DNA methylation age is associated with mortality in a longitudinal Danish twin study

An epigenetic profile defining the DNA methylation age (DNAm age) of an individual has been suggested to be a biomarker of aging, and thus possibly providing a tool for assessment of health and mortality. In this study, we estimated the DNAm age of 378 Danish twins, age 30–82 years, and furthermore included a 10‐year longitudinal study of the 86 oldest‐old twins (mean age of 86.1 at follow‐up), which subsequently were followed for mortality for 8 years. We found that the DNAm age is highly correlated with chronological age across all age groups (r = 0.97), but that the rate of change of DNAm age decreases with age. The results may in part be explained by selective mortality of those with a high DNAm age. This hypothesis was supported by a classical survival analysis showing a 35% (4–77%) increased mortality risk for each 5‐year increase in the DNAm age vs. chronological age. Furthermore, the intrapair twin analysis revealed a more‐than‐double mortality risk for the DNAm oldest twin compared to the co‐twin and a ‘dose–response pattern’ with the odds of dying first increasing 3.2 (1.05–10.1) times per 5‐year DNAm age difference within twin pairs, thus showing a stronger association of DNAm age with mortality in the oldest‐old when controlling for familial factors. In conclusion, our results support that DNAm age qualifies as a biomarker of aging.     

DNA methylation in white blood cells

Alterations in DNA methylation patterns, both at specific loci and overall in the genome, have been associated with many different health outcomes. In cancer and other diseases, most of these changes have been observed at the tissue level. Data on whether DNA methylation changes in white blood cells (WBC) can serve as a useful biomarker for different health outcomes are much more limited, but rapidly emerging. Epidemiologic studies have reported associations between global WBC methylation and several different cancers including cancers of the colon, bladder, stomach, breast and head and neck, as well as schizophrenia and myelodysplastic syndrome. Evidence for WBC methylation at specific loci and disease risk is more limited, but increasing. Differences in WBC DNA methylation by selected risk factors including demographic (age, gender, race), environmental exposures (benzene, persistent organic pollutants, lead, arsenic, and air pollution), and other risk factors (cigarette smoke, alcohol drinking, body size, physical activity and diet) have been observed in epidemiologic studies though the patterns are far from consistent. Challenges in inferences from the existing data are primarily due to the cross-sectional and small size of most studies to date as well as the differences in results across assay type and source of DNA. Large, prospective studies will be needed to understand whether changes in risk factors are associated with changes in DNA methylation patterns, and if changes in DNA methylation patterns are associated with changes in disease endpoints.     

The early life social environment and DNA methylation: DNA methylation mediating the long-term impact of social environments early in life

Although epidemiological data provides evidence that there is an interaction between genetics (nature) and the social and physical environments (nurture) in human development; the main open question remains the mechanism. The pattern of distribution of methyl groups in DNA is different from cell-type to cell type and is conferring cell specific identity on DNA during cellular differentiation and organogenesis. This is an innate and highly programmed process. However, recent data suggests that DNA methylation is not only involved in cellular differentiation but that it is also involved in modulation of genome function in response to signals from the physical, biological and social environments. We propose that modulation of DNA methylation in response to environmental cues early in life serves as a mechanism of life-long genome “adaptation” that molecularly embeds the early experiences of a child (“nurture”) in the genome (“nature”). There is an emerging line of data supporting this hypothesis in rodents, non-human primates and humans that will be reviewed here. However, several critical questions remain including the identification of mechanisms that transmit the signals from the social environment to the DNA methylation/demethylation enzymes.Key words: DNA methylation, psychiatry, development, epidemiology, environment     

Cord blood buffy coat DNA methylation is comparable to whole cord blood methylation

Cord blood DNA methylation is associated with numerous health outcomes and environmental exposures. Whole cord blood DNA reflects all nucleated blood cell types, while centrifuging whole blood separates red blood cells, generating a white blood cell buffy coat. Both sample types are used in DNA methylation studies. Cell types have unique methylation patterns and processing can impact cell distributions, which may influence comparability. We evaluated differences in cell composition and DNA methylation between cord blood buffy coat and whole cord blood samples. Cord blood DNA methylation was measured with the Infinium EPIC BeadChip (Illumina) in eight individuals, each contributing buffy coat and whole blood samples. We analyzed principal components (PC) of methylation, performed hierarchical clustering, and computed correlations of mean-centered methylation between pairs. We conducted moderated t-tests on single sites and estimated cell composition. DNA methylation PCs were associated with individual (P_PC1 = 1.4 × 10^?9; P_PC2 = 2.9 × 10^?5; P_PC3 = 3.8 × 10^-5; P_PC4 = 4.2 × 10^-6; P_PC5 = 9.9 × 10^-13, P_PC6 = 1.3 × 10^?11) and not with sample type (P_PC1-6>0.7). Samples hierarchically clustered by individual. Pearson correlations of mean-centered methylation between paired samples ranged from r = 0.66 to r = 0.87. No individual site significantly differed between buffy coat and whole cord blood when adjusting for multiple comparisons (five sites had unadjusted P<10^?5). Estimated cell type proportions did not differ by sample type (P = 0.46), and estimated proportions were highly correlated between paired samples (r = 0.99). Differences in methylation and cell composition between buffy coat and whole cord blood are much lower than inter-individual variation, demonstrating that both sample preparation types can be analytically combined and compared.     

Neonatal DNA methylation patterns associate with gestational age

Risk for adverse neonatal outcome increases with declining gestational age (GA), and changes in DNA methylation may contribute to the relationship between GA and adverse health outcomes in offspring. To test this hypothesis, we evaluated the association between GA and more than 27,000 CpG sites in neonatal DNA extracted from umbilical cord blood from two prospectively-characterized cohorts: (1) a discovery cohort consisting of 259 neonates from women with a history of neuropsychiatric disorders and (2) a replication cohort consisting of 194 neonates of uncomplicated mothers. GA was determined by obstetrician report and maternal last menstrual period. The associations between proportion of DNA methylated and GA were evaluated by fitting a separate linear mixed effects model for each CpG site, adjusting for relevant covariates including neonatal sex, race, parity, birth weight percentile and chip effects. CpG sites in 39 genes were associated with GA (false discovery rate < 0.05) in the discovery cohort. The same CpG sites in 25 of these genes replicated in the replication cohort, with each association replicating in the same direction. Notably, these CpG sites were located in genes previously implicated in labor and delivery (e.g., AVP, OXT, CRHBP and ESR1) or that may influence the risk for adverse health outcomes later in life (e.g., DUOX2, TMEM176A and CASP8). All associations were independent of method of delivery or induction of labor. These results suggest neonatal DNA methylation varies with GA even in term deliveries. The potential contribution of these changes to clinically significant postnatal outcomes warrants further investigation.     

Neonatal DNA methylation patterns associate with gestational age

Risk for adverse neonatal outcome increases with declining gestational age (GA), and changes in DNA methylation may contribute to the relationship between GA and adverse health outcomes in offspring. To test this hypothesis, we evaluated the association between GA and more than 27,000 CpG sites in neonatal DNA extracted from umbilical cord blood from two prospectively-characterized cohorts: (1) a discovery cohort consisting of 259 neonates from women with a history of neuropsychiatric disorders and (2) a replication cohort consisting of 194 neonates of uncomplicated mothers. GA was determined by obstetrician report and maternal last menstrual period. The associations between proportion of DNA methylated and GA were evaluated by fitting a separate linear mixed effects model for each CpG site, adjusting for relevant covariates including neonatal sex, race, parity, birth weight percentile and chip effects. CpG sites in 39 genes were associated with GA (false discovery rate &lt; 0.05) in the discovery cohort. The same CpG sites in 25 of these genes replicated in the replication cohort, with each association replicating in the same direction. Notably, these CpG sites were located in genes previously implicated in labor and delivery (e.g., AVP, OXT, CRHBP and ESR1) or that may influence the risk for adverse health outcomes later in life (e.g., DUOX2, TMEM176A and CASP8). All associations were independent of method of delivery or induction of labor. These results suggest neonatal DNA methylation varies with GA even in term deliveries. The potential contribution of these changes to clinically significant postnatal outcomes warrants further investigation.     

Improved age determination of blood and teeth samples using a selected set of DNA methylation markers

Age estimation from DNA methylation markers has seen an exponential growth of interest, not in the least from forensic scientists. The current published assays, however, can still be improved by lowering the number of markers in the assay and by providing more accurate models to predict chronological age. From the published literature we selected 4 age-associated genes (ASPA, PDE4C, ELOVL2, and EDARADD) and determined CpG methylation levels from 206 blood samples of both deceased and living individuals (age range: 0–91 years). This data was subsequently used to compare prediction accuracy with both linear and non-linear regression models. A quadratic regression model in which the methylation levels of ELOVL2 were squared showed the highest accuracy with a Mean Absolute Deviation (MAD) between chronological age and predicted age of 3.75 years and an adjusted R² of 0.95. No difference in accuracy was observed for samples obtained either from living and deceased individuals or between the 2 genders. In addition, 29 teeth from different individuals (age range: 19–70 years) were analyzed using the same set of markers resulting in a MAD of 4.86 years and an adjusted R² of 0.74. Cross validation of the results obtained from blood samples demonstrated the robustness and reproducibility of the assay. In conclusion, the set of 4 CpG DNA methylation markers is capable of producing highly accurate age predictions for blood samples from deceased and living individuals     

DNA methylation 40 years later: Its role in human health and disease

A long path, initiated more than 40 years ago, has led to a deeper understanding of the complexity of gene regulation in eukaryotic genomes. In addition to genetic mechanisms, the imbalance in the epigenetic control of gene expression may profoundly alter the finely tuned machinery leading to gene regulation. Here, we review the impact of the studies on DNA methylation, the "primadonna" in the epigenetic scenario, on the understanding of basic phenomena, such as X inactivation and genomic imprinting. The effect of deregulation of DNA methylation on human health, will be also discussed. Finally, an attempt to predict future directions of this rapidly evolving field has been proposed, with the certainty that, fortunately, science is always better than predictions.     

外周全血中与老化相关的DNA甲基化标记的来源

机体老化与癌症、神经退行性疾病等许多复杂疾病相关。目前,研究者已在外周全血中识别了大量的与老化相关的DNA甲基化标记,这些标记可能反映外周血白细胞在机体老化过程中发生的变化,也可能反映外周血中与年龄相关的细胞构成比例的变化。文章利用3组正常个体外周全血DNA甲基化谱,采用Spearman秩相关分析识别了与老化相关的CpG甲基化位点(age-related DNA methylation CpG sites, arCpGs)并评价了其可重复性;利用去卷积算法估计了各外周血样本中髓性和淋巴性细胞的比例并分析了其与年龄的相关性;比较了在外周全血、CD4+T细胞和CD14+单核细胞中识别的arCpGs的一致性。结果显示,在独立外周全血数据中识别的arCpGs具有显著的可重复性(超几何检验,P=1.65×10^-11)。外周血髓性和淋巴性细胞的比例分别与年龄显著正、负相关(Spearman秩相关检验,P<0.05,r≤0.22),它们间DNA甲基化水平差异较大的CpG位点倾向于在外周全血中被识别为arCpGs。在CD4+T细胞中识别的arCpGs与在外周全血中识别的arCpGs显著交叠(超几何检验,P=6.14×10^-12),且99.1%的交叠位点在CD4+T细胞及外周全血中的DNA甲基化水平与年龄的正、负相关性一致。尽管在CD14+单核细胞中识别的arCpGs与在外周全血中识别的arCpGs并不显著交叠,但是在交叠的51个arCpGs中,有90.1%的位点在CD14+单核细胞、外周全血以及CD4+T细胞中的DNA甲基化水平与年龄的正、负相关性一致,提示它们可能主要反映细胞间共同的改变。在外周全血中识别的arCpGs主要反映某些白细胞共同或特异的DNA甲基化改变,但是也有一部分反映外周血细胞比例构成的变化。     

Familial resemblances in blood leukocyte DNA methylation levels

Epigenetic factors such as DNA methylation are DNA alterations affecting gene expression that can convey environmental information through generations. Only a few studies have demonstrated epigenetic inheritance in humans. Our objective is to quantify genetic and common environmental determinants of familial resemblances in DNA methylation levels, using a family based sample. DNA methylation was measured in 48 French Canadians from 16 families as part of the GENERATION Study. We used the Illumina HumanMethylation450 BeadChip array to measure DNA methylation levels in blood leukocytes on 485,577 CpG sites. Heritability was assessed using the variance components method implemented in the QTDT software, which partitions the variance into polygenic (G), common environmental (C), and non-shared environmental (E) effects. We computed maximal heritability, genetic heritability, and common environmental effect for all probes (12.7%, 8.2%, and 4.5%, respectively) and for statistically significant probes (81.8%, 26.9%, and 54.9%, respectively). Higher maximal heritability was observed in the Major Histocompatibility Complex region on chromosome 6. In conclusion, familial resemblances in DNA methylation levels are mainly attributable to genetic factors when considering the average across the genome, but common environmental effect plays an important role when considering statistically significant probes. Further epigenome-wide studies on larger samples combined with genome-wide genotyping studies are needed to better understand the underlying mechanisms of DNA methylation heritability.     

DNA methylation age of human tissues and cell types

Background

It is not yet known whether DNA methylation levels can be used to accurately predict age across a broad spectrum of human tissues and cell types, nor whether the resulting age prediction is a biologically meaningful measure.

Results

I developed a multi-tissue predictor of age that allows one to estimate the DNA methylation age of most tissues and cell types. The predictor, which is freely available, was developed using 8,000 samples from 82 Illumina DNA methylation array datasets, encompassing 51 healthy tissues and cell types. I found that DNA methylation age has the following properties: first, it is close to zero for embryonic and induced pluripotent stem cells; second, it correlates with cell passage number; third, it gives rise to a highly heritable measure of age acceleration; and, fourth, it is applicable to chimpanzee tissues. Analysis of 6,000 cancer samples from 32 datasets showed that all of the considered 20 cancer types exhibit significant age acceleration, with an average of 36 years. Low age-acceleration of cancer tissue is associated with a high number of somatic mutations and TP53 mutations, while mutations in steroid receptors greatly accelerate DNA methylation age in breast cancer. Finally, I characterize the 353 CpG sites that together form an aging clock in terms of chromatin states and tissue variance.

Conclusions

I propose that DNA methylation age measures the cumulative effect of an epigenetic maintenance system. This novel epigenetic clock can be used to address a host of questions in developmental biology, cancer and aging research.     

The early life social environment and DNA methylation

Although epidemiological data provides evidence that there is an interaction between genetics (nature) and the social and physical environments (nurture) in human development; the main open question remains the mechanism. The pattern of distribution of methyl groups in DNA is different from cell-type to cell type and is conferring cell specific identity on DNA during cellular differentiation and organogenesis. This is an innate and highly programmed process. However, recent data suggests that DNA methylation is not only involved in cellular differentiation but that it is also involved in modulation of genome function in response to signals from the physical, biological and social environments. We propose that modulation of DNA methylation in response to environmental cues early in life serves as a mechanism of life-long genome "adaptation" that molecularly embeds the early experiences of a child ("nurture") in the genome ("nature"). There is an emerging line of data supporting this hypothesis in rodents, non-human primates and humans that will be reviewed here. However, several critical questions remain including the identification of mechanisms that transmit the signals from the social environment to the DNA methylation/demethylation enzymes.     

DNA methylation dynamics during the mammalian life cycle

DNA methylation is dynamically remodelled during the mammalian life cycle through distinct phases of reprogramming and de novo methylation. These events enable the acquisition of cellular potential followed by the maintenance of lineage-restricted cell identity, respectively, a process that defines the life cycle through successive generations. DNA methylation contributes to the epigenetic regulation of many key developmental processes including genomic imprinting, X-inactivation, genome stability and gene regulation. Emerging sequencing technologies have led to recent insights into the dynamic distribution of DNA methylation during development and the role of this epigenetic mark within distinct genomic contexts, such as at promoters, exons or imprinted control regions. Additionally, there is a better understanding of the mechanistic basis of DNA demethylation during epigenetic reprogramming in primordial germ cells and during pre-implantation development. Here, we discuss our current understanding of the developmental roles and dynamics of this key epigenetic system.     

Early life socioeconomic factors and genomic DNA methylation in mid-life

Epigenetic modifications may be one mechanism linking early life factors, including parental socioeconomic status (SES), to adult onset disease risk. However, SES influences on DNA methylation patterns remain largely unknown. In a US birth cohort of women, we examined whether indicators of early life and adult SES were associated with white blood cell methylation of repetitive elements (Sat2, Alu and LINE-1) in adulthood. Low family income at birth was associated with higher Sat2 methylation (β = 19.7, 95% CI: 0.4, 39.0 for lowest vs. highest income quartile) and single parent family was associated with higher Alu methylation (β = 23.5, 95% CI: 2.6, 44.4), after adjusting for other early life factors. Lower adult education was associated with lower Sat2 methylation (β = -16.7, 95% CI: -29.0, -4.5). There were no associations between early life SES and LINE-1 methylation. Overall, our preliminary results suggest possible influences of SES across the life-course on genomic DNA methylation in adult women. However, these preliminary associations need to be replicated in larger prospective studies.