Low sensory responsiveness is associated with accelerated aging in midlife.

Objectives This study aimed to examine the association and dose-relationship between different intensities of work-related and leisure-time physical activity (PA) and biological age (BA). Design: A cross-sectional study. Setting and participants: We used data of 5,216 participants aged 45 and over in the National Health and Nutrition Examination Surveys (NHANES). Measurements: PA was self-reported using the Global Physical Activity Questionnaire (GPAQ), and BAs were calculated by the PhenoAge and Klemera-Doubal method (KDM). In the analyses, survey-weighted generalized linear models were used to explore associations between PA and BAs. Restricted cubic spline characterized the dose-response relationship of PA and BAs. Subgroup analyses were conducted by age, sex, and ethnicity. Results Work-related light-intensity PA (LPA) was significantly associated with younger PhenoAge (β=0.507, 95%CI: -0.957, -0.056, p = 0.031) and KDM (β=0.908, 95%CI: -1.774, -0.042, p = 0.042). There was a U-shaped dose-response relationship between LPA and BAs (all p < 0.05). Leisure-time moderate-intensity PA (MPA) was associated with younger PhenoAge (β=0.789, 95%CI: -1.573, -0.006, p=0.049) and KDM (β=1.910, 95%CI: -3.417, -0.402, p = 0.017). There was a U-shaped dose-response relationship between MPA and BAs (all p < 0.05). In subgroup analyses for older adults, all intensities of PA were significantly associated with decreased BAs (all p < 0.05). Conclusions: Doing PA could delay the BAs, specifically the work-related LPA and leisure-time MPA. Older adults can benefit from all intensities of PA regardless of the PA of different environments and intensities.

Aging is a recognized risk factor for periodontitis, while biological aging could provide more accurate insights into an individual's functional status. This study aimed to investigate the potential association between biological aging and periodontitis. Epidemiological data from 9803 participants in the 2009–2014 National Health and Nutrition Examination Survey were analyzed at a cross-sectional level to assess this link. Three biological ages [Klemera–Doubal method (KDM), PhenoAge, and homeostatic dysregulation (HD)] and two measures of accelerated biological aging (BioAgeAccel and PhenoAgeAccel) were set as primary exposure and were calculated. Logistic regression and restricted cubic spline regression were employed to examine the relationship between biological aging and periodontitis. Additionally, Mendelian randomization analysis was conducted to explore the causal connection between accelerated biological aging and periodontitis. After adjusting for age, gender, race, educational level, marital status, ratio of family income, and disease conditions, this study, found a significant association between subjects with older higher biological ages, accelerated biological aging, and periodontitis. Specifically, for a per year increase in the three biological ages (HD, KDM, and PhenoAge), the risk of periodontitis increases by 15%, 3%, and 4% respectively. Individuals who had positive BioAgeAccel or PhenoAgeAccel were 20% or 37% more likely to develop periodontitis compared with those who had negative BioAgeAccel or PhenoAgeAccel. Furthermore, a significant non-linear positive relationship was observed between the three biological ages, accelerated biological aging, and periodontitis. However, the Mendelian randomization analysis indicated no causal effect of accelerated biological aging on periodontitis. Our findings suggest that biological aging may contribute to the risk of periodontitis, highlighting the potential utility of preventive strategies targeting aging-related pathways in reducing periodontitis risk among older adults.

BackgroundInsulin resistance (IR) has been reported to be associated with aging; however, few studies have investigated the relationship between IR and biological age (BA). The Triglyceride–glucose (TyG) index is a recognized marker of IR. Currently, there is insufficient evidence regarding the relationship between the TyG index and biological aging. This study aims to provide deeper insights into the connections between the TyG index and biological aging.MethodsWe conducted a cross-sectional study using data from the National Health and Nutrition Examination Survey (NHANES), including 12,074 adults (aged 20 and older) from the 2001–2010 and 2015–2018 cycles. Comprehensive TyG and BA data were extracted for analysis. To explore the relationship between the TyG index and BA, linear regressions were employed, while logistic regression models were used to examine the association between the TyG index and accelerated aging. Additionally, trend tests, subgroup analyses, and smoothed fitted curves were conducted to assess the robustness of the findings.ResultsWe included 12,074 participants with a mean age of 46.91 years (SD, 16.64); of these, 50.25% were female and 49.75% were male. Each 1-unit increase in the TyG index was associated with a 1.64-year rise in Klemera–Doubal method (KDM) biological age and a 117% higher risk of accelerated aging. Similarly, each 1-unit increase in the TyG index corresponded to a 0.40-year increase in phenotypic age, resulting in a 15% higher risk of accelerated aging. The analysis also revealed nonlinear positive relationships between the TyG index and biological aging, particularly for KDM biological age (P for non-linearity < 0.001) and phenotypic age (P for non-linearity = 0.005), with a turning point at 8.66. Across all subgroups, the TyG index consistently showed a positive correlation with biological aging, even in the presence of significant interactions.ConclusionsThere is a significant positive association between the TyG index and biological aging. Higher TyG levels are linked to increased biological age and a greater risk of accelerated aging.

Biological age (BA) metrics, constructed by physical and biochemical markers, are increasingly recognized as powerful tools to quantify the biological processes associated with aging. Health and function in a population of the same chronological age (CA) varies between individuals. BA metrics, such as Klemera-Doubal Method (KDM), PhenoAge, and Homeostatic Dysregulation (HD) provide an age independent assessment of health status. Here, we aimed to examine the robustness and utility of BA metrics using data from a 12-week, randomized, parallel group, double-blind, placebo-controlled pilot study evaluating the safety and tolerability of a ketone ester (n=23; M=14, F=9; age=76y, range 65-90y). KDM and PhenoAge, and their residuals, showed strong correlations with CA (r=0.80 and r=0.89, respectively). In contrast, HD and its residual exhibited minimal correlation with CA (r=0.04). Using LASSO regression models, we identified several significant predictors of BA, including red cell distribution width, monocyte percentage, blood urea nitrogen, pulse and blood pressure, C-reactive protein, and total cholesterol and high-density lipoprotein. The models’ reliability was confirmed by minimizing prediction errors through cross-validated mean squared error paths, validating their robustness and generalizability. Our results validate KDM and PhenoAge as reliable BA metrics, emphasizing their potential use in clinical settings to assess aging and predict health outcomes. The biomarkers we found to predict BA reflect key biologic processes, such as inflammation, immune, kidney, and cardiac function, and metabolism, underscoring the relevance of BA as a complement to CA in assessing aging and age-related health risks.

Tea consumption and attenuation of biological aging: a longitudinal analysis from two cohort studies

BackgroundThe relationship between periodontitis and cardiovascular disease (CVD) has been extensively studied, but the role of biological aging in this relationship remains poorly understood. This study is dedicated to investigating the effect of periodontitis on the incidence of CVD and to elucidating the potential mediating role of biological aging. Furthermore, this study will seek to elucidate the causal association between periodontitis, CVD, and biological aging.MethodsWe included 3269 participants from the National Health and Nutrition Examination Survey (2009–2014) with diagnostic information on periodontitis and composite CVD events. Biological aging was evaluated by utilizing both the Klemera–Doubal method’s calculated biological age (KDMAge) and phenotypic age (PhenoAge). Logistic regression, restricted cubic spline (RCS) analysis, and subgroup analysis were used for data analysis. Mediation analysis was employed to explore the mediating role of biological aging. Subsequently, Mendelian randomization (MR) analyses were performed using genome-wide association study databases to explore potential causal relationships between periodontitis, CVD, and biological aging.ResultsPeriodontitis was associated with a higher risk of CVD. Participants with periodontitis were found to have increased levels of biological aging, and elevated levels of biological aging were associated with increased CVD risk. Mediation analyses showed a partial mediating effect of biological aging (PhenoAge: 44.6%; KDMAge: 22.9%) between periodontitis and CVD risk. MR analysis showed that periodontitis played a causal role in increasing the risk of small vessel stroke, while myocardial infarction was found to increase the risk of periodontitis. In addition, reverse MR analysis showed that phenotypic aging can increase the risk of periodontitis, and there is a two-way causal relationship between CVD and biological aging.ConclusionsPeriodontitis is associated with an increased CVD risk, partially mediated by biological aging, with a complex causal interrelationship. Targeted interventions for periodontal health may slow the biological aging processes and reduce CVD risk.

Associations between exposure to adverse childhood experiences and biological aging: Evidence from the Canadian Longitudinal Study on Aging

The Human Immunomics Initiative (HII), a joint project between the Harvard T.H. Chan School of Public Health and the Human Vaccines Project (HVP), focuses on studying immunity and the predictability of immuneresponsiveness to vaccines in aging populations. This paper describes the hypotheses and methodological approaches of this new collaborative initiative. Central to our thinking is the idea that predictors of age-related non-communicable diseases are the same as predictors for infectious diseases like COVID-19 and influenza. Fundamental to our approach is to differentiate between chronological, biological and immune age, and to use existing large-scale population cohorts. The latter provide well-typed phenotypic data on individuals’ health status over time, readouts of routine clinical biochemical biomarkers to determine biological age, and bio-banked plasma samples to deep phenotype humoral immune responses as biomarkers of immune age. The first phase of the program involves 1. the exploration of biological age, humoral biomarkers of immune age, and genetics in a large multigenerational cohort, and 2. the subsequent development of models of immunity in relation to health status in a second, prospective cohort of an aging population. In the second phase, vaccine responses and efficacy of licensed COVID-19 vaccines in the presence and absence of influenza-, pneumococcal- and pertussis vaccines routinely offered to elderly, will be studied in older aged participants of prospective population-based cohorts in different geographical locations who will be selected for representing distinct biological and immune ages. The HII research program is aimed at relating vaccine responsiveness to biological and immune age, and identifying aging-related pathways crucial to enhance vaccine effectiveness in aging populations.

Per- and polyfluoroalkyl substances (PFASs) can impact various systems in the human body. However, their influence on biological aging remains unclear. This study aims to investigate the association between PFASs exposure and biological aging based on data from 9756 participants in the China National Human Biomonitoring Program and assesses the potential moderating effect of Dietary Diversity Score (DDS). Biological age indexes were calculated using the Klemera-Doubal method (KDM) and Mahalanobis distance (MD). The DDS was calculated based on the consumption frequency of 13 food groups over the past 12 months. Most PFASs showed positive associations with KDM-age acceleration (KDM-AA), while no statistically significant associations were observed with MD. The dose-response relationships of PFASs with KDM-AA and MD were steeper at low concentrations of PFASs, and then the slope appeared flat at higher concentrations. The weighted quantile sum revealed positive mixture effects of PFASs on biological aging. PFHpS and PFNA were both major contributors to KDM-AA and MD. DDS appeared to potentially modify the association between PFASs and biological aging. Our findings demonstrate that PFASs were significantly associated with accelerated biological aging, whereas higher DDS mitigates these adverse effects, highlighting the importance of this preventive measure.

ObjectiveThis study examines the association between estimated glucose disposal rate (eGDR) and accelerated aging in middle-aged and older adults, with a focus on the mediating role of estimated pulse wave velocity (ePWV).MethodsData from the 2011 wave of the China Health and Retirement Longitudinal Study (CHARLS) were analyzed, including middle-aged and older participants. Biological age was estimated using the Klemera-Doubal method, and accelerated aging was defined as the difference between biological and chronological age. The eGDR was calculated based on waist circumference, hypertension status, and HbA1c levels, while ePWV was estimated using mean blood pressure and age. Logistic regression models assessed the relationship between baseline eGDR, ePWV, and accelerated aging, adjusting for confounders.ResultsA total of 8,529 participants (mean age 59.31 years) were included. A significant inverse association was found between eGDR and accelerated aging. Participants with the lowest eGDR quartile had an 81% higher risk of accelerated aging compared to those in the highest quartile (OR = 0.19, 95% CI 0.17–0.22, P < 0.001). Mediation analysis showed that ePWV mediated 12.90% of the relationship between eGDR and accelerated aging (95% CI 9.20%–16.60%).ConclusionReduced insulin sensitivity, indicated by low eGDR, is a significant risk factor for accelerated aging. Vascular aging, measured by ePWV, mediates part of this relationship. These findings highlight the importance of monitoring insulin sensitivity and vascular health to mitigate aging and age-related health risks.

BackgroundBiological aging is a heterogeneous process that varies across organs and systems. The dynamic hormonal changes during the menopausal transition may have profound and organ-specific impacts on biological aging. However, the relationship between the menopausal transition and both comprehensive and organ-specific biological aging remains poorly understood. This study aimed to investigate the associations between menopausal factors and both comprehensive and organ-specific biological aging, as well as the modifying role of reproductive history.MethodsThis study included 37,244 women from the China Multi-Ethnic Cohort (CMEC) and 140,479 from the UK Biobank (UKB). Menopausal factors included menopausal status, menopausal transition, and age at menopause. Comprehensive and organ-specific biological ages (BAs) were calculated using the Klemera-Doubal method and clinical biomarkers and have been shown to predict age-related health outcomes. Multiple linear regression and change-to-change models were applied, with stratified analyses based on reproductive history.ResultsCompared with pre-menopausal women, those who were peri- or post-menopausal or had undergone hysterectomy or oophorectomy exhibited greater acceleration in comprehensive, liver, metabolic, and kidney BA. In longitudinal change-to-change models, women undergoing menopausal transition showed greater increases in comprehensive BA (CMEC: β = 1.33, 95% CI = 0.89, 1.76; UKB: β = 2.60, 95% CI = 1.91, 3.30), as well as liver, metabolic, and kidney BAs compared to those remaining pre-menopausal. Earlier age at menopause was associated with accelerated comprehensive BA in UKB (< 40 years: β = 0.69, 95% CI = 0.39, 0.98; 40–44 years: β = 0.24, 95% CI = 0.09, 0.40). Across organ-specific BAs, liver BA showed the strongest associations with menopausal factors. Reproductive history like age at live birth and number of live births emerged as potential modifiers of these associations.ConclusionsMenopause, particularly the menopausal transition, was associated with accelerated comprehensive and organ-specific biological aging, with liver aging being most affected. These findings underscore the menopausal transition as a critical window for interventions to enhance women’s health and longevity.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12916-025-04223-7.

Reply from Ross D. Pollock, Norman R. Lazarus, Janet M. Lord and Stephen D. R. Harridge.

The biological processes that constitute ageing and lead to age-related disease risks are poorly understood. Improved knowledge of biomarkers that are indicators of ageing could highlight biological pathways where research should be focused, in order to identify modifiable risk factors and reduce risks currently attributed to chronological age. Previous studies have been limited in scale. Among 0.5 million participants aged 40–70 recruited into the UK Biobank between 2006–2010, we considered measurements for over 50 biomarkers describing physical and biochemical function, collected using touchscreen questionnaires, physical measurement devices, blood tests and urine tests. Linkage to electronic health records provided information on prior disease, and incidence of hospital-related outcomes and mortality for a median follow up duration of 6.0 years. The Klemera-Doubal method (recommended by previous studies) was used to derive a biological age by combining biomarkers strongly related to age, and was applied separately within each sex and by level of prior disease. In our ongoing research, worse lung function, lower fat-free body mass and lower bio-impedance metabolic rate emerge as strong risk factors of greater biological age. The effects of pre-preparation of biomarker measurements, such as adjusting for height or taking principle components, will be explored. We will discuss the predictive power of biological age for all-cause mortality and discharge to care homes, and the extent to which the predictive power of chronological age is captured by biological age and varies by prior disease.

Ageing is a complex process influenced by modifiable factors such as diet, which may accelerate or decelerate physiological decline. While chronological age increases uniformly, biological ageing varies between individuals, reflecting differences in health status and the resilience of biological systems. The Klemera-Doubal Method (KDM), a composite biomarker-based index often used as an estimate of biological age, has been associated with morbidity and mortality in large cohorts. This study examined whether dietary manipulation of protein source and macronutrient composition affects KDM estimates in older adults. We analysed data from the Nutrition for Healthy Living study, a 2 × 2 factorial dietary intervention trial involving 104 participants aged 65-75 years. Participants were randomised to one of four diets: omnivorous/high-fat (OHF), omnivorous/high-carbohydrate (OHC), semi-vegetarian/high-fat (VHF) or semi-vegetarian/high-carbohydrate (VHC). KDM-derived δAge (the difference between KDM- and chronological-age) was calculated before and after a 4-week intervention. The OHF group, most like participants' baseline diets, showed no meaningful change in δAge. Compared to OHF, participants in the OHC group showed a significant reduction in δAge. The VHF and VHC groups showed similar reductions in δAge, relative to OHF, though not all reached statistical significance. KDM-derived δAge appears responsive to dietary change within 4 weeks and may offer a useful proxy for evaluating shifts in physiological status. Caution is warranted in interpreting such changes as evidence of biological age reversal as observed shifts may reflect acute physiological responsiveness to dietary inputs rather than altered ageing trajectories. Longer-term treatment would be needed to assess changes in age-related disease risks.

BackgroundCarotenoids have been shown to have multiple health benefits, including antioxidant and anti-inflammatory. The data for the effect of dietary specific carotenoids on biological aging is limited. Our study aims to examine the association between dietary carotenoid intake levels and biological aging.MethodsThis cross-sectional study was performed among 27,338 adults from NHANES 1999–2018. Dietary intake was assessed through two 24-hour dietary recall interviews. Biological aging indices included allostatic load (AL), homeostatic dysregulation (HD), Klemera-Doubal method (KDM), and phenoAge (PA). Multiple linear regression, weighted quantile sum (WQS) regression and quantile g-computation (QG-comp) were used to explore the associations of single carotenoid and mixed carotenoids with biological aging.ResultsAssociations between dietary carotenoid intake levels and biological aging indices were significant among adults across the United States. Multiple linear regression showed that most carotenoids were significantly negatively correlated with AL (β = -0.017 - -0.011), HD (β = -0.045 - -0.032), KDM (β = -0.984 - -0.471), and PA (β = -0.975 - -0.539). Subgroup analysis indicated that male, older individuals, smokers, alcohol drinkers, and less physically active individuals are particularly sensitive populations. Meanwhile, WQS regression and QG-comp analyses consistently indicated a negative association between mixed carotenoids exposure and four biological aging indices, highlighting that lutein/zeaxanthin and β-carotene were responsible for the outcomes.ConclusionsIncreased dietary intakes of various carotenoids were associated with lower biological aging indices, which was possibly and mainly driven by lutein/zeaxanthin and β-carotene.