DNA methylation aging clocks: challenges and recommendations

Age-related DNA methylation changes are sex-specific: a comprehensive assessment

The existence of a sex gap in human health and longevity has been widely documented. Autosomal DNA methylation differences between males and females have been reported, but so far few studies have investigated if DNA methylation is differently affected by aging in males and females. We performed a meta-analysis of 4 large whole blood datasets, comparing 4 aspects of epigenetic age-dependent remodeling between the two sexes: differential methylation, variability, epimutations and entropy. We reported that a large fraction (43%) of sex-associated probes undergoes age-associated DNA methylation changes, and that a limited number of probes show age-by-sex interaction. We experimentally validated 2 regions mapping in FIGN and PRR4 genes and showed sex-specific deviations of their methylation patterns in models of decelerated (centenarians) and accelerated (Down syndrome) aging. While we did not find sex differences in the age-associated increase in epimutations and entropy, we showed that the number of probes having an age-related increase in methylation variability is 15 times higher in males compared to females. Our results can offer new epigenetic tools to study the interaction between aging and sex and can pave the way to the identification of molecular triggers of sex differences in longevity and age-related diseases prevalence.

Promising biomarkers of human aging: In search of a multi-omics panel to understand the aging process from a multidimensional perspective

The aging process has been linked to the occurrence of chronic diseases and functional impairments, including cancer, sarcopenia, frailty, metabolic, cardiovascular, and neurodegenerative diseases. Nonetheless, aging is highly variable and heterogeneous and represents a challenge for its characterization. In this sense, intrinsic capacity (IC) stands as a novel perspective by the World Health Organization, which integrates the individual wellbeing, environment, and risk factors to understand aging. However, there is a lack of quantitative and qualitative attributes to define it objectively. Therefore, in this review we attempt to summarize the most relevant and promising biomarkers described in clinical studies at date over different molecular levels, including epigenomics, transcriptomics, proteomics, metabolomics, and the microbiome. To aid gerontologists, geriatricians, and biomedical researchers to understand the aging process through the IC. Aging biomarkers reflect the physiological state of individuals and the underlying mechanisms related to homeostatic changes throughout an individual lifespan; they demonstrated that aging could be measured independently of time (that may explain its heterogeneity) and to be helpful to predict age-related syndromes and mortality. In summary, we highlight the areas of opportunity and gaps of knowledge that must be addressed to fully integrate biomedical findings into clinically useful tools and interventions.

Mitochondrial metabolism and DNA methylation: a review of the interaction between two genomes

Mitochondria are controlled by the coordination of two genomes: the mitochondrial and the nuclear DNA. As such, variations in nuclear gene expression as a consequence of mutations and epigenetic modifications can affect mitochondrial functionality. Conversely, the opposite could also be true. However, the relationship between mitochondrial dysfunction and epigenetics, such as nuclear DNA methylation, remains largely unexplored. Mitochondria function as central metabolic hubs controlling some of the main substrates involved in nuclear DNA methylation, via the one carbon metabolism, the tricarboxylic acid cycle and the methionine pathway. Here, we review key findings and highlight new areas of focus, with the ultimate goal of getting one step closer to understanding the genomic effects of mitochondrial dysfunction on nuclear epigenetic landscapes.

The use of DNA methylation clock in aging research

One of the key characteristics of aging is a progressive loss of physiological integrity, which weakens bodily functions and increases the risk of death. A robust biomarker is important for the assessment of biological age, the rate of aging, and a person's health status. DNA methylation clocks, novel biomarkers of aging, are composed of a group of cytosine-phosphate-guanine dinucleotides, the DNA methylation status of which can be used to accurately measure subjective age. These clocks are considered accurate biomarkers of chronological age for humans and other vertebrates. Numerous studies have demonstrated these clocks to quantify the rate of biological aging and the effects of longevity and anti-aging interventions. In this review, we describe the purpose and use of DNA methylation clocks in aging research.

DNA methylation-based age estimation in pediatric healthy tissues and brain tumors

Several DNA methylation clocks have been developed to reflect chronological age of human tissues, but most clocks have been trained on adult samples. The rapid methylome changes in children and the role of epigenetics in pediatric tumors calls for tools accurately estimating methylation age in children. We aimed to evaluate seven methylation clocks in multiple tissues from healthy children to inform future studies on the optimal clock for pediatric cohorts, and analyzed the methylation age in brain tumors. We found that clocks trained on pediatric samples were the best in all tested tissues, highlighting the need for dedicated clocks. For blood samples, the Skin and blood clock had the best correlation with chronological age, while PedBE was the most accurate for saliva and buccal samples, and Horvath for brain tissue. Horvath methylation age was accelerated in pediatric brain tumors and the acceleration was subtype-specific for atypical teratoid rhabdoid tumor (ATRT), ependymoma, medulloblastoma and glioma. The subtypes with the highest acceleration corresponded to the worst prognostic categories in ATRT, ependymoma and glioma, whereas the relationship was reversed in medulloblastoma. This suggests that methylation age has potential as a prognostic biomarker in pediatric brain tumors and should be further explored.

Epigenetic regulation of neural lineage elaboration: Implications for therapeutic reprogramming

The vulnerability of the mammalian brain is mainly due to its limited ability to generate new neurons once fully matured. Direct conversion of non-neuronal cells to neurons opens up a new avenue for therapeutic intervention and has made great strides also for in vivo applications in the injured brain. These great achievements raise the issue of adequate identity and chromatin hallmarks of the induced neurons. This may be particularly important, as aberrant epigenetic settings may reveal their adverse effects only in certain brain activity states. Therefore, we review here the knowledge about epigenetic memory and partially resetting of chromatin hallmarks from other reprogramming fields, before moving to the knowledge in direct neuronal reprogramming, which is still limited. Most importantly, novel tools are available now to manipulate specific epigenetic marks at specific sites of the genome. Applying these will eventually allow erasing aberrant epigenetic memory and paving the way towards new therapeutic approaches for brain repair.

Association of Neighborhood Deprivation With Epigenetic Aging Using 4 Clock Metrics

IMPORTANCE

Neighborhood deprivation is associated with age-related disease, mortality, and reduced life expectancy. However, biological pathways underlying these associations are not well understood.

OBJECTIVE

To evaluate the association between neighborhood deprivation and epigenetic measures of age acceleration and genome-wide methylation.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study used data from the Sister Study, a prospective cohort study comprising 50 884 women living in the US and Puerto Rico aged 35 to 74 years at enrollment who had a sister with breast cancer but had not had breast cancer themselves. Cohort enrollment occurred between July 2003 and March 2009. Participants completed a computer-assisted telephone interview on demographic, socioeconomic, lifestyle, and residential factors and provided anthropometric measures and peripheral blood samples at a home examination. DNA methylation data obtained for 2630 non-Hispanic White women selected for a case-cohort study in 2014 were used in this cross-sectional analysis. DNA methylation was measured using the HumanMethylation450 BeadChips in whole blood samples collected at baseline. Data analysis for this study was performed from October 17, 2019, to August 27, 2020.

EXPOSURES

Each participants' primary address was linked to an established index of neighborhood deprivation.

MAIN OUTCOMES AND MEASURES

Epigenetic age was estimated using 4 epigenetic clocks (Horvath, Hannum, PhenoAge, and GrimAge). Age acceleration was determined using residuals from regressing chronologic age on each of the 4 epigenetic age metrics. Linear regression was used to estimate associations between neighborhood deprivation and epigenetic age acceleration as well as DNA methylation at individual cytosine-guanine sites across the genome.

RESULTS

Mean (SD) age of the 2630 participants was 56.9 (8.7) years. Those with the greatest (>75th percentile) vs least (≤25th percentile) neighborhood deprivation had higher epigenetic age acceleration estimated by Hannum (β = 0.23; 95% CI, 0.01-0.45), PhenoAge (β = 0.28; 95% CI, 0.06-.50), and GrimAge (β = 0.37; 95% CI, 0.12-0.62). Increasing US quartiles of neighborhood deprivation exhibited a trend with Hannum, PhenoAge, and GrimAge. For example, GrimAge showed a significant dose-response (P test for trend <.001) as follows: level 2 vs level 1 (β = 0.30; 95% CI, 0.17-0.42), level 3 vs level 1 (β = 0.35; 95% CI, 0.19-0.50), and level 4 vs level 1 (β = 0.37; 95% CI, 0.12-0.62). Neighborhood deprivation was found to be associated with 3 cytosine-phosphate-guanine sites, with 1 of these annotated to a known gene MAOB (P = 9.71 × 10-08).

CONCLUSIONS AND RELEVANCE

The findings of this study suggest that residing in a neighborhood with a higher deprivation index appears to be reflected by methylation-based markers of aging.

The proliferative history shapes the DNA methylome of B-cell tumors and predicts clinical outcome

We report a systematic analysis of the DNA methylation variability in 1,595 samples of normal cell subpopulations and 14 tumor subtypes spanning the entire human B-cell lineage. Differential methylation among tumor entities relates to differences in cellular origin and to de novo epigenetic alterations, which allowed us to build an accurate machine learning-based diagnostic algorithm. We identify extensive patient-specific methylation variability in silenced chromatin associated with the proliferative history of normal and neoplastic B cells. Mitotic activity generally leaves both hyper- and hypomethylation imprints, but some B-cell neoplasms preferentially gain or lose DNA methylation. Subsequently, we construct a DNA methylation-based mitotic clock called epiCMIT, whose lapse magnitude represents a strong independent prognostic variable in B-cell tumors and is associated with particular driver genetic alterations. Our findings reveal DNA methylation as a holistic tracer of B-cell tumor developmental history, with implications in the differential diagnosis and prediction of clinical outcome.

Nutrition in Cancer Therapy in the Elderly-An Epigenetic Connection?

The continuous increase in life expectancy results in a steady increase of cancer risk, which consequently increases the population of older adults with cancer. Older adults have their age-related nutritional needs and often suffer from comorbidities that may affect cancer therapy. They frequently are malnourished and present advanced-stage cancer. Therefore, this group of patients requires a special multidisciplinary approach to optimize their therapy and increase quality of life impaired by aging, cancer, and the side effects of therapy. Evaluation strategies, taking advantage of comprehensive geriatric assessment tools, including the comprehensive geriatric assessment (CGA), can help individualize treatment. As epigenetics, an emerging element of the regulation of gene expression, is involved in both aging and cancer and the epigenetic profile can be modulated by the diet, it seems to be a candidate to assist with planning a nutritional intervention in elderly populations with cancer. In this review, we present problems associated with the diet and nutrition in the elderly undergoing active cancer therapy and provide some information on epigenetic aspects of aging and cancer transformation. Nutritional interventions modulating the epigenetic profile, including caloric restriction and basal diet with modifications (elimination diet, supplementary diet) are discussed as the ways to improve the efficacy of cancer therapy and maintain the quality of life of older adults with cancer.

Epigenetic regulation of white adipose tissue in the onset of obesity and metabolic diseases

Obesity and metabolic syndrome are among the most prevalent health problems in developed countries. The impairment of adipose tissue (AT) function is partially responsible for the aetiology of these conditions. Epigenetics refers to several processes that add modifications to either the DNA or chromatin architectural proteins (histones). These processes can regulate gene expression, chromatin compaction and DNA repair. Epigenetics includes mechanisms by which the cell can adapt the cellular response to the environmental conditions. Here, we review the role of epigenetics in the onset of obesity and related metabolic disorders, with special focus on AT. We highlight the importance of nutrients and lifestyle in the regulation of the epigenetic mechanisms and how they can impact on AT plasticity and function in obesity and metabolic diseases. Thus, the epigenetic landscape emerges as a fine-tune regulator of the cellular responses according to the energetic, metabolic and physiological conditions of the cell. Alterations in metabolic pathways deregulated during obesity and metabolic syndrome could in part explain the disturbances in the epigenetic marks of the AT in these disorders. The understanding of how this epigenetic deregulation may affect AT biology and function could lead to new therapeutic approaches based on epigenetic strategies.

The Human Blood Transcriptome in a Large Population Cohort and Its Relation to Aging and Health

Background: The blood transcriptome is expected to provide a detailed picture of an organism's physiological state with potential outcomes for applications in medical diagnostics and molecular and epidemiological research. We here present the analysis of blood specimens of 3,388 adult individuals, together with phenotype characteristics such as disease history, medication status, lifestyle factors, and body mass index (BMI). The size and heterogeneity of this data challenges analytics in terms of dimension reduction, knowledge mining, feature extraction, and data integration.

Methods: Self-organizing maps (SOM)-machine learning was applied to study transcriptional states on a population-wide scale. This method permits a detailed description and visualization of the molecular heterogeneity of transcriptomes and of their association with different phenotypic features.

Results: The diversity of transcriptomes is described by personalized SOM-portraits, which specify the samples in terms of modules of co-expressed genes of different functional context. We identified two major blood transcriptome types where type 1 was found more in men, the elderly, and overweight people and it upregulated genes associated with inflammation and increased heme metabolism, while type 2 was predominantly found in women, younger, and normal weight participants and it was associated with activated immune responses, transcriptional, ribosomal, mitochondrial, and telomere-maintenance cell-functions. We find a striking overlap of signatures shared by multiple diseases, aging, and obesity driven by an underlying common pattern, which was associated with the immune response and the increase of inflammatory processes.

Conclusions: Machine learning applications for large and heterogeneous omics data provide a holistic view on the diversity of the human blood transcriptome. It provides a tool for comparative analyses of transcriptional signatures and of associated phenotypes in population studies and medical applications.

Blood-based epigenetic estimators of chronological age in human adults using DNA methylation data from the Illumina MethylationEPIC array

BACKGROUND

Epigenetic clocks have been recognized for their precise prediction of chronological age, age-related diseases, and all-cause mortality. Existing epigenetic clocks are based on CpGs from the Illumina HumanMethylation450 BeadChip (450 K) which has now been replaced by the latest platform, Illumina MethylationEPIC BeadChip (EPIC). Thus, it remains unclear to what extent EPIC contributes to increased precision and accuracy in the prediction of chronological age.

RESULTS

We developed three blood-based epigenetic clocks for human adults using EPIC-based DNA methylation (DNAm) data from the Norwegian Mother, Father and Child Cohort Study (MoBa) and the Gene Expression Omnibus (GEO) public repository: 1) an Adult Blood-based EPIC Clock (ABEC) trained on DNAm data from MoBa (n = 1592, age-span: 19 to 59 years), 2) an extended ABEC (eABEC) trained on DNAm data from MoBa and GEO (n = 2227, age-span: 18 to 88 years), and 3) a common ABEC (cABEC) trained on the same training set as eABEC but restricted to CpGs common to 450 K and EPIC. Our clocks showed high precision (Pearson correlation between chronological and epigenetic age (r) > 0.94) in independent cohorts, including GSE111165 (n = 15), GSE115278 (n = 108), GSE132203 (n = 795), and the Epigenetics in Pregnancy (EPIPREG) study of the STORK Groruddalen Cohort (n = 470). This high precision is unlikely due to the use of EPIC, but rather due to the large sample size of the training set.

CONCLUSIONS

Our ABECs predicted adults' chronological age precisely in independent cohorts. As EPIC is now the dominant platform for measuring DNAm, these clocks will be useful in further predictions of chronological age, age-related diseases, and mortality.

Hippocampal and cortical tissue-specific epigenetic clocks indicate an increased epigenetic age in a mouse model for Alzheimer's disease

Epigenetic clocks are based on age-associated changes in DNA methylation of CpG-sites, which can accurately measure chronological age in different species. Recently, several studies have indicated that the difference between chronological and epigenetic age, defined as the age acceleration, could reflect biological age indicating functional decline and age-associated diseases. In humans, an epigenetic clock associated Alzheimer's disease (AD) pathology with an acceleration of the epigenetic age. In this study, we developed and validated two mouse brain region-specific epigenetic clocks from the C57BL/6J hippocampus and cerebral cortex. Both clocks, which could successfully estimate chronological age, were further validated in a widely used mouse model for AD, the triple transgenic AD (3xTg-AD) mouse. We observed an epigenetic age acceleration indicating an increased biological age for the 3xTg-AD mice compared to non-pathological C57BL/6J mice, which was more pronounced in the cortex as compared to the hippocampus. Genomic region enrichment analysis revealed that age-dependent CpGs were enriched in genes related to developmental, aging-related, neuronal and neurodegenerative functions. Due to the limited access of human brain tissues, these epigenetic clocks specific for mouse cortex and hippocampus might be important in further unravelling the role of epigenetic mechanisms underlying AD pathology or brain aging in general.

Telomere-Related Disorders in Fetal Membranes Associated With Birth and Adverse Pregnancy Outcomes

Telomere disorders have been associated with aging-related diseases, including diabetes, vascular, and neurodegenerative diseases. The main consequence of altered telomere is the induction of the state of irreversible cell cycle arrest. Though several mechanisms responsible for the activation of senescence have been identified, it is still unclear how a cell is indeed induced to become irreversibly arrested. Most tissues in the body will experience senescence throughout its lifespan, but intrinsic and extrinsic stressors, such as chemicals, pollution, oxidative stress (OS), and inflammation accelerate the process. Pregnancy is a state of OS, as the higher metabolic demand of the growing fetus results in increased reactive oxygen species production. As a temporary organ in the mother, senescence in fetal membranes and placenta is expected and linked to term parturition (>37 weeks of gestation). However, a persistent, overwhelming, or premature OS affects placental antioxidant capacity, with consequent accumulation of OS causing damage to lipids, proteins, and DNA in the placental tissues. Therefore, senescence and its main inducer, telomere length (TL) reduction, have been associated with pregnancy complications, including stillbirth, preeclampsia, intrauterine growth restriction, and prematurity. Fetal membranes have a notable role in preterm births, which continue to be a major health issue associated with increased risk of neo and perinatal adverse outcomes and/or predisposition to disease in later life; however, the ability to mediate a delay in parturition during such cases is limited, because the pathophysiology of preterm births and physiological mechanisms of term births are not yet fully elucidated. Here, we review the current knowledge regarding the regulation of telomere-related senescence mechanisms in fetal membranes, highlighting the role of inflammation, methylation, and telomerase activity. Moreover, we present the evidences of TL reduction and senescence in gestational tissues by the time of term parturition. In conclusion, we verified that telomere regulation in fetal membranes requires a more complete understanding, in order to support the development of successful effective interventions of the molecular mechanisms that triggers parturition, including telomere signals, which may vary throughout placental tissues.

Epigenetic mutation load is weakly correlated with epigenetic age acceleration

DNA methylation (DNAm) age estimators are widely used to study aging-related conditions. It is not yet known whether DNAm age is associated with the accumulation of stochastic epigenetic mutations (SEMs), which reflect dysfunctions of the epigenetic maintenance system. Here, we defined epigenetic mutation load (EML) as the total number of SEMs per individual. We assessed associations between EML and DNAm age acceleration estimators using biweight midcorrelations in four population-based studies (total n = 6,388). EML was not only positively associated with chronological age (meta r = 0.171), but also with four measures of epigenetic age acceleration: the Horvath pan tissue clock, intrinsic epigenetic age acceleration, the Hannum clock, and the GrimAge clock (meta-analysis correlation ranging from r = 0.109 to 0.179). We further conducted pathway enrichment analyses for each participant's SEMs. The enrichment result demonstrated the stochasticity of epigenetic mutations, meanwhile implicated several pathways: signaling, neurogenesis, neurotransmitter, glucocorticoid, and circadian rhythm pathways may contribute to faster DNAm age acceleration. Finally, investigating genomic-region specific EML, we found that EMLs located within regions of transcriptional repression (TSS1500, TSS200, and 1stExon) were associated with faster age acceleration. Overall, our findings suggest a role for the accumulation of epigenetic mutations in the aging process.

Improvements and inter-laboratory implementation and optimization of blood-based single-locus age prediction models using DNA methylation of the ELOVL2 promoter

Several blood-based age prediction models have been developed using less than a dozen to more than a hundred DNA methylation biomarkers. Only one model (Z-P1) based on pyrosequencing has been developed using DNA methylation of a single locus located in the ELOVL2 promoter, which is considered as one of the best age-prediction biomarker. Although multi-locus models generally present better performances compared to the single-locus model, they require more DNA and present more inter-laboratory variations impacting the predictions. Here we developed 17,018 single-locus age prediction models based on DNA methylation of the ELOVL2 promoter from pooled data of four different studies (training set of 1,028 individuals aged from 0 and 91 years) using six different statistical approaches and testing every combination of the 7 CpGs, aiming to improve the prediction performances and reduce the effects of inter-laboratory variations. Compared to Z-P1 model, three statistical models with the optimal combinations of CpGs presented improved performances (MAD of 4.41–4.77 in the testing set of 385 individuals) and no age-dependent bias. In an independent testing set of 100 individuals (19–65 years), we showed that the prediction accuracy could be further improved by using different CpG combinations and increasing the number of technical replicates (MAD of 4.17).

"Epigenome-wide methylation profile of chronic kidney disease-derived arterial DNA uncovers novel pathways in disease-associated cardiovascular pathology."

Chronic kidney disease (CKD) related cardiovascular disease (CVD) is characterized by vascular remodelling with well-established structural and functional changes in the vascular wall such as arterial stiffness, matrix deposition, and calcification. These phenotypic changes resemble pathology seen in ageing, and are likely to be mediated by sustained alterations in gene expression, which may be caused by epigenetic changes such as tissue-specific DNA methylation. We aimed to investigate tissue specific changes in DNA methylation that occur in CKD-related CVD. Genome-wide DNA methylation changes were examined in bisulphite converted genomic DNA isolated from the vascular media of CKD and healthy arteries. Methylation-specific PCR was used to validate the array data, and the association between DNA methylation and gene and protein expression was examined. The DNA methylation age was compared to the chronological age in both cases and controls. Three hundred and nineteen differentially methylated regions (DMR) were identified spread across the genome. Pathway analysis revealed that DMRs associated with genes were involved in embryonic and vascular development, and signalling pathways such as TGFβ and FGF. Expression of top differentially methylated gene HOXA5 showed a significant negative correlation with DNA methylation. Interestingly, DNA methylation age and chronological age were highly correlated, but there was no evidence of accelerated age-related DNA methylation in the arteries of CKD patients. In conclusion, we demonstrated that differential DNA methylation in the arterial tissue of CKD patients represents a potential mediator of arterial pathology and may be used to uncover novel pathways in the genesis of CKD-associated complications.

Seagull: lasso, group lasso and sparse-group lasso regularization for linear regression models via proximal gradient descent

Background

Statistical analyses of biological problems in life sciences often lead to high-dimensional linear models. To solve the corresponding system of equations, penalization approaches are often the methods of choice. They are especially useful in case of multicollinearity, which appears if the number of explanatory variables exceeds the number of observations or for some biological reason. Then, the model goodness of fit is penalized by some suitable function of interest. Prominent examples are the lasso, group lasso and sparse-group lasso. Here, we offer a fast and numerically cheap implementation of these operators via proximal gradient descent. The grid search for the penalty parameter is realized by warm starts. The step size between consecutive iterations is determined with backtracking line search. Finally, seagull -the R package presented here- produces complete regularization paths.

Results

Publicly available high-dimensional methylation data are used to compare seagull to the established R package SGL. The results of both packages enabled a precise prediction of biological age from DNA methylation status. But even though the results of seagull and SGL were very similar (R² > 0.99), seagull computed the solution in a fraction of the time needed by SGL. Additionally, seagull enables the incorporation of weights for each penalized feature.

Conclusions

The following operators for linear regression models are available in seagull: lasso, group lasso, sparse-group lasso and Integrative LASSO with Penalty Factors (IPF-lasso). Thus, seagull is a convenient envelope of lasso variants.

Analysis of epigenetic aging in vivo and in vitro: Factors controlling the speed and direction

IMPACT STATEMENT

Aging is associated with DNA methylation (DNAm) changes. Recent advancement of the whole-genome DNAm analysis technology allowed scientists to develop DNAm-based age estimators. A majority of these estimators use DNAm data from a single tissue type such as blood. In 2013, a multi-tissue age estimator using DNAm pattern of 353 CpGs was developed by Steve Horvath. This estimator was named "epigenetic clock", and the improved version using DNAm pattern of 391 CpGs was developed in 2018. The estimated age by epigenetic clock is named DNAmAge. DNAmAge can be used as a biomarker of aging predicting the risk of age-associated diseases and mortality. Although the DNAm-based age estimators were developed, the mechanism of epigenetic aging is still enigmatic. The biological significance of epigenetic aging is not well understood, either. This minireview discusses the current understanding of the mechanism of epigenetic aging and the future direction of aging research.

Inhibition of Cdc42 activity extends lifespan and decreases circulating inflammatory cytokines in aged female C57BL/6 mice

Cdc42 is a small RhoGTPase regulating multiple functions in eukaryotic cells. The activity of Cdc42 is significantly elevated in several tissues of aged mice, while the Cdc42 gain‐of‐activity mouse model presents with a premature aging‐like phenotype and with decreased lifespan. These data suggest a causal connection between elevated activity of Cdc42, aging, and reduced lifespan. Here, we demonstrate that systemic treatment of aged (75‐week‐old) female C57BL/6 mice with a Cdc42 activity‐specific inhibitor (CASIN) for 4 consecutive days significantly extends average and maximum lifespan. Moreover, aged CASIN‐treated animals displayed a youthful level of the aging‐associated cytokines IL‐1β, IL‐1α, and INFγ in serum and a significantly younger epigenetic clock as based on DNA methylation levels in blood cells. Overall, our data show that systemic administration of CASIN to reduce Cdc42 activity in aged mice extends murine lifespan.

Targeted bisulfite sequencing for biomarker discovery

Cytosine methylation is one of the best studied epigenetic modifications. In mammals, DNA methylation patterns vary among cells and is mainly found in the CpG context. DNA methylation is involved in important processes during development and differentiation and its dysregulation can lead to or is associated with diseases, such as cancer, loss-of-imprinting syndromes and neurological disorders. It has been also shown that DNA methylation at the cellular, tissue and organism level varies with age. To overcome the costs of Whole-Genome Bisulfite Sequencing, the gold standard method to detect 5-methylcytosines at a single base resolution, DNA methylation arrays have been developed and extensively used. This method allows one to assess the status of a fraction of the CpG sites present in the genome of an organism. In order to combine the relatively low cost of Methylation Arrays and digital signals of bisulfite sequencing, we developed a Targeted Bisulfite Sequencing method that can be applied to biomarker discovery for virtually any phenotype. Here we describe a comprehensive step-by-step protocol to build a DNA methylation-based epigenetic clock.

An epigenetic clock for human skeletal muscle

BACKGROUND

Ageing is associated with DNA methylation changes in all human tissues, and epigenetic markers can estimate chronological age based on DNA methylation patterns across tissues. However, the construction of the original pan-tissue epigenetic clock did not include skeletal muscle samples and hence exhibited a strong deviation between DNA methylation and chronological age in this tissue.

METHODS

To address this, we developed a more accurate, muscle-specific epigenetic clock based on the genome-wide DNA methylation data of 682 skeletal muscle samples from 12 independent datasets (18-89 years old, 22% women, 99% Caucasian), all generated with Illumina HumanMethylation (HM) arrays (HM27, HM450, or HMEPIC). We also took advantage of the large number of samples to conduct an epigenome-wide association study of age-associated DNA methylation patterns in skeletal muscle.

RESULTS

The newly developed clock uses 200 cytosine-phosphate-guanine dinucleotides to estimate chronological age in skeletal muscle, 16 of which are in common with the 353 cytosine-phosphate-guanine dinucleotides of the pan-tissue clock. The muscle clock outperformed the pan-tissue clock, with a median error of only 4.6 years across datasets (vs. 13.1 years for the pan-tissue clock, P < 0.0001) and an average correlation of ρ = 0.62 between actual and predicted age across datasets (vs. ρ = 0.51 for the pan-tissue clock). Lastly, we identified 180 differentially methylated regions with age in skeletal muscle at a false discovery rate < 0.005. However, gene set enrichment analysis did not reveal any enrichment for gene ontologies.

CONCLUSIONS

We have developed a muscle-specific epigenetic clock that predicts age with better accuracy than the pan-tissue clock. We implemented the muscle clock in an r package called Muscle Epigenetic Age Test available on Bioconductor to estimate epigenetic age in skeletal muscle samples. This clock may prove valuable in assessing the impact of environmental factors, such as exercise and diet, on muscle-specific biological ageing processes.

Epigenetic measures of ageing predict the prevalence and incidence of leading causes of death and disease burden

BACKGROUND

Individuals of the same chronological age display different rates of biological ageing. A number of measures of biological age have been proposed which harness age-related changes in DNA methylation profiles. These measures include five 'epigenetic clocks' which provide an index of how much an individual's biological age differs from their chronological age at the time of measurement. The five clocks encompass methylation-based predictors of chronological age (HorvathAge, HannumAge), all-cause mortality (DNAm PhenoAge, DNAm GrimAge) and telomere length (DNAm Telomere Length). A sixth epigenetic measure of ageing differs from these clocks in that it acts as a speedometer providing a single time-point measurement of the pace of an individual's biological ageing. This measure of ageing is termed DunedinPoAm. In this study, we test the association between these six epigenetic measures of ageing and the prevalence and incidence of the leading causes of disease burden and mortality in high-income countries (n ≤ 9537, Generation Scotland: Scottish Family Health Study).

RESULTS

DNAm GrimAge predicted incidence of clinically diagnosed chronic obstructive pulmonary disease (COPD), type 2 diabetes and ischemic heart disease after 13 years of follow-up (hazard ratios = 2.22, 1.52 and 1.41, respectively). DunedinPoAm predicted the incidence of COPD and lung cancer (hazard ratios = 2.02 and 1.45, respectively). DNAm PhenoAge predicted incidence of type 2 diabetes (hazard ratio = 1.54). DNAm Telomere Length associated with the incidence of ischemic heart disease (hazard ratio = 0.80). DNAm GrimAge associated with all-cause mortality, the prevalence of COPD and spirometry measures at the study baseline. These associations were present after adjusting for possible confounding risk factors including alcohol consumption, body mass index, deprivation, education and tobacco smoking and surpassed stringent Bonferroni-corrected significance thresholds.

CONCLUSIONS

Our data suggest that epigenetic measures of ageing may have utility in clinical settings to complement gold-standard methods for disease assessment and management.

DNA sequence-dependent activity and base flipping mechanisms of DNMT1 regulate genome-wide DNA methylation

DNA methylation maintenance by DNMT1 is an essential process in mammals but molecular mechanisms connecting DNA methylation patterns and enzyme activity remain elusive. Here, we systematically analyzed the specificity of DNMT1, revealing a pronounced influence of the DNA sequences flanking the target CpG site on DNMT1 activity. We determined DNMT1 structures in complex with preferred DNA substrates revealing that DNMT1 employs flanking sequence-dependent base flipping mechanisms, with large structural rearrangements of the DNA correlating with low catalytic activity. Moreover, flanking sequences influence the conformational dynamics of the active site and cofactor binding pocket. Importantly, we show that the flanking sequence preferences of DNMT1 highly correlate with genomic methylation in human and mouse cells, and 5-azacytidine triggered DNA demethylation is more pronounced at CpG sites with flanks disfavored by DNMT1. Overall, our findings uncover the intricate interplay between CpG-flanking sequence, DNMT1-mediated base flipping and the dynamic landscape of DNA methylation.

DNA Methylation Clocks and Their Predictive Capacity for Aging Phenotypes and Healthspan

The number of age predictors based on DNA methylation (DNAm) profile is rising due to their potential in predicting healthspan and application in age-related illnesses, such as neurodegenerative diseases. The cumulative assessment of DNAm levels at age-related CpGs (DNAm clock) may reflect biological aging. Such DNAm clocks have been developed using various training models and could mirror different aspects of disease/aging mechanisms. Hence, evaluating several DNAm clocks together may be the most effective strategy in capturing the complexity of the aging process. However, various confounders may influence the outcome of these age predictors, including genetic and environmental factors, as well as technical differences in the selected DNAm arrays. These factors should be taken into consideration when interpreting DNAm clock predictions. In the current review, we discuss 15 reported DNAm clocks with consideration for their utility in investigating neurodegenerative diseases and suggest research directions towards developing a more optimal measure for biological aging.

Imprecise DNMT1 activity coupled with neighbor-guided correction enables robust yet flexible epigenetic inheritance

The epigenome, including DNA methylation, is stably propagated during mitotic division. However, single-cell clonal expansion produces heterogeneous methylomes, thus raising the question of how the DNA methylome remains stable despite constant epigenetic drift. Here, we report that a clonal population of DNA (cytosine-5)-methyltransferase 1 (DNMT1)-only cells produces a heterogeneous methylome, which is robustly propagated on cell expansion and differentiation. Our data show that DNMT1 has imprecise maintenance activity and possibly possesses weak de novo activity, leading to spontaneous 'epimutations'. However, these epimutations tend to be corrected through a neighbor-guided mechanism, which is likely to be enabled by the environment-sensitive de novo activity ('tuner') and maintenance activity ('stabilizer') of DNMT1. By generating base-resolution maps of de novo and maintenance activities, we find that H3K9me2/3-marked regions show enhanced de novo activity, and CpG islands have both poor maintenance and de novo activities. The imprecise epigenetic machinery coupled with neighbor-guided correction may be a fundamental mechanism underlying robust yet flexible epigenetic inheritance.

Epigenetic clocks may come out of rhythm-implications for the estimation of chronological age in forensic casework

There is a growing perception that DNA methylation may be influenced by exogenous and endogenous parameters. Knowledge of these factors is of great relevance for the interpretation of DNA-methylation data for the estimation of chronological age in forensic casework. We performed a literature review to identify parameters, which might be of relevance for the prediction of chronological age based on DNA methylation. The quality of age predictions might particularly be influenced by lifetime adversities (chronic stress, trauma/post-traumatic stress disorder (PTSD), violence, low socioeconomic status/education), cancer, obesity and related diseases, infectious diseases (especially HIV and Cytomegalovirus (CMV) infections), sex, ethnicity and exposure to toxins (alcohol, smoking, air pollution, pesticides). Such factors may alter the DNA methylation pattern and may explain the partly high deviations between epigenetic age and chronological age in single cases (despite of low mean absolute deviations) that can also be observed with “epigenetic clocks” comprising a high number of CpG sites. So far, only few publications dealing with forensic age estimation address these confounding factors. Future research should focus on the identification of further relevant confounding factors and the development of models that are “robust” against the influence of such biological factors by systematic investigations under targeted inclusion of diverse and defined cohorts.

Highly accurate skin-specific methylome analysis algorithm as a platform to screen and validate therapeutics for healthy aging

BACKGROUND

DNA methylation (DNAm) age constitutes a powerful tool to assess the molecular age and overall health status of biological samples. Recently, it has been shown that tissue-specific DNAm age predictors may present superior performance compared to the pan- or multi-tissue counterparts. The skin is the largest organ in the body and bears important roles, such as body temperature control, barrier function, and protection from external insults. As a consequence of the constant and intimate interaction between the skin and the environment, current DNAm estimators, routinely trained using internal tissues which are influenced by other stimuli, are mostly inadequate to accurately predict skin DNAm age.

RESULTS

In the present study, we developed a highly accurate skin-specific DNAm age predictor, using DNAm data obtained from 508 human skin samples. Based on the analysis of 2,266 CpG sites, we accurately calculated the DNAm age of cultured skin cells and human skin biopsies. Age estimation was sensitive to the biological age of the donor, cell passage, skin disease status, as well as treatment with senotherapeutic drugs.

CONCLUSIONS

This highly accurate skin-specific DNAm age predictor constitutes a holistic tool that will be of great use in the analysis of human skin health status/molecular aging, as well as in the analysis of the potential of established and novel compounds to alter DNAm age.

Epigenetic Clock: DNA Methylation in Aging

Aging, which is accompanied by decreased organ function and increased disease incidence, limits human lifespan and has attracted investigators for thousands of years. In recent decades, with the rapid development of biology, scientists have shown that epigenetic modifications, especially DNA methylation, are key regulators involved in this process. Regular fluctuations in global DNA methylation levels have been shown to accurately estimate biological age and disease prognosis. In this review, we discuss recent findings regarding the relationship between variations in DNA methylation level patterns and aging. In addition, we introduce the known mechanisms by which DNA methylation regulators affect aging and related diseases. As more studies uncover the mechanisms by which DNA methylation regulates aging, antiaging interventions and treatments for related diseases may be developed that enable human life extension.

Wandering along the epigenetic timeline

BACKGROUND

Increasing life expectancy but also healthspan seems inaccessible as of yet but it may become a reality in the foreseeable future. To extend lifespan, it is essential to unveil molecular mechanisms involved in ageing. As for healthspan, a better understanding of the mechanisms involved in age-related pathologies is crucial.

MAIN BODY

We focus on the epigenetic side of ageing as ageing is traced by specific epigenetic patterns and can be measured by epigenetic clocks. We discuss to what extent exposure to environmental factor, such as alcohol use, unhealthy diet, tobacco and stress, promotes age-related conditions. We focused on inflammation, cancer and Alzheimer's disease. Finally, we discuss strategies to reverse time based on epigenetic reprogramming.

CONCLUSIONS

Reversibility of the epigenetic marks makes them promising targets for rejuvenation. For this purpose, a better understanding of the epigenetic mechanisms underlying ageing is essential. Epigenetic clocks were successfully designed to monitor these mechanisms and the influence of environmental factors. Further studies on age-related diseases should be conducted to determine their epigenetic signature, but also to pinpoint the defect in the epigenetic machinery and thereby identify potential therapeutic targets. As for rejuvenation, epigenetic reprogramming is still at an early stage.

Determination of the phenotypic age in residents of Mexico City: effect of accelerated ageing on lung function and structure

INTRODUCTION

Phenotypic age better represents age-related biological dysregulation than chronological age. Recently, a multisystem-based ageing measure, which integrates chronological age and nine biomarkers, was proposed.

METHODS

Phenotypic age was determined in 774 residents of Mexico City over 60 years old and without respiratory problems. We arbitrarily classified as "accelerated" ageing, those showing >4 years compared with their chronological age, and "slowed" ageing, those with <4 years compared with chronological age. Demographic risk factors were analysed with structured questionnaires. Lung structure was evaluated by high-resolution computed tomography and functional competence was analysed by forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1), diffusion capacity of carbon monoxide (D LCO), and the 6-minute walk test (6MWT).

RESULTS

Overall, 13% of this cohort showed accelerated ageing, which was corroborated with four independent biomarkers of ageing, 42% had normal ageing and 46% had slowed ageing. Risk factors associated with accelerated ageing were male sex (OR 4.4, 95% CI 2.4-7.9; p<0.01), diabetes mellitus (OR 9.7, 95% CI 5.5-17.2; p<0.01), and long-term sleep duration (OR 2.9 95% CI 1.34-6.35, p<0.01). Among smokers, there was a slight but significant association with the number of pack-years. Subjects with accelerated ageing showed decreased FVC (p<0.0001), FEV1 (p<0.0001), D LCO (p<0.02) and walking distance in the 6MWT (p=0.0001). Slowed-ageing subjects presented less frequently with emphysematous lesions compared with those with accelerated ageing.

CONCLUSIONS

A small but significant proportion of residents of Mexico City age rapidly, which is associated with male sex, diabetes, and long-term sleep duration. They exhibit lower levels of lung function and develop emphysema more frequently.

Nutritional Epigenomics and Age-Related Disease

Recent advances in epigenetic research have enabled the development of epigenetic clocks, which have greatly enhanced our ability to investigate molecular processes that contribute to aging and age-related disease. These biomarkers offer the potential to measure the effect of environmental exposures linked to dynamic changes in DNA methylation, including nutrients, as factors in age-related disease. They also offer a compelling insight into how imbalances in the supply of nutrients, particularly B-vitamins, or polymorphisms in regulatory enzymes involved in 1-carbon metabolism, the key pathway that supplies methyl groups for epigenetic reactions, may influence epigenetic age and interindividual disease susceptibility. Evidence from recent studies is critically reviewed, focusing on the significant contribution of the epigenetic clock to nutritional epigenomics and its impact on health outcomes and age-related disease. Further longitudinal studies and randomized nutritional interventions are required to advance the field.

The biological age of the heart is consistently younger than chronological age

Chronological age represents the main factor in donor selection criteria for organ transplantation, however aging is very heterogeneous. Defining the biological aging of individual organs may contribute to supporting this process. In this study we examined the biological age of the heart [right (RA)/left atrium (LA)] and peripheral blood leucocytes in the same subject, and compared these to assess whether blood mirrors cardiac biological aging. Biological aging was studied in 35 donors (0.4–72 years) by exploring mitotic and non-mitotic pathways, using telomere length (TL) and age-dependent methylation changes in certain CpG loci (DNAmAge). Heart non-mitotic DNAmAge was strongly younger than that of both blood (− 10 years, p < 0.0001) and chronological age (− 12 years, p < 0.0001). Instead, heart and blood mitotic age (TL) were similar, and there was no difference in DNAmAge and TL between RA and LA. DNAmAge negatively correlated with TL in heart and blood (p ≤ 0.01). Finally, blood and heart TL (p < 0.01) and DNAmAge (p < 0.0001) were correlated. Therefore, blood can be a proxy indicator of heart biological age. While future investigation on post-transplant graft performance in relation to biological aging is still needed, our study could contribute to opening up novel basic and clinical research platforms in the field of organ transplantation.

Investigation of promoter methylation of MCPH1 gene in circulating cell-free DNA of brain tumor patients

INTRODUCTION

Despite advanced diagnostic and therapeutic techniques, many brain tumors are still diagnosed at high grades and, therefore finding novel molecular markers may assist in early detection and reducing brain tumors-related mortality rate. Owing to the previous reports on the importance of MCPH1 gene in tumorigenesis, the present study was aimed to study the promoter methylation of MCPH1 gene in paired circulating cell-free DNA (cfDNA) and tumor tissues of brain tumor patients.

MATERIALS AND METHODS

Fourteen fresh paired serum and tumor tissue samples in addition to 18 isolated serum samples were collected from patients affected by different grades of brain tumor. Genomic DNA and cfDNA was isolated from tissue and serum samples using QIAamp DNA Mini Kit Norgen Bioteck Kit, respectively. Methylation DNA immunoprecipitation Real-time polymerization chain reaction (MeDIP-Real-time PCR) was performed on isolated DNA samples using EpiQuik MeDIP Ultra Kit and specific primer pairs. cfDNA quantity was determined through Real-time PCR analysis using specific primer pairs designed for GAPDH gene.

RESULTS

MCPH1 was methylated in 54% of cfDNA samples which was significantly associated with tumor grade, as well (P-value = 0.02). The methylation rate of MCPH1 was found as 78% in the tissue samples which was meaningfully associated with tumor grade (P-value = 0.03). Moreover, methylation of the MCPH1 gene was consistent in 57% of the same cfDNA and tissue samples. Methylation of MCPH1 gene in neither tumor tissues nor cfDNA was not correlated with age and sex of the patients.

DISCUSSION AND CONCLUSION

Due to the conformity of methylation of MCPH1 gene in cfDNA and tissue samples in more than half of the enrolled patients, especially in higher grades of tumors, it seems that MCPH1 promoter methylation could be a potential epimarker in not only detection of brain tumors but also in response to chemo- and radiotherapy which warranted further assessment.

Intestinal stem cells heterogeneity and clonal dominance during aging: two faces of the same coin?

Intestinal epithelium undergoes dysfunctions and diseases over time with an exponential increase in the elderly population. Recent studies reported that the intestinal stem cells (ISCs) show a functional decline during aging and a lack of an appropriate cell identity control. Increase of cell-to-cell heterogeneity is a hallmark of aging tissues and organs, however there is little experimental evidence with regard to the cell heterogeneity of the ISCs. On the other hand, the ISCs continuously experience a niche clonality process that diminishes the initial cell heterogeneity over time. In this review, we discuss the latest findings on these topics focusing on the potential mechanisms driving intestinal stem cell heterogeneity and clonality during aging.

Quantification of the pace of biological aging in humans through a blood test, the DunedinPoAm DNA methylation algorithm

Biological aging is the gradual, progressive decline in system integrity that occurs with advancing chronological age, causing morbidity and disability. Measurements of the pace of aging are needed as surrogate endpoints in trials of therapies designed to prevent disease by slowing biological aging. We report a blood-DNA-methylation measure that is sensitive to variation in pace of biological aging among individuals born the same year. We first modeled change-over-time in 18 biomarkers tracking organ-system integrity across 12 years of follow-up in n = 954 members of the Dunedin Study born in 1972-1973. Rates of change in each biomarker over ages 26-38 years were composited to form a measure of aging-related decline, termed Pace-of-Aging. Elastic-net regression was used to develop a DNA-methylation predictor of Pace-of-Aging, called DunedinPoAm for Dunedin(P)ace(o)f(A)ging(m)ethylation. Validation analysis in cohort studies and the CALERIE trial provide proof-of-principle for DunedinPoAm as a single-time-point measure of a person's pace of biological aging.

Decelerated epigenetic aging associated with mood stabilizers in the blood of patients with bipolar disorder

There is high mortality among patients with bipolar disorder (BD). Studies have reported accelerated biological aging in patients with BD. Recently, Horvath and Hannum et al. independently developed DNA methylation (DNAm) profiles as "epigenetic clocks," which are the most accurate biological age estimate. This led to the development of two accomplished measures of epigenetic age acceleration (EAA) using blood samples, namely, intrinsic and extrinsic EAA (IEAA and EEAA, respectively). IEAA, which is based on Horvath's clock, is independent of blood cell counts and indicates cell-intrinsic aging. On the other hand, EEAA, which is based on Hannum's clock, is associated with age-dependent changes in blood cell counts and indicates immune system aging. Further, Lu et al. developed the "GrimAge" clock, which can strongly predict the mortality risk, and DNAm-based telomere length (DNAmTL). We used a DNAm dataset from whole blood samples obtained from 30 patients with BD and 30 healthy controls. We investigated Horvath EAA, IEAA, Hannum EAA, EEAA, Grim EAA, DNAmTL, and DNAm-based blood cell composition. Compared with controls, there was a decrease in Horvath EAA and IEAA in patients with BD. Further, there was a significant decrease in Horvath EAA and IEAA in patients with BD taking medication combinations of mood stabilizers (including lithium carbonate, sodium valproate, and carbamazepine) than in those taking no medication/monotherapy. This study provides novel evidence indicating decelerated epigenetic aging associated with mood stabilizers in patients with BD.

Aberrant DNA methylation in the PAX2 promoter is associated with Müllerian duct anomalies

PURPOSE

Abnormalities during Müllerian duct and female reproductive tract formation during embryonic development result in Müllerian duct anomalies (MDA). Previous studies have identified a role for mutations in related genes and DNA copy number variation (CNV). However, the correlation between gene methylation and MDA remains to be understood.

METHODS

Endometrial tissues were collected from patients with septate (n = 23) or normal uterus (n = 28). We detected the methylation status of CpG sites and mRNA levels of nine candidate genes, including HOXA10, EMX2, TP63, ITGB3, PAX2, LHX1, GSC, WNT4, and H19, using MethyTarget and quantitative real-time polynucleotide chain reaction (qRT-PCR), respectively RESULTS: Compared with healthy controls, we detected three hypomethylated CpG sites (P < 0.05) and increased mRNA levels of PAX2 (P < 0.05) in individuals with MDA. HOXA10, EMX2, TP63, ITGB3, LHX1, and GSC had 1, 1, 2, 1, 5, and 2 differentially methylated CpG sites (P < 0.05), respectively, but there were no significant differences in their mRNA levels (P > 0.05). WNT4 and H19 did not show differences in methylation (P > 0.05) and mRNA levels (P > 0.05).

CONCLUSIONS

Aberrant DNA methylation within the promoter of PAX2 may contribute to the development of MDA by regulating its gene expression. However, the methylation status of HOXA10, EMX2, TP63, ITGB3, LHX1, GSC, WNT4, and H19, may not contribute to the development of MDA.

The shift of the paradigm between ageing and diseases

In the area of the Medical Sciences, the chronological age has always been, and still is, an indicator by which we try to understand the health status of an individual. However, besides considering people born with an already expressed disease, each human genome has sequence alterations called predisposing mutations; carriers of such genetic alterations have an increased risk of contracting diseases during their life. In addition, the exposome, i.e. the totality of environmental noxae (“hits”) to which our body is exposed throughout life (through ingestion, breathing, body surface hits, and psychosociological stress agents, etc.) contributes to increase gradually but inexorably the frailty of an organism, and this process is usually referred to as “physiological ageing”. This position paper proposes that we invert our visual angle and view the passage-of-time not as the cause of diseases, but consider the genome alterations present at birth and the noxae received during our life as the real major causes of ageing. The Biomedical Sciences are now increasingly unraveling the etiopathogenesis of most chronic degenerative diseases; thus, it will be possible to monitor and treat those that most contribute to the increased frailty of each person, which is now referred to with the misnomer “physiological ageing”. These concepts are not banal; indeed, they imply that we must try to avoid the causes of alterations that result later in chronic degenerative diseases. Thus, we should shift our attention from the cure to the prevention of alterations/diseases also to improve both the length and quality of our life. Moreover, this approach involves real personalized or individualized medicine, thus conferring a more direct benefit to each of us by finalizing either the cure or the monitoring of diseases.

DNA Methylation in the Diagnosis of Monogenic Diseases

DNA methylation in the human genome is largely programmed and shaped by transcription factor binding and interaction between DNA methyltransferases and histone marks during gamete and embryo development. Normal methylation profiles can be modified at single or multiple loci, more frequently as consequences of genetic variants acting in cis or in trans, or in some cases stochastically or through interaction with environmental factors. For many developmental disorders, specific methylation patterns or signatures can be detected in blood DNA. The recent use of high-throughput assays investigating the whole genome has largely increased the number of diseases for which DNA methylation analysis provides information for their diagnosis. Here, we review the methylation abnormalities that have been associated with mono/oligogenic diseases, their relationship with genotype and phenotype and relevance for diagnosis, as well as the limitations in their use and interpretation of results.

MethylNet: an automated and modular deep learning approach for DNA methylation analysis

BACKGROUND

DNA methylation (DNAm) is an epigenetic regulator of gene expression programs that can be altered by environmental exposures, aging, and in pathogenesis. Traditional analyses that associate DNAm alterations with phenotypes suffer from multiple hypothesis testing and multi-collinearity due to the high-dimensional, continuous, interacting and non-linear nature of the data. Deep learning analyses have shown much promise to study disease heterogeneity. DNAm deep learning approaches have not yet been formalized into user-friendly frameworks for execution, training, and interpreting models. Here, we describe MethylNet, a DNAm deep learning method that can construct embeddings, make predictions, generate new data, and uncover unknown heterogeneity with minimal user supervision.

RESULTS

The results of our experiments indicate that MethylNet can study cellular differences, grasp higher order information of cancer sub-types, estimate age and capture factors associated with smoking in concordance with known differences.

CONCLUSION

The ability of MethylNet to capture nonlinear interactions presents an opportunity for further study of unknown disease, cellular heterogeneity and aging processes.

The Effect of Tobacco Smoking Differs across Indices of DNA Methylation-Based Aging in an African American Sample: DNA Methylation-Based Indices of Smoking Capture These Effects

Smoking is one of the leading preventable causes of morbidity and mortality worldwide, prompting interest in its association with DNA methylation-based measures of biological aging. Considerable progress has been made in developing DNA methylation-based measures that correspond to self-reported smoking status. In addition, assessment of DNA methylation-based aging has been expanded to better capture individual differences in risk for morbidity and mortality. Untested to date, however, is whether smoking is similarly related to older and newer indices of DNA methylation-based aging, and whether DNA methylation-based indices of smoking can be used in lieu of self-reported smoking to examine effects on DNA methylation-based aging measures. In the current investigation we examine mediation of the impact of self-reported cigarette consumption on accelerated, intrinsic DNA methylation-based aging using indices designed to predict chronological aging, phenotypic aging, and mortality risk, as well as a newly developed DNA methylation-based measure of telomere length. Using a sample of 500 African American middle aged smokers and non-smokers, we found that a) self-reported cigarette consumption was associated with accelerated intrinsic DNA methylation-based aging on some but not all DNA methylation-based aging indices, b) for those aging outcomes associated with self-reported cigarette consumption, DNA methylation-based indicators of smoking typically accounted for greater variance than did self-reported cigarette consumption, and c) self-reported cigarette consumption effects on DNA methylation-based aging indices typically were fully mediated by DNA methylation-based indicators of smoking (e.g., PACKYRS from GrimAge; or cg05575921 CpG site). Results suggest that when DNA methylation-based indices of smoking are substituted for self-reported assessments of smoking, they will typically fully reflect the varied impact of cigarette smoking on intrinsic, accelerated DNA methylation-based aging.

The challenges of estimating biological age

A comparison of nine different approaches over a period of 20 years reveals the most promising indicators for biological age.

Impaired lipid metabolism by age-dependent DNA methylation alterations accelerates aging

Epigenetic alterations and metabolic dysfunction are two hallmarks of aging. However, the mechanism of how their interaction regulates aging, particularly in mammals, remains largely unknown. Here we show ELOVL fatty acid elongase 2 (Elovl2), a gene whose epigenetic alterations are most highly correlated with age prediction, contributes to aging by regulating lipid metabolism. Impaired Elovl2 function disturbs lipid synthesis with increased endoplasmic reticulum stress and mitochondrial dysfunction, leading to key accelerated aging phenotypes. Restoration of mitochondrial activity can rescue age-related macular degeneration (AMD) phenotypes induced by Elovl2 deficiency in human retinal pigmental epithelial (RPE) cells. We revealed an epigenetic-metabolism axis contributing to aging and potentially to antiaging therapy.