Age-associated DNA methylation in pediatric populations

A multi-tissue full lifespan epigenetic clock for mice

Human DNA-methylation data have been used to develop highly accurate biomarkers of aging ("epigenetic clocks"). Recent studies demonstrate that similar epigenetic clocks for mice (Mus Musculus) can be slowed by gold standard anti-aging interventions such as calorie restriction and growth hormone receptor knock-outs. Using DNA methylation data from previous publications with data collected in house for a total 1189 samples spanning 193,651 CpG sites, we developed 4 novel epigenetic clocks by choosing different regression models (elastic net- versus ridge regression) and by considering different sets of CpGs (all CpGs vs highly conserved CpGs). We demonstrate that accurate age estimators can be built on the basis of highly conserved CpGs. However, the most accurate clock results from applying elastic net regression to all CpGs. While the anti-aging effect of calorie restriction could be detected with all types of epigenetic clocks, only ridge regression based clocks replicated the finding of slow epigenetic aging effects in dwarf mice. Overall, this study demonstrates that there are trade-offs when it comes to epigenetic clocks in mice. Highly accurate clocks might not be optimal for detecting the beneficial effects of anti-aging interventions.

Early-life adversity and neurological disease: age-old questions and novel answers

Neurological illnesses, including cognitive impairment, memory decline and dementia, affect over 50 million people worldwide, imposing a substantial burden on individuals and society. These disorders arise from a combination of genetic, environmental and experiential factors, with the latter two factors having the greatest impact during sensitive periods in development. In this Review, we focus on the contribution of adverse early-life experiences to aberrant brain maturation, which might underlie vulnerability to cognitive brain disorders. Specifically, we draw on recent robust discoveries from diverse disciplines, encompassing human studies and experimental models. These discoveries suggest that early-life adversity, especially in the perinatal period, influences the maturation of brain circuits involved in cognition. Importantly, new findings suggest that fragmented and unpredictable environmental and parental signals comprise a novel potent type of adversity, which contributes to subsequent vulnerabilities to cognitive illnesses via mechanisms involving disordered maturation of brain 'wiring'.

Age-related DNA hydroxymethylation is enriched for gene expression and immune system processes in human peripheral blood

DNA methylation (DNAm) has a well-established association with age in many tissues, including peripheral blood mononuclear cells (PBMCs). Compared to DNAm, the closely related epigenetic modification known as DNA hydroxymethylation (DNAhm) was much more recently discovered in mammals. Preliminary investigations have observed a positive correlation between gene body DNAhm and cis-gene expression. While some of these studies have observed an association between age and global DNAhm, none have investigated region-specific age-related DNAhm in human blood samples. In this study, we investigated DNAhm and gene expression in PBMCs of 10 young and 10 old, healthy female volunteers. Thousands of regions were differentially hydroxymethylated in the old vs. young individuals in gene bodies, exonic regions, enhancers, and promoters. Consistent with previous work, we observed directional consistency between age-related differences in DNAhm and gene expression. Further, age-related DNAhm and genes with high levels of DNAhm were enriched for immune system processes which may support a role of age-related DNAhm in immunosenescence.

Continuous Developmental and Early Life Trichloroethylene Exposure Promoted DNA Methylation Alterations in Polycomb Protein Binding Sites in Effector/Memory CD4+ T Cells

Trichloroethylene (TCE) is an industrial solvent and drinking water pollutant associated with CD4⁺ T cell-mediated autoimmunity. In our mouse model, discontinuation of TCE exposure during adulthood after developmental exposure did not prevent immunotoxicity. To determine whether persistent effects were linked to epigenetic changes we conducted whole genome reduced representation bisulfite sequencing (RRBS) to evaluate methylation of CpG sites in autosomal chromosomes in activated effector/memory CD4⁺ T cells. Female MRL+/+ mice were exposed to vehicle control or TCE in the drinking water from gestation until ~37 weeks of age [postnatal day (PND) 259]. In a subset of mice, TCE exposure was discontinued at ~22 weeks of age (PND 154). At PND 259, RRBS assessment revealed more global methylation changes in the continuous exposure group vs. the discontinuous exposure group. A majority of the differentially methylated CpG regions (DMRs) across promoters, islands, and regulatory elements were hypermethylated (~90%). However, continuous developmental TCE exposure altered the methylation of 274 CpG sites in promoters and CpG islands. In contrast, only 4 CpG island regions were differentially methylated (hypermethylated) in the discontinuous group. Interestingly, 2 of these 4 sites were also hypermethylated in the continuous exposure group, and both of these island regions are associated with lysine 27 on histone H3 (H3K27) involved in polycomb complex-dependent transcriptional repression via H3K27 tri-methylation. CpG sites were overlapped with the Open Regulatory Annotation database. Unlike the discontinuous group, continuous TCE treatment resulted in 129 DMRs including 12 unique transcription factors and regulatory elements; 80% of which were enriched for one or more polycomb group (PcG) protein binding regions (i.e., SUZ12, EZH2, JARID2, and MTF2). Pathway analysis of the DMRs indicated that TCE primarily altered the methylation of genes associated with regulation of cellular metabolism and cell signaling. The results demonstrated that continuous developmental exposure to TCE differentially methylated binding sites of PcG proteins in effector/memory CD4⁺ cells. There were minimal yet potentially biologically significant effects that occurred when exposure was discontinued. These results point toward a novel mechanism by which chronic developmental TCE exposure may alter terminally differentiated CD4⁺ T cell function in adulthood.

Age prediction of children and adolescents aged 6-17 years: an epigenome-wide analysis of DNA methylation

The DNA methylation age, a good reflection of human aging process, has been used to predict chronological age of adults and newborns. However, the prediction model for children and adolescents was absent. In this study, we aimed to generate a prediction model of chronological age for children and adolescents aged 6-17 years by using age-specific DNA methylation patterns from 180 Chinese twin individuals. We identified 6,350 age-related CpGs from the epigenome-wide association analysis (N=179). 116 known age-related sites in children were confirmed. 83 novel CpGs were selected as predictors from all age-related loci by elastic net regression and they could accurately predict the chronological age of the pediatric population, with a correlation of 0.99 and the error of 0.23 years in the training dataset (N=90). The predictive accuracy in the testing dataset (N=89) was high (correlation=0.93, error=0.62 years). Among the 83 predictors, 49 sites were novel probes not existing on the Illumina 450K BeadChip. The top two predictors of age were on the PRKCB and REG4 genes, which are associated with diabetes and cancer, respectively. Our results suggest that the chronological age can be accurately predicted among children and adolescents aged 6-17 years by 83 newly identified CpG sites.

Maternal and Post-weaning High-Fat Diets Produce Distinct DNA Methylation Patterns in Hepatic Metabolic Pathways within Specific Genomic Contexts

Calorie-dense high-fat diets (HF) are associated with detrimental health outcomes, including obesity, cardiovascular disease, and diabetes. Both pre- and post-natal HF diets have been hypothesized to negatively impact long-term metabolic health via epigenetic mechanisms. To understand how the timing of HF diet intake impacts DNA methylation and metabolism, male Sprague–Dawley rats were exposed to either maternal HF (MHF) or post-weaning HF diet (PHF). At post-natal week 12, PHF rats had similar body weights but greater hepatic lipid accumulation compared to the MHF rats. Genome-wide DNA methylation was evaluated, and analysis revealed 1744 differentially methylation regions (DMRs) between the groups with the majority of the DMR located outside of gene-coding regions. Within differentially methylated genes (DMGs), intragenic DNA methylation closer to the transcription start site was associated with lower gene expression, whereas DNA methylation further downstream was positively correlated with gene expression. The insulin and phosphatidylinositol (PI) signaling pathways were enriched with 25 DMRs that were associated with 20 DMGs, including PI3 kinase (Pi3k), pyruvate kinase (Pklr), and phosphodiesterase 3 (Pde3). Together, these results suggest that the timing of HF diet intake determines DNA methylation and gene expression patterns in hepatic metabolic pathways that target specific genomic contexts.

Human aging DNA methylation signatures are conserved but accelerated in cultured fibroblasts

Aging is associated with progressive and site-specific changes in DNA methylation (DNAm). These global changes are captured by DNAm clocks that accurately predict chronological age in humans but relatively little is known about how clocks perform in vitro. Here we culture primary human fibroblasts across the cellular lifespan (~6 months) and use four different DNAm clocks to show that age-related DNAm signatures are conserved and accelerated in vitro. The Skin & Blood clock shows the best linear correlation with chronological time (r = 0.90), including during replicative senescence. Although similar in nature, the rate of epigenetic aging is approximately 62x times faster in cultured cells than in the human body. Consistent with in vivo data, cells aged under hyperglycemic conditions exhibit an approximately three years elevation in baseline DNAm age. Moreover, candidate gene-based analyses further corroborate the conserved but accelerated biological aging process in cultured fibroblasts. Fibroblasts mirror the established DNAm topology of the age-related ELOVL2 gene in human blood and the rapid hypermethylation of its promoter cg16867657, which correlates with a linear decrease in ELOVL2 mRNA levels across the lifespan. Using generalized additive modeling on twelve timepoints across the lifespan, we also show how single CpGs exhibit loci-specific, linear and nonlinear trajectories that reach rates up to -47% (hypomethylation) to +23% (hypermethylation) per month. Together, these high-temporal resolution global, gene-specific, and single CpG data highlight the conserved and accelerated nature of epigenetic aging in cultured fibroblasts, which may constitute a system to evaluate age-modifying interventions across the lifespan.

Studies of hTERT DNA methylation assays on the human age prediction

As an important aspect of epigenetics, DNA methylation has been proven to be suitable for forensic DNA analysis. By detecting changes in DNA methylation, it is desirable to construct a model of age patterns associated with it to infer the age of the individual. The hTERT gene methylation is closely related to tumors, but there are few reports on the relationship between hTERT gene promoter methylation and age. In this study, we utilized the methylation-specific polymerase chain reaction and real-time PCR (relative quantification and absolute quantification) approach to explore the connection between hTERT DNA methylation and age prediction. We fit three models for age prediction based on methylation assay for 90 blood samples from donors aged 1-79 years old. Among them, the model of absolute quantification of real-time enabled the age prediction with R² = 0.9634. We verified the linear regression model with a validation set of 30 blood samples where prediction average error was 4.29 years. Generally, this reliable method improves the DNA methylation analysis of forensic samples.

Age-related changes in DNA methylation levels at CpG sites in bull spermatozoa and in vitro fertilization-derived blastocyst-stage embryos revealed by combined bisulfite restriction analysis

Age-associated methylation changes in genomic DNA have been recently reported in spermatozoa, and these changes can contribute to decline in fertility. In a previous study, we analyzed the genome-wide DNA methylation profiles of bull spermatozoa using a human DNA methylation microarray and identified one CpG site (CpG-1) that potentially reflects age-related methylation changes. In the present study, cryopreserved semen samples from a Japanese Black bull were collected at five different ages, which were referred to as JD1-5: 14, 19, 28, 54, and 162 months, respectively, and were used for genome-wide DNA methylation analysis and in vitro fertilization (IVF). Distinct age-related changes in methylation profiles were observed, and 77 CpG sites were found to be differently methylated between young and adult samples (JD1-2 vs. JD4-5). Using combined bisulfite restriction analysis (COBRA), nine CpG sites (including CpG-1) were confirmed to exhibit significant differences in their age-dependent methylation levels. Eight CpG sites showed an age-dependent increase in their methylation levels, whereas only one site showed age-dependent hypomethylation; in particular, these changes in methylation levels occurred rapidly at a young age. COBRA revealed low methylation levels in some CpG regions in the majority of the IVF blastocyst-stage embryos derived from spermatozoa at JD2-5. Interestingly, bulls with different ages did not show differences in their methylation levels. In conclusion, our findings indicated that methylation levels at nine CpG sites in spermatozoa changed with increasing age and that some CpG regions were demethylated after fertilization. Further studies are required to determine whether age-dependent different methylation levels in bull spermatozoa can affect fertility.

The role of DNA methylation and hydroxymethylation in immunosenescence

A healthy functioning immune system is critical to stave off infectious diseases, but as humans and other organisms age, their immune systems decline. As a result, diseases that were readily thwarted in early life pose nontrivial harm and can even be deadly in late life. Immunosenescence is defined as the general deterioration of the immune system with age, and it is characterized by functional changes in hematopoietic stem cells (HSCs) and specific blood cell types as well as changes in levels of numerous factors, particularly those involved in inflammation. Potential mechanisms underlying immunosenescence include epigenetic changes such as changes in DNA methylation (DNAm) and DNA hydroxymethylation (DNAhm) that occur with age. The purpose of this review is to describe what is currently known about the relationship between immunosenescence and the age-related changes to DNAm and DNAhm, and to discuss experimental approaches best suited to fill gaps in our understanding.

Neonatal bloodspot DNA methylation patterns are associated with childhood weight status in the Healthy Families Project

BACKGROUND

This study measured longitudinal DNA methylation dynamics at growth-related genes during childhood, and then tested whether DNA methylation at various stages of childhood was associated with obesity status.

METHODS

Using neonatal bloodspot (n = 132) and matched childhood blood samples (n = 65), DNA methylation was quantified at a repetitive element (long interspersed nuclear element-1 (LINE-1)), two imprinted genes (IGF2, H19), and four non-imprinted genes (LEP, PPARA, ESR1, SREBF1) related to growth and adiposity. Logistic regression was used to test whether neonatal bloodspot DNA methylation at target genes was associated with log odds of obesity (Y/N) in children recruited from three age groups-12-24 months old (n = 40), 3-5 years of age (n = 40), and 10-12 years of age (n = 52).

RESULTS

In 3-5 year olds, neonatal bloodspot LINE-1 methylation was negatively associated with obesity (log odds = -0.40, p = 0.04). Across childhood age group in matched blood samples, DNA methylation levels in blood decreased (p < 0.05) at LINE-1, PPARA, ESR1, SREBF1, IGF2, and H19, and increased (p < 0.05) at LEP.

CONCLUSIONS

Our results suggest that age-related epigenetic changes occur at growth-related genes in the first decade of life, and that gene-specific neonatal bloodspot DNA methylation may be a useful biomarker of obesity likelihood during childhood.

Evaluating DNA methylation age on the Illumina MethylationEPIC Bead Chip

DNA methylation age (DNAm age) has become a widely utilized epigenetic biomarker for the aging process. The Horvath method for determining DNAm age is perhaps the most widely utilized and validated DNA methylation age assessment measure. Horvath DNAm age is calculated based on methylation measurements at 353 loci, present on Illumina's 450k and 27k DNA methylation microarrays. With increasing use of the more recently developed Illumina MethylationEPIC (850k) microarray, it is worth revisiting this aging measure to evaluate estimation differences due to array design. Of the requisite 353 loci, 17 are missing from the 850k microarray. Similarly, an alternate, 71 loci DNA methylation age assessment measure created by Hannum et al. is missing 6 requisite loci. Using 17 datasets with 27k, 450k, and/or 850k methylation data, we compared each sample's epigenetic age estimated from all 353 loci required by the Horvath DNAm age calculator, and using only the 336 loci available on the 850k array. In 450k/27k data, removing loci not on the 850k array resulted in underestimation of Horvath's DNAm age. Underestimation of Horvath DNAm age increased from ages 0 to ~20, remaining stable thereafter (mean deviation = -3.46 y, SD = 1.13 for individuals ≥20 years). Underestimation of Horvath's DNAm age by the reduced 450k/27k data was similar to the underestimation observed in the 850k data indicating it is driven by missing probes. In analogous examination of Hannum's DNAm age, the magnitude and direction of epigenetic age misestimation varied with chronological age. In conclusion, inter-array deviations in DNAm age estimations may be largely driven by missing probes between arrays, despite default probe imputation procedures. Though correlations and associations based on Horvath's DNAm age may be unaffected, researchers should exercise caution when interpreting results based on absolute differences in DNAm age or when mixing samples assayed on different arrays.

Socioeconomic position during pregnancy and DNA methylation signatures at three stages across early life: epigenome-wide association studies in the ALSPAC birth cohort

BACKGROUND

Socioeconomic experiences are recognized determinants of health, and recent work has shown that social disadvantages in early life may induce sustained biological changes at molecular level that are detectable later in life. However, the dynamics and persistence of biological embedding of socioeconomic position (SEP) remains vastly unexplored.

METHODS

Using the data from the ALSPAC birth cohort, we performed epigenome-wide association studies of DNA methylation changes at three life stages (birth, n = 914; childhood at mean age 7.5 years, n = 973; and adolescence at mean age 15.5 years, n = 974), measured using the Illumina HumanMethylation450 Beadchip, in relation to pregnancy SEP indicators (maternal and paternal education and occupation).

RESULTS

Across the four early life SEP metrics investigated, only maternal education was associated with methylation levels at birth, and four CpGs mapped to SULF1, GLB1L2 and RPUSD1 genes were identified [false discovery rate (FDR)-corrected P-value <0.05]. No epigenetic signature was found associated with maternal education in child samples, but methylation levels at 20 CpG loci were found significantly associated with maternal education in adolescence. Although no overlap was found between the differentially methylated CpG sites at different ages, we identified two CpG sites at birth and during adolescence which are 219 bp apart in the SULF1 gene that encodes an heparan sulphatase involved in modulation of signalling pathways. Using data from an independent birth cohort, the ENVIRONAGE cohort, we were not able to replicate these findings.

CONCLUSIONS

Taken together, our results suggest that parental SEP, and particularly maternal education, may influence the offspring's methylome at birth and adolescence.

DNA methylation signatures as biomarkers of prior environmental exposures

Purpose of review

This review demonstrates the growing body of evidence connecting DNA methylation to prior exposure. It highlights the potential to use DNA methylation patterns as a feasible, stable, and accurate biomarker of past exposure, opening new opportunities for environmental and gene-environment interaction studies among existing banked samples.

Recent findings

We present the evidence for association between past exposure, including prenatal exposures, and DNA methylation measured at a later time in the life course. We demonstrate the potential utility of DNA methylation-based biomarkers of past exposure using results from multiple studies of smoking as an example. Multiple studies show the ability to accurately predict prenatal smoking exposure based on DNA methylation measured at birth, in childhood, and even adulthood. Separate sets of DNA methylation loci have been used to predict past personal smoking exposure (postnatal) as well. Further, it appears that these two types of exposures, prenatal and previous personal exposure, can be isolated from each other. There is also a suggestion that quantitative methylation scores may be useful for estimating dose. We highlight the remaining needs for rigor in methylation biomarker development including analytic challenges as well as the need for development across multiple developmental windows, multiple tissue types, and multiple ancestries.

Summary

If fully developed, DNA methylation-based biomarkers can dramatically shift our ability to carry out environmental and genetic-environmental epidemiology using existing biobanks, opening up unprecedented opportunities for environmental health.

Longitudinal genome-wide DNA methylation analysis uncovers persistent early-life DNA methylation changes

Background

Early life is a period of drastic epigenetic remodeling in which the epigenome is especially sensitive to extrinsic and intrinsic influence. However, the epigenome-wide dynamics of the DNA methylation changes that occur during this period have not been sufficiently characterized in longitudinal studies.

Methods

To this end, we studied the DNA methylation status of more than 750,000 CpG sites using Illumina MethylationEPIC arrays on 33 paired blood samples from 11 subjects at birth and at 5 and 10 years of age, then characterized the chromatin context associated with these loci by integrating our data with histone, chromatin-state and enhancer-element external datasets, and, finally, validated our results through bisulfite pyrosequencing in two independent longitudinal cohorts of 18 additional subjects.

Results

We found abundant DNA methylation changes (110,726 CpG sites) during the first lustrum of life, while far fewer alterations were observed in the subsequent 5 years (460 CpG sites). However, our analysis revealed persistent DNA methylation changes at 240 CpG sites, indicating that there are genomic locations of considerable epigenetic change beyond immediate birth. The chromatin context of hypermethylation changes was associated with repressive genomic locations and genes with developmental and cell signaling functions, while hypomethylation changes were linked to enhancer regions and genes with immunological and mRNA and protein metabolism functions. Significantly, our results show that genes that suffer simultaneous hyper- and hypomethylation are functionally distinct from exclusively hyper- or hypomethylated genes, and that enhancer-associated methylation is different in hyper- and hypomethylation scenarios, with hypomethylation being more associated to epigenetic changes at blood tissue-specific enhancer elements.

Conclusions

These data show that epigenetic remodeling is dramatically reduced after the first 5 years of life. However, there are certain loci which continue to manifest DNA methylation changes, pointing towards a possible functionality beyond early development. Furthermore, our results deepen the understanding of the genomic context associated to hyper- or hypomethylation alterations during time, suggesting that hypomethylation of blood tissue-specific enhancer elements could be of importance in the establishment of functional states in blood tissue during early-life.

Electronic supplementary material

The online version of this article (10.1186/s12967-018-1751-9) contains supplementary material, which is available to authorized users.

Integration of DNA methylation patterns and genetic variation in human pediatric tissues help inform EWAS design and interpretation

Background

The widespread use of accessible peripheral tissues for epigenetic analyses has prompted increasing interest in the study of tissue-specific DNA methylation (DNAm) variation in human populations. To date, characterizations of inter-individual DNAm variability and DNAm concordance across tissues have been largely performed in adult tissues and therefore are limited in their relevance to DNAm profiles from pediatric samples. Given that DNAm patterns in early life undergo rapid changes and have been linked to a wide range of health outcomes and environmental exposures, direct investigations of tissue-specific DNAm variation in pediatric samples may help inform the design and interpretation of DNAm analyses from early life cohorts. In this study, we present a systematic comparison of genome-wide DNAm patterns between matched pediatric buccal epithelial cells (BECs) and peripheral blood mononuclear cells (PBMCs), two of the most widely used peripheral tissues in human epigenetic studies. Specifically, we assessed DNAm variability, cross-tissue DNAm concordance and genetic determinants of DNAm across two independent early life cohorts encompassing different ages.

Results

BECs had greater inter-individual DNAm variability compared to PBMCs and highly the variable CpGs are more likely to be positively correlated between the matched tissues compared to less variable CpGs. These sites were enriched for CpGs under genetic influence, suggesting that a substantial proportion of DNAm covariation between tissues can be attributed to genetic variation. Finally, we demonstrated the relevance of our findings to human epigenetic studies by categorizing CpGs from published DNAm association studies of pediatric BECs and peripheral blood.

Conclusions

Taken together, our results highlight a number of important considerations and practical implications in the design and interpretation of EWAS analyses performed in pediatric peripheral tissues.

Electronic supplementary material

The online version of this article (10.1186/s13072-018-0245-6) contains supplementary material, which is available to authorized users.

DNA Methylation and Hydroxymethylation and Behavior

Environmentally sensitive molecular mechanisms in the brain, such as DNA methylation, have become a significant focus of neuroscience research because of mounting evidence indicating that they are critical in response to social situations, stress, threats, and behavior. The recent identification of 5-hydroxymethylcytosine (5hmC), which is enriched in the brain (tenfold over peripheral tissues), raises new questions as to the role of this base in mediating epigenetic effects in the brain. The development of genome-wide methods capable of distinguishing 5-methylcytosine (5mC) from 5hmC has revealed that a growing number of behaviors are linked to independent disruptions of 5mC and 5hmC levels, further emphasizing the unique importance of both of these modifications in the brain. Here, we review the recent links that indicate DNA methylation (both 5mC and 5hmC) is highly dynamic and that perturbations in this modification may contribute to behaviors related to psychiatric disorders and hold clinical relevance.

Association of BAX hypermethylation with coronary heart disease is specific to individuals aged over 70

INTRODUCTION

As a member of B-cell lymphoma-2 (BCL-2) gene family, BCL-2 associated X (BAX) is important for cell apoptosis. In this work, we investigated the association of BAX promoter DNA methylation with coronary heart disease (CHD) in Han Chinese.

METHODS

A SYBR green-based quantitative methylation specific PCR (qMSP) was used to test BAX methylation levels in 959 CHD cases and 514 controls.

RESULTS

Although BAX methylation was not associated with CHD in the total samples, further breakdown analysis by age showed that BAX hypermethylation was significantly associated with CHD for individuals aged over 70 (median percentage of methylation ratio [PMR], 10.70% in cases versus (vs) 2.25% in controls, P =.046). Moreover, BAX methylation was associated with smoking and lipoprotein A (Lp(a)) for individuals aged over 70 (CHD: smoking P = .012, Lp(a) P = .001; non-CHD: smoking P = .051, Lp(a) P = .004). Further analysis of Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) data showed BAX expression was upregulated by 5-aza-2'-deoxycytidine demethylation agent (fold = 1.66, P = .038) and inversely correlated with BAX methylation (r = -0.428, P = 8E-05).

CONCLUSIONS

Our study supported that BAX hypermethylation might contribute to CHD risk via downregulation of BAX expression for individuals aged over 70.

An integrated transcriptome analysis in T-cell acute lymphoblastic leukemia links DNA methylation subgroups to dysregulated TAL1 and ANTP homeobox gene expression

Classification of pediatric T‐cell acute lymphoblastic leukemia (T‐ALL) patients into CIMP (CpG Island Methylator Phenotype) subgroups has the potential to improve current risk stratification. To investigate the biology behind these CIMP subgroups, diagnostic samples from Nordic pediatric T‐ALL patients were characterized by genome‐wide methylation arrays, followed by targeted exome sequencing, telomere length measurement, and RNA sequencing. The CIMP subgroups did not correlate significantly with variations in epigenetic regulators. However, the CIMP+ subgroup, associated with better prognosis, showed indicators of longer replicative history, including shorter telomere length (P = 0.015) and older epigenetic (P < 0.001) and mitotic age (P < 0.001). Moreover, the CIMP+ subgroup had significantly higher expression of ANTP homeobox oncogenes, namely TLX3, HOXA9, HOXA10, and NKX2‐1, and novel genes in T‐ALL biology including PLCB4, PLXND1, and MYO18B. The CIMP− subgroup, with worse prognosis, was associated with higher expression of TAL1 along with frequent STIL‐TAL1 fusions (2/40 in CIMP+ vs 11/24 in CIMP−), as well as stronger expression of BEX1. Altogether, our findings suggest different routes for leukemogenic transformation in the T‐ALL CIMP subgroups, indicated by different replicative histories and distinct methylomic and transcriptomic profiles. These novel findings can lead to new therapeutic strategies.

Epigenetic influences on aging: a longitudinal genome-wide methylation study in old Swedish twins

Age-related changes in DNA methylation were observed in cross-sectional studies, but longitudinal evidence is still limited. Here, we aimed to characterize longitudinal age-related methylation patterns using 1011 blood samples collected from 385 Swedish twins (age at entry: mean 69 and standard deviation 9.7, 73 monozygotic and 96 dizygotic pairs) up to five times (mean 2.6) over 20 years (mean 8.7). We identified 1316 age-associated methylation sites (P<1.3×10⁻⁷) using a longitudinal epigenome-wide association study design. We measured how estimated cellular compositions changed with age and how much they confounded the age effect. We validated the results in two independent longitudinal cohorts, where 118 CpGs were replicated in Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS, 390 samples) (P<3.9×10⁻⁵), 594 in Lothian Birth Cohort (LBC, 3018 samples) (P<5.1×10⁻⁵) and 63 in both. Functional annotation of age-associated CpGs showed enrichment in CCCTC-binding factor (CTCF) and other transcription factor binding sites. We further investigated genetic influences on methylation and found no interaction between age and genetic effects in the 1316 age-associated CpGs. Moreover, in the same CpGs, methylation differences within twin pairs increased with 6.4% over 10 years, where monozygotic twins had smaller intra-pair differences than dizygotic twins. In conclusion, we show that age-related methylation changes persist in a longitudinal perspective, and are fairly stable across cohorts. The changes are under genetic influence, although this effect is independent of age. Moreover, methylation variability increase over time, especially in age-associated CpGs, indicating the increase of environmental contributions on DNA methylation with age.

Polyamine Metabolism and Gene Methylation in Conjunction with One-Carbon Metabolism

Recent investigations have revealed that changes in DNA methylation status play an important role in aging-associated pathologies and lifespan. The methylation of DNA is regulated by DNA methyltransferases (DNMT1, DNMT3a, and DNMT3b) in the presence of S-adenosylmethionine (SAM), which serves as a methyl group donor. Increased availability of SAM enhances DNMT activity, while its metabolites, S-adenosyl-l-homocysteine (SAH) and decarboxylated S-adenosylmethionine (dcSAM), act to inhibit DNMT activity. SAH, which is converted from SAM by adding a methyl group to cytosine residues in DNA, is an intermediate precursor of homocysteine. dcSAM, converted from SAM by the enzymatic activity of adenosylmethionine decarboxylase, provides an aminopropyl group to synthesize the polyamines spermine and spermidine. Increased homocysteine levels are a significant risk factor for the development of a wide range of conditions, including cardiovascular diseases. However, successful homocysteine-lowering treatment by vitamins (B6, B12, and folate) failed to improve these conditions. Long-term increased polyamine intake elevated blood spermine levels and inhibited aging-associated pathologies in mice and humans. Spermine reversed changes (increased dcSAM, decreased DNMT activity, aberrant DNA methylation, and proinflammatory status) induced by the inhibition of ornithine decarboxylase. The relation between polyamine metabolism, one-carbon metabolism, DNA methylation, and the biological mechanism of spermine-induced lifespan extension is discussed.

Implementing a method for studying longitudinal DNA methylation variability in association with age

Interindividual variability of DNA methylation is a mechanism of the epigenetic drift in aging. Studies on cross-sectional data have discovered a change in methylation variability in association with age. However, thus far, no method explored DNA methylation variability in longitudinal data, which was the aim of this study. First, we performed a simulation study to explore methods for estimating methylation variability in longitudinal data. Second, an epigenome-wide association study (EWAS) on 1011 longitudinal samples (385 individuals followed up to 18 years) was performed to identify age-varying methylation sites using these methods. Following Breusch-Pagan test of heteroscedasticity, we showed that a linear regression model, where the residuals were used in a mixed effect model with a random intercept, properly estimated the change of interindividual variability over time. Our EWAS identified 570 CpG sites where methylation variability was significantly associated with age (P < 1.3 × 10-7). Gene regions of identified loci were enriched in nervous system development functions. In conclusion, we provide a method for analyzing methylation variability in longitudinal data and further identified age-varying methylation loci in a longitudinal analysis using these methods.

Multi-generational impacts of arsenic exposure on genome-wide DNA methylation and the implications for arsenic-induced skin lesions

As a nonmutagenic human carcinogen, arsenic (As)'s carcinogenic activity is likely the result of epigenetic changes, particularly alterations in DNA methylation. While increasing studies indicate a potentially important role for timing of As exposure on DNA methylation patterns and the subsequent differential risks for As toxicity and carcinogenesis, there is a lack of research that tackles these critical questions, particularly in human based populations. Here we reported a family-based study including three generations, in which each generation living in the same household had a distinctive timing of As exposure: in adulthood, in utero and during early childhood, and in germlines exposure for grandparents, parents, and grandchildren, respectively. We generated genome-wide DNA methylation data for 18 As-exposed families, nine control families, as well as 18 arsenical skin lesion patients. Our analysis showed that As exposure may leave detectable DNA methylation changes even though exposure occurred decades ago, and the most significant changes of global DNA methylation were observed among patients afflicted with arsenical skin lesions. As exposure across generations shared common differentially methylated DNA loci and regions (744 DML and 15 DMRs) despite the distinctive exposure timing in each generation. Importantly, based on these DML, clustering analysis grouped skin lesion patients together with grandparents in exposed families in the same cluster, separated from grandparents in control families. Further analysis identified a number of DML and several molecular pathways that were significantly distinguished between controls, exposed populations, as well as skin lesion patients. Finally, our exploratory analysis suggested that some of these DML altered by As exposure, may have the potential to be inherited affecting not only those directly exposed but also later generations. Together, our results suggest that common DML and/or DMRs associated with an increased risk for disease development could be identified regardless of when exposure to As occurred during their life span, and thus may be able to serve as biomarkers for identifying individuals at risk for As-induced skin lesions and possible cancers.

Children's biobehavioral reactivity to challenge predicts DNA methylation in adolescence and emerging adulthood

A growing body of research has documented associations between adverse childhood environments and DNA methylation, highlighting epigenetic processes as potential mechanisms through which early external contexts influence health across the life course. The present study tested a complementary hypothesis: indicators of children's early internal, biological, and behavioral responses to stressful challenges may also be linked to stable patterns of DNA methylation later in life. Children's autonomic nervous system reactivity, temperament, and mental health symptoms were prospectively assessed from infancy through early childhood, and principal components analysis (PCA) was applied to derive composites of biological and behavioral reactivity. Buccal epithelial cells were collected from participants at 15 and 18 years of age. Findings revealed an association between early life biobehavioral inhibition/disinhibition and DNA methylation across many genes. Notably, reactive, inhibited children were found to have decreased DNA methylation of the DLX5 and IGF2 genes at both time points, as compared to non‐reactive, disinhibited children. Results of the present study are provisional but suggest that the gene's profile of DNA methylation may constitute a biomarker of normative or potentially pathological differences in reactivity. Overall, findings provide a foundation for future research to explore relations among epigenetic processes and differences in both individual‐level biobehavioral risk and qualities of the early, external childhood environment.

Identification of Hyper-Methylated Tumor Suppressor Genes-Based Diagnostic Panel for Esophageal Squamous Cell Carcinoma (ESCC) in a Chinese Han Population

DNA methylation-based biomarkers were suggested to be promising for early cancer diagnosis. However, DNA methylation-based biomarkers for esophageal squamous cell carcinoma (ESCC), especially in Chinese Han populations have not been identified and evaluated quantitatively. Candidate tumor suppressor genes (N = 65) were selected through literature searching and four public high-throughput DNA methylation microarray datasets including 136 samples totally were collected for initial confirmation. Targeted bisulfite sequencing was applied in an independent cohort of 94 pairs of ESCC and normal tissues from a Chinese Han population for eventual validation. We applied nine different classification algorithms for the prediction to evaluate to the prediction performance. ADHFE1, EOMES, SALL1 and TFPI2 were identified and validated in the ESCC samples from a Chinese Han population. All four candidate regions were validated to be significantly hyper-methylated in ESCC samples through Wilcoxon rank-sum test (ADHFE1, P = 1.7 × 10^-3; EOMES, P = 2.9 × 10^-9; SALL1, P = 3.9 × 10^-7; TFPI2, p = 3.4 × 10^-6). Logistic regression based prediction model shown a moderately ESCC classification performance (Sensitivity = 66%, Specificity = 87%, AUC = 0.81). Moreover, advanced classification method had better performances (random forest and naive Bayes). Interestingly, the diagnostic performance could be improved in non-alcohol use subgroup (AUC = 0.84). In conclusion, our data demonstrate the methylation panel of ADHFE1, EOMES, SALL1 and TFPI2 could be an effective methylation-based diagnostic assay for ESCC.

Epigenetic age-predictor for mice based on three CpG sites

Epigenetic clocks for mice were generated based on deep-sequencing analysis of the methylome. Here, we demonstrate that site-specific analysis of DNA methylation levels by pyrosequencing at only three CG dinucleotides (CpGs) in the genes Prima1, Hsf4, and Kcns1 facilitates precise estimation of chronological age in murine blood samples, too. DBA/2 mice revealed accelerated epigenetic aging as compared to C57BL6 mice, which is in line with their shorter life-expectancy. The three-CpG-predictor provides a simple and cost-effective biomarker to determine biological age in large intervention studies with mice.

Epigenetic marks are chemical modifications found throughout the genome – the DNA within cells. By influencing the activity of nearby genes, the marks govern developmental processes and help cells to adapt to changes in their surroundings. Some epigenetic marks can be gained or lost with age. A lot of aging research focuses on one type of mark, called “DNA methylation”. By measuring the presence or absence of specific methyl groups, scientists can estimate biological age – which may differ from calendar age.

Recent studies have developed computer models called epigenetic aging clocks to predict the biological age of mouse cells. These clocks use epigenetic data collected from the entire genomes of mice, and are useful for understanding how the aging process is affected by genetic parameters, diet, or other environmental factors. Yet, the genome sequencing methods used to construct most existing epigenetic clocks are expensive, labor-intensive, and cannot be easily applied to large groups of mice.

Han et al. have developed a new way to predict biological aging in mice that needs methylation information from just three particular sections of the genome. Even though this approach is much faster and less expensive than other epigenetic approaches to measuring aging, it has a similar level of accuracy to existing models. Han et al. use the new method to show that cells from different strains of laboratory mice age at different rates. Furthermore, in a strain that has a shorter life expectancy, aging seems to be accelerated.

The new approach developed by Han et al. will make it easier to study how aging in mice is affected by different interventions. Further studies will also be needed to better understand how epigenetic marks relate to biological aging.

Human Age Prediction Based on DNA Methylation Using a Gradient Boosting Regressor

All tissues of organisms will become old as time goes on. In recent years, epigenetic investigations have found that there is a close correlation between DNA methylation and aging. With the development of DNA methylation research, a quantitative statistical relationship between DNA methylation and different ages was established based on the change rule of methylation with age, it is then possible to predict the age of individuals. All the data in this work were retrieved from the Illumina HumanMethylation BeadChip platform (27K or 450K). We analyzed 16 sets of healthy samples and 9 sets of diseased samples. The healthy samples included a total of 1899 publicly available blood samples (0–103 years old) and the diseased samples included 2395 blood samples. Six age-related CpG sites were selected through calculating Pearson correlation coefficients between age and DNA methylation values. We built a gradient boosting regressor model for these age-related CpG sites. 70% of the data was randomly selected as training data and the other 30% as independent data in each dataset for 25 runs in total. In the training dataset, the healthy samples showed that the correlation between predicted age and DNA methylation was 0.97, and the mean absolute deviation (MAD) was 2.72 years. In the independent dataset, the MAD was 4.06 years. The proposed model was further tested using the diseased samples. The MAD was 5.44 years for the training dataset and 7.08 years for the independent dataset. Furthermore, our model worked well when it was applied to saliva samples. These results illustrated that the age prediction based on six DNA methylation markers is very effective using the gradient boosting regressor.

armDNA: A functional beta model for detecting age-related genomewide DNA methylation marks

DNA methylation has been shown to play an important role in many complex diseases. The rapid development of high-throughput DNA methylation scan technologies provides great opportunities for genomewide DNA methylation-disease association studies. As methylation is a dynamic process involving time, it is quite plausible that age contributes to its variation to a large extent. Therefore, in analyzing genomewide DNA methylation data, it is important to identify age-related DNA methylation marks and delineate their functional relationship. This helps us to better understand the underlying biological mechanism and facilitate early diagnosis and prognosis analysis of complex diseases. We develop a functional beta model for analyzing DNA methylation data and detecting age-related DNA methylation marks on the whole genome by naturally taking sampling scheme into account and accommodating flexible age-methylation dynamics. We focus on DNA methylation data obtained through the widely used bisulfite conversion technique and propose to use a beta model to relate the DNA methylation level to the age. Adjusting for certain confounders, the functional age effect is left completely unspecified, offering great flexibility and allowing extra data dynamics. An efficient algorithm is developed for estimating unknown parameters, and the Wald test is used to detect age-related DNA methylation marks. Simulation studies and several real data applications were provided to demonstrate the performance of the proposed method.

Somatic genome alterations in relation to age in lung squamous cell carcinoma

Lung squamous cell carcinoma (LUSC) is the most common cause of global cancer-related mortality and the major risk factors is smoking consumption. By analyzing ∼500 LUSC samples from The Cancer Genome Atlas, we detected a higher mutational burden as well as a higher level of methylation changes in younger patients. The SNPs mutational profiling showed enrichments of smoking-related signature 4 and defective DNA mismatch repair (MMR)-related signature 6 in younger patients, while the defective DNA MMR signature 26 was enriched among older patients. Furthermore, gene set enrichment analysis was performed in order to explore functional effect of somatic alterations in relation to patient age. Extracellular Matrix-Receptor Interaction, Nucleotide Excision Repair and Axon Guidance seem crucial disrupted pathways in younger patients. We hypothesize that a higher sensitivity to smoking-related damages and the enrichment of defective DNA MMR related mutations may contribute to the higher mutational burden of younger patients. The two distinct age-related defective DNA MMR signatures 6 and 26 might be crucial mutational patterns in LUSC tumorigenesis which may develop distinct phenotypes. Our study provides indications of age-dependent differences in mutational backgrounds (SNPs and CNVs) as well as epigenetic patterns that might be relevant for age adjusted treatment approaches.

Tracing human stem cell lineage during development using DNA methylation

Stem cell maturation is a fundamental, yet poorly understood aspect of human development. We devised a DNA methylation signature deeply reminiscent of embryonic stem cells (a fetal cell origin signature, FCO) to interrogate the evolving character of multiple human tissues. The cell fraction displaying this FCO signature was highly dependent upon developmental stage (fetal versus adult), and in leukocytes, it described a dynamic transition during the first 5 yr of life. Significant individual variation in the FCO signature of leukocytes was evident at birth, in childhood, and throughout adult life. The genes characterizing the signature included transcription factors and proteins intimately involved in embryonic development. We defined and applied a DNA methylation signature common among human fetal hematopoietic progenitor cells and have shown that this signature traces the lineage of cells and informs the study of stem cell heterogeneity in humans under homeostatic conditions.

Aging and Apolipoprotein E in HIV Infection

With the implementation of increasingly effective antiretroviral therapy (ART) over the past three decades, individuals infected with HIV live a much longer life. HIV infection is no longer a terminal but rather a chronic disease. However, the lifespan of infected individuals remains shorter than that of their uninfected peers. Even with ART, HIV infection may potentiate “premature” aging. Organ-associated disease and systemic syndromes that occur in treated HIV-infection are like that of older, uninfected individuals. Brain aging may manifest as structural changes or neurocognitive impairment that are beyond the chronological age. The spectrum of neurological, cognitive, and motor deficiencies, currently described as HIV-associated neurocognitive disorders (HAND), may reflect earlier onset of mechanisms common to HIV infection and aging (accelerated aging). HAND could also reflect the neurological impact of HIV infection superimposed on comorbidities linked to age and chronic inflammation, leading to a higher prevalence of neurocognitive impairment across the age span (accentuated aging). In addition, apolipoprotein E (ApoE), one of the most influential host risk factors for developing Alzheimer’s disease, has been implicated in the development of HAND. But studies differ as to whether ApoE is relevant, and whether age and ApoE interact to impair brain function in the HIV-infected patient. What is clear is that HIV-infected individuals are living longer with HIV, and therefore factors related to aging and health need to be examined in the context of current, effective ART. This review addresses the recent evidence for the influence of aging and ApoE on HIV-associated neurocognitive impairment.

DNA methylation-based age prediction from various tissues and body fluids

Aging is a natural and gradual process in human life. It is influenced by heredity, environment, lifestyle, and disease. DNA methylation varies with age, and the ability to predict the age of donor using DNA from evidence materials at a crime scene is of considerable value in forensic investigations. Recently, many studies have reported age prediction models based on DNA methylation from various tissues and body fluids. Those models seem to be very promising because of their high prediction accuracies. In this review, the changes of age-associated DNA methylation and the age prediction models for various tissues and body fluids were examined, and then the applicability of the DNA methylation-based age prediction method to the forensic investigations was discussed. This will improve the understandings about DNA methylation markers and their potential to be used as biomarkers in the forensic field, as well as the clinical field.

Case-control meta-analysis of blood DNA methylation and autism spectrum disorder

Background

Several reports have suggested a role for epigenetic mechanisms in ASD etiology. Epigenome-wide association studies (EWAS) in autism spectrum disorder (ASD) may shed light on particular biological mechanisms. However, studies of ASD cases versus controls have been limited by post-mortem timing and severely small sample sizes. Reports from in-life sampling of blood or saliva have also been very limited in sample size and/or genomic coverage. We present the largest case-control EWAS for ASD to date, combining data from population-based case-control and case-sibling pair studies.

Methods

DNA from 968 blood samples from children in the Study to Explore Early Development (SEED 1) was used to generate epigenome-wide array DNA methylation (DNAm) data at 485,512 CpG sites for 453 cases and 515 controls, using the Illumina 450K Beadchip. The Simons Simplex Collection (SSC) provided 450K array DNAm data on an additional 343 cases and their unaffected siblings. We performed EWAS meta-analysis across results from the two data sets, with adjustment for sex and surrogate variables that reflect major sources of biological variation and technical confounding such as cell type, batch, and ancestry. We compared top EWAS results to those from a previous brain-based analysis. We also tested for enrichment of ASD EWAS CpGs for being targets of meQTL associations using available SNP genotype data in the SEED sample.

Findings

In this meta-analysis of blood-based DNA from 796 cases and 858 controls, no single CpG met a Bonferroni discovery threshold of p < 1.12 × 10^− 7. Seven CpGs showed differences at p < 1 × 10^− 5 and 48 at 1 × 10^− 4. Of the top 7, 5 showed brain-based ASD associations as well, often with larger effect sizes, and the top 48 overall showed modest concordance (r = 0.31) in direction of effect with cerebellum samples. Finally, we observed suggestive evidence for enrichment of CpG sites controlled by SNPs (meQTL targets) among the EWAS CpG hits, which was consistent across EWAS and meQTL discovery p value thresholds.

Conclusions

No single CpG site showed a large enough DNAm difference between cases and controls to achieve epigenome-wide significance in this sample size. However, our results suggest the potential to observe disease associations from blood-based samples. Among the seven sites achieving suggestive statistical significance, we observed consistent, and stronger, effects at the same sites among brain samples. Discovery-oriented EWAS for ASD using blood samples will likely need even larger samples and unified genetic data to further understand DNAm differences in ASD.

Electronic supplementary material

The online version of this article (10.1186/s13229-018-0224-6) contains supplementary material, which is available to authorized users.

Tracking age-correlated DNA methylation markers in the young

DNA methylation is the most extensively studied epigenetic signature, with a large number of studies reporting age-correlated CpG sites in overlapping genes. However, most of these studies lack sample coverage of individuals under 18 years old and therefore little is known about the progression of DNA methylation patterns in children and adolescents. In the present study we aimed to select candidate age-correlated DNA methylation markers based on public datasets from Illumina BeadChip arrays and previous publications, then to explore the resulting markers in 209 blood samples from donors aged between 2 to 18 years old using the EpiTYPER® DNA methylation analysis system. Results from our analyses identified six genes highly correlated with age in the young, in particular the gene KCNAB3, which indicates its potential as a highly informative and specific age biomarker for childhood and adolescence. We outline a preliminary age prediction model based on quantile regression that uses data from the six CpG sites most strongly correlated with age ranges extended to include children and adolescents.

Change in FK506 binding protein 5 (FKBP5) methylation over time among preschoolers with adversity

FK506 binding protein 5 (FKBP5) alters stress response system functioning, and childhood maltreatment is associated with methylation of the FKBP5 gene. Yet it is unknown if maltreatment contributes to change in FKBP5 methylation over time. The current study draws upon a sample of 231 preschoolers, including 123 with child welfare documentation of moderate to severe maltreatment in the past 6 months, to understand if maltreatment contributes to change in FKBP5 methylation over a 6-month period. Review of child protection records and semistructured interviews in the home were used to assess maltreatment and exposure to other contextual stressors, as well as service utilization. Methylation of FKBP5 at two CpG sites in intron 7 was measured from saliva DNA at the time of initial study enrollment, and 6 months following enrollment. Child maltreatment was associated with change in FKBP5 methylation over time, but only when children were exposed to high levels of other contextual stressors. Service utilization was associated with increases in methylation over time, but only among children with the FKPB5 rs1360780 protective CC genotype. Methylation of FKBP5 is sensitive to stress exposure and may be a mechanism linking early adversity to long-term health and developmental outcomes.

Integrated epigenetic and genetic analysis identifies markers of prognostic significance in pediatric acute myeloid leukemia

Acute myeloid leukemia (AML) may be an epigenetically-driven malignancy because it harbors fewer genomic mutations than other cancers. In recent studies of AML in adults, DNA methylation patterns associate with clinical risk groups and prognosis. However, thorough evaluations of methylation in pediatric AML have not been done. Therefore, we performed an integrated analysis (IA) of the methylome and transcriptome with clinical outcome in 151 pediatric patients from the multi-center AML02 clinical trial discovery cohort. Intriguingly, reduced methylation and increased expression of DNMT3B was associated with worse clinical outcomes (IA p ≤ 10⁻⁵; q ≤ 0.002). In particular, greater DNMT3B expression associated with worse minimal residual disease (MRD; p < 10⁻⁵; q = 0.01), a greater rate of relapse or resistant disease (RR) (p = 0.00006; q = 0.06), and event-free survival (EFS; p = 0.00003; q = 0.04). Also, greater DNMT3B expression associated with greater genome-wide methylation burden (GWMB; R = 0.39; p = 10⁻⁶) and greater GWMB associated with worse clinical outcomes (IA p < 10⁻⁵). In an independent validation cohort of 132 similarly treated AAML0531 clinical trial patients, greater DNMT3B expression associated with greater GWMB, worse MRD, worse RR, and worse EFS (all p < 0.03); also, greater GWMB associated with worse MRD (p = 0.004) and EFS (p = 0.037). These results indicate that DNMT3B and GWMB may have a central role in the development and prognosis of pediatric AML.

Age-related DNA methylation changes are tissue-specific with ELOVL2 promoter methylation as exception

Background

The well-established association of chronological age with changes in DNA methylation is primarily founded on the analysis of large sets of blood samples, while conclusions regarding tissue-specificity are typically based on small number of samples, tissues and CpGs. Here, we systematically investigate the tissue-specific character of age-related DNA methylation changes at the level of the CpG, functional genomic region and nearest gene in a large dataset.

Results

We assembled a compendium of public data, encompassing genome-wide DNA methylation data (Illumina 450k array) on 8092 samples from 16 different tissues, including 7 tissues with moderate to high sample numbers (Dataset size range 96–1202, N_total = 2858). In the 7 tissues (brain, buccal, liver, kidney, subcutaneous fat, monocytes and T-helper cells), we identified 7850 differentially methylated positions that gained (gain-aDMPs; cut-offs: P_bonf ≤ 0.05, effect size ≥ 2%/10 years) and 4,287 that lost DNA methylation with age (loss-aDMPs), 92% of which had not previously been reported for whole blood. The majority of all aDMPs identified occurred in one tissue only (gain-aDMPs: 85.2%; loss-aDMPs: 97.4%), an effect independent of statistical power. This striking tissue-specificity extended to both the functional genomic regions (defined by chromatin state segmentation) and the nearest gene. However, aDMPs did accumulate in regions with the same functional annotation across tissues, namely polycomb-repressed CpG islands for gain-aDMPs and regions marked by active histone modifications for loss-aDMPs.

Conclusion

Our analysis shows that age-related DNA methylation changes are highly tissue-specific. These results may guide the development of improved tissue-specific markers of chronological and, perhaps, biological age.

Electronic supplementary material

The online version of this article (10.1186/s13072-018-0191-3) contains supplementary material, which is available to authorized users.

Identification of rare de novo epigenetic variations in congenital disorders

Certain human traits such as neurodevelopmental disorders (NDs) and congenital anomalies (CAs) are believed to be primarily genetic in origin. However, even after whole-genome sequencing (WGS), a substantial fraction of such disorders remain unexplained. We hypothesize that some cases of ND-CA are caused by aberrant DNA methylation leading to dysregulated genome function. Comparing DNA methylation profiles from 489 individuals with ND-CAs against 1534 controls, we identify epivariations as a frequent occurrence in the human genome. De novo epivariations are significantly enriched in cases, while RNAseq analysis shows that epivariations often have an impact on gene expression comparable to loss-of-function mutations. Additionally, we detect and replicate an enrichment of rare sequence mutations overlapping CTCF binding sites close to epivariations, providing a rationale for interpreting non-coding variation. We propose that epivariations contribute to the pathogenesis of some patients with unexplained ND-CAs, and as such likely have diagnostic relevance.

DNA Methylome Marks of Exposure to Particulate Matter at Three Time Points in Early Life

Maternal exposure to airborne particulate matter (PM) has been associated with restricted fetal growth and reduced birthweight. Here, we performed methylome-wide analyses of cord and children's blood DNA in relation to residential exposure to PM smaller than 10 μm (PM10). This study included participants of the Avon Longitudinal Study of Pregnancy and Childhood (ALSPAC, cord blood, n = 780; blood at age 7, n = 757 and age 15-17, n = 850) and the EXPOsOMICS birth cohort consortium including cord blood from ENVIR ONAGE ( n = 197), INMA ( n = 84), Piccolipiù ( n = 99) and Rhea ( n = 75). We could not identify significant CpG sites, by meta-analyzing associations between maternal PM10 exposure during pregnancy and DNA methylation in cord blood, nor by studying DNA methylation and concordant annual exposure at 7 and 15-17 years. The CpG cg21785536 was inversely associated with PM10 exposure using a longitudinal model integrating the three studied age groups (-1.2% per 10 μg/m3; raw p-value = 3.82 × 10-8). Pathway analyses on the corresponding genes of the 100 strongest associated CpG sites of the longitudinal model revealed enriched pathways relating to the GABAergic synapse, p53 signaling and NOTCH1. We provided evidence that residential PM10 exposure in early life affects methylation of the CpG cg21785536 located on the EGF Domain Specific O-Linked N-Acetylglucosamine Transferase gene.

The epigenetic clock and physical development during childhood and adolescence: longitudinal analysis from a UK birth cohort

Background: Statistical models that use an individual’s DNA methylation levels to estimate their age (known as epigenetic clocks) have recently been developed, with 96% correlation found between epigenetic and chronological age. We postulate that differences between estimated and actual age [age acceleration (AA)] can be used as a measure of developmental age in early life.

Methods: We obtained DNA methylation measures at three time points (birth, age 7 years and age 17 years) in 1018 children from the Avon Longitudinal Study of Parents and Children (ALSPAC). Using an online calculator, we estimated epigenetic age, and thus AA, for each child at each time point. We then investigated whether AA was prospectively associated with repeated measures of height, weight, body mass index (BMI), bone mineral density, bone mass, fat mass, lean mass and Tanner stage.

Results: Positive AA at birth was associated with higher average fat mass [1321 g per year of AA, 95% confidence interval (CI) 386, 2256 g] from birth to adolescence (i.e. from age 0–17 years) and AA at age 7 was associated with higher average height (0.23 cm per year of AA, 95% CI 0.04, 0.41 cm). Conflicting evidence for the role of AA (at birth and in childhood) on changes during development was also found, with higher AA being positively associated with changes in weight, BMI and Tanner stage, but negatively with changes in height and fat mass.

Conclusions: We found evidence that being ahead of one’s epigenetic age acceleration is related to developmental characteristics during childhood and adolescence. This demonstrates the potential for using AA as a measure of development in future research.

Methyl-Donor and Cofactor Nutrient Intakes in the First 2-3 Years and Global DNA Methylation at Age 4: A Prospective Cohort Study

BACKGROUND

During the early postnatal period, the impact of nutrition on DNA methylation has not been well studied in humans. The aim was to quantify the relationship between one-carbon metabolism nutrient intake during the first three years of life and global DNA methylation levels at four years.

DESIGN

Childhood dietary intake was assessed using infant feeding questionnaires, food frequency questionnaires, 4-day weighed food records and 24-h food records. The dietary records were used to estimate the intake of methionine, folate, vitamins B2, B6 and B12 and choline. The accumulative nutrient intake specific rank from three months to three years of age was used for analysis. Global DNA methylation (%5-methyl cytosines (%5-mC)) was measured in buccal cells at four years of age, using an enzyme-linked immunosorbent assay (ELISA) commercial kit. Linear regression models were used to quantify the statistical relationships.

RESULTS

Data were collected from 73 children recruited from the Women and their Children's Health (WATCH) study. No association was found between one-carbon metabolism nutrient intake and global DNA methylation levels (P > 0.05). Global DNA methylation levels in males were significantly higher than in females (median %5-mC: 1.82 vs. 1.03, males and females respectively, (P < 0.05)).

CONCLUSION

No association was found between the intake of one-carbon metabolism nutrients during the early postnatal period and global DNA methylation levels at age four years. Higher global DNA methylation levels in males warrants further investigation.

Methylation of the genes ROD1, NLRC5, and HKR1 is associated with aging in Hainan centenarians

Background

Human aging is a hot topic in biology, and it has been associated with DNA methylation changes at specific genomic sites. We aimed to study the changes of DNA methylation at a single-CpG-site resolution using peripheral blood samples from centenarians.

Methods

Using Illumina 450 K Methylation BeadChip microarray assays, we carried out a pool-based, epigenome-wide investigation of DNA methylation of blood samples from 12 centenarians and 12 healthy controls. Differentially methylated cytosine-phosphate-guanosine (CpG) sites were selected for further pyrosequencing analysis of blood samples from 30 centenarians and 30 healthy controls.

Result

We identified a total of 31 high-confidence CpG sites with differential methylation profiles between the groups: 9 (29%) were hypermethylated and 22 (71%) were hypomethylated in centenarians. It was also found that hypermethylation of HKR1 and hypomethylation of ROD1 and NLRC5 genes strongly correlated with age in centenarians.

Conclusion

Our results indicate that the methylation profile combination of HKR1, ROD1, and NLRC5 could be a promising biomarker for aging in Hainan centenarians.

Electronic supplementary material

The online version of this article (10.1186/s12920-018-0334-1) contains supplementary material, which is available to authorized users.

Back to the future: Epigenetic clock plasticity towards healthy aging

Aging is the most important risk factor for major human lifestyle diseases, including cancer, neurological and cardiometabolic disorders. Due to the complex interplay between genetics, lifestyle and environmental factors, some individuals seem to age faster than others, whereas centenarians seem to have a slower aging process. Therefore, a biochemical biomarker reflecting the relative biological age would be helpful to predict an individual's health status and aging disease risk. Although it is already known for years that cumulative epigenetic changes occur upon aging, DNA methylation patterns were only recently used to construct an epigenetic clock predictor for biological age, which is a measure of how well your body functions compared to your chronological age. Moreover, the epigenetic DNA methylation clock signature is increasingly applied as a biomarker to estimate aging disease susceptibility and mortality risk. Finally, the epigenetic clock signature could be used as a lifestyle management tool to monitor healthy aging, to evaluate preventive interventions against chronic aging disorders and to extend healthy lifespan. Dissecting the mechanism of the epigenetic aging clock will yield valuable insights into the aging process and how it can be manipulated to improve health span.

Systems Biology in Aging Research

Systems biology is an approach to collect high-dimensional data and analyze in an integrated manner. As aging is a complicated physiological functional decline in biological system, the methods in systems biology could be utilized in aging studies. Here we reviewed recent advances in systems biology in aging research and divide them into two major parts. One is the data resource, which includes omics data from DNA, RNA, proteins, epigenetic changes, metabolisms, and recently single-cell-level variations. The other is the data analysis methods consisting of network and modeling approaches. With all the data and the tools to analyze them, we could further promote our understanding of the systematic aging.

Epigenetic mechanisms in coronary artery disease: The current state and prospects

Coronary artery disease (CAD) is the leading cause of morbidity and mortality. CAD has both genetic and environmental causes. In the past two decades, the understanding of epigenetics has advanced swiftly and vigorously. It has been demonstrated that epigenetic modifications are associated with the onset and progression of CAD. This review aims to improve the understanding of the epigenetic mechanisms closely related to CAD and to provide a novel perspective on the onset and development of CAD. Epigenetic changes include DNA methylation, histone modification, microRNA and lncRNA, which are interrelated with critical genes and influence the expression of those genes. In addition, miRNA plays a diverse role in the pathological process of CAD. Numerous studies have found that some cardiac-specific miRNAs have potential as certain diagnostic biomarkers and treatment targets for CAD. In this review, the aberrant epigenetic mechanisms that contribute to CAD will be discussed. We will also provide novel insight into the epigenetic mechanisms that target CAD.