Measure Of Biological Age Research Articles

Geroscience-Centric Perspective for Geriatric Psychiatry: Integrating Aging Biology With Geriatric Mental Health Research

The geroscience hypothesis asserts that physiological aging is caused by a small number of biological pathways. Despite the explosion of geroscience research over the past couple of decades, the research on how serious mental illnesses (SMI) affects the biological aging processes is still in its infancy. In this review, we aim to provide a critical appraisal of the emerging literature focusing on how we measure biological aging systematically, and in the brain and how SMIs affect biological aging measures in older adults. We will also review recent developments in the field of cellular senescence and potential targets for interventions for SMIs in older adults, based on the geroscience hypothesis.

Association of biological age with health outcomes and its modifiable factors.

Identifying the clinical implications and modifiable and unmodifiable factors of aging requires the measurement of biological age (BA) and age gap. Leveraging the biomedical traits involved with physical measures, biochemical assays, genomic data, and cognitive functions from the healthy participants in the UK Biobank, we establish an integrative BA model consisting of multi-dimensional indicators. Accelerated aging (age gap >3.2 years) at baseline is associated incident circulatory diseases, related chronic disorders, all-cause, and cause-specific mortality. We identify 35 modifiable factors for age gap (p < 4.81 × 10-4 ), where pulmonary functions, body mass, hand grip strength, basal metabolic rate, estimated glomerular filtration rate, and C-reactive protein show the most significant associations. Genetic analyses replicate the possible associations between age gap and health-related outcomes and further identify CST3 as an essential gene for biological aging, which is highly expressed in the brain and is associated with immune and metabolic traits. Our study profiles the landscape of biological aging and provides insights into the preventive strategies and therapeutic targets for aging.

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.

Associations of DNA-methylation measures of biological aging with social disparities in child and adolescent mental health.

Children who experience environmental adversities are at increased risk of both internalizing and externalizing disorders. Epigenetic mechanisms may regulate the influence of environmental adversities on mental health. We examined the hypothesis that salivary DNA-methylation patterns of pace of biological aging (DunedinPoAm) and inflammation (DNAm-CRP) are socially stratified and associated with mental health in 1,183 children (609 female, age M=13.6y) from the Texas Twin Project. Analyses were preregistered. Participants' DNA-methylation algorithms and psychiatric symptoms differed by socioeconomic contexts and race/ethnicity. Children with more parent-reported internalizing symptoms had higher DunedinPoAm and DNAm-CRP scores, and children with more aggression problems had higher DNAm-CRP. DunedinPoAm partially mediated advantage of White racial identity on internalizing. Similarly, DNAm-CRP partially mediated advantage of higher family socioeconomic contexts and, in a separate model, White racial identity on reduced internalizing symptoms. Children's epigenetic measures of pace of biological aging and inflammation are associated with social inequalities and mental health.

Associations of healthy aging index and all-cause and cause-specific mortality: a prospective cohort study of UK Biobank participants.

The healthy aging index (HAI) has been recently developed as a surrogate measure of biological age. However, to what extent the HAI is associated with all-cause and cause-specific mortality and whether this association differs in younger and older adults remains unknown. We aimed to quantify the association between the HAI and mortality in a population of UK adults. In the prospective cohort study, data are obtained from the UK Biobank. Five HAI components (systolic blood pressure, reaction time, cystatin C, serum glucose, forced vital capacity) were scored 0 (healthiest), 1, and 2 (unhealthiest) according to sex-specific tertiles or clinically relevant cut-points and summed to construct the HAI (range 0-10). Cox proportional hazard regression models were used to estimate the associations of the HAI with the risk of all-cause and cause-specific mortality. 387,794 middle-aged and older participants were followed up for a median of 8.9years (IQR 8.3-9.5). A total of 14,112 all-cause deaths were documented. After adjustments, each 1-point increase in the HAI was related to a higher risk of all-cause mortality (hazards ratio [HR], 1.17; 95%CI, 1.15-1.18). Such association was stronger among adults younger than 60years (1.19, 1.17-1.21) than that among those 60years and older (1.15, 1.14-1.17) (P interaction < 0.001). For each unit increment of the HAI, the multivariate-adjusted HRs for risk of death were 1.28 (1.25-1.31) for cardiovascular diseases, 1.09 (1.07-1.10) for cancer, 1.36 (1.29-1.44) for digestive disease, 1.42 (1.35-1.48) for respiratory disease, 1.42 (1.33-1.51) for infectious diseases, and 1.15 (1.09-1.21) for neurodegenerative disease, respectively. Our findings indicate that the HAI is positively associated with all-cause and cause-specific mortality independent of chronological age. Our results further underscore the importance of effective early-life interventions to slow aging and prevent premature death.

Using Epigenetic Clocks to Characterize Biological Aging in Studies of Children and Childhood Exposures: a Systematic Review.

Biological age, measured via epigenetic clocks, offers a unique and useful tool for prevention scientists to explore the short- and long-term implications of age deviations for health, development, and behavior. The use of epigenetic clocks in pediatric research is rapidly increasing, and there is a need to review the landscape of this work to understand the utility of these clocks for prevention scientists. We summarize the current state of the literature on the use of specific epigenetic clocks in childhood. Using systematic review methods, we identified studies published through February 2023 that used one of three epigenetic clocks as a measure of biological aging. These epigenetic clocks could either be used as a predictor of health outcomes or as a health outcome of interest. The database search identified 982 records, 908 of which were included in a title and abstract review. After full-text screening, 68 studies were eligible for inclusion. While findings were somewhat mixed, a majority of included studies found significant associations between the epigenetic clock used and the health outcome of interest or between an exposure and the epigenetic clock used. From these results, we propose the use of epigenetic clocks as a tool to understand how exposures impact biologic aging pathways and development in early life, as well as to monitor the effectiveness of preventive interventions that aim to reduce exposure and associated adverse health outcomes.

Metal mixtures and DNA methylation measures of biological aging in American Indian populations

IntroductionNative American communities suffer disproportionately from elevated metal exposures and increased risk for cardiovascular diseases and diabetes. DNA methylation is a sensitive biomarker of aging-related processes and novel epigenetic-based “clocks” can be used to estimate accelerated biological aging that may underlie increased risk. Metals alter DNA methylation, yet little is known about their individual and combined impact on epigenetic age acceleration. Our objective was to investigate the associations of metals on several DNA methylation-based aging measures in the Strong Heart Study (SHS) cohort. MethodsBlood DNA methylation data from 2,301 SHS participants was used to calculate age acceleration of epigenetic clocks (PhenoAge, GrimAge, DunedinPACE, Hannum, Horvath). Urinary metals [arsenic (As), cadmium (Cd), tungsten (W), zinc (Zn), selenium (Se), molybdenum (Mo)] were creatinine-adjusted and categorized into quartiles. We examined associations of individual metals through linear regression models and used Bayesian Kernel Machine Regression (BKMR) for the impact of the total metal mixture on epigenetic age acceleration. ResultsThe mixture of nonessential metals (W, As, Cd) was associated with greater GrimAge acceleration and DunedinPACE, while the essential metal mixture (Se, Zn, Mo) was associated with lower epigenetic age acceleration. Cd was associated with increased epigenetic age acceleration across all clocks and BKMR analysis suggested nonlinear associations between Se and DunedinPACE, GrimAge, and PhenoAge acceleration. No interactions between individual metals were observed. The associations between Cd, Zn, and epigenetic age acceleration were greater in never smokers in comparison to current/former smokers. ConclusionNonessential metals were positively associated with greater epigenetic age acceleration, with strongest associations observed between Cd and DunedinPACE and GrimAge acceleration. In contrast, essential metals were associated with lower epigenetic aging. Examining the influence of metal mixtures on epigenetic age acceleration can provide insight into metals and aging-related diseases.

Promoting health and productivity among ageing workers: a longitudinal study on work ability, biological and cognitive age in modern workplaces (PROAGEING study)

BackgroundLarge changes in ageing population and in retirement age are increasing the number of older people in the workforce, raising many challenges for policymakers in promoting employment opportunities and health for older workers. In this respect, longitudinal assessments of workability, well-being perception and cognitive skills over time may allow to detect factors influencing workers’ health. Moreover, new available molecular markers permit the measurement of biological age and age-related changes. Most studies analysed one aspect at time (psychological, biological, labour productivity), without considering their interaction. Aims of the study are to evaluate the relationship between workability, cognitive skills, and biological age in a population of ageing workers; to conduct a cross-sectional analysis to assess the impact of occupational exposures on workability, cognitive skills, and biological age; to evaluate inter-individuals changes in a prospective analysis with a re-evaluation of each worker.MethodsOur study plans to enrol 1000 full-time workers, aged over 50, undergoing the medical surveillance required by the current Italian Legislation. Data collection includes information about: (a) work ability and psychosocial risk factors (work ability index, HSE Management Standard-21 item, Utrecht Work Engagement Scale, World Health Organisation-Five, Well-Being Index, job satisfaction, general well-being, technostress); (b) cognitive skills (Stroop Color and Word test, Simon task, Corsi’s block-tapping test, Digit span test); (c) sleep habits and psychological well-being (Pittsburgh Sleep Quality Index, Insomnia Severity Index, Ford Insomnia Response to Stress Test; Symptom Check List 90, Psychological Well-Being Index, Profile of Mood State, Beck Depression Inventory, Beck Anxiety Inventory, Perceived Stress Scale, Brief COPE); (d) biological age (telomere length, DNA methylation) for 500 workers. All workers will repeat the evaluation after one year.DiscussionThis study aims to increase our knowledge about interactions between work ability, cognitive ability, well-being perception and psychological status also by including molecular markers, with a longitudinal and multidisciplinary approach. By bringing better insights into the relationship between risk factors and their impact on perceived and biological health, this study also aims at identifying possible interventions and protective measures to ensure aged workers’ well-being, consistent with all the eminent calls for actions promoted by key International and European labour organizations.

Epigenetic and Metabolomic Biomarkers for Biological Age: A Comparative Analysis of Mortality and Frailty Risk.

Biological age captures a person's age-related risk of unfavorable outcomes using biophysiological information. Multivariate biological age measures include frailty scores and molecular biomarkers. These measures are often studied in isolation, but here we present a large-scale study comparing them. In 2 prospective cohorts (n = 3 222), we compared epigenetic (DNAm Horvath, DNAm Hannum, DNAm Lin, DNAm epiTOC, DNAm PhenoAge, DNAm DunedinPoAm, DNAm GrimAge, and DNAm Zhang) and metabolomic-based (MetaboAge and MetaboHealth) biomarkers in reflection of biological age, as represented by 5 frailty measures and overall mortality. Biomarkers trained on outcomes with biophysiological and/or mortality information outperformed age-trained biomarkers in frailty reflection and mortality prediction. DNAm GrimAge and MetaboHealth, trained on mortality, showed the strongest association with these outcomes. The associations of DNAm GrimAge and MetaboHealth with frailty and mortality were independent of each other and of the frailty score mimicking clinical geriatric assessment. Epigenetic, metabolomic, and clinical biological age markers seem to capture different aspects of aging. These findings suggest that mortality-trained molecular markers may provide novel phenotype reflecting biological age and strengthen current clinical geriatric health and well-being assessment.

MRI‐based measure of dementia risk derived using machine learning is strongly associated with measures of longevity and biological age

AbstractBackgroundMachine learning and artificial intelligence methods have been applied to brain images to estimate measures of brain aging. However, only rarely have these measures been examined in the context of biologic age. Here, we investigated associations of an MRI‐based measure of dementia risk the Alzheimer’s disease pattern similarity (AD‐PS) scores with measures of longevity and biological age.MethodParticipants were those from visit 5 of the Atherosclerosis Risk in Community Study with cognitive status adjudication and MRI available. The AD‐PS score was estimated based on previously reported machine learning methods. We evaluated associations of the AD‐PS score with all‐cause mortality. Participants were stratified by AD‐PS tertiles and the analyses were adjusted for age, race, sex, hypertension and smoking. AD‐PS score was examined in association with 32 proteins reported to be associated with age. In these analyses, we used Bonferroni correction (α = 0.05,p&lt;0.0016). Finally, associations with a deficit accumulation index(DAI) based on 38 health items was investigated. In both cases, linear regression models were adjusted for age, race and sex. Sensitivity analyses using only cognitively normal (CN) individuals were performed.ResultMortality – A total of 356 participants died within 8 years of follow‐up. The AD‐PS score was significantly associated(p&lt;0.001) with time to all‐cause mortality. Participants in the lowest tertile had lower all‐cause mortality rate compared to those in the highest tertile (HR: 0.43;95% CI:0.31,0.60). The association remained significant when restricting the sample to only CN subjects (HR for lowest tertile:0.53; 95% CI:0.35,0.81, p = 0.0028).Age related proteins ‐ The AD‐PS scores were significantly associated (p&lt;0.05, uncorrected) with 10 of the 32 proteins. Growth/differentiation factor 15(GDF‐15) and pleiotrophin remained significant after correction for multiple‐testing. Analysis of CN participants showed a subset of the same proteins to be significant (p&lt;0.05,uncorrected) but only the GDF‐15 remained significant after correction for multiple‐testing.DAI ‐ A linear regression model showed a significant association between DAI and AD‐PS scores overall (coeff = 0.52; 95% CI:0.37‐0.67) and in the CN subset (coeff = 0.3,95% CI:0.13‐0.48).ConclusionWhile the AD‐PS scores were created as a measure of dementia risk, our analyses suggest that they could also be capturing brain aging.

Machine-learning derived measures of vascular and brain age are independently associated with cognitive function

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): UiT The Arctic University of Norway, Northern Norway Regional Health Authority. Background/Introduction Machine learning models have been applied to magnetic resonance images of the brain to estimate brain age gap as a biomarker of biological aging. Because of its association with cognitive performance and neurological disorders, brain age gap has become an indicator of general brain health. Among others, cardiovascular risk factors are associated with brain health. Recently a novel non-invasive biomarker of vascular ageing has been proposed based on the application of a deep-learning algorithm to digitised 12-lead electrocardiograms. The difference between electrocardiogram predicted age and chronological age is defined as vascular age gap and has been shown to be associated with an adverse cardiovascular profile. However, the association of vascular age gap with cognitive health and dementias has not yet been examined. Purpose We apply a causal mediation framework to vascular age gap, brain age gap and cognitive function data obtained in the same individuals who took part in a population-based study in Norway. We hypothesise that cardiovascular risk factors encapsulated in vascular age gap can indirectly affect cognitive function by increasing the brain age gap. Methods We applied a deep learning algorithm (1) to electrocardiograms (N=7779, age 40-85 years) collected from the population-based sample in Norway (mean age 63.8 years, 45.3% men) to obtain a vascular age gap. For a subsample (N=1693) magnetic resonance images of the brain were also available and another deep neural network algorithm (2) was applied to obtain a biomarker of brain age. For 1678 participants with both vascular age gap and brain age gap available we used mediation analysis to test whether brain age gap mediates the effects of vascular age gap on cognitive function (as measured by mini mental status test, word memory test, digit–symbol coding test, tapping test) by estimating total, direct and indirect effects. Results We found a weak correlation (Pearson’s r = 0.12) between vascular age gap and brain age gap. Both age gaps were associated with cognitive scores capturing psychomotor speed, attention and mental flexibility. For a 1 standard deviation (7.3 years) increase in vascular age gap digit-symbol coding test score decreased by 0.63 (95%CI: -0.89, -0.36; p&amp;lt;0.001) points, and tapping test decreased by 0.36 (95%CI: -0.56, -0.14; p=0.001). Only 13% of effect of vascular age gap on cognitive test results was mediated by brain age gap. Conclusion(s) Vascular age gap was weakly associated with poorer cognitive functioning, and only 13% of this association was mediated by brain age gap. This suggests that cognitive decline linked to accumulated damage of the vascular system is not fully captured by structural changes in the brain. Further investigations of novel measures of biological aging in relation to cognitive decline are warranted as these may hold promise for improved understanding of mechanisms and clinical prediction.

A novel estimate of biological aging by multiple fitness tests is associated with risk scores for age-related diseases.

Introduction: Recent research highlights the need for a correct instrument for monitoring the individual health status, especially in the elderly. Different definitions of biological aging have been proposed, with a consistent positive association of physical activity and physical fitness with decelerated aging trajectories. The six-minute walking test is considered the current gold standard for estimating the individual fitness status in the elderly. Methods: In this study, we investigated the possibility of overcoming the main limitations of assessing fitness status based on a single measure. As a result, we developed a novel measure of fitness status based on multiple fitness tests. In 176 Sardinian individuals aged 51-80years we collected the results of eight fitness tests to measure participants' functional mobility, gait, aerobic condition, endurance, upper and lower limb strength, and static and dynamic balance. In addition, the participants' state of health was estimated through validated risk scores for cardiovascular diseases, diabetes, mortality, and a comorbidity index. Results: Six measures contributing to fitness age were extracted, with TUG showing the largest contribution (beta = 2.23 SDs), followed by handgrip strength (beta = -1.98 SDs) and 6MWT distance (beta = -1.11 SDs). Based on fitness age estimates, we developed a biological aging measure using an elastic net model regression as a linear combination of the results of the fitness tests described above. Our newly developed biomarker was significantly associated with risk scores for cardiovascular events (ACC-AHA: r = 0.61; p = 0.0006; MESA: r = 0.21; p = 0.002) and mortality (Levine mortality score: r = 0.90; p = 0.0002) and outperformed the previous definition of fitness status based on the six-minute walking test in predicting an individual health status. Discussion: Our results indicate that a composite measure of biological age based on multiple fitness tests may be helpful for screening and monitoring strategies in clinical practice. However, additional studies are needed to test standardisation and to calibrate and validate the present results.

Associations of socioeconomic disparities with buccal DNA-methylation measures of biological aging

BackgroundIndividuals who are socioeconomically disadvantaged are at increased risk for aging-related diseases and perform less well on tests of cognitive function. The weathering hypothesis proposes that these disparities in physical and cognitive health arise from an acceleration of biological processes of aging. Theories of how life adversity is biologically embedded identify epigenetic alterations, including DNA methylation (DNAm), as a mechanistic interface between the environment and health. Consistent with the weathering hypothesis and theories of biological embedding, recently developed DNAm algorithms have revealed profiles reflective of more advanced aging and lower cognitive function among socioeconomically-at-risk groups. These DNAm algorithms were developed using blood-DNA, but social and behavioral science research commonly collect saliva or cheek-swab DNA. This discrepancy is a potential barrier to research to elucidate mechanisms through which socioeconomic disadvantage affects aging and cognition. We therefore tested if social gradients observed in blood DNAm measures could be reproduced using buccal-cell DNA obtained from cheek swabs.ResultsWe analyzed three DNAm measures of biological aging and one DNAm measure of cognitive performance, all of which showed socioeconomic gradients in previous studies: the PhenoAge and GrimAge DNAm clocks, DunedinPACE, and Epigenetic-g. We first computed blood-buccal cross-tissue correlations in n = 21 adults (GEO111165). Cross-tissue correlations were low-to-moderate (r = .25 to r = .48). We next conducted analyses of socioeconomic gradients using buccal DNAm data from SOEP-G (n = 1128, 57% female; age mean = 42 yrs, SD = 21.56, range 0–72). Associations of socioeconomic status with DNAm measures of aging were in the expected direction, but were smaller as compared to reports from blood DNAm datasets (r = − .08 to r = − .13).ConclusionsOur findings are consistent with the hypothesis that socioeconomic disadvantage is associated with DNAm indicators of worse physical health. However, relatively low cross-tissue correlations and attenuated effect sizes for socioeconomic gradients in buccal DNAm compared with reports from analysis of blood DNAm suggest that in order to take full advantage of buccal DNA samples, DNAm algorithms customized to buccal DNAm are needed.

Longitudinal fundus imaging and its genome-wide association analysis provide evidence for a human retinal aging clock.

Biological age, distinct from an individual's chronological age, has been studied extensively through predictive aging clocks. However, these clocks have limited accuracy in short time-scales. Here we trained deep learning models on fundus images from the EyePACS dataset to predict individuals' chronological age. Our retinal aging clocking, 'eyeAge', predicted chronological age more accurately than other aging clocks (mean absolute error of 2.86 and 3.30 years on quality-filtered data from EyePACS and UK Biobank, respectively). Additionally, eyeAge was independent of blood marker-based measures of biological age, maintaining an all-cause mortality hazard ratio of 1.026 even when adjusted for phenotypic age. The individual-specific nature of eyeAge was reinforced via multiple GWAS hits in the UK Biobank cohort. The top GWAS locus was further validated via knockdown of the fly homolog, Alk, which slowed age-related decline in vision in flies. This study demonstrates the potential utility of a retinal aging clock for studying aging and age-related diseases and quantitatively measuring aging on very short time-scales, opening avenues for quick and actionable evaluation of gero-protective therapeutics.

Cross-National and Cross-Generational Evidence That Educational Attainment May Slow the Pace of Aging in European-Descent Individuals.

Individuals with more education are at lower risk of developing multiple, different age-related diseases than their less-educated peers. A reason for this might be that individuals with more education age slower. There are 2 complications in testing this hypothesis. First, there exists no definitive measure of biological aging. Second, shared genetic factors contribute toward both lower educational attainment and the development of age-related diseases. Here, we tested whether the protective effect of educational attainment was associated with the pace of aging after accounting for genetic factors. We examined data from 5 studies together totaling almost 17,000 individuals with European ancestry born in different countries during different historical periods, ranging in age from 16 to 98 years old. To assess the pace of aging, we used DunedinPACE, a DNA methylation algorithm that reflects an individual's rate of aging and predicts age-related decline and Alzheimer's disease and related disorders. To assess genetic factors related to education, we created a polygenic score based on the results of a genome-wide association study of educational attainment. Across the 5 studies, and across the life span, higher educational attainment was associated with a slower pace of aging even after accounting for genetic factors (meta-analysis effect size = -0.20; 95% confidence interval [CI]: -0.30 to -0.10; p = .006). Further, this effect persisted after taking into account tobacco smoking (meta-analysis effect size = -0.13; 95% CI: -0.21 to -0.05; p = .01). These results indicate that higher levels of education have positive effects on the pace of aging, and that the benefits can be realized irrespective of individuals' genetics.

Which Types of Stress Are Associated With Accelerated Biological Aging? Comparing Perceived Stress, Stressful Life Events, Childhood Adversity, and Posttraumatic Stress Disorder.

Stress and stressful events are associated with poorer health; however, there are multiple ways to conceptualize and measure stress and stress responses. One physiological mechanism through which stress could result in poorer health is accelerated biological aging. This study tested which types of stress were associated with accelerated biological aging in adulthood. Studying 955 participants from the Dunedin Longitudinal Study, we tested whether four types of stress assessed from ages 32 to 45 years-perceived stress, number of stressful life events, adverse childhood experiences, and posttraumatic stress disorder-were associated with accelerated biological aging. Higher levels of all four measures of stress were significantly associated with accelerated aging in separate models. In a combined model, more perceived stress and more stressful life events remained associated with faster aging, and the stress measures explained 6.9% of the variance in aging. The magnitudes of the associations between the four measures of stress and biological aging were comparable to associations for smoking and low education, two established risk factors for accelerated aging. People with high levels of perceived stress, numerous adverse childhood experiences (4+), high stressful life event counts, or posttraumatic stress disorder were aging an additional estimated 2.4 months, 1.1 additional months, 1.4 months, and 1.4 months per year, respectively. Assessing stress, particularly perceived stress, could help identify people at risk of accelerated aging. Intervening to treat stress or the health-relevant sequelae of stress could potentially slow the rate at which people are aging, improving their health as they age.

Abstract 5757: Breast cancer diagnosis and treatment associated with acceleration of biological aging over time in a racially diverse cohort of women

Abstract Leukocyte DNA methylation (DNAm) at individual sites across the genome can be used to construct measures of biological age. Positive age acceleration—when biological age is older than chronological age—is associated with higher risk of age-associated diseases. Recent adjuvant therapy is reported to increase age acceleration, but the longer-term effects of a breast cancer diagnosis and treatment on age acceleration remain unknown. Here, we use blood samples collected at two timepoints to examine changes in age acceleration over time comparing women who did and did not develop breast cancer. Paired whole blood samples were drawn an average of 8 years apart (range: 5-11 years) in a sample of non-Hispanic White and Black (Hispanic and non-Hispanic) women. DNAm was profiled using Infinium MethylationEPIC BeadChips. Approximately half the women were diagnosed and treated for breast cancer between blood draws (cases; n= 190, baseline mean age= 57) whereas the other half remained breast cancer-free (controls; n= 227, baseline mean age= 56). Longitudinal changes in three age acceleration metrics were compared to determine whether an intervening breast cancer diagnosis and treatment was associated with trajectories in biological aging. On average, the cases were diagnosed with breast cancer 3.5 years after the initial blood draw and 4 years before the second blood draw. Among the cases, 36% were treated with chemotherapy, 65% with radiation therapy, and 70% with hormonal therapies; 45% of the cases received two types of therapy, and 13% received all three. Compared to women who remained cancer-free, women diagnosed and treated for breast cancer had increases in age acceleration over time as measured by PhenoAgeAccel (adjusted standardized mean difference (β)= 0.13, 95% CI: 0.00, 0.26), GrimAgeAccel (β= 0.13, 95% CI: 0.03, 0.24), and DunedinPACE (β= 0.35, 95% CI: 0.23, 0.48). The associations did not vary by timing of diagnosis between the blood draws or race; however, women diagnosed with estrogen receptor (ER) negative tumors appeared to experience faster increases in age acceleration than women diagnosed with ER positive tumors (GrimAgeAccel; ER negative β= 0.27, 95% CI: 0.07, 0.47; ER positive β= 0.10, 95% CI: -0.01, 0.21; P-interaction= 0.14). To investigate the impact of different types of breast cancer therapies, associations were examined using a case-only design. In models that simultaneously included chemotherapy, radiation therapy and hormone therapy, radiation therapy had the strongest associations with accelerated biological aging as measured by PhenoAgeAccel (β= 0.38, 95% CI: 0.18, 0.58), GrimAgeAccel (β= 0.27, 95% CI: 0.09, 0.45), and DunedinPACE (β= 0.25, 95% CI: 0.03, 0.47). We find that years after the initial diagnosis, breast cancer survivors have significantly accelerated biological aging; treatment modalities may differentially influence these rates. Citation Format: Jacob K. Kresovich, Katie M. O'Brien, Zongli Xu, Clarice R. Weinberg, Dale P. Sandler, Jack A. Taylor. Breast cancer diagnosis and treatment associated with acceleration of biological aging over time in a racially diverse cohort of women. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5757.

노화의 개념, 진단 및 관리

Anti-aging medicine is defined as ‘the newest clinical specialty, the optimum of wellness and longevity, and employs extensive therapies and treatment in the preventive health care field far beyond just cholesterol testing and mammogram, by American Academy of Anti-aging Medicine. Aging theories is dived into two main theories, genetic control theory and acquired theory. Though many aging theories have been developed, any single theory is not universally accepted. Aging is defined as a time-related decline in physiological functions and changes in morphology. Aging is usually evaluated by questionnaires (AGHDA), self-test, aging biomarkers tests, and biological age measurements. Biological age measurement is usually considered as the index to evaluate the overall health status and aging degree in clinical practice. The goal of aging management is not only to treat age-related diseases, but to improve the diverse function of body and improve quality of life. Five major methods for aging management are the elimination of risk factors, management of chronic diseases, caloric restriction with nutritional balance, medium-intensity regular exercise, and stress management. Many other methods, such as, anti-oxidant therapy, hormone replacement, smart drugs, immune boosters, detoxification, and alternative medicine have been tried for aging management.

The variable associations between PFASs and biological aging by sex and reproductive stage in NHANES 1999–2018

BackgroundPer- and polyfluoroalkyl substances (PFASs) are endocrine disrupting chemicals that have myriad effects on human physiology. Estrogenic PFASs may influence biological aging by mimicking the activity of endogenous estrogens, which can decrease inflammation and oxidative stress and enhance telomerase activity. We hypothesized that PFAS exposure would be differentially associated with measures of biological aging based on biological sex and reproductive stage. MethodsWe analyzed associations between serum PFAS levels and measures of biological aging for pre- and postmenopausal women and men (n = 3193) using data from the 2003 to 2018 waves of the National Health and Nutrition Examination Survey. Examining PFASs both individually and in mixture models, we investigated four measures of clinical aging (Homeostatic Dysregulation, the Klemera-Doubal Method, Phenotypic Age Acceleration, and Allostatic Load), oxidative stress, and telomere length. ResultsPFOA and PFOS were negatively associated with Phenotypic Age Acceleration (e.g. decelerated aging) for men B = −0.22, 95% CI: −0.32, −0.12; B = −0.04, 95% CI: −0.06, −0.03) , premenopausal women (B = −0.58, 95% CI: −0.83, −0.32; B = −0.15, 95% CI: −0.20, −0.09), and postmenopausal women (B= −0.22, 95% CI: −0.43, −0.01; B = −0.05, 95% CI: −0.08, −0.02). In mixture models, we found net negative effects for Phenotypic Age Acceleration and Allostatic Load for men, premenopausal women, and postmenopausal women. We also found significant mixture effects for the antioxidants bilirubin and albumin among the three sample groups. We found no evidence to support effects on telomere length. DiscussionOur findings suggest that PFAS exposure may be inversely associated with some measures of biological aging at the relatively low levels of exposure in this sample, regardless of reproductive stage and sex, which does not support our hypothesis. This research provides insights into how PFAS exposure may variably influence aging measures depending on the physiological process investigated.

Potential reversal of biological age in women 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.