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

The Latent Aging of Cells

As epigenetic clocks have evolved from powerful estimators of chronological aging to predictors of mortality and disease risk, it begs the question of what role DNA methylation plays in the aging process. We hypothesize that while it has the potential to serve as an informative biomarker, DNA methylation could also be a key to understanding the biology entangled between aging, (de)differentiation, and epigenetic reprogramming. Here we use an unsupervised approach to analyze time associated DNA methylation from both in vivo and in vitro samples to measure an underlying signal that ties these phenomena together. We identify a methylation pattern shared across all three, as well as a signal that tracks aging in tissues but appears refractory to reprogramming, suggesting that aging and reprogramming may not be fully mirrored processes.

Does diet influence aging? Evidence from animal studies

Nutrition profoundly influences the risk for many age-related diseases. Whether nutrition influences human aging biology directly is less clear. Studies in different animal species indicate that reducing food intake ("caloric restriction" [CR]) can increase lifespan and delay the onset of diseases and the biological hallmarks of aging. Obesity has been described as "accelerated aging" and therefore the lifespan and health benefits generated by CR in both aging and obesity may occur via similar mechanisms. Beyond calorie intake, studies based on nutritional geometry have shown that protein intake and the interaction between dietary protein and carbohydrates influence age-related health and lifespan. Studies where animals are calorically restricted by providing free access to diluted diets have had less impact on lifespan than those studies where animals are given a reduced aliquot of food each day and are fasting between meals. This has drawn attention to the role of fasting in health and aging, and exploration of the health effects of various fasting regimes. Although definitive human clinical trials of nutrition and aging would need to be unfeasibly long and unrealistically controlled, there is good evidence from animal experiments that some nutritional interventions based on CR, manipulating dietary macronutrients, and fasting can influence aging biology and lifespan.

Vascular dementia: From pathobiology to emerging perspectives

Vascular dementia (VaD) is the second most common type of dementia. VaD is synonymous with ageing, and its symptoms place a significant burden on the health and wellbeing of older people. Despite the identification of a substantial number of risk factors for VaD, the pathological mechanisms underpinning this disease remain to be fully elucidated. Consequently, a biogerontological imperative exists to highlight the modifiable lifestyle factors which can mitigate against the risk of developing VaD. This review will critically examine some of the factors which have been revealed to modulate VaD risk. The survey commences by providing an overview of the putative mechanisms which are associated with the pathobiology of VaD. Next, the factors which influence the risk of developing VaD are examined. Finally, emerging treatment avenues including epigenetics, the gut microbiome, and pro-longevity pharmaceuticals are discussed. By drawing this key evidence together, it is our hope that it can be used to inform future experimental investigations in this field.

Exploring the effects of Dasatinib, Quercetin, and Fisetin on DNA methylation clocks: a longitudinal study on senolytic interventions

Senolytics, small molecules targeting cellular senescence, have emerged as potential therapeutics to enhance health span. However, their impact on epigenetic age remains unstudied. This study aimed to assess the effects of Dasatinib and Quercetin (DQ) senolytic treatment on DNA methylation (DNAm), epigenetic age, and immune cell subsets. In a Phase I pilot study, 19 participants received DQ for 6 months, with DNAm measured at baseline, 3 months, and 6 months. Significant increases in epigenetic age acceleration were observed in first-generation epigenetic clocks and mitotic clocks at 3 and 6 months, along with a notable decrease in telomere length. However, no significant differences were observed in second and third-generation clocks. Building upon these findings, a subsequent investigation evaluated the combination of DQ with Fisetin (DQF), a well-known antioxidant and antiaging senolytic molecule. After one year, 19 participants (including 10 from the initial study) received DQF for 6 months, with DNAm assessed at baseline and 6 months. Remarkably, the addition of Fisetin to the treatment resulted in non-significant increases in epigenetic age acceleration, suggesting a potential mitigating effect of Fisetin on the impact of DQ on epigenetic aging. Furthermore, our analyses unveiled notable differences in immune cell proportions between the DQ and DQF treatment groups, providing a biological basis for the divergent patterns observed in the evolution of epigenetic clocks. These findings warrant further research to validate and comprehensively understand the implications of these combined interventions.

Developmental origins of psycho-cardiometabolic multimorbidity in adolescence and their underlying pathways through methylation markers: a two-cohort study

Understanding the biological mechanisms behind multimorbidity patterns in adolescence is important as they may act as intermediary risk factor for long-term health. We aimed to explore relationship between prenatal exposures and adolescent's psycho-cardiometabolic intermediary traits mediated through epigenetic biomarkers, using structural equation modeling (SEM). We used data from mother-child dyads from pregnancy and adolescents at 16-17 years from two prospective cohorts: Northern Finland Birth Cohort 1986 (NFBC1986) and Raine Study from Australia. Factor analysis was applied to generate two different latent factor structures: (a) prenatal exposures and (b) adolescence psycho-cardiometabolic intermediary traits. Furthermore, three types of epigenetic biomarkers were included: (1) DNA methylation score for maternal smoking during pregnancy (DNAmMSS), (2) DNAm age estimate PhenoAge and (3) DNAm estimate for telomere length (DNAmTL). Similar factor structure was observed between both cohorts yielding three prenatal factors, namely BMI (Body Mass Index), SOP (Socio-Obstetric-Profile), and Lifestyle, and four adolescent factors: Anthropometric, Insulin-Triglycerides, Blood Pressure, and Mental health. In the SEM pathways, stronger direct effects of F1prenatal-BMI (NFBC1986 = β: 0.27; Raine = β: 0.39) and F2prenatal-SOP (β: -0.11) factors were observed on adolescent psycho-cardiometabolic multimorbidity. We observed an indirect effect of prenatal latent factors through epigenetic markers on a psycho-cardiometabolic multimorbidity factor in Raine study (P < 0.05). The present study exemplifies an evidence-based approach in two different birth cohorts to demonstrate similar composite structure of prenatal exposures and psycho-cardiometabolic traits (despite cultural, social, and genetic differences) and a common plausible pathway between them through underlying epigenetic markers.

DNA repair-deficient premature aging models display accelerated epigenetic age

Several premature aging mouse models have been developed to study aging and identify interventions that can delay age-related diseases. Yet, it is still unclear whether these models truly recapitulate natural aging. Here, we analyzed DNA methylation in multiple tissues of four previously reported mouse models of premature aging (Ercc1, LAKI, Polg, and Xpg). We estimated DNA methylation (DNAm) age of these samples using the Horvath clock. The most pronounced increase in DNAm age could be observed in Ercc1 mice, a strain which exhibits a deficit in DNA nucleotide excision repair. Similarly, we detected an increase in epigenetic age in fibroblasts isolated from patients with progeroid syndromes associated with mutations in DNA excision repair genes. These findings highlight that mouse models with deficiencies in DNA repair, unlike other premature aging models, display accelerated epigenetic age, suggesting a strong connection between DNA damage and epigenetic dysregulation during aging.

Epigenetic drift underlies epigenetic clock signals, but displays distinct responses to lifespan interventions, development, and cellular dedifferentiation

Changes in DNA methylation with age are observed across the tree of life. The stereotypical nature of these changes can be modeled to produce epigenetic clocks capable of predicting chronological age with unprecedented accuracy. Despite the predictive ability of epigenetic clocks and their utility as biomarkers in clinical applications, the underlying processes that produce clock signals are not fully resolved, which limits their interpretability. Here, we develop a computational approach to spatially resolve the within read variability or "disorder" in DNA methylation patterns and test if age-associated changes in DNA methylation disorder underlie signals comprising epigenetic clocks. We find that epigenetic clock loci are enriched in regions that both accumulate and lose disorder with age, suggesting a link between DNA methylation disorder and epigenetic clocks. We then develop epigenetic clocks that are based on regional disorder of DNA methylation patterns and compare their performance to other epigenetic clocks by investigating the influences of development, lifespan interventions, and cellular dedifferentiation. We identify common responses as well as critical differences between canonical epigenetic clocks and those based on regional disorder, demonstrating a fundamental decoupling of epigenetic aging processes. Collectively, we identify key linkages between epigenetic disorder and epigenetic clocks and demonstrate the multifaceted nature of epigenetic aging in which stochastic processes occurring at non-random loci produce predictable outcomes.

Application of array-based age prediction models to post-mortem tissue samples

Since DNA methylation at specific CpG sites exhibits a strong age association, researchers have developed numerous age prediction models based on the methylation BeadChip array. These models harness epigenetic clocks that hold the potential to narrow down the search range for unknown suspects and unidentified victims. This study collected 180 post-mortem tissue samples comprising nine tissue types (blood, brain, heart, lung, liver, kidney, muscle, epidermis, and dermis) from autopsies of 20 Koreans aged 18-78. Subsequently, DNA methylation profiling was conducted using the Infinium MethylationEPIC array. We tested several array-based age prediction models using the data obtained from various tissues. The pan-tissue clock exhibited a moderately accurate prediction across all nine tissue types (MAE = 8.7 years, r = 0.88). Notably, the DNAm ages of the Hannum clock, the skin & blood clock, and the Zhang clock strongly correlated with the actual age in blood samples (MAE < approximately 5 years, r > 0.9). PhenoAge yielded an MAE of 10.1 years and an r-value of 0.92. The muscle-specific epigenetic clock, the MEAT package, demonstrated high prediction accuracy in muscle samples (MAE = 4.7 years, r = 0.93). Those previously reported array-based age prediction models were mainly constructed in Europeans but performed well in Koreans. In addition, tests involving various quantities of DNA and fragmented DNA have shown that DNA quantity and quality affected methylation measurements and age prediction results. However, robust age prediction models exist under low amounts of DNA and fragmented DNA conditions.

Measuring healthy ageing: current and future tools

Human ageing is a complex, multifactorial process characterised by physiological damage, increased risk of age-related diseases and inevitable functional deterioration. As the population of the world grows older, placing significant strain on social and healthcare resources, there is a growing need to identify reliable and easy-to-employ markers of healthy ageing for early detection of ageing trajectories and disease risk. Such markers would allow for the targeted implementation of strategies or treatments that can lessen suffering, disability, and dependence in old age. In this review, we summarise the healthy ageing scores reported in the literature, with a focus on the past 5 years, and compare and contrast the variables employed. The use of approaches to determine biological age, molecular biomarkers, ageing trajectories, and multi-omics ageing scores are reviewed. We conclude that the ideal healthy ageing score is multisystemic and able to encompass all of the potential alterations associated with ageing. It should also be longitudinal and able to accurately predict ageing complications at an early stage in order to maximize the chances of successful early intervention.

Hidalgo B, Aroke EN. Neighborhood Environment and Epigenetic Age: A Scoping Review

BACKGROUND

Interest in how the neighborhood environment impacts age-related health conditions has been increasing for decades. Epigenetic changes are environmentally derived modifications to the genome that alter the way genes function-thus altering health status. Epigenetic age, a biomarker for biological age, has been shown to be a useful predictor of several age-related health conditions. Consequently, its relation to the neighborhood environment has been the focus of a growing body of literature.

OBJECTIVE

We aimed to describe the scope of the evidence on the relationship between neighborhood environmental characteristics and epigenetic age.

METHODS

Using scoping review following methods established by Arksey and O'Malley, we first defined our research questions and searched the literature in PubMed, PsycINFO, and EMBASE. Next, we selected the literature to be included, and finally, we analyzed and summarized the information.

RESULTS

Nine articles met the inclusion criteria. Most studies examined deprivation as the neighborhood characteristic of interest. While all studies were observational in design, the articles included diverse participants, including men and women, adults and children, and multiple ethnicities. Results demonstrated a relationship between the neighborhood environment and epigenetic age, whether the characteristic of interest is socioeconomic or physical.

CONCLUSIONS

Overall, studies concluded there was a relationship between neighborhood characteristics and epigenetic age, whether the characteristic of interest was socioeconomic or physical. However, findings varied based on how the neighborhood characteristic and/or epigenetic age was measured. Furthermore, a paucity of investigations on physical characteristics was noticeable and warrants increased attention.

Associations Between Epigenetic Age Acceleration and microRNA Expression Among U.S. Firefighters

Epigenetic changes may be biomarkers of health. Epigenetic age acceleration (EAA), the discrepancy between epigenetic age measured via epigenetic clocks and chronological age, is associated with morbidity and mortality. However, the intersection of epigenetic clocks with microRNAs (miRNAs) and corresponding miRNA-based health implications have not been evaluated. We analyzed DNA methylation and miRNA profiles from blood sampled among 332 individuals enrolled across 2 U.S.-based firefighter occupational studies (2015-2018 and 2018-2020). We considered 7 measures of EAA in leukocytes (PhenoAge, GrimAge, Horvath, skin-blood, and Hannum epigenetic clocks, and extrinsic and intrinsic epigenetic age acceleration). We identified miRNAs associated with EAA using individual linear regression models, adjusted for sex, race/ethnicity, chronological age, and cell type estimates, and investigated downstream effects of associated miRNAs with miRNA enrichment analyses and genomic annotations. On average, participants were 38 years old, 88% male, and 75% non-Hispanic white. We identified 183 of 798 miRNAs associated with EAA (FDR q < 0.05); 126 with PhenoAge, 59 with GrimAge, 1 with Horvath, and 1 with the skin-blood clock. Among miRNAs associated with Horvath and GrimAge, there were 61 significantly enriched disease annotations including age-related metabolic and cardiovascular conditions and several cancers. Enriched pathways included those related to proteins and protein modification. We identified miRNAs associated with EAA of multiple epigenetic clocks. PhenoAge had more associations with individual miRNAs, but GrimAge and Horvath had greater implications for miRNA-associated pathways. Understanding the relationship between these epigenetic markers could contribute to our understanding of the molecular underpinnings of aging and aging-related diseases.

Investigation of the impact of biogeographic ancestry on DNA methylation based age predictions comparing a Middle East and a Central European population

DNA methylation based age prediction is a new method in the toolbox of forensic genetics. Typically, the method is applied in the course of police investigation e.g. to predict the age of an unknown person that has left a biological trace at a crime scene. The method can also be used to answer other forensic questions, for example to estimate the age of unknown human bodies in the course of the identification process. In the present study, we tested for a potential impact of biogeographic ancestry (BGA) on age predictions using five age dependent methylated CpG sites within the genetic regions of ELOVL2, MIR29B2CHG, FHL2, KLF14 and TRIM59. We collected 102 blood samples each from donors living in Iraq, Middle East (ME) and Germany, Central Europe (EU). Both sample sets were matched in sex and age ranging from 18 to 68 years with exactly one male and female sample per year of age. All samples were analyzed by bisulfite pyrosequencing applying a multiplex pre-amplification strategy based on a single input of 35 ng converted DNA in the PCR. For the CpGs in MIR29B2CHG, FHL2 and KLF14, we observed significantly different methylation levels between the two populations. While we were able to train two highly accurate prediction models for the respective population with mean absolute deviations between predicted and actual ages (MAD) of 3.34 years for the ME model, and 2.72 years for the EU model, we found an absolute prediction difference between the two population specific models of more than 4 years. A combined model for both populations compensated the methylation difference between the two populations, providing MADs of prediction of only 3.81 years for ME and 3.31 years for EU samples. In total, the results of the present study strongly support the benefit of BGA information for more reliable methylation based age predictions.

Differences in epigenetic age by HIV status among patients with a non-AIDS defining cancer

OBJECTIVE

People with HIV (PWH) are living longer and experiencing higher numbers of non-AIDS-defining cancers (NADC). Epigenetic aging biomarkers have been linked to cancer risk, and cancer is now a leading cause of death in PWH, but these biomarkers have not been investigated in PWH and cancer.

DESIGN

In order to compare epigenetic age by HIV status, HIV-uninfected participants were matched to PWH by reported age, tumor site, tumor sequence number, and cancer treatment status.

METHODS

DNA from blood was assayed using Illumina MethylationEPIC BeadChip, and we estimated immune cell composition and aging from three epigenetic clocks: Horvath, GrimAge, and epiTOC2. Age acceleration by clock was computed as the residual from the expected value, calculated using linear regression, for each study participant. Comparisons across HIV status used the Wilcoxon rank sum test. Hazard ratios and 95% confidence intervals for the association between age acceleration and survival in PWH were estimated with Cox regression.

RESULTS

Among 65 NADC participants with HIV and 64 without, biological age from epiTOC2 ( P  < 0.0001) and GrimAge ( P  = 0.017) was significantly higher in PWH. Biological age acceleration was significantly higher in PWH using epiTOC2 ( P  < 0.01) and GrimAge ( P  < 0.0001), with the difference in GrimAge remaining statistically significant after adjustment for immune cell composition. Among PWH, GrimAge acceleration was significantly associated with increased risk of death (hazard ratio 1.11; 95% confidence interval (CI) 1.04-1.18).

CONCLUSION

We observed a higher epigenetic age in PWH with a NADC diagnosis compared with their HIV-uninfected counterparts, as well as a significant association between this accelerated biological aging and survival for patients diagnosed with a NADC.

A roadmap for social determinants of health and biological nursing research in the National Institute of Nursing Research 2022-2026 Strategic Plan: Optimizing health and advancing health equity using antiracist framing

BACKGROUND

Health equity is essential for improving the well-being of all individuals and groups, and research remains a critical element for understanding barriers to health equity. While considering how to best support research that acknowledges current health challenges, it is crucial to understand the role of social justice frameworks within health equity research and the contributions of minoritized researchers. Additionally, there should be an increased understanding of the influence of social determinants of health on biological mechanisms.

PURPOSE

Biological health equity research seeks to understand and address health disparities among historically excluded populations.

DISCUSSION

While there are examples of studies in this area led by minoritized researchers, some individuals and groups remain understudied due to underfunding. Research within minoritized populations must be prioritized to authentically achieve health equity. Furthermore, there should be increased funding from National Institutes of Health to support minoritized researchers working in this area.

Biomarkers of aging in frailty and age-associated disorders: State of the art and future perspective

According to the Geroscience concept that organismal aging and age-associated diseases share the same basic molecular mechanisms, the identification of biomarkers of age that can efficiently classify people as biologically older (or younger) than their chronological (i.e. calendar) age is becoming of paramount importance. These people will be in fact at higher (or lower) risk for many different age-associated diseases, including cardiovascular diseases, neurodegeneration, cancer, etc. In turn, patients suffering from these diseases are biologically older than healthy age-matched individuals. Many biomarkers that correlate with age have been described so far. The aim of the present review is to discuss the usefulness of some of these biomarkers (especially soluble, circulating ones) in order to identify frail patients, possibly before the appearance of clinical symptoms, as well as patients at risk for age-associated diseases. An overview of selected biomarkers will be discussed in this regard, in particular we will focus on biomarkers related to metabolic stress response, inflammation, and cell death (in particular in neurodegeneration), all phenomena connected to inflammaging (chronic, low-grade, age-associated inflammation). In the second part of the review, next-generation markers such as extracellular vesicles and their cargos, epigenetic markers and gut microbiota composition, will be discussed. Since recent progresses in omics techniques have allowed an exponential increase in the production of laboratory data also in the field of biomarkers of age, making it difficult to extract biological meaning from the huge mass of available data, Artificial Intelligence (AI) approaches will be discussed as an increasingly important strategy for extracting knowledge from raw data and providing practitioners with actionable information to treat patients.

Profound DNA methylomic differences between single- and multi-fraction alpha irradiations of lung fibroblasts

BACKGROUND

Alpha (α)-radiation is a ubiquitous environmental agent with epigenotoxic effects. Human exposure to α-radiation at potentially harmful levels can occur repetitively over the long term via inhalation of naturally occurring radon gas that accumulates in enclosed spaces, or as a result of a single exposure from a nuclear accident. Alterations in epigenetic DNA methylation (DNAm) have been implicated in normal aging and cancer pathogenesis. Nevertheless, the effects of aberrations in the methylome of human lung cells following exposure to single or multiple α-irradiation events on these processes remain unexplored.

RESULTS

We performed genome-wide DNAm profiling of human embryonic lung fibroblasts from control and irradiated cells using americium-241 α-sources. Cells were α-irradiated in quadruplicates to seven doses using two exposure regimens, a single-fraction (SF) where the total dose was given at once, and a multi-fraction (MF) method, where the total dose was equally distributed over 14 consecutive days. Our results revealed that SF irradiations were prone to a decrease in DNAm levels, while MF irradiations mostly increased DNAm. The analysis also showed that the gene body (i.e., exons and introns) was the region most altered by both the SF hypomethylation and the MF hypermethylation. Additionally, the MF irradiations induced the highest number of differentially methylated regions in genes associated with DNAm biomarkers of aging, carcinogenesis, and cardiovascular disease. The DNAm profile of the oncogenes and tumor suppressor genes suggests that the fibroblasts manifested a defensive response to the MF α-irradiation. Key DNAm events of ionizing radiation exposure, including changes in methylation levels in mitochondria dysfunction-related genes, were mainly identified in the MF groups. However, these alterations were under-represented, indicating that the mitochondria undergo adaptive mechanisms, aside from DNAm, in response to radiation-induced oxidative stress.

CONCLUSIONS

We identified a contrasting methylomic profile in the lung fibroblasts α-irradiated to SF compared with MF exposures. These findings demonstrate that the methylome response of the lung cells to α-radiation is highly dependent on both the total dose and the exposure regimen. They also provide novel insights into potential biomarkers of α-radiation, which may contribute to the development of innovative approaches to detect, prevent, and treat α-particle-related diseases.

DNA Methylation Age Acceleration as a Potential Biomarker for Early Onset of Rapid Eye Movement Sleep Behavior Disorder

Rapid eye movement sleep behavior disorder (RBD) is the strongest prodromal marker for α-synucleinopathies. The Horvath DNA methylation age (DNAm-age) is an epigenetic clock reflecting biological aging. We found an association of DNAm-age acceleration with RBD age at onset at baseline (N = 162, B = -0.68, standard error [SE] = 0.12, p = 2.59e-08) and follow-up (n = 45, B = -1.07, SE = 0.21, p = 9.73e-06). The result remained similar after accounting for genetic risk factors (eg, RBD polygenic risk score). On average, RBD patients with faster versus slow/normal epigenetic aging had a 5.2-year earlier phenoconversion, and the Cox regression analysis revealed a trend toward significance (n = 53, hazard ratio = 1.05, 95% confidence interval = 0.99-1.11, p = 0.06). Our findings suggest that DNAm-age acceleration is a potential biomarker for earlier RBD onset. ANN NEUROL 2023.

NCAE: data-driven representations using a deep network-coherent DNA methylation autoencoder identify robust disease and risk factor signatures

Precision medicine relies on the identification of robust disease and risk factor signatures from omics data. However, current knowledge-driven approaches may overlook novel or unexpected phenomena due to the inherent biases in biological knowledge. In this study, we present a data-driven signature discovery workflow for DNA methylation analysis utilizing network-coherent autoencoders (NCAEs) with biologically relevant latent embeddings. First, we explored the architecture space of autoencoders trained on a large-scale pan-tissue compendium (n = 75 272) of human epigenome-wide association studies. We observed the emergence of co-localized patterns in the deep autoencoder latent space representations that corresponded to biological network modules. We determined the NCAE configuration with the strongest co-localization and centrality signals in the human protein interactome. Leveraging the NCAE embeddings, we then trained interpretable deep neural networks for risk factor (aging, smoking) and disease (systemic lupus erythematosus) prediction and classification tasks. Remarkably, our NCAE embedding-based models outperformed existing predictors, revealing novel DNA methylation signatures enriched in gene sets and pathways associated with the studied condition in each case. Our data-driven biomarker discovery workflow provides a generally applicable pipeline to capture relevant risk factor and disease information. By surpassing the limitations of knowledge-driven methods, our approach enhances the understanding of complex epigenetic processes, facilitating the development of more effective diagnostic and therapeutic strategies.

Genomic Instability and Epigenetic Changes during Aging

Aging is considered the deterioration of physiological functions along with an increased mortality rate. This scientific review focuses on the central importance of genomic instability during the aging process, encompassing a range of cellular and molecular changes that occur with advancing age. In particular, this revision addresses the genetic and epigenetic alterations that contribute to genomic instability, such as telomere shortening, DNA damage accumulation, and decreased DNA repair capacity. Furthermore, the review explores the epigenetic changes that occur with aging, including modifications to histones, DNA methylation patterns, and the role of non-coding RNAs. Finally, the review discusses the organization of chromatin and its contribution to genomic instability, including heterochromatin loss, chromatin remodeling, and changes in nucleosome and histone abundance. In conclusion, this review highlights the fundamental role that genomic instability plays in the aging process and underscores the need for continued research into these complex biological mechanisms.

Fail-tests of DNA methylation clocks, and development of a noise barometer for measuring epigenetic pressure of aging and disease

This study shows that Elastic Net (EN) DNA methylation (DNAme) clocks have low accuracy of predictions for individuals of the same age and a low resolution between healthy and disease cohorts; caveats inherent in applying linear model to non-linear processes. We found that change in methylation of cytosines with age is, interestingly, not the determinant for their selection into the clocks. Moreover, an EN clock's selected cytosines change when non-clock cytosines are removed from the training data; as expected from optimization in a machine learning (ML) context, but inconsistently with the identification of health markers in a biological context. To address these limitations, we moved from predictions to measurement of biological age, focusing on the cytosines that on average remain invariable in their methylation through lifespan, postulated to be homeostatically vital. We established that dysregulation of such cytosines, measured as the sums of standard deviations of their methylation values, quantifies biological noise, which in our hypothesis is a biomarker of aging and disease. We term this approach a "noise barometer" - the pressure of aging and disease on an organism. These noise-detecting cytosines are particularly important as sums of SD on the entire 450K DNAme array data yield a random pattern through chronology. Testing how many cytosines of the 450K arrays become noisier with age, we found that the paradigm of DNAme noise as a biomarker of aging and disease remarkably manifests in ~1/4 of the total. In that large set even the cytosines that have on average constant methylation through age show increased SDs and can be used as noise detectors of the barometer.

Human immune phenotyping reveals accelerated aging in type 1 diabetes

The proportions and phenotypes of immune cell subsets in peripheral blood undergo continual and dramatic remodeling throughout the human life span, which complicates efforts to identify disease-associated immune signatures in type 1 diabetes (T1D). We conducted cross-sectional flow cytometric immune profiling on peripheral blood from 826 individuals (stage 3 T1D, their first-degree relatives, those with ≥2 islet autoantibodies, and autoantibody-negative unaffected controls). We constructed an immune age predictive model in unaffected participants and observed accelerated immune aging in T1D. We used generalized additive models for location, shape, and scale to obtain age-corrected data for flow cytometry and complete blood count readouts, which can be visualized in our interactive portal (ImmScape); 46 parameters were significantly associated with age only, 25 with T1D only, and 23 with both age and T1D. Phenotypes associated with accelerated immunological aging in T1D included increased CXCR3+ and programmed cell death 1-positive (PD-1+) frequencies in naive and memory T cell subsets, despite reduced PD-1 expression levels on memory T cells. Phenotypes associated with T1D after age correction were predictive of T1D status. Our findings demonstrate advanced immune aging in T1D and highlight disease-associated phenotypes for biomarker monitoring and therapeutic interventions.

Targeting epigenetics: A novel promise for Alzheimer's disease treatment

So far, the search for a cure for Alzheimer Disease (AD) has been unsuccessful. The only approved drugs attenuate some symptoms, but do not halt the progress of this disease, which affects 50 million people worldwide and will increase its incidence in the coming decades. Such scenario demands new therapeutic approaches to fight against this devastating dementia. In recent years, multi-omics research and the analysis of differential epigenetic marks in AD subjects have contributed to our understanding of AD; however, the impact of epigenetic research is yet to be seen. This review integrates the most recent data on pathological processes and epigenetic changes relevant for aging and AD, as well as current therapies targeting epigenetic machinery in clinical trials. Evidence shows that epigenetic modifications play a key role in gene expression, which could provide multi-target preventative and therapeutic approaches in AD. Both novel and repurposed drugs are employed in AD clinical trials due to their epigenetic effects, as well as increasing number of natural compounds. Given the reversible nature of epigenetic modifications and the complexity of gene-environment interactions, the combination of epigenetic-based therapies with environmental strategies and drugs with multiple targets might be needed to properly help AD patients.

Epigenetic clocks and research implications of the lack of data on whom they have been developed: a review of reported and missing sociodemographic characteristics

Epigenetic clocks are increasingly being used as a tool to assess the impact of a wide variety of phenotypes and exposures on healthy ageing, with a recent focus on social determinants of health. However, little attention has been paid to the sociodemographic characteristics of participants on whom these clocks have been based. Participant characteristics are important because sociodemographic and socioeconomic factors are known to be associated with both DNA methylation variation and healthy ageing. It is also well known that machine learning algorithms have the potential to exacerbate health inequities through the use of unrepresentative samples - prediction models may underperform in social groups that were poorly represented in the training data used to construct the model. To address this gap in the literature, we conducted a review of the sociodemographic characteristics of the participants whose data were used to construct 13 commonly used epigenetic clocks. We found that although some of the epigenetic clocks were created utilizing data provided by individuals from different ages, sexes/genders, and racialized groups, sociodemographic characteristics are generally poorly reported. Reported information is limited by inadequate conceptualization of the social dimensions and exposure implications of gender and racialized inequality, and socioeconomic data are infrequently reported. It is important for future work to ensure clear reporting of tangible data on the sociodemographic and socioeconomic characteristics of all the participants in the study to ensure that other researchers can make informed judgements about the appropriateness of the model for their study population.

Measuring healthy ageing: current and future tools

Human ageing is a complex, multifactorial process characterised by physiological damage, increased risk of age-related diseases and inevitable functional deterioration. As the population of the world grows older, placing significant strain on social and healthcare resources, there is a growing need to identify reliable and easy-to-employ markers of healthy ageing for early detection of ageing trajectories and disease risk. Such markers would allow for the targeted implementation of strategies or treatments that can lessen suffering, disability, and dependence in old age. In this review, we summarise the healthy ageing scores reported in the literature, with a focus on the past 5 years, and compare and contrast the variables employed. The use of approaches to determine biological age, molecular biomarkers, ageing trajectories, and multi-omics ageing scores are reviewed. We conclude that the ideal healthy ageing score is multisystemic and able to encompass all of the potential alterations associated with ageing. It should also be longitudinal and able to accurately predict ageing complications at an early stage in order to maximize the chances of successful early intervention.

On the thermodynamics of DNA methylation process

DNA methylation is an epigenetic mechanism that plays important roles in various biological processes including transcriptional and post-transcriptional regulation, genomic imprinting, aging, and stress response to environmental changes and disease. Consistent with thermodynamic principles acting within living systems and the application of maximum entropy principle, we propose a theoretical framework to understand and decode the DNA methylation process. A central tenet of this argument is that the probability density function of DNA methylation information-divergence summarizes the statistical biophysics underlying spontaneous methylation background and implicitly bears on the channel capacity of molecular machines conforming to Shannon's capacity theorem. On this theoretical basis, contributions from the molecular machine (enzyme) logical operations to Gibb entropy (S) and Helmholtz free energy (F) are intrinsic. Application to the estimations of S on datasets from Arabidopsis thaliana suggests that, as a thermodynamic state variable, individual methylome entropy is completely determined by the current state of the system, which in biological terms translates to a correspondence between estimated entropy values and observable phenotypic state. In patients with different types of cancer, results suggest that a significant information loss occurs in the transition from differentiated (healthy) tissues to cancer cells. This type of analysis may have important implications for early-stage diagnostics. The analysis of entropy fluctuations on experimental datasets revealed existence of restrictions on the magnitude of genome-wide methylation changes originating by organismal response to environmental changes. Only dysfunctional stages observed in the Arabidopsis mutant met1 and in cancer cells do not conform to these rules.

How can we modulate aging through nutrition and physical exercise? An epigenetic approach

The World Health Organization predicts that by 2050, 2.1 billion people worldwide will be over 60 years old, a drastic increase from only 1 billion in 2019. Considering these numbers, strategies to ensure an extended "healthspan" or healthy longevity are urgently needed. The present study approaches the promotion of healthspan from an epigenetic perspective. Epigenetic phenomena are modifiable in response to an individual's environmental exposures, and therefore link an individual's environment to their gene expression pattern. Epigenetic studies demonstrate that aging is associated with decondensation of the chromatin, leading to an altered heterochromatin structure, which promotes the accumulation of errors. In this review, we describe how aging impacts epigenetics and how nutrition and physical exercise can positively impact the aging process, from an epigenetic point of view. Canonical histones are replaced by histone variants, concomitant with an increase in histone post-translational modifications. A slight increase in DNA methylation at promoters has been observed, which represses transcription of previously active genes, in parallel with global genome hypomethylation. Aging is also associated with deregulation of gene expression - usually provided by non-coding RNAs - leading to both the repression of previously transcribed genes and to the transcription of previously repressed genes. Age-associated epigenetic events are less common in individuals with a healthy lifestyle, including balanced nutrition, caloric restriction and physical exercise. Healthy aging is associated with more tightly condensed chromatin, fewer PTMs and greater regulation by ncRNAs.

Transdiagnostic evaluation of epigenetic age acceleration and burden of psychiatric disorders

Different psychiatric disorders as well as exposure to adverse life events have individually been associated with multiple age-related diseases and mortality. Age acceleration in different epigenetic clocks can serve as biomarker for such risk and could help to disentangle the interplay of psychiatric comorbidity and early adversity on age-related diseases and mortality. We evaluated five epigenetic clocks (Horvath, Hannum, PhenoAge, GrimAge and DunedinPoAm) in a transdiagnostic psychiatric sample using epigenome-wide DNA methylation data from peripheral blood of 429 subjects from two studies at the Max Planck Institute of Psychiatry. Burden of psychiatric disease, represented by a weighted score, was significantly associated with biological age acceleration as measured by GrimAge and DunedinPoAm (R2-adj. 0.22 and 0.33 for GrimAge and DunedinPoAm, respectively), but not the other investigated clocks. The relation of burden of psychiatric disease appeared independent of differences in socioeconomic status and medication. Our findings indicate that increased burden of psychiatric disease may associate with accelerated biological aging. This highlights the importance of medical management of patients with multiple psychiatric comorbidities and the potential usefulness of specific epigenetic clocks for early detection of risk and targeted intervention to reduce mortality in psychiatric patients.

Accelerated epigenetic aging and myopenia in young adult cancer survivors

BACKGROUND

Young adult cancer survivors experience early aging-related morbidities and mortality. Biological aging biomarkers may identify at-risk survivors and increase our understanding of mechanisms underlying this accelerated aging.

METHODS

Using an observational study design, we cross-sectionally measured DNA methylation-based epigenetic age in young adult cancer survivors at a tertiary, academic state cancer hospital. Participants were a convenience sample of consecutively enrolled survivors of childhood, adolescent, and young adult cancers treated with either an anthracycline or alkylating agent, and who were at least 3 months post-treatment. Similarly aged healthy comparators were consecutively enrolled. Cancer treatment and treatment intensity were compared to DNA methylation-based epigenetic age and pace of aging.

RESULTS

Sixty survivors (58 completing assessments, mean age 20.5 years, range 18-29) and 27 comparators (mean age 20 years, range 17-29) underwent DNA methylation measurement. Survivors were predominantly female (62%) and white (60%) and averaged nearly 6 years post-treatment (range 0.2-25 years). Both epigenetic age (AgeAccelGrim: 1.5 vs. -2.4, p < 0.0001; AgeAccelPheno 2.3 vs. -3.8, p = 0.0013) and pace of aging (DunedinPACE 0.99 vs. 0.83, p < 0.0001) were greater in survivors versus comparators. In case-case adjusted analysis, compared to survivors with normal muscle mass, myopenic survivors had higher AgeAccelGrim (2.2 years, 95% CI 0.02-4.33, p = 0.02), AgeAccelPheno (6.2 years, 2.36-10.09, p < 0.001), and DunedinPACE (0.11, 0.05-0.17, p < 0.001).

CONCLUSIONS

Epigenetic age is older and pace of aging is faster in young adult cancer survivors compared to noncancer peers, which is evident in the early post-therapy period. Survivors with physiological impairment demonstrate greater epigenetic age advancement. Measures of epigenetic age may identify young adult survivors at higher risk for poor functional and health outcomes.

Genetic and Epigenetic Study of Monozygotic Twins Affected by Parkinson’s Disease

Background: Genetic and epigenetic modifiers of age at onset of Parkinson’s disease (PD) are largely unknown. It remains unclear whether DNA methylation (DNAm) age acceleration is linked to age at onset in PD patients of different ethnicities with a similar genetic background. We aim to characterize the clinical, genomic and epigenomic features of three pairs of Chinese monozygotic twins discordant for PD onset by up to 10 years. Methods: We conducted whole genome sequencing, multiplex ligation-dependent probe amplification and genome-wide DNAm array to evaluate the three pairs of Chinese monozygotic twins discordant for age at onset of PD (families A–C). Results: We identified two heterozygous PRKN mutations (exon 2–4 deletion and p.Met1Thr) in PD affected members of one family. Somatic mutation analyses of investigated families did not reveal any variants that could explain the phenotypic discordance in the twin pairs. Of note, our epigenetic study revealed that the twins with earlier-onset had a trend of faster DNAm age acceleration than the later-onset/asymptomatic twins, but without statistical significance. Conclusion: The link between DNAm age acceleration and PD onset in Chinese patients should be interpreted with cautious, and need to be further verified in an extended PD cohort with similar genetic background.

Potential reversal of biological age following an 8-week methylation-supportive diet and lifestyle program: a case series

Here we report on a case series of six women who completed a methylation-supportive diet and lifestyle program designed to impact DNA methylation and measures of biological aging. The intervention consisted of an 8-week program that included diet, sleep, exercise and relaxation guidance, supplemental probiotics and phytonutrients and nutritional coaching. DNA methylation and biological age analysis (Horvath DNAmAge clock (2013), normalized using the SeSAMe pipeline [a]) was conducted on blood samples at baseline and at the end of the 8-week period. Five of the six participants exhibited a biological age reduction of between 1.22 and 11.01 years from their baseline biological age. There was a statistically significant (p=.039) difference in the participants' mean biological age before (55.83 years) and after (51.23 years) the 8-week diet and lifestyle intervention, with an average decrease of 4.60 years. The average chronological age at the start of the program was 57.9 years and all but one participant had a biological age younger than their chronological age at the start of the program, suggesting that biological age changes were unrelated to disease improvement and instead might be attributed to underlying aging mechanisms.

DNA Methylation as a Biomarker for Monitoring Disease Outcome in Patients with Hypovitaminosis and Neurological Disorders

DNA methylation remains an under-recognized diagnostic biomarker for several diseases, including neurodegenerative disorders. In this study, we examined differences in global DNA methylation (5mC) levels in serum samples from patients during the initial- and the follow-up visits. Each patient underwent a blood analysis and neuropsychological assessments. The analysis of 5mC levels revealed two categories of patients; Group A who, during the follow-up, had increased 5mC levels, and Group B who had decreased 5mC levels. Patients with low Fe-, folate-, and vitamin B12- levels during the initial visit showed increased levels of 5mC after treatment when assessed during the follow-up. During the follow-up, 5mC levels in Group A patients increased after treatment for hypovitaminosis with the nutraceutical compounds Animon Complex and MineraXin Plus. 5mC levels were maintained during the follow-up in Group A patients treated for neurological disorders with the bioproducts AtreMorine and NeoBrainine. There was a positive correlation between 5mC levels and MMSE scores, and an inverse correlation between 5mC and ADAS-Cog scores. This expected correlation was observed in Group A patients only. Our study appears to indicate that 5mC has a diagnostic value as a biomarker across different pathologies.

Risk Factors of Severe COVID-19: A Review of Host, Viral and Environmental Factors

The clinical course and outcome of COVID-19 are highly variable, ranging from asymptomatic infections to severe disease and death. Understanding the risk factors of severe COVID-19 is relevant both in the clinical setting and at the epidemiological level. Here, we provide an overview of host, viral and environmental factors that have been shown or (in some cases) hypothesized to be associated with severe clinical outcomes. The factors considered in detail include the age and frailty, genetic polymorphisms, biological sex (and pregnancy), co- and superinfections, non-communicable comorbidities, immunological history, microbiota, and lifestyle of the patient; viral genetic variation and infecting dose; socioeconomic factors; and air pollution. For each category, we compile (sometimes conflicting) evidence for the association of the factor with COVID-19 outcomes (including the strength of the effect) and outline possible action mechanisms. We also discuss the complex interactions between the various risk factors.

Pilot Study of Second-Generation DNA Methylation Epigenetic Markers in Relation to Cognitive and Neuropsychiatric Symptoms in Older Adults

BACKGROUND

Associations between epigenetic aging with cognitive aging and neuropsychiatric measures are not well-understood.

OBJECTIVE

1) To assess cross-sectional correlations between second-generation DNA methylation (DNAm)-based clocks of healthspan and lifespan (i.e., GrimAge, PhenoAge, and DNAm-based estimator of telomere length [DNAmTL]) and cognitive and neuropsychiatric measures; 2) To examine longitudinal associations between change in DNAm markers and change in cognition over 2 years.

METHODS

Participants were members of VITAL-DEP (VITamin D and OmegA-3 TriaL- Depression Endpoint Prevention) study. From previously ascertained cognitive groups (i.e., cognitively normal and mild cognitive impairment), we randomly selected 45 participants, aged≥60 years, who completed in-person neuropsychiatric assessments at baseline and 2 years. The primary outcome was global cognitive score (averaging z-scores of 9 tests). Neuropsychiatric Inventory severity scores were mapped from neuropsychiatric symptoms (NPS) from psychological scales and structured diagnostic interviews. DNAm was assayed using Illumina MethylationEPIC 850K BeadChip at baseline and 2 years. We calculated baseline partial Spearman correlations between DNAm markers and cognitive and NPS measures. We constructed multivariable linear regression models to examine longitudinal relations between DNAm markers and cognition.

RESULTS

At baseline, we observed a suggestive negative correlation between GrimAge clock markers and global cognition but no signal between DNAm markers and NPS measures. Over 2 years: each 1-year increase in DNAmGrimAge was significantly associated with faster declines in global cognition; each 100-base pair increase in DNAmTL was significantly associated with better global cognition.

CONCLUSION

We found preliminary evidence of cross-sectional and longitudinal associations between DNAm markers and global cognition.

Within subject cross-tissue analyzes of epigenetic clocks in substance use disorder postmortem brain and blood

There is a possible accelerated biological aging in patients with substance use disorders (SUD). The evaluation of epigenetic clocks, which are accurate estimators of biological aging based on DNA methylation changes, has been limited to blood tissue in patients with SUD. Consequently, the impact of biological aging in the brain of individuals with SUD remains unknown. In this study, we evaluated multiple epigenetic clocks (DNAmAge, DNAmAgeHannum, DNAmAgeSkinBlood, DNAmPhenoAge, DNAmGrimAge, and DNAmTL) in individuals with SUD (n = 42), including alcohol (n = 10), opioid (n = 19), and stimulant use disorder (n = 13), and controls (n = 10) in postmortem brain (prefrontal cortex) and blood tissue obtained from the same individuals. We found a higher DNAmPhenoAge (β = 0.191, p-value = 0.0104) and a nominally lower DNAmTL (β = -0.149, p-value = 0.0603) in blood from individuals with SUD compared to controls. SUD subgroup analysis showed a nominally lower brain DNAmTL in subjects with alcohol use disorder, compared to stimulant use disorder and controls (β = 0.0150, p-value = 0.087). Cross-tissue analyzes indicated a lower blood DNAmTL and a higher blood DNAmAge compared to their respective brain values in the SUD group. This study highlights the relevance of tissue specificity in biological aging studies and suggests that peripheral measures of epigenetic clocks in SUD may depend on the specific type of drug used.

Sex differences in epigenetic age in Mediterranean high longevity regions

Sex differences in aging manifest in disparities in disease prevalence, physical health, and lifespan, where women tend to have greater longevity relative to men. However, in the Mediterranean Blue Zones of Sardinia (Italy) and Ikaria (Greece) are regions of centenarian abundance, male-female centenarian ratios are approximately one, diverging from the typical trend and making these useful regions in which to study sex differences of the oldest old. Additionally, these regions can be investigated as examples of healthy aging relative to other populations. DNA methylation (DNAm)-based predictors have been developed to assess various health biomarkers, including biological age, Pace of Aging, serum interleukin-6 (IL-6), and telomere length. Epigenetic clocks are biological age predictors whose deviation from chronological age has been indicative of relative health differences between individuals, making these useful tools for interrogating these differences in aging. We assessed sex differences between the Horvath, Hannum, GrimAge, PhenoAge, Skin and Blood, and Pace of Aging predictors from individuals in two Mediterranean Blue Zones and found that men displayed positive epigenetic age acceleration (EAA) compared to women according to all clocks, with significantly greater rates according to GrimAge (β = 3.55; p = 1.22 × 10^-12), Horvath (β = 1.07; p = 0.00378) and the Pace of Aging (β = 0.0344; p = 1.77 × 10^-08). Other DNAm-based biomarkers findings indicated that men had lower DNAm-predicted serum IL-6 scores (β = -0.00301, p = 2.84 × 10^-12), while women displayed higher DNAm-predicted proportions of regulatory T cells than men from the Blue Zone (p = 0.0150, 95% Confidence Interval [0.00131, 0.0117], Cohen's d = 0.517). All clocks showed better correlations with chronological age in women from the Blue Zones than men, but all clocks showed large mean absolute errors (MAE >30 years) in both sexes, except for PhenoAge (MAE <5 years). Thus, despite their equal survival to older ages in these Mediterranean Blue Zones, men in these regions remain biologically older by most measured DNAm-derived metrics than women, with the exception of the IL-6 score and proportion of regulatory T cells.

Dimensions of childhood adversity differentially affect biological aging in major depression

Adverse childhood experiences have been consistently linked with physical and mental health disorders in adulthood that may be mediated, in part, via the effects of such exposures on biological aging. Using recently developed "epigenetic clocks", which provide an estimate of biological age, several studies have demonstrated a link between the cumulative exposure to childhood adversities and accelerated epigenetic aging. However, not all childhood adversities are equivalent and less is known about how distinct dimensions of childhood adversity relate to epigenetic aging metrics. Using two measures of childhood adversity exposure, we assess how the dimensions of Maltreatment and Household Dysfunction relate to epigenetic aging using two "second-generation" clocks, GrimAge and PhenoAge, in a cohort of unmedicated somatically healthy adults with moderate to severe major depression (n = 82). Our results demonstrate that the dimension of Maltreatment is associated with epigenetic age acceleration (EAA) using the PhenoAge but not the GrimAge clock. This association was observed using both the Childhood Trauma questionnaire (CTQ; β = 0.272, p = 0.013) and the Adverse Childhood Experiences (ACEs) questionnaire (β = 0.307, p = 0.005) and remained significant when adjusting for exposure to the dimension of Household Dysfunction (β = 0.322, p = 0.009). In contrast, the dimension of Household Dysfunction is associated with epigenetic age deceleration (β = -0.194, p = 0.083) which achieved significance after adjusting for exposure to the dimension of Maltreatment (β = -0.304, p = 0.022). This study is the first to investigate these effects among individuals with Major Depressive Disorder and suggests that these dimensions of adversity may be associated with disease via distinct biological mechanisms.

Parkinson's disease-associated, sex-specific changes in DNA methylation at PARK7 (DJ-1), SLC17A6 (VGLUT2), PTPRN2 (IA-2β), and NR4A2 (NURR1) in cortical neurons

Evidence for epigenetic regulation playing a role in Parkinson's disease (PD) is growing, particularly for DNA methylation. Approximately 90% of PD cases are due to a complex interaction between age, genes, and environmental factors, and epigenetic marks are thought to mediate the relationship between aging, genetics, the environment, and disease risk. To date, there are a small number of published genome-wide studies of DNA methylation in PD, but none accounted for cell type or sex in their analyses. Given the heterogeneity of bulk brain tissue samples and known sex differences in PD risk, progression, and severity, these are critical variables to account for. In this genome-wide analysis of DNA methylation in an enriched neuronal population from PD postmortem parietal cortex, we report sex-specific PD-associated methylation changes in PARK7 (DJ-1), SLC17A6 (VGLUT2), PTPRN2 (IA-2β), NR4A2 (NURR1), and other genes involved in developmental pathways, neurotransmitter packaging and release, and axon and neuron projection guidance.

Epigenetic Clock Acceleration Is Linked to Age at Onset of Parkinson's Disease

BACKGROUND

Aging is the strongest risk factor for Parkinson's disease (PD), which is a clinically heterogeneous movement disorder with highly variable age at onset. DNA methylation age (DNAm age) is an epigenetic clock that could reflect biological aging.

OBJECTIVES

The aim was to evaluate whether PD age at onset is associated with DNAm-age acceleration (difference between DNAm age and chronological age).

METHODS

We used the genome-wide Infinium MethylationEPIC array to assess DNAm age in discovery (n = 96) and replication (n = 182) idiopathic PD cohorts and a unique longitudinal LRRK2 cohort (n = 220) at four time points over a 3-year period, comprising 91 manifesting and 129 nonmanifesting G2019S carriers at baseline. Cox proportional hazard regression and multivariate linear regression were used to evaluate the relation between DNAm-age acceleration and PD age at onset, which was highly variable in manifesting G2019S carriers (36-75 years) and both idiopathic PD cohorts (26-77 and 35-81 years).

RESULTS

DNAm-age acceleration remained steady over the 3-year period in most G2019S carriers. It was strongly associated with age at onset in the LRRK2 cohort (P = 2.25 × 10^-15 ) and discovery idiopathic PD cohort (P = 5.39 × 10^-9 ), suggesting that every 5-year increase in DNAm-age acceleration is related to about a 6-year earlier onset. This link was replicated in an independent idiopathic PD cohort (P = 1.91 × 10^-10 ). In each cohort, the faster-aging group has an increased hazard for an earlier onset (up to 255%).

CONCLUSIONS

This study is the first to demonstrate that DNAm-age acceleration is related to PD age at onset, which could be considered in disease-modifying clinical trials. Future studies should evaluate the stability of DNAm-age acceleration over longer time periods, especially for phenoconverters from nonmanifesting to manifesting individuals. © 2022 International Parkinson and Movement Disorder Society.

Digital methylation assessments of alcohol and cigarette consumption account for common variance in accelerated epigenetic ageing

Smoking and Heavy Alcohol Consumption (HAC) are established risk factors for myriad complex disorders of ageing. Yet many prior studies of Epigenetic Ageing (EA) have shown only modest effects of smoking and drinking on accelerated ageing. One potential reason for this conundrum might be the reliance of some prior EA studies on self-reported substance use, which may be unreliable in many samples. To test whether novel, non-self-reported indices would show a stronger association of smoking and HAC to EA, we used methylation sensitive digital PCR (MSdPCR) and data from 437 African American subjects from Wave 7 of the Family and Community Health Study Offspring Cohort to examine the effects of subjective and objective measures of smoking and HAC on 7 indices of EA. Because of limited overall correlations between the various EA indices, we examined patterns of association separately for each index. Consistent with expectations, MSdPCR assessments of smoking and HAC, but not self-reported alcohol consumption, were strongly correlated with accelerated EA. MSdPCR assessments of smoking and HAC accounted for 57% of GrimAge acceleration and the shared variance in GrimAge and DunedinPOAM accelerated EA. We conclude that MSdPCR assessments of smoking and HAC are valuable tools for understanding EA, represent directly targetable conditions for the prevention of premature ageing, and substantially improve upon self-reported assessment of smoking and HAC.

DNA repair as a shared hallmark in cancer and ageing

Increasing evidence demonstrates that DNA damage and genome instability play a crucial role in ageing. Mammalian cells have developed a wide range of complex and well‐orchestrated DNA repair pathways to respond to and resolve many different types of DNA lesions that occur from exogenous and endogenous sources. Defects in these repair pathways lead to accelerated or premature ageing syndromes and increase the likelihood of cancer development. Understanding the fundamental mechanisms of DNA repair will help develop novel strategies to treat ageing‐related diseases. Here, we revisit the processes involved in DNA damage repair and how these can contribute to diseases, including ageing and cancer. We also review recent mechanistic insights into DNA repair and discuss how these insights are being used to develop novel therapeutic strategies for treating human disease. We discuss the use of PARP inhibitors in the clinic for the treatment of breast and ovarian cancer and the challenges associated with acquired drug resistance. Finally, we discuss how DNA repair pathway‐targeted therapeutics are moving beyond PARP inhibition in the search for ever more innovative and efficacious cancer therapies.

Evaluation of different computational methods for DNA methylation-based biological age

In recent years there has been a widespread interest in researching biomarkers of aging that could predict physiological vulnerability better than chronological age. Aging, in fact, is one of the most relevant risk factors for a wide range of maladies, and molecular surrogates of this phenotype could enable better patients stratification. Among the most promising of such biomarkers is DNA methylation-based biological age. Given the potential and variety of computational implementations (epigenetic clocks), we here present a systematic review of such clocks. Furthermore, we provide a large-scale performance comparison across different tissues and diseases in terms of age prediction accuracy and age acceleration, a measure of deviance from physiology. Our analysis offers both a state-of-the-art overview of the computational techniques developed so far and a heterogeneous picture of performances, which can be helpful in orienting future research.

A cautionary note on altered pace of aging in the COVID-19 era

Coronavirus disease 2019 (COVID-19) is highly age-dependent due to hi-jacking the molecular control of the immune cells by the severe acute respiratory syndrome-corona virus 2 (SARS-CoV-2) leading to aberrant DNA methylation (DNAm) pattern of blood in comparison to normal individuals. These epigenetic modifications have been linked to perturbations to the epigenetic clock, development of long COVID-19 syndrome, and all-cause mortality risk. I reviewed the effects of COVID-19 on different molecular age markers such as the DNAm, telomere length (TL), and signal joint T-cell receptor excision circle (sjTREC). Integrating the accumulated clinical research data, COVID-19 and novel medical management may alter the pace of aging in adult individuals (<60 years). As such, COVID-19 might be a confounder in epigenetic age estimation similar to life style diversities, pathogens and pathologies which may influence the interpretation of DNAm data. Similarly, the SARS-CoV-2 affects T-lymphocyte function with possible influence on sjTREC levels. In contrast, TL measurements performed years before the SARS-CoV-2 pandemic proved that short TL predisposes to severe COVID- 19 independently from chronological age. However, the persistence of COVID-19 epigenetic scars and the durability of the immune response after vaccination and their effect on the ongoing pace of aging are still unknown. In the light of these data, the heterogeneous nature of the samples in these studies mandates a systematic evaluation of the currrent methods. SARS-CoV-2 may modify the reliability of the age estimation models in real casework because blood is the most common biological sample encountered in forensic contexts.

Analysis of Epigenetic Age Acceleration and Healthy Longevity Among Older US Women

IMPORTANCE

Accelerated biological aging is associated with decreased physical capability and cognitive functioning, which are associated with increased risk of morbidity and mortality.

OBJECTIVE

We investigated associations between epigenetic age acceleration (EAA), a biomarker associated with aging, and healthy longevity among older women.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study was a secondary analysis of participants in the Women's Health Initiative (WHI) who were eligible to survive to age 90 years by September 30, 2020. Participants were located in multiple centers. This study was restricted to women with genome-wide DNA methylation data, generated from baseline blood samples within 3 WHI ancillary studies. Median (IQR) follow-up times from baseline were 21.6 (19.6-22.9) years and 21.4 (19.8-22.7) years for women who survived to age 90 years with and without intact mobility, respectively, and 13.2 (8.8-16.7) for women who did not survive to age 90 years. Data were analyzed from December 2020 to July 2021.

EXPOSURES

EAA was estimated using 4 established "clocks": Horvath pantissue, Hannum, Pheno, and Grim.

MAIN OUTCOMES AND MEASURES

Using multinomial logistic regression, odds ratios (ORs) and 95% CIs were estimated for 3 healthy longevity outcomes for each clock: survival to age 90 years with intact mobility, survival to age 90 years without intact mobility, and no survival to age 90 years.

RESULTS

Among 1813 women, there were 464 women (mean [SD] age at baseline, 71.6 [3.5] years) who survived to age 90 years with intact mobility and cognitive functioning, 420 women (mean [SD] age at baseline, 71.3 [3.2] years) who survived to age 90 years without intact mobility and cognitive functioning, and 929 women (mean [SD] age at baseline, 70.2 [3.4] years) who did not survive to age 90 years. Women who survived to age 90 years with intact mobility and cognitive function were healthier at baseline compared with women who survived without those outcomes or who did not survive to age 90 years (eg, 143 women [30.8%] vs 101 women [24.0%] and 202 women [21.7%] with 0 chronic conditions). The odds of surviving to age 90 years with intact mobility were lower for every 1 SD increase in EAA compared with those who did not survive to age 90 years as measured by AgeAccelHorvath (OR, 0.82; 95% CI, 0.69-0.96; P = .01), AgeAccelHannum (OR, 0.67; 95% CI, 0.56-0.80; P < .001), AgeAccelPheno (OR, 0.60; 95% CI, 0.51-0.72; P < .001), and AgeAccelGrim (OR, 0.68; 95% CI, 0.55-0.84; P < .001). ORs were similar for women who survived to age 90 years with intact mobility and cognitive function (eg, AgeAccelHorvath: OR per 1 SD increase in EAA, 0.83; 95% CI, 0.71-0.98; P = .03) compared with women who did not survive to age 90 years.

CONCLUSIONS AND RELEVANCE

These findings suggest that EAA may be a valid biomarker associated with healthy longevity among older women and may be used for risk stratification and risk estimation of future functional and cognitive aging. Outcomes suggest that future studies may focus on the potential for public health interventions to counteract EAA and its association with poor health outcomes to lower disease burden while increasing longevity.

Counteracting aged DNA methylation states to combat ageing and age-related diseases

DNA methylation (DNAm) overwrites information about multiple extrinsic factors on the genome. Age is one of these factors. Age causes characteristic DNAm changes that are thought to be not only major drivers of normal ageing but also precursors to diseases, cancer being one of these. Although there is still much to learn about the relationship between ageing, age-related diseases and DNAm, we now know how to interpret some of the effects caused by age in the form of changes in methylation marks at specific loci. In fact, these changes form the basis of the so called "epigenetic clocks", which translate the genomic methylation profile into an "epigenetic age". Epigenetic age does not only estimate chronological age but can also predict the risk of chronic diseases and mortality. Epigenetic age is believed to be one of the most accurate metrics of biological age. Initial evidence has recently been gathered pointing to the possibility that the rate of epigenetic ageing can be slowed down or even reversed. In this review, we discuss some of the most relevant advances in this field. Expected outcome is that this approach can provide insights into how to preserve health and reduce the impact of ageing diseases in humans.

Telomere length and epigenetic clocks as markers of cellular aging: a comparative study

Telomere length (TL) and DNA methylation-based epigenetic clocks are markers of biological age, but the relationship between the two is not fully understood. Here, we used multivariable regression models to evaluate the relationships between leukocyte TL (LTL; measured by qPCR [n = 635] or flow FISH [n = 144]) and five epigenetic clocks (Hannum, DNAmAge pan-tissue, PhenoAge, SkinBlood, or GrimAge clocks), or their epigenetic age acceleration measures in healthy adults (age 19-61 years). LTL showed statistically significant negative correlations with all clocks (qPCR: r =  - 0.26 to - 0.32; flow FISH: r =  - 0.34 to - 0.49; p < 0.001 for all). Yet, models adjusted for age, sex, and race revealed significant associations between three of five clocks (PhenoAge, GrimAge, and Hannum clocks) and LTL by flow FISH (p < 0.01 for all) or qPCR (p < 0.001 for all). Significant associations between age acceleration measures for the same three clocks and qPCR or flow FISH TL were also found (p < 0.01 for all). Additionally, LTL (by qPCR or flow FISH) showed significant associations with extrinsic epigenetic age acceleration (EEAA: p < 0.0001 for both), but not intrinsic epigenetic age acceleration (IEAA; p > 0.05 for both). In conclusion, the relationships between LTL and epigenetic clocks were limited to clocks reflecting phenotypic age. The observed association between LTL and EEAA reflects the ability of both measures to detect immunosenescence. The observed modest correlations between LTL and epigenetic clocks highlight a possible benefit from incorporating both measures in understanding disease etiology and prognosis.

Inflammation, Aging, and Cardiovascular Disease: JACC Review Topic of the Week

Aging and inflammation both contribute pivotally to cardiovascular (CV) and cerebrovascular disease, the leading causes of death and disability worldwide. The concept of inflamm-aging recognizes that low-grade inflammatory pathways observed in the elderly contribute to CV risk. Understanding the mechanisms that link inflammation and aging could reveal new therapeutic targets and offer options to cope with the growing aging population worldwide. This review reports recent scientific advances in the pathways through which inflamm-aging mediates age-dependent decline in CV function and disease onset and considers critically the translational potential of such concepts into everyday clinical practice.