Age-associated Methylation Research Articles

Age-associated methylation change of TAP1 promoter in piglet

Diarrhea and edematous disease are two major causes of mortality in postweaning piglets. These conditions lead to huge economic losses in the swine industry. Escherichia coli F18 is the primary causative agent of these two diseases. Transported associated with antigen processing (TAP) plays an important role in the immune response and the TAP1 gene could be an effective anti-E. coli F18 molecular marker in pigs. The aim of this study was to determine the correlation between TAP1 gene promoter CpG island methylation status and mRNA expression in piglets. In this study, bisulfite sequencing PCR (BSP) was used to detect the methylation status of the TAP1 gene promoter CpG islands and fluorescence quantitative PCR was used to detect TAP1 expression in the jejunum of Sutai piglets from birth to weaning age. The fragment of the TAP1 gene promoter region under investigation has no mutation, has 13 putative transcription factor binding sites containing 19 CpG sites, and may be important for regulation of gene expression. With increasing age, the overall methylation levels decreased, while the TAP1 expression levels increased, indicating a negative correlation between TAP1 expression and promoter methylation levels. Variance analysis showed significant differences in the methylation status of CpG_4, CpG_13 and CpG_15 among the different age groups (P<0.05). Our data indicate that TAP1 expression is increased by demethylation of promoter CpG islands, with CpG_4, CpG_13 and CpG_15 implicated as the critical regulatory sites.

Polycomb repressive complex 2 epigenomic signature defines age-associated hypermethylation and gene expression changes

Although age-associated gene expression and methylation changes have been reported throughout the literature, the unifying epigenomic principles of aging remain poorly understood. Recent explosion in availability and resolution of functional/regulatory genome annotation data (epigenomic data), such as that provided by the ENCODE and Roadmap Epigenomics projects, provides an opportunity for the identification of epigenomic mechanisms potentially altered by age-associated differentially methylated regions (aDMRs) and regulatory signatures in the promoters of age-associated genes (aGENs). In this study we found that aDMRs and aGENs identified in multiple independent studies share a common Polycomb Repressive Complex 2 signature marked by EZH2, SUZ12, CTCF binding sites, repressive H3K27me3, and activating H3K4me1 histone modification marks, and a “poised promoter” chromatin state. This signature is depleted in RNA Polymerase II-associated transcription factor binding sites, activating H3K79me2, H3K36me3, H3K27ac marks, and an “active promoter” chromatin state. The PRC2 signature was shown to be generally stable across cell types. When considering the directionality of methylation changes, we found the PRC2 signature to be associated with aDMRs hypermethylated with age, while hypomethylated aDMRs were associated with enhancers. In contrast, aGENs were associated with the PRC2 signature independently of the directionality of gene expression changes. In this study we demonstrate that the PRC2 signature is the common epigenomic context of genomic regions associated with hypermethylation and gene expression changes in aging.

Acceleration of age-associated methylation patterns in HIV-1-infected adults.

Patients with treated HIV-1-infection experience earlier occurrence of aging-associated diseases, raising speculation that HIV-1-infection, or antiretroviral treatment, may accelerate aging. We recently described an age-related co-methylation module comprised of hundreds of CpGs; however, it is unknown whether aging and HIV-1-infection exert negative health effects through similar, or disparate, mechanisms. We investigated whether HIV-1-infection would induce age-associated methylation changes. We evaluated DNA methylation levels at >450,000 CpG sites in peripheral blood mononuclear cells (PBMC) of young (20-35) and older (36-56) adults in two separate groups of participants. Each age group for each data set consisted of 12 HIV-1-infected and 12 age-matched HIV-1-uninfected samples for a total of 96 samples. The effects of age and HIV-1 infection on methylation at each CpG revealed a strong correlation of 0.49, p<1 x10-200 and 0.47, p<1x10-200. Weighted gene correlation network analysis (WGCNA) identified 17 co-methylation modules; module 3 (ME3) was significantly correlated with age (cor=0.70) and HIV-1 status (cor=0.31). Older HIV-1+ individuals had a greater number of hypermethylated CpGs across ME3 (p=0.015). In a multivariate model, ME3 was significantly associated with age and HIV status (Data set 1: βage= 0.007088, p=2.08 x 10-9; βHIV= 0.099574, p=0.0011; Data set 2: βage= 0.008762, p=1.27x 10-5; βHIV= 0.128649, p= 0.0001). Using this model, we estimate that HIV-1 infection accelerates age-related methylation by approximately 13.7 years in data set 1 and 14.7 years in data set 2. The genes related to CpGs in ME3 are enriched for polycomb group target genes known to be involved in cell renewal and aging. The overlap between ME3 and an aging methylation module found in solid tissues is also highly significant (Fisher-exact p=5.6 x 10-6, odds ratio=1.91). These data demonstrate that HIV-1 infection is associated with methylation patterns that are similar to age-associated patterns and suggest that general aging and HIV-1 related aging work through some common cellular and molecular mechanisms. These results are an important first step for finding potential therapeutic targets and novel clinical approaches to mitigate the detrimental effects of both HIV-1-infection and aging.

An epigenetic map of age-associated autosomal loci in northern European families at high risk for the metabolic syndrome.

BackgroundThe prevalence of chronic diseases such as cancer, type 2 diabetes, metabolic syndrome (MetS), and cardiovascular disease increases with age in all populations. Epigenetic features are hypothesized to play important roles in the pathophysiology of age-associated diseases, but a map of these markers is lacking. We searched for genome-wide age-associated methylation signatures in peripheral blood of individuals at high risks for MetS by profiling 485,000 CpG sites in 192 individuals of Northern European ancestry using the Illumina HM450 array. Subjects (ages 6–85 years) were part of seven extended families, and 73% of adults and 32% of children were overweight or obese.ResultsWe found 22,122 genome-wide significant age-associated CpG sites (Pα=0.05 = 3.65 × 10−7 after correction for multiple testing) of which 14,155 are positively associated with age while 7,967 are negatively associated. By applying a positional density-based clustering algorithm, we generated a map of epigenetic ‘hot-spots’ of age-associated genomic segments, which include 290 age-associated differentially methylated CpG clusters (aDMCs), of which 207 are positively associated with age. Gene/pathway enrichment analyses were performed on these clusters using FatiGO. Genes localized to both the positively (n = 241) and negatively (n = 16) age-associated clusters are significantly enriched in specific KEGG pathways and GO terms. The most significantly enriched pathways are the hedgehog signaling pathway (adjusted P = 3.96 × 10−3) and maturity-onset diabetes of the young (MODY) (adjusted P = 6.26 × 10−3) in the positive aDMCs and type I diabetes mellitus (adjusted P = 3.69 × 10−7) in the negative aDMCs. We also identified several epigenetic loci whose age-associated change rates differ between subjects diagnosed with MetS and those without.ConclusionWe conclude that in a family cohort at high risk for MetS, age-associated epigenetic features enrich in biological pathways important for determining the fate of fat cells and for insulin production. We also observe that several genes known to be related to MetS show differential epigenetic response to age in individuals with and without MetS.Electronic supplementary materialThe online version of this article (doi:10.1186/s13148-015-0048-6) contains supplementary material, which is available to authorized users.

Age-related DNA methylation changes for forensic age-prediction.

There is no available method of age-prediction for biological samples. The accumulating evidences indicate that DNA methylation patterns change with age. Aging resembles a developmentally regulated process that is tightly controlled by specific epigenetic modifications and age-associated methylation changes exist in human genome. In this study, three age-related methylation fragments were isolated and identified in blood of 40 donors. Age-related methylation changes with each fragment was validated and replicated in a general population sample of 65 donors over a wide age range (11-72years). Methylation of these fragments is linearly correlated with age over a range of six decades (r = 0.80-0.88). Using average methylation of CpG sites of three fragments, a regression model that explained 95% of the variance in age was built and is able to predict an individual's age with great accuracy (R (2 )= 0.93). The predicted value is highly correlated with the observed age in the sample (r = 0.96) and has great accuracy of average 4years difference between predicted age and true age. This study implicates that DNA methylation can be an available biological marker of age-prediction. Further measurement of relevant markers in the genome could be a tool in routine screening to predict age of forensic biological samples.

Age-Associated Sperm DNA Methylation Alterations: Possible Implications in Offspring Disease Susceptibility

Recent evidence demonstrates a role for paternal aging on offspring disease susceptibility. It is well established that various neuropsychiatric disorders (schizophrenia, autism, etc.), trinucleotide expansion associated diseases (myotonic dystrophy, Huntington's, etc.) and even some forms of cancer have increased incidence in the offspring of older fathers. Despite strong epidemiological evidence that these alterations are more common in offspring sired by older fathers, in most cases the mechanisms that drive these processes are unclear. However, it is commonly believed that epigenetics, and specifically DNA methylation alterations, likely play a role. In this study we have investigated the impact of aging on DNA methylation in mature human sperm. Using a methylation array approach we evaluated changes to sperm DNA methylation patterns in 17 fertile donors by comparing the sperm methylome of 2 samples collected from each individual 9–19 years apart. With this design we have identified 139 regions that are significantly and consistently hypomethylated with age and 8 regions that are significantly hypermethylated with age. A representative subset of these alterations have been confirmed in an independent cohort. A total of 117 genes are associated with these regions of methylation alterations (promoter or gene body). Intriguingly, a portion of the age-related changes in sperm DNA methylation are located at genes previously associated with schizophrenia and bipolar disorder. While our data does not establish a causative relationship, it does raise the possibility that the age-associated methylation of the candidate genes that we observe in sperm might contribute to the increased incidence of neuropsychiatric and other disorders in the offspring of older males. However, further study is required to determine whether, and to what extent, a causative relationship exists.

Isolation and identification of age-related DNA methylation markers for forensic age-prediction.

Age-prediction is an important part of forensic science. There is no available method of individual age-prediction for general forensic biological samples at crime scenes. Accumulating evidence indicates that aging resembles a developmentally regulated process tightly controlled by specific age-associated methylation exists in human genome. This study isolated and identified eight gene fragments in which the degree of cytosine methylation is significantly correlated with age in blood of 40 donors. Furthermore, we validated two CpG sites of each gene fragment and replicated our results in a general population sample of 40 males and 25 females with a wide age-range (11-72 years). The methylation of these fragments is linear with age over a range of six decades (Fragment P1 (r=-0.64), P2 (r=-0.58), P3 (r=-0.79), R1 (r=0.82), R2 (r=0.63), R3 (r=0.59), R4 (r=0.63) and R5 (r=0.62)). Using average methylation of two CpG sites from each fragment, we built a regression model that explained 95% of the variance in age and is able to predict the age of an individual with great accuracy (R(2)=0.918). The predicted values are highly correlated with the observed age in the sample (r=0.91). This study implicates that DNA methylation will be an available biological marker of age-prediction. Furthermore, measurement of relevant sites in the genome could be a tool in routine forensic screening to predict age of biological samples.

Aging of blood can be tracked by DNA methylation changes at just three CpG sites

BackgroundHuman aging is associated with DNA methylation changes at specific sites in the genome. These epigenetic modifications may be used to track donor age for forensic analysis or to estimate biological age.ResultsWe perform a comprehensive analysis of methylation profiles to narrow down 102 age-related CpG sites in blood. We demonstrate that most of these age-associated methylation changes are reversed in induced pluripotent stem cells (iPSCs). Methylation levels at three age-related CpGs - located in the genes ITGA2B, ASPA and PDE4C - were subsequently analyzed by bisulfite pyrosequencing of 151 blood samples. This epigenetic aging signature facilitates age predictions with a mean absolute deviation from chronological age of less than 5 years. This precision is higher than age predictions based on telomere length. Variation of age predictions correlates moderately with clinical and lifestyle parameters supporting the notion that age-associated methylation changes are associated more with biological age than with chronological age. Furthermore, patients with acquired aplastic anemia or dyskeratosis congenita - two diseases associated with progressive bone marrow failure and severe telomere attrition - are predicted to be prematurely aged.ConclusionsOur epigenetic aging signature provides a simple biomarker to estimate the state of aging in blood. Age-associated DNA methylation changes are counteracted in iPSCs. On the other hand, over-estimation of chronological age in bone marrow failure syndromes is indicative for exhaustion of the hematopoietic cell pool. Thus, epigenetic changes upon aging seem to reflect biological aging of blood.

Splicing factor 3B1 hypomethylation is associated with altered SF3B1 transcript expression in older humans

Ageing in man is associated with changes to the splicing factor pool. A proportion of splicing factors are regulated during ageing by mechanisms involving the Ataxia Telangiectasia Mutated (ATM) gene, but the factors that determine the remaining proportion have yet to be identified.DNA methylation is known to be an important regulatory mechanism of gene expression. We assessed age-associated methylation and expression levels for 27 splicing factor genes, in peripheral blood samples from the InCHIANTI study. Examination of splicing patterns at specific loci was examined in a second cohort, the Exeter 10000 study.27/502 methylation probes in 17 different genes were associated with age. Most changes were not associated with transcript expression levels or splicing patterns, but hypomethylation of the SF3B1 promoter region was found to mediate 53% of the relationship between age and transcript expression at this locus (p=0.02).DNA methylation does not appear to play a major role in regulation of the splicing factors, but changes in SF3B1 expression may be attributable to promoter hypomethylation at this locus. SF3B1 encodes a critical component of the U2 snRNP; altered expression of this gene may therefore contribute to the loss of regulated mRNA splicing that occurs with age.

An integrative network algorithm identifies age-associated differential methylation interactome hotspots targeting stem-cell differentiation pathways

Epigenetic changes have been associated with ageing and cancer. Identifying and interpreting epigenetic changes associated with such phenotypes may benefit from integration with protein interactome models. We here develop and validate a novel integrative epigenome-interactome approach to identify differential methylation interactome hotspots associated with a phenotype of interest. We apply the algorithm to cancer and ageing, demonstrating the existence of hotspots associated with these phenotypes. Importantly, we discover tissue independent age-associated hotspots targeting stem-cell differentiation pathways, which we validate in independent DNA methylation data sets, encompassing over 1000 samples from different tissue types. We further show that these pathways would not have been discovered had we used a non-network based approach and that the use of the protein interaction network improves the overall robustness of the inference procedure. The proposed algorithm will be useful to any study seeking to identify interactome hotspots associated with common phenotypes.

Proliferation-Dependent Alterations of the DNA Methylation Landscape Underlie Hematopoietic Stem Cell Aging

The functional potential of hematopoietic stem cells (HSCs) declines during aging, and in doing so, significantly contributes to hematopoietic pathophysiology in the elderly. To explore the relationship between age-associated HSC decline and the epigenome, we examined global DNA methylation of HSCs during ontogeny in combination with functional analysis. Although the DNA methylome is generally stable during aging, site-specific alterations of DNA methylation occur at genomic regions associated with hematopoietic lineage potential and selectively target genes expressed in downstream progenitor and effector cells. We found that age-associated HSC decline, replicative limits, and DNA methylation are largely dependent on the proliferative history of HSCs, yet appear to be telomere-length independent. Physiological aging and experimentally enforced proliferation of HSCs both led to DNA hypermethylation of genes regulated by Polycomb Repressive Complex 2. Our results provide evidence that epigenomic alterations of the DNA methylation landscape contribute to the functional decline of HSCs during aging.

Specific age-associated DNA methylation changes in human dermal fibroblasts.

Epigenetic modifications of cytosine residues in the DNA play a critical role for cellular differentiation and potentially also for aging. In mesenchymal stromal cells (MSC) from human bone marrow we have previously demonstrated age-associated methylation changes at specific CpG-sites of developmental genes. In continuation of this work, we have now isolated human dermal fibroblasts from young (<23 years) and elderly donors (>60 years) for comparison of their DNA methylation profiles using the Infinium HumanMethylation27 assay. In contrast to MSC, fibroblasts could not be induced towards adipogenic, osteogenic and chondrogenic lineage and this is reflected by highly significant differences between the two cell types: 766 CpG sites were hyper-methylated and 752 CpG sites were hypo-methylated in fibroblasts in comparison to MSC. Strikingly, global DNA methylation profiles of fibroblasts from the same dermal region clustered closely together indicating that fibroblasts maintain positional memory even after in vitro culture. 75 CpG sites were more than 15% differentially methylated in fibroblasts upon aging. Very high hyper-methylation was observed in the aged group within the INK4A/ARF/INK4b locus and this was validated by pyrosequencing. Age-associated DNA methylation changes were related in fibroblasts and MSC but they were often regulated in opposite directions between the two cell types. In contrast, long-term culture associated changes were very consistent in fibroblasts and MSC. Epigenetic modifications at specific CpG sites support the notion that aging represents a coordinated developmental mechanism that seems to be regulated in a cell type specific manner.

Aging and Environmental Exposures Alter Tissue-Specific DNA Methylation Dependent upon CpG Island Context

Epigenetic control of gene transcription is critical for normal human development and cellular differentiation. While alterations of epigenetic marks such as DNA methylation have been linked to cancers and many other human diseases, interindividual epigenetic variations in normal tissues due to aging, environmental factors, or innate susceptibility are poorly characterized. The plasticity, tissue-specific nature, and variability of gene expression are related to epigenomic states that vary across individuals. Thus, population-based investigations are needed to further our understanding of the fundamental dynamics of normal individual epigenomes. We analyzed 217 non-pathologic human tissues from 10 anatomic sites at 1,413 autosomal CpG loci associated with 773 genes to investigate tissue-specific differences in DNA methylation and to discern how aging and exposures contribute to normal variation in methylation. Methylation profile classes derived from unsupervised modeling were significantly associated with age (P<0.0001) and were significant predictors of tissue origin (P<0.0001). In solid tissues (n = 119) we found striking, highly significant CpG island–dependent correlations between age and methylation; loci in CpG islands gained methylation with age, loci not in CpG islands lost methylation with age (P<0.001), and this pattern was consistent across tissues and in an analysis of blood-derived DNA. Our data clearly demonstrate age- and exposure-related differences in tissue-specific methylation and significant age-associated methylation patterns which are CpG island context-dependent. This work provides novel insight into the role of aging and the environment in susceptibility to diseases such as cancer and critically informs the field of epigenomics by providing evidence of epigenetic dysregulation by age-related methylation alterations. Collectively we reveal key issues to consider both in the construction of reference and disease-related epigenomes and in the interpretation of potentially pathologically important alterations.