Age-dependent DNA methylation of genes that are suppressed in stem cells is a hallmark of cancer

A model for the aberrant DNA methylomes in aging cells and cancer cells

DNA methylation at the fifth position of cytosine is a major epigenetic mark conserved in plants and mammals. Genome-wide DNA methylation patterns are dynamically controlled by integrated activities of establishment, maintenance, and removal. In both plants and mammals, a pattern of global DNA hypomethylation coupled with increased methylation levels at some specific genomic regions arises at specific developmental stages and in certain abnormal cells, such as mammalian aging cells and cancer cells as well as some plant epigenetic mutants. Here we provide an overview of this distinct DNA methylation pattern in mammals and plants, and propose that a methylstat, which is a cis-element responsive to both DNA methylation and active demethylation activities and controlling the transcriptional activity of a key DNA methylation regulator, can help to explain the enigmatic DNA methylation patterns in aging cells and cancer cells.

DNA methylation-based biomarkers and the epigenetic clock theory of ageing

Identifying and validating molecular targets of interventions that extend the human health span and lifespan has been difficult, as most clinical biomarkers are not sufficiently representative of the fundamental mechanisms of ageing to serve as their indicators. In a recent breakthrough, biomarkers of ageing based on DNA methylation data have enabled accurate age estimates for any tissue across the entire life course. These 'epigenetic clocks' link developmental and maintenance processes to biological ageing, giving rise to a unified theory of life course. Epigenetic biomarkers may help to address long-standing questions in many fields, including the central question: why do we age?

Detection of cell-type-specific risk-CpG sites in epigenome-wide association studies

In epigenome-wide association studies, the measured signals for each sample are a mixture of methylation profiles from different cell types. Current approaches to the association detection claim whether a cytosine-phosphate-guanine (CpG) site is associated with the phenotype or not at aggregate level and can suffer from low statistical power. Here, we propose a statistical method, HIgh REsolution (HIRE), which not only improves the power of association detection at aggregate level as compared to the existing methods but also enables the detection of risk-CpG sites for individual cell types.

Cellular heterogeneity is one of the major confounding factors in EWAS studies. Here the authors present a statistical method, HIgh REsolution (HIRE), which enables the detection of risk-CpG sites for individual cell types.

Neural crest stem cells from human epidermis of aged donors maintain their multipotency in vitro and in vivo

Neural crest (NC) cells are multipotent stem cells that arise from the embryonic ectoderm, delaminate from the neural tube in early vertebrate development and migrate throughout the developing embryo, where they differentiate into various cell lineages. Here we show that multipotent and functional NC cells can be derived by induction with a growth factor cocktail containing FGF2 and IGF1 from cultures of human inter-follicular keratinocytes (KC) isolated from elderly donors. Adult NC cells exhibited longer doubling times as compared to neonatal NC cells, but showed limited signs of cellular senescence despite the advanced age of the donors and exhibited significantly younger epigenetic age as compared to KC. They also maintained their multipotency, as evidenced by their ability to differentiate into all NC-specific lineages including neurons, Schwann cells, melanocytes, and smooth muscle cells (SMC). Notably, upon implantation into chick embryos, adult NC cells behaved similar to their embryonic counterparts, migrated along stereotypical pathways and contributed to multiple NC derivatives in ovo. These results suggest that KC-derived NC cells may provide an easily accessible, autologous source of stem cells that can be used for treatment of neurodegenerative diseases or as a model system for studying disease pathophysiology and drug development.

As time flies by: Investigating cardiac aging in the short-lived Drosophila model

Aging is associated with a decline in heart function across the tissue, cellular, and molecular levels. The risk of cardiovascular disease grows significantly over time, and as developed countries continue to see an increase in lifespan, the cost of cardiovascular healthcare for the elderly will undoubtedly rise. The molecular basis for cardiac function deterioration with age is multifaceted and not entirely clear, and there is a limit to what investigations can be performed on human subjects or mammalian models. Drosophila melanogaster has emerged as a useful model organism for studying aging in a short timeframe, benefitting from a suite of molecular and genetic tools and displaying highly conserved traits of cardiac senescence. Here, we discuss recent advances in our understanding of cardiac aging and how the fruit fly has aided in these developments.

Epigenetic Regulation of TRAIL Signaling: Implication for Cancer Therapy

One of the main characteristics of carcinogenesis relies on genetic alterations in DNA and epigenetic changes in histone and non-histone proteins. At the chromatin level, gene expression is tightly controlled by DNA methyl transferases, histone acetyltransferases (HATs), histone deacetylases (HDACs), and acetyl-binding proteins. In particular, the expression level and function of several tumor suppressor genes, or oncogenes such as c-Myc, p53 or TRAIL, have been found to be regulated by acetylation. For example, HATs are a group of enzymes, which are responsible for the acetylation of histone proteins, resulting in chromatin relaxation and transcriptional activation, whereas HDACs by deacetylating histones lead to chromatin compaction and the subsequent transcriptional repression of tumor suppressor genes. Direct acetylation of suppressor genes or oncogenes can affect their stability or function. Histone deacetylase inhibitors (HDACi) have thus been developed as a promising therapeutic target in oncology. While these inhibitors display anticancer properties in preclinical models, and despite the fact that some of them have been approved by the FDA, HDACi still have limited therapeutic efficacy in clinical terms. Nonetheless, combined with a wide range of structurally and functionally diverse chemical compounds or immune therapies, HDACi have been reported to work in synergy to induce tumor regression. In this review, the role of HDACs in cancer etiology and recent advances in the development of HDACi will be presented and put into perspective as potential drugs synergizing with TRAIL's pro-apoptotic potential.

Losing Sense of Self and Surroundings: Hematopoietic Stem Cell Aging and Leukemic Transformation

Aging leads to functional decline of the hematopoietic system, manifested by an increased incidence of hematological disease in the elderly. Deterioration of hematopoietic integrity with age originates in part from the degraded functionality of hematopoietic stem cells (HSCs). Here, we review recent findings identifying changes in metabolic programs and loss of epigenetic identity as major drivers of old HSC dysfunction and their role in promoting leukemia onset in the context of age-related clonal hematopoiesis (ARCH). We discuss how inflammatory and growth signals from the aged bone marrow (BM) microenvironment contribute to cell-intrinsic HSC aging phenotypes and favor leukemia development. Finally, we address how metabolic, epigenetic, and inflammatory pathways could be targeted to enhance old HSC fitness and prevent leukemic transformation.

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.

Predicting gene expression using DNA methylation in three human populations

Background

DNA methylation, an important epigenetic mark, is well known for its regulatory role in gene expression, especially the negative correlation in the promoter region. However, its correlation with gene expression across genome at human population level has not been well studied. In particular, it is unclear if genome-wide DNA methylation profile of an individual can predict her/his gene expression profile. Previous studies were mostly limited to association analyses between single CpG site methylation and gene expression. It is not known whether DNA methylation of a gene has enough prediction power to serve as a surrogate for gene expression in existing human study cohorts with DNA samples other than RNA samples.

Results

We examined DNA methylation in the gene region for predicting gene expression across individuals in non-cancer tissues of three human population datasets, adipose tissue of the Multiple Tissue Human Expression Resource Projects (MuTHER), peripheral blood mononuclear cell (PBMC) from Asthma and normal control study participates, and lymphoblastoid cell lines (LCL) from healthy individuals. Three prediction models were investigated, single linear regression, multiple linear regression, and least absolute shrinkage and selection operator (LASSO) penalized regression. Our results showed that LASSO regression has superior performance among these methods. However, the prediction power is generally low and varies across datasets. Only 30 and 42 genes were found to have cross-validation R² greater than 0.3 in the PBMC and Adipose datasets, respectively. A substantially larger number of genes (258) were identified in the LCL dataset, which was generated from a more homogeneous cell line sample source. We also demonstrated that it gives better prediction power not to exclude any CpG probe due to cross hybridization or SNP effect.

Conclusion

In our three population analyses DNA methylation of CpG sites at gene region have limited prediction power for gene expression across individuals with linear regression models. The prediction power potentially varies depending on tissue, cell type, and data sources. In our analyses, the combination of LASSO regression and all probes not excluding any probe on the methylation array provides the best prediction for gene expression.

DNA methylation profiling implicates exposure to PCBs in the pathogenesis of B-cell chronic lymphocytic leukemia

OBJECTIVES

To characterize the impact of PCB exposure on DNA methylation in peripheral blood leucocytes and to evaluate the corresponding changes in relation to possible health effects, with a focus on B-cell lymphoma.

METHODS

We conducted an epigenome-wide association study on 611 adults free of diagnosed disease, living in Italy and Sweden, in whom we also measured plasma concentrations of 6 PCB congeners, DDE and hexachlorobenzene.

RESULTS

We identified 650 CpG sites whose methylation correlates strongly (FDR < 0.01) with plasma concentrations of at least one PCB congener. Stronger effects were observed in males and in Sweden. This epigenetic exposure profile shows extensive and highly statistically significant overlaps with published profiles associated with the risk of future B-cell chronic lymphocytic leukemia (CLL) as well as with clinical CLL (38 and 28 CpG sites, respectively). For all these sites, the methylation changes were in the same direction for increasing exposure and for higher disease risk or clinical disease status, suggesting an etiological link between exposure and CLL. Mediation analysis reinforced the suggestion of a causal link between exposure, changes in DNA methylation and disease. Disease connectivity analysis identified multiple additional diseases associated with differentially methylated genes, including melanoma for which an etiological link with PCB exposure is established, as well as developmental and neurological diseases for which there is corresponding epidemiological evidence. Differentially methylated genes include many homeobox genes, suggesting that PCBs target stem cells. Furthermore, numerous polycomb protein target genes were hypermethylated with increasing exposure, an effect known to constitute an early marker of carcinogenesis.

CONCLUSIONS

This study provides mechanistic evidence in support of a link between exposure to PCBs and the etiology of CLL and underlines the utility of omic profiling in the evaluation of the potential toxicity of environmental chemicals.

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.

Computational Methods for Detection of Differentially Methylated Regions Using Kernel Distance and Scan Statistics

MOTIVATION

Researchers in genomics are increasingly interested in epigenetic factors such as DNA methylation because they play an important role in regulating gene expression without changes in the sequence of DNA. Abnormal DNA methylation is associated with many human diseases.

RESULTS

We propose two different approaches to test for differentially methylated regions (DMRs) associated with complex traits, while accounting for correlations among CpG sites in the DMRs. The first approach is a nonparametric method using a kernel distance statistic and the second one is a likelihood-based method using a binomial spatial scan statistic. The kernel distance method uses the kernel function, while the binomial scan statistic approach uses a mixed-effects model to incorporate correlations among CpG sites. Extensive simulations show that both approaches have excellent control of type I error, and both have reasonable statistical power. The binomial scan statistic approach appears to have higher power, while the kernel distance method is computationally faster. The proposed methods are demonstrated using data from a chronic lymphocytic leukemia (CLL) study.

DNA Methylation Clocks in Aging: Categories, Causes, and Consequences

Age-associated changes to the mammalian DNA methylome are well documented and thought to promote diseases of aging, such as cancer. Recent studies have identified collections of individual methylation sites whose aggregate methylation status measures chronological age, referred to as the DNA methylation clock. DNA methylation may also have value as a biomarker of healthy versus unhealthy aging and disease risk; in other words, a biological clock. Here we consider the relationship between the chronological and biological clocks, their underlying mechanisms, potential consequences, and their utility as biomarkers and as targets for intervention to promote healthy aging and longevity.

The Link Between Epigenetic Clocks for Aging and Senescence

Replicative senescence of cells in vitro is often considered as counterpart for aging of the organism in vivo. In fact, both processes are associated with functional decay and similar molecular modifications. On epigenetic level, replicative senescence and aging evoke characteristic modifications in the DNA methylation (DNAm) pattern, but at different sites in the genome. Various epigenetic signatures, which are often referred to as epigenetic clocks, provide useful biomarkers: Senescence-associated epigenetic modifications can be used for quality control of cell preparations or to elucidate effects of culture conditions on the state of cellular aging. Age-associated epigenetic modifications hold high expectations to determine chronological age in forensics or to identify parameters that impact on biological aging. Despite these differences, there are some striking similarities between senescence- and age-associated DNAm, such as complete rejuvenation during reprogramming into induced pluripotent stem cells (iPSCs). It is yet unclear what makes epigenetic clocks tick, but there is evidence that the underlying mechanisms of both processes are related to similar modifications in the histone code or higher order chromatin. Replicative senescence therefore appears to be a suitable model system to gain better insight into how organismal aging might be governed epigenetically.

Targeting Cell Senescence for the Treatment of Age-Related Bone Loss

PURPOSE OF REVIEW

We review cell senescence in the context of age-related bone loss by broadly discussing aging mechanisms in bone, currently known inducers and markers of senescence, the senescence-associated secretory phenotype (SASP), and the emerging roles of senescence in bone homeostasis and pathology.

RECENT FINDINGS

Cellular senescence is a state of irreversible cell cycle arrest induced by insults or stressors including telomere attrition, oxidative stress, DNA damage, oncogene activation, and other intrinsic or extrinsic triggers and there is mounting evidence for the role of senescence in aging bone. Cellular aging also instigates a SASP that exerts detrimental paracrine and likely systemic effects. With aging, multiple cell types in the bone microenvironment become senescent, with osteocytes and myeloid cells as primary contributors to the SASP. Targeting undesired senescent cells may be a favorable strategy to promote bone anabolic and anti-resorptive functions in aging bone, with the possibility of improving bone quality and function with normal aging and/or disease.

Human age prediction based on DNA methylation of non-blood tissues

BACKGROUND AND OBJECTIVE

The study of human aging contributes to disease prevention, treatment and life extension. Recently, epigenetics studies have evidenced that there is a close association between DNA methylation and human ages. A quantitatively statistical modeling between DNA methylation and ages could predict the person's age more accurately.

METHODS

We propose a regression model to predict human age based on gradient boosting regressor (GBR). We collect a total of 1280 publicly available non-blood tissues samples with ages ranged from 0 to 90 years old. We calculate the Pearson correlation between CpG's DNA methylation level and age to select age-related CpGs.

RESULTS

Thirteen age-related CpG sites are selected. GBR has the smallest mean absolute deviation to the actual age comparing with other three different models including Bayesian ridge, multiple linear regression, and support vector regression. In the training datasets, the cross-validation results show that the correlation R² between predicted age and DNA methylation is 0.89, and the mean absolute deviation is 4.66 years. In an independent testing set with 262 samples, the GBR achieves the mean absolute deviation of 6.08 years. Meanwhile we also briefly describe the function of the selected thirteen CpG sites.

CONCLUSIONS

We build an age predictor to study the association between ages and the DNA methylation of human non-blood tissues. Our new model provides a more accurate estimation of human ages which will be instrumental for understanding the regulation of DNA methylation on human aging and will accurately monitor the individual aging process.

An epigenetic pacemaker is detected via a fast conditional expectation maximization algorithm

AIM

DNA methylation has proven to be a remarkably accurate biomarker for human age, allowing the prediction of chronological age to within a couple of years. Recently, we proposed that the Universal PaceMaker (UPM), a flexible paradigm for modeling evolution, could be applied to epigenetic aging. Nevertheless, application to real data was restricted to small datasets for technical limitations.

MATERIALS & METHODS

We partition the set of variables into to two subsets and optimize the likelihood function on each set separately. This yields an extremely efficient Conditional Expectation Maximization algorithm, alternating between the two sets while increasing the overall likelihood.

RESULTS

Using the technique, we could reanalyze datasets of larger magnitude and show significant advantage to the UPM approach.

CONCLUSION

The UPM more faithfully models epigenetic aging than the time linear approach while methylated sites accelerate and decelerate jointly.

Synchrony and asynchrony between an epigenetic clock and developmental timing

Epigenetic changes have been used to estimate chronological age across the lifespan, and some studies suggest that epigenetic "aging" clocks may already operate in developing tissue. To better understand the relationship between developmental stage and epigenetic age, we utilized the highly regular sequence of development found in the mammalian neural retina and a well-established epigenetic aging clock based on DNA methylation. Our results demonstrate that the epigenetic age of fetal retina is highly correlated with chronological age. We further establish that epigenetic aging progresses normally in vitro, suggesting that epigenetic aging is a property of individual tissues. This correlation is also retained in stem cell-derived retinal organoids, but is accelerated in individuals with Down syndrome, a progeroid-like condition. Overall, our results suggest that epigenetic aging begins as early as a few weeks post-conception, in fetal tissues, and the mechanisms underlying the phenomenon of epigenetic aging might be studied in developing organs.

Approaches towards Longevity: Reprogramming, Senolysis, and Improved Mitotic Competence as Anti-Aging Therapies

Mainstream approaches that are currently used as anti-aging therapies primarily explore the senescence and epigenetic drift aging hallmarks and they are at two ends of the spectrum. While senolytic therapies include either the selective elimination of senescent cells or the disruption of their secretome with the use of drugs or natural compounds, cellular reprogramming uses genetic manipulation to revert cells all the way back to pluripotency. Here, we describe the progress that has been made on these therapies, while highlighting the major challenges involved. Moreover, based on recent findings elucidating the impact of mitotic shutdown and aneuploidy in cellular senescence, we discuss the modulation of mitotic competence as an alternative strategy to delay the hallmarks of aging. We propose that a regulated rise in mitotic competence of cells could circumvent certain limitations that are present in the senolytic and reprogramming approaches, by acting to decelerate senescence and possibly restore the epigenetic landscape.

Epigenetic Priming in Cancer Initiation

Recent evidence from hematopoietic and epithelial tumors revealed that the contribution of oncogenes to cancer development is mediated mainly through epigenetic priming of cancer-initiating cells, suggesting that genetic lesions that initiate the cancer process might be dispensable for the posterior tumor progression and maintenance. Epigenetic priming may remain latent until it is later triggered by endogenous or environmental stimuli. This Opinion article addresses the impact of epigenetic priming in cancer development and in the design of new therapeutic approaches.

Aging-like Spontaneous Epigenetic Silencing Facilitates Wnt Activation, Stemness, and BrafV600E-Induced Tumorigenesis

We addressed the precursor role of aging-like spontaneous promoter DNA hypermethylation in initiating tumorigenesis. Using mouse colon-derived organoids, we show that promoter hypermethylation spontaneously arises in cells mimicking the human aging-like phenotype. The silenced genes activate the Wnt pathway, causing a stem-like state and differentiation defects. These changes render aged organoids profoundly more sensitive than young ones to transformation by BrafV600E, producing the typical human proximal BRAFV600E-driven colon adenocarcinomas characterized by extensive, abnormal gene-promoter CpG-island methylation, or the methylator phenotype (CIMP). Conversely, CRISPR-mediated simultaneous inactivation of a panel of the silenced genes markedly sensitizes to BrafV600E-induced transformation. Our studies tightly link aging-like epigenetic abnormalities to intestinal cell fate changes and predisposition to oncogene-driven colon tumorigenesis.

Epigenetic changes during aging and their reprogramming potential

The aging process results in significant epigenetic changes at all levels of chromatin and DNA organization. These include reduced global heterochromatin, nucleosome remodeling and loss, changes in histone marks, global DNA hypomethylation with CpG island hypermethylation, and the relocalization of chromatin modifying factors. Exactly how and why these changes occur is not fully understood, but evidence that these epigenetic changes affect longevity and may cause aging, is growing. Excitingly, new studies show that age-related epigenetic changes can be reversed with interventions such as cyclic expression of the Yamanaka reprogramming factors. This review presents a summary of epigenetic changes that occur in aging, highlights studies indicating that epigenetic changes may contribute to the aging process and outlines the current state of research into interventions to reprogram age-related epigenetic changes.

DNA methylation in the human frontal cortex reveals a putative mechanism for age-by-disease interactions

A consistent gene set undergoes age-associated expression changes in the human cerebral cortex, and our Age-by-Disease Model posits that these changes contribute to psychiatric diseases by "pushing" the expression of disease-associated genes in disease-promoting directions. DNA methylation (DNAm) is an attractive candidate mechanism for age-associated gene expression changes. We used the Illumina HumanMethylation450 array to characterize genome-wide DNAm in the postmortem orbital frontal cortex from 20 younger (<42 years) and 19 older (>60 years) subjects. DNAm data were integrated with existing normal brain aging expression data and sets of psychiatric disease risk genes to test the hypothesis that age-associated DNAm changes contribute to age-associated gene expression changes and, by extension, susceptibility to psychiatric diseases. We found that age-associated differentially methylated regions (aDMRs) are common, robust, bidirectional, concentrated in CpG island shelves and sea, depleted in CpG islands, and enriched among genes undergoing age-associated expression changes (OR = 2.30, p = 1.69 × 10^-27). We found the aDMRs are enriched among genetic association-based risk genes for schizophrenia, Alzheimer's disease (AD), and major depressive disorder (MDD) (OR = 2.51, p = 0.00015; OR = 2.38, p = 0.036; and OR = 3.08, p = 0.018, respectively) as well as expression-based MDD-associated genes (OR = 1.48, p = 0.00012). Similar patterns of enrichment were found for aDMRs that correlate with local gene expression. These results were replicated in a large publically-available dataset, and confirmed by meta-analysis of the two datasets. Our findings suggest DNAm is a molecular mechanism for age-associated gene expression changes and support a role for DNAm in age-by-disease interactions through preferential targeting of disease-associated genes.

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.

ACES: a machine learning toolbox for clustering analysis and visualization

Background

Studies that aim at explaining phenotypes or disease susceptibility by genetic or epigenetic variants often rely on clustering methods to stratify individuals or samples. While statistical associations may point at increased risk for certain parts of the population, the ultimate goal is to make precise predictions for each individual. This necessitates tools that allow for the rapid inspection of each data point, in particular to find explanations for outliers.

Results

ACES is an integrative cluster- and phenotype-browser, which implements standard clustering methods, as well as multiple visualization methods in which all sample information can be displayed quickly. In addition, ACES can automatically mine a list of phenotypes for cluster enrichment, whereby the number of clusters and their boundaries are estimated by a novel method. For visual data browsing, ACES provides a 2D or 3D PCA or Heat Map view. ACES is implemented in Java, with a focus on a user-friendly, interactive, graphical interface.

Conclusions

ACES has been proven an invaluable tool for analyzing large, pre-filtered DNA methylation data sets and RNA-Sequencing data, due to its ease to link molecular markers to complex phenotypes. The source code is available from https://github.com/GrabherrGroup/ACES.

DNA methylation age is not affected in psoriatic skin tissue

Background

Psoriasis (Ps) is a common chronic inflammatory skin disease. The keratinocytes of psoriatic skin defy normal apoptosis and exhibit active cell proliferation. Aberrant DNA methylation (DNAm) has been suggested relevant through regulating the expression of Ps susceptibility genes. However, it is unclear whether the biological age inferred from DNA methylome is affected.

Results

To address the above issue, we applied a recently developed methylation clock model to our Chinese Han population dataset, which includes DNAm data of 114 involved psoriatic skin tissues (PP) and 41 uninvolved psoriatic skin tissues (PN) from Ps patients, and 62 normal skin tissues (NN) from health controls. We first confirmed the applicability of the clock in PN and NN. We then showed that PP samples have largely unchanged DNAm age, and that no association was observed between available clinical features and DNAm age acceleration. Examination of genome-wide CpGs yielded age-associated CpGs with concordant age-association coefficients among the three groups, which was also supported by an external dataset. We also interestingly observed two clock CpGs differentially methylated between PP and PN.

Conclusions

Overall, our results suggest no significant alteration in DNAm age in PN and PP. Therefore, the increase in keratinocyte proliferation and alteration in DNAm caused by Ps may not affect the biological age of psoriatic skin tissue.

Electronic supplementary material

The online version of this article (10.1186/s13148-018-0584-y) contains supplementary material, which is available to authorized users.

A Clinical Trial Using Methylation Age to Evaluate Current Antiaging Practices

Recent advances in the technology of "aging clocks" based on DNA methylation suggest that it may be possible to measure changes in the rate of human aging over periods as short as a year or two. To the extent that methylation (and other biomarkers) are valid surrogates for biological age, the testing of antiaging interventions has thus become radically cheaper, faster, and more practical. Together with colleagues at UCLA, I have initiated a clinical trial to evaluate some of the most popular antiaging strategies currently deployed by "early adopters" in the lay community of personal health activists. We are recruiting 5000 subjects, age 45-65, and interviewing them in detail about their diet, drugs and supplements, exercise, social, and other practices that plausibly contribute to modulate the rate of aging. They agree to submit blood samples for analysis of methylation age at the beginning, middle, and end of a 2-year test period. Primary endpoint is the difference in methylation age over the course of 2 years. We are in the process of developing a specialized clock, optimized for individual differences over time. Results will be viewed as an exploratory study to identify synergistic combinations of age-retarding treatments. It is our expectation that there is a great deal of redundancy in the strategies that have been researched and promoted to the aware public; thus, most combinations can retard the rate of aging by only a few percent, consistent with the best known single measures. However, we hope that among the many strategies that our subjects have adopted, there will be some combinations that synergize and achieve age retardation by ≥25% or more. A mock-up analysis of computer-generated data has been performed to fix parameters of the study, and confirm that such combinations will be able to be detected with good probability, should they exist. All data (redacted for privacy) will be open sourced, available to the scientific community and to the public.

Tipping the Scale Toward Gastric Disease: A Host-Pathogen Genomic Mismatch?

PURPOSE OF REVIEW

Chronic infection with Helicobacter pylori infection is necessary but not sufficient to initiate development of intestinal-type gastric adenocarcinoma. It is not clear what additional factors tip the scale from commensal bacteria towards a pathogen that facilitates development of gastric cancer. Genetic variants in both the pathogen and host have been implicated, but neither alone explains a substantial portion of disease risk.

RECENT FINDINGS

In this review, we consider studies that address the important role of human and bacterial genetics, ancestry and their interactions in determining gastric disease risk. We observe gaps in the current literature that should guide future work to confirm the hypothesis of the interacting roles of host and bacterial genetics that will be necessary to translate these findings into clinically relevant information.

SUMMARY

We summarize genetic risk factors for gastric disease in both H. pylori and human hosts. However, genetic variation of one or the other organism in isolation insufficiently explains gastric disease risk. The most promising models of gastric disease risk simultaneously consider the genetic variation of both the H. pylori and human host, under a co-evolution model.

Role of Endogenous Glucocorticoids in Cancer in the Elderly

Although not a disease itself, aging represents a risk factor for many aging-related illnesses, including cancer. Numerous causes underlie the increased incidence of malignancies in the elderly, for example, genomic instability and epigenetic alterations that occur at cellular level, which also involve the immune cells. The progressive decline of the immune system functions that occurs in aging defines immunosenescence, and includes both innate and adaptive immunity; the latter undergoes major alterations. Aging and chronic stress share the abnormal hypothalamic–pituitary–adrenal axis activation, where altered peripheral glucocorticoids (GC) levels and chronic stress have been associated with accelerated cellular aging, premature immunosenescence, and aging-related diseases. Consequently, changes in GC levels and sensitivity contribute to the signs of immunosenescence, namely fewer naïve T cells, poor immune response to new antigens, decreased cell-mediated immunity, and thymic involution. GC signaling alterations also involve epigenetic alterations in DNA methylation, with transcription modifications that may contribute to immunosenescence. Immune cell aging leads to decreased levels of immunosurveillance, thereby providing tumor cells one more route for immune system escape. Here, the contribution of GC secretion and signaling dysregulation to the increased incidence of tumorigenesis in the elderly is reviewed.

The role of DNA methylation in epigenetics of aging

Recent research suggests that epigenetics, especially DNA methylation, plays a mechanistic role in aging. Epigenetic clocks, which measure changes in a few hundred specific CpG sites, can accurately predict chronological age in a variety of species, including humans. These clocks are currently the bestbiomarkers for predicting mortality in humans. Additionally, several studies have characterized the effects of aging across the methylome in a wide variety of tissues from humans and mice. A small fraction (~2%) of the CpG sites show age-related changes, either hypermethylation or hypomethylation with aging. Evaluation of non-CpG site methylation has only been examined in a few studies, with about ~0.5% of these sites showing achange with age. Therefore, while only a small fraction of cytosines in the genome show changes in DNA methylation with age, this represents 2 to 3 million cytosines in the genome. Importantly, the only study to compare the effect of aging on DNA methylation in male and female mice and humans found that N95% of the age-related changes in DNA methylation in the hippocampus were sexually divergent, i.e., the methylation did not differ between males and females atyoung age but age-related changes occurred in one sex but not the other. The age-related changes in DNA methylation tend to be enriched and under-represented in specific genomic contexts, with some commonalities between tissues and species that require further investigation. The strongest evidence that the age-related changes in DNA methylation play a role in aging comes from studies of anti-aging interventions (e.g., caloric restriction, dwarfism, and rapamycin treatment) in mice. These anti-aging interventions deaccelerate the epigenetic clocks and reverse/prevent 20 to 40% of the age-related changes in DNA methylation. It will be important in the future to demonstrate that at least some of the age-related changes in DNA methylation directly lead to alterations in the transcriptome of cells/tissues that could potentially contribute to aging.

Hypermethylation of EIF4E promoter is associated with early onset of gastric cancer

Although gastric cancer (GC) in young adults (≤ 45 years) accounts for fewer than 10% of newly diagnosed cases, the young patients are more likely to have advanced disease at presentation compared with elderly patients. Previous studies have identified that the DNA methylation of genomes are different during aging. Our study aimed to explore the association between DNA methylation and the onset of GC. We applied Illumina HumanMethylation450 BeadChip to examine methylation expression profiles and compared methylation expression patterns in five early onset GC patients and seven elderly patients. Additionally, we evaluated the associations of methylation expression with different clinicopathological characteristics of GC. Our results showed that the pattern of genome-wide methylation expression was significantly different between early onset and elderly GC. The top 10 hypomethylation and hypermethylation CpG sites were selected for further analyses in The Cancer Genome Atlas (TCGA) database. We found that the hypermethylation of cg11037477, located at the promoter of EIF4E, was significantly associated with age at diagnosis and the expression of EIF4E. Besides, GC patients with high level of cg11037477 were more likely to have advance disease with T3/T4 invasion and III/IV stage. The cg11037477 hypermethylation and EIF4E down-expression were significantly related to poor survival of GC patients. Our study provides new insights into the molecular mechanism of early onset patients with GC and suggests that methylation of cg11037477 and expression of EIF4E may act as prognostic markers in GC.

Age-dependent methylation in epigenetic clock CpGs is associated with G-quadruplex, co-transcriptionally formed RNA structures and tentative splice sites

Horvath's epigenetic clock consists of 353 CpGs whose methylation levels can accurately predict the age of individuals. Using bioinformatics analysis, we investigated the conformation, energy characteristics and presence of tentative splice sites of the sequences surrounding the epigenetic clock CpGs, in relation to the median methylation changes in different ages, the presence of CpG islands and their position in genes. Common characteristics in the 100 nt sequences surrounding the epigenetic clock CpGs are G-quadruplexes and/or tentative splice site motifs. Median methylation increases significantly in sequences which adopt less stable structures during transcription. Methylation is higher when CpGs overlap with G-quadruplexes than when they precede them. Median methylation in epigenetic clock CpGs is higher in sequences expressed as single products rather than in multiple products and those containing single donors and multiple acceptors. Age-related methylation variation is significant in sequences without G-quadruplexes, particularly those producing low stability nascent RNA and those with splice sites. CpGs in sequences close to transcription start sites and those which are possibly never expressed (hypothetical proteins) undergo similar extent of age-related median methylation decrease and increase. Preservation of methylation is observed in CpG islands without G-quadruplexes, contrary to CpGs far from CpG islands (open sea). Sequences containing G-quadruplexes and RNA pseudoknots, determining the recognition by H3K27 histone methyltransferase, are hypomethylated. The presented structural DNA and co-transcriptional RNA analysis of epigenetic clock sequences, foreshadows the association of age-related methylation changes with the principle biological processes of DNA and histone methylation, splicing and chromatin silencing.

Age-specific changes in genome-wide methylation enrich for Foxa2 and estrogen receptor alpha binding sites

The role of DNA methylation patterns in complex phenotypes remains unclear. To explore this question, we adapted our methods for rare variant analysis to characterize genome-wide murine DNA hybridization array to investigate methylation at CpG islands, shores, and regulatory elements. We have applied this platform to compare age and tissue- specific methylation differences in the brain and spleen of young and aged mice. As expected from prior studies, there are clear global differences in organ-specific, but not age-specific, methylation due mostly to changes at repetitive elements. Surprisingly, out of 200,000 loci there were only 946 differentially methylated cytosines (DMCs) between young and old samples (529 hypermethylated, 417 hypomethylated in aged mice) compared to thousands of tissue-specific DMCs. Hypermethylated loci were clustered around the promoter region of Sfi1, exon 2 of Slc11a2, Drg1, Esr1 and Foxa2 transcription factor binding sites. In particular, there were 75 hypermethylated Foxa2 binding sites across a 2.7 Mb region of chromosome 11. Hypomethylated loci were clustered around Mid1, Isoc2b and genome-wide loci with binding sites for Foxa2 and Esr1, which are known to play important roles in development and aging. These data suggest discreet tissue-independent methylation changes associated with aging processes such as cell division (Sfi1, Mid1), energy production (Drg1, Isoc2b) and cell death (Foxa2, Esr1).

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.

Perinatally acquired HIV infection accelerates epigenetic aging in South African adolescents

OBJECTIVE

Recent studies demonstrate that infection with the HIV-1 is associated with accelerated aging effects in adults according to a highly accurate epigenetic biomarker of aging known as epigenetic clock. However, it is not yet known whether epigenetic age acceleration occurs as early as adolescence in perinatally HIV-infected (PHIV+) youth.

DESIGN

Observational study of PHIV and HIV-uninfected adolescents enrolled in the Cape Town Adolescent Antiretroviral Cohort Study.

METHODS

The Illumina EPIC array was used to generate blood DNA methylation data from 204 PHIV and 44 age-matched, uninfected (HIV-) adolescents aged 9-12 years old. The epigenetic clock software and method was used to estimate two measures of epigenetic age acceleration. Each participant completed a comprehensive neuropsychological test battery upon enrollment to Cape Town Adolescent Antiretroviral Cohort.

RESULTS

HIV is associated with biologically older blood in PHIV+ adolescents according to both measures of epigenetic age acceleration. One of the measures, extrinsic epigenetic age acceleration, is negatively correlated with measures of cognitive functioning (executive functioning, working memory, processing speed).

CONCLUSION

Overall, our results indicate that epigenetic age acceleration in blood can be observed in PHIV+ adolescents and that these epigenetic changes accompany poorer cognitive functioning.

Identification of DAPK1 Promoter Hypermethylation as a Biomarker for Intra-Epithelial Lesion and Cervical Cancer: A Meta-Analysis of Published Studies, TCGA, and GEO Datasets

Background: Promoter hypermethylation in death-associated protein kinase 1 (DAPK1) gene has been long linked to cervical neoplasia, but the established results remained controversial. Here, we performed a meta-analysis to assess the associations of DAPK1 promoter hypermethylation with low-grade intra-epithelial lesion (HSIL), high-grade intra-epithelial lesion (HSIL), cervical cancer (CC), and clinicopathological features of CC.

Methods: Published studies with qualitative methylation data were initially searched from PubMed, Web of Science, EMBASE, and China National Knowledge Infrastructure databases (up to March 2018). Then, quantitative methylation datasets, retrieved from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, were pooled to validate the results of published studies.

Results: In a meta-analysis of 37 published studies, DAPK1 promoter hypermethylation progressively increased the risk of LSIL by 2.41-fold (P = 0.012), HSIL by 7.62-fold (P < 0.001), and CC by 23.17-fold (P < 0.001). Summary receiver operating characteristic curves suggested a potential diagnostic value of DAPK1 promoter hypermethylation in CC, with a large area-under-the-curve of 0.83, a high specificity of 97%, and a moderate sensitivity of 59%. There were significant impacts of DAPK1 promoter hypermethylation on histological type (odds ratio (OR) = 3.53, P < 0.001) and FIGO stage of CC (OR = 2.15, P = 0.003). Then, a pooled analysis of nine TCGA and GEO datasets, covering 13 CPG sites within DAPK1 promoter, identified eight CC-associated sites, six sites with diagnostic values for CC (pooled specificities: 74–90%; pooled sensitivities: 70–81%), nine loci associated with the histological type of CC, and all 13 loci with down-regulated effects on DAPK1 mRNA expression.

Conclusion: The meta-analysis suggests that DAPK1 promoter hypermethylation is significantly associated with the disease severity of cervical neoplasia. DAPK1 methylation detection exhibits a promising ability to discriminate CC from cancer-free controls.

Integrative genomic analysis of adult mixed phenotype acute leukemia delineates lineage associated molecular subtypes

Mixed phenotype acute leukemia (MPAL) is a rare subtype of acute leukemia characterized by leukemic blasts presenting myeloid and lymphoid markers. Here we report data from integrated genomic analysis on 31 MPAL samples and compare molecular profiling with that from acute myeloid leukemia (AML), B cell acute lymphoblastic leukemia (B-ALL), and T cell acute lymphoblastic leukemia (T-ALL). Consistent with the mixed immunophenotype, both AML-type and ALL-type mutations are detected in MPAL. Myeloid-B and myeloid-T MPAL show distinct mutation and methylation signatures that are associated with differences in lineage-commitment gene expressions. Genome-wide methylation comparison among MPAL, AML, B-ALL, and T-ALL sub-classifies MPAL into AML-type and ALL-type MPAL, which is associated with better clinical response when lineage-matched therapy is given. These results elucidate the genetic and epigenetic heterogeneity of MPAL and its genetic distinction from AML, B-ALL, and T-ALL and further provide proof of concept for a molecularly guided precision therapy approach in MPAL.

Mixed phenotype acute leukemia (MPAL) is a rare leukemia that presents both myeloid and lymphoid markers on blasts. Here the authors perform genomic analysis to show MPAL involves genetic and epigenetic heterogeneity and is genetically distinct from AML, B-ALL, and T-ALL.

New variable selection strategy for analysis of high-dimensional DNA methylation data

In genetic association studies, regularization methods are often used due to their computational efficiency for analysis of high-dimensional genomic data. DNA methylation data generated from Infinium HumanMethylation450 BeadChip Kit have a group structure where an individual gene consists of multiple Cytosine-phosphate-Guanine (CpG) sites. Consequently, group-based regularization can precisely detect outcome-related CpG sites. Representative examples are sparse group lasso (SGL) and network-based regularization. The former is powerful when most of the CpG sites within the same gene are associated with a phenotype outcome. In contrast, the latter is preferred when only a few of the CpG sites within the same gene are related to the outcome. In this paper, we propose new variable selection strategy based on a selection probability that measures selection frequency of individual variables selected by both SGL and network-based regularization. In extensive simulation study, we demonstrated that the proposed strategy can show relatively outstanding selection performance under any situation, compared with both SGL and network-based regularization. Also, we applied the proposed strategy to identify differentially methylated CpG sites and their corresponding genes from ovarian cancer data.

Models of epigenetic age capture patterns of DNA methylation in glioma associated with molecular subtype, survival, and recurrence

Background

Models of epigenetic aging (epigenetic clocks) have been implicated as potentially useful markers for cancer risk and prognosis. Using 2 previously published methods for modeling epigenetic age, Horvath's clock and epiTOC, we investigated epigenetic aging patterns related to World Health Organization grade and molecular subtype as well as associations of epigenetic aging with glioma survival and recurrence.

Methods

Epigenetic ages were calculated using Horvath's clock and epiTOC on 516 lower-grade glioma and 141 glioblastoma cases along with 136 nontumor (normal) brain samples. Associations of tumor epigenetic age with patient chronological age at diagnosis were assessed with correlation and linear regression, and associations were validated in an independent cohort of 203 gliomas. Contribution of epigenetic age to survival prediction was assessed using Cox proportional hazards modeling. Sixty-three samples from 18 patients with primary-recurrent glioma pairs were also analyzed and epigenetic age difference and rate of epigenetic aging of primary-recurrent tumors were correlated to time to recurrence.

Results

Epigenetic ages of gliomas were near-universally accelerated using both Horvath's clock and epiTOC compared with normal tissue. The 2 independent models of epigenetic aging were highly associated with each other and exhibited distinct aging patterns reflective of molecular subtype. EpiTOC was found to be a significant independent predictor of survival. Epigenetic aging of gliomas between primary and recurrent tumors was found to be highly variable and not significantly associated with time to recurrence.

Conclusions

We demonstrate that epigenetic aging reflects coherent modifications of the epigenome and can potentially provide additional prognostic power for gliomas.

Impaired DNA demethylation of C/EBP sites causes premature aging

Here, Schäfer et al. investigated whether DNA methylation alterations are involved in aging. Using knockout mice for adapter proteins for site-specific demethylation by TET methylcytosine dioxygenases Gadd45a and Ing1, they show that enhancer methylation can affect aging and imply that C/EBP proteins play an unexpected role in this process.

Changes in DNA methylation are among the best-documented epigenetic alterations accompanying organismal aging. However, whether and how altered DNA methylation is causally involved in aging have remained elusive. GADD45α (growth arrest and DNA damage protein 45A) and ING1 (inhibitor of growth family member 1) are adapter proteins for site-specific demethylation by TET (ten-eleven translocation) methylcytosine dioxygenases. Here we show that Gadd45a/Ing1 double-knockout mice display segmental progeria and phenocopy impaired energy homeostasis and lipodystrophy characteristic of Cebp (CCAAT/enhancer-binding protein) mutants. Correspondingly, GADD45α occupies C/EBPβ/δ-dependent superenhancers and, cooperatively with ING1, promotes local DNA demethylation via long-range chromatin loops to permit C/EBPβ recruitment. The results indicate that enhancer methylation can affect aging and imply that C/EBP proteins play an unexpected role in this process. Our study suggests a causal nexus between DNA demethylation, metabolism, and organismal aging.

Distinct chromatin signatures of DNA hypomethylation in aging and cancer

Cancer is an aging‐associated disease, but the underlying molecular links between these processes are still largely unknown. Gene promoters that become hypermethylated in aging and cancer share a common chromatin signature in ES cells. In addition, there is also global DNA hypomethylation in both processes. However, the similarity of the regions where this loss of DNA methylation occurs is currently not well characterized, and it is unknown if such regions also share a common chromatin signature in aging and cancer. To address this issue, we analyzed TCGA DNA methylation data from a total of 2,311 samples, including control and cancer cases from patients with breast, kidney, thyroid, skin, brain, and lung tumors and healthy blood, and integrated the results with histone, chromatin state, and transcription factor binding site data from the NIH Roadmap Epigenomics and ENCODE projects. We identified 98,857 CpG sites differentially methylated in aging and 286,746 in cancer. Hyper‐ and hypomethylated changes in both processes each had a similar genomic distribution across tissues and displayed tissue‐independent alterations. The identified hypermethylated regions in aging and cancer shared a similar bivalent chromatin signature. In contrast, hypomethylated DNA sequences occurred in very different chromatin contexts. DNA hypomethylated sequences were enriched at genomic regions marked with the activating histone posttranslational modification H3K4me1 in aging, while in cancer, loss of DNA methylation was primarily associated with the repressive H3K9me3 mark. Our results suggest that the role of DNA methylation as a molecular link between aging and cancer is more complex than previously thought.

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.

Robust joint score tests in the application of DNA methylation data analysis

Background

Recently differential variability has been showed to be valuable in evaluating the association of DNA methylation to the risks of complex human diseases. The statistical tests based on both differential methylation level and differential variability can be more powerful than those based only on differential methylation level. Anh and Wang (2013) proposed a joint score test (AW) to simultaneously detect for differential methylation and differential variability. However, AW’s method seems to be quite conservative and has not been fully compared with existing joint tests.

Results

We proposed three improved joint score tests, namely iAW.Lev, iAW.BF, and iAW.TM, and have made extensive comparisons with the joint likelihood ratio test (jointLRT), the Kolmogorov-Smirnov (KS) test, and the AW test. Systematic simulation studies showed that: 1) the three improved tests performed better (i.e., having larger power, while keeping nominal Type I error rates) than the other three tests for data with outliers and having different variances between cases and controls; 2) for data from normal distributions, the three improved tests had slightly lower power than jointLRT and AW. The analyses of two Illumina HumanMethylation27 data sets GSE37020 and GSE20080 and one Illumina Infinium MethylationEPIC data set GSE107080 demonstrated that three improved tests had higher true validation rates than those from jointLRT, KS, and AW.

Conclusions

The three proposed joint score tests are robust against the violation of normality assumption and presence of outlying observations in comparison with other three existing tests. Among the three proposed tests, iAW.BF seems to be the most robust and effective one for all simulated scenarios and also in real data analyses.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2185-3) contains supplementary material, which is available to authorized users.

DNA Methylation Patterns in Normal Tissue Correlate more Strongly with Breast Cancer Status than Copy-Number Variants

Normal tissue at risk of neoplastic transformation is characterized by somatic mutations, copy-number variation and DNA methylation changes. It is unclear however, which type of alteration may be more informative of cancer risk. We analyzed genome-wide DNA methylation and copy-number calls from the same DNA assay in a cohort of healthy breast samples and age-matched normal samples collected adjacent to breast cancer. Using statistical methods to adjust for cell type heterogeneity, we show that DNA methylation changes can discriminate normal-adjacent from normal samples better than somatic copy-number variants. We validate this important finding in an independent dataset. These results suggest that DNA methylation alterations in the normal cell of origin may offer better cancer risk prediction and early detection markers than copy-number changes.