Individual and joint contributions of genetic and methylation risk scores for enhancing lung cancer risk stratification: data from a population-based cohort in Germany

Development of a metabolomic risk score for exposure to traffic-related air pollution: A multi-cohort study

To synthesize vast amounts of high-throughput biological information, omics-fields like epigenetics have applied risk scores to develop biomarkers for environmental exposures. Extending the risk score analytic tool to the metabolomic data would be highly beneficial. This research aimed to develop and evaluate metabolomic risk score (metRS) approaches reflecting the biological response to traffic-related air pollution (TRAP) exposure (fine particulate matter, black carbon, and nitrogen dioxide). A simulation study compared three metRS methodologies: elastic net regression, which uses penalized regression to select metabolites, and two variations of thresholding, where a p-value cutoff is used to select metabolites. The methods performance was compared to assess 1) ability to correctly select metabolites associated with daily TRAP and 2) ability of the risk score to predict daily TRAP exposure. Power calculations and false discovery rates (FDR) were calculated for each approach. This metRS was applied to two real cohorts, the Center for Health Discovery and Wellbeing (CHDWB, n = 180) and Environment and Reproductive Health (EARTH, n = 200). In simulations, elastic net regression consistently presented inflated FDR for both high and low effect sizes and across all three sample sizes (n = 200; 500; 1000). Power to detect correct metabolites exceeded 0.8 for all three sample sizes in all three methods. In the real data application assessing associations of metabolomics risk scores and TRAP, associations were largely null. While we did not identify strong associations between the risk scores and TRAP in the real data application, metabolites selected by the risk score approaches were enriched in pathways that are well-known for their association with TRAP. These results demonstrate that certain methodologies to construct metabolomics risk scores are statistically robust and valid; however, standardized metabolic profiling and large sample sizes are required.

A clinically effective model based on cell-free DNA methylation and low-dose CT for risk stratification of pulmonary nodules

Accurate, non-invasive, and cost-effective tools are needed to assist pulmonary nodule diagnosis and management due to increasing detection by low-dose computed tomography (LDCT). We perform genome-wide methylation sequencing on malignant and non-malignant lung tissues and designed a panel of 263 differential DNA methylation regions, which is used for targeted methylation sequencing on blood cell-free DNA (cfDNA) in two prospectively collected and retrospectively analyzed multicenter cohorts. We develop and optimize an integrative model for risk stratification of pulmonary nodules based on 40 cfDNA methylation biomarkers, age, and five simple computed tomography (CT) imaging features using machine learning approaches and validate its good performance in two cohorts. Using the two-threshold strategy can effectively reduce unnecessary invasive surgeries, overtreatment costs, and injury for patients with benign nodules while advising immediate treatment for patients with lung cancer, which can potentially improve the overall diagnosis of lung cancer following LDCT/CT screening.

A review of disease risk prediction methods and applications in the omics era

Risk prediction and disease prevention are the innovative care challenges of the 21st century. Apart from freeing the individual from the pain of disease, it will lead to low medical costs for society. Until very recently, risk assessments have ushered in a new era with the emergence of omics technologies, including genomics, transcriptomics, epigenomics, proteomics, and so on, which potentially advance the ability of biomarkers to aid prediction models. While risk prediction has achieved great success, there are still some challenges and limitations. We reviewed the general process of omics-based disease risk model construction and the applications in four typical diseases. Meanwhile, we highlighted the problems in current studies and explored the potential opportunities and challenges for future clinical practice.

Cigarette Smoking and E-cigarette Use Induce Shared DNA Methylation Changes Linked to Carcinogenesis

Tobacco use is a major modifiable risk factor for adverse health outcomes, including cancer, and elicits profound epigenetic changes thought to be associated with long-term cancer risk. While electronic cigarettes (e-cigarettes) have been advocated as harm reduction alternatives to tobacco products, recent studies have revealed potential detrimental effects, highlighting the urgent need for further research into the molecular and health impacts of e-cigarettes. Here, we applied computational deconvolution methods to dissect the cell- and tissue-specific epigenetic effects of tobacco or e-cigarette use on DNA methylation (DNAme) in over 3,500 buccal/saliva, cervical, or blood samples, spanning epithelial and immune cells at directly and indirectly exposed sites. The 535 identified smoking-related DNAme loci [cytosine-phosphate-guanine sites (CpG)] clustered into four functional groups, including detoxification or growth signaling, based on cell type and anatomic site. Loci hypermethylated in buccal epithelial cells of smokers associated with NOTCH1/RUNX3/growth factor receptor signaling also exhibited elevated methylation in cancer tissue and progressing lung carcinoma in situ lesions, and hypermethylation of these sites predicted lung cancer development in buccal samples collected from smokers up to 22 years prior to diagnosis, suggesting a potential role in driving carcinogenesis. Alarmingly, these CpGs were also hypermethylated in e-cigarette users with a limited smoking history. This study sheds light on the cell type-specific changes to the epigenetic landscape induced by smoking-related products.

SIGNIFICANCE

The use of both cigarettes and e-cigarettes elicits cell- and exposure-specific epigenetic effects that are predictive of carcinogenesis, suggesting caution when broadly recommending e-cigarettes as aids for smoking cessation.

Cancer-specific risk prediction with a serum microRNA signature

We recently derived and validated a serum-based microRNA risk score (miR-score) that predicted colorectal cancer (CRC) occurrence with very high accuracy within 14 years of follow-up in a population-based cohort study from Germany (ESTHER cohort). Here, we aimed to evaluate associations of the CRC-specific miR-score with the risk of developing other common cancers, including female breast cancer (BC), lung cancer (LC), and prostate cancer (PC), in the ESTHER cohort. MicroRNAs (miRNAs) were profiled by quantitative real-time PCR in serum samples collected at baseline from randomly selected incident cases of BC (n = 90), LC (n = 88), and PC (n = 93) and participants without diagnosis of CRC, LC, BC, or PC (controls, n = 181) until the end of the 17-year follow-up. Multivariate logistic regression models were used to evaluate the associations of the miR-score with BC, LC, and PC incidence. The miR-score showed strong inverse associations with BC and LC incidence [odds ratio per 1 standard deviation increase: 0.60 (95% confidence interval [CI] 0.43-0.82), p = 0.0017, and 0.64 (95% CI 0.48-0.84),p = 0.0015, respectively]. Associations with PC were not statistically significant but pointed in the positive direction. Our study highlights the potential of serum-based miRNA biomarkers for cancer-specific risk prediction. Further large cohort studies aiming to investigate, validate, and optimize the use of circulating miRNA signatures for cancer risk assessment are warranted.

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.

Pruning and thresholding approach for methylation risk scores in multi-ancestry populations

Recent efforts have focused on developing methylation risk scores (MRS), a weighted sum of the individual's DNA methylation (DNAm) values of pre-selected CpG sites. Most of the current MRS approaches that utilize Epigenome-wide association studies (EWAS) summary statistics only include genome-wide significant CpG sites and do not consider co-methylation. New methods that relax the p-value threshold to include more CpG sites and account for the inter-correlation of DNAm might improve the predictive performance of MRS. We paired informed co-methylation pruning with P-value thresholding to generate pruning and thresholding (P+T) MRS and evaluated its performance among multi-ancestry populations. Through simulation studies and real data analyses, we demonstrated that pruning provides an improvement over simple thresholding methods for prediction of phenotypes. We demonstrated that European-derived summary statistics can be used to develop P+T MRS among other populations such as African populations. However, the prediction accuracy of P+T MRS may differ across multi-ancestry population due to environmental/cultural/social differences.

Evidence relating cigarette, cigar and pipe smoking to lung cancer and chronic obstructive pulmonary disease: Meta-analysis of recent data from three regions

BACKGROUND

There is a need to have up-to-date information for various diseases on the risk related to the use of different smoked products and the use of other nicotine-containing products. Here, we contribute to the information pool by presenting up-to-date quantitative evidence for North America, Europe and Japan and for both lung cancer and chronic obstructive pulmonary disease (COPD) on the relative risk (RR) relating to current vs never product use for each of the three smoked tobacco products, cigarettes, cigars and pipes.

AIM

To estimate lung cancer and COPD current smoking RRs for the three products using recent data for the three regions.

METHODS

Publications in English from 2010 to 2020 were considered that, based on epidemiological studies in the three regions, estimated the current smoking RR of lung cancer and/or COPD for one or more of the three products. The studies should involve at least 100 cases of the disease considered, not be restricted to specific lung cancer types or populations with specific medical conditions, and should be of cohort or nested case-control study design or randomized controlled trials. Literature searches were conducted on MEDLINE separately for lung cancer and for COPD, examining titles and abstracts initially, and then full texts. Additional papers were sought from reference lists of selected papers, reviews and meta-analyses. For each study identified, the most recent available data on each product were entered on current smoking, as well as on characteristics of the study and the RR estimates. Combined RR estimates were derived using random-effects meta-analysis. For cigarette smoking, where far more data were available, heterogeneity was studied by a wide range of factors. For cigar and pipe smoking, a more limited heterogeneity analysis was carried out. Results were compared with those from previous meta-analyses published since 2000.

RESULTS

Current cigarette smoking: For lung cancer, 44 studies (26 North American, 14 European, three Japanese, and one in multiple continents), gave an overall estimate of 12.14 [95% confidence interval (CI) 10.30-14.30]. The estimates were higher (heterogeneity P < 0.001) for North American (15.15, CI 12.77-17.96) and European studies (12.30, CI 9.77-15.49) than for Japanese studies (3.61, CI 2.87-4.55), consistent with previous evidence of lower RRs for Asia. RRs were higher (P < 0.05) for death (14.85, CI 11.99-18.38) than diagnosis (10.82, CI 8.61-13.60). There was some variation (P < 0.05) by study population, with higher RRs for international and regional studies than for national studies and studies of specific populations. RRs were higher in males, as previously reported, the within-study male/female ratio of RRs being 1.52 (CI 1.20-1.92). RRs did not vary significantly (P ≥ 0.05) by other factors. For COPD, RR estimates were provided by 18 studies (10 North American, seven European, and one Japanese). The overall estimate of 9.19 (CI 6.97-12.13), was based on heterogeneous data (P < 0.001), and higher than reported earlier. There was no (P > 0.1) variation by sex, region or exclusive use, but limited evidence (0.05 < P < 0.1) that RR estimates were greater where cases occurring shortly after baseline were ignored; where bronchiectasis was excluded from the COPD definition; and with greater confounder adjustment. Within-study comparisons showed adjusted RRs exceeded unadjusted RRs. Current cigar smoking: Three studies gave an overall lung cancer RR of 2.73 (CI 2.36-3.15), with no heterogeneity, lower than the 4.67 (CI 3.49-6.25) reported in an earlier review. Only one study gave COPD results, the RR (2.44, CI 0.98-6.05) being imprecise. Current pipe smoking: Four studies gave an overall lung cancer RR of 4.93 (CI 1.97-12.32), close to the 5.20 (CI 3.50-7.73) given earlier. However, the estimates were heterogeneous, with two above 10, and two below 3. Only one study gave COPD results, the RR (1.12, CI 0.29-4.40), being imprecise. For both diseases, the lower RR estimates for cigars and for pipes than for current smoking of cigarettes aligns with earlier published evidence.

CONCLUSION

Current cigarette smoking substantially increases lung cancer and COPD risk, more so in North America and Europe than Japan. Limited evidence confirms lower risks for cigars and pipes than cigarettes.

Epigenome-wide DNA methylation signature of plasma zinc and their mediation roles in the association of zinc with lung cancer risk

Essential trace element zinc is associated with decreased lung cancer risk, but underlying mechanisms remain unclear. This study aimed to investigate role of DNA methylation in zinc-lung cancer association. We conducted a case-cohort study within prospective Dongfeng-Tongji cohort, including 359 incident lung cancer cases and a randomly selected sub-cohort of 1399 participants. Epigenome-wide association study (EWAS) was used to examine association of plasma zinc with DNA methylation in peripheral blood. For the zinc-related CpGs, their mediation effects on zinc-lung cancer association were assessed; their diagnostic performance for lung cancer was testified in the case-cohort study and further validated in another 126 pairs of lung cancer case-control study. We identified 28 CpGs associated with plasma zinc at P < 1.0 × 10^-5 and seven of them (cg07077080, cg01077808, cg17749033, cg15554270, cg26125625, cg10669424, and cg15409013 annotated to GSR, CALR3, SLC16A3, PHLPP2, SLC12A8, VGLL4, and ADAMTS16, respectively) were associated with incident risk of lung cancer. Moreover, the above seven CpGs were differently methylated between 126 pairs of lung cancer and adjacent normal lung tissues and had the same directions with EWAS of zinc. They could mediate a separate 7.05%∼22.65% and a joint 29.42% of zinc-lung cancer association. Compared to using traditional factors, addition of methylation risk score exerted improved discriminations for lung cancer both in case-cohort study [area under the curve (AUC) = 0.818 vs. 0.738] and in case-control study (AUC = 0.816 vs. 0.646). Our results provide new insights for the biological role of DNA methylation in the inverse association of zinc with incident lung cancer.

Complex trait methylation scores in the prediction of major depressive disorder

BACKGROUND

DNA methylation (DNAm) is associated with time-varying environmental factors that contribute to major depressive disorder (MDD) risk. We sought to test whether DNAm signatures of lifestyle and biochemical factors were associated with MDD to reveal dynamic biomarkers of MDD risk that may be amenable to lifestyle interventions.

METHODS

Here, we calculated methylation scores (MS) at multiple p-value thresholds for lifestyle (BMI, smoking, alcohol consumption, and educational attainment) and biochemical (high-density lipoprotein (HDL) and total cholesterol) factors in Generation Scotland (GS) (N=9,502) and in a replication cohort (ALSPAC_adults, N=565), using CpG sites reported in previous well-powered methylome-wide association studies. We also compared their predictive accuracy for MDD to a MDD MS in an independent GS sub-sample (N=4,432).

FINDINGS

Each trait MS was significantly associated with its corresponding phenotype in GS (β_range=0.089-1.457) and in ALSPAC (β_range=0.078-2.533). Each MS was also significantly associated with MDD before and after adjustment for its corresponding phenotype in GS (β_range=0.053-0.145). After accounting for relevant lifestyle factors, MS for educational attainment (β=0.094) and alcohol consumption (MS_p-value<0.01-0.5; β_range=-0.069-0.083) remained significantly associated with MDD in GS. Smoking (AUC=0.569) and educational attainment (AUC=0.585) MSs could discriminate MDD from controls better than the MDD MS (AUC=0.553) in the independent GS sub-sample. Analyses implicating MDD did not replicate across ALSPAC, although the direction of effect was consistent for all traits when adjusting for the MS corresponding phenotypes.

INTERPRETATION

We showed that lifestyle and biochemical MS were associated with MDD before and after adjustment for their corresponding phenotypes (p_nominal<0.05), but not when smoking, alcohol consumption, and BMI were also included as covariates. MDD results did not replicate in the smaller, female-only independent ALSPAC cohort (N_ALSPAC=565; N_GS=9,502), potentially due to demographic differences or low statistical power, but effect sizes were consistent with the direction reported in GS. DNAm scores for modifiable MDD risk factors may contribute to disease vulnerability and, in some cases, explain additional variance to their observed phenotypes.

FUNDING

Wellcome Trust.

Integration of Genomic Risk Scores to Improve the Prediction of Childhood Asthma Diagnosis

Genome-wide and epigenome-wide association studies have identified genetic variants and differentially methylated nucleotides associated with childhood asthma. Incorporation of such genomic data may improve performance of childhood asthma prediction models which use phenotypic and environmental data. Using genome-wide genotype and methylation data at birth from the Isle of Wight Birth Cohort (n = 1456), a polygenic risk score (PRS), and newborn (nMRS) and childhood (cMRS) methylation risk scores, were developed to predict childhood asthma diagnosis. Each risk score was integrated with two previously published childhood asthma prediction models (CAPE and CAPP) and were validated in the Manchester Asthma and Allergy Study. Individually, the genomic risk scores demonstrated modest-to-moderate discriminative performance (area under the receiver operating characteristic curve, AUC: PRS = 0.64, nMRS = 0.55, cMRS = 0.54), and their integration only marginally improved the performance of the CAPE (AUC: 0.75 vs. 0.71) and CAPP models (AUC: 0.84 vs. 0.82). The limited predictive performance of each genomic risk score individually and their inability to substantially improve upon the performance of the CAPE and CAPP models suggests that genetic and epigenetic predictors of the broad phenotype of asthma are unlikely to have clinical utility. Hence, further studies predicting specific asthma endotypes are warranted.

Exploring the Ethics of Implementation of Epigenomics Technologies in Cancer Screening: A Focus Group Study

New epigenomics technologies are being developed and used for the detection and prediction of various types of cancer. By allowing for timely intervention or preventive measures, epigenomics technologies show promise for public health, notably in population screening. In order to assess whether implementation of epigenomics technologies in population screening may be morally acceptable, it is important to understand – in an early stage of development – ethical and societal issues that may arise. We held 3 focus groups with experts in science and technology studies (STS) (n = 13) in the Netherlands, on 3 potential future applications of epigenomic technologies in screening programmes of increasing scope: cervical cancer, female cancers and ‘global’ cancer. On the basis of these discussions, this paper identifies ethical issues pertinent to epigenomics-based population screening, such as risk communication, trust and public acceptance; personal responsibility, stigmatisation and societal pressure, and data protection and data governance. It also points out how features of epigenomics (eg, modifiability) and changing concepts (eg, of cancer) may challenge the existing evaluative framework for screening programmes. This paper aims to anticipate and prepare for future ethical challenges when epigenomics technologies can be tested and introduced in public health settings.

Smoking-associated upregulation of CBX3 suppresses ARHGAP24 expression to activate Rac1 signaling and promote tumor progression in lung adenocarcinoma

Although tobacco smoking is a risk factor for lung adenocarcinoma (LUAD), the mechanisms by which tobacco smoking induces LUAD development remain elusive. Histone methylation levels in human bronchial epithelial cells have been reported to increase after exposure to cigarettes. In this study, we explored the mechanisms regulating histone methylation in LUAD in response to smoking. We found that the histone H3K9 methylation reader CBX3 was upregulated in current smokers with LUAD, and that CBX3 overexpression promoted LUAD progression. Functional enrichment analyses revealed that CBX3 regulated the activation of Rho GTPases in LUAD. We also found that by forming a complex with TRIM28, TRIM24, and RBBP4, CBX3 repressed the expression of ARHGAP24 and increased the amount of active Rac1 in LUAD cells. Collectively, these results suggest that smoking associated upregulation of CBX3 promotes LUAD progression by activating the ARHGAP24/Rac1 pathway. Hence, the CBX3/ARHGAP24/Rac1 axis may represent a promising therapeutic target in smoking-induced LUAD.

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.