseline (active and former smokers combined) compared to 42% in the 4th (highest) quartile (>62% methylation extent). For former smokers, the cumulative incidence of myocardial infarction was higher in the lowest methylation extent (1st-50th percentile) compared to the highest methylation extent (51st-100th percentile). Compared to never smokers, the multivariable adjusted subhazard ratio for myocardial infarction was 1.09 (95%CI:0.88-1.35) for former smokers with the highest methylation degree, 1.38 (1.06-1.80) for active smokers with the highest methylation extent, 1.39 (1.08-1.78) for former smokers with the lowest methylation extent, and 1.61 (1.35-1.92) for active smokers with the lowest methylation extent.

CONCLUSIONS

AHRR cg05575921 hypomethylation as an epigenetic marker of smoking history predicts risk of myocardial infarction, particularly in former smokers. Further, AHRR hypomethylation, regardless of smoking status, was associated with increased risk of myocardial infarction.

AHRR cg05575921 methylation in relation to smoking and PM2.5 exposure among Taiwanese men and women

Background

Polycyclic aromatic hydrocarbon (PAH)-rich substances like cigarette smoke and PM_2.5 induce aryl hydrocarbon receptor (AHR)-mediated aryl hydrocarbon receptor repressor (AHRR) methylation. AHRR cg05575921 and coagulation factor II (thrombin) receptor-like 3 (F2RL3) cg03636183 methylation patterns are well-established biomarkers for smoking. Even though AHRR cg05575921 methylation has recently been associated with PM_2.5, the interaction between smoking and PM_2.5 on AHRR methylation is yet to be fully explored. We evaluated AHRR and F2RL3 CpG sites to identify potential significant markers in relation to PM_2.5 and smoking in Taiwanese adults.

Methods

DNA methylation and smoking data of 948 participants aged 30–70 years were obtained from the Taiwan Biobank Database (2008–2015), while PM_2.5 data were obtained from the Air Quality Monitoring Database (2006–2011).

Results

Smoking and PM_2.5 were independently associated with hypomethylation (lower levels) of AHRR cg05575921, AHRR cg23576855, F2RL3 cg03636183, and F2LR3 cg21911711 after multiple-comparison correction (Bonferroni P < 0.00028409). Cg05575921 was the most hypomethylated AHRR CpG site, while cg03636183 was the most hypomethylated F2RL3 CpG site. Overall, cg05575921 was the most hypomethylated CpG site: β = − 0.03909, P < 0.0001; − 0.17536, P < 0.0001 for former and current smoking, respectively (P-trend_smoking < 0.0001) and − 0.00141, P < 0.0001 for PM_2.5. After adjusting for F2RL3 cg03636183, smoking and PM_2.5 remained significantly associated with cg05575921 hypomethylation: β − 0.02221, P < 0.0001; − 0.11578, P < 0.0001 for former and current smoking, respectively (P-trend_smoking < 0.0001) and − 0.0070, P = 0.0120 for PM_2.5. After stratification by sex, smoking and PM_2.5 remained associated (P < 0.05) with cg05575921 hypomethylation in both men (β = − 0.04274, − 0.17700, and − 0.00163 for former smoking, current smoking, and PM_2.5, respectively) and women (β = − 0.01937, − 0.17255, and − 0.00105 for former smoking, current smoking, and PM_2.5, respectively). After stratification by residential area, former and current smoking remained associated (P < 0.05) with cg05575921 hypomethylation: β = − 0.03918 and − 0.17536, respectively (P-trend_smoking < 0.0001). Living in the central and southern areas was also associated (P < 0.05) with cg05575921 hypomethylation: β = − 0.01356 and − 0.01970, respectively (P-trend_area < 0.0001).

Conclusion

Smoking and PM_2.5 were independently associated with hypomethylation of cg05575921, cg23576855, cg03636183, and cg21911711. The most hypomethylated CpG site was cg05575921 and its association with smoking and PM_2.5 was dose-dependent.

Leveraging the urban-rural divide for epigenetic research

Urbanization coincides with a complex change in environmental exposure and a rapid increase in noncommunicable diseases (NCDs). Epigenetics, including DNA methylation (DNAm), is thought to mediate part of the association between genetic/environmental exposure and NCDs. The urban-rural divide provides a unique opportunity to investigate the effect of the combined presence of multiple forms of environmental exposure on DNAm and the related increase in disease risk. This review evaluates the ability of three epidemiological study designs (migration, income-comparative and urban-rural designs) to investigate the role of DNAm in the association between urbanization and the rise in NCD prevalence. We also discuss the ability of each study design to address the gaps in the current literature, including the complex methylation-mediated risk attributable to the cluster of forms of exposure characterizing urban and rural living, while providing a platform for developing countries to leverage their demographic discrepancies in future research ventures.

Promoter Methylation of Selected Genes in Non-Small-Cell Lung Cancer Patients and Cell Lines

Specific gene promoter DNA methylation is becoming a powerful epigenetic biomarker in cancer diagnostics. Five genes (CDH1, CDKN2Ap16, RASSF1A, TERT, and WT1) were selected based on their frequently published potential as epigenetic markers. Diagnostic promoter methylation assays were generated based on bisulfite-converted DNA pyrosequencing. The methylation patterns of 144 non-small-cell lung cancer (NSCLC) and 7 healthy control formalin-fixed paraffin-embedded (FFPE) samples were analyzed to evaluate the applicability of the putative diagnostic markers. Statistically significant changes in methylation levels are shown for TERT and WT1. Furthermore, 12 NSCLC and two benign lung cell lines were characterized for promoter methylation. The in vitro tests involved a comparison of promoter methylation in 2D and 3D cultures, as well as therapeutic tests investigating the impact of CDH1/CDKN2Ap16/RASSF1A/TERT/WT1 promoter methylation on sensitivity to tyrosine kinase inhibitor (TKI) and DNA methyl-transferase inhibitor (DNMTI) treatments. We conclude that the selected markers have potential and putative impacts as diagnostic or even predictive marker genes, although a closer examination of the resulting protein expression and pathway regulation is needed.

Smoking, DNA Methylation, and Lung Function: a Mendelian Randomization Analysis to Investigate Causal Pathways

Whether smoking-associated DNA methylation has a causal effect on lung function has not been thoroughly evaluated. We first investigated the causal effects of 474 smoking-associated CpGs on forced expiratory volume in 1 s (FEV1) in UK Biobank (n = 321,047) by using two-sample Mendelian randomization (MR) and then replicated this investigation in the SpiroMeta Consortium (n = 79,055). Second, we used two-step MR to investigate whether DNA methylation mediates the effect of smoking on FEV1. Lastly, we evaluated the presence of horizontal pleiotropy and assessed whether there is any evidence for shared causal genetic variants between lung function, DNA methylation, and gene expression by using a multiple-trait colocalization ("moloc") framework. We found evidence of a possible causal effect for DNA methylation on FEV1 at 18 CpGs (p < 1.2 × 10-4). Replication analysis supported a causal effect at three CpGs (cg21201401 [LIME1 and ZGPAT], cg19758448 [PGAP3], and cg12616487 [EML3 and AHNAK] [p < 0.0028]). DNA methylation did not clearly mediate the effect of smoking on FEV1, although DNA methylation at some sites might influence lung function via effects on smoking. By using "moloc", we found evidence of shared causal variants between lung function, gene expression, and DNA methylation. These findings highlight potential therapeutic targets for improving lung function and possibly smoking cessation, although larger, tissue-specific datasets are required to confirm these results.

DNA Methylation and Type 2 Diabetes: the Use of Mendelian Randomization to Assess Causality

Purpose of Review

This review summarises recent advances in the field of epigenetics in order to understand the aetiology of type 2 diabetes (T2D).

Recent Findings

DNA methylation at a number of loci has been shown to be robustly associated with T2D, including TXNIP, ABCG1, CPT1A, and SREBF1. However, due to the cross-sectional nature of many epidemiological studies and predominant analysis in samples derived from blood rather than disease relevant tissues, inferring causality is difficult. We therefore outline the use of Mendelian randomisation (MR) as one method able to assess causality in epigenetic studies of T2D.

Summary

Epidemiological studies have been fruitful in identifying epigenetic markers of T2D. Triangulation of evidence including utilisation of MR is essential to delineate causal from non-causal biomarkers of disease. Understanding the causality of epigenetic markers in T2D more fully will aid prioritisation of CpG sites as early biomarkers to detect disease or in drug development to target epigenetic mechanisms in order to treat patients.