Quantification of biological aging in young adults

Childhood Maltreatment and Biological Aging in Middle Adulthood: The Role of Psychiatric Symptoms

Background

Childhood maltreatment and psychiatric morbidity have each been associated with accelerated biological aging primarily through cross-sectional studies. Using data from a prospective longitudinal study of individuals with histories of childhood maltreatment and control participants followed into midlife, we tested 2 hypotheses examining whether 1) psychiatric symptoms mediate the relationship between childhood maltreatment and biological aging and 2) psychiatric symptoms of anxiety, depression, or posttraumatic stress disorder (PTSD) act in conjunction with childhood maltreatment to exacerbate the association of child maltreatment to aging.

Methods

Children (ages 0-11 years) with documented histories of maltreatment and demographically matched control children were followed into adulthood (N = 607) and interviewed over several waves of the study. Depression, anxiety, and PTSD symptoms were assessed at mean ages of 29 (interview 1) and 40 (interview 2) years. Biological age was measured from blood chemistries collected later (mean age = 41 years) using the Klemera-Doubal method. Hypotheses were tested using linear regressions and path analyses.

Results

Adults with documented histories of childhood maltreatment showed more symptoms of depression, PTSD, and anxiety at both interviews and more advanced biological aging, compared with control participants. PTSD symptoms at both interviews and depression and anxiety symptoms only at interview 2 predicted accelerated biological aging. There was no evidence of mediation; however, anxiety and depression moderated the relationship between childhood maltreatment and biological aging.

Conclusions

These new findings reveal the shorter- and longer-term longitudinal impact of PTSD on biological aging and the amplifying effect of anxiety and depression on the relationship between child maltreatment and biological aging.

Frailty and biological age. Which best describes our aging and longevity?

Frailty and Biological Age are two closely related concepts; however, frailty is a multisystem geriatric syndrome that applies to elderly subjects, whereas biological age is a gerontologic way to describe the rate of aging of each individual, which can be used from the beginning of the aging process, in adulthood. If frailty reaches less consensus on the definition, it is a term much more widely used than this of biological age, which shows a clearer definition but is scarcely employed in social and medical fields. In this review, we suggest that this Biological Age is the best to describe how we are aging and determine our longevity, and several examples support our proposal.

Frailty and all-cause and cancer-related mortality in cancer patients: A prospective cohort study

PURPOSE

To evaluate the associations between frailty and all-cause and cancer-related mortality. Additionally, the objective is to compare the magnitude of these associations between older adults and younger adults.

METHODS

We gathered baseline data from NHANES (1999-2018) and developed a cumulative index consisting of 39 items to evaluate frailty. The National Death Index database was utilized to track the survival status of individuals. The Cox regression model was employed to estimate the associations between frailty status and all-cause and cancer-related mortality.

RESULTS

Ultimately, 3398 cancer patients were included in the analysis, comprising 910 younger adults and 2488 older adults. Compared to non-frail patients, the elevated all-cause and cancer-related mortality among pre-frail patients was not statistically significant (HRs = 1.312, 95%CI: 0.956-1.800, P = 0.092; HRs = 1.462, 0.811-2.635, P = 0.207). However, a significant elevation of both all-cause and cancer-related mortality risk was observed among frail patients (HRs = 2.213, 1.617-3.030, P < 0.001; HRs = 2.463, 95%CI = 1.370-4.429, P = 0.003). Frailty individuals demonstrated a more pronounced association with the prediction of all-cause mortality in younger (HRs = 2.230, 1.073-4.634, P = 0.032) than in older adults (HRs = 2.090, 1.475-2.960, P < 0.001). Sensitivity analysis consistently revealed robust results. RCS plots suggested a progressively escalating dose-response correlation between frailty and both all-cause and cancer-related mortality risk.

CONCLUSIONS

Pre-frailty did not result in an increase in mortality risks compared to non-frailty. However, frailty caused a higher all-cause and cancer-related mortality risk than non-frailty. Identifying those at risk and implementing targeted interventions may contribute to extending healthy life expectancy, regardless of age.

Systematic mapping of organism-scale gene-regulatory networks in aging using population asynchrony

In aging, physiologic networks decline in function at rates that differ between individuals, producing a wide distribution of lifespan. Though 70% of human lifespan variance remains unexplained by heritable factors, little is known about the intrinsic sources of physiologic heterogeneity in aging. To understand how complex physiologic networks generate lifespan variation, new methods are needed. Here, we present Asynch-seq, an approach that uses gene-expression heterogeneity within isogenic populations to study the processes generating lifespan variation. By collecting thousands of single-individual transcriptomes, we capture the Caenorhabditis elegans "pan-transcriptome"-a highly resolved atlas of non-genetic variation. We use our atlas to guide a large-scale perturbation screen that identifies the decoupling of total mRNA content between germline and soma as the largest source of physiologic heterogeneity in aging, driven by pleiotropic genes whose knockdown dramatically reduces lifespan variance. Our work demonstrates how systematic mapping of physiologic heterogeneity can be applied to reduce inter-individual disparities in aging.

Time Changes of Survival and Cardiovascular Determinants in a Cohort of Middle-Aged Men Followed Up for 61 Years until Extinction

OBJECTIVE

To study possible determinants of longevity in a cohort of middle-aged men followed for 61 years until extinction using measurements taken at baseline and at years 31 or 61 of follow-up.

MATERIAL AND METHODS

In 1960, two rural cohorts including a total of 1712 men aged 40-59 years were enrolled within the Italian section of the Seven Countries Study of Cardiovascular Diseases, and measurements related to mainly cardiovascular risk factors, lifestyle behaviors, and chronic diseases were taken at year 0 and year 31 of follow-up (when only 390 could be examined). Multiple linear regression models were computed to relate personal characteristics with the length of survival in both dead men and survivors.

RESULTS

Baseline cardiovascular risk factors, smoking and dietary habits, and chronic diseases (taken at year 0 with men aged 40-59 years) were significant predictors of the length of survival both from year 0 to year 31 and from year 0 to year 61, but only chronic diseases were independent predictors for the period of 31 to 61 years. Significant predictors of survival using measurements taken at year 31 (age range 71 to 90 years) were only smoking and dietary habits and chronic diseases.

CONCLUSIONS

During a lifetime of follow-up, the personal characteristics with continuous predictive power of survival were only lifestyle behaviors and major chronic diseases.

Trauma, adversity, and biological aging: behavioral mechanisms relevant to treatment and theory

Although stress and adversity are largely universal experiences, people exposed to greater hardship are at increased risk for negative health consequences. Recent studies identify accelerated biological aging as a mechanism that could explain how trauma and adversity gives rise to poor health, and advances in this area of study coincide with technological innovations in the measurement of biological aging, particularly epigenetic profiles consistent with accelerated aging derived from DNA methylation. In this review, we provide an overview of the current literature examining how adversity might accelerate biological aging, with a specific focus on social and health behaviors. The most extensive evidence in this area suggests that health-compromising behaviors, particularly smoking, may partially explain the association between adversity and accelerated aging. Although there is relatively less published support for the role of social behaviors, emerging evidence points to the importance of social connection as a mechanism for future study. Our review highlights the need to determine the extent to which the associations from adversity to accelerated aging are consistent with causal processes. As we consider these questions, the review emphasizes methodological approaches from the causal inference literature that can help deepen our understanding of how stress and trauma might result in poor health. The use of these methodologies will help provide evidence as to which behavioral interventions might slow aging and improve health, particularly among populations that more often experience adversity and trauma.

Identifying critical age and gender-based metabolomic shifts in a Japanese population of the Tohoku Medical Megabank cohort

Understanding the physiological changes associated with aging and the associated disease risks is essential to establish biomarkers as indicators of biological aging. This study used the NMR-measured plasma metabolome to calculate age-specific metabolite indices. In doing so, the scope of the study was deliberately simplified to capture general trends and insights into age-related changes in metabolic patterns. In addition, changes in metabolite concentrations with age were examined in detail, with the period from 55-59 to 60-64 years being a period of significant metabolic change, particularly in men, and from 45-49 to 50-54 years in females. These results illustrate the different variations in metabolite concentrations by sex and provide new insights into the relationship between age and metabolic diseases.

One-Year Frailty Transitions Among Persons With HIV Aged 70 Years or Older on Antiretroviral Treatment

Background

People with HIV (PWH) are aging. Frailty is an age-related condition predictive of hospitalization and mortality. Here, we assessed the frequency and factors associated with frailty transitions at 1-year follow-up in elderly PWH.

Methods

Five hundred eight PWH aged 70 years or older who were on antiretroviral treatment were included in the French multicenter SEPTAVIH study in 2019-2020. Participants were classified as robust, prefrail, or frail according to Fried frailty phenotype at baseline and at 1 year. Logistic regression models were used to evaluate socioeconomic and medical factors associated with transition between frailty states. Models were adjusted for gender, age at baseline, education, and period of HIV diagnosis (before vs after 1996).

Results

Seventeen PWH died during the 1-year follow-up. Of the remaining 491 PWH (median age, 73 years), frailty status worsened for 18% of participants and improved for 14% at 1 year. Advanced age, baseline CD4+ T-cell count <350 cells/mm3, and type 2 diabetes were associated with transition from prefrailty to frailty (adjusted odds ratio [aOR], 1.10 per 1-year positive difference; 95% CI, 1.01-1.20; aOR, 3.05; 95% CI, 1.14-8.18; and aOR, 2.63; 95% CI, 1.05-6.57; respectively). Being female was associated with more frequent improvement from prefrailty to robustness (aOR, 2.50; 95% CI, 1.09-5.55).

Conclusions

Preventing frailty in elderly PWH is a long-term problem, beginning with the early diagnosis of HIV infection and the management of comorbidities.

Towards Healthy Longevity: Comprehensive Insights from Molecular Targets and Biomarkers to Biological Clocks

Aging is a complex and time-dependent decline in physiological function that affects most organisms, leading to increased risk of age-related diseases. Investigating the molecular underpinnings of aging is crucial to identify geroprotectors, precisely quantify biological age, and propose healthy longevity approaches. This review explores pathways that are currently being investigated as intervention targets and aging biomarkers spanning molecular, cellular, and systemic dimensions. Interventions that target these hallmarks may ameliorate the aging process, with some progressing to clinical trials. Biomarkers of these hallmarks are used to estimate biological aging and risk of aging-associated disease. Utilizing aging biomarkers, biological aging clocks can be constructed that predict a state of abnormal aging, age-related diseases, and increased mortality. Biological age estimation can therefore provide the basis for a fine-grained risk stratification by predicting all-cause mortality well ahead of the onset of specific diseases, thus offering a window for intervention. Yet, despite technological advancements, challenges persist due to individual variability and the dynamic nature of these biomarkers. Addressing this requires longitudinal studies for robust biomarker identification. Overall, utilizing the hallmarks of aging to discover new drug targets and develop new biomarkers opens new frontiers in medicine. Prospects involve multi-omics integration, machine learning, and personalized approaches for targeted interventions, promising a healthier aging population.

Trajectories of Hearing From Childhood to Adulthood

OBJECTIVES

The Dunedin Multidisciplinary Health and Development Study provides a unique opportunity to document the progression of ear health and hearing ability within the same cohort of individuals from birth. This investigation draws on hearing data from 5 to 13 years and again at 45 years of age, to explore the associations between childhood hearing variables and hearing and listening ability at age 45.

DESIGN

Multiple linear regression analyses were used to assess associations between childhood hearing (otological status and mid-frequency pure-tone average) and (a) age 45 peripheral hearing ability (mid-frequency pure-tone average and high-frequency pure-tone average), and (b) age 45 listening ability (listening in spatialized noise and subjective questionnaire on listening experiences). Sex, childhood socioeconomic status, and adult IQ were included in the model as covariates.

RESULTS

Peripheral hearing and listening abilities at age 45 were consistently associated with childhood hearing acuity at mid-frequencies. Otological status was a moderate predicting factor for high-frequency hearing and utilization of spatial listening cues in adulthood.

CONCLUSIONS

We aim to use these findings to develop a foundational model of hearing trajectories. This will form the basis for identifying precursors, to be investigated in a subsequent series of analyses, that may protect against or exacerbate hearing-associated cognitive decline in the Dunedin Study cohort as they progress from mid-life to older age.

Principal component-based clinical aging clocks identify signatures of healthy aging and targets for clinical intervention

Clocks that measure biological age should predict all-cause mortality and give rise to actionable insights to promote healthy aging. Here we applied dimensionality reduction by principal component analysis to clinical data to generate a clinical aging clock (PCAge) identifying signatures (principal components) separating healthy and unhealthy aging trajectories. We found signatures of metabolic dysregulation, cardiac and renal dysfunction and inflammation that predict unsuccessful aging, and we demonstrate that these processes can be impacted using well-established drug interventions. Furthermore, we generated a streamlined aging clock (LinAge), based directly on PCAge, which maintains equivalent predictive power but relies on substantially fewer features. Finally, we demonstrate that our approach can be tailored to individual datasets, by re-training a custom clinical clock (CALinAge), for use in the Comprehensive Assessment of Long-term Effects of Reducing Intake of Energy (CALERIE) study of caloric restriction. Our analysis of CALERIE participants suggests that 2 years of mild caloric restriction significantly reduces biological age. Altogether, we demonstrate that this dimensionality reduction approach, through integrating different biological markers, can provide targets for preventative medicine and the promotion of healthy aging.

Associations of phthalates with accelerated aging and the mitigating role of physical activity

Phthalates are positioned as potential risk factors for health-related diseases. However, the effects of exposure to phthalates on accelerated aging and the potential modifications of physical activity remain unclear. A total of 2317 participants containing complete study-related information from the National Health and Nutrition Examination Survey 2007-2010 were included in the current study. We used two indicators, the Klemera-Doubal method biological age acceleration (BioAgeAccel) and phenotypic age acceleration (PhenoAgeAccel), to assess the accelerated aging status of the subjects. Multiple linear regression (single pollutant models), weighted quantile sum (WQS) regression, Quantile g-computation, and Bayesian kernel machine regression (BKMR) models were utilized to explore the associations between urinary phthalate metabolites and accelerated aging. Three groups of physical activity with different intensities were used to evaluate the modifying effects on the above associations. Results indicated that most phthalate metabolites were significantly associated with BioAgeAccel and PhenoAgeAccel, with effect values (β) ranging from 0.16 to 0.21 and 0.16-0.37, respectively. The WQS indices were positively associated with BioAgeAccel (0.33, 95% CI: 0.11, 0.54) and PhenoAgeAccel (0.50, 95% CI: 0.19, 0.82). Quantile g-computation indicated that phthalate mixtures were associated with accelerated aging, with effect values of 0.15 (95% CI: 0.02, 0.28) for BioAgeAccel and 0.39 (95% CI: 0.12, 0.67) for PhenoAgeAccel respectively. The BKMR models indicated a significant positive association between the concentrations of urinary phthalate mixtures with the two indicators. In addition, we found that most phthalate metabolites showed the strongest effects on accelerated aging in the no physical activity group and that the effects decreased gradually with increasing levels of physical activity (P < 0.05 for trend). Similar results were also observed in the mixed exposure models (WQS and Quantile g-computation). This study indicates that phthalates exposure is associated with accelerated aging, while physical activity may be a crucial barrier against phthalates exposure-related aging.

Perceptions of Adulthood and Mental Health

BACKGROUND

In contrast to conventional definitions, the contemporary conceptualization of adulthood emphasizes psychological characteristics over sociodemographic milestones. At the same time, an increasing number of theorists propose that the way individuals view adulthood may have a significant impact on the mental health of both adolescents and adults. However, empirical examination of this hypothesis has been notably limited to date. The aim of this study is to explore the association between individuals' perceptions of adulthood and multiple dimensions of mental health.

METHOD

This study applied some adulthood markers and multiple mental health indexes (including well-being, optimism, Alexithymia, satisfaction with life, Goldberg's index of mental health, the dark triad, and dimensional personality disorders) to a community sample comprising 1772 individuals in Spain, spanning ages from 16 to 93 years.

RESULTS

The findings support the overarching hypothesis, as perceptions of adulthood display strong correlations with nearly every assessed index of mental health, particularly those that comprise a dimension of negative emotions. These associations persist even after accounting for age and socio-economic status, and in alignment with the psychological paradigm of adulthood, they show a notable consistency across various age groups.

CONCLUSIONS

This study establishes that such perceptions of adulthood represent a modifiable factor contributing to positive mental health. The implications of these findings for the formulation of public policies aimed at promoting mental health in the context of adulthood, as well as a number of future studies, are deliberated.

Accelerated biological aging six decades after prenatal famine exposure

To test the hypothesis that early-life adversity accelerates the pace of biological aging, we analyzed data from the Dutch Hunger Winter Families Study (DHWFS, N = 951). DHWFS is a natural-experiment birth-cohort study of survivors of in-utero exposure to famine conditions caused by the German occupation of the Western Netherlands in Winter 1944 to 1945, matched controls, and their siblings. We conducted DNA methylation analysis of blood samples collected when the survivors were aged 58 to quantify biological aging using the DunedinPACE, GrimAge, and PhenoAge epigenetic clocks. Famine survivors had faster DunedinPACE, as compared with controls. This effect was strongest among women. Results were similar for GrimAge, although effect-sizes were smaller. We observed no differences in PhenoAge between survivors and controls. Famine effects were not accounted for by blood-cell composition and were similar for individuals exposed early and later in gestation. Findings suggest in-utero undernutrition may accelerate biological aging in later life.

Improvement in Epigenetic Aging Clock Induced by BioBran Containing Rice Kefiran in Relation to Various Biomarkers: A Pilot Study

Many lifestyle-related diseases such as cancer, dementia, myocardial infarction, and stroke are known to be caused by aging, and the WHO's ICD-11 (International Classification of Diseases, 11th edition) created the code "aging-related" in 2022. In other words, aging is irreversible but aging-related diseases are reversible, so taking measures to treat them is important for health longevity and preventing other diseases. Therefore, in this study, we used BioBran containing rice kefiran as an approach to improve aging. Rice kefiran has been reported to improve the intestinal microflora, regulate the intestines, and have anti-aging effects. BioBran has also been reported to have antioxidant effects and improve liver function, and human studies have shown that it affects the diversity of the intestinal microbiota. Quantitative measures of aging that correlate with disease risk are now available through the epigenetic clock test, which examines the entire gene sequence and determines biological age based on the methylation level. Horvath's Clock is the best known of many epigenetic clock tests and was published by Steve Horvath in 2013. In this study, we examine the effect of using Horvath's Clock to improve aging and report on the results, which show a certain effect.

Diet, Pace of Biological Aging, and Risk of Dementia in the Framingham Heart Study

OBJECTIVE

People who eat healthier diets are less likely to develop dementia, but the biological mechanism of this protection is not well understood. We tested the hypothesis that healthy diet protects against dementia because it slows the pace of biological aging.

METHODS

We analyzed Framingham Offspring Cohort data. We included participants ≥60 years-old, free of dementia and having dietary, epigenetic, and follow-up data. We assessed healthy diet as long-term adherence to the Mediterranean-Dash Intervention for Neurodegenerative Delay diet (MIND, over 4 visits spanning 1991-2008). We measured the pace of aging from blood DNA methylation data collected in 2005-2008 using the DunedinPACE epigenetic clock. Incident dementia and mortality were defined using study records compiled from 2005 to 2008 visit through 2018.

RESULTS

Of n = 1,644 included participants (mean age 69.6, 54% female), n = 140 developed dementia and n = 471 died over 14 years of follow-up. Greater MIND score was associated with slower DunedinPACE and reduced risks for dementia and mortality. Slower DunedinPACE was associated with reduced risks for dementia and mortality. In mediation analysis, slower DunedinPACE accounted for 27% of the diet-dementia association and 57% of the diet-mortality association.

INTERPRETATION

Findings suggest that slower pace of aging mediates part of the relationship of healthy diet with reduced dementia risk. Monitoring pace of aging may inform dementia prevention. However, a large fraction of the diet-dementia association remains unexplained and may reflect direct connections between diet and brain aging that do not overlap other organ systems. Investigation of brain-specific mechanisms in well-designed mediation studies is warranted. ANN NEUROL 2024;95:1069-1079.

Demographic characteristics and epigenetic biological aging among post-9/11 veterans: Associations of DunedinPACE with sex, race, and age

Measures of epigenetic aging derived from DNA methylation (DNAm) have enabled the assessment of biological aging in new populations and cohorts. In the present study, we used an epigenetic measure of aging, DunedinPACE, to examine rates of aging across demographic groups in a sample of 2,309 United States military veterans from the VISN 6 MIRECC's Post-Deployment Mental Health Study. As assessed by DunedinPACE, female veterans were aging faster than male veterans (β = 0.39, 95 % CI [0.29, 0.48], p < .001), non-Hispanic Black veterans were aging faster than non-Hispanic White veterans (β = 0.58, 95 % CI [0.50, 0.66], p < .001), and older veterans were biologically aging faster than younger veterans (β = 0.21, 95 % CI [0.18, 0.25], p < .001). In secondary analyses, these differences in rates of aging were not explained by a variety of biopsychosocial covariates. In addition, the percentage of European genetic admixture in non-Hispanic Black veterans was not associated with DunedinPACE. Our findings suggest that female and non-Hispanic Black veterans are at greater risk of accelerated aging among post-9/11 veterans. Interventions that slow aging might provide relatively greater benefit among veterans comprising these at-risk groups.

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.

Ohwia caudata aqueous extract attenuates senescence in aging adipose-derived mesenchymal stem cells

Stem cells exhibit pluripotency and self-renewal abilities. Adipose-derived mesenchymal stem cells can potentially be used to reconstruct various tissues. They possess significant versatility and alleviate various aging-related diseases. Unfortunately, aging leads to senescence, apoptosis, and a decline in regenerative capacity in adipose-derived mesenchymal stem cells. These changes necessitate a strategy to mitigate the effects of aging on stem cells. Ohwia caudata (O. caudata) has therapeutic effects against several illnesses. However, studies on whether O. caudata has therapeutic effects against aging are lacking. In this study, we aimed to identify potential therapeutic anti-aging effects in the crude aqueous extract of O. caudata on adipose-derived mesenchymal stem cells. Using 0.1 μM doxorubicin, we induced aging in human adipose-derived mesenchymal stem cells (hADMSCs) and evaluated whether various concentrations of O. caudata aqueous extract exhibit anti-aging effects on them. The O. caudata extract exhibited significant antioxidant effects on hADMSCs without any toxicity. Furthermore, after treatment with the O. caudata aqueous extract, the levels of mitochondrial superoxide, DNA double-strand breaks, and telomere shortening were reduced in the hADMSCs subjected to doxorubicin-induced aging. The extract also suppressed doxorubicin-induced aging by upregulating klotho and downregulating p21 in hADMSCs. These findings indicated that the O. caudata extract exhibited anti-aging properties that modulated hADMSC homeostasis. Therefore, it could be a potential candidate for restoring the self-renewal ability and multipotency of aging hADMSCs.

Conditional independence as a statistical assessment of evidence integration processes

Intuitively, combining multiple sources of evidence should lead to more accurate decisions than considering single sources of evidence individually. In practice, however, the proper computation may be difficult, or may require additional data that are inaccessible. Here, based on the concept of conditional independence, we consider expressions that can serve either as recipes for integrating evidence based on limited data, or as statistical benchmarks for characterizing evidence integration processes. Consider three events, A, B, and C. We find that, if A and B are conditionally independent with respect to C, then the probability that C occurs given that both A and B are known, P(C|A, B), can be easily calculated without the need to measure the full three-way dependency between A, B, and C. This simplified approach can be used in two general ways: to generate predictions by combining multiple (conditionally independent) sources of evidence, or to test whether separate sources of evidence are functionally independent of each other. These applications are demonstrated with four computer-simulated examples, which include detecting a disease based on repeated diagnostic testing, inferring biological age based on multiple biomarkers of aging, discriminating two spatial locations based on multiple cue stimuli (multisensory integration), and examining how behavioral performance in a visual search task depends on selection histories. Besides providing a sound prescription for predicting outcomes, this methodology may be useful for analyzing experimental data of many types.

Using non-invasive behavioral and physiological data to measure biological age in wild baboons

Biological aging is near-ubiquitous in the animal kingdom, but its timing and pace vary between individuals and over lifespans. Prospective, individual-based studies of wild animals-especially non-human primates-help identify the social and environmental drivers of this variation by indicating the conditions and exposure windows that affect aging processes. However, measuring individual biological age in wild primates is challenging because several of the most promising methods require invasive sampling. Here, we leverage observational data on behavior and physiology, collected non-invasively from 319 wild female baboons across 2402 female-years of study, to develop a composite predictor of age: the non-invasive physiology and behavior (NPB) clock. We found that age predictions from the NPB clock explained 51% of the variation in females' known ages. Further, deviations from the clock's age predictions predicted female survival: females predicted to be older than their known ages had higher adult mortality. Finally, females who experienced harsh early-life conditions were predicted to be about 6 months older than those who grew up in more benign conditions. While the relationship between early adversity and NPB age is noisy, this estimate translates to a predicted 2-3 year reduction in mean adult lifespan in our model. A constraint of our clock is that it is tailored to data collection approaches implemented in our study population. However, many of the clock's components have analogs in other populations, suggesting that non-invasive data can provide broadly applicable insight into heterogeneity in biological age in natural populations.

Identifying dementia from cognitive footprints in hospital records among Chinese older adults: a machine-learning study

Background

By combining theory-driven and data-driven methods, this study aimed to develop dementia predictive algorithms among Chinese older adults guided by the cognitive footprint theory.

Methods

Electronic medical records from the Clinical Data Analysis and Reporting System in Hong Kong were employed. We included patients with dementia diagnosed at 65+ between 2010 and 2018, and 1:1 matched dementia-free controls. We identified 51 features, comprising exposures to established modifiable factors and other factors before and after 65 years old. The performances of four machine learning models, including LASSO, Multilayer perceptron (MLP), XGBoost, and LightGBM, were compared with logistic regression models, for all patients and subgroups by age.

Findings

A total of 159,920 individuals (40.5% male; mean age [SD]: 83.97 [7.38]) were included. Compared with the model included established modifiable factors only (area under the curve [AUC] 0.689, 95% CI [0.684, 0.694]), the predictive accuracy substantially improved for models with all factors (0.774, [0.770, 0.778]). Machine learning and logistic regression models performed similarly, with AUC ranged between 0.773 (0.768, 0.777) for LASSO and 0.780 (0.776, 0.784) for MLP. Antipsychotics, education, antidepressants, head injury, and stroke were identified as the most important predictors in the total sample. Age-specific models identified different important features, with cardiovascular and infectious diseases becoming prominent in older ages.

Interpretation

The models showed satisfactory performances in identifying dementia. These algorithms can be used in clinical practice to assist decision making and allow timely interventions cost-effectively.

Funding

The Research Grants Council of Hong Kong under the Early Career Scheme 27110519.

Association Between Aortic Valve Sclerosis and Clonal Hematopoiesis of Indeterminate Potential

Background

The mechanism and medical treatment target for degenerative aortic valve disease, including aortic stenosis, is not well studied. In this study, we investigated the effect of clonal hematopoiesis of indeterminate potential (CHIP) on the development of aortic valve sclerosis (AVS), a calcified aortic valve without significant stenosis.

Methods

Participants with AVS (valves ≥2 mm thick, high echogenicity, and a peak transaortic velocity of <2.5 m/sec) and an age- and sex-matched control group were enrolled. Twenty-four CHIP genes with common variants in cardiovascular disease were used to generate a next-generation sequencing panel. The primary endpoint was the CHIP detection rate between the AVS and control groups. Inverse-probability treatment weighting (IPTW) analysis was performed to adjust for differences in baseline characteristics.

Results

From April 2020 to April 2022, 187 participants (125 with AVS and 62 controls) were enrolled; the mean age was 72.6±8.5 yrs, and 54.5% were male. An average of 1.3 CHIP variants was observed. CHIP detection, defined by a variant allele frequency (VAF) of ≥0.5%, was similar between the groups. However, the AVS group had larger CHIP clones: 49 (39.2%) participants had a VAF of ≥1% (vs. 13 [21.0%] in the control group; P=0.020), and 25 (20.0%) had a VAF of ≥2% (vs. 4 [6.5%]; P=0.028). AVS is independently associated with a VAF of ≥1% (adjusted odds ratio: 2.44, 95% confidence interval: 1.11-5.36; P=0.027). This trend was concordant and clearer in the IPTW cohort.

Conclusions

Participants with AVS more commonly had larger CHIP clones than age- and sex-matched controls. Further studies are warranted to identify causality between AVS and CHIP.

Associations of seven measures of biological age acceleration with frailty and all-cause mortality among adult survivors of childhood cancer in the St. Jude Lifetime Cohort

Survivors of childhood cancer may experience accelerated biological aging, resulting in premature frailty and death. We used seven measures of biological age in the St. Jude Lifetime (SJLIFE) Cohort to compare biological age acceleration between the SJLIFE Cohort and the third United States National Health and Nutrition Examination Survey controls, explore trajectories of biological age according to cancer treatment and type, and test associations of biological age acceleration with frailty and death (mean follow-up of 26.5 years) among survivors. Survivors of cancer aged 5% faster per year and measured, on average, 0.6-6.44 years biologically older compared to controls and 5-16 years biologically older compared to age-matched individuals at the population level. Survivors treated with hematopoietic cell transplant and vinca alkaloid chemotherapy evidenced the fastest trajectories of biological aging. Biologically, older and faster-aging survivors consistently and robustly had a higher risk of frailty and died earlier than those with slower biological aging, suggesting a potential opportunity to intervene on excess aging.

Pace of Aging in older adults matters for healthspan and lifespan

As societies age, policy makers need tools to understand how demographic aging will affect population health and to develop programs to increase healthspan. The current metrics used for policy analysis do not distinguish differences caused by early-life factors, such as prenatal care and nutrition, from those caused by ongoing changes in people's bodies due to aging. Here we introduce an adapted Pace of Aging method designed to quantify differences between individuals and populations in the speed of aging-related health declines. The adapted Pace of Aging method, implemented in data from N=13,626 older adults in the US Health and Retirement Study, integrates longitudinal data on blood biomarkers, physical measurements, and functional tests. It reveals stark differences in rates of aging between population subgroups and demonstrates strong and consistent prospective associations with incident morbidity, disability, and mortality. Pace of Aging can advance the population science of healthy longevity.

Developmental epigenomic effects of maternal financial problems

Early-life adversity as neglect or low socioeconomic status is associated with negative physical/mental health outcomes and plays an important role in health trajectories through life. The early-life environment has been shown to be encoded as changes in epigenetic markers that are retained for many years.We investigated the effect of maternal major financial problems (MFP) and material deprivation (MD) on their children's epigenome in the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort. Epigenetic aging, measured with epigenetic clocks, was weakly accelerated with increased MFP. In subsequent EWAS, MFP, and MD showed strong, independent programing effects on children's genomes. MFP in the period from birth to age seven was associated with genome-wide epigenetic modifications on children's genome visible at age 7 and partially remaining at age 15.These results support the hypothesis that physiological processes at least partially explain associations between early-life adversity and health problems later in life. Both maternal stressors (MFP/MD) had similar effects on biological pathways, providing preliminary evidence for the mechanisms underlying the effects of low socioeconomic status in early life and disease outcomes later in life. Understanding these associations is essential to explain disease susceptibility, overall life trajectories and the transition from health to disease.

Adherence to Life's Essential 8 is associated with delayed biological aging: a population-based cross-sectional study

INTRODUCTION AND OBJECTIVES

The aim of this study was to explore the potential of adhering to the American Heart Association's updated Life's Essential 8 (LE8) scores in delaying biological aging amid growing concerns about aging populations and related diseases.

METHODS

A total of 18 261 adults (≥ 20 years old) were examined using National Health and Nutrition Examination Survey data from 2005-2010 and 2015-2018. The LE8 includes 8 components, covering health behaviors and factors. Acceleration of biological aging was defined as an excess of biological/phenotypic age over chronological age, assessed by using clinical biomarkers. The association between LE8 score and biological aging was explored through regression analyses.

RESULTS

Each 10-point increase in LE8 scores was associated with a 1.19-year decrease in biological age and a 1.63-year decrease in phenotypic age. Individuals with high cardiovascular health (CVH) had a 90% reduction in their risk of accelerated aging based on biological age and an 81% reduction based on phenotypic age compared with individuals with low CVH. Bootstrap-based model estimates and weighted quantile sum regression suggested that health factors, particularly blood glucose, had strong impact on delaying aging. The association between smoking and biological aging seemed to differ depending on the definition of aging used. Among all subgroups, LE8 consistently correlated negatively with biological aging, despite observed interactions. Three sensitivity analyses confirmed the robustness of our conclusions.

CONCLUSIONS

A higher CVH is associated with a lower risk of biological aging. Maintaining elevated LE8 levels across demographics, regardless of cardiovascular history, is recommended to delay aging and promote healthy aging, with significant implications for primary health care.

A Comparison of 5 Measures of Accelerated Biological Aging and Their Association With Incident Cardiovascular Disease: The CARDIA Study

BACKGROUND

Accelerated biological aging is an increasingly popular way to track the acceleration of biology over time that may not be captured by calendar time. Biological aging has been linked to external and internal chronic stressors and has the potential to be used clinically to understand a person's personalized functioning and predict future disease. We compared the association of different measures of biological aging and incident cardiovascular disease (CVD) overall and by race.

METHODS AND RESULTS

We used multiple informants models to compare the strength of clinical marker-derived age acceleration, 5 measures of epigenetic age acceleration (intrinsic and extrinsic epigenetic age acceleration, GrimAge acceleration, and PhenoAge acceleration), and 1 established clinical predictor of future CVD, Framingham 10-year risk score, with incident CVD over an 11-year period (2007-2018). Participants were 913 self-identified Black or White (41% and 59%, respectively) female or male (51% and 49%, respectively) individuals enrolled in the US-based CARDIA (Coronary Artery Risk Development in Young Adults) cohort study. The analytic baseline for this study was the 20-year follow-up examination (2005-2006; median age 45 years). We also included race-specific analysis. We found that all measures were modestly correlated with one another. However, clinical marker-derived age acceleration and Framingham 10-year risk score were more strongly associated with incident CVD than all the epigenetic measures. Clinical marker-derived age acceleration and Framingham 10-year risk score were not significantly different than one another in their association with incident CVD.

CONCLUSIONS

The type of accelerated aging measure should be taken into consideration when comparing their association with clinical outcomes. A multisystem clinical composite shows associations with incident CVD equally to a well-known clinical predictor.

Leukocyte telomere length in multiple sclerosis: relationship between disability severity and pregnancy history

BACKGROUND

Aging-related processes contribute to neurodegeneration and disability in multiple sclerosis (MS). Biomarkers of biological aging such as leukocyte telomere length (LTL) could help personalise prognosis. Pregnancy has been shown to be protective against disability accumulation in women with MS, though it is unclear if this effect relates to aging mechanisms or LTL.

OBJECTIVES

This study aimed to cross-sectionally characterise LTL in a cohort of individuals with MS, and to correlate LTL with disability severity and pregnancy history.

METHODS

We extracted DNA from the whole blood of 501 people with MS in Melbourne, Australia. Expanded Disability Status Scale (EDSS) score and demographic data, as well as pregnancy history for 197 females, were obtained at sample collection. Additional data were extracted from the MSBase Registry. LTL was determined in base pairs (bp) using real-time quantitative polymerase chain reaction.

RESULTS

A relationship between EDSS score and shorter LTL was robust to multivariable adjustment for demographic and clinical factors including chronological age, with an adjusted LTL reduction per 1.0 increase in EDSS of 97.1 bp (95 % CI = 9.7-184.5 bp, p = 0.030). Adjusted mediation analysis found chronological age accounted for 33.6 % of the relationship between LTL and EDSS score (p = 0.018). In females with pregnancy data, history of pregnancy was associated with older age (median 49.7 vs 33.0 years, p < 0.001). There were no significant relationships between adjusted LTL and any history of pregnancy (LTL increase of 65.3 bp, 95 % CI = -471.0-601.5 bp, p = 0.81) or number of completed pregnancies (LTL increase of 14.6 bp per pregnancy, 95 % CI = -170.3-199.6 bp, p = 0.87).

CONCLUSIONS

The correlation between LTL and disability independent of chronological age and other factors points to a link between neurological reserve in MS and biological aging, and a potential research target for pathophysiological and therapeutic mechanisms. Although LTL did not significantly differ by pregnancy history, longitudinal analyses could help identify interactions with prospectively captured pregnancy effects.

Meta-analysis of epigenetic aging in schizophrenia reveals multifaceted relationships with age, sex, illness duration, and polygenic risk

BACKGROUND

The study of biological age acceleration may help identify at-risk individuals and reduce the rising global burden of age-related diseases. Using DNA methylation (DNAm) clocks, we investigated biological aging in schizophrenia (SCZ), a mental illness that is associated with an increased prevalence of age-related disabilities and morbidities. In a whole blood DNAm sample of 1090 SCZ cases and 1206 controls across four European cohorts, we performed a meta-analysis of differential aging using three DNAm clocks (i.e., Hannum, Horvath, and Levine). To dissect how DNAm aging contributes to SCZ, we integrated information on duration of illness and SCZ polygenic risk, as well as stratified our analyses by chronological age and biological sex.

RESULTS

We found that blood-based DNAm aging is significantly altered in SCZ independent from duration of the illness since onset. We observed sex-specific and nonlinear age effects that differed between clocks and point to possible distinct age windows of altered aging in SCZ. Most notably, intrinsic cellular age (Horvath clock) is decelerated in SCZ cases in young adulthood, while phenotypic age (Levine clock) is accelerated in later adulthood compared to controls. Accelerated phenotypic aging was most pronounced in women with SCZ carrying a high polygenic burden with an age acceleration of + 3.82 years (CI 2.02-5.61, P = 1.1E-03). Phenotypic aging and SCZ polygenic risk contributed additively to the illness and together explained up to 14.38% of the variance in disease status.

CONCLUSIONS

Our study contributes to the growing body of evidence of altered DNAm aging in SCZ and points to intrinsic age deceleration in younger adulthood and phenotypic age acceleration in later adulthood in SCZ. Since increased phenotypic age is associated with increased risk of all-cause mortality, our findings indicate that specific and identifiable patient groups are at increased mortality risk as measured by the Levine clock. Our study did not find that DNAm aging could be explained by the duration of illness of patients, but we did observe age- and sex-specific effects that warrant further investigation. Finally, our results show that combining genetic and epigenetic predictors can improve predictions of disease outcomes and may help with disease management in schizophrenia.

A blood biomarker of the pace of aging is associated with brain structure: replication across three cohorts

Biological aging is the correlated decline of multi-organ system integrity central to the etiology of many age-related diseases. A novel epigenetic measure of biological aging, DunedinPACE, is associated with cognitive dysfunction, incident dementia, and mortality. Here, we tested for associations between DunedinPACE and structural MRI phenotypes in three datasets spanning midlife to advanced age: the Dunedin Study (age=45 years), the Framingham Heart Study Offspring Cohort (mean age=63 years), and the Alzheimer's Disease Neuroimaging Initiative (mean age=75 years). We also tested four additional epigenetic measures of aging: the Horvath clock, the Hannum clock, PhenoAge, and GrimAge. Across all datasets (total N observations=3380; total N individuals=2322), faster DunedinPACE was associated with lower total brain volume, lower hippocampal volume, greater burden of white matter microlesions, and thinner cortex. Across all measures, DunedinPACE and GrimAge had the strongest and most consistent associations with brain phenotypes. Our findings suggest that single timepoint measures of multi-organ decline such as DunedinPACE could be useful for gauging nervous system health.

Organ-specific biological clocks: Ageotyping for personalized anti-aging medicine

Aging is a complex multidimensional, progressive remodeling process affecting multiple organ systems. While many studies have focused on studying aging across multiple organs, assessment of the contribution of individual organs to overall aging processes is a cutting-edge issue. An organ's biological age might influence the aging of other organs, revealing a multiorgan aging network. Recent data demonstrated a similar yet asynchronous inter-organs and inter-individuals progression of aging, thereby providing a foundation to track sources of declining health in old age. The integration of multiple omics with common clinical parameters through artificial intelligence has allowed the building of organ-specific aging clocks, which can predict the development of specific age-related diseases at high resolution. The peculiar individual aging-trajectory, referred to as ageotype, might provide a novel tool for a personalized anti-aging, preventive medicine. Here, we review data relative to biological aging clocks and omics-based data, suggesting different organ-specific aging rates. Additional research on longitudinal data, including young subjects and analyzing sex-related differences, should be encouraged to apply ageotyping analysis for preventive purposes in clinical practice.

DNA methylation and chromatin accessibility predict age in the domestic dog

Across mammals, the epigenome is highly predictive of chronological age. These "epigenetic clocks," most of which have been built using DNA methylation (DNAm) profiles, have gained traction as biomarkers of aging and organismal health. While the ability of DNAm to predict chronological age has been repeatedly demonstrated, the ability of other epigenetic features to predict age remains unclear. Here, we use two types of epigenetic information-DNAm, and chromatin accessibility as measured by ATAC-seq-to develop age predictors in peripheral blood mononuclear cells sampled from a population of domesticated dogs. We measured DNAm and ATAC-seq profiles for 71 dogs, building separate predictive clocks from each, as well as the combined dataset. We also use fluorescence-assisted cell sorting to quantify major lymphoid populations for each sample. We found that chromatin accessibility can accurately predict chronological age (R2 ATAC = 26%), though less accurately than the DNAm clock (R2 DNAm = 33%), and the clock built from the combined datasets was comparable to both (R2 combined = 29%). We also observed various populations of CD62L+ T cells significantly correlated with dog age. Finally, we found that all three clocks selected features that were in or near at least two protein-coding genes: BAIAP2 and SCARF2, both previously implicated in processes related to cognitive or neurological impairment. Taken together, these results highlight the potential of chromatin accessibility as a complementary epigenetic resource for modeling and investigating biologic age.

Signs of aging in midlife: physical function and sex differences in microbiota

Microbiota composition has been linked to physical activity, health measures, and biological age, but a shared profile has yet to be shown. The aim of this study was to examine the associations between microbiota composition and measures of function, such as a composite measure of physical capacity, and biological age in midlife, prior to onset of age-related diseases. Seventy healthy midlife individuals (age 44.58 ± 0.18) were examined cross-sectionally, and their gut-microbiota profile was characterized from stool samples using 16SrRNA gene sequencing. Biological age was measured using the Klemera-Doubal method and a composition of blood and physiological biomarkers. Physical capacity was calculated based on sex-standardized functional tests. We demonstrate that the women had significantly richer microbiota, p = 0.025; however, microbiota diversity was not linked with chronological age, biological age, or physical capacity for either women or men. Men had slightly greater β-diversity; however, β-diversity was positively associated with biological age and with physical capacity for women only (p = 0.01 and p = 0.04; respectively). For women, an increase in abundance of Roseburia faecis and Collinsella aerofaciens, as well as genus Ruminococcus and Dorea, was significantly associated with higher biological age and lower physical capacity; an increase in abundance of Akkermansia muciniphila and genera Bacteroides and Alistipes was associated with younger biological age and increased physical capacity. Differentially abundant taxa were also associated with non-communicable diseases. These findings suggest that microbiota composition is a potential mechanism linking physical capacity and health status; personalized probiotics may serve as a new means to support health-promoting interventions in midlife. Investigating additional factors underlying this link may facilitate the development of a more accurate method to estimate the rate of aging.

Does diet influence aging? Evidence from animal studies

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

Relationship between fatty acid intake and aging: a Mendelian randomization study

BACKGROUND

Observational studies have previously shown a possible link between fatty acids and aging-related diseases, raising questions about its health implications. However, the causal relationship between the two remains uncertain.

METHODS

Univariable and multivariable Mendelian randomization (MR) was used to analyze the relationship between five types of fatty acids-polyunsaturated fatty acid (PUFA), monounsaturated fatty acid (MUFA), saturated fatty acid (SFA), Omega-6 fatty acid (Omega-6 FA), and Omega-3 fatty acid (Omega-3 FA) and three markers of aging: telomere length (TL), frailty index (FI), and facial aging (FclAg). The primary approach for Mendelian randomization (MR) analysis involved utilizing the inverse variance weighted (IVW) method, with additional supplementary methods employed.

RESULTS

Univariate MR analysis revealed that MUFA, PUFA, SFA, and Omega-6 fatty acids were positively associated with TL (MUFA OR: 1.019, 95% CI: 1.006-1.033; PUFA OR: 1.014, 95% CI: 1.002-1.026; SFA OR: 1.016, 95% CI: 1.002-1.031; Omega-6 FAs OR=1.031, 95% CI: 1.006-1.058). PUFA was also associated with a higher FI (OR: 1.033, 95% CI: 1.009-1.057). In multivariate MR analysis, after adjusting for mutual influences among the five fatty acids, MUFA and PUFA were positively independently associated with TL (MUFA OR: 1.1508, 95% CI = 1.0724-1.2350; PUFA OR: 1.1670, 95% CI = 1.0497-1.2973, while SFA was negatively correlated (OR: 0.8005, 95% CI: 0.7045-0.9096).

CONCLUSIONS

Our research presents compelling evidence of a causal association between certain fatty acids and indicators of the aging process. In particular, MUFA and PUFA may play a role in slowing down the aging process, while SFAs may contribute to accelerated aging. These findings could have significant implications for dietary recommendations aimed at promoting healthy aging.

Utilizing epigenetics to study the shared nature of development and biological aging across the lifespan

Recently, biological aging has been quantified in DNA-methylation samples of older adults and applied as so-called "methylation profile scores" (MPSs) in separate target samples, including samples of children. This nascent research indicates that (1) biological aging can be quantified early in the life course, decades before the onset of aging-related disease, (2) is affected by common environmental predictors of childhood development, and (3) shows overlap with "developmental processes" (e.g., puberty). Because the MPSs were computed using algorithms developed in adults, these studies indicate a molecular link between childhood environments, development, and adult biological aging. Yet, if MPSs can be used to connect development and aging, previous research has only traveled one way, deriving MPSs developed in adults and applying them to samples of children. Researchers have not yet quantified epigenetic measures that reflect the pace of child development, and tested whether resulting MPSs are associated with physical and psychological aging. In this perspective I posit that combining measures of biological aging with new quantifications of child development has the power to address fundamental questions about life span: How are development and experience in childhood related to biological aging in adulthood? And what is aging?

Association between sleep traits and biological aging risk: a Mendelian randomization study based on 157 227 cases and 179 332 controls

STUDY OBJECTIVES

To investigate whether sleep traits are associated with the risk of biological aging using a case-control design with Mendelian randomization (MR) analyses.

METHODS

We studied 336 559 participants in the UK Biobank cohort, including 157 227 cases of accelerated biological aging and 179 332 controls. PhenoAge, derived from clinical traits, estimated biological ages, and the discrepancies from chronological age were defined as age accelerations (PhenoAgeAccel). Sleep behaviors were assessed with a standardized questionnaire. propensity score matching matched control participants to age-accelerated participants, and a conditional multivariable logistic regression model estimated odds ratio (OR) and 95% confidence intervals (95% CI). Causal relationships between sleep traits and PhenoAgeAccel were explored using linear and nonlinear MR methods.

RESULTS

A U-shaped association was found between sleep duration and PhenoAgeAccel risk. Short sleepers had a 7% higher risk (OR = 1.07; 95% CI: 1.03 to 1.11), while long sleepers had an 18% higher risk (OR = 1.18; 95% CI: 1.15 to 1.22), compared to normal sleepers (6-8 hours/day). Evening chronotype was linked to higher PhenoAgeAccel risk than morning chronotype (OR = 1.14; 95% CI: 1.10 to 1.18), while no significant associations were found for insomnia or snoring. Morning chronotype had a protective effect on PhenoAgeAccel risk (OR = 0.87, 95% CI: 0.79 to 0.95) per linear MR analysis. Genetically predicted sleep duration showed a U-shaped relationship with PhenoAgeAccel, suggesting a nonlinear association (pnonlinear < 0.001).

CONCLUSIONS

The study suggests that improving sleep can slow biological aging, highlighting the importance of optimizing sleep as an intervention to mitigate aging's adverse effects.

The geriatric nutrition risk index is longitudinally associated with incident Sarcopenia: evidence from a 5-year prospective cohort

BACKGROUND

Previous studies investigating the association between the geriatric nutrition risk index (GNRI) and sarcopenia either lacked longitudinal evidence or narrowly focused on specific populations.

AIMS

We aimed to reveal longitudinal associations of GNRI with sarcopenia risk in community-dwelling Chinese. We also investigated interaction effects of potential factors on such associations.

METHODS

We included participants aged ≥ 50 years with sufficient data from the WCHAT study who did not have sarcopenia at baseline and completed sarcopenia assessment during follow-up. GNRI was calculated according to the formula based on serum albumin, height and weight. Sarcopenia was diagnosed according to the 2019 AWGS consensus. Longitudinal associations between GNRI and sarcopenia were estimated by logistic regression with GNRI as either a continuous or categorical variable by tertiles, using generalized estimating equations (GEE) as sensitivity analyses. Subgroup analyses by potential covariates were conducted to detect interaction effects.

RESULTS

A total of 1907 participants without baseline sarcopenia were finally included, of whom 327 (17.1%) developed incident sarcopenia during 5-year follow-up. After controlling for confounders, sarcopenia risk decreased with each one standard deviation increase in GNRI (ORadjusted=0.36, 95% CI 0.31-0.43), and it also decreased successively from the lowest (< 111.2) through middle (111.2-117.7) to the highest (≥ 117.8) tertile of the GNRI level (P for trend < 0.001). Similar results were yielded by GEE. Such associations generally remained robust across subgroups with distinct characteristics, while significant differences were observed between different age groups (≥ 65 vs. <65 years) (interaction P-value < 0.05).

CONCLUSION

GNRI is longitudinally associated with sarcopenia risk with possibly age-specific differences in association magnitude, which holds implications for policymakers to conduct population-based risk assessment.

Educational Mobility, Pace of Aging, and Lifespan Among Participants in the Framingham Heart Study

Importance

People who complete more education live longer lives with better health. New evidence suggests that these benefits operate through a slowed pace of biological aging. If so, measurements of the pace of biological aging could offer intermediate end points for studies of how interventions to promote education will affect healthy longevity.

Objective

To test the hypothesis that upward educational mobility is associated with a slower pace of biological aging and increased longevity.

Design, Setting, and Participants

This prospective cohort study analyzed data from 3 generations of participants in the Framingham Heart Study: (1) the original cohort, enrolled beginning in 1948; (2) the Offspring cohort, enrolled beginning in 1971; and (3) the Gen3 cohort, enrolled beginning in 2002. A 3-generation database was constructed to quantify intergenerational educational mobility. Mobility data were linked with blood DNA-methylation data collected from the Offspring cohort in 2005 to 2008 (n = 1652) and the Gen3 cohort in 2009 to 2011 (n = 1449). Follow-up is ongoing. Data analysis was conducted from June 2022 to November 2023 using data obtained from the National Institutes of Health database of Genotypes and Phenotypes (dbGaP).

Exposure

Educational mobility was measured by comparing participants' educational outcomes with those of their parents.

Main Outcomes and Measures

The pace of biological aging was measured from whole-blood DNA-methylation data using the DunedinPACE epigenetic clock. For comparison purposes, the analysis was repeated using 4 other epigenetic clocks. Survival follow-up was conducted through 2019.

Results

This study analyzed data from 3101 participants from the Framingham Heart Study; 1652 were in the Offspring cohort (mean [SD] age, 65.57 [9.22] years; 764 [46.2%] male) and 1449 were in the Gen3 cohort (mean [SD] age, 45.38 [7.83] years; 691 [47.7%] male). Participants who were upwardly mobile in educational terms tended to have slower pace of aging in later life (r = -0.18 [95% CI, -0.23 to -0.13]; P < .001). This pattern of association was similar across generations and held in within-family sibling comparisons. There were 402 Offspring cohort participants who died over the follow-up period. Upward educational mobility was associated with lower mortality risk (hazard ratio, 0.89 [95% CI, 0.81 to 0.98]; P = .01). Slower pace of aging accounted for approximately half of this association.

Conclusions and Relevance

This cohort study's findings support the hypothesis that interventions to promote educational attainment may slow the pace of biological aging and promote longevity. Epigenetic clocks have potential as near-term outcome measures of intervention effects on healthy aging. Experimental evidence is needed to confirm findings.

Dissipative scaling of development and aging in multicellular organisms

Evolution, self-replication and ontogenesis are highly dynamic, irreversible and self-organizing processes dissipating energy. While progress has been made to decipher the role of thermodynamics in cellular fission, it is not yet clear how entropic balances shape organism growth and aging. This paper derives a general dissipation theory for the life history of organisms. It implies a self-regulated energy dissipation facilitating exponential growth within a hierarchical and entropy lowering self-organization. The theory predicts ceilings in energy expenditures imposed by geometric constrains, which promote thermal optimality during development, and a dissipative scaling across organisms consistent with ecological scaling laws combining isometric and allometric terms. The theory also illustrates how growing organisms can tolerate damage through continuous extension and production of new dissipative structures low in entropy. However, when organisms reduce their rate of cell division and reach a steady adult state, they become thermodynamically unstable, increase internal entropy by accumulating damage, and age.

A late-life neurogenetic signature of exposure to combat stress - A monozygotic discordant twin study

Animal models suggest that experiencing high-stress levels induces changes in amygdalar circuitry and gene expression. In humans, combat exposure has been shown to alter amygdalar responsivity and connectivity, but abnormalities have been indicated to normalize at least partially upon the termination of stress exposure. In contrast, other evidence suggests that combat exposure continues to exert influence on exposed individuals well beyond deployment and homecoming, as indicated by longitudinal psychosocial evidence from veterans, and observation of greater health decline in veterans late in life. Accordingly, the experience of combat stress early in life may affect amygdalar responsivity late in life, a possibility requiring careful consideration of the confounding effects of aging, genetic factors, and symptoms of post-traumatic stress disorder. Here, we investigated amygdalar responsivity in a unique sample of 16 male monozygotic (MZ) twin pairs in their sixties, where one but not the other sibling had been exposed to combat stress in early adulthood. Forty years after combat experience, a generally blunted amygdalar response was observed in combat-exposed veterans compared to their non-exposed twin siblings. Spatial associations between these phenotypical changes and patterns of gene expression in the brain were found for genes involved in the synaptic organization and chromatin structure. Protein-protein interactions among the set of identified genes pointed to histone modification mechanisms. We conclude that exposure to combat stress early in life continues to impact brain function beyond the termination of acute stress and appears to exert prolonged effects on amygdalar function later in life via neurogenetic mechanisms.

Consequences of heterogeneity in aging: parental age at death predicts midlife all-cause mortality and hospitalization in a Swedish national birth cohort

BACKGROUND

The processes that underlie aging may advance at different rates in different individuals and an advanced biological age, relative to the chronological age, is associated with increased risk of disease and death. Here we set out to quantify the extent to which heterogeneous aging shapes health outcomes in midlife by following a Swedish birth-cohort and using parental age at death as a proxy for biological age in the offspring.

METHODS

We followed a nationwide Swedish birth cohort (N = 89,688) between the ages of 39 and 66 years with respect to hospitalizations and death. Cox regressions were used to quantify the association, in the offspring, between parental age at death and all-cause mortality, as well as hospitalization for conditions belonging to the 10 most common ICD-10 chapters.

RESULTS

Longer parental lifespan was consistently associated with reduced risks of hospitalization and all-cause mortality. Differences in risk were mostly evident from before the age of 50 and persisted throughout the follow-up. Each additional decade of parental survival decreased the risk of offspring all-cause mortality by 22% and risks of hospitalizations by 9 to 20% across the 10 diseases categories considered. The number of deaths and hospitalizations attributable to having parents not living until old age were 1500 (22%) and 11,000 (11%) respectively.

CONCLUSIONS

Our findings highlight that increased parental lifespan is consistently associated with health benefits in the offspring across multiple outcomes and suggests that heterogeneous aging processes have clinical implications already in midlife.

Cellular reprogramming as a tool to model human aging in a dish

The design of human model systems is highly relevant to unveil the underlying mechanisms of aging and to provide insights on potential interventions to extend human health and life span. In this perspective, we explore the potential of 2D or 3D culture models comprising human induced pluripotent stem cells and transdifferentiated cells obtained from aged or age-related disorder-affected donors to enhance our understanding of human aging and to catalyze the discovery of anti-aging interventions.

Fasting-mimicking diet causes hepatic and blood markers changes indicating reduced biological age and disease risk

In mice, periodic cycles of a fasting mimicking diet (FMD) protect normal cells while killing damaged cells including cancer and autoimmune cells, reduce inflammation, promote multi-system regeneration, and extend longevity. Here, we performed secondary and exploratory analysis of blood samples from a randomized clinical trial (NCT02158897) and show that 3 FMD cycles in adult study participants are associated with reduced insulin resistance and other pre-diabetes markers, lower hepatic fat (as determined by magnetic resonance imaging) and increased lymphoid to myeloid ratio: an indicator of immune system age. Based on a validated measure of biological age predictive of morbidity and mortality, 3 FMD cycles were associated with a decrease of 2.5 years in median biological age, independent of weight loss. Nearly identical findings resulted from  a second clinical study (NCT04150159). Together these results provide initial support for beneficial effects of the FMD on multiple cardiometabolic risk factors and biomarkers of biological age.

Self-perceptions of aging: A conceptual and empirical overview

This article defines self-perceptions of aging (SPA) as individuals' perceptions, expectations, and experiences regarding their own process of growing old(er). As such, SPA are considered a critically important element of the aging self. Furthermore, the authors present a heuristic model that positions adults' SPA within a lifespan developmental and cultural-societal context and elaborates distal and proximal antecedents, process modes, and developmental outcomes. The remainder of the article summarizes recent empirical findings and discusses future challenges and directions.

Educational patterning in biological health seven years apart: Findings from the Tromsø Study

BACKGROUND

Social-to-biological processes is one set of mechanisms underlying the relationship between social position and health. However, very few studies have focused on the relationship between social factors and biology at multiple time points. This work investigates the relationship between education and the dynamic changes in a composite Biological Health Score (BHS) using two time points seven years apart in a Norwegian adult population.

METHODS

We used data from individuals aged 30 years and above who participated in Tromsø6 (2007-2008) and Tromsø7 (2015-2016) (n = 8117). BHS was defined using ten biomarkers measured from blood samples and representing three physiological systems (cardiovascular, metabolic, inflammatory). The higher the BHS, the poorer the health status.

FINDINGS

Linear regression models carried out on BHS revealed a strong educational gradient at two distinct time points but also over time. People with lower educational attainment were at higher risk of poor biological health at a given time point (βlow education Tromsø6=0.30 [95 %-CI=0.18-0.43] and βlow education Tromsø7=0.30 [95 %-CI=0.17-0.42]). They also presented higher longitudinal BHS compared to people with higher education (βlow education = 0.89 [95 %-CI=0.56-1.23]). Certain biomarkers related to the cardiovascular system and the metabolic system were strongly socially distributed, even after adjustment for sex, age, health behaviours and body mass index.

CONCLUSION

This longitudinal analysis highlights that participants with lower education had their biological health deteriorated to a greater extent over time compared to people with higher education. Our findings provide added evidence of the biological embodiment of social position, particularly with respect to dynamic aspects for which little evidence exists.

Biological age as estimated by baseline circulating metabolites is associated with incident diabetes and mortality

OBJECTIVES

It is unclear how metabolomic assessment of biological aging performs in non-White populations and whether such an approach can predict future mortality. We aimed to evaluate the application of serum metabolomics combined with machine learning methodologies to predict incident diabetes and mortality in a Thai population.

DESIGN, SETTING AND PARTICIPANTS

We analyzed serum samples and mortality data over 11 years from among 454 participants with no previous history of diabetes and with a fasting plasma glucose ≥85th percentile (5.4 mmol/L) but <7 mmol/L.

MEASUREMENTS

Untargeted serum metabolomics were assessed using liquid chromatography/mass spectrometry. A deep artificial neural network was used to predict biological age based on serum metabolite profiles and chronological age.

RESULTS

The mean age of participants was 40.5 ± 6.4 years, and 70.8% were men. We found a significant positive correlation between metabolomic age and chronological age (r = 0.71, P < 0.001). After 5 years, 61 of 404 participants with available glycated hemoglobin status (15.1%) progressed to diabetes. Chronological age was associated with incident diabetes but was not significant (P = 0.08), after adjusting for BMI and sex. Metabolomic age was significantly related to incident diabetes after controlling for BMI and sex (P < 0.05). Over the 11-year follow-up, 10 participants died owing to non-accidental causes. When metabolomic age and chronological age were included together in the model, metabolomic age (but not chronological age) was associated with mortality, independent of age, sex, and BMI. Among all identifiable metabolites, beta-D-mannosylphosphodecaprenyl and phosphatidylserines were the five leading metabolites associated with mortality.

CONCLUSION

We concluded that serum metabolomic profile was associated with incident diabetes as well as mortality over our 11-year study period, which may render it potentially useful in assessing biological aging in humans.

The biological age model for evaluating the degree of aging in centenarians

BACKGROUND

Biological age (BA) has been used to assess individuals' aging conditions. However, few studies have evaluated BA models' applicability in centenarians.

METHODS

Important organ function examinations were performed in 1798 cases of the longevity population (80∼115 years old) in Hainan, China. Eighty indicators were selected that responded to nutritional status, cardiovascular function, liver and kidney function, bone metabolic function, endocrine system, hematological system, and immune system. BA models were constructed using multiple linear regression (MLR), principal component analysis (PCA), Klemera and Doubal method (KDM), random forest (RF), support vector machine (SVM), extreme gradient boosting (XGBoost), and light gradient boosting machine (lightGBM) methods. A tenfold crossover validated the efficacy of models.

RESULTS

A total of 1398 participants were enrolled, of whom centenarians accounted for 49.21%. Seven aging markers were obtained, including estimated glomerular filtration rate, albumin, pulse pressure, calf circumference, body surface area, fructosamine, and complement 4. Eight BA models were successfully constructed, namely MLR, PCA, KDM1, KDM2, RF, SVM, XGBoost and lightGBM, which had the worst R2 of 0.45 and the best R2 of 0.92. The best R2 for cross-validation was KDM2 (0.89), followed by PCA (0.62).

CONCLUSION

In this study, we successfully applied eight methods, including traditional methods and machine learning, to construct models of biological age, and the performance varied among the models.

Methodology Advances in Vertebrate Age Estimation

Age is a core metric in vertebrate management, and the correct estimation of the age of an individual plays a principal role in comprehending animal behavior, identifying genealogical information, and assessing the potential reproductive capacity of populations. Vertebrates have a vertebral column and a distinct head containing a developed brain; they have played an important role in the study of biological evolution. However, biological age estimations constantly exhibit large deviations due to the diversity of vertebrate taxon species, sample types, and determination methods. To systematically and comprehensively understand age estimation methods in different situations, we classify the degree of damage to vertebrates during sample collection, present the sample types and their applications, list commonly applied methods, present methodological recommendations based on the combination of accuracy and implementability, and, finally, predict future methods for vertebrate age assessments, taking into account the current level of research and requirements. Through comprehensive data gathering and compilation, this work serves as an introduction and summary for those who are eager to catch up on related fields and facilitates the rapid and accurate selection of an evaluation method for researchers engaged in related research. This is essential to promote animal conservation and guide the smooth implementation of conservation management plans.