Search

Background: Methylation quantitative trait loci (mQTLs) are the genetic variants that may affect the DNA methylation patterns of CpG sites. However, their roles in influencing the disturbances of smoking-related epigenetic changes have not been well established. This study was conducted to address whether mQTLs exist in the vicinity of smoking-related CpG sites (± 50 kb) and to examine their associations with smoking exposure and all-cause mortality in older adults. Results: We obtained DNA methylation profiles in whole blood samples by Illumina Infinium Human Methylation 450 BeadChip array of two independent subsamples of the ESTHER study (discovery set, n = 581; validation set, n = 368) and their corresponding genotyping data using the Illumina Infinium OncoArray BeadChip. After correction for multiple testing (FDR), we successfully identified that 70 out of 151 previously reported smoking-related CpG sites were significantly associated with 192 SNPs within the 50 kb search window of each locus. The 192 mQTLs significantly influenced the active smoking-related DNA methylation changes, with percentage changes ranging from 0.01 to 18.96%, especially for the weakly/moderately smoking-related CpG sites. However, these identified mQTLs were not directly associated with active smoking exposure or all-cause mortality. Conclusions: Our findings clearly demonstrated that if not dealt with properly, the mQTLs might impair the power of epigenetic-based models of smoking exposure to a certain extent. In addition, such genetic variants could be the key factor to distinguish between the heritable and smoking-induced impact on epigenome disparities. These mQTLs are of special importance when DNA methylation markers measured by Illumina Infinium assay are used for any comparative population studies related to smoking-related cancers and chronic diseases. [ABSTRACT FROM AUTHOR]

Background: Colorectal cancer (CRC) is the third most common cancer worldwide. If detected at an early stage, prognosis is good. Despite increasing evidence for the benefits of implemented screening programs, such as screening colonoscopy, compliance is rather low. Hence there is demand for non-invasive tests for the early detection of CRC with high acceptance in population-wide screening. The objective of this study was to identify and evaluate leukocyte DNA methylation patterns as a potential biomarker for early detection of CRC. Methods: Blood samples of patients scheduled for a screening colonoscopy were collected before the procedure. Additionally, blood samples from CRC cases recruited in a clinical setting were collected. DNA was extracted from leukocytes, and DNA methylation was measured with the Infinium 450K BeadChip. In total, 46 CRC cases and 140 controls from the screening setting and 93 CRC cases from the clinical setting were measured. Results: An epigenome-wide discovery revealed two CpG sites in the promoter region of KIAA1549L that were significantly differentially methylated between cases and controls. A third marker in the body region of BCL2 was discovered in a candidate approach testing biomarkers reported in the literature. Logistic regression models built on these three markers yielded an optimism-corrected c-statistic of 0.69 in the screening setting and 0.73 in the clinical setting. Conclusions: Although diagnostic performance of the DNA methylation signature identified in this first epigenomewide association study of leukocyte DNA methylation with CRC in a screening setting is not competitive with established screening tests, the identified markers may contribute to multimarker panels for early detection of CRC. [ABSTRACT FROM AUTHOR]

Background: There is a growing interest in simple molecular biomarkers for biological aging. Age-associated DNA methylation (DNAm) changes at specific CG dinucleotides can be combined into epigenetic age predictors to estimate chronological age-and the deviation of chronological and predicted age (Δage) seems to be associated with all-cause mortality. In this study, we have further validated this association and analyzed whether or not individual age-associated CG-dinucleotides (CpGs) are related to life expectancy. Findings: In the German ESTHER cohort, we used 864 DNAm profiles of blood samples as the discovery set and 1000 DNAm profiles as the validation set to predict chronological age with three previously reported age predictors-based on 99, 71, or 353 age-associated CpGs. Several of these individual CpGs were significantly associated with life expectancy, and for some of these CpGs, this was even reproducible in the independent datasets. Notably, those CpGs that revealed significant association with life expectancy were overall rather hypomethylated upon aging. Conclusion: Individual age-associated CpGs may provide biomarkers for all-cause mortality-but confounding factors need to be critically taken into consideration and alternative methods, which facilitate more quantitative measurements at individual CpGs, might be advantageous. Our data suggest that particularly specific CpGs that become hypomethylated upon aging are indicative of biological aging. [ABSTRACT FROM AUTHOR]

Background: Newly established blood DNA methylation markers that are strongly associated with smoking might open new avenues for lung cancer (LC) screening. We aimed to assess the performance of the top hits from previous epigenome-wide association studies in prediction of LC incidence. In a prospective nested case-control study, DNA methylation at AHRR (cg05575921), 6p21.33 (cg06126421), and F2RL3 (cg03636183) were measured by pyrosequencing in baseline whole blood samples of 143 incident LC cases identified during 11 years of follow-up and 457 age- and sex-matched controls without diagnosis of LC until the end of follow-up. The individual and joint associations of the 3 markers with LC risk were estimated by logistic regression, adjusted for potential confounders including smoking status and cigarette pack-years. The predictive performance was evaluated for both the individual markers and their combinations derived from multiple algorithms. Results: Pronounced demethylation of all 3 markers was observed at baseline among cases compared to controls. Risk of developing LC increased with decreasing DNA methylation levels, with adjusted ORs (95% CI) of 15.86 (4.18–60.17), 8. 12 (2.69–4.48), and 10.55 (3.44–32.31), respectively, for participants in the lowest quartile of AHRR, 6p21.33, and F2RL3 compared to participants in the highest 2 quartiles of each site among controls. The individual 3 markers exhibited similar accuracy in predicting LC incidence, with AUCs ranging from 0.79 to 0.81. Combination of the 3 markers did not improve the predictive performance (AUC=0.80). The individual markers or their combination outperformed self-reported smoking exposure particularly in light smokers. No variation in risk prediction was identified with respect to age, follow-up time, and histological subtypes. Conclusions: AHRR, 6p21.33, and F2RL3 methylation in blood DNA are predictive for LC development, which might be useful for identification of risk groups for further specific screening, such as CT examination. [ABSTRACT FROM AUTHOR]

Background: Previous studies have developed models predicting methylation age from DNA methylation in blood and other tissues (epigenetic clock) and suggested the difference between DNA methylation and chronological ages as a marker of healthy aging. The goal of this study was to confirm and expand such observations by investigating whether different concepts of the epigenetic clocks in a population-based cohort are associated with cancer, cardiovascular, and all-cause mortality. Results: DNA methylation age was estimated in a cohort of 1863 older people, and the difference between age predicted by DNA methylation and chronological age (Δage) was calculated. A case-cohort design and weighted proportional Cox hazard models were used to estimate associations of Δage with cancer, cardiovascular, and all-cause mortality. Hazard ratios for Δage (per 5 years) calculated using the epigenetic clock developed by Horvath were 1.23 (95 % CI 1.10-1.38) for all-cause mortality, 1.22 (95 % CI 1.03-1.45) for cancer mortality, and 1.19 (95 % CI 0.98-1.43) for cardiovascular mortality after adjustment for batch effects, age, sex, educational level, history of chronic diseases, hypertension, smoking status, body mass index, and leucocyte distribution. Associations were similar but weaker for Δage calculated using the epigenetic clock developed by Hannum. Conclusions: These results show that age acceleration in terms of the difference between age predicted by DNA methylation and chronological age is an independent predictor of all-cause and cause-specific mortality and may be useful as a general marker of healthy aging. [ABSTRACT FROM AUTHOR]

Active smoking is a major preventable public health problem and an established critical factor for epigenetic modification. In this systematic review, we identified 17 studies addressing the association of active smoking exposure with methylation modifications in blood DNA, including 14 recent epigenome-wide association studies (EWASs) and 3 gene-specific methylation studies (GSMSs) on the gene regions identified by EWASs. Overall, 1460 smoking-associated CpG sites were identified in the EWASs, of which 62 sites were detected in multiple (≥3) studies. The three most frequently reported CpG sites (genes) in whole blood samples were cg05575921 (AHRR), cg03636183 (F2RL3), and cg19859270 (GPR15), followed by other loci within intergenic regions 2q37.1 and 6p21.33. These significant smoking-related genes were further assessed by specific methylation assays in three GSMSs and reflected not only current but also lifetime or long-term exposure to active smoking. In conclusion, this review summarizes the evidences for the use of blood DNA methylation patterns as biomarkers of smoking exposure for research and clinical practice. In particular, it provides a reservoir for constructing a smoking exposure index score which could be used to more precisely quantify long-term smoking exposure and evaluate the risks of smoking-induced diseases. [ABSTRACT FROM AUTHOR]