Biological Age Research Articles

Accelerated biological aging, healthy behaviors, and genetic susceptibility with incidence of stroke and its subtypes: A prospective cohort study.

Stroke risk increases with chronological age, but the relationship with biological age (BA) acceleration is poorly understood. We aimed to examine the association between BA acceleration and incident stroke and its subtypes, explore the modifying effects on genetic susceptibility, and assess how BA acceleration mediates the effect of behavior score. We studied 253,932 UK Biobank participants and computed two BA measures (Klemera-Doubal Method [KDM], Phenotypic Age [PhenoAge]), with BA acceleration calculated by regressing BA on chronological age. The polygenic risk score (PRS) was derived from 87 genetic loci. The behaviors score was based on diet, physical activity, tobacco/nicotine, sleep, and BMI. During a median follow-up of 13.6 years, 5460 strokes, 4337 ischemic stroke (IS), 951 intracerebral hemorrhage (ICH), and 553 subarachnoid hemorrhage (SAH) cases were documented. Adjusting for confounding factors, each standard deviation increase in BA acceleration was associated with higher stroke risk: for KDM-BA acceleration, stroke (HR = 1.28, 95% CI = 1.25-1.32), IS (1.32, 1.28-1.36), ICH (1.15, 1.08-1.23), and SAH (1.16, 1.07-1.27); for PhenoAge acceleration, stroke (1.22, 1.19-1.25), IS (1.26, 1.22-1.29), ICH (1.08, 1.02-1.16), and SAH (1.08, 1.00-1.18). Compared to participants with the lowest PRS and BA acceleration, those with the highest PRS and BA acceleration had the highest stroke risk (KDM-BA acceleration: 2.19, 1.85-2.59; PhenoAge acceleration: 2.03, 1.69-2.42). Additionally, there was an additive interaction between KDM-BA acceleration and PRS. The mediation proportion of BA acceleration in associations of behaviors score with incident stroke and its subtypes ranged from 15.84% to 33.08%. BA acceleration may raise stroke risk, especially in those with high genetic risk. Maintaining healthy behaviors may help mitigate this risk.

The prospective association of cellular markers of biological aging with menopause in the Coronary Artery Risk Development in Young Adults Study.

Evidence from cross-sectional studies mainly among postmenopausal women suggests that biological aging is associated with reproductive senescence. We evaluated the prospective association of cellular markers of biological aging measured during the premenopausal period, and changes in these markers, with age at menopause. We studied 583 premenopausal women (39% Black) from the Coronary Artery Risk Development in Young Adults Study who had data on biological aging markers in 2000-2001 and reached menopause by 2020-2021. Linear regression models were used to evaluate the association of telomere length, mitochondrial DNA copy number, intrinsic or extrinsic epigenetic age acceleration, and PhenoAge or GrimAge acceleration with age at menopause. The mean age at baseline was 41.2 ± 3.3 years, with the mean age at menopause being 49.1 (median, 50) years. About one in five women had surgical menopause. In chronological age-adjusted models, only baseline GrimAge acceleration was associated with age at menopause; women whose epigenetic age was older than their chronological age reached menopause at 0.12 years (~6 weeks) earlier compared with women with equal epigenetic and chronological age (β = -0.123; 95% CI, -0.224 to -0.022; P = 0.018). However, this association was not statistically significant after adjustment for sociodemographic, behavior/lifestyle, and metabolic factors. Similar results were observed when changes in these biological aging markers were evaluated. The same associations were observed in analyses limited to women who reached natural menopause. Sociodemographic, behavior/lifestyle, and metabolic factors remain comparable, if not more robust predictors of the age at menopause compared with cellular measures of biological age.

Perceived age estimation from facial image and demographic data in young and middle-aged South Korean adults

Biological age is an indicator of whether an individual is experiencing rapid, slowing, or normal aging. Perceived age is highly correlated with biological age, which reflects health appraisal and is often used as a clinical marker of aging. Perceived age has been reported as an important indicator of biological age and general health status, not only in older adult populations but also in young and middle-aged adults. However, there is a lack of objective methods for quantifying perceived age in these younger age groups. Thus, this study aimed to propose a novel perceived age estimation algorithm to meet the need for an objective method to predict perceived age. This cross-sectional study included 609 healthy men and 1388 healthy women (29.02–57.91 years, average 44.4 years) from 2017 to 2019 using data from the Korean Medicine Daejeon Citizen Cohort Study. The proposed algorithm comprised two steps. First, the initial predicted perceived age was estimated from facial images using a convolutional neural network (CNN) ensemble model. Then, the final perceived age was estimated using regression from the chronological age, sex, BMI, and initial predicted perceived age obtained in the first step. Better performance results were obtained by model averaging and model stacking generated from various basic regression models. The averaging models of Lasso, XGBoost, and CatBoost showed a mean absolute error of 2.2944, indicating that this algorithm can be used as a screening method for general health status in the population.

A socio-ecological approach to understanding self-regulation among adolescents with developmental challenges and delays

Abstract Drawing from the socio-ecological model, this study examined the relationships between child, family, and neighborhood/community factors and self-regulation among five subgroups of adolescents aged 12–17 years with developmental challenges and delays (Attention Deficit Disorder/Attention-Deficit/Hyperactivity Disorder, Autism/Autism Spectrum Disorder, developmental delay, learning disability, and intellectual disability). Data for this study came from the 2019 National Survey of Children’s Health, a nationally representative dataset (n=3,181). Using multiple regression analyses, we found that not all five subgroups of adolescents shared similar experiences. In sum, having good health and health insurance was positively associated with self-regulation, while adverse childhood experiences and being bullied were negatively linked to self-regulation. Family and neighborhood/community-related variables that were positively related to adolescents’ self-regulation consisted of parent-child closeness, having college-educated parents, household food security, and parents’ knowledge of where to obtain help in their neighborhood. Family variables negatively associated with adolescents’ self-regulation included living in two-parent households and receiving public assistance, but only for adolescents with intellectual disabilities. Socio-demographic variables significantly linked to adolescents’ self-regulation were biological sex, age, Hispanic ethnicity, and race. Future research and practice should focus on identifying and addressing the diverse ecological factors influencing adolescents’ social-emotional development to improve behavioral outcomes and support their transition to adulthood.

Baboons, bacteria, and biological clocks address an age-old question.

Studying the fecal microbiota of wild baboons helps provide new insight into the factors that influence biological aging.

Assessing the utility of epigenetic clocks for health prediction in South Korean

Epigenetic clocks have been developed to track both chronological age and biological age, which is defined by physiological biomarkers and the risk of adverse health outcomes. Epigenetic age acceleration (EAA) has been found to predict various diseases, aging-related factors, and mortality. However, epigenetic clocks have predominantly been developed with individuals of European or Hispanic ancestry, and their association with health outcomes and environmental factors has not been sufficiently assessed in East Asian populations. Here, we investigated nine epigenetic clocks: five trained on chronological age (first-generation) and four on biological age (second-generation), using DNA methylation data from blood samples of South Koreans. EAAs of second-generation epigenetic clocks reflected the risk of chronic diseases (type 2 diabetes and hypertension), levels of health-related blood markers (alanine aminotransferase, aspartate aminotransferase, high density lipoprotein, triglyceride, and high sensitivity C-reactive protein), and lung functions (percentage of predicted FEV1 and percentage of predicted FVC), while EAAs of first generation clocks did not. Using follow-up data, we also found that EAAs of second-generation clocks were associated with the time to onset risks of chronic diseases. Health behavior factors (drinking, smoking, exercise, body mass index, and waist-hip ratio), socioeconomic status (income level and educational attainment), and psychosocial status were associated with EAAs of second-generation clocks, while only smoking status was associated with EAAs of first-generation clocks. We conducted validation analyses in an independent South Korean cohort and replicated the association of EAAs with health outcomes and environmental factors. Age acceleration of epigenetic clocks is influenced by various environmental factors and can serve as an effective predictor of health in South Korea.

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 9.1years. 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.

Healthful plant-based diets are negatively associated with the rate of biological aging: A national study based on US adults

Plant-based diets are recognized for their health benefits. However, evidence on the association between plant-based diet quality and aging in the US population is limited. This study aimed to investigate the association between different plant-based diet indices, phenotypic age acceleration (PhenoAgeAccel), and biological age acceleration (BioAgeAccel). We hypothesized that healthful plant-based diets would negatively affect PhenoAgeAccel and BioAgeAccel in US adults. The cross-sectional analysis included 22,363 participants, and information was obtained from the National Health and Nutrition Examination Survey database. The quality of plant-based diet was assessed using three indices: overall plant-based diet index (PDI), healthful PDI (hPDI), and unhealthful PDI (uPDI). Phenotypic age (PA) and biological age (BA) was calculated based on a linear combination of chronological age and 12 multi-system clinical chemistry biomarkers in accordance with the previously established method. PhenoAgeAccel and BioAgeAccel are the residuals of the PA and BA. Weighted linear regression analyses were performed to evaluate the relationships between PDI, hPDI and uPDI, and PhenoAgeAccel and BioAgeAccel. After adjusting for all covariates, we observed that a 10-unit higher PDI score was associated with 0.80 years lower PhenoAgeAccel (β: −0.80, 95% confidence interval [CI]: -0.94,-0.67), and 1.91 years lower BioAgeAccel (β: −1.91, 95% CI: -2.42,-1.40). A 10-unit higher hPDI score was associated with 0.83 years lower PhenoAgeAccel (β: −0.83, 95% CI: -0.96,-0.70), and 1.76 years lower BioAgeAccel (β: −1.76, 95% CI: -2.18,-1.34). Conversely, a 10-unit higher uPDI score was associated with 0.77 years higher PhenoAgeAccel (β: 0.77, 95% CI: 0.66,0.89) and 1.21 years higher BioAgeAccel (β: 1.21, 95% CI: 0.80,1.62). These findings suggest that US adults may be able to slow the aging process by increasing adherence to a healthy plant-based diet.

Regularized scalar-on-function regression analysis to assess functional association of critical physical activity window with biological age

Regularized scalar-on-function regression analysis to assess functional association of critical physical activity window with biological age

Tissue‐specific methylomic responses to a lifestyle intervention in older adults associate with metabolic and physiological health improvements

AbstractAcross the lifespan, diet and physical activity profiles substantially influence immunometabolic health. DNA methylation, as a tissue‐specific marker sensitive to behavioral change, may mediate these effects through modulation of transcription factor binding and subsequent gene expression. Despite this, few human studies have profiled DNA methylation and gene expression simultaneously in multiple tissues or examined how molecular levels react and interact in response to lifestyle changes. The Growing Old Together (GOTO) study is a 13‐week lifestyle intervention in older adults, which imparted health benefits to participants. Here, we characterize the DNA methylation response to this intervention at over 750 thousand CpGs in muscle, adipose, and blood. Differentially methylated sites are enriched for active chromatin states, located close to relevant transcription factor binding sites, and associated with changing expression of insulin sensitivity genes and health parameters. In addition, measures of biological age are consistently reduced, with decreases in grimAge associated with observed health improvements. Taken together, our results identify responsive molecular markers and demonstrate their potential to measure progression and finetune treatment of age‐related risks and diseases.

Age-related clonal hematopoiesis and HIV infection are associated with geriatric outcomes: The ARCHIVE study.

While HIV infection and clonal hematopoiesis (CH) have been linked with inflammatory dysregulation and an increased risk of aging-related comorbidities, their relationship with clinical geriatric syndromes has not been well defined. In the Age-related Clonal Haematopoiesis in an HIV Evaluation Cohort (ARCHIVE) study (NCT04641013), we measure associations between HIV and CH and geriatric syndromes. Of 345 participants (176 with HIV and 169 without HIV), 23% had at least one mutation associated with CH: 27% with HIV and 18% without HIV (p= 0.048). In adjusted analyses, HIV infection is independently associated with increased phenotypic age acceleration (coefficient 1.73, 95% confidence interval [CI] 0.3, 3.16) and CH is independently associated with being frail (vs. pre-frail/robust; odds ratio 2.38, 95% CI 1.01, 5.67) and with having reduced quality of life (coefficient -2.18, 95% CI -3.92, -0.44). Our findings suggest that HIV is associated with increased biological age and that CH may be used as a biomarker for adverse geriatric outcomes.

Design of the VOILA-intervention study: A 12-week nutrition and resistance exercise intervention in metabolic or mobility compromised Dutch older adults and the response on immune-metabolic, gut and muscle health parameters

BackgroundExercise and nutrition interventions can slow ageing-induced decline in physiology. However, effects are heterogeneous and usually studied separately per outcome domain. In the VOILA study, we simultaneously study various health outcomes relevant for older adults and the inter-individual heterogeneity in response to a lifestyle intervention. MethodsVOILA is a 12-week lifestyle intervention in 3 groups of older adults (≥60 years), with compromised mobility (n=50), compromised metabolic health (n=50), or recovering from total knee replacement (TKR, n=70, of which 20 randomized to standard care only). The intervention includes high-intensity resistance exercise training thrice weekly, nutritional counselling, and nutritional supplements every morning and evening (including 20-25g whey protein and (evening only) 5.5g Biotis™ GOS). We measure immune-metabolic, gut health, muscle mass and physical functioning at baseline and after completion of the intervention/standard care. An additional reference group of healthy older adults (n=50) will undergo baseline measurements only. DiscussionImprovements in various physiological systems are expected, but with differences between groups/individuals. This study will provide insights into how the physiological state of older adults influences the extent of lifestyle-induced health improvements to create better tailored interventions to attenuate biological ageing and improve the health span of subgroups and individuals.

The Mediating Role of Body Mass Index in the Association Between Dietary Index for Gut Microbiota and Biological Age: A Study Based on NHANES 2007–2018

Objective: The dietary index for gut microbiota (DI-GM) is a newly proposed metric for assessing diet quality, and its relationship with biological age is unclear. We hypothesize that consuming foods conducive to a healthy gut microbiota environment may decelerate aging. Methods: This cross-sectional study utilized data from the National Health and Nutrition Examination Survey (NHANES) spanning the years 2007 to 2018. The DI-GM was calculated by averaging the intakes from two 24-h dietary recall interviews. The biological age indicators were assessed using the Klemera–Doubal Method (KDM), phenotypic age (PA), and homeostasis disorder (HD). Logistic regression, restricted cubic splines (RCS), and mediation analysis were employed to explore the association between DI-GM and KDM, PA, and HD. Results: The study included 20,671 participants. According to the logistic regression model, adjusting for all covariates, a negative association was observed between the DI-GM score and biomarkers of biological aging. Compared to participants in the lowest quartile for DI-GM scores, those in the highest quartile exhibited reduced odds ratio (OR) for all of the biological age indicators, namely biological age assessed via KDM (OR: 0.69, 95% CI: 0.60–0.79), PA (OR: 0.84, 95% CI: 0.73–0.97), and HD (OR: 0.86, 95% CI: 0.76–0.98). Additionally, RCS analysis revealed a nonlinear association between DI-GM and biological age. Mediation analysis showed that the body mass index (BMI) partly mediated the association between DI-GM and biological age. Conclusions: Therefore, we concluded that a higher DI-GM score is associated with a lower risk of accelerated aging, with BMI mediating this association. Future research should validate these findings through the use of longitudinal studies.

Molecular Aspects of Loss of Y-linked Proteins and Their Potential Applications in Cell Biology

Loss of proteins linked to Y chromosome (LOY) is a biomarker in human that is typically found in male blood samples. In healthy males, its frequency often rises with age. Additionally, it has lately been linked to numerous illnesses, including cancer with significantly high prevalence. A healthy male development depends on the Y chromosome and associated proteins. The deletion of this chromosome’s proteins or even its LOY variant may have effects on the male body. These proteins serve purposes beyond those of the male reproductive system. Paternity testing, ancestry research, and sexual assault investigations are just a few of the forensic situations where Y-linked protein analyses are frequently used. Due to its connection to the aging process, LOY detection has the benefit of being a biological age biomarker. The possibility of using LOY as a biomarker brings to light the need to define the molecular process underlying its occurrence and its potential applications in both health and forensic studies. Humans frequently experience LOY, a non-physiological post-zygotic molecular change that mostly affects male blood cells[Forsberg, 2017; Forsberg et al., 2017]. It is a natural part of aging and has been related to a number of illnesses, including as Alzheimer’s, Autoimmune disorders, Schizophrenia, Cardiovascular problems, and different malignancies[Holmes et al., 1985;Persanietal., 2012; Dumanskiet al., 2016; Forsberg, 2017; Forsberg et al., 2017; Haitjemaet al., 2017;]. It is possible to think about LOY as a biological age marker and a biomarker that predicts male age-related disorders [Dumanskiet al., 2016].However, LOY analysis might obstruct the forensic examination of male samples while also being helpful in forensic investigations by offering important details.

Association between cardiometabolic index and biological aging in the US population: evidence from NHANES 2015–2020

Association between cardiometabolic index and biological aging in the US population: evidence from NHANES 2015–2020

Advanced liver fibrosis, but not MASLD, is associated with accelerated biological aging: a population-based study

BackgroundThe process of biological aging in patients diagnosed with chronic liver disease remains unclear.AimThe current study aims to investigate if there is an accelerated biological aging process in participants with advanced fibrosis (AF) and metabolic dysfunction-associated steatotic liver disease (MASLD).MethodsData from the 2017–2018 NHANES cycle were analyzed. AF was determined based on the values of liver stiffness measurement (LSM) and MASLD was defined according to new consensus nomenclature. Klemera-Doubal method biological age (KDM bioage) and Phenotypic age (Phenoage) were adopted to quantify biological age. Phenoage advancement (Phenoage_advance) and KDM advancement (KDM_advance) were generated as the difference between the calculated biological age and chronological age, and a positive residual was regarded as an indicator of accelerated biological aging.ResultsA total of 3974 participants was enrolled. The weight mean KDM_advance and phenoage_advance in AF group was 4.22 years (95%CI: 2.96–5.49 years) and 2.61 years (95%CI: 1.80–3.41 years), while in MASLD group was 0.37 years (95%CI: -0.28–1.03 years) and 0.04 years (95%CI: -0.64–0.72 years), respectively. Multivariate linear regression analysis showed that participants with AF had older KDM_advance and phenoage_advance compared with those without AF (1.50 years (95%CI: 0.23–2.77 years), P = 0.02; 1.00 years (95%CI: 0.18–1.82 years), P = 0.02; respectively), in models adjusting demographic characteristics, socioeconomic status, lifestyle factors, and comorbidities. No significant association was found between MASLD and KDM_advance and phenoage_advance.ConclusionsAF, not MASLD, was independently associated with accelerated biological aging in adults from a US representative sample.

Selection for early reproduction leads to accelerated aging and extensive metabolic remodeling in Drosophila melanogaster.

While experimental evolution studies featuring Drosophila melanogaster have generated significant insights into the forces that shape aging and life history patterns, more recent efforts incorporating genomic and transcriptomic data have had comparatively little success identifying the molecular mechanisms underlying these patterns. Here we work to incorporate molecular phenotyping into this general framework as a way forward. Specifically, we characterize how the metabolome changes with age in populations of D. melanogaster where hundreds of generations of selection for early reproduction have led to enrichment for an accelerated aging phenotype. By comparing to control populations, we show that the metabolome does appear to capture true signals of "biological age" and provides a new avenue for understanding the factors that underlie complex trait variation in real populations.

Associations between ethylene oxide exposure and biological age acceleration: evidence from NHANES 2013–2016

IntroductionPopulation aging is a global concern, with the World Health Organization predicting that by 2030, one in six individuals worldwide will be 60 years or older. Ethylene oxide (EO) is a widely used industrial chemical with potential health risks, including associations with age-related diseases. This study investigates the relationship between EO exposure and biological age acceleration.MethodData from the National Health and Nutrition Examination Survey (NHANES) 2013–2016 were analyzed, including 3,155 participants after exclusions. Blood EO levels were measured using hemoglobin adducts (HbEO). Biological age acceleration was assessed using two methods: Phenotypic Age Acceleration (PhenoAgeAccel) and Klemera-Doubal Method Age Acceleration (KDM-AA). Linear and logistic regression models were applied, adjusting for various covariates, and restricted cubic spline (RCS) regression was used to explore non-linear associations.ResultsHigher EO exposure was significantly associated with increased PhenoAgeAccel and KDM-AA across all models. In the continuous model, substantial positive associations were observed (PhenoAgeAccel: β = 0.73, p < 0.001; KDM-AA: β = 0.66, p < 0.001) in Model 3. Quintile analysis indicated a trend of increasing biological age acceleration with higher EO exposure. RCS regression demonstrated a significant linear relationship between EO exposure and PhenoAgeAccel (p for non-linearity = 0.067), as well as with KDM-AA (p for non-linearity = 0.083). Subgroup and interaction analyses revealed significant modifying effects by factors such as body mass index, gender, diabetes status, and physical activity level.ConclusionOur study demonstrates a significant association between EO exposure and accelerated biological aging. These findings highlight the need for further prospective and mechanistic studies to validate and explore this phenomenon.

Disentangling the relationship between biological age and frailty in community-dwelling older Mexican adults.

Older adults have highly heterogeneous aging rates. To explore the association of biological age (BA) and accelerated aging with frailty in community-dwelling older adults. We assessed 735 community-dwelling older adults from the Coyocan Cohort. BA was measured using AnthropoAge, accelerated aging with AnthropoAgeAccel, and frailty using Fried's phenotype and the frailty index. We explored the association of BA and accelerated aging (AnthropoAgeAccel ≥ 0) with frailty at baseline and characterized the body composition and physical function phenotype of accelerated aging in non-frail/frail participants. We also explored accelerated aging as a risk factor for frailty progression after 3-years of follow-up. Older adults with accelerated aging have higher frailty prevalence and indices, lower handgrip strength and gait speed. AnthropoAgeAccel was associated with higher frailty indices (β = 0.0053, 95%CI 0.0027-0.0079), and increased odds of frailty at baseline (OR 1.16, 95%CI 1.09-1.25). We observed sex-based differences in body composition and physical function linked to accelerated aging in non-frail participants; however, these differences were absent in pre-frail/frail participants. Accelerated aging at baseline was associated with higher risk of frailty progression over time (OR 1.74, 95%CI 1.11-2.75). Despite being intertwined, biological accelerated aging is largely independent of frailty in community-dwelling older adults.

Multimorbidity is associated with myocardial DNA damage, nucleolar stress, dysregulated energy metabolism, and senescence in cardiovascular disease

This study investigates why individuals with multimorbidity—two or more chronic conditions—are more prone to adverse outcomes after surgery. In our cohort, ninety-eight of 144 participants had multimorbidity. The myocardial transcriptome and metabolites involved in energy production were measured in 53 and 57 sequential participants, respectively. Untargeted analysis of the metabolome in blood and myocardium was performed in 30 sequential participants. Mitochondrial respiration in circulating mononuclear cells was measured in 70 participants. Results highlighted four main biological processes associated with multimorbidity: DNA damage with epigenetic changes, mitochondrial energy disruption, cellular aging (senescence) and innate immune response. Histone 2B, its ubiquitination enzymes and AKT3 were upregulated in the multimorbid group. Plasma senescence-associated proteins (IL-1β, GM-CSF) increased with more comorbidities. DNA damage and nucleolar instability were specifically apparent in multimorbid myocardium. We conclude that multimorbidity in cardiovascular patients accelerates biological aging, making them more vulnerable to metabolic stress.