Age-related DNA Methylation Research Articles

Targeting the hypothalamus for modeling age-related DNA methylation and developing OXT-GnRH combinational therapy against Alzheimer’s disease-like pathologies in male mouse model

The hypothalamus plays an important role in aging, but it remains unclear regarding the underlying epigenetics and whether this hypothalamic basis can help address aging-related diseases. Here, by comparing mouse hypothalamus with two other limbic system components, we show that the hypothalamus is characterized by distinctively high-level DNA methylation during young age and by the distinct dynamics of DNA methylation and demethylation when approaching middle age. On the other hand, age-related DNA methylation in these limbic system components commonly and sensitively applies to genes in hypothalamic regulatory pathways, notably oxytocin (OXT) and gonadotropin-releasing hormone (GnRH) pathways. Middle age is associated with transcriptional declines of genes which encode OXT, GnRH and signaling components, which similarly occur in an Alzheimer’s disease (AD)-like model. Therapeutically, OXT-GnRH combination is substantially more effective than individual peptides in treating AD-like disorders in male 5×FAD model. In conclusion, the hypothalamus is important for modeling age-related DNA methylation and developing hypothalamic strategies to combat AD.

Systematic Review of Associations between Anxiety, Depression, and Functional/Biological aging among Cancer Survivors.

Evidence suggests a mind-body component to aging, through which psychological distress from anxiety and depression drives molecular changes that promote early decline (ie, accelerated aging). Cancer survivors experience particularly high rates of anxiety and depression. Some survivors also have accelerated aging, though the relationships between anxiety/depression and aging are not clear. A synthesis of evidence is needed to understand the state of the science and impending priorities. PubMed, Embase, CINAHL, Web of Science, and PsycNet databases were searched for studies that measured associations between depression, anxiety, and non-chronological aging in cancer survivors (2012 to 2022). Data were methodologically evaluated. Survivorship studies were included if they were peer-reviewed, published in English from 2012-2022, and measured associations between anxiety/depression and aging. 51 studies were included. Just over half were cross-sectional (53%). Foci included functional (n = 35, 69%) and biological (n = 16, 31%). Functional aging measures included frailty, sarcopenia, geriatric assessment, and cognition. Biological aging measures included telomere length, telomerase, age-related inflammatory blood-based biomarkers, renal insufficiency, anemia, and DNA methylation. 223 associations were tested. Associations between anxiety, depression and aging were generally positive, though with varying strengths. Most compelling were associations between functional aging-depression. There were concerns for selection and measurement biases. Findings suggest positive associations between anxiety, depression and aging among cancer survivors. Future work is needed to clarify temporality, develop a consensus on the operationalization of aging, and diversify cohorts.

Skin Rejuvenation by Modulation of DNA Methylation.

Skin aging is driven by a complex set of cellular pathways. Among these, epigenetic mechanisms have garnered particular attention, because of their sensitivity to environmental and lifestyle factors. DNA methylation represents the longest known and best understood epigenetic mechanism. We explain how DNA methylation might function as an interface between the environment and the genome of human skin. Exposures to different environmental factors and lifestyles are known to modulate age-related methylation patterns, as illustrated by their effect on DNA methylation clocks. Human skin provides a particularly well-suited tissue for understanding age-related methylation changes and it has been shown recently that modulation of DNA methylation can induce skin rejuvenation. We explain how the use of mildly demethylating agents can be safeguarded to ensure the specific removal of age-related DNA methylation changes. We also identify important areas of future research, leading to a deeper understanding of the mechanisms that drive epigenetic aging and to the development of further refined intervention strategies.

DNA methylation correlates of chronological age in diverse human tissue types

BackgroundWhile the association of chronological age with DNA methylation (DNAm) in whole blood has been extensively studied, the tissue-specificity of age-related DNAm changes remains an active area of research. Studies investigating the association of age with DNAm in tissues such as brain, skin, immune cells, fat, and liver have identified tissue-specific and non-specific effects, thus, motivating additional studies of diverse human tissue and cell types.ResultsHere, we performed an epigenome-wide association study, leveraging DNAm data (Illumina EPIC array) from 961 tissue samples representing 9 tissue types (breast, lung, colon, ovary, prostate, skeletal muscle, testis, whole blood, and kidney) from the Genotype-Tissue Expression (GTEx) project. We identified age-associated CpG sites (false discovery rate < 0.05) in 8 tissues (all except skeletal muscle, n = 47). This included 162,002 unique hypermethylated and 90,626 hypomethylated CpG sites across all tissue types, with 130,137 (80%) hypermethylated CpGs and 74,703 (82%) hypomethylated CpG sites observed in a single tissue type. While the majority of age-associated CpG sites appeared tissue-specific, the patterns of enrichment among genomic features, such as chromatin states and CpG islands, were similar across most tissues, suggesting common mechanisms underlying cellular aging. Consistent with previous findings, we observed that hypermethylated CpG sites are enriched in regions with repressed polycomb signatures and CpG islands, while hypomethylated CpG sites preferentially occurred in non-CpG islands and enhancers. To gain insights into the functional effects of age-related DNAm changes, we assessed the correlation between DNAm and local gene expression changes to identify age-related expression quantitative trait methylation (age-eQTMs). We identified several age-eQTMs present in multiple tissue-types, including in the CDKN2A, HENMT1, and VCWE regions.ConclusionOverall, our findings will aid future efforts to develop biomarkers of aging and understand mechanisms of aging in diverse human tissue types.

Unveiling the molecular landscape of cognitive aging: insights from polygenic risk scores, DNA methylation, and gene expression

BackgroundAging represents a significant risk factor for the occurrence of cerebral small vessel disease, associated with white matter (WM) lesions, and to age-related cognitive alterations, though the precise mechanisms remain largely unknown. This study aimed to investigate the impact of polygenic risk scores (PRS) for WM integrity, together with age-related DNA methylation, and gene expression alterations, on cognitive aging in a cross-sectional healthy aging cohort. The PRSs were calculated using genome-wide association study (GWAS) summary statistics for magnetic resonance imaging (MRI) markers of WM integrity, including WM hyperintensities, fractional anisotropy (FA), and mean diffusivity (MD). These scores were utilized to predict age-related cognitive changes and evaluate their correlation with structural brain changes, which distinguish individuals with higher and lower cognitive scores. To reduce the dimensionality of the data and identify age-related DNA methylation and transcriptomic alterations, Sparse Partial Least Squares-Discriminant Analysis (sPLS-DA) was used. Subsequently, a canonical correlation algorithm was used to integrate the three types of omics data (PRS, DNA methylation, and gene expression data) and identify an individual “omics” signature that distinguishes subjects with varying cognitive profiles.ResultsWe found a positive association between MD-PRS and long-term memory, as well as a correlation between MD-PRS and structural brain changes, effectively discriminating between individuals with lower and higher memory scores. Furthermore, we observed an enrichment of polygenic signals in genes related to both vascular and non-vascular factors. Age-related alterations in DNA methylation and gene expression indicated dysregulation of critical molecular features and signaling pathways involved in aging and lifespan regulation. The integration of multi-omics data underscored the involvement of synaptic dysfunction, axonal degeneration, microtubule organization, and glycosylation in the process of cognitive aging.ConclusionsThese findings provide valuable insights into the biological mechanisms underlying the association between WM coherence and cognitive aging. Additionally, they highlight how age-associated DNA methylation and gene expression changes contribute to cognitive aging.

Epigenetics in Alzheimer's Disease: A Critical Overview.

Epigenetic modifications have been implicated in a number of complex diseases as well as being a hallmark of organismal aging. Several reports have indicated an involvement of these changes in Alzheimer's disease (AD) risk and progression, most likely contributing to the dysregulation of AD-related gene expression measured by DNA methylation studies. Given that DNA methylation is tissue-specific and that AD is a brain disorder, the limitation of these studies is the ability to identify clinically useful biomarkers in a proxy tissue, reflective of the tissue of interest, that would be less invasive, more cost-effective, and easily obtainable. The age-related DNA methylation changes have also been used to develop different generations of epigenetic clocks devoted to measuring the aging in different tissues that sometimes suggests an age acceleration in AD patients. This review critically discusses epigenetic changes and aging measures as potential biomarkers for AD detection, prognosis, and progression. Given that epigenetic alterations are chemically reversible, treatments aiming at reversing these modifications will be also discussed as promising therapeutic strategies for AD.

Reliable detection of stochastic epigenetic mutations and associations with cardiovascular aging.

Stochastic epigenetic mutations (SEMs) have been proposed as novel aging biomarkers to capture heterogeneity in age-related DNA methylation changes. SEMs are defined as outlier methylation patterns at cytosine-guanine dinucleotide sites, categorized as hypermethylated (hyperSEM) or hypomethylated (hypoSEM) relative to a reference. Because SEMs are defined by their outlier status, it is critical to differentiate extreme values due to technical noise or data artifacts from those due to real biology. Using technical replicate data, we found SEM detection is not reliable: across 3 datasets, 24 to 39% of hypoSEM and 46 to 67% of hyperSEM are not shared between replicates. We identified factors influencing SEM reliability-including blood cell type composition, probe beta-value statistics, genomic location, and presence of SNPs. We used these factors in a training dataset to build a machine learning-based filter that removes unreliable SEMs, and found this filter enhances reliability in two independent validation datasets. We assessed associations between SEM loads and aging phenotypes in the Framingham Heart Study and discovered that associations with aging outcomes were in large part driven by hypoSEMs at baseline methylated probes and hyperSEMs at baseline unmethylated probes, which are the same subsets that demonstrate highest technical reliability. These aging associations were preserved after filtering out unreliable SEMs and were enhanced after adjusting for blood cell composition. Finally, we utilized these insights to formulate best practices for SEM detection and introduce a novel R package, SEMdetectR, which uses parallel programming for efficient SEM detection with comprehensive options for detection, filtering, and analysis.

DNA methylation clocks for estimating biological age in Chinese cohorts.

Epigenetic clocks are accurate predictors of human chronological age based on the analysis of DNA methylation (DNAm) at specific CpG sites. However, a systematic comparison between DNA methylation data and other omics datasets has not yet been performed. Moreover, available DNAm age predictors are based on datasets with limited ethnic representation. To address these knowledge gaps, we generated and analyzed DNA methylation datasets from two independent Chinese cohorts, revealing age-related DNAm changes. Additionally, a DNA methylation aging clock (iCAS-DNAmAge) and a group of DNAm-based multi-modal clocks for Chinese individuals were developed, with most of them demonstrating strong predictive capabilities for chronological age. The clocks were further employed to predict factors influencing aging rates. The DNAm aging clock, derived from multi-modal aging features (compositeAge-DNAmAge), exhibited a close association with multi-omics changes, lifestyles, and disease status, underscoring its robust potential for precise biological age assessment. Our findings offer novel insights into the regulatory mechanism of age-related DNAm changes and extend the application of the DNAm clock for measuring biological age and aging pace, providing the basis for evaluating aging intervention strategies.

Causality-enriched epigenetic age uncouples damage and adaptation.

Machine learning models based on DNA methylation data can predict biological age but often lack causal insights. By harnessing large-scale genetic data through epigenome-wide Mendelian randomization, we identified CpG sites potentially causal for aging-related traits. Neither the existing epigenetic clocks nor age-related differential DNA methylation are enriched in these sites. These CpGs include sites that contribute to aging and protect against it, yet their combined contribution negatively affects age-related traits. We established a new framework to introduce causal information into epigenetic clocks, resulting in DamAge and AdaptAge-clocks that track detrimental and adaptive methylation changes, respectively. DamAge correlates with adverse outcomes, including mortality, while AdaptAge is associated with beneficial adaptations. These causality-enriched clocks exhibit sensitivity to short-term interventions. Our findings provide a detailed landscape of CpG sites with putative causal links to lifespan and healthspan, facilitating the development of aging biomarkers, assessing interventions, and studying reversibility of age-associated changes.

TET2-Mediated Dysregulation of Heterochromatin in Age-Related Clonal Hematopoiesis

Aging is one of the major negative factors of normal hematopoiesis, characterized by a decline in the self-renewal capabilities of hematopoietic stem and progenitor cells (HSPCs), alongside a myeloid lineage bias, thereby sabotaging the immune system and increasing the risk of malignant transformation. Epigenetic deregulation is a hallmark feature representative of aging and significantly contributes to age-related dysfunction in multiple systems. DNA methylation drifting is commonly observed during aging, especially within the partially methylated domains (PMDs). PMDs are intriguing heterochromatin regions featured by their late-replicating, lamina-associated, and B-compartment localized properties in HiC analysis. While heterochromatin is generally considered devoid of genes, it nonetheless plays a pivotal role in maintaining genomic stability. However, the link between age-related DNA methylation loss in PMDs and heterochromatin dysfunction remains elusive. In this study, we juxtapose the influence of aging on both wild-type (WT) and Tet2 knockout (KO) HSPCs. Tet2 depletion was found to counteract the functional deterioration typically associated with aging by preserving robust self-renewal and repopulation capacities in aging HSPCs. This resistance to functional decay may account for the age-related clonal hematopoiesis observed in Tet2KO HSPCs. At a molecular level, we identified distinct epigenetic regulatory mechanisms mediated by Dnmt3a and Tet2 at heterochromatin. These mechanisms are associated with alterations in 3D genome architecture during HSPC aging. Age-related dysregulation of heterochromatin leads to the upregulation of endogenous retroviruses (ERVs), which subsequently activate intracellular innate immune response and contribute to the functional decline of aging HSPCs. The application of reverse transcriptase inhibitors was shown to suppress ERV production and interferon-stimulated genes (ISGs) expression, thereby ameliorating age-related defects in aged HSPCs. Our findings provide compelling evidence supporting the intricate interplay between DNMT and TET in regulating DNA (de)methylation equilibrium in heterochromatin and euchromatin during stem cell aging. Moreover, our study offers critical insights into the mechanisms underlying age-related heterochromatin dysfunction, which contributes to the functional deterioration of HSPCs during aging.

The inactive X chromosome accumulates widespread epigenetic variability with age

BackgroundLoss of epigenetic control is a hallmark of aging. Among the most prominent roles of epigenetic mechanisms is the inactivation of one of two copies of the X chromosome in females through DNA methylation. Hence, age-related disruption of X-chromosome inactivation (XCI) may contribute to the aging process in women.MethodsWe analyzed 9,777 CpGs on the X chromosome in whole blood samples from 2343 females and 1688 males (Illumina 450k methylation array) and replicated findings in duplicate using one whole blood and one purified monocyte data set (in total, 991/924 females/males). We used double generalized linear models to detect age-related differentially methylated CpGs (aDMCs), whose mean methylation level differs with age, and age-related variably methylated CpGs (aVMCs), whose methylation level becomes more variable with age.ResultsIn females, aDMCs were relatively uncommon (n = 33) and preferentially occurred in regions known to escape XCI. In contrast, many CpGs (n = 987) were found to display an increased variance with age (aVMCs). Of note, the replication rate of aVMCs was also high in purified monocytes (94%), indicating an independence of cell composition. aVMCs accumulated in CpG islands and regions subject to XCI suggesting that they stemmed from the inactive X. In males, carrying an active copy of the X chromosome only, aDMCs (n = 316) were primarily driven by cell composition, while aVMCs replicated well (95%) but were infrequent (n = 37).ConclusionsOur results imply that age-related DNA methylation differences at the inactive X chromosome are dominated by the accumulation of variability.

Time to relapse in chronic lymphocytic leukemia and DNA-methylation-based biological age

Chronic lymphocytic leukemia (CLL) is a mature B cell neoplasm with a predilection for older individuals. While previous studies have identified epigenetic signatures associated with CLL, whether age-related DNA methylation changes modulate CLL relapse remains elusive. In this study, we examined the association between epigenetic age acceleration and time to CLL relapse in a publicly available dataset. DNA methylation profiling of 35 CLL patients prior to initiating chemoimmunotherapy was performed using the Infinium HumanMethylation450 BeadChip. Four epigenetic age acceleration metrics (intrinsic epigenetic age acceleration [IEAA], extrinsic epigenetic age acceleration [EEAA], PhenoAge acceleration [PhenoAA], and GrimAge acceleration [GrimAA]) were estimated from blood DNA methylation levels. Linear, quantile, and logistic regression and receiver operating characteristic curve analyses were conducted to assess the association between each epigenetic age metric and time to CLL relapse. EEAA (p = 0.011) and PhenoAA (p = 0.046) were negatively and GrimAA (p = 0.040) was positively associated with time to CLL relapse. Simultaneous assessment of EEAA and GrimAA in male patients distinguished patients who relapsed early from patients who relapsed later (p = 0.039). No associations were observed with IEAA. These findings suggest epigenetic age acceleration prior to chemoimmunotherapy initiation is associated with time to CLL relapse. Our results provide novel insight into the association between age-related DNA methylation changes and CLL relapse and may serve has biomarkers for treatment relapse, and potentially, treatment selection.

Exercise is associated with younger methylome and transcriptome profiles in human skeletal muscle.

Exercise training prevents age-related decline in muscle function. Targeting epigenetic aging is a promising actionable mechanism and late-life exercise mitigates epigenetic aging in rodent muscle. Whether exercise training can decelerate, or reverse epigenetic aging in humans is unknown. Here, we performed a powerful meta-analysis of the methylome and transcriptome of an unprecedented number of human skeletal muscle samples (n = 3176). We show that: (1) individuals with higher baseline aerobic fitness have younger epigenetic and transcriptomic profiles, (2) exercise training leads to significant shifts of epigenetic and transcriptomic patterns toward a younger profile, and (3) muscle disuse "ages" the transcriptome. Higher fitness levels were associated with attenuated differential methylation and transcription during aging. Furthermore, both epigenetic and transcriptomic profiles shifted toward a younger state after exercise training interventions, while the transcriptome shifted toward an older state after forced muscle disuse. We demonstrate that exercise training targets many of the age-related transcripts and DNA methylation loci to maintain younger methylome and transcriptome profiles, specifically in genes related to muscle structure, metabolism, and mitochondrial function. Our comprehensive analysis will inform future studies aiming to identify the best combination of therapeutics and exercise regimes to optimize longevity.

Age-related methylation changes in the human sperm epigenome.

Advanced paternal age is associated with increased risks for reproductive and offspring medical problems. Accumulating evidence suggests age-related changes in the sperm epigenome as one underlying mechanism. Using reduced representation bisulfite sequencing on 73 sperm samples of males attending a fertility center, we identified 1,162 (74%) regions which were significantly (FDR-adjusted) hypomethylated and 403 regions (26%) being hypermethylated with age. There were no significant correlations with paternal BMI, semen quality, or ART outcome. The majority (1,152 of 1,565; 74%) of age-related differentially methylated regions (ageDMRs) were located within genic regions, including 1,002 genes with symbols. Hypomethylated ageDMRs were closer to transcription start sites than hypermethylated DMRs, half of which reside in gene-distal regions. In this and conceptually related genome-wide studies, so far 2,355 genes have been reported with significant sperm ageDMRs, however most (90%) of them in only one study. The 241 genes which have been replicated at least once showed significant functional enrichments in 41 biological processes associated with development and the nervous system and in 10 cellular components associated with synapses and neurons. This supports the hypothesis that paternal age effects on the sperm methylome affect offspring behaviour and neurodevelopment. It is interesting to note that sperm ageDMRs were not randomly distributed throughout the human genome; chromosome 19 showed a highly significant twofold enrichment with sperm ageDMRs. Although the high gene density and CpG content have been conserved, the orthologous marmoset chromosome 22 did not appear to exhibit an increased regulatory potential by age-related DNA methylation changes.

DNA methylation entropy as a measure of stem cell replication and aging

BackgroundEpigenetic marks are encoded by DNA methylation and accumulate errors as organisms age. This drift correlates with lifespan, but the biology of how this occurs is still unexplained. We analyze DNA methylation with age in mouse intestinal stem cells and compare them to nonstem cells.ResultsAge-related changes in DNA methylation are identical in stem and nonstem cells, affect most prominently CpG islands and correlate weakly with gene expression. Age-related DNA methylation entropy, measured by the Jensen-Shannon Distribution, affects up to 25% of the detectable CpG sites and is a better measure of aging than individual CpG methylation. We analyze this entropy as a function of age in seven other tissues (heart, kidney, skeletal muscle, lung, liver, spleen, and blood) and it correlates strikingly with tissue-specific stem cell division rates. Thus, DNA methylation drift and increased entropy with age are primarily caused by and are sensors for, stem cell replication in adult tissues.ConclusionsThese data have implications for the mechanisms of tissue-specific functional declines with aging and for the development of DNA-methylation-based biological clocks.

Is adiposity related to repeat measures of blood leukocyte DNA methylation across childhood and adolescence?

Epigenetic modifications such as DNA methylation may influence gene expression and phenotypes, including obesity in childhood. The directionality of this relationship is nevertheless unclear, and some evidence suggests that adiposity modifies the epigenome, rather than the other way around. In this pilot study, we utilize data from the Early Life Exposures in Mexico to Environmental Toxicants (ELEMENT) study to examine whether measures of adiposity in childhood and early adolescence are associated with repeated measures of blood leukocyte DNA methylation at LINE-1 repetitive elements and two genes implicated in growth and adiposity: H19 and HSD11B2. Longitudinal epigenetic data were generated from cord blood and blood from follow-up visits in early and late adolescence. We assessed interactions between age and measures of body mass index (BMI) at 5 years of age and weight, BMI and waist circumference in early adolescence to infer whether adiposity deflects age-related DNA methylation changes throughout childhood. Applying linear mixed-effects models, we found an inverse association between measures of childhood BMI (kg/m2 ) and early-teen weight (kg) with repeat measures of H19 DNA methylation. We did not observe any statistically significant associations (p-value <.05) between any anthropometric measures and DNA methylation at LINE-1 or HSD11B2. We did not demonstrate statistically significant evidence in support of deflection of age-related DNA methylation trajectories by adiposity-related measures (age by adiposity interaction term). Given the pilot nature of this study, the relationships between repeat measures of DNA methylation and adiposity-measures across childhood merit further exploration in larger study populations.

A single short reprogramming early in life initiates and propagates an epigenetically related mechanism improving fitness and promoting an increased healthy lifespan.

Recent advances in cell reprogramming showed that OSKM induction is able to improve cell physiology in vitro and in vivo. Here, we show that a single short reprogramming induction is sufficient to prevent musculoskeletal functions deterioration of mice, when applied in early life. In addition, in old age, treated mice have improved tissue structures in kidney, spleen, skin, and lung, with an increased lifespan of 15% associated with organ-specific differential age-related DNA methylation signatures rejuvenated by the treatment. Altogether, our results indicate that a single short reprogramming early in life might initiate and propagate an epigenetically related mechanism to promote a healthy lifespan.

Integrative Approaches of DNA Methylation Patterns According to Age, Sex and Longitudinal Changes.

In humans, age-related DNA methylation has been studied in blood, tissues, buccal swabs, and fibroblasts, and changes in DNA methylation patterns according to age and sex have been detected. To date, approximately 137,000 samples have been analyzed from 14,000 studies, and the information has been uploaded to the NCBI GEO database. A correlation between age and methylation level and longitudinal changes in methylation levels was revealed in both sexes. Here, 20 public datasets derived from whole blood were analyzed using the Illumina BeadChip. Batch effects with respect to the time differences were correlated. The overall change in the pattern was provided as the inverse of the coefficient of variation (COV). Of the 20 datasets, nine were from a longitudinal study. All data had age and sex as common variables. Comprehensive details of age-, sex-, and longitudinal change-based DNA methylation levels in the whole blood sample were elucidated in this study. ELOVL2 and FHL2 showed the maximum correlation between age and DNA methylation. The methylation patterns of genes related to mental health differed according to age. Age-correlated genes have been associated with malformations (anteverted nostril, craniofacial abnormalities, and depressed nasal bridge) and drug addiction (drug habituation and smoking). Based on 20 public DNA methylation datasets, methylation levels according to age and longitudinal changes by sex were identified and visualized using an integrated approach. The results highlight the molecular mechanisms underlying the association of sex and biological age with changes in DNA methylation, and the importance of optimal genomic information management.

Age-Related DNA Methylation in Normal Kidney Tissue Identifies Epigenetic Cancer Risk Susceptibility Loci in the ANKRD34B and ZIC1 Genes.

Both age-dependent and age-independent alteration of DNA methylation in human tissues are functionally associated with the development of many malignant and non-malignant human diseases. TCGA-KIRC data were biometrically analyzed to identify new loci with age-dependent DNA methylation that may contribute to tumor risk in normal kidney tissue. ANKRD34B and ZIC1 were evaluated as candidate genes by pyrosequencing of 539 tissues, including 239 normal autopsy, 157 histopathologically tumor-adjacent normal, and 143 paired tumor kidney samples. All candidate CpG loci demonstrated a strong correlation between relative methylation levels and age (R = 0.70–0.88, p < 2 × 10−16) and seven out of 10 loci were capable of predicting chronological age in normal kidney tissues, explaining 84% of the variance (R = 0.92). Moreover, significantly increased age-independent methylation was found for 9 out of 10 CpG loci in tumor-adjacent tissues, compared to normal autopsy tissues (p = 0.001–0.028). Comparing tumor and paired tumor-adjacent tissues revealed two patient clusters showing hypermethylation, one cluster without significant changes in methylation, and a smaller cluster demonstrating hypomethylation in the tumors (p < 1 × 10−10). Taken together, our results show the presence of additional methylation risk factors besides age for renal cancer in normal kidney tissue. Concurrent tumor-specific hypermethylation suggests a subset of these loci are candidates for epigenetic renal cancer susceptibility.

Making sense of the ageing methylome.

Over time, the human DNA methylation landscape accrues substantial damage, which has been associated with a broad range of age-related diseases, including cardiovascular disease and cancer. Various age-related DNA methylation changes have been described, including at the level of individual CpGs, such as differential and variable methylation, and at the level of the whole methylome, including entropy and correlation networks. Here, we review these changes in the ageing methylome as well as the statistical tools that can be used to quantify them. We detail the evidence linking DNA methylation to ageing phenotypes and the longevity strategies aimed at altering both DNA methylation patterns and machinery to extend healthspan and lifespan. Lastly, we discuss theories on the mechanistic causes of epigenetic ageing.