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We previously described a DNA methylation (DNAm) based biomarker of human mortality risk DNAm GrimAge. Here we describe version 2 of GrimAge (trained on individuals aged between 40 and 92) which leverages two new DNAm based estimators of (log transformed) plasma proteins: high sensitivity C-reactive protein (logCRP) and hemoglobin A1C (logA1C). We evaluate GrimAge2 in 13,399 blood samples across nine study cohorts. After adjustment for age and sex, GrimAge2 outperforms GrimAge in predicting mortality across multiple racial/ethnic groups (meta P=3.6x10-167 versus P=2.6x10-144) and in terms of associations with age related conditions such as coronary heart disease, lung function measurement FEV1 (correlation= -0.31, P=1.1x10-136), computed tomography based measurements of fatty liver disease. We present evidence that GrimAge version 2 also applies to younger individuals and to saliva samples where it tracks markers of metabolic syndrome. DNAm logCRP is positively correlated with morbidity count (P=1.3x10-54). DNAm logA1C is highly associated with type 2 diabetes (P=5.8x10-155). DNAm PAI-1 outperforms the other age-adjusted DNAm biomarkers including GrimAge2 in correlating with triglyceride (cor=0.34, P=9.6x10-267) and visceral fat (cor=0.41, P=4.7x10-41). Overall, we demonstrate that GrimAge version 2 is an attractive epigenetic biomarker of human mortality and morbidity risk.

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.

Individuals suffering from Werner syndrome (WS) exhibit many clinical signs of accelerated aging. While the underlying constitutional mutation leads to accelerated rates of DNA damage, it is not yet known whether WS is also associated with an increased epigenetic age according to a DNA methylation based biomarker of aging (the "Epigenetic Clock"). Using whole blood methylation data from 18 WS cases and 18 age matched controls, we find that WS is associated with increased extrinsic epigenetic age acceleration (p=0.0072) and intrinsic epigenetic age acceleration (p=0.04), the latter of which is independent of age-related changes in the composition of peripheral blood cells. A multivariate model analysis reveals that WS is associated with an increase in DNA methylation age (on average 6.4 years, p=0.011) even after adjusting for chronological age, gender, and blood cell counts. Further, WS might be associated with a reduction in naïve CD8+ T cells (p=0.025) according to imputed measures of blood cell counts. Overall, this study shows that WS is associated with an increased epigenetic age of blood cells which is independent of changes in blood cell composition. The extent to which this alteration is a cause or effect of WS disease phenotypes remains unknown.

Several articles describe highly accurate age estimation methods based on human DNA-methylation data. It is not yet known whether similar epigenetic aging clocks can be developed based on blood methylation data from canids. Using Reduced Representation Bisulfite Sequencing, we assessed blood DNA-methylation data from 46 domesticated dogs (Canis familiaris) and 62 wild gray wolves (C. lupus). By regressing chronological dog age on the resulting CpGs, we defined highly accurate multivariate age estimators for dogs (based on 41 CpGs), wolves (67 CpGs), and both combined (115 CpGs). Age related DNA methylation changes in canids implicate similar gene ontology categories as those observed in humans suggesting an evolutionarily conserved mechanism underlying age-related DNA methylation in mammals.

Estimates of biological age based on DNA methylation patterns, often referred to as "epigenetic age", "DNAm age", have been shown to be robust biomarkers of age in humans. We previously demonstrated that independent of chronological age, epigenetic age assessed in blood predicted all-cause mortality in four human cohorts. Here, we expanded our original observation to 13 different cohorts for a total sample size of 13,089 individuals, including three racial/ethnic groups. In addition, we examined whether incorporating information on blood cell composition into the epigenetic age metrics improves their predictive power for mortality. All considered measures of epigenetic age acceleration were predictive of mortality (p≤8.2x10-9), independent of chronological age, even after adjusting for additional risk factors (p

Age of Huntington's disease (HD) motoric onset is strongly related to the number of CAG trinucleotide repeats in the huntingtin gene, suggesting that biological tissue age plays an important role in disease etiology. Recently, a DNA methylation based biomarker of tissue age has been advanced as an epigenetic aging clock. We sought to inquire if HD is associated with an accelerated epigenetic age. DNA methylation data was generated for 475 brain samples from various brain regions of 26 HD cases and 39 controls. Overall, brain regions from HD cases exhibit a significant epigenetic age acceleration effect (p=0.0012). A multivariate model analysis suggests that HD status increases biological age by 3.2 years. Accelerated epigenetic age can be observed in specific brain regions (frontal lobe, parietal lobe, and cingulate gyrus). After excluding controls, we observe a negative correlation (r=-0.41, p=5.5×10-8) between HD gene CAG repeat length and the epigenetic age of HD brain samples. Using correlation network analysis, we identify 11 co-methylation modules with a significant association with HD status across 3 broad cortical regions. In conclusion, HD is associated with an accelerated epigenetic age of specific brain regions and more broadly with substantial changes in brain methylation levels.

It has been a long standing hypothesis that blood tissue of PD Parkinson's disease (PD) patients may exhibit signs of accelerated aging. Here we use DNA methylation based biomarkers of aging ("epigenetic clock") to assess the aging rate of blood in two ethnically distinct case-control data sets. Using n=508 Caucasian and n=84 Hispanic blood samples, we assess a) the intrinsic epigenetic age acceleration of blood (IEAA), which is independent of blood cell counts, and b) the extrinsic epigenetic age acceleration rate of blood (EEAA) which is associated with age dependent changes in blood cell counts. Blood of PD subjects exhibits increased age acceleration according to both IEAA (p=0.019) and EEAA (p=6.1 x 10(-3)). We find striking differences in imputed blood cell counts between PD cases and controls. Compared to control subjects, PD subjects contains more granulocytes (p=1.0 x 10(-9) in Caucasians, p=0.00066 in Hispanics) but fewer T helper cells (p=1.4 x 10(-6) in Caucasians, p=0.0024 in Hispanics) and fewer B cells (p=1.6 x 10(-5) in Caucasians, p=4.5 x 10(-5) in Hispanics). Overall, this study shows that the epigenetic age of the immune system is significantly increased in PD patients and that granulocytes play a significant role.

We previously reported the unusual case of a teenage girl stricken with multifocal developmental dysfunctions whose physical development was dramatically delayed resulting in her appearing to be a toddler or at best a preschooler, even unto the occasion of her death at the age of 20 years. Her life-long physician felt that the disorder was unique in the world and that future treatments for age-related diseases might emerge from its study. The objectives of our research were to determine if other such cases exist, and if so, whether aging is actually slowed. Of seven children characterized by dramatically slow developmental rates, five also had associated disorders displayed by the first case. All of the identified subjects were female. To objectively measure the age of blood tissue from these subjects, we used a highly accurate biomarker of aging known as "epigenetic clock" based on DNA methylation levels. No statistically significant differences in chronological and epigenetic ages were detected in any of the newly discovered cases.

Aging is a progressive time-dependent biological process affecting differentially individuals, who can sometimes present exceptional longevity. Epigenetic alterations are one of the hallmarks of aging, which comprise the epigenetic drift and clock at DNA methylation level. In the present study, we estimated the DNA methylation-based age (DNAmage) using four epigenetic clocks based on a small number of CpGs in French centenarians and semi-supercentenarians (CSSC, n=214) as well as nonagenarians' and centenarians' offspring (NCO, n=143) compared to individuals from the French general population (CG, n=149). DNA methylation analysis of the nine CpGs included in the epigenetic clocks showed high correlation with chronological age (-0.66>R>0.54) and also the presence of an epigenetic drift for four CpGs that was only visible in CSSC. DNAmage analysis showed that CSSC and to a lesser extend NCO present a younger DNAmage than their chronological age (15-28.5 years for CSSC, 4.4-11.5 years for NCO and 4.2-8.2 years for CG), which were strongly significant in CSSC compared to CG (p-values<2.2e-16). These differences suggest that epigenetic aging and potentially biological aging are slowed in exceptionally long-lived individuals and that epigenetic clocks based on a small number of CpGs are sufficient to reveal alterations of the global epigenetic clock.

Epigenetic clocks based on DNA methylation (DNAm) can accurately predict chronological age and are thought to capture biological aging. A variety of epigenetic clocks have been developed for different tissue types and age ranges, but none have focused on postnatal age prediction for preterm infants. Epigenetic estimators of biological age might be especially informative in epidemiologic studies of neonates since DNAm is highly dynamic during the neonatal period and this is a key developmental window. Additionally, markers of biological aging could be particularly important for those born preterm since they are at heightened risk of developmental impairments. We aimed to fill this gap by developing epigenetic clocks for neonatal aging in preterm infants. As part of the Neonatal Neurobehavior and Outcomes in Very Preterm Infants (NOVI) study, buccal cells were collected at NICU discharge to profile DNAm levels in 542 very preterm infants. We applied elastic net regression to identify four epigenetic clocks (NEOage Clocks) predictive of post-menstrual and postnatal age, compatible with the Illumina EPIC and 450K arrays. We observed high correlations between predicted and reported ages (0.93 - 0.94) with root mean squared errors (1.28 - 1.63 weeks). Epigenetic estimators of neonatal aging in preterm infants can be useful tools to evaluate biological maturity and associations with neonatal and long-term morbidities.

DNA methylation age acceleration, the discrepancy between epigenetic age and chronological age, is associated with mortality and chronic diseases, including diabetes, hypertension, and hyperlipidemia. In this study, we investigate whether medications commonly used to treat these diseases in 15 drug categories are associated with four epigenetic age acceleration measures: HorvathAge acceleration (HorvathAA), HannumAge acceleration (HannumAA), PhenoAge acceleration, and GrimAge acceleration (GrimAA) using cross-sectional (Phase 1, N=1,100) and longitudinal (Phases 1 and 2, N=266) data from African Americans in the Genetic Epidemiology Network of Arteriopathy (GENOA) study. In cross-sectional analyses, the use of calcium channel blockers was associated with 1.27 years lower HannumAA after adjusting for covariates including hypertension (p=0.001). Longitudinal analyses showed that, compared to those who never used antihypertensives, those who started to take antihypertensives after Phase 1 had a 0.97-year decrease in GrimAA (p=0.007). In addition, compared to those who never used NSAID analgesics, those who started to take them after Phase 1 had a 2.61-year increase in HorvathAA (p=0.0005). Our study demonstrates that three commonly used medications are associated with DNAm age acceleration in African Americans and sheds light on the potential epigenetic effects of pharmaceuticals on aging at the cellular level.

The view of aging has evolved in parallel with the advances in biomedical sciences. Long considered as an irreversible process where interventions were only aimed at slowing down its progression, breakthrough discoveries like animal cloning and cell reprogramming have deeply changed our understanding of postnatal development, giving rise to the emerging view that the epigenome is the driver of aging. The idea was significantly strengthened by the converging discovery that DNA methylation (DNAm) at specific CpG sites could be used as a highly accurate biomarker of age defined by an algorithm known as the Horvath clock. It was at this point where epigenetic rejuvenation came into play as a strategy to reveal to what extent biological age can be set back by making the clock tick backwards. Initial evidence suggests that when the clock is forced to tick backwards in vivo , it is only able to drag the phenotype to a partially rejuvenated condition. In order to explain the results, a bimodular epigenome is proposed, where module A represents the DNAm clock component and module B the remainder of the epigenome. Epigenetic rejuvenation seems to hold the key to arresting or even reversing organismal aging.

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 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.

The severity and outcome of coronavirus disease 2019 (COVID-19) largely depends on a patient's age. Adults over 65 years of age represent 80% of hospitalizations and have a 23-fold greater risk of death than those under 65. In the clinic, COVID-19 patients most commonly present with fever, cough and dyspnea, and from there the disease can progress to acute respiratory distress syndrome, lung consolidation, cytokine release syndrome, endotheliitis, coagulopathy, multiple organ failure and death. Comorbidities such as cardiovascular disease, diabetes and obesity increase the chances of fatal disease, but they alone do not explain why age is an independent risk factor. Here, we present the molecular differences between young, middle-aged and older people that may explain why COVID-19 is a mild illness in some but life-threatening in others. We also discuss several biological age clocks that could be used in conjunction with genetic tests to identify both the mechanisms of the disease and individuals most at risk. Finally, based on these mechanisms, we discuss treatments that could increase the survival of older people, not simply by inhibiting the virus, but by restoring patients' ability to clear the infection and effectively regulate immune responses.

Lung function, strongly associated with morbidity and mortality, decreases with age. This study examines whether poor adult lung function is associated with age accelerations (AAs). DNA methylation (DNAm) based AAs, lifespan predictors (GrimAge and plasminogen activator inhibitor 1-PAI1) and their related age-adjusted measures were estimated from peripheral blood at two time points (8-to-11 years apart) in adults from two cohorts: SAPALDIA (n=987) and ECRHS (n=509). Within each cohort and stratified by gender (except for estimators from GrimAge and PAI1), AAs were used as predictors in multivariate linear regression with cross-sectional lung function parameters, and in covariate-adjusted mixed linear regression with longitudinal change in lung function and meta-analysed.AAs were found cross-sectionally associated with lower mean FEV1 (Forced Expiratory Volume in one second) (AA-residuals:P-value=4x10 -4 ; Intrinsic Epigenetic AA:P-value=2x10 -4 ) in females at the follow-up time point only, and the same trend was observed for FVC (Forced Vital Capacity). Both lifespan and plasma level predictors were observed strongly associated with lung function decline and the decline was stronger in the follow-up time points (strongest association between FEV1 and DNAmAge GrimAge:P-value=1.25x10 -17 ).This study suggests that DNAm based lifespan and plasma level predictors can be utilised as important factors to assess lung health in adults.

Measures derived using blood DNA methylation are increasingly under investigation as indicators of disease and mortality risk. Three existing epigenetic age measures or "epigenetic clocks" appear associated with breast cancer. Two newly-developed epigenetic mortality predictors may be related to all-cancer incidence, but associations with specific cancers have not been examined in large studies. Using HumanMethylation450 BeadChips to measure blood DNA methylation in 2,773 cancer-free women enrolled in the Sister Study, we calculated two epigenetic mortality predictors: 'GrimAgeAccel' and the 'mortality score' (MS). Using Cox proportional hazard models, neither GrimAgeAccel nor the MS were associated with overall breast cancer incidence (GrimAgeAccel hazard ratio [HR]: 1.06, 95% confidence interval [CI]: 0.98-1.14, P =0.17; MS HR: 0.99, 95% CI: 0.92-1.07, P =0.85); however, a weak, positive association was observed for GrimAgeAccel and invasive breast cancer (HR: 1.08, 95% CI: 0.99-1.17, P =0.08). Stratification of invasive cancers by menopause status at diagnoses revealed the association was predominantly observed for postmenopausal breast cancer (HR: 1.10, 95% CI: 1.01, 1.20, P =0.04). Although the MS was unrelated to breast cancer risk, we find evidence that GrimAgeAccel may be weakly associated with invasive breast cancer, particularly for women diagnosed after menopause.

Identifying factors that influence fetal growth in a sex-specific manner can help unravel mechanisms that explain sex differences in adverse neonatal outcomes and in-utero origins of cardiovascular disease disparities. Premature aging of the placenta, a tissue that supports fetal growth and exhibits sex-specific epigenetic changes, is associated with pregnancy complications. Using DNA methylation-based age estimator, we investigated the sex-specific relationship of placental epigenetic aging with fetal growth across 13-40 weeks gestation, neonatal size, and risk of low birth weight. Placental epigenetic age acceleration (PAA), the difference between DNA methylation age and gestational age, was associated with reduced fetal weight among males but with increased fetal weight among females. PAA was inversely associated with fetal weight, abdominal circumference, and biparietal diameter at 32-40 weeks among males but was positively associated with all growth measures among females across 13-40 weeks. A 1-week increase in PAA was associated with 2-fold (95% CI 1.2, 3.2) increased odds for low birth weight and 1.5-fold (95% CI 1.1, 2.0) increased odds for small-for-gestational age among males. In all, fetal growth was significantly reduced in males but not females exposed to a rapidly aging placenta. Epigenetic aging of the placenta may underlie sex differences in neonatal outcomes.

The human pan-tissue epigenetic clock is widely used for estimating age across the entire lifespan, but it does not lend itself well to estimating gestational age (GA) based on placental DNAm methylation (DNAm) data. We replicate previous findings demonstrating a strong correlation between GA and genome-wide DNAm changes. Using substantially more DNAm arrays (n=1,102 in the training set) than a previous study, we present three new placental epigenetic clocks: 1) a robust placental clock (RPC) which is unaffected by common pregnancy complications (e.g., gestational diabetes, preeclampsia), and 2) a control placental clock (CPC) constructed using placental samples from pregnancies without known placental pathology, and 3) a refined RPC for uncomplicated term pregnancies. These placental clocks are highly accurate estimators of GA based on placental tissue; e.g., predicted GA based on RPC is highly correlated with actual GA (r>0.95 in test data, median error less than one week). We show that epigenetic clocks derived from cord blood or other tissues do not accurately estimate GA in placental samples. While fundamentally different from Horvath's pan-tissue epigenetic clock, placental clocks closely track fetal age during development and may have interesting applications.

Aging is associated with a genome-wide change of DNA methylation (DNAm). "DNAm age" is defined as the predicted chronological age by the age estimator based on DNAm. The estimator is called the epigenetic clock. The molecular mechanism underlining the epigenetic clock is still unknown. Here, we evaluated the effects of hypoxia and two immortalization factors, hTERT and SV40-LargeT (LT), on the DNAm age of human fibroblasts in vitro. We detected the cell division-associated progression of DNAm age after >10 population doublings. Moreover, the progression of DNAm age was slower under hypoxia (1% oxygen) compared to normoxia (21% oxygen), suggesting that oxygen levels determine the speed of the epigenetic aging. We show that the speed of cell division-associated DNAm age progression depends on the chronological age of the cell donor. hTERT expression did not arrest cell division-associated progression of DNAm age in most cells. SV40LT expression produced inconsistent effects, including rejuvenation of DNAm age. Our results show that a) oxygen and the targets of SV40LT (e.g. p53) modulate epigenetic aging rates and b) the chronological age of donor cells determines the speed of mitosis-associated DNAm age progression in daughter cells.

An algorithm assessing the methylation levels of 353 informative CpG sites in the human genome permits accurate prediction of the chronologic age of a subject. Interestingly, when there is discrepancy between the predicted age and chronologic age (age acceleration or "AgeAccel"), patients are at risk for morbidity and mortality. Identification of infertile patients at risk for accelerated reproductive senescence may permit preventative action. This study aimed to assess the accuracy of the "epigenetic clock" concept in reproductive age women undergoing fertility treatment by applying the age prediction algorithm in peripheral (white blood cells [WBCs]) and follicular somatic cells (cumulus cells [CCs]), and to identify whether women with premature reproductive aging (diminished ovarian reserve) were at risk of AgeAccel in their age prediction. Results indicated that the epigenetic algorithm accurately predicts age when applied to WBCs but not to CCs. The age prediction of CCs was substantially younger than chronologic age regardless of the patient's age or response to stimulation. In addition, telomeres of CCs were significantly longer than that of WBCs. Our findings suggest that CCs do not demonstrate changes in methylome-predicted age or telomere-length in association with increasing female age or ovarian response to stimulation.

Age-associated DNA methylation changes have been widely reported across many different tissue and cell types. Epigenetic 'clocks' that can predict chronological age with a surprisingly high degree of accuracy appear to do so independently of tissue and cell-type, suggesting that a component of epigenetic drift is cell-type independent. However, the relative amount of age-associated DNAm changes that are specific to a cell or tissue type versus the amount that occurs independently of cell or tissue type is unclear and a matter of debate, with a recent study concluding that most epigenetic drift is tissue-specific. Here, we perform a novel comprehensive statistical analysis, including matched multi cell-type and multi-tissue DNA methylation profiles from the same individuals and adjusting for cell-type heterogeneity, demonstrating that a substantial amount of epigenetic drift, possibly over 70%, is shared between significant numbers of different tissue/cell types. We further show that ELOVL2 is not unique and that many other CpG sites, some mapping to genes in the Wnt and glutamate receptor signaling pathways, are altered with age across at least 10 different cell/tissue types. We propose that while most age-associated DNAm changes are shared between cell-types that the putative functional effect is likely to be tissue-specific.

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

The paramount role of senescent cells in ageing has prompted suggestions that re-expression of telomerase may prevent ageing; a proposition that is predicated on the assumption that senescent cells are the sole cause of ageing. Recently, several DNA methylation-based age estimators (epigenetic clocks) have been developed and they revealed that increased epigenetic age is associated with a host of age-related conditions, and is predictive of lifespan. Employing these clocks to measure epigenetic age in vitro , we interrogated the relationship between epigenetic ageing and telomerase activity. Although hTERT did not induce any perceptible change to the rate of epigenetic ageing, hTERT-expressing cells, which bypassed senescence, continued to age epigenetically. Employment of hTERT mutants revealed that neither telomere synthesis nor immortalisation is necessary for the continued increase in epigenetic age by these cells. Instead, the extension of their lifespan is sufficient to support continued epigenetic ageing of the cell. These characteristics, observed in cells from numerous donors and cell types, reveal epigenetic ageing to be distinct from replicative senescence. Hence, while re-activation of hTERT may stave off physical manifestation of ageing through avoidance of replicative senescence, it would have little impact on epigenetic ageing which continues in spite of telomerase activity.

Identifying reliable biomarkers of aging is a major goal in geroscience. While the first generation of epigenetic biomarkers of aging were developed using chronological age as a surrogate for biological age, we hypothesized that incorporation of composite clinical measures of phenotypic age that capture differences in lifespan and healthspan may identify novel CpGs and facilitate the development of a more powerful epigenetic biomarker of aging. Using an innovative two-step process, we develop a new epigenetic biomarker of aging, DNAm PhenoAge, that strongly outperforms previous measures in regards to predictions for a variety of aging outcomes, including all-cause mortality, cancers, healthspan, physical functioning, and Alzheimer's disease. While this biomarker was developed using data from whole blood, it correlates strongly with age in every tissue and cell tested. Based on an in-depth transcriptional analysis in sorted cells, we find that increased epigenetic, relative to chronological age, is associated with increased activation of pro-inflammatory and interferon pathways, and decreased activation of transcriptional/translational machinery, DNA damage response, and mitochondrial signatures. Overall, this single epigenetic biomarker of aging is able to capture risks for an array of diverse outcomes across multiple tissues and cells, and provide insight into important pathways in aging.

Survival predictors are of potential use for informing on biological age and targeting prevention of aging-related morbidity. We assessed associations of 2 novel methylomic survival indicators, a methylation-based mortality risk score (MRscore) and the epigenetic clock-derived age acceleration (AA), with a well-known survival predictor, frailty index (FI), and compared the 3 indicators in mortality prediction. In a large population-based cohort with 14-year follow-up, we found both MRscore and AA to be independently associated with FI, but the association was much stronger for MRscore than for AA. Although all 3 indicators were individually associated with all-cause mortality, robust associations only persisted for MRscore and FI when simultaneously including the 3 indicators in regression models, with hazard ratios (95% CI) of 1.91 (1.63-2.22), 1.37 (1.25-1.51), and 1.05 (0.90-1.22), respectively, per standard deviation increase of MRscore, FI, and AA. Prediction error curves, Harrell's C-statistics, and time-dependent AUCs all showed higher predictive accuracy for MRscore than for FI and AA. These findings were validated in independent samples. Our study demonstrates the ability of the MRscore to strongly enhance survival prediction beyond established markers of biological age, such as FI and AA, and it thus bears potential of a surrogate endpoint for clinical research and intervention.

Behavioral and lifestyle factors have been shown to relate to a number of health-related outcomes, yet there is a need for studies that examine their relationship to molecular aging rates. Toward this end, we use recent epigenetic biomarkers of age that have previously been shown to predict all-cause mortality, chronic conditions, and age-related functional decline. We analyze cross-sectional data from 4,173 postmenopausal female participants from the Women's Health Initiative, as well as 402 male and female participants from the Italian cohort study, Invecchiare nel Chianti.Extrinsic epigenetic age acceleration (EEAA) exhibits significant associations with fish intake (p=0.02), moderate alcohol consumption (p=0.01), education (p=3x10 -5 ), BMI (p=0.01), and blood carotenoid levels (p=1x10 -5 )-an indicator of fruit and vegetable consumption, whereas intrinsic epigenetic age acceleration (IEAA) is associated with poultry intake (p=0.03) and BMI (p=0.05). Both EEAA and IEAA were also found to relate to indicators of metabolic syndrome, which appear to mediate their associations with BMI. Metformin-the first-line medication for the treatment of type 2 diabetes-does not delay epigenetic aging in this observational study. Finally, longitudinal data suggests that an increase in BMI is associated with increase in both EEAA and IEAA.Overall, the epigenetic age analysis of blood confirms the conventional wisdom regarding the benefits of eating a high plant diet with lean meats, moderate alcohol consumption, physical activity, and education, as well as the health risks of obesity and metabolic syndrome.

Given the dramatic increase in ageing populations, it is of great importance to understand the genetic and molecular determinants of healthy ageing and longevity. Semi-supercentenarians (subjects who reached an age of 105-109 years) arguably represent the gold standard of successful human ageing because they managed to avoid or postpone the onset of major age-related diseases. Relatively few studies have looked at epigenetic determinants of extreme longevity in humans. Here we test whether families with extreme longevity are epigenetically distinct from controls according to an epigenetic biomarker of ageing which is known as "epigenetic clock". We analyze the DNA methylation levels of peripheral blood mononuclear cells (PBMCs) from Italian families constituted of 82 semi-supercentenarians (mean age: 105.6 ± 1.6 years), 63 semi-supercentenarians' offspring (mean age: 71.8 ± 7.8 years), and 47 age-matched controls (mean age: 69.8 ± 7.2 years). We demonstrate that the offspring of semi-supercentenarians have a lower epigenetic age than age-matched controls (age difference=5.1 years, p=0.00043) and that centenarians are younger (8.6 years) than expected based on their chronological age. By contrast, no significant difference could be observed for estimated blood cell counts (such as naïve or exhausted cytotoxic T cells or helper T cells). Future studies will be needed to replicate these findings in different populations and to extend them to other tissues. Overall, our results suggest that epigenetic processes might play a role in extreme longevity and healthy human ageing.

There is an urgent need to develop molecular biomarkers of brain age in order to advance our understanding of age related neurodegeneration. Recently, we developed a highly accurate epigenetic biomarker of tissue age (known as epigenetic clock) which is based on DNA methylation levels. Here we use n=700 dorsolateral prefrontal cortex (DLPFC) samples from Caucasian subjects of the Religious Order Study and the Rush Memory and Aging Project to examine the association between epigenetic age and Alzheimer's disease (AD) related cognitive decline, and AD related neuropathological markers. Epigenetic age acceleration of DLPFC is correlated with several neuropathological measurements including diffuse plaques (r=0.12, p=0.0015), neuritic plaques (r=0.11, p=0.0036), and amyloid load (r=0.091, p=0.016). Further, it is associated with a decline in global cognitive functioning (β=-0.500, p=0.009), episodic memory (β=-0.411, p=0.009) and working memory (β=-0.405, p=0.011) among individuals with AD. The neuropathological markers may mediate the association between epigenetic age and cognitive decline. Genetic complex trait analysis (GCTA) revealed that epigenetic age acceleration is heritable (h2=0.41) and has significant genetic correlations with diffuse plaques (r=0.24, p=0.010) and possibly working memory (r=-0.35, p=0.065). Overall, these results suggest that the epigenetic clock may lend itself as a molecular biomarker of brain age.

Lung cancer is considered an age-associated disease, whose progression is in part due to accumulation of genomic instability as well as age-related decline in system integrity and function. Thus even among individuals exposed to high levels of genotoxic carcinogens, such as those found in cigarette smoke, lung cancer susceptibility may vary as a function of individual differences in the rate of biological aging. We recently developed a highly accurate candidate biomarker of aging based on DNA methylation (DNAm) levels, which may prove useful in assessing risk of aging-related diseases, such as lung cancer. Using data on 2,029 females from the Women's Health Initiative, we examined whether baseline measures of "intrinsic epigenetic age acceleration" (IEAA) predicted subsequent lung cancer incidence. We observed 43 lung cancer cases over the nearly twenty years of follow-up. Results showed that standardized measures of IEAA were significantly associated with lung cancer incidence (HR: 1.50, P=3.4x10-3). Furthermore, stratified Cox proportional hazard models suggested that the association may be even stronger among older individuals (70 years or above) or those who are current smokers. Overall, our results suggest that IEAA may be a useful biomarker for evaluating lung cancer susceptibility from a biological aging perspective.