The epigenetic clock is correlated with physical and cognitive fitness in the Lothian Birth Cohort 1936

Perfluoroalkyl substances influence DNA methylation in school-age children highly exposed through drinking water contaminated from firefighting foam: a cohort study in Ronneby, Sweden

Perfluoroalkyl substances (PFASs) are widespread synthetic substances with various adverse health effects. A potential mechanism of toxicity for PFASs is via epigenetic changes, such as DNA methylation. Previous studies have evaluated associations between PFAS exposure and DNA methylation among newborns and adults. However, no study has evaluated how PFASs influence DNA methylation among children of school age. In this exploratory study with school-age children exposed to PFASs through drinking water highly contaminated from firefighting foams, we aimed to investigate whether exposure to PFASs was associated with alteration in DNA methylation and epigenetic age acceleration. Sixty-three children aged 7-11 years from the Ronneby Biomarker Cohort (Sweden) were included. The children were either controls with only background exposure (n = 32; perfluorooctane sulfonic acid: median 2.8 and range 1-5 ng/ml) or those exposed to very high levels of PFASs (n = 31; perfluorooctane sulfonic acid: median 295 and range 190-464 ng/ml). These two groups were matched on sex, age, and body mass index. Genome-wide methylation of whole-blood DNA was analyzed using the Infinium MethylationEPIC BeadChip kit. Epigenetic age acceleration was derived from the DNA methylation data. Twelve differentially methylated positions and seven differentially methylated regions were found when comparing the high-exposure group to the control group. There were no differences in epigenetic age acceleration between these two groups (P = 0.66). We found that PFAS exposure was associated with DNA methylation at specific genomic positions and regions in children at school age, which may indicate a possible mechanism for linking PFAS exposure to health effects.

Association Between Posttraumatic Stress Disorder and Epigenetic Age Acceleration in a Sample of Twins

OBJECTIVE

Posttraumatic stress disorder (PTSD) has been related to accelerated biological aging processes, but objective evidence for this association is limited. DNA methylation (DNAm) age acceleration is a novel measure of biological aging that may help clarify if PTSD is related to biological aging processes. We aim to examine whether PTSD is associated with biological aging using a comprehensive set of DNAm age acceleration markers and to what extent the unshared environment contributes to the association.

METHODS

Using a cross-sectional co-twin control study design, we investigated the association of the clinical diagnosis and symptom severity of PTSD with six measurements of DNAm age acceleration based on epigenome-wide data derived from peripheral blood lymphocytes of 296 male twins from the Vietnam Era Twin Registry.

RESULTS

Twins with current PTSD had significantly advanced DNAm age acceleration compared with twins without PTSD for five of six measures of DNAm age acceleration. Across almost all measures of DNAm age acceleration, twins with current PTSD were "epigenetically older" than their twin brothers without PTSD: estimated differences ranged between 1.6 (95% confidence interval = 0.0-3.1) and 2.7 (95% confidence interval = 0.5-4.8) biological age year-equivalents. A higher Clinician-Administered PTSD Scale score was also associated with a higher within-pair DNAm age acceleration. Results remained consistent after adjustment for behavioral and cardiovascular risk factors.

CONCLUSIONS

PTSD is associated with epigenetic age acceleration, primarily through unshared environmental mechanisms as opposed to genetic or familial factors. These results suggest that PTSD is related to systemic processes relevant to biological aging.

The metabolome as a biomarker of aging in Drosophila melanogaster

Many biomarkers have been shown to be associated not only with chronological age but also with functional measures of biological age. In human populations, it is difficult to show whether variation in biological age is truly predictive of life expectancy, as such research would require longitudinal studies over many years, or even decades. We followed adult cohorts of 20 Drosophila Genetic Reference Panel (DGRP) strains chosen to represent the breadth of lifespan variation, obtain estimates of lifespan, baseline mortality, and rate of aging, and associate these parameters with age‐specific functional traits including fecundity and climbing activity and with age‐specific targeted metabolomic profiles. We show that activity levels and metabolome‐wide profiles are strongly associated with age, that numerous individual metabolites show a strong association with lifespan, and that the metabolome provides a biological clock that predicts not only sample age but also future mortality rates and lifespan. This study with 20 genotypes and 87 metabolites, while relatively small in scope, establishes strong proof of principle for the fly as a powerful experimental model to test hypotheses about biomarkers and aging and provides further evidence for the potential value of metabolomic profiles as biomarkers of aging.

Evaluation of Epigenetic Age Based on DNA Methylation Analysis of Several CpG Sites in Ukrainian Population

Epigenetic clocks are the models, which use CpG methylation levels for the age prediction of an organism. Although there were several epigenetic clocks developed there is a demand for development and evaluation of the relatively accurate and sensitive epigenetic clocks that can be used for routine research purposes. In this study, we evaluated two epigenetic clock models based on the 4 CpG sites and 2 CpG sites in the human genome using the pyrosequencing method for their methylation level estimation. The study sample included 153 people from the Ukrainian population with the age from 0 to 101. Both models showed a high correlation with the chronological age in our study sample (R² = 0.85 for the 2 CpG model and R² = 0.92 for the 4 CpG model). We also estimated the accuracy metrics of the age prediction in our study sample. For the age group from 18 to 80 MAD was 5.1 years for the 2 CpG model and 4.1 years for the 4 CpG model. In this regard, we can conclude, that the models evaluated in the study have good age predictive accuracy, and can be used for the epigenetic age evaluation due to the relative simplicity and time-effectiveness.

A catalogue of omics biological ageing clocks reveals substantial commonality and associations with disease risk

Biological age (BA), a measure of functional capacity and prognostic of health outcomes that discriminates between individuals of the same chronological age (chronAge), has been estimated using a variety of biomarkers. Previous comparative studies have mainly used epigenetic models (clocks), we use ~1000 participants to compare fifteen omics ageing clocks, with correlations of 0.21-0.97 with chronAge, even with substantial sub-setting of biomarkers. These clocks track common aspects of ageing with 95% of the variance in chronAge being shared among clocks. The difference between BA and chronAge - omics clock age acceleration (OCAA) - often associates with health measures. One year’s OCAA typically has the same effect on risk factors/10-year disease incidence as 0.09/0.25 years of chronAge. Epigenetic and IgG glycomics clocks appeared to track generalised ageing while others capture specific risks. We conclude BA is measurable and prognostic and that future work should prioritise health outcomes over chronAge.

Seven-CpG DNA Methylation Age Determined by Single Nucleotide Primer Extension and Illumina's Infinium MethylationEPIC Array Provide Highly Comparable Results

DNA methylation age (DNAm age, epigenetic clock) is a novel and promising biomarker of aging. It is calculated from the methylation fraction of specific cytosine phosphate guanine sites (CpG sites) of genomic DNA. Several groups have proposed epigenetic clock algorithms and these differ mostly regarding the number and location of the CpG sites considered and the method used to assess the methylation status. Most epigenetic clocks are based on a large number of CpGs, e.g. as measured by DNAm microarrays. We have recently evaluated an epigenetic clock based on the methylation fraction of seven CpGs that were determined by methylation-sensitive single nucleotide primer extension (MS-SNuPE). This method is more cost-effective when compared to array-based technologies as only a few CpGs need to be examined. However, there is only little data on the correspondence in epigenetic age estimation using the 7-CpG clock and other algorithms. To bridge this gap, in this study we measured the 7-CpG DNAm age using two methods, via MS-SNuPE and via the MethylationEPIC array, in a sample of 1,058 participants of the Berlin Aging Study II (BASE-II), assessed as part of the GendAge study. On average, participants were 75.6 years old (SD: 3.7, age range: 64.9-90.0, 52.6% female). Agreement between methods was assessed by Bland-Altman plots. DNAm age was highly correlated between methods (Pearson's r = 0.9) and Bland-Altman plots showed a difference of 3.1 years. DNAm age by the 7-CpG formula was 71.2 years (SD: 6.9 years, SNuPE) and 68.1 years (SD: 6.4 years, EPIC array). The mean of difference in methylation fraction between methods for the seven individual CpG sites was between 0.7 and 13 percent. To allow direct conversion of DNAm age obtained from both methods we developed an adjustment formula with a randomly selected training set of 529 participants using linear regression. After conversion of the Illumina data in a second and independent validation set, the adjusted DNAm age was 71.44 years (SD: 6.1 years, n = 529). In summary, we found the results of DNAm clocks to be highly comparable. Furthermore, we developed an adjustment formula that allows for direct conversion of DNAm age estimates between methods and enables one singular clock to be used in studies that employ either the Illumina or the SNuPE method.

Relationship between five Epigenetic Clocks, Telomere Length and Functional Capacity assessed in Older Adults: Cross-sectional and Longitudinal Analyses

DNA methylation age acceleration (DNAmAA, derived from an epigenetic clock) and relative leukocyte telomere length (rLTL) are widely accepted biomarkers of aging. Nevertheless, it is still unclear which aspects of aging they represent best. Here we evaluated longitudinal associations between baseline rLTL and DNAmAA (estimated with 7-CpG clock) and functional assessments covering different domains of aging. Additionally, we made use of cross-sectional data on these assessments and examined their association with DNAmAA estimated by five different DNAm age measures. Two-wave longitudinal data was available for 1,083 participants of the Berlin Aging Study II (BASE-II) who were re-examined on average 7.4 years after baseline as part of the GendAge study. Functional outcomes were assessed with Fried's frailty score, Tinetti mobility test, falls in the past 12 months (yes/no), Finger-floor distance, Mini Mental State Examination (MMSE), Center for Epidemiologic Studies Depression Scale (CES-D), Activities of Daily Living (ADL), Instrumented ADL (IADL) and Mini Nutritional Assessment (MNA). Overall, we found no evidence for an association between the molecular biomarkers measured at baseline, rLTL and DNAmAA (7-CpG clock), and functional assessments assessed at follow-up. Similarly, a cross-sectional analyses of follow-up data did also not show evidence for associations of the various DNAmAA measures (7-CpG clock, Horvath's clock, Hannum's clock PhenoAge, and GrimAge) with functional assessments. In conclusion, neither rLTL nor 7-CpG DNAmAA were able to predict impairment in the analyzed assessments over a ~7-year time-course. Similarly, DNAmAA estimated from five epigenetic clocks was not a good cross-sectional marker of health deterioration either.

The Relationship between Epigenetic Age and Myocardial Infarction/Acute Coronary Syndrome in a Population-Based Nested Case-Control Study

We investigated the relationship between ‘epigenetic age’ (EA) derived from DNA methylation (DNAm) and myocardial infarction (MI)/acute coronary syndrome (ACS). A random population sample was examined in 2003/2005 (n = 9360, 45–69, the HAPIEE project) and followed up for 15 years. From this cohort, incident MI/ACS (cases, n = 129) and age- and sex-stratified controls (n = 177) were selected for a nested case-control study. Baseline EA (Horvath’s, Hannum’s, PhenoAge, Skin and Blood) and the differences between EA and chronological age (CA) were calculated (ΔAHr, ΔAHn, ΔAPh, ΔASB). EAs by Horvath’s, Hannum’s and Skin and Blood were close to CA (median absolute difference, MAD, of 1.08, –1.91 and –2.03 years); PhenoAge had MAD of −9.29 years vs. CA. The adjusted odds ratios (ORs) of MI/ACS per 1–year increments of ΔAHr, ΔAHn, ΔASB and ΔAPh were 1.01 (95% CI 0.95–1.07), 1.01 (95% CI 0.95–1.08), 1.02 (95% CI 0.97–1.06) and 1.01 (0.93–1.09), respectively. When classified into tertiles, only the highest tertile of ΔAPh showed a suggestion of increased risk of MI/ACS with OR 2.09 (1.11–3.94) independent of age and 1.84 (0.99–3.52) in the age- and sex-adjusted model. Metabolic modulation may be the likely mechanism of this association. In conclusion, this case-control study nested in a prospective population-based cohort did not find strong associations between accelerated epigenetic age markers and risk of MI/ACS. Larger cohort studies are needed to re-examine this important research question.

Emerging rejuvenation strategies-Reducing the biological age

Several interventions have recently emerged that were proposed to reverse rather than just attenuate aging, but the criteria for what it takes to achieve rejuvenation remain controversial. Distinguishing potential rejuvenation therapies from other longevity interventions, such as those that slow down aging, is challenging, and these anti-aging strategies are often referred to interchangeably. We suggest that the prerequisite for a rejuvenation intervention is a robust, sustained, and systemic reduction in biological age, which can be assessed by biomarkers of aging, such as epigenetic clocks. We discuss known and putative rejuvenation interventions and comparatively analyze them to explore underlying mechanisms.

Associations between alcohol use and accelerated biological ageing

Harmful alcohol use is a leading cause of premature death and is associated with age-related disease. Biological ageing is highly variable between individuals and may deviate from chronological ageing, suggesting that biomarkers of biological ageing (derived from DNA methylation or brain structural measures) may be clinically relevant. Here, we investigated the relationships between alcohol phenotypes and both brain and DNA methylation age estimates. First, using data from UK Biobank and Generation Scotland, we tested the association between alcohol consumption (units/week) or hazardous use (Alcohol Use Disorders Identification Test [AUDIT] scores) and accelerated brain and epigenetic ageing in 20,258 and 8051 individuals, respectively. Second, we used Mendelian randomisation (MR) to test for a causal effect of alcohol consumption levels and alcohol use disorder (AUD) on biological ageing. Alcohol use showed a consistent positive association with higher predicted brain age (AUDIT-C: β = 0.053, p = 3.16 × 10-13 ; AUDIT-P: β = 0.052, p = 1.6 × 10-13 ; total AUDIT score: β = 0.062, p = 5.52 × 10-16 ; units/week: β = 0.078, p = 2.20 × 10-16 ), and two DNA methylation-based estimates of ageing, GrimAge (units/week: β = 0.053, p = 1.48 × 10-7 ) and PhenoAge (units/week: β = 0.077, p = 2.18x10-10 ). MR analyses revealed limited evidence for a causal effect of AUD on accelerated brain ageing (β = 0.118, p = 0.044). However, this result should be interpreted cautiously as the significant effect was driven by a single genetic variant. We found no evidence for a causal effect of alcohol consumption levels on accelerated biological ageing. Future studies investigating the mechanisms associating alcohol use with accelerated biological ageing are warranted.

Cumulative risks predict epigenetic age in adult survivors of extremely low birth weight

Long-term sequelae of extremely low birth weight (ELBW; ≤1000 g) may contribute to accelerated biological aging. This hypothesis was examined by analyzing a range of risk factors with a molecular age marker in adults born at ELBW or normal birth weight (NBW; ≥2500 g). DNAm age-the weighted average of DNA methylation at 353 cytosine-phosphate-guanine (CpG) sites from across the genome-was derived from a sample of 45 ELBW (M_age  = 32.35 years) and 47 NBW control (M_age  = 32.44 years) adults, using the Illumina 850k BeadChip Array. At two assessments undertaken 9 years apart (at 23 and 32 years), cumulative risks were summed from six domains with potential to affect physiological and psychological health: resting respiratory sinus arrhythmia, blood pressure, basal cortisol, grip strength, body mass index, and self-esteem. At age 32 years, cumulative risks were differentially associated with epigenetic age in ELBW survivors (interaction, p < 0.01). For each additional risk factor they possessed, ELBW survivors (B = 1.43) were biologically 2.16 years older than NBW adults (B = -0.73), by the fourth decade of life. Developmental change, epigenetic maintenance, and intervention targets are discussed.

Genome-wide DNA methylation profiling in nonagenarians suggests an effect of PM20D1 in late onset Alzheimer's disease

Background

The aim of this study is to identify differentially methylated regions (DMRs) in the genomes of a sample of cognitively healthy individuals and a sample of individuals with LOAD, all of them nonagenarians from Costa Rica.

Methods

In this study, we compared whole blood DNA methylation profiles of 32 individuals: 21 cognitively healthy and 11 with LOAD, using the Infinium MethylationEPIC BeadChip. First, we calculated the epigenetic age of the participants based on Horvath’s epigenetic clock. DMRcate and Bumphunter were used to identify DMRs. After in silico and knowledge-based filtering of the DMRs, we performed a methylation quantitative loci (mQTL) analysis (rs708727 and rs960603).

Results

On average, the epigenetic age was 73 years in both groups, which represents a difference of over 20 years between epigenetic and chronological age in both affected and unaffected individuals. Methylation analysis revealed 11 DMRs between groups, which contain six genes and two pseudogenes. These genes are involved in cell cycle regulation, embryogenesis, synthesis of ceramides, and migration of interneurons to the cerebral cortex. One of the six genes is PM20D1, for which altered expression has been reported in LOAD. After genotyping previously reported mQTL SNPs for the gene, we found that average methylation in the PM20D1 DMR differs between genotypes for rs708727, but not for rs960603.

Conclusions

This work supports the possible role of PM20D1 in protection against AD, by showing differential methylation in blood of affected and unaffected nonagenarians. Our results also support the influence of genetic factors on PM20D1 methylation levels.

Epigenetic Aging Biomarkers Associated With Cognitive Impairment in Older African American Adults With Human Immunodeficiency Virus (HIV)

BACKGROUND

Accelerated epigenetic aging using DNA methylation (DNAm)-based biomarkers has been reported in people with human immunodeficiency virus (HIV, PWH), but limited data are available among African Americans (AA), women, and older PWH.

METHODS

DNAm was measured using Illumina EPIC Arrays for 107 (69 PWH and 38 HIV-seronegative controls) AA adults ≥60 years in New York City. Six DNAm-based biomarkers of aging were estimated: (1) epigenetic age acceleration (EAA), (2) extrinsic epigenetic age acceleration (EEAA), (3) intrinsic epigenetic age acceleration (IEAA), (4) GrimAge, (5) PhenoAge, and (6) DNAm-estimated telomere length (DNAm-TL). The National Institutes of Health (NIH) Toolbox Cognition Battery (domains: executive function, attention, working memory, processing speed, and language) and Montreal Cognitive Assessment (MoCA) were administered. Participants were assessed for frailty by the Fried criteria.

RESULTS

The PWH and control groups did not differ by sex, chronological age, or ethnicity. In total, 83% of PWH had a viral load <50 copies/mL, and 94% had a recent CD4 ≥200 cells/µL. The PWH group had a higher EAA, EEAA, GrimAge, and PhenoAge, and a lower DNAm-TL compared to the controls. IEAA was not different between groups. For PWH, there were significant negative correlations between IEAA and executive function, attention, and working memory and PhenoAge and attention. No associations between biomarkers and frailty were detected.

CONCLUSIONS

Evidence of epigenetic age acceleration was observed in AA older PWH using DNAm-based biomarkers of aging. There was no evidence of age acceleration independent of cell type National Institutes of Health composition (IEAA) associated with HIV, but this measure was associated with decreased cognitive function among PWH.

Rejuvant®, a potential life-extending compound formulation with alpha-ketoglutarate and vitamins, conferred an average 8 year reduction in biological aging, after an average of 7 months of use, in the TruAge DNA methylation test

The search continues for possible interventions that delay and/or reverse biological aging, resulting in extended healthspan and lifespan. Interventions delaying aging in animal models are well established; however, most lack validation in humans. The length of human lifespan makes it impractical to perform survival analysis. Instead, aging biomarkers, such as DNA methylation (DNAm) clocks, have been developed to monitor biological age. Herein we report a retrospective analysis of DNA methylation age in 42 individuals taking Rejuvant®, an alpha-ketoglutarate based formulation, for an average period of 7 months. DNAm testing was performed at baseline and by the end of treatment with Rejuvant® supplementation. Remarkably, individuals showed an average decrease in biological aging of 8 years (p-value=6.538x10^-12). Furthermore, the supplementation with Rejuvant® is robust to individual differences, as indicated by the fact that a large majority of participants decreased their biological age. Moreover, we found that Rejuvant® is of additional benefit to chronologically and biologically older individuals. While continued testing, particularly in a placebo-controlled design, is required, the nearly 8-year reversal in the biological age of individuals taking Rejuvant® for 4 to 10 months is noteworthy, making the natural product cocktail an intriguing candidate to affect human aging.

DNA Methylation in Genetic and Sporadic Forms of Neurodegeneration: Lessons from Alzheimer's, Related Tauopathies and Genetic Tauopathies

Genetic and sporadic forms of tauopathies, the most prevalent of which is Alzheimer's Disease, are a scourge of the aging society, and in the case of genetic forms, can also affect children and young adults. All tauopathies share ectopic expression, mislocalization, or aggregation of the microtubule associated protein TAU, encoded by the MAPT gene. As TAU is a neuronal protein widely expressed in the CNS, the overwhelming majority of tauopathies are neurological disorders. They are characterized by cognitive dysfunction often leading to dementia, and are frequently accompanied by movement abnormalities such as parkinsonism. Tauopathies can lead to severe neurological deficits and premature death. For some tauopathies there is a clear genetic cause and/or an epigenetic contribution. However, for several others the disease etiology is unclear, with few tauopathies being environmentally triggered. Here, we review current knowledge of tauopathies listing known genetic and important sporadic forms of these disease. Further, we discuss how DNA methylation as a major epigenetic mechanism emerges to be involved in the disease pathophysiology of Alzheimer's, and related genetic and non-genetic tauopathies. Finally, we debate the application of epigenetic signatures in peripheral blood samples as diagnostic tools and usages of epigenetic therapy strategies for these diseases.

Comparative neuropathology in aging primates: A perspective

While humans exhibit a significant degree of neuropathological changes associated with deficits in cognitive and memory functions during aging, non-human primates (NHP) present with more variable expressions of pathological alterations among individuals and species. As such, NHP with long life expectancy in captivity offer an opportunity to study brain senescence in the absence of the typical cellular pathology caused by age-related neurodegenerative illnesses commonly seen in humans. Age-related changes at neuronal population, single cell, and synaptic levels have been well documented in macaques and marmosets, while age-related and Alzheimer's disease-like neuropathology has been characterized in additional species including lemurs as well as great apes. We present a comparative overview of existing neuropathologic observations across the primate order, including classic age-related changes such as cell loss, amyloid deposition, amyloid angiopathy, and tau accumulation. We also review existing cellular and ultrastructural data on neuronal changes, such as dendritic attrition and spine alterations, synaptic loss and pathology, and axonal and myelin pathology, and discuss their repercussions on cellular and systems function and cognition.

Reduction in Epigenetic Age Acceleration Is Related to Empathy in Mothers with Neglectful Caregiving

DNA methylation clocks are used as molecular estimators of epigenetic age, but with little evidence in mothers and none in neglectful mothering. We investigated differences in epigenetic age acceleration (EAA) and the role of empathy using the PhenoAge clock. We collected saliva samples from mothers with extreme disregard for their child's needs (50 in the neglect group, NG) and mothers with non-neglectful caregiving (87 in the control group, CG). Mothers completed an empathy scale, along with questionnaires of their own childhood maltreatment, adverse life events and psychiatric disorders. Sociodemographic variables potentially affecting EAA were also measured. The ANCOVA solution showed a significant increase in EAA in the NG compared to the CG, after adjustment for maternal age, number of pregnancies, financial assistance, adverse events, childhood maltreatment and psychiatric disorder. The group interaction effects showed a reduction in EAA for greater empathic concern and for a higher education level both as positive factors, and an increment in EAA for mothers living in a two-parent family as a risk factor, all in the NG. Our findings open the search for protective factors of EAA associated with caregiver behavior to reduce health vulnerabilities and poor social functioning, especially for mothers at risk of maladaptive caregiving.

Healthy eating patterns and epigenetic measures of biological age

BACKGROUND

Healthy eating is associated with lower risks of disease and mortality, but the mechanisms underlying these associations are unclear. Age is strongly related to health outcomes, and biological age can be estimated using the blood methylome.

OBJECTIVES

To determine whether healthy eating patterns are associated with methylation-based measures of biological age.

METHODS

Among women in the Sister Study, we calculated scores on 4 recommendation-based healthy eating indexes [Dietary Approaches to Stop Hypertension diet, Healthy Eating Index-2015, Alternative Healthy Eating Index (aHEI-2010), and the Alternative Mediterranean diet] using a validated 110-item Block FFQ completed at enrollment. Genome-wide DNA methylation data were generated using the HumanMethylation450 BeadChip on whole blood samples collected at enrollment from a case-cohort sample of 2694 women and were used to calculate 4 measures of epigenetic age acceleration (Hannum AgeAccel, Horvath AgeAccel, PhenoAgeAccel, and GrimAgeAccel). Linear regression models, adjusted for covariates and cohort sampling weights, were used to examine cross-sectional associations between eating patterns and measures of biological age.

RESULTS

All 4 healthy eating indexes had inverse associations with epigenetic age acceleration, most notably with PhenoAgeAccel and GrimAgeAccel. Of these, the strongest associations were for aHEI-2010 [per 1-SD increase in diet quality, PhenoAgeAccel β = -0.5 y (95% CI: -0.8 to -0.2 y) and GrimAgeAccel β = -0.4 y (95% CI: -0.6 to -0.3 y)]. Although effect modification was not observed for most lifestyle factors, in analyses stratified by physical activity, the benefits of a healthy diet on epigenetic age acceleration were more pronounced among women who did not meet physical activity guidelines (reporting <2.5 h/wk of exercise).

CONCLUSIONS

Higher diet quality is inversely associated with methylation-based measures of biological age. Improving diet could have the most benefits in lowering biological age among women with lower levels of physical activity. This trial was registered at clinicaltrials.gov as NCT00047970.

Low serum klotho associated with all-cause mortality among a nationally representative sample of American adults

α-Klotho (klotho) is a protein involved in suppressing oxidative stress and inflammation. In animal models, it is reported to underlie numerous aging phenotypes and longevity. Among a nationally representative sample of adults aged 40 to 79 in the United States, we investigated whether circulating concentrations of klotho is a marker of mortality risk. Serum klotho was measured by ELISA on 10,069 individuals enrolled in the National Health and Nutrition Examination Survey between 2007-2014. Mortality follow-up data based on the National Death Index were available through December 31, 2015. After a mean follow-up of 58 months (range: 1-108), 616 incident deaths occurred. Using survey-weighted Cox regression models adjusted for age, sex and survey cycle, low serum klotho concentration (< 666 pg/mL) was associated with a 31% higher risk of death (compared to klotho concentration > 985 pg/mL, HR: 1.31, 95% CI: 1.00, 1.71, P= 0.05). Associations were consistent for mortality caused by heart disease or cancer. Associations of klotho with all-cause mortality did not appear to differ by most participant characteristics. However, we observed effect modification by physical activity, such that low levels of serum klotho were more strongly associated with mortality among individuals who did not meet recommendation-based physical activity guidelines. Our findings suggest that, among the general population of American adults, circulating levels of klotho may serve as a marker of mortality risk.

Epigenetic clock and methylation studies in the rhesus macaque

Methylation levels at specific CpG positions in the genome have been used to develop accurate estimators of chronological age in humans, mice, and other species. Although epigenetic clocks are generally species-specific, the principles underpinning them appear to be conserved at least across the mammalian class. This is exemplified by the successful development of epigenetic clocks for mice and several other mammalian species. Here, we describe epigenetic clocks for the rhesus macaque (Macaca mulatta), the most widely used nonhuman primate in biological research. Using a custom methylation array (HorvathMammalMethylChip40), we profiled n = 281 tissue samples (blood, skin, adipose, kidney, liver, lung, muscle, and cerebral cortex). From these data, we generated five epigenetic clocks for macaques. These clocks differ with regard to applicability to different tissue types (pan-tissue, blood, skin), species (macaque only or both humans and macaques), and measure of age (chronological age versus relative age). Additionally, the age-based human-macaque clock exhibits a high age correlation (R = 0.89) with the vervet monkey (Chlorocebus sabaeus), another Old World species. Four CpGs within the KLF14 promoter were consistently altered with age in four tissues (adipose, blood, cerebral cortex, skin). Future studies will be needed to evaluate whether these epigenetic clocks predict age-related conditions in the rhesus macaque.

Epigenetic clock and methylation studies in cats

Human DNA methylation profiles have been used successfully to develop highly accurate biomarkers of aging ("epigenetic clocks"). Although these human epigenetic clocks are not immediately applicable to all species of the animal kingdom, the principles underpinning them appear to be conserved even in animals that are evolutionarily far removed from humans. This is exemplified by recent development of epigenetic clocks for mice and other mammalian species. Here, we describe epigenetic clocks for the domestic cat (Felis catus), based on methylation profiles of CpGs with flanking DNA sequences that are highly conserved between multiple mammalian species. Methylation levels of these CpGs are measured using a custom-designed Infinium array (HorvathMammalMethylChip40). From these, we present 3 epigenetic clocks for cats; of which, one applies only to blood samples from cats, while the remaining two dual-species human-cat clocks apply both to cats and humans. We demonstrate that these domestic cat clocks also lead to high age correlations in cheetahs, tigers, and lions. It is expected that these epigenetic clocks for cats possess the potential to be further developed for monitoring feline health as well as being used for identifying and validating anti-aging interventions.

The association between epigenetic clocks and physical functioning in older women: a three-year follow-up

Background

Epigenetic clocks are composite markers developed to predict chronological age or mortality risk from DNA methylation (DNAm) data. The present study investigated the associations between 4 epigenetic clocks (Horvath’s and Hannum’s DNAmAge and DNAm GrimAge and PhenoAge) and physical functioning during a 3-year follow-up.

Method

We studied 63- to 76-year-old women (N = 413) from the Finnish Twin Study on Aging. DNAm was measured from blood samples at baseline. Age acceleration (AgeAccel), that is, discrepancy between chronological age and DNAm age, was determined as residuals from linear model. Physical functioning was assessed under standardized laboratory conditions at baseline and at follow-up. A cross-sectional analysis was performed with path models, and a longitudinal analysis was conducted with repeated measures linear models. A nonrandom missing data analysis was performed.

Results

In comparison to the other clocks, GrimAgeAccel was more strongly associated with physical functioning. At baseline, GrimAgeAccel was associated with lower performance in the Timed Up and Go (TUG) test and the 6-minute walk test. At follow-up, significant associations were observed between GrimAgeAccel and lowered performance in the TUG, 6-minute and 10-m walk tests, and knee extension and ankle plantar flexion strength tests.

Conclusions

The DNAm GrimAge, a novel estimate of biological aging, associated with decline in physical functioning over the 3-year follow-up in older women. However, associations between chronological age and physical function phenotypes followed similar pattern. Current epigenetic clocks do not provide strong benefits in predicting the decline of physical functioning at least during a rather short follow-up period and restricted age range.

Epigenetic age prediction

Advanced age is the main common risk factor for cancer, cardiovascular disease and neurodegeneration. Yet, more is known about the molecular basis of any of these groups of diseases than the changes that accompany ageing itself. Progress in molecular ageing research was slow because the tools predicting whether someone aged slowly or fast (biological age) were unreliable. To understand ageing as a risk factor for disease and to develop interventions, the molecular ageing field needed a quantitative measure; a clock for biological age. Over the past decade, a number of age predictors utilising DNA methylation have been developed, referred to as epigenetic clocks. While they appear to estimate biological age, it remains unclear whether the methylation changes used to train the clocks are a reflection of other underlying cellular or molecular processes, or whether methylation itself is involved in the ageing process. The precise aspects of ageing that the epigenetic clocks capture remain hidden and seem to vary between predictors. Nonetheless, the use of epigenetic clocks has opened the door towards studying biological ageing quantitatively, and new clocks and applications, such as forensics, appear frequently. In this review, we will discuss the range of epigenetic clocks available, their strengths and weaknesses, and their applicability to various scientific queries.

Epigenetic Age Acceleration Reflects Long-Term Cardiovascular Health

[Figure: see text].

Molecular markers of aging, exercise capacity, & physical activity in COPD

BACKGROUND

Exercise capacity (EC) and physical activity (PA) are independent, potentially modifiable predictors of clinical outcomes in COPD. Molecular measures of biological age may help characterize variability in EC and PA observed among COPD patients.

METHODS

Veterans with COPD (FEV₁/FVC<0.7 or emphysema on chest computed tomography) enrolled in 2 cohorts at VA Boston completed questionnaires, a 6-min walk distance (6MWD) for EC, and blood collection at enrollment. PA data (average daily step count) was collected using an HJ-720 ITC pedometer over ≥5 days. A subset of subjects returned for repeat assessment after 12 weeks. DNA methylation data was generated using the HumanMethylationEPIC platform; epigenetic estimates of biological age and age acceleration were generated using established algorithms. Multivariable models examined the associations between biological age, 6MWD, PA and future acute exacerbations (AEs), adjusting for chronological age, sex, race, smoking status, pack-years, body mass index, cohort, and estimated cell counts.

RESULTS

Subjects (n = 269) were predominantly male (98.5%), white (92.9%), and elderly (70.6 ± 8.5 years) with average FEV₁% of 57.7 ± 21.1, 6MWD of 374.3 ± 93.5 m, and daily steps of 3043.4 ± 2374 at baseline. In adjusted models, multiple measures of baseline epigenetic age and age acceleration were inversely associated with 6MWD; only GrimAge was inversely associated with PA. Longitudinal change in Hannum-Age was inversely associated with change in EC at 12 weeks (n = 94). No measures of biological age were significantly associated with prospective AEs over 1.3 ± 0.3 years.

CONCLUSIONS

Epigenetic measures of biological age are independent predictors of EC and PA, but not AEs, among individuals with COPD.

Stress-induced aberrations in sensory processing predict worse cognitive outcomes in healthy aging adults

It is well recognized that not all individuals age equivalently, with functional dependence attributable, at least in part, to stress accumulated across the lifespan. Amongst these dependencies are age-related declines in cognitive function, which may be the result of impaired inhibitory processing (e.g., sensory gating). Herein, we examined the unique roles of life and biological stress on somatosensory gating dynamics in 74 adults (22-72 years old). Participants completed a sensory gating paired-pulse electrical stimulation paradigm of the right median nerve during magnetoencephalography (MEG) and data were subjected to advanced oscillatory and time-domain analysis methods. We observed separable mechanisms by which increasing levels of life and biological stress predicted higher oscillatory gating ratios, indicative of age-related impairments in inhibitory function. Specifically, elevations in life stress significantly modulated the neural response to the first stimulation in the pair, while elevations in biological stress significantly modulated the neural response to the second stimulation in the pair. In contrast, neither elevations in life nor biological stress significantly predicted the gating of time-domain neural activity in the somatosensory cortex. Finally, our study is the first to link stress-induced decline in sensory gating to cognitive dysfunction, suggesting that gating paradigms may hold promise for detecting discrepant functional trajectories in age-related pathologies in the future.

Applying a Life Course Biological Age Framework to Improving the Care of Individuals With Adult Cancers: Review and Research Recommendations

Importance

The practice of oncology will increasingly involve the care of a growing population of individuals with midlife and late-life cancers. Managing cancer in these individuals is complex, based on differences in biological age at diagnosis. Biological age is a measure of accumulated life course damage to biological systems, loss of reserve, and vulnerability to functional deterioration and death. Biological age is important because it affects the ability to manage the rigors of cancer therapy, survivors' function, and cancer progression. However, biological age is not always clinically apparent. This review presents a conceptual framework of life course biological aging, summarizes candidate measures, and describes a research agenda to facilitate clinical translation to oncology practice.

Observations

Midlife and late-life cancers are chronic diseases that may arise from cumulative patterns of biological aging occurring over the life course. Before diagnosis, each new patient was on a distinct course of biological aging related to past exposures, life experiences, genetics, and noncancer chronic disease. Cancer and its treatments may also be associated with biological aging. Several measures of biological age, including p16INK4a, epigenetic age, telomere length, and inflammatory and body composition markers, have been used in oncology research. One or more of these measures may be useful in cancer care, either alone or in combination with clinical history and geriatric assessments. However, further research will be needed before biological age assessment can be recommended in routine practice, including determination of situations in which knowledge about biological age would change treatment, ascertaining whether treatment effects on biological aging are short-lived or persistent, and testing interventions to modify biological age, decrease treatment toxic effects, and maintain functional abilities.

Conclusions and Relevance

Understanding differences in biological aging could ultimately allow clinicians to better personalize treatment and supportive care, develop tailored survivorship care plans, and prescribe preventive or ameliorative therapies and behaviors informed by aging mechanisms.

Epigenetic Age in Young African American Adults With Perinatally Acquired HIV

BACKGROUND

Prior studies have measured accelerated aging in people with HIV using a DNA methylation (DNAm)-based biomarker of aging, "epigenetic age," but data are limited in African American (AA) young adults with perinatally acquired HIV infection (PHIV).

METHODS

We performed a cross-sectional study of AA young adults aged 20-35 years with PHIV (N = 31) and seronegative controls (N = 30) using DNAm measured in whole blood and cognitive function measured by the NIH Toolbox. Illumina EPIC array was used to measure DNAm age and accelerated aging markers including epigenetic age acceleration (EAA), as well as extrinsic (EEAA) and intrinsic (IEAA) EAA.

RESULTS

PHIV and controls did not differ by sex (45 vs. 43% male), chronological age (26.2 vs. 28.0 years), or ethnicity. Chronological age and DNAm age were correlated (r = 0.56, P < 0.01). PHIV had a higher mean EAA (2.86 ± 6.5 vs. -2.96 ± 3.9, P < 0.01) and EEAA (4.57 ± 13.0 vs. -4.72 ± 6.0, P < 0.01) than controls; however, IEAA was not different between groups. Among PHIV, EAA and EEAA were higher in those with HIV viral load ≥50 copies/mL than <50 copies/mL (EEA: 8.1 ± 5.2 vs. 0.11 ± 5.5, P = 0 < 0.01 and EEAA: 16.1 ± 10.6 vs. -1.83 ± 9.7, P < 0.01). We observed negative correlations (r = -0.36 to -0.31) between EEAA and executive function, attention, and language scores.

CONCLUSIONS

In conclusion, EAA in blood was observed in AA young adults with PHIV on ART using 2 measures, including EEAA which upweights the contribution of immunosenescent cell types. However, there was no evidence of age acceleration with a measure independent of cell type composition.

Aging biomarkers and the brain

Quantifying biological aging is critical for understanding why aging is the primary driver of morbidity and mortality and for assessing novel therapies to counter pathological aging. In the past decade, many biomarkers relevant to brain aging have been developed using various data types and modeling techniques. Aging involves numerous interconnected processes, and thus many complementary biomarkers are needed, each capturing a different slice of aging biology. Here we present a hierarchical framework highlighting how these biomarkers are related to each other and the underlying biological processes. We review those measures most studied in the context of brain aging: epigenetic clocks, proteomic clocks, and neuroimaging age predictors. Many studies have linked these biomarkers to cognition, mental health, brain structure, and pathology during aging. We also delve into the challenges and complexities in interpreting these biomarkers and suggest areas for further innovation. Ultimately, a robust mechanistic understanding of these biomarkers will be needed to effectively intervene in the aging process to prevent and treat age-related disease.

Maternal biological age assessed in early pregnancy is associated with gestational age at birth

Maternal age is an established predictor of preterm birth independent of other recognized risk factors. The use of chronological age makes the assumption that individuals age at a similar rate. Therefore, it does not capture interindividual differences that may exist due to genetic background and environmental exposures. As a result, there is a need to identify biomarkers that more closely index the rate of cellular aging. One potential candidate is biological age (BA) estimated by the DNA methylome. This study investigated whether maternal BA, estimated in either early and/or late pregnancy, predicts gestational age at birth. BA was estimated from a genome-wide DNA methylation platform using the Horvath algorithm. Linear regression methods assessed the relationship between BA and pregnancy outcomes, including gestational age at birth and prenatal perceived stress, in a primary and replication cohort. Prenatal BA estimates from early pregnancy explained variance in gestational age at birth above and beyond the influence of other recognized preterm birth risk factors. Sensitivity analyses indicated that this signal was driven primarily by self-identified African American participants. This predictive relationship was sensitive to small variations in the BA estimation algorithm. Benefits and limitations of using BA in translational research and clinical applications for preterm birth are considered.

Risk Factors Influencing the Outcomes of Kidney Re-Transplantation

BACKGROUND Our kidney transplant waitlist includes 20% re-transplantations (TX2). Knowing what to expect is a clinical obligation. MATERIAL AND METHODS We compared graft and patient survival of all 162 TX2 patients, transplanted 2000 to 2009, with 162 patients after first transplantation (TX1) matched for age, sex, living/non-living donation, and transplantation date. Patient follow-up was 10 years. RESULTS TX2 graft and patient survivals were inferior to TX1 (p<0.001 and p=0.047). TX2 patients had a longer cumulative dialysis vintage, more human leucocyte antigen (HLA) mismatches, more panel-reactive HLA antibodies, more often received induction therapy with rabbit-antithymocyte globulin (rATG), and had a lower body mass index (all p<0.05). Death from infection and graft failure by rejection was more frequent after TX2 (both p<0.05) but not after TX1. Multivariable Cox regression analysis revealed that both cohorts had graft failure and death risk associated with infection and cardiovascular disease, and graft failure by humoral rejection. However, only TX2 patients had an additional risk of graft failure with early inferior graft function and of patient death with ≥2 comorbidities. Moreover, Kaplan-Meier analysis showed that TX2 and not TX1 patients had a lower graft and patient survival associated with infection and with ≥2 comorbidities (all p<0.05). CONCLUSIONS Re-transplantation is associated with worse graft outcomes mainly because of immunologic and graft-quality reasons, although the high number of comorbidities and infection severities aside from cardiovascular disease drive mortality. The more frequent rATG induction of TX2 patients could promote infection by enhancing immunosuppression. By addressing comorbidities, outcomes could possibly be improved.

DNA methylation-based age clocks: From age prediction to age reversion

Aging as an irretrievable occurrence throughout the entire life is characterized by a progressive decline in physiological functionality and enhanced disease vulnerability. Numerous studies have demonstrated that epigenetic modifications, particularly DNA methylation (DNAm), correlate with aging and age-related diseases. Several investigations have attempted to predict chronological age using the age-related alterations in the DNAm of certain CpG sites. Here we categorize different studies that tracked the aging process in the DNAm landscape to show how epigenetic age clocks evolved from a chronological age estimator to an indicator of lifespan and healthspan. We also describe the health and disease predictive potential of estimated epigenetic age acceleration regarding different clinical conditions and lifestyle factors. Considering the revealed age-related epigenetic changes, the recent age-reprogramming strategies are discussed which are promising methods for resetting the aging clocks.

Inflammation, epigenetics, and metabolism converge to cell senescence and ageing: the regulation and intervention

Remarkable progress in ageing research has been achieved over the past decades. General perceptions and experimental evidence pinpoint that the decline of physical function often initiates by cell senescence and organ ageing. Epigenetic dynamics and immunometabolic reprogramming link to the alterations of cellular response to intrinsic and extrinsic stimuli, representing current hotspots as they not only (re-)shape the individual cell identity, but also involve in cell fate decision. This review focuses on the present findings and emerging concepts in epigenetic, inflammatory, and metabolic regulations and the consequences of the ageing process. Potential therapeutic interventions targeting cell senescence and regulatory mechanisms, using state-of-the-art techniques are also discussed.

In vivo biomarkers of structural and functional brain development and aging in humans

Brain aging is a major determinant of aging. Along with the aging population, prevalence of neurodegenerative diseases is increasing, therewith placing economic and social burden on individuals and society. Individual rates of brain aging are shaped by genetics, epigenetics, and prenatal environmental. Biomarkers of biological brain aging are needed to predict individual trajectories of aging and the risk for age-associated neurological impairments for developing early preventive and interventional measures. We review current advances of in vivo biomarkers predicting individual brain age. Telomere length and epigenetic clock, two important biomarkers that are closely related to the mechanistic aging process, have only poor deterministic and predictive accuracy regarding individual brain aging due to their high intra- and interindividual variability. Phenotype-related biomarkers of global cognitive function and brain structure provide a much closer correlation to age at the individual level. During fetal and perinatal life, autonomic activity is a unique functional marker of brain development. The cognitive and structural biomarkers also boast high diagnostic specificity for determining individual risks for neurodegenerative diseases.

Epigenetic Markers of Aging Predict the Neural Oscillations Serving Selective Attention

Chronological age remains an imperfect measure of accumulated physiological stress. Biological measures of aging may provide key advantages, allowing scientists focusing on age-related functional changes to use metrics derived from epigenetic factors like DNA methylation (DNAm), which could provide greater precision. Here we investigated the relationship between methylation-based age and an essential cognitive function that is known to exhibit age-related decline: selective attention. We found that DNAm-age predicted selective attention abilities and fully mediated the relationship between selective attention and chronological age. Using neuroimaging with magnetoencephalography, we found that gamma activity in the anterior cingulate was robustly predicted by DNAm-derived biological age, revealing the neural dynamics underlying this DNAm age-related cognitive decline. Anterior cingulate gamma activity also significantly predicted behavior on the selective attention task, indicating its functional relevance. These findings suggest that DNAm age may be a better predictor of cognitive and brain aging than more traditional chronological metrics.

DNAm-based signatures of accelerated aging and mortality in blood are associated with low renal function

BACKGROUND

The difference between an individual's chronological and DNA methylation predicted age (DNAmAge), termed DNAmAge acceleration (DNAmAA), can capture life-long environmental exposures and age-related physiological changes reflected in methylation status. Several studies have linked DNAmAA to morbidity and mortality, yet its relationship with kidney function has not been assessed. We evaluated the associations between seven DNAm aging and lifespan predictors (as well as GrimAge components) and five kidney traits (estimated glomerular filtration rate [eGFR], urine albumin-to-creatinine ratio [uACR], serum urate, microalbuminuria and chronic kidney disease [CKD]) in up to 9688 European, African American and Hispanic/Latino individuals from seven population-based studies.

RESULTS

We identified 23 significant associations in our large trans-ethnic meta-analysis (p < 1.43E-03 and consistent direction of effect across studies). Age acceleration measured by the Extrinsic and PhenoAge estimators, as well as Zhang's 10-CpG epigenetic mortality risk score (MRS), were associated with all parameters of poor kidney health (lower eGFR, prevalent CKD, higher uACR, microalbuminuria and higher serum urate). Six of these associations were independently observed in European and African American populations. MRS in particular was consistently associated with eGFR (β =  - 0.12, 95% CI = [- 0.16, - 0.08] change in log-transformed eGFR per unit increase in MRS, p = 4.39E-08), prevalent CKD (odds ratio (OR) = 1.78 [1.47, 2.16], p = 2.71E-09) and higher serum urate levels (β = 0.12 [0.07, 0.16], p = 2.08E-06). The "first-generation" clocks (Hannum, Horvath) and GrimAge showed different patterns of association with the kidney traits. Three of the DNAm-estimated components of GrimAge, namely adrenomedullin, plasminogen-activation inhibition 1 and pack years, were positively associated with higher uACR, serum urate and microalbuminuria.

CONCLUSION

DNAmAge acceleration and DNAm mortality predictors estimated in whole blood were associated with multiple kidney traits, including eGFR and CKD, in this multi-ethnic study. Epigenetic biomarkers which reflect the systemic effects of age-related mechanisms such as immunosenescence, inflammaging and oxidative stress may have important mechanistic or prognostic roles in kidney disease. Our study highlights new findings linking kidney disease to biological aging, and opportunities warranting future investigation into DNA methylation biomarkers for prognostic or risk stratification in kidney disease.

Postpartum sleep loss and accelerated epigenetic aging

BACKGROUND

Insufficient sleep has been linked to accelerated biological aging in adults, providing a possible mechanism through which sleep may influence disease risk. In the current paper, we test the hypothesis that short sleep in postpartum would predict older biological age in women one year post birth, as indicated by accelerated epigenetic aging.

METHODS

As part of a larger study of pregnancy and postpartum health (Healthy Babies Before Birth, HB3), 33 mothers provided blood samples for epigenetic aging clock estimates. intrinsic epigenetic age acceleration (IEAA), extrinsic apigenetic age acceleration, phenotypic epigenetic age acceleration (PEAA), GrimAge, DNAmPAI-1, and DNAm telomere length (TL) were calculated using established protocols. Sleep duration was categorized as insufficient sleep (<7 hours per night) or healthy sleep duration (7+ hours per night). Sleep quality was determined using the Pittsburgh Sleep Quality Index (Global score >5).

RESULTS

Maternal postpartum sleep duration at 6 months, but not 12 months, following a birth was predictive of older 12-month IEAA, B (SE) = 3.0 (1.2), P = .02, PEAA, B (SE) = 7.3 (2.0), P = .002, and DNAmTL, B (SE) = -0.18 (0.07), P = .01, but not other indices, all P> .127. Self-reported poor sleep quality at 6 and 12 months was not significantly related to epigenetic age.

CONCLUSIONS

These findings suggest that insufficient sleep duration during the early postpartum period is associated with accelerated biological aging. As the sample size is small, additional research is warranted with a larger sample size to replicate these findings.

Extremely Low Birth Weight and Accelerated Biological Aging

BACKGROUND AND OBJECTIVES

Extremely low birth weight (ELBW) (<1000 g) survivors are exposed to elevated levels of physiologic stress during their lives and may be susceptible to accelerated aging. Using the oldest known longitudinally followed cohort of ELBW survivors, we compared biological aging in this group using an epigenetic clock to a sample of matched normal birth weight (NBW) (>2500 g) control participants.

METHODS

Buccal cells were collected from 45 ELBW survivors and 49 NBW control participants at 30 to 35 years of age. Epigenetic age was calculated from the weighted average of DNA methylation at 353 cytosine-phosphate-guanine sequence within DNA sites, by using the Illumina Infinium Human Methylation EPIC 850k BeadChip array.

RESULTS

Before and after statistically adjusting for neurosensory impairment and the presence of chronic health conditions, a significant sex by birth weight group interaction was observed in the 353-site epigenetic-clock assay (P = .03), whereby ELBW men had a significantly older epigenetic age than NBW men (4.6 years; P = .01). Women born at ELBW were not found to be epigenetically older than their NBW peers.

CONCLUSIONS

The results of this study suggest that prenatal exposures may play an important role in aging, and that men born preterm may experience accelerated aging relative to their peers. We further highlight the need to monitor and promote the health of preterm survivors, with a particular focus on healthy aging across the life span.

DNA Methylation GrimAge and Incident Diabetes: The Coronary Artery Risk Development in Young Adults (CARDIA) Study

DNA methylation (DNAm)-based biological age (epigenetic age) has been suggested as a useful biomarker of age-related conditions including type 2 diabetes (T2D), and its newest iterations (GrimAge measurements) have shown early promise. In this study, we explored the association between epigenetic age and incident T2D in the context of their relationships with obesity. A total of 1,057 participants in the Coronary Artery Risk Development in Young Adults (CARDIA) study were included in the current analyses. We stratified the participants into three groups: normal weight, overweight, and obese. A 1-year increase of GrimAge was associated with higher 10-year (study years 15-25) incidence of T2D (odds ratio [OR] 1.06, 95% CI 1.01-1.11). GrimAge acceleration, which represents the deviation of GrimAge from chronological age, was derived from the residuals of a model of GrimAge and chronological age, and any GrimAge acceleration (positive GrimAA: having GrimAge older than chronological age) was associated with significantly higher odds of 10-year incidence of T2D in obese participants (OR 2.57, 95% CI 1.61-4.11). Cumulative obesity was estimated by years since obesity onset, and GrimAge partially mediated the statistical association between cumulative obesity and incident diabetes or prediabetes (proportion mediated = 8.0%). In conclusion, both older and accelerated GrimAge were associated with higher risk of T2D, particularly among obese participants. GrimAge also statistically mediated the associations between cumulative obesity and T2D. Our findings suggest that epigenetic age measurements with DNAm can potentially be used as a risk factor or biomarker associated with T2D development.

Epigenetic clocks reveal a rejuvenation event during embryogenesis followed by aging

The notion that the germ line does not age goes back to the 19th-century ideas of August Weismann. However, being metabolically active, the germ line accumulates damage and other changes over time, i.e., it ages. For new life to begin in the same young state, the germ line must be rejuvenated in the offspring. Here, we developed a multi-tissue epigenetic clock and applied it, together with other aging clocks, to track changes in biological age during mouse and human prenatal development. This analysis revealed a significant decrease in biological age, i.e., rejuvenation, during early stages of embryogenesis, followed by an increase in later stages. We further found that pluripotent stem cells do not age even after extensive passaging and that the examined epigenetic age dynamics is conserved across species. Overall, this study uncovers a natural rejuvenation event during embryogenesis and suggests that the minimal biological age (ground zero) marks the beginning of organismal aging.

Alcohol consumption and methylation-based measures of biological age

Epigenetic age acceleration is considered a measure of biological aging based on genome-wide patterns of DNA methylation. Although age acceleration has been associated with incidence of diseases and death, less is known about how it is related to lifestyle behaviors. Among 2,316 women, we evaluate associations between self-reported alcohol consumption and various metrics of epigenetic age acceleration. Recent average alcohol consumption was defined as the mean number of drinks consumed per week within the past year; lifetime average consumption was estimated as the mean number of drinks per year drinking. Whole blood genome-wide DNA methylation was measured with HumanMethylation450 BeadChips and used to assess four epigenetic clocks (Hannum, Horvath, PhenoAge, GrimAge) and their corresponding metrics of epigenetic age acceleration (Hannum AgeAccel, Horvath AgeAccel, PhenoAgeAccel, GrimAgeAccel). Although alcohol consumption showed little association with most age acceleration metrics, both lifetime and recent average consumption measures were positively associated with GrimAgeAccel (lifetime, per additional 135 drinks/year: β=0.30 years, 95% CI: 0.11, 0.48, p=0.002; recent, per additional 5 drinks/week: β=0.19 years, 95% CI: 0.01, 0.37, p=0.04). In a mutually adjusted model, only average lifetime alcohol consumption remained associated with GrimAgeAccel (lifetime, per additional 135 drinks/year: β=0.27 years, 95% CI: 0.04, 0.50, p=0.02; recent, per 5 additional drinks/week: β=0.05 years, 95% CI: -0.16, 0.26, p=0.64). Although alcohol use does not appear to be strongly associated with biological age measured by most epigenetic clocks, lifetime average consumption is associated with higher biological age assessed by the GrimAge epigenetic clock.

Combined healthy lifestyle score and risk of epigenetic aging: a discordant monozygotic twin study

We investigated whether lifestyle influences epigenetic aging in 143 monozygotic twin pairs discordant for the combined healthy lifestyle score. Twins were scored for four lifestyle factors as unhealthy or healthy; non-smoker, moderate drinker, adequate fruit and vegetable intake, and sufficient physical activity. The combined healthy lifestyle score was calculated for each participant by summing the binary score for each factor. Individual and co-twin analyses were used to assess the relationship between single or combined lifestyle scores, along with DNA methylation age acceleration (AA) calculated using Horvath’s and Li’s epigenetic clocks, focusing on AA and intrinsic epigenetic age acceleration (IEAA) measures. Compared with the twins that scored no or one healthy lifestyle point, those who scored four healthy lifestyle points had lower Li_IEAA with similar results observed in the co-twin analysis. No significant relationships were found in analyses based on Horvath’s clock, although the direction of correlations was consistent with that determined using Li’s clock. Smoking and drinking did not significantly affect DNA methylation AA; however, physical activity and intake of vegetables and fruits did, although the influence varied depending on the epigenetic clock. Our findings suggest that a healthy lifestyle may be an important way to delay aging and prevent age-related diseases.

Blood and skeletal muscle ageing determined by epigenetic clocks and their associations with physical activity and functioning

The aim of this study was to investigate the correspondence of different biological ageing estimates (i.e. epigenetic age) in blood and muscle tissue and their associations with physical activity (PA), physical function and body composition. Two independent cohorts (N = 139 and N = 47) were included, whose age span covered adulthood (23–69 years). Whole blood and m. vastus lateralis samples were collected, and DNA methylation was analysed. Four different DNA methylation age (DNAmAge) estimates were calculated using genome-wide methylation data and publicly available online tools. A novel muscle-specific methylation age was estimated using the R-package ‘MEAT’. PA was measured with questionnaires and accelerometers. Several tests were conducted to estimate cardiorespiratory fitness and muscle strength. Body composition was estimated by dual-energy X-ray absorptiometry. DNAmAge estimates from blood and muscle were highly correlated with chronological age, but different age acceleration estimates were weakly associated with each other. The monozygotic twin within-pair similarity of ageing pace was higher in blood (r = 0.617–0.824) than in muscle (r = 0.523–0.585). Associations of age acceleration estimates with PA, physical function and body composition were weak in both tissues and mostly explained by smoking and sex. The muscle-specific epigenetic clock MEAT was developed to predict chronological age, which may explain why it did not associate with functional phenotypes. The Horvath’s clock and GrimAge were weakly associated with PA and related phenotypes, suggesting that higher PA would be linked to accelerated biological ageing in muscle. This may, however, be more reflective of the low capacity of epigenetic clock algorithms to measure functional muscle ageing than of actual age acceleration. Based on our results, the investigated epigenetic clocks have rather low value in estimating muscle ageing with respect to the physiological adaptations that typically occur due to ageing or PA. Thus, further development of methods is needed to gain insight into muscle tissue-specific ageing and the underlying biological pathways.

Clonal haematopoiesis of indeterminate potential: intersections between inflammation, vascular disease and heart failure

Ageing is a major risk factor for the development of cardiovascular disease (CVD) and cancer. Whilst the cumulative effect of exposure to conventional cardiovascular risk factors is important, recent evidence highlights clonal haematopoiesis of indeterminant potential (CHIP) as a further key risk factor. CHIP reflects the accumulation of somatic, potentially pro-leukaemic gene mutations within haematopoietic stem cells over time. The most common mutations associated with CHIP and CVD occur in genes that also play central roles in the regulation of inflammation. While CHIP carriers have a low risk of haematological malignant transformation (<1% per year), their relative risk of mortality is increased by 40% and this reflects an excess of cardiovascular events. Evidence linking CHIP, inflammation and atherosclerotic disease has recently become better defined. However, there is a paucity of information about the role of CHIP in the development and progression of heart failure, particularly heart failure with preserved ejection fraction (HFpEF). While systemic inflammation plays a role in the pathophysiology of both heart failure with reduced and preserved ejection fraction (EF), it may be of greater relevance in the pathophysiology of HFpEF, which is also strongly associated with ageing. This review describes CHIP and its pathogenetic links with ageing, inflammation and CVD, while providing insight into its putative role in HFpEF.

High social status males experience accelerated epigenetic aging in wild baboons

Aging, for virtually all life, is inescapable. However, within populations, biological aging rates vary. Understanding sources of variation in this process is central to understanding the biodemography of natural populations. We constructed a DNA methylation-based age predictor for an intensively studied wild baboon population in Kenya. Consistent with findings in humans, the resulting 'epigenetic clock' closely tracks chronological age, but individuals are predicted to be somewhat older or younger than their known ages. Surprisingly, these deviations are not explained by the strongest predictors of lifespan in this population, early adversity and social integration. Instead, they are best predicted by male dominance rank: high-ranking males are predicted to be older than their true ages, and epigenetic age tracks changes in rank over time. Our results argue that achieving high rank for male baboons - the best predictor of reproductive success - imposes costs consistent with a 'live fast, die young' life-history strategy.

Longitudinal changes in epigenetic age in youth with perinatally acquired HIV and youth who are perinatally HIV-exposed uninfected

OBJECTIVES

To quantify the rate of change in epigenetic age compared with chronological age over time in youth with perinatally acquired HIV (YPHIV) and youth who are perinatally HIV-exposed uninfected (YPHEU).

DESIGN

Longitudinal study of 32 YPHIV and 8 YPHEU with blood samples collected at two time points at least 3 years apart.

METHODS

DNA methylation was measured using the Illumina MethylationEPIC array and epigenetic age was calculated using the Horvath method. Linear mixed effects models were fit to estimate the average change in epigenetic age for a 1-year change in chronological age separately for YPHIV and YPHEU.

RESULTS

Median age was 10.9 and 16.8 years at time 1 and 2, respectively. Groups were balanced by sex (51% male) and race (67% black). Epigenetic age increased by 1.23 years (95% CI 1.03--1.43) for YPHIV and 0.95 years (95% CI 0.74--1.17) for YPHEU per year increase in chronological age. Among YPHIV, in a model with chronological age, a higher area under the curve (AUC) viral load was associated with an increase in epigenetic age over time [2.19 years per log10 copies/ml, (95% CI 0.65--3.74)], whereas a higher time-averaged AUC CD4+ T-cell count was associated with a decrease in epigenetic age over time [-0.34 years per 100 cells/μl, (95% CI -0.63 to -0.06)] in YPHIV.

CONCLUSION

We observed an increase in the rate of epigenetic aging over time in YPHIV, but not in YPHEU. In YPHIV, higher viral load and lower CD4+ T-cell count were associated with accelerated epigenetic aging, emphasizing the importance of early and sustained suppressive treatment for YPHIV, who will receive lifelong ART.

Epigenetic Aging and Hematopoietic Cell Transplantation in Patients With Severe Aplastic Anemia

Cellular aging in hematopoietic cell transplantation (HCT) is important in the context of immune reconstitution and age-related complications. Recently, several DNA-methylation (DNAm)-based biomarkers of aging known as "epigenetic clocks" have been introduced as novel tools to predict cellular age. Here, we used Cox proportional hazards models to assess the possible associations of donor pre-HCT DNAm age, and its post-HCT changes, using the recently published lifespan-associated epigenetic clock known as "DNAm-GrimAge," with outcomes among patients with severe aplastic anemia (SAA). The study included 732 SAA patients from the Transplant Outcomes in Aplastic Anemia project, who underwent unrelated donor HCT and for whom a donor pre-HCT blood DNA sample was available; 41 also had a post-HCT sample collected at day 100. In multivariable analyses, we found similar associations for donor chronological age and pre-HCT DNAm-GrimAge with post-HCT survival (hazard ratio [HR] per decade = 1.13; 95% confidence interval [CI], 0.99-1.28; P = .07 and HR = 1.14; 95% CI, 0.99-1.28; P = .06, respectively). In donors with 10+ years of GrimAge acceleration (ie, deviation from expected DNAm age for chronological age), elevated risks of chronic graft versus host disease (HR = 2.4; 95% CI, 1.21-4.65; P = .01) and possibly post-HCT mortality (HR = 1.79; 95% CI, 0.96-3.33; P = .07) were observed. In the subset with post-HCT samples, we observed a significant increase in DNAm-GrimAge in the first 100 days after HCT (median change 12.5 years, range 1.4 to 26.4). Higher DNAm-GrimAge after HCT was associated with inferior survival (HR per year = 1.11; 95% CI, 1.02-1.21; P = .01), predominantly within the first year after HCT. This study highlights the possible role cellular aging may play in HCT outcomes.