Quest for a summary measure of biological age: the health and retirement study

Sex and education differences in trajectories of physiological ageing: longitudinal analysis of a prospective English cohort study

Background

Physiological age (PA) derived from clinical indicators including blood-based biomarkers and tests of physiological function can be compared with chronological age to examine disparities in health between older adults of the same age. Though education interacts with sex to lead to inequalities in healthy ageing, their combined influence on longitudinally-measured PA has not been explored. We derived PA based on longitudinally-measured clinical indicators and examined how sex and education interact to inform PA trajectories.

Methods

Three waves of clinical indicators (2004/05-2012/13) drawn from the English Longitudinal Study of Ageing (ages 50-100 years) were used to estimate PA, which was internally validated by confirming associations with incident chronic conditions, functional limitations, and memory impairment after adjustment for chronological age and sex. Joint models were used to construct PA trajectories in 8,891 ELSA participants to examine sex and educational disparities in PA.

Findings

Among the least educated participants, there were negligible sex differences in PA until age 60 (sex difference [men-women] age 50=-0.6 years [95% confidence interval=-2.2-0.6]; age 60=0.4 [-0.6-1.4]); at age 70, women were 1.5 years (0.7-2.2) older than men. Among the most educated participants, women were 3.8 years (1.6-6.0) younger than men at age 50, and 2.7 years (0.4-5.0) younger at age 60, with a non-significant sex difference at age 70.

Interpretation

Higher education provides a larger midlife buffer to physiological ageing for women than men. Policies to promote gender equity in higher education may contribute to improving women's health across a range of ageing-related outcomes.

Development of a novel transcriptomic measure of aging: Transcriptomic Mortality-risk Age (TraMA)

Increasingly, research suggests that aging is a coordinated multi-system decline in functioning that occurs at multiple biological levels. We developed and validated a transcriptomic (RNA-based) aging measure we call Transcriptomic Mortality-risk Age (TraMA) using RNA-seq data from the 2016 Health and Retirement Study using elastic net Cox regression analyses to predict 4-year mortality hazard. In a holdout test sample, TraMA was associated with earlier mortality, more chronic conditions, poorer cognitive functioning, and more limitations in activities of daily living. TraMA was also externally validated in the Long Life Family Study and several publicly available datasets. Results suggest that TraMA is a robust, portable RNAseq-based aging measure that is comparable, but independent from past biological aging measures (e.g., GrimAge). TraMA is likely to be of particular value to researchers interested in understanding the biological processes underlying health and aging, and for social, psychological, epidemiological, and demographic studies of health and aging.

Clinical biomarker-based biological age predicts deaths in Brazilian adults: the ELSA-Brasil study

Biological age is a construct that seeks to evaluate the biological wear and tear process of the organism that cannot be observed by chronological age. We estimate individuals' biological age based on biomarkers from multiple systems and validate it through its association with mortality from natural causes. Biological age was estimated in 12,109 participants (6621 women and 5488 men) from the first visit of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) who had valid data for the biomarkers used in the analyses. Biological age was estimated using the Klemera and Doubal method. The difference between chronological age and biological age (Δage) was computed. Cox proportional hazard models stratified by sex were used to assess whether Δage was associated with mortality risk after a median follow-up of 9.1 years. The accuracy of the models was estimated by the area under the curve (AUC). Δage had equal mean for men and women, with greater variability for men. Cox models showed that every 1-year increase in Δage was associated with increased mortality in men (HR (95% CI) 1.21; 1.17-1.25) and women (HR (95% CI) 1.24; 1.15-1.34), independently of chronological age. Results of the AUC demonstrated that the predictive power of models that only included chronological age (AUC chronological age = 0.7396) or Δage (AUC Δage = 0.6842) was lower than those that included both, chronological age and Δage (AUC chronological age + Δage = 0.802), in men. This difference was not observed in women. We demonstrate that biological age is strongly related to mortality in both genders and is a valid predictor of death in Brazilian adults, especially among men.

Modeling Disability-Free Life Expectancy With Duration Dependence: A Research Note on the Bias in the Markov Assumption

Demographic studies on healthy life expectancy often rely on the Markov assumption, which fails to consider the duration of exposure to risk. To address this limitation, models like the duration-dependent multistate life table (DDMSLT) have been developed. However, these models cannot be directly applied to left-censored survey data, as they require knowledge of the time spent in the initial state, which is rarely known because of survey design. This research note presents a flexible approach for utilizing this type of survey data within the DDMSLT framework to estimate multistate life expectancies. The approach involves partially dropping left-censored observations and truncating the duration length after which duration dependence is assumed to be minimal. Utilizing the U.S. Health and Retirement Study, we apply this approach to compute disability-free/healthy life expectancy (HLE) among older adults in the United States and compare duration-dependent models to the typical multistate model with the Markov assumption. Findings suggest that while duration dependence is present in transition probabilities, its effect on HLE is averaged out. As a result, the bias in this case is minimal, and the Markov assumption provides a plausible and parsimonious estimate of HLE.

The Association Between Accelerated Biological Aging and Cardiovascular Outcomes in Older Adults with Hypertension

BACKGROUND

Current hypertension treatments rely on chronological age, which may not reflect individual differences in aging and its impact on cardiovascular health. This study aimed to determine whether biological age can predict adverse outcomes in older adults with hypertension, independent of traditional risk factors including chronological age.

METHODS

An analysis of a prospective cohort was conducted using data from the Health and Retirement Study, a longitudinal survey of older adults in the United States. The Klemera-Doubal method was employed to calculate the biological age of the participants with hypertension at the time of enrollment in 2016. Discrete-time survival analysis was conducted to analyze the relationship between accelerated biological aging and the risk of mortality, heart disease, and stroke over four years of follow-up.

RESULTS

A total of 4,442 individuals were analyzed. Of these, 2,438 showed decelerated aging, whereas 2,004 experienced accelerated aging (biological age > chronological age). The median age of the patients in both groups was around 70 years. Both groups had similar racial and ethnic distributions and predominantly consisted of non-Hispanic whites. The accelerated aging group had a higher prevalence of chronic diseases, lower education levels, and less wealth than the decelerated aging group. After adjustment for these differences, accelerated aging was associated with a higher risk of a composite outcome of death, heart disease, and stroke, with an adjusted hazard ratio (a-HR) of 1.62 (95% confidence interval: 1.27-2.06, P = .001).

CONCLUSIONS

Accelerated biological age is a predictor of cardiovascular outcomes and death in patients with hypertension.

Evaluation of two scoring systems assessing the epiphyseal union at shoulder joint as predictors of chronological age among a sample of Egyptians

Age estimation has extensive medicolegal implications in civil and criminal identification. Despite the surge in adopting radiological investigations to assess developmental bony changes, the shoulder joint is understudied. A cross-sectional study was conducted, enrolling 283 shoulder radiographs of Egyptians, investigating the reliability of two previously established scores as predictors of chronological age using the epiphyseal maturation of proximal humerus and acromion process. Epiphyseal union of proximal humerus commenced at age of 16.1-17 and completed around 21, while complete acromial union was observed around the age of 20.8. Females significantly preceded males and showed lower mean total Scores A and B at different maturation stages. There was a significant strong positive correlation between the chronological age and the epiphyseal maturation of humerus, acromion and total shoulder scores with correlation coefficients between 0.84 and 0.9. The receiver operating characteristic curves showed significant discriminating power of the total shoulder Scores A and B as predictors of the ages of 14 and 16, with area under curves above 0.9, minimal accuracy of 96.5 % and p values of 0.001. Six proposed models were established where the model "age = 0.318 + (0.388) total shoulder Score A + (2.842) total shoulder Score B + 1.931 (sex)" showed the best significant prediction power of radiographic evaluation of epiphyseal maturation in the proximal humerus and acromion in estimating the ages between 8 and around 20 years (R2 of 0.812). Applying this model to assess the chronological age, especially if the results from the hand and teeth are inconclusive, is promising.

Identifying biological markers and sociodemographic factors that influence the gap between phenotypic and chronological ages

INTRODUCTION

The world's population is aging rapidly, leading to increased public health and economic burdens due to age-related cardiovascular and neurodegenerative diseases. Early risk detection is essential for prevention and to improve the quality of life in elderly individuals. Plus, health risks associated with aging are not directly tied to chronological age, but are also influenced by a combination of environmental exposures. Past research has introduced the concept of "Phenotypic Age," which combines age with biomarkers to estimate an individual's health risk.

METHODS

This study explores which factors contribute most to the gap between chronological and phenotypic ages. We combined ten machine learning regression techniques applied to the NHANES dataset, containing demographic, laboratory and socioeconomic data from 41,474 patients, to identify the most important features. We then used clustering analysis and a mixed-effects model to stratify by sex, ethnicity, and education.

RESULTS

We identified 28 demographic, biological and environmental factors related to a significant gap between phenotypic and chronological ages. Stratifying for sex, education and ethnicity, we found statistically significant differences in the outcome distributions.

CONCLUSION

By showing that health risk prevention should consider both biological and sociodemographic factors, we offer a new approach to predict aging rates and potentially improve targeted prevention strategies for age-related conditions.

Generations of epigenetic clocks and their links to socioeconomic status in the Health and Retirement Study

Aim: This is a brief description of links between nine epigenetic clocks related to human aging and socioeconomic and behavioral characteristics as well as health outcomes.Materials & methods: We estimate frequently used and novel clocks from one data source, the Health and Retirement Study.Results: While all of these clocks are thought to reflect "aging," they use different CpG sites and do not strongly relate to each other. First and fourth generation clocks are not as linked to socioeconomic status or health outcomes as second and third generation clocks.Conclusion: Epigenetic clocks reflect exciting new tools and their continued evolution is likely to improve our understanding of how exposures get under the skin to accelerate aging.

The mouse Social Frailty Index (mSFI): a novel behavioral assessment for impaired social functioning in aging mice

Various approaches exist to quantify the aging process and estimate biological age on an individual level. Frailty indices based on an age-related accumulation of physical deficits have been developed for human use and translated into mouse models. However, declines observed in aging are not limited to physical functioning but also involve social capabilities. The concept of "social frailty" has been recently introduced into human literature, but no index of social frailty exists for laboratory mice yet. To fill this gap, we developed a mouse Social Frailty Index (mSFI) consisting of seven distinct assays designed to quantify social functioning which is relatively simple to execute and is minimally invasive. Application of the mSFI in group-housed male C57BL/6 mice demonstrated a progressively elevated levels of social frailty through the lifespan. Conversely, group-housed females C57BL/6 mice manifested social frailty only at a very old age. Female mice also showed significantly lower mSFI score from 10 months of age onward when compared to males. We also applied the mSFI in male C57BL/6 mice under chronic subordination stress and in chronic isolation, both of which induced larger increases in social frailty compared to age-matched group-housed males. Lastly, we show that the mSFI is enhanced in mouse models that show accelerated biological aging such as progeroid Ercc1-/Δ and Xpg-/- mice of both sexes compared to age matched littermate wild types. In summary, the mSFI represents a novel index to quantify trajectories of biological aging in mice and may help elucidate links between impaired social behavior and the aging process.

Gene-Environment Interactions and Gene-Gene Interactions on Two Biological Age Measures: Evidence from Taiwan Biobank Participants

PhenoAge and BioAge are two commonly used biological age (BA) measures. The author here searched for gene-environment interactions (GxE) and gene-gene interactions (GxG) on PhenoAgeAccel (age-adjusted PhenoAge) and BioAgeAccel (age-adjusted BioAge) of 111,996 Taiwan Biobank (TWB) participants, including a discovery set of 86,536 TWB2 individuals and a replication set of 25,460 TWB1 individuals. Searching for variance quantitative trait loci (vQTLs) provides a convenient way to evaluate GxE and GxG. A total of 4 nearly independent (linkage disequilibrium measure r2 < 0.01) PhenoAgeAccel-vQTLs are identified from 5,303,039 autosomal TWB2 SNPs (p < 5E-8), whereas no vQTLs are found from BioAgeAccel. These 4 PhenoAgeAccel-vQTLs (rs35276921, rs141927875, rs10903013, and rs76038336) are further replicated by TWB1 (p < 5E-8). They are located in the OR51B5, FAM234A, and AXIN1 genes. All 4 PhenoAgeAccel-vQTLs are significantly associated with PhenoAgeAccel (p < 5E-8). A phylogenetic heat map of the GxE analyses showed that smoking exacerbated the PhenoAgeAccel-vQTLs' aging effects, while higher educational attainment attenuated the PhenoAgeAccel-vQTLs' aging effects. Body mass index, chronological age, alcohol consumption, and sex do not prominently modulate PhenoAgeAccel-vQTLs' aging effects. Based on these vQTL results, rs141927875-rs35276921 interaction (p = 4.7E-61) and rs76038336-rs10903013 interaction (p = 3.3E-116) on PhenoAgeAccel are detected.

Blaming the young is always more accessible rather than accusing the older employees: an experimental view over age and health in organizations

Introduction

The stereotype content model postulates that different groups evoke different emotions and reactions based on two dimensions: intention toward others (warmth) and competence.

Methods

In this study, we used an experimental design and a qualitative approach to investigate how managerial strategies are selected and motivated when a subordinate makes a work task related error but belongs to a group that is stereotypical perceived differently in terms of warmth and competence (age groups with or without a medical condition). Thus 75 employees analyzed one of the five hypothetical cases and described the managerial strategy and motivation for usage.

Results

Data revealed that managerial strategies incorporate more active harm elements for younger employees in contrast with vulnerable groups (older employees with unspecified medical conditions, younger or older employees with a medical condition), who benefit from more active facilitation strategies. The strategy usage motivation is also different in the case of younger employees, the control group and the vulnerable groups.

Discussion

The study outcomes bring additional evidence to support the stereotype content model theory and the socioemotional selectivity theory, enriching applicability on organizational practice and human resources management.

Parental Divorce in Childhood and the Accelerated Epigenetic Aging for Earlier and Later Cohorts: Role of Mediators of Chronic Depressive Symptoms, Education, Smoking, Obesity, and Own Marital Disruption

We examine effects of parental divorce on epigenetic aging in later adulthood for two birth cohorts: one born in the early 20th century and the other born in the later 20th century. Using data from the Health and Retirement Study (n = 1,545), we examine the relationship between parental divorce in childhood and accelerated epigenetic aging in older adulthood as indicated by the Dunedin methylation Pace of Aging score. We assess how this relationship is mediated by chronic depressive symptoms, education, lifetime smoking, body mass index (BMI), and an older adult's own divorce. The mean age of the earlier cohort is 85.8 (SD = 3.9) and that of the later cohort is 60.2 (SD = 2.8). We find that parental divorce was related to faster aging in the later-born cohort, and that 56% of this relationship (b = 0.060) was mediated by chronic depressive symptoms (b = 0.013), lower education levels (b = 0.005), and smoking (b = 0.019). For the earlier cohort, there was no effect of parental divorce on epigenetic aging. Parental divorce in childhood may have lasting effects on later-life health, as reflected in the rate of epigenetic aging. However, the effects and mechanisms of this relationship differ across cohorts living in different social environments.

The embodiment of parental death in early life through accelerated epigenetic aging: Implications for understanding how parental death before 18 shapes age-related health risk among older adults

Parental death in early life has been linked to various adverse health outcomes in older adulthood. This study extends prior research to evaluate how parental death in early life is tied to accelerated epigenetic aging, a potentially important biological mechanism from which social and environmental exposures impact age-related health. We used data from the 2016 Venous Blood Study (VBS), a component of the Health and Retirement Study (HRS), to examine the association between parental death in early life and accelerated epigenetic aging as measured by three widely used epigenetic clocks (PCPhenoAge, PCGrimAge, and DunedinPACE). We also assessed whether some of the association is explained by differences in educational attainment, depressive symptoms, and smoking behavior. Methods included a series of linear regression models and formal mediation analysis. Findings indicated that parental death in early life is associated with accelerated epigenetic aging for PCPhenoAge and DunedinPACE. The inclusion of educational attainment, depressive symptoms, and smoking behavior attenuated this association, with formal mediation analysis providing additional support for these observations. Parental death in early life may be one of the most difficult experiences an individual may face. The elevated biological risk associated with parental death in early life may operate through immediate changes but also through more downstream risk factors. This study highlights how early life adversity can set in motion biological changes that have lifelong consequences.

Accelerated Pace of Aging in Schizophrenia: Five Case-Control Studies

BACKGROUND

Schizophrenia is associated with increased risk of developing multiple aging-related diseases, including metabolic, respiratory, and cardiovascular diseases, and Alzheimer's and related dementias, leading to the hypothesis that schizophrenia is accompanied by accelerated biological aging. This has been difficult to test because there is no widely accepted measure of biological aging. Epigenetic clocks are promising algorithms that are used to calculate biological age on the basis of information from combined cytosine-phosphate-guanine sites (CpGs) across the genome, but they have yielded inconsistent and often negative results about the association between schizophrenia and accelerated aging. Here, we tested the schizophrenia-aging hypothesis using a DNA methylation measure that is uniquely designed to predict an individual's rate of aging.

METHODS

We brought together 5 case-control datasets to calculate DunedinPACE (Pace of Aging Calculated from the Epigenome), a new measure trained on longitudinal data to detect differences between people in their pace of aging over time. Data were available from 1812 psychosis cases (schizophrenia or first-episode psychosis) and 1753 controls. Mean chronological age was 38.9 (SD = 13.6) years.

RESULTS

We observed consistent associations across datasets between schizophrenia and accelerated aging as measured by DunedinPACE. These associations were not attributable to tobacco smoking or clozapine medication.

CONCLUSIONS

Schizophrenia is accompanied by accelerated biological aging by midlife. This may explain the wide-ranging risk among people with schizophrenia for developing multiple different age-related physical diseases, including metabolic, respiratory, and cardiovascular diseases, and dementia. Measures of biological aging could prove valuable for assessing patients' risk for physical and cognitive decline and for evaluating intervention effectiveness.

Retirement Makes You Old? Causal Effect of Retirement on Biological Age

Retirement is a critical life event for older people. Health scholars have scrutinized the health effects of retirement, but its consequences on age-related diseases and mortality are unclear. We extend this body of research by integrating measurements of biological age, representing the physiological decline preceding disease onset. Using data from the UK Biobank and a fuzzy regression discontinuity design, we estimated the effects of retirement on two biomarker-based biological age measures. Results showed that retirement significantly increases biological age for those induced to retire by the State Pension eligibility by 0.871-2.503 years, depending on sex and specific biological age measurement. Given the emerging scientific discussion about direct interventions to biological age to achieve additional improvements in population health, the positive effect of retirement on biological age has important implications for an increase in the State Pension eligibility age and its potential consequences on population health, public health care policy, and older people's labor force participation. Overall, this study provides novel empirical evidence contributing to the question of what social factors make people old.

Heterogeneity of increased biological age in type 2 diabetes correlates with differential tissue DNA methylation, biological variables, and pharmacological treatments

Biological age (BA) closely depicts age-related changes at a cellular level. Type 2 diabetes mellitus (T2D) accelerates BA when calculated using clinical biomarkers, but there is a large spread in the magnitude of individuals' age acceleration in T2D suggesting additional factors contributing to BA. Additionally, it is unknown whether BA can be changed with treatment. We hypothesized that potential determinants of the heterogeneous BA distribution in T2D could be due to differential tissue aging as reflected at the DNA methylation (DNAm) level, or biological variables and their respective therapeutic treatments. Publicly available DNAm samples were obtained to calculate BA using the DNAm phenotypic age (DNAmPhenoAge) algorithm. DNAmPhenoAge showed age acceleration in T2D samples of whole blood, pancreatic islets, and liver, but not in adipose tissue or skeletal muscle. Analysis of genes associated with differentially methylated CpG sites found a significant correlation between eight individual CpG methylation sites and gene expression. Clinical biomarkers from participants in the NHANES 2017-2018 and ACCORD cohorts were used to calculate BA using the Klemera and Doubal (KDM) method. Cardiovascular and glycemic biomarkers associated with increased BA while intensive blood pressure and glycemic management reduced BA to CA levels, demonstrating that accelerated BA can be restored in the setting of T2D.

Geroscience and pathology: a new frontier in understanding age-related diseases

Geroscience, a burgeoning discipline at the intersection of aging and disease, aims to unravel the intricate relationship between the aging process and pathogenesis of age-related diseases. This paper explores the pivotal role played by geroscience in reshaping our understanding of pathology, with a particular focus on age-related diseases. These diseases, spanning cardiovascular and cerebrovascular disorders, malignancies, and neurodegenerative conditions, significantly contribute to the morbidity and mortality of older individuals. We delve into the fundamental cellular and molecular mechanisms underpinning aging, including mitochondrial dysfunction and cellular senescence, and elucidate their profound implications for the pathogenesis of various age-related diseases. Emphasis is placed on the importance of assessing key biomarkers of aging and biological age within the realm of pathology. We also scrutinize the interplay between cellular senescence and cancer biology as a central area of focus, underscoring its paramount significance in contemporary pathological research. Moreover, we shed light on the integration of anti-aging interventions that target fundamental aging processes, such as senolytics, mitochondria-targeted treatments, and interventions that influence epigenetic regulation within the domain of pathology research. In conclusion, the integration of geroscience concepts into pathological research heralds a transformative paradigm shift in our understanding of disease pathogenesis and promises breakthroughs in disease prevention and treatment.

The Semmelweis Study: a longitudinal occupational cohort study within the framework of the Semmelweis Caring University Model Program for supporting healthy aging

The Semmelweis Study is a prospective occupational cohort study that seeks to enroll all employees of Semmelweis University (Budapest, Hungary) aged 25 years and older, with a population of 8866 people, 70.5% of whom are women. The study builds on the successful experiences of the Whitehall II study and aims to investigate the complex relationships between lifestyle, environmental, and occupational risk factors, and the development and progression of chronic age-associated diseases. An important goal of the Semmelweis Study is to identify groups of people who are aging unsuccessfully and therefore have an increased risk of developing age-associated diseases. To achieve this, the study takes a multidisciplinary approach, collecting economic, social, psychological, cognitive, health, and biological data. The Semmelweis Study comprises a baseline data collection with open healthcare data linkage, followed by repeated data collection waves every 5 years. Data are collected through computer-assisted self-completed questionnaires, followed by a physical health examination, physiological measurements, and the assessment of biomarkers. This article provides a comprehensive overview of the Semmelweis Study, including its origin, context, objectives, design, relevance, and expected contributions.

Improving Cognitive Function with Nutritional Supplements in Aging: A Comprehensive Narrative Review of Clinical Studies Investigating the Effects of Vitamins, Minerals, Antioxidants, and Other Dietary Supplements

Cognitive impairment and dementia are burgeoning public health concerns, especially given the increasing longevity of the global population. These conditions not only affect the quality of life of individuals and their families, but also pose significant economic burdens on healthcare systems. In this context, our comprehensive narrative review critically examines the role of nutritional supplements in mitigating cognitive decline. Amidst growing interest in non-pharmacological interventions for cognitive enhancement, this review delves into the efficacy of vitamins, minerals, antioxidants, and other dietary supplements. Through a systematic evaluation of randomized controlled trials, observational studies, and meta-analysis, this review focuses on outcomes such as memory enhancement, attention improvement, executive function support, and neuroprotection. The findings suggest a complex interplay between nutritional supplementation and cognitive health, with some supplements showing promising results and others displaying limited or context-dependent effectiveness. The review highlights the importance of dosage, bioavailability, and individual differences in response to supplementation. Additionally, it addresses safety concerns and potential interactions with conventional treatments. By providing a clear overview of current scientific knowledge, this review aims to guide healthcare professionals and researchers in making informed decisions about the use of nutritional supplements for cognitive health.

Biological age and brain age in midlife: relationship to multimorbidity and mental health

Biological age and brain age estimated using biological and neuroimaging measures have recently emerged as surrogate aging biomarkers shown to be predictive of diverse health outcomes. As aging underlies the development of many chronic conditions, surrogate aging biomarkers capture health at the whole person level, having the potential to improve our understanding of multimorbidity. Our study investigates whether elevated biological age and brain age are associated with an increased risk of multimorbidity using a large dataset from the Midlife in the United States Refresher study. Ensemble learning is utilized to combine multiple machine learning models to estimate biological age using a comprehensive set of biological markers. Brain age is obtained using Gaussian processes regression and neuroimaging data. Our study is the first to examine the relationship between accelerated brain age and multimorbidity. Furthermore, it is the first attempt to explore how biological age and brain age are related to multimorbidity in mental health. Our findings hold the potential to advance the understanding of disease accumulation and their relationship with aging.

Discordant Biological and Chronological Age: Implications for Cognitive Decline and Frailty

BACKGROUND

Older adults with discordant biological and chronological ages (BA and CA) may vary in cognitive and physical function from those with concordant BA and CA.

METHODS

To make our approach clinically accessible, we created easy-to-interpret participant groups in the Health, Aging, and Body Composition Study (N = 2 458, 52% female participants, 65% White participants, age: 73.5 ± 2.8) based on medians of CA, and a previously validated BA index comprised of readily available clinical tests. Joint models estimated associations of BA-CA group with cognition (Modified Mini-Mental State Examination [3MS] and Digit Symbol Substitution Test [DSST]) and frailty over 10 years.

RESULTS

The sample included the following: 32%, Young group (BA and CA < median); 21%, Prematurely Aging group (BA ≥ median, CA < median), 27%, Old group (BA and CA ≥ median), and 20%, Resilient group (BA < median, CA ≥ median). In education-adjusted models of cognition, among those with CA < median, the Prematurely Aging group performed worse than the Young at baseline (3MS and DSST p < .0001), but among those with CA ≥ median, the Resilient group did not outperform the Old group (3MS p = .31; DSST p = .25). For frailty, the Prematurely Aging group performed worse than the Young group at baseline (p = .0001), and the Resilient group outperformed the Old group (p = .003). For all outcomes, groups did not differ on change over time based on the same pairwise comparisons (p ≥ .40).

CONCLUSIONS

Discordant BA and CA identify groups who have greater cognitive and physical functional decline or are more protected than their CA would suggest. This information can be used for risk stratification.

Can We Slow Down Biological Age Progression? Study Protocol for the proBNPage Reduction (PBAR) Randomized, Double-Blind, Placebo-Controlled Trial (Effects of 4 "Anti-Aging" Food Supplements in Healthy Older Adults)

Purpose

The availability of a simple and reliable marker of biological age might allow an acceleration of the research in the field of longevity extension. Previous studies suggest that this marker might be the N-terminal of B-type natriuretic peptide precursor (NT-proBNP), from which proBNPage, a biological age surrogate, can be calculated. Objectives of the study: 1) To fine-tune the method of proBNPage progression assessment and 2) To establish whether 4 "anti-aging" treatments, which provided promising results in previous studies, can modify proBNPage progression.

Patients and Methods

This is a double-blind randomized placebo-controlled clinical trial on 120 adults aged 65-80 years, free of cardiovascular diseases. Participants will be randomized into 3 groups: A) Coenzyme Q10 100 mg bid + Selenium 100 mcg; B) Resveratrol 350 mg bid + TA-65 (Astragalus Membranaceus extract) 100U; C) Placebo-1 bid + Placebo-2. They will be followed for 2 years and checked 8 times, to assess both proBNPage progression and treatment safety. Secondary variables (handgrip strength, aerobic capacity at the step test and quality of life) will also be assessed. Primary outcome will be the demonstration of significant changes of proBNPage, compared to baseline, in the 3 groups at 6, 12, 18 and 24 months. Secondary outcome will be the demonstration of similar changes of secondary variables. Statistical analyses will be mainly performed by repeated measures ANOVA (both according to intention to treat and per protocol) and paired t tests. The study was approved by the Ethics Committee Area Vasta Emilia Centro, Emilia-Romagna Region, ID: 64/2022/Sper/AOUBo. Trial registration: ClinicalTrials.gov, NCT05500742.

Conclusion

The use of proBNPage as a surrogate of biological age may prove an easy method to select anti-aging treatments worthy of further, more complex assessments.

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

OBJECTIVES

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.

METHODS

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.

RESULTS

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).

DISCUSSION

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.

Aging on the Job? The Association Between Occupational Characteristics and Accelerated Biological Aging

OBJECTIVES

There is a common belief that demanding jobs can make workers age faster, but there is little empirical evidence linking occupational characteristics to accelerated biological aging. We examine how occupational categorizations and self-reported working conditions are associated with expanded biological age, which incorporates 22 biomarkers and captures physiologic dysregulation throughout several bodily systems.

METHODS

Data are from 1,133 participants in the Health and Retirement Study who were aged 51-60 and working for pay in the 2010 or 2012 wave and who participated in the 2016 Venous Blood Study. We estimate associations between occupational category (professional/managerial, sales/clerical, service, and manual) and self-reported working conditions (psychosocial demands, job control, heavy lifting, and working 55 or more hours per week) and expanded biological age.

RESULTS

Compared to same-age individuals working in professional or managerial positions, those working in service jobs appear 1.65 years older biologically even after adjusting for social and economic characteristics, self-reported working conditions, health insurance, and lifestyle-related risk factors. Low job control is associated with 1.40 years, heavy lifting with 2.08 years, and long working hours with 1.87 years of accelerated biological aging.

DISCUSSION

Adverse occupational characteristics held at midlife, particularly service work, low job control, heavy lifting, and long work hours, are associated with accelerated biological aging. These findings suggest that work may be important for the overall aging process beyond its associations with specific diseases or risk factors.

Racial/Ethnic Differences in Biological Aging and Their Life Course Socioeconomic Determinants: The 2016 Health and Retirement Study

Objectives: This study examined differences in accelerated biological aging among non-Hispanic Blacks, Hispanics, and non-Hispanic Whites in the United States and assessed whether including life course socioeconomic conditions attenuated observed racial/ethnic differences. Methods: Data came from the Venous Blood Collection Subsample of the Health and Retirement Study. We used a comprehensive summary measure of biological age (BA-22). We determined whether key lifetime socioeconomic conditions contributed to racial/ethnic differences in biological aging. Results: Findings indicated that non-Hispanic Blacks and Hispanics have accelerated aging, and non-Hispanic Whites have decelerated aging. Racial/ethnic differences were strongly tied to educational attainment. We also observed a significant difference by birthplace for Hispanics. US-born Hispanics had accelerated biological aging, whereas foreign-born Hispanics did not. In age-stratified analyses, these racial/ethnic differences were found for adults aged 56-74, but not for adults aged 75+. Conclusions: These findings provide insight into biological differences underlying racial/ethnic disparities in health.

Epigenetic-based age acceleration in a representative sample of older Americans: Associations with aging-related morbidity and mortality

Biomarkers developed from DNA methylation (DNAm) data are of growing interest as predictors of health outcomes and mortality in older populations. However, it is unknown how epigenetic aging fits within the context of known socioeconomic and behavioral associations with aging-related health outcomes in a large, population-based, and diverse sample. This study uses data from a representative, panel study of US older adults to examine the relationship between DNAm-based age acceleration measures in the prediction of cross-sectional and longitudinal health outcomes and mortality. We examine whether recent improvements to these scores, using principal component (PC)-based measures designed to remove some of the technical noise and unreliability in measurement, improve the predictive capability of these measures. We also examine how well DNAm-based measures perform against well-known predictors of health outcomes such as demographics, SES, and health behaviors. In our sample, age acceleration calculated using "second and third generation clocks," PhenoAge, GrimAge, and DunedinPACE, is consistently a significant predictor of health outcomes including cross-sectional cognitive dysfunction, functional limitations and chronic conditions assessed 2 y after DNAm measurement, and 4-y mortality. PC-based epigenetic age acceleration measures do not significantly change the relationship of DNAm-based age acceleration measures to health outcomes or mortality compared to earlier versions of these measures. While the usefulness of DNAm-based age acceleration as a predictor of later life health outcomes is quite clear, other factors such as demographics, SES, mental health, and health behaviors remain equally, if not more robust, predictors of later life outcomes.

Familial aggregation of the aging process: biological age measured in young adult offspring as a predictor of parental mortality

Measures of biological age (BA) integrate information across organ systems to quantify "biological aging," i.e., inter-individual differences in aging-related health decline. While longevity and lifespan aggregate in families, reflecting transmission of genes and environments across generations, little is known about intergenerational continuity of biological aging or the extent to which this continuity may be modified by environmental factors. Using data from the Jerusalem Perinatal Study (JPS), we tested if differences in offspring BA were related to mortality in their parents. We measured BA using biomarker data collected from 1473 offspring during clinical exams in 2007-2009, at age 32 ± 1.1. Parental mortality was obtained from population registry data for the years 2004-2016. We fitted parametric survival models to investigate the associations between offspring BA and parental all-cause and cause-specific mortality. We explored potential differences in these relationships by socioeconomic position (SEP) and offspring sex. Participants' BAs widely varied (SD = 6.95). Among those measured to be biologically older, parents had increased all-cause mortality (HR = 1.10, 95% CI: 1.08, 1.13), diabetes mortality (HR = 1.19, 95% CI: 1.08, 1.30), and cancer mortality (HR = 1.07, 95% CI: 1.02, 1.13). The association with all-cause mortality was stronger for families with low compared with high SEP (P_interaction = 0.04) and for daughters as compared to sons (P_interaction < 0.001). Using a clinical-biomarker-based BA estimate, observable by young adulthood prior to the onset of aging-related diseases, we demonstrate intergenerational continuity of the aging process. Furthermore, variation in this familial aggregation according to household socioeconomic position (SEP) at offspring birth and between families of sons and daughters proposes that the environment alters individuals' aging trajectory set by their parents.

Association of Pace of Aging Measured by Blood-Based DNA Methylation With Age-Related Cognitive Impairment and Dementia

BACKGROUND AND OBJECTIVES

DNA methylation algorithms are increasingly used to estimate biological aging; however, how these proposed measures of whole-organism biological aging relate to aging in the brain is not known. We used data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the Framingham Heart Study (FHS) Offspring Cohort to test the association between blood-based DNA methylation measures of biological aging and cognitive impairment and dementia in older adults.

METHODS

We tested 3 "generations" of DNA methylation age algorithms (first generation: Horvath and Hannum clocks; second generation: PhenoAge and GrimAge; and third generation: DunedinPACE, Dunedin Pace of Aging Calculated from the Epigenome) against the following measures of cognitive impairment in ADNI: clinical diagnosis of dementia and mild cognitive impairment, scores on Alzheimer disease (AD) / Alzheimer disease and related dementias (ADRD) screening tests (Alzheimer's Disease Assessment Scale, Mini-Mental State Examination, and Montreal Cognitive Assessment), and scores on cognitive tests (Rey Auditory Verbal Learning Test, Logical Memory test, and Trail Making Test). In an independent replication in the FHS Offspring Cohort, we further tested the longitudinal association between the DNA methylation algorithms and the risk of developing dementia.

RESULTS

In ADNI (N = 649 individuals), the first-generation (Horvath and Hannum DNA methylation age clocks) and the second-generation (PhenoAge and GrimAge) DNA methylation measures of aging were not consistently associated with measures of cognitive impairment in older adults. By contrast, a third-generation measure of biological aging, DunedinPACE, was associated with clinical diagnosis of Alzheimer disease (beta [95% CI] = 0.28 [0.08-0.47]), poorer scores on Alzheimer disease/ADRD screening tests (beta [Robust SE] = -0.10 [0.04] to 0.08[0.04]), and cognitive tests (beta [Robust SE] = -0.12 [0.04] to 0.10 [0.03]). The association between faster pace of aging, as measured by DunedinPACE, and risk of developing dementia was confirmed in a longitudinal analysis of the FHS Offspring Cohort (N = 2,264 individuals, hazard ratio [95% CI] = 1.27 [1.07-1.49]).

DISCUSSION

Third-generation blood-based DNA methylation measures of aging could prove valuable for measuring differences between individuals in the rate at which they age and in their risk for cognitive decline, and for evaluating interventions to slow aging.

Estimated Pulse Wave Velocity and All-Cause Mortality: Findings From the Health and Retirement Study

Background and Objectives

The gold standard method for the assessment of vascular aging is carotid-femoral pulse wave velocity (cfPWV). cfPWV can be estimated from 2 commonly assessed clinical variables-age and blood pressure. This analysis uses data from the Health and Retirement Study to examine the relationship between estimated pulse wave velocity (ePWV) and mortality among 9,293 middle age and older adults.

Research Design and Methods

Cox proportional hazard models were used to predict mortality occurring over a 10- to 12-year period. Controls were included for sociodemographic characteristics (age, gender, race, ethnicity, wealth, income, and education), health status (history of cardiovascular disease [CVD], diabetes, and stroke and related medication use), health behaviors (smoking, physical activity, and body mass index), and CVD-related biomarkers (systolic and diastolic blood pressure, C-reactive protein, cystatin c, hemoglobin A1c, total cholesterol, and high-density lipoprotein cholesterol).

Results

By 2018, 26.19% of the weighted analytic sample were reported as deceased. In the fully specified models that control for age, age-squared, systolic and diastolic blood pressure, sociodemographic variables, health status and behaviors, and biomarkers, ePWV was associated with a greater likelihood of mortality.

Discussion and Implications

An estimate of PWV derived from age and blood pressure is independently associated with an increased likelihood of death in a representative sample of middle age and older adults in the United States.

Diet Quality and Biological Risk in a National Sample of Older Americans

Objectives: Using comprehensive measures of biological risk, this study aims to investigate the relationship between intake of individual dietary components, overall diet quality, and biological dysregulation. Methods: We analyzed nationally representative data from 3734 older adults who participated in the Health and Retirement Study Venous Blood Study in 2016 and Health Care and Nutrition Survey in 2013. Results: Eleven out of 13 individual dietary components were associated with lower biological risk. Respondents with poor/suboptimal quality diet had higher biological risk than those with good quality diet. Discussion: Findings from this study emphasize the importance of healthy eating in improving health of older adults. Encouraging intake of fruits, greens and beans, whole grains, and fatty acids, while limiting consumption of sodium, added sugar, and saturated fat would improve overall diet quality and contribute to the prevention of chronic diseases and morbidity.

Social mobility and biological aging among older adults in the United States

Lower socioeconomic status is associated with faster biological aging, the gradual and progressive decline in system integrity that accumulates with advancing age. Efforts to promote upward social mobility may, therefore, extend healthy lifespan. However, recent studies suggest that upward mobility may also have biological costs related to the stresses of crossing social boundaries. We tested associations of life-course social mobility with biological aging using data from participants in the 2016 Health and Retirement Study (HRS) Venous Blood Study who provided blood-chemistry (n = 9,255) and/or DNA methylation (DNAm) data (n = 3,976). We quantified social mobility from childhood to later-life using data on childhood family characteristics, educational attainment, and wealth accumulation. We quantified biological aging using 3 DNAm "clocks" and 3 blood-chemistry algorithms. We observed substantial social mobility among study participants. Those who achieved upward mobility exhibited less-advanced and slower biological aging. Associations of upward mobility with less-advanced and slower aging were consistent for blood-chemistry and DNAm measures of biological aging, and were similar for men and women and for Black and White Americans (Pearson-r effect-sizes ∼0.2 for blood-chemistry measures and the DNAm GrimAge clock and DunedinPoAm pace-of-aging measures; effect-sizes were smaller for the DNAm PhenoAge clock). Analysis restricted to educational mobility suggested differential effects by racial identity; mediating links between educational mobility and healthy aging may be disrupted by structural racism. In contrast, mobility producing accumulation of wealth appeared to benefit White and Black Americans equally, suggesting economic intervention to reduce wealth inequality may have potential to heal disparities in healthy aging.

All-Subset Analysis Improves the Predictive Accuracy of Biological Age for All-Cause Mortality in Chinese and U.S. Populations

BACKGROUND

Klemera-Doubal's method (KDM) is an advanced and widely applied algorithm for estimating biological age (BA), but it has no uniform paradigm for biomarker processing. This article proposed all subsets of biomarkers for estimating BAs and assessed their association with mortality to determine the most predictive subset and BA.

METHODS

Clinical biomarkers, including those from physical examinations and blood assays, were assessed in the China Health and Nutrition Survey (CHNS) 2009 wave. Those correlated with chronological age (CA) were combined to produce complete subsets, and BA was estimated by KDM from each subset of biomarkers. A Cox proportional hazards regression model was used to examine and compare each BA's effect size and predictive capacity for all-cause mortality. Validation analysis was performed in the Chinese Longitudinal Healthy Longevity Survey (CLHLS) and National Health and Nutrition Examination Survey (NHANES). KD-BA and Levine's BA were compared in all cohorts.

RESULTS

A total of 130 918 panels of BAs were estimated from complete subsets comprising 3-17 biomarkers, whose Pearson coefficients with CA varied from 0.39 to 1. The most predictive subset consisted of 5 biomarkers, whose estimated KD-BA had the most predictive accuracy for all-cause mortality. Compared with Levine's BA, the accuracy of the best-fitting KD-BA in predicting death varied among specific populations.

CONCLUSION

All-subset analysis could effectively reduce the number of redundant biomarkers and significantly improve the accuracy of KD-BA in predicting all-cause mortality.

Evaluation of a blood-based geroscience biomarker index in a randomized trial of caloric restriction and exercise in older adults with heart failure with preserved ejection fraction

Intermediate endpoints are needed to evaluate the effect of interventions targeting the biology of aging in clinical trials. A working group identified five blood-based biomarkers that may serve such a purpose as an integrated index. We evaluated the responsiveness of the panel to caloric restriction or aerobic exercise in the context of a randomized clinical trial conducted in patients with heart failure with preserved ejection fraction (HFpEF) with obese phenotype who were predominantly female. Obese HFpEF is highly prevalent in women, and is a geriatric syndrome whose disease pathology is driven by non-cardiac factors and shared drivers of aging. We measured serum Interleukin-6, TNF-α-receptor-I, growth differentiating factor-15, cystatin C, and N-terminal pro-b-type natriuretic peptide at baseline and after 20 weeks in older participants with stable obese HFpEF participating in a randomized, controlled, 2 × 2 factorial trial of caloric restriction and/or aerobic exercise. We calculated a composite biomarker index, summing baseline quintile scores for each biomarker, and analyzed the effect of the interventions on the index and individual biomarkers and their associations with changes in physical performance. This post hoc analysis included 88 randomized participants (71 women [81%]). The mean ± SD age was 66.6 ± 5.3 years, and body mass index (BMI) was 39.3 ± 6.3 kg/m2. Using mixed models, mean values of the biomarker index improved over 20 weeks with caloric restriction (- 0.82 [Formula: see text] 0.58 points, p = 0.05), but not with exercise (- 0.28 [Formula: see text] 0.59 points, p = [Formula: see text]), with no evidence of an interaction effect of CR [Formula: see text] EX [Formula: see text] time (p = 0.80) with adjustment for age, gender, and BMI. At baseline, the biomarker index was inversely correlated with 6-min walk distance, scores on the short physical performance battery, treadmill test peak workload and exercise time to exhaustion (all [Formula: see text] s = between - 0.21 and - 0.24). A reduction in the biomarker index was also associated with increased 4-m usual walk speed ([Formula: see text] s =  - 0.31). Among older patients with chronic obese HFpEF, caloric restriction improved a biomarker index designed to reflect biological aging. Moreover, the index was associated with physical performance and exercise tolerance.

Integrating DNA Methylation Measures of Biological Aging into Social Determinants of Health Research

PURPOSE OF REVIEW

Acceleration of biological processes of aging is hypothesized to drive excess morbidity and mortality in socially disadvantaged populations. DNA methylation measures of biological aging provide tools for testing this hypothesis.

RECENT FINDINGS

Next-generation DNA methylation measures of biological aging developed to predict mortality risk and physiological decline are more predictive of morbidity and mortality than the original epigenetic clocks developed to predict chronological age. These new measures show consistent evidence of more advanced and faster biological aging in people exposed to socioeconomic disadvantage and may be able to record the emergence of socially determined health inequalities as early as childhood. Next-generation DNA methylation measures of biological aging also indicate race/ethnic disparities in biological aging. More research is needed on these measures in samples of non-Western and non-White populations. New DNA methylation measures of biological aging open opportunities for refining inference about the causes of social disparities in health and devising policies to eliminate them. Further refining measures of biological aging by including more diversity in samples used for measurement development is a critical priority for the field.

The association of proBNPage with manifestations of age-related cardiovascular, physical, and psychological impairment in community-dwelling older adults

NT-proB-type natriuretic peptide (NT-proBNP) serum concentration can be transformed by simple formulas into proBNPage, a surrogate of biological age strongly associated with chronological age, all-cause mortality, and disease count. This cross-sectional study aimed to assess whether proBNPage is also associated with other manifestations of the aging process in comparison with other variables. The study included 1117 noninstitutionalized older adults (73.1 ± 5.6 years, 537 men). Baseline measurements of serum NT-proBNP, erythrocyte sedimentation rate, hemoglobin, lymphocytes, and creatinine, which have previously been shown to be highly associated with both age and all-cause mortality, were performed. These variables were compared between subjects with and without manifestations of cardiovascular impairment (myocardial infarction (MI), stroke, peripheral artery disease (PAD), arterial revascularizations (AR)), physical impairment (long step test duration (LSTD), walking problems, falls, deficit in one or more activities of daily living), and psychological impairment (poor self-rating of health (PSRH), anxiety/depression, Mini Mental State Examination (MMSE) score < 24). ProBNPage (years) was independently associated (OR, 95% CI) with MI (1.08, 1.07-1.10), stroke (1.02, 1.00-1.05), PAD (1.04, 1.01-1.06), AR (1.06, 1.04-1.08), LSTD (1.03, 1.02-1.04), walking problems (1.02, 1.01-1.03), and PSRH (1.02, 1.01-1.02). For 5 of these 7 associations, the relationship was stronger than that of chronological age. In addition, proBNPage was univariately associated with MMSE score < 24, anxiety/depression, and falls. None of the other variables provided comparable performances. Thus, in addition to the known associations with mortality and disease count, proBNPage is also associated with cardiovascular manifestations as well as noncardiovascular manifestations of the aging process.