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

Epigenetic age is associated with baseline and 3-year change in frailty in the Canadian Longitudinal Study on Aging

BACKGROUND

The trajectory of frailty in older adults is important to public health; therefore, markers that may help predict this and other important outcomes could be beneficial. Epigenetic clocks have been developed and are associated with various health-related outcomes and sociodemographic factors, but associations with frailty are poorly described. Further, it is uncertain whether newer generations of epigenetic clocks, trained on variables other than chronological age, would be more strongly associated with frailty than earlier developed clocks. Using data from the Canadian Longitudinal Study on Aging (CLSA), we tested the hypothesis that clocks trained on phenotypic markers of health or mortality (i.e., Dunedin PoAm, GrimAge, PhenoAge and Zhang in Nat Commun 8:14617, 2017) would best predict changes in a 76-item frailty index (FI) over a 3-year interval, as compared to clocks trained on chronological age (i.e., Hannum in Mol Cell 49:359-367, 2013, Horvath in Genome Biol 14:R115, 2013, Lin in Aging 8:394-401, 2016, and Yang Genome Biol 17:205, 2016).

RESULTS

We show that in 1446 participants, phenotype/mortality-trained clocks outperformed age-trained clocks with regard to the association with baseline frailty (mean = 0.141, SD = 0.075), the greatest of which is GrimAge, where a 1-SD increase in ΔGrimAge (i.e., the difference from chronological age) was associated with a 0.020 increase in frailty (95% CI 0.016, 0.024), or ~ 27% relative to the SD in frailty. Only GrimAge and Hannum (Mol Cell 49:359-367, 2013) were significantly associated with change in frailty over time, where a 1-SD increase in ΔGrimAge and ΔHannum 2013 was associated with a 0.0030 (95% CI 0.0007, 0.0050) and 0.0028 (95% CI 0.0007, 0.0050) increase over 3 years, respectively, or ~ 7% relative to the SD in frailty change.

CONCLUSION

Both prevalence and change in frailty are associated with increased epigenetic age. However, not all clocks are equally sensitive to these outcomes and depend on their underlying relationship with chronological age, healthspan and lifespan. Certain clocks were significantly associated with relatively short-term changes in frailty, thereby supporting their utility in initiatives and interventions to promote healthy aging.

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.

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.

Higher diet quality relates to decelerated epigenetic aging

BACKGROUND

DNA methylation-based epigenetic age measures have been used as biological aging markers and are associated with a healthy lifespan. Few population-based studies have examined the relation between diet and epigenetic age acceleration.

OBJECTIVES

We aimed to investigate the relation between diet quality and epigenetic age acceleration.

METHODS

We analyzed data from 1995 participants (mean age, 67 years; 55% women) of the Framingham Heart Study Offspring Cohort. Cross-sectional associations between the Dietary Approaches to Stop Hypertension (DASH) score and 3 whole-blood DNA methylation-derived epigenetic age acceleration measures-Dunedin Pace of Aging Methylation (DunedinPoAm), GrimAge acceleration (GrimAA), and PhenoAge acceleration (PhenoAA)-were examined. A mediation analysis was conducted to assess the mediating role of epigenetic age acceleration in relation to DASH and all-cause mortality.

RESULTS

A higher DASH score was associated with lower levels of DunedinPoAm (β = -0.05; SE = 0.02; P = 0.007), GrimAA (β = -0.09; SE = 0.02; P < 0.001), and PhenoAA (β = -0.07; SE = 0.02; P = 0.001). All 3 epigenetic measures mediated the association between the DASH score and all-cause mortality, with mean proportions of 22.1% for DunedinPoAm (Pmediation = 0.04), 45.1% for GrimAA (Pmediation = 0.001), and 22.9% for PhenoAA (Pmediation = 0.03). An interaction was observed between the DASH score and smoking status in relation to the epigenetic aging markers. The association between the DASH score and epigenetic aging markers tended to be stronger in "ever-smokers" (former and current smokers) compared to "never-smokers." The proportions of mediation were 31.3% for DunedinPoAm, 46.8% for GrimAA, and 10.3% for PhenoAA in ever-smokers, whereas no significant mediation was observed in never-smokers.

CONCLUSIONS

Higher diet quality is associated with slower epigenetic age acceleration, which partially explains the beneficial effect of diet quality on the lifespan. Our findings emphasize that adopting a healthy diet is crucial for maintaining healthy aging.

Socioeconomic Disadvantage and the Pace of Biological Aging in Children

BACKGROUND AND OBJECTIVES

Children who grow up in socioeconomic disadvantage face increased burden of disease and disability throughout their lives. One hypothesized mechanism for this increased burden is that early-life disadvantage accelerates biological processes of aging, increasing vulnerability to subsequent disease. To evaluate this hypothesis and the potential impact of preventive interventions, measures are needed that can quantify early acceleration of biological aging in childhood.

METHODS

Saliva DNA methylation and socioeconomic circumstances were measured in N = 600 children and adolescents aged 8 to 18 years (48% female) participating in the Texas Twin Project. We measured pace of biological aging using the DunedinPoAm DNA methylation algorithm, developed to quantify the pace-of-aging-related decline in system integrity. We tested if children in more disadvantaged families and neighborhoods exhibited a faster pace of aging as compared with children in more affluent contexts.

RESULTS

Children living in more disadvantaged families and neighborhoods exhibited a faster DunedinPoAm-measured pace of aging (r = 0.18; P = .001 for both). Latinx-identifying children exhibited a faster DunedinPoAm-measured pace of aging compared with both White- and Latinx White-identifying children, consistent with higher levels of disadvantage in this group. Children with more advanced pubertal development, higher BMI, and more tobacco exposure exhibited faster a faster DunedinPoAm-measured pace of aging. However, DunedinPoAm-measured pace of aging associations with socioeconomic disadvantage were robust to control for these factors.

CONCLUSIONS

Children growing up under conditions of socioeconomic disadvantage exhibit a faster pace of biological aging. DNA methylation pace of aging might be useful as a surrogate end point in evaluation of programs and policies to address the childhood social determinants of lifelong health disparities.

Associations of Age, Sex, Race/Ethnicity, and Education With 13 Epigenetic Clocks in a Nationally Representative U.S. Sample: The Health and Retirement Study

BACKGROUND

Many DNA methylation-based indicators have been developed as summary measures of epigenetic aging. We examine the associations between 13 epigenetic clocks, including 4 second generation clocks, as well as the links of the clocks to social, demographic, and behavioral factors known to be related to health outcomes: sex, race/ethnicity, socioeconomic status, obesity, and lifetime smoking pack-years.

METHODS

The Health and Retirement Study is the data source which is a nationally representative sample of Americans over age 50. Assessment of DNA methylation was based on the EPIC chip and epigenetic clocks were developed based on existing literature.

RESULTS

The clocks vary in the strength of their relationships with age, with each other and with independent variables. Second generation clocks trained on health-related characteristics tend to relate more strongly to the sociodemographic and health behaviors known to be associated with health outcomes in this age group.

CONCLUSIONS

Users of this publicly available data set should be aware that epigenetic clocks vary in their relationships to age and to variables known to be related to the process of health change with age.

Association of History of Psychopathology With Accelerated Aging at Midlife

IMPORTANCE

Individuals with mental disorders are at an elevated risk of developing chronic age-related physical diseases. However, it is not clear whether psychopathology is also associated with processes of accelerated aging that precede the onset of age-related disease.

OBJECTIVE

To test the hypothesis that a history of psychopathology is associated with indicators of accelerated aging at midlife.

DESIGN, SETTING, AND PARTICIPANTS

This prospective cohort study was based on the Dunedin Multidisciplinary Health and Development Study, a population-representative birth cohort of 1037 individuals born between April 1, 1972, and March 31, 1973, in Dunedin, New Zealand. Members were followed up to age 45 years (until April 2019). Data were analyzed from January 6 to December 7, 2020.

EXPOSURES

Mental disorders were assessed in 6 diagnostic assessments from ages 18 to 45 years and transformed through confirmatory factor analysis into continuous measures of general psychopathology (p-factor) and dimensions of internalizing, externalizing, and thought disorders (all standardized to a mean [SD] of 100 [15]).

MAIN OUTCOMES AND MEASURES

Signs of aging (biological pace of aging; declines in sensory, motor, and cognitive functioning; and facial age) were assessed up to age 45 years using previously validated measures including biomarkers, clinical tests, and self-reports.

RESULTS

Of the original 1037 cohort participants, 997 were still alive at age 45 years, of whom 938 (94%) were assessed (474 men [50.5%]). Participants who had experienced more psychopathology exhibited a faster pace of biological aging (β, 0.27; 95% CI, 0.21-0.33; P < .01); experienced more difficulties with hearing (β, 0.18; 95% CI, 0.12-0.24; P < .01), vision (β, 0.08; 95% CI, 0.01-0.14; P < .05), balance (β, 0.20; 95% CI, 0.14-0.26; P < .01), and motor functioning (β, 0.19; 95% CI, 0.12-0.25; P < .01); experienced more cognitive difficulties (β, 0.24; 95% CI, 0.18-0.31; P < .01); and were rated as looking older (β, 0.20; 95% CI, 0.14-0.26; P < .01). Associations persisted after controlling for sex, childhood health indicators, maltreatment, and socioeconomic status and after taking into account being overweight, smoking, use of antipsychotic medication, and the presence of physical disease. Tests of diagnostic specificity revealed that associations were generalizable across externalizing, internalizing, and thought disorders.

CONCLUSIONS AND RELEVANCE

In this cohort study, a history of psychopathology was associated with accelerated aging at midlife, years before the typical onset of age-related diseases. This link is not specific to any particular disorder family but generalizes across disorders. Prevention of psychopathology and monitoring of individuals with mental disorders for signs of accelerated aging may have the potential to reduce health inequalities and extend healthy lives.

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.

Disparities in the pace of biological aging among midlife adults of the same chronological age have implications for future frailty risk and policy

Some humans age faster than others. Variation in biological aging can be measured in midlife, but the implications of this variation are poorly understood. We tested associations between midlife biological aging and indicators of future frailty-risk in the Dunedin cohort of 1037 infants born the same year and followed to age 45. Participants' Pace of Aging was quantified by tracking declining function in 19 biomarkers indexing the cardiovascular, metabolic, renal, immune, dental, and pulmonary systems across ages 26, 32, 38, and 45 years. At age 45 in 2019, participants with faster Pace of Aging had more cognitive difficulties, signs of advanced brain aging, diminished sensory-motor functions, older appearance, and more pessimistic perceptions of aging. People who are aging more rapidly than same-age peers in midlife may prematurely need supports to sustain independence that are usually reserved for older adults. Chronological age does not adequately identify need for such supports.

Is your environment making you older? Molecular biomarkers and new approaches to investigate the influences of environmental chemicals through aging

Aging is characterized by a gradual and progressive decline in system integrity that occurs with advancing chronological age. Although it is a physiological process, aging is associated with a myriad of age-related diseases (ARDs), including frailty, sarcopenia, chronic obstructive pulmonary disease, cardiovascular disease, cancer, and neurodegenerative diseases. While not exclusively ARDs, many of these diseases lead to death, a lesser quality of life, and increased healthcare costs for individuals and systems. ARDs share several underlying molecular mechanisms, such as cellular damage, inflammation, DNA methylation changes, stem cells exhaustion, and DNA mutations, which have been outlined as hallmarks of aging. Evidence suggests that environmental exposures, including but not limited to metals, air pollution, endocrine-disrupting chemicals, and noise, may accelerate biological aging. Over the past few years, aging research has identified new molecular biomarkers of the aging process. When applied to investigate environmental influences, these biomarkers can help identify individuals who are particularly susceptible to the influences of environmental exposures on aging processes and therefore guide in implementing possible preventive measures.

A systematic review of childhood maltreatment and DNA methylation: candidate gene and epigenome-wide approaches

Childhood maltreatment is a major risk factor for chronic and severe mental and physical health problems across the lifespan. Increasing evidence supports the hypothesis that maltreatment is associated with epigenetic changes that may subsequently serve as mechanisms of disease. The current review uses a systematic approach to identify and summarize the literature related to childhood maltreatment and alterations in DNA methylation in humans. A total of 100 empirical articles were identified in our systematic review of research published prior to or during March 2020, including studies that focused on candidate genes and studies that leveraged epigenome-wide data in both children and adults. Themes arising from the literature, including consistent and inconsistent patterns of results, are presented. Several directions for future research, including important methodological considerations for future study design, are discussed. Taken together, the literature on childhood maltreatment and DNA methylation underscores the complexity of transactions between the environment and biology across development.

Unite to predict

Integrating the analysis of molecular data from different sources may improve our understanding of the effects of biological aging.

An integrative study of five biological clocks in somatic and mental health

Biological clocks have been developed at different molecular levels and were found to be more advanced in the presence of somatic illness and mental disorders. However, it is unclear whether different biological clocks reflect similar aging processes and determinants. In ~3000 subjects, we examined whether five biological clocks (telomere length, epigenetic, transcriptomic, proteomic, and metabolomic clocks) were interrelated and associated to somatic and mental health determinants. Correlations between biological aging indicators were small (all r < 0.2), indicating little overlap. The most consistent associations of advanced biological aging were found for male sex, higher body mass index (BMI), metabolic syndrome, smoking, and depression. As compared to the individual clocks, a composite index of all five clocks showed most pronounced associations with health determinants. The large effect sizes of the composite index and the low correlation between biological aging indicators suggest that one's biological age is best reflected by combining aging measures from multiple cellular levels.

Childhood self-control forecasts the pace of midlife aging and preparedness for old age

The ability to control one's own emotions, thoughts, and behaviors in early life predicts a range of positive outcomes in later life, including longevity. Does it also predict how well people age? We studied the association between self-control and midlife aging in a population-representative cohort of children followed from birth to age 45 y, the Dunedin Study. We measured children's self-control across their first decade of life using a multi-occasion/multi-informant strategy. We measured their pace of aging and aging preparedness in midlife using measures derived from biological and physiological assessments, structural brain-imaging scans, observer ratings, self-reports, informant reports, and administrative records. As adults, children with better self-control aged more slowly in their bodies and showed fewer signs of aging in their brains. By midlife, these children were also better equipped to manage a range of later-life health, financial, and social demands. Associations with children's self-control could be separated from their social class origins and intelligence, indicating that self-control might be an active ingredient in healthy aging. Children also shifted naturally in their level of self-control across adult life, suggesting the possibility that self-control may be a malleable target for intervention. Furthermore, individuals' self-control in adulthood was associated with their aging outcomes after accounting for their self-control in childhood, indicating that midlife might offer another window of opportunity to promote healthy aging.

Targeted methods for epigenetic age predictions in mice

Age-associated DNA methylation reflects aspect of biological aging—therefore epigenetic clocks for mice can elucidate how the aging process in this model organism is affected by specific treatments or genetic background. Initially, age-predictors for mice were trained for genome-wide DNA methylation profiles and we have recently described a targeted assay based on pyrosequencing of DNA methylation at only three age-associated genomic regions. Here, we established alternative approaches using droplet digital PCR (ddPCR) and barcoded bisulfite amplicon sequencing (BBA-seq). At individual CG dinucleotides (CpGs) the correlation of DNA methylation with chronological age was slightly higher for pyrosequencing and ddPCR as compared to BBA-seq. On the other hand, BBA-seq revealed that neighboring CpGs tend to be stochastically modified at murine age-associated regions. Furthermore, the binary sequel of methylated and non-methylated CpGs in individual reads can be used for single-read predictions, which may reflect heterogeneity in epigenetic aging. In comparison to C57BL/6 mice the single-read age-predictions using BBA-seq were also accelerated in the shorter-lived DBA/2 mice, and in C57BL/6 mice with a lifespan quantitative trait locus of DBA/2 mice. Taken together, we describe alternative targeted methods for epigenetic age predictions that provide new perspectives for aging-intervention studies in mice.

Decline in biological resilience as key manifestation of aging: Potential mechanisms and role in health and longevity

Decline in biological resilience (ability to recover) is a key manifestation of aging that contributes to increase in vulnerability to death with age eventually limiting longevity even in people without major chronic diseases. Understanding the mechanisms of this decline is essential for developing efficient anti-aging and pro-longevity interventions. In this paper we discuss: a) mechanisms of the decline in resilience with age, and aging components that contribute to this decline, including depletion of body reserves, imperfect repair mechanisms, and slowdown of physiological processes and responses with age; b) anti-aging interventions that may improve resilience or attenuate its decline; c) biomarkers of resilience available in human and experimental studies; and d) genetic factors that could influence resilience. There are open questions about optimal anti-aging interventions that would oppose the decline in resilience along with extending longevity limits. However, the area develops quickly, and prospects are exciting.

DNA methylation-based biomarkers of age acceleration and all-cause death, myocardial infarction, stroke, and cancer in two cohorts: The NAS, and KORA F4

Background

DNA methylation (DNAm) may play a role in age-related outcomes. It is not yet known which DNAm-based biomarkers of age acceleration (BoAA) has the strongest association with age-related endpoints.

Methods

We collected the blood samples from two independent cohorts: the Normative Ageing Study, and the Cooperative Health Research in the Region of Augsburg cohort. We measured epigenome-wide DNAm level, and generated five DNAm BoAA at baseline. We used Cox proportional hazards model to analyze the relationships between BoAA and all-cause death. We applied the Fine and Gray competing risk model to estimate the risk of BoAA on myocardial infarction (MI), stroke, and cancer, accounting for death of other reasons as the competing risks. We used random-effects meta-analyses to pool the individual results, with adjustment for multiple testing.

Findings

The mean chronological ages in the two cohorts were 74, and 61, respectively. Baseline GrimAgeAccel, and DNAm-related mortality risk score (DNAmRS) both had strong associations with all-cause death, MI, and stroke, independent from chronological age. For example, a one standard deviation (SD) increment in GrimAgeAccel was significantly associated with increased risk of all-cause death [hazard ratio (HR): 2.01; 95% confidence interval (CI), 1.15, 3.50], higher risk of MI (HR: 1.44; 95% CI, 1.16, 1.79), and elevated risk of stroke (HR: 1.42; 95% CI, 1.06, 1.91). There were no associations between any BoAA and cancer.

Interpretation

From the public health perspective, GrimAgeAccel is the most useful tool for identifying at-risk elderly, and evaluating the efficacy of anti-aging interventions.

Funding

National Institute of Environmental Health Sciences of U.S., Harvard Chan-NIEHS Center for Environmental Health, German Federal Ministry of Education and Research, and the State of Bavaria in Germany.

Whole blood DNA methylation aging markers predict colorectal cancer survival: a prospective cohort study

Background

Blood DNA methylation-based aging algorithms predict mortality in the general population. We investigated the prognostic value of five established DNA methylation aging algorithms for patients with colorectal cancer (CRC).

Methods

AgeAccelHorvath, AgeAccelHannum, DNAmMRscore, AgeAccelPheno and AgeAccelGrim were constructed using whole blood epi-genomic data from 2206 CRC patients. After a median follow-up of 6.2 years, 1079 deaths were documented, including 596 from CRC. Associations of the aging algorithms with survival outcomes were evaluated using the Cox regression and survival curves. Harrell’s C-statistics were computed to investigate predictive performance.

Results

Adjusted hazard ratios (95% confidence intervals) of all-cause mortality for patients in the third compared to the first tertile were 1.66 (1.32, 2.09) for the DNAmMRscore, 1.35 (1.14, 1.59) for AgeAccelPheno and 1.65 (1.37, 2.00) for AgeAccelGrim, even after adjustment for age, sex and stage. AgeAccelHorvath and AgeAccelHannum were not associated with all-cause or CRC-specific mortality. In stage-specific analyses, associations were much stronger for patients with early or intermediate stage cancers (stages I, II and III) than for patients with metastatic (stage IV) cancers. Associations were weaker and less often statistically significant for CRC-specific mortality. Adding DNAmMRscore, AgeAccelPheno or AgeAccelGrim to models including age, sex and tumor stage improved predictive performance moderately.

Conclusions

DNAmMRscore, AgeAccelPheno and AgeAccelGrim could serve as non-invasive CRC prognostic biomarkers independent of other commonly used markers. Further research should aim for tailoring and refining such algorithms for CRC patients and to explore their value for enhanced prediction of treatment success and treatment decisions.

A Longitudinal Epigenetic Aging and Leukocyte Analysis of Simulated Space Travel: The Mars-500 Mission

Astronauts undertaking long-duration space missions may be vulnerable to unique stressors that can impact human aging. Nevertheless, few studies have examined the relationship of mission duration with DNA-methylation-based biomarkers of aging in astronauts. Using data from the six participants of the Mars-500 mission, a high-fidelity 520-day ground simulation experiment, we tested relationships of mission duration with five longitudinally measured blood DNA-methylation-based metrics: DNAmGrimAge, DNAmPhenoAge, DNA-methylation-based estimator of telomere length (DNAmTL), mitotic divisions (epigenetic mitotic clock [epiTOC2]), and pace of aging (PoA). We provide evidence that, relative to baseline, mission duration was associated with significant decreases in epigenetic aging. However, only decreases in DNAmPhenoAge remained significant 7 days post-mission. We also observed significant changes in estimated proportions of plasmablasts, CD4T, CD8 naive, and natural killer (NK) cells. Only decreases in NK cells remained significant post-mission. If confirmed more broadly, these findings contribute insights to improve the understanding of the biological aging implications for individuals experiencing long-duration space travel.

Long-duration space travel is marked by a unique combination of stressors known to impact human aging. Using data from six participants of the Mars-500 mission, a high-fidelity 520-day ground simulation experiment, Nwanaji-Enwerem et al. report significant associations of mission duration with decreased biological aging measured via blood DNA methylation.

Socio-Environmental, Lifestyle, Behavioural, and Psychological Determinants of Biological Ageing: The Singapore Longitudinal Ageing Study

INTRODUCTION

The identification of modifiable health span-promoting factors is a public health priority.

OBJECTIVE

To explore the socio-environmental, lifestyle, behavioural, and psychological determinants of a clinical phenotypic measure of biological ageing in the Singapore Longitudinal Ageing Study (SLAS) cohort.

METHODS

Using cross-sectional data on 2,844 SLAS-2 adults with a chronological age (CA) ≥55 years, we estimated biological age (BA) using a validated panel of clinical, biochemical, physiological, and functional indicators (8 in men and 10 in women) and calculated the difference between BA and CA (BA - CA in years). Potential determinants included education, housing status, loss of a spouse, living alone, lifestyle and health activity, smoking, alcohol consumption, nutritional risks, consumption of milk, soy, fruit, vegetables, coffee and tea, sleep parameters, and life satisfaction.

RESULTS

The mean CA was 67.0 (standard deviation [SD] 7.9; range 55-94) years. The estimated BA varied more widely (SD 8.9 years; range 47.5-119.9 years), and BA - CA ranged from -11.3 to 30.0 years. In stepwise selection regression analyses, multiple significant independent determinants in a final model were larger for private housing, being single/divorced/widowed, productivity, cognitive and leisure time activity scores, 10 h/week of moderate-to-vigorous physical activity, unintended loss of weight, life satisfaction, and daily consumption of fruits 1-2 or ≥3 servings and Chinese tea 1-2 or ≥3 cups daily, together explaining 16% of BA - CA variance in men and 14% in women. Associated BA - CA estimates were highest in men with high-end housing status (-1.8 years, effect size 0.015) and unintended weight loss (1.5 years, effect size 0.017).

CONCLUSION

We identified determinants of biological ageing which can promote health span.

Behavioral and Social Research to Accelerate the Geroscience Translation Agenda

Geroscience is the study of how to slow biological aging to extend healthspan and longevity. Geroscience has not heretofore incorporated behavioral or social-science methods or findings into its agenda, but the current expansion of the agenda to human trials of anti-aging therapies will be greatly aided by behavioral and social science. This article recommends some ways in which geroscience can be augmented through collaboration with behavioral and social science to: accomplish translation from animal models to humans; inform the design of clinical trials of anti-aging therapies; develop outcome measures for evaluating efficacy of anti-aging therapies, and reduce and not exacerbate health disparities.

Anti-tumor necrosis factor drug responses and skin-blood DNA methylation age: Relationships in moderate-to-severe psoriasis

Studies have examined the utility of DNA methylation as a biomarker of psoriasis treatment responses, but investigations of treatment responses with Skin-Blood DNA methylation age (SkinBloodAge)-a methylation-based measure of health designed using skin tissues-are lacking. Using a HumanMethylation450 BeadChip blood DNA methylation data set from 70 white patients who presented with moderate-to-severe plaque psoriasis and were treated with anti-tumor necrosis factor (TNF) agents in Madrid, Spain, we examined the cross-sectional relationships of SkinBloodAge with anti-TNF treatment responses. Partial responders had a 7.2-year higher mean SkinBloodAge than excellent responders (P = .03). In linear regression models adjusted for chronological age, sex and anti-TNF agents - on average - partial responders had a 2.65-year higher SkinBloodAge than excellent responders (95%CI: 0.44, 4.86, P = .02). This relationship was attenuated in a sensitivity analysis adjusting for white blood cells including known T-cell mediators of psoriasis pathophysiology (β = 1.91-years, 95%CI: -0.50, 4.32, P = .12). Overall, our study suggests that partial responders to anti-TNF therapy have higher SkinBloodAges when compared to excellent responders. Although these findings still need to be confirmed more broadly, they further suggest that SkinBloodAge may be a useful treatment response biomarker that can be incorporated with other blood tests before anti-TNF therapy initiation in moderate-to-severe psoriasis patients.

"Epigenetic clocks": Theory and applications in human biology

All humans age, but how we age-and how fast-differs considerably from person to person. This deviation between apparent age and chronological age is often referred to as "biological age" (BA) and until recently robust tools for studying BA have been scarce. "Epigenetic clocks" are starting to change this. Epigenetic clocks use predictable changes in the epigenome, usually DNA methylation, to estimate chronological age with unprecedented accuracy. More importantly, deviations between epigenetic age and chronological age predict a broad range of health outcomes and mortality risks better than chronological age alone. Thus, epigenetic clocks appear to capture fundamental molecular processes tied to BA and can serve as powerful tools for studying health, development, and aging across the lifespan. In this article, I review epigenetic clocks, especially as they relate to key theoretical and applied issues in human biology. I first provide an overview of how epigenetic clocks are constructed and what we know about them. I then discuss emerging applications of particular relevance to human biologists-those related to reproduction, life-history, stress, and the environment. I conclude with an overview of the methods necessary for implementing epigenetic clocks, including considerations of study design, sample collection, and technical considerations for processing and interpreting epigenetic clocks. The goal of this review is to highlight some of the ways that epigenetic clocks can inform questions in human biology, and vice versa, and to provide human biologists with the foundational knowledge necessary to successfully incorporate epigenetic clocks into their research.

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

BACKGROUND

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

RESULTS

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

CONCLUSIONS

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

Putting epigenetic biomarkers to the test for clinical trials

Reliable biomarkers are needed to test the effectiveness of interventions intended to improve health and extend lifespan.

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

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