Longitudinal trajectories, correlations and mortality associations of nine biological ages across 20-years follow-up

Association between frailty index and epigenetic aging acceleration in older adults: Evidence from the health and retirement study

BACKGOUND

This study aimed to examine the associations between the frailty index and four epigenetic aging acceleration (EAA) estimators in cross-sectional and longitudinal settings.

METHODS

The frailty index in the older adults was measured according to a cumulative health-deficit model. Four different epigenetic age measures (Hannum, PhenoAge, GrimAge, and DunedinPoAm38) were regressed against chronological age, and the resulting standardized residuals were indicative of EAA. The longitudinal relationship between EAA at baseline and changes in the frailty index during the 4-year follow-up were examined using a mixed linear model.

RESULTS

A single standard deviation (SD) increment in the frailty index was associated with a faster EAA, as indicated by the four clocks in Hannum (b = 0.057; P = 0.015), PhenoAge (b = 0.096; P < 0.001), GrimAge (b = 0.120; P < 0.001), and DunedinPoAm38 (b = 0.062; P = 0.002) in the fully adjusted model. A 1-SD increment in the GrimAge EAA was associated with a 0.003 frailty index increase (b = 0.003; P = 0.002). A 1-SD increment in DunedinPoAm38 EAA was associated with a 0.002 frailty index increase (b = 0.002; P = 0.009).

CONCLUSIONS

The frailty index was cross-sectionally associated with EAA, while only GrimAge and DunedinPoAm38 EAA predicted changes in the frailty index. More research is needed to understand the interplay between pathways.

Early-Life Exposure to Tobacco Smoke and the Risk of Idiopathic Pulmonary Fibrosis: A Population-Based Cohort Study

Rationale: Tobacco smoking is a well-established risk factor for idiopathic pulmonary fibrosis (IPF), yet the influence of early-life tobacco exposure on future IPF risk remains poorly understood. Objectives: We sought to test the hypothesis that early-life tobacco exposure may elevate the risk of developing IPF, with this effect potentially modified by genetic susceptibility to IPF and mediated through accelerated biological aging. Methods: Using data from over 430,000 participants in the UK Biobank, we performed a prospective cohort study to examine the associations of maternal smoking around birth and age of smoking initiation with IPF risk. We evaluated the combined effects and interactions between early-life tobacco exposure and genetic susceptibility to IPF, which were quantified using polygenic risk scores. We assessed biological aging, as measured by telomere length and phenotypic age, as potential mediators in the associations between early-life tobacco exposure and IPF risk. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Results: Maternal smoking around birth was associated with a higher risk of IPF (HR = 1.26; 95% CI = 1.11-1.43). Compared with never-smokers, individuals who initiated smoking in childhood (HR = 3.65; 95% CI = 3.02-4.41), adolescence (HR = 2.64; 95% CI = 2.28-3.05), and adulthood (HR = 2.09; 95% CI = 1.79-2.44) exhibited increased IPF risk (P for trend <0.001). An additive interaction was observed between age of smoking initiation and genetic risk for IPF. Individuals with high genetic risk, maternal smoking exposure, and childhood smoking initiation had a 16-fold greater risk of IPF (HR = 16.47; 95% CI = 9.57-28.32), compared with those with low genetic risk and no tobacco exposure. Telomere length and phenotypic age each mediated approximately 10% of the effect of maternal smoking on IPF, with weaker mediation effects observed for later ages of smoking initiation. Conclusions: Early-life tobacco exposure may elevate the risk of IPF, with effects modified by genetic susceptibility and partially mediated through accelerated biological aging.

Biological Ageing and the Risk of Inflammatory Bowel Disease: Exploring the Role of Lifestyle and Genetic Susceptibility in a Nationwide Prospective Study

BACKGROUND

Accelerated biological aging has been linked to an increased risk of inflammatory bowel disease (IBD), though its interplay with genetic susceptibility remains unclear.

METHODS

We analyzed data from 310 441 UK Biobank participants to investigate associations between PhenoAge acceleration (a measure of biological aging), genetic risk, and the incidence of ulcerative colitis (UC) and Crohn's disease (CD).

RESULTS

During follow-up, 3364 participants (1.08%) developed UC and 1831 (0.59%) developed CD. After adjusting for all confounders, each 1-year increase in PhenoAge acceleration was associated with a 6.9% increase in UC risk (HR = 1.069, 95% CI, 1.063-1.074) and an 8.5% increase in CD risk (HR = 1.085, 95% CI, 1.079-1.092). Participants who were biologically older showed a higher risk of UC (HR = 1.928, 95% CI, 1.799-2.067) and CD (HR = 2.557, 95% CI, 2.330-2.807) compared with their younger counterparts. Moreover, PhenoAge acceleration partially mediated the associations of alcohol consumption and cigarette smoking with UC and CD risk (11.2%-27.2%). We observed dose-response associations between polygenic risk scores and both UC and CD. Compared with the bottom quintile, high-risk participants (top quintile) showed a 439.9% increase (HR = 2.229, 95% CI, 1.949-2.550) in UC risk and a 501.7% increase (HR = 6.017, 95% CI, 5.254-6.891) in CD risk. Notably, individuals with both high genetic risk and accelerated aging exhibited the greatest susceptibility (UC: HR = 11.569, 95% CI, 9.658-13.858; CD: HR = 12.018, 95% CI, 9.569-15.094).

CONCLUSIONS

PhenoAge acceleration may serve as a useful biomarker for identifying high-risk individuals, offering potential for integration into targeted prevention strategies and personalized treatment approaches for IBD.This study explores how accelerated biological aging (PhenoAge acceleration) and genetic susceptibility influence the risk of inflammatory bowel disease. Findings indicate that higher PhenoAge acceleration and genetic risk scores significantly increase the likelihood of developing ulcerative colitis and Crohn's disease.

Health octo tool matches personalized health with rate of aging

Medical practice mainly addresses single diseases, neglecting multimorbidity as a heterogeneous health decline across organ systems. Aging is a multidimensional process and cannot be captured by a single metric. Therefore, we assessed global health in longitudinal studies, BLSA (n = 907), InCHIANTI (n = 986), and NHANES (n = 40,790), by examining disease severities in 13 bodily systems, generating the Body Organ Disease Number (BODN), reflecting progressive system morbidities. We used Bayesian ordinal models, regressing BODN over organ specific and all organs disease severities to obtain Body System-Specific Clocks and the Body Clock, respectively. The Body Clock is BODN weighted by the posterior coefficient of diseases for each individual. It supersedes the frailty index, predicting disability, geriatric syndrome, SPPB, and mortality with ≥90% accuracy. The Health Octo Tool, derived from Bodily System-Specific Clocks, the Body Clock and Clocks that incorporate walking speed and disability and their aging rates, captures multidimensional aging heterogeneity across organs and individuals.

Signatures of Nonlinear Aging: Molecular Stages of Life: Sudden Changes During Aging as Potential Biomarkers for an Age Classification System

The traditional view of aging as a gradual, progressive process is increasingly being challenged. A growing body of evidence suggests the existence of abrupt transitions in the aging process, marked by sudden molecular shifts. Interestingly, the data indicates that such transitions occur not only in late life but also throughout the entire lifespan. Further research on the nature of such events could enhance our understanding of aging and pave the way for novel therapeutic strategies, including personalized medicine. We propose that these abrupt molecular shifts could serve as biomarkers, dividing the lifespan into distinct stages and providing the foundation for a much-needed staging system for aging. Furthermore, we argue that the sudden changes may be the hallmarks of aging tipping points, that is, points in time where aging processes are quickly amplified after surpassing critical biological thresholds.

Dietary Diversity Modified the Association of Per- and Polyfluoroalkyl Substances with Accelerated Biological Aging: Evidence from the China National Human Biomonitoring Study

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.

Low blood levels of selenium, selenoprotein P and GPx3 are associated with accelerated biological aging: results from the Berlin Aging Study II (BASE-II)

BACKGROUND

Biological age reflects inter-individual differences in biological function and capacity beyond chronological age. DNA methylation age (DNAmA) and its deviation from chronological age, DNAmA acceleration (DNAmAA), which was calculated as residuals of leukocyte cell count adjusted linear regression of DNAmA on chronological age, were used to estimate biological age in this study. Low levels of serum selenium, selenoprotein P (SELENOP), and the selenocysteine-containing glutathione peroxidase 3 (GPx3) are associated with adverse health outcomes and selenium supplementation is discussed as an anti-aging intervention.

METHODS

In this study, we cross-sectionally analyzed 1568 older participants from the observational Berlin Aging Study II (mean age ± SD: 68.8 ± 3.7 years, 51% women). Serum selenium was measured by total reflection X-ray fluorescence (TXRF) spectroscopy and SELENOP was determined by sandwich ELISA. GPx3 was assessed as part of a proteomics dataset using liquid chromatography-mass spectrometry (LC-MS). The relationship between selenium biomarkers and epigenetic clock measures was analyzed using linear regression analyses. P values and 95% confidence intervals (not adjusted for multiple testing) are stated for each analysis.

RESULTS

Participants with deficient serum selenium levels (< 90 μg/L) had a higher rate of biological aging (DunedinPACE, β = - 0.02, SE = 0.01, 95% CI - 0.033 to - 0.004, p = 0.010, n = 865). This association remained statistically significant after adjustment for age, sex, BMI, smoking, and first four genetic principal components (β = - 0.02, SE = 0.01, 95% CI - 0.034 to - 0.004, p = 0.012, n = 757). Compared to the highest quartile, participants in the lowest quartile of SELENOP levels showed an accelerated biological aging rate (DunedinPACE, β = - 0.03, SE = 0.01, 95% CI - 0.051 to - 0.008, p = 0.007, n = 740, fully adjusted model). Similarly, after adjustment for confounders, accelerated biological age was found in participants within the lowest GPx3 quartile compared to participants in the fourth quartile (DunedinPACE, β = - 0.04, SE = 0.01, 95% CI - 0.06 to - 0.02, p = 0.001, n = 674 and GrimAge, β = - 0.98, SE = 0.32, 95% CI - 1.6 to - 0.4, p = 0.002, n = 608). Only the association with GPx3 remained statistically significant after multiple testing correction.

CONCLUSION

Our study suggests that low levels of selenium biomarkers are associated with accelerated biological aging measured through epigenetic clocks. This effect was not substantially changed after adjustment for known confounders.

Vascular-related biological stress, DNA methylation, allostatic load and domain-specific cognition: an integrated machine learning and causal inference approach

BACKGROUND

Vascular disease in aging populations spans a wide range of disorders including strokes, circulation disorders and hypertension. As individuals age, vascular disorders co-occur and hence exert combined effects. In the present study we introduce vascular-related biological stress as a novel biomarker to capture the combined effects of vascular disease burden for more precision in early detection of cognitive changes in aging.

OBJECTIVE

to determine the role of vascular-related biological Stress, DNA methylation-based biological aging and Allostatic Load in the relationship between vascular disorders and major cognitive domains including global cognition, episodic memory and executive function in a representative sample of adults across the age span.

METHODS

The present study included participants from MIDUS refresher sample. Vascular-related biological stress included: BMI, Average blood pressure, sitting, Waist-hip ratio, Blood hemoglobin A1c percent, Blood dehydroepiandrosterone (ng/mL), Blood fasting insulin levels uIU/mL, Blood serum interleukin-8 (pg/mL), Blood serum interleukin-6 (pg/mL), Blood fasting glucose levels mg/dL and Blood fibrinogen (mg/dL). DNA methylation-based biological age measures included GrimAge2 that was constructed based on DNA methylation surrogate markers for select plasma proteins and smoking-pack years. Allostatic load scores were calculated based on biomarkers commonly used in allostatic load calculations: cortisol (urine), norepinephrine (urine), epinephrine (urine), dopamine (urine), glycosylated hemoglobin (HBA1C, blood), low density lipoprotein (LDL, blood), C-reactive protein (CRP, blood) dehydroepiandrosterone sulfate (DHEAS, blood), high-density lipoprotein (HDL, blood) and systolic blood pressure (average, sitting). Least Absolute Shrinkage and Selection Operator (LASSO) and response models (item and continuous) were used to calculate vascular-related biological stress and theta scores. Four-way decomposition modeling approach was used to calculate the natural direct and indirect effects in the relationship between vascular disease and major cognitive domains.

RESULTS

550 individuals with data on biomarkers, DNA methylation and cognition assessments were included in the present study. Median age was 54 (range = 26, 78) with females representing 48% of the sample. In the relationship between vascular disease and cognition, the overall proportions mediated through vascular-related biological stress (item-response scale) were 0.60 (P = 0.01); 1.1 (P = 0.308); 0.53 (P = 0.002) for global cognition, episodic memory and executive function respectively. The overall proportions mediated through DNA methylation (GrimAge2) were 0.27 (P = 0.002); 0.39 (P = 0.102); 0.20, (P = 0.002) for global cognition, episodic memory and executive function respectively and 0.10 (P = 0.08); 0.09 (P = 0.5); 0.07 (P = 0.18) through allostatic load (sum scores).

CONCLUSIONS

Our findings suggest that vascular-related biological stress, DNA methylation and to some extent allostatic load mediate the effects of vascular disease on global cognition and executive function.

Association Between Body Iron Status and Biological Aging

BACKGROUND/OBJECTIVES

Iron is necessary for bodily function, but abnormal levels can increase the risk of chronic diseases. Studies of leukocyte telomere length suggest blood iron levels are positively associated with cellular senescence and accelerated aging. However, associations between blood iron and more robust metrics of biological aging, specifically those based on DNA methylation, have not been examined.

METHODS

In a random sample of women from the Sister Study (n = 1260) with measured serum iron (ferritin, iron, transferrin saturation), we used linear regression models to assess cross-sectional associations between standardized serum iron and three methylation-based biological aging metrics (GrimAgeAccel, PhenoAgeAccel, and DunedinPACE), with and without adjustment for smoking, alcohol, menopause status, education, time since menopause, exercise, and diet.

RESULTS

In adjusted models, a one standard deviation increase in serum ferritin was positively associated with higher standardized levels of DunedinPACE, GrimAgeAccel, and PhenoAgeAccel (DunedinPACE: 0.05, (0.00, 0.10); PhenoAgeAccel: 0.06 (0.00, 0.11); GrimAgeAccel: 0.06 (0.01, 0.11)). In contrast, higher serum iron and transferrin saturation were inversely associated with the biological aging metrics (serum iron, DunedinPACE: -0.02, (-0.07, 0.03); PhenoAgeAccel: -0.04 (-0.10, 0.01); GrimAgeAccel: -0.05 (-0.10, -0.01); transferrin saturation (DunedinPACE: -0.01, (-0.06, 0.05); PhenoAgeAccel: -0.01 (-0.06, 0.05); GrimAgeAccel: -0.05 (-0.10, -0.01))).

CONCLUSIONS

The positive association with ferritin is consistent with the proposed role of oxidative stress in accelerated aging associated with high iron exposure. However, the observed inverse associations with serum iron and transferrin saturation are not consistent with this common explanation, and future studies are needed to examine potential explanations.

The Relationship between Visceral Fat Accumulation and Risk of Cardiometabolic Multimorbidity: The Roles of Accelerated Biological Aging

OBJECTIVES

To investigate the association between visceral fat accumulation and the risk of cardiometabolic multimorbidity (CMM) and the potential roles of accelerated biological aging in this relationship.

METHODS

Using data from the UK Biobank, a nationwide cohort study was conducted using the available baseline body roundness index (BRI) measurement. Biological aging was assessed using the Klemera-Doubal method for biological age and the phenotypic age algorithms. The association between the BRI and CMM was estimated using the Cox proportional hazards regression model, while the roles of biological aging were examined through interaction and mediation analyses.

RESULTS

During a median follow-up of 14.52 years, 6156 cases of CMM were identified. A significant association was observed between the BRI and CMM. The hazard ratio (HR) for CMM was 3.72 (95% confidence interval [CI]: 3.35-4.13) for individuals in the highest quartile compared with those in the lowest quartile of the BRI. More importantly, the BRI (AUC, 0.701; 95% CI, 0.694-0.707) demonstrated superior predictive performance relative to body mass index (AUC, 0.657; 95% CI, 0.650-0.664). Furthermore, the BRI exhibited additive interactions with accelerated biological aging on the risk of CMM, and accelerated biological aging partially mediated the association between the BRI and CMM.

CONCLUSIONS

These findings provide evidence for the application of the BRI as a novel and readily accessible screening tool associated with CMM, suggesting that the effective management of visceral fat and biological aging deceleration may hold promise for reducing CMM risk.

The association between dietary quality and biological aging: two-mediation analysis

AIMS

Previous research has emphasized the firm link between diet and human health. However, the connection between comprehensive dietary patterns and biological aging has not been fully investigated. Our aim was to explore the potential association between dietary quality and delaying aging.

METHODS

A total of 20,763 participants from the National Health and Nutrition Examination Survey were included in this cross-sectional study. The Mediterranean diet score (MDS), dietary approaches to stop hypertension index (DASHI), and healthy eating index 2020 (HEI2020) were utilized to assess dietary quality. Biological age was determined using the Klemera-Doubal method (KDM) biological age and phenotypic age (Levine's), with the difference between biological age and chronological age representing aging acceleration. Independent relationships between dietary quality and biological aging were analyzed using weighted adjusted linear and logistic regression. Nonlinear trends and robustness of conclusions were examined. A secondary objective was to examine the role of Klotho and γ-glutamyltransferase (GGT) in mediation analyses.

RESULTS

Dietary quality exhibited a negative association with biological aging, as evidenced by the interplay between three dietary patterns and two aging measures (The β of the linear regressions were all < 0). Restricted cubic splines confirmed the linear relationship, while subgroup interactions bolstered the stability of the results. Mediation analysis indicated that klotho and GGT partially mediated the association between dietary quality and biological aging (combined proportion mediation: 4.1-8.0%).

CONCLUSION

Dietary quality is closely associated with biological aging, with anti-aging proteins and oxidative stress potentially serving as underlying mediation mechanisms.

Evaluating Risk Factors for Early-Onset Colorectal Cancer in a Large, Prospective Cohort

BACKGROUND

Despite the worrisome rise of early-onset colorectal cancer (EOCRC), risk factors have not been definitively established. We use a large, granular database to evaluate risk factors for EOCRC, investigate differences in associations with EOCRC and later-onset CRC (LOCRC), and compare metrics of accelerated aging, a hypothesized driver of EOCRC.

METHODS

This was a case-control analysis within the UK Biobank. Risk factors for each cancer were identified and compared, including aging measures (chronological age, telomere length, PhenoAge, and homeostatic dysregulation).

RESULTS

A total of 31,164 persons were matched. We found an increased risk of EOCRC with PRS (OR 1.53; 95% CI 1.19-1.97; p < 0.001). LOCRC was associated with increasing PRS (OR 1.48; 95% CI 1.44 - 1.53; p < 0.001), increasing waist-to-hip ratio (OR 5.81; 95% CI 3.25 - 10.38; p < 0.001), family history of CRC (OR 1.27; 95% CI 1.16 - 1.40; p < 0.001), and history of smoking (OR 1.11; 95% CI 1.03 - 1.19; p = 0.01). Male sex and prior CRC screening were associated with reduced risk of LOCRC. The inclusion of PhenoAge as the measure of aging demonstrated the best model fit for both EOCRC and LOCRC. For each year that PhenoAge exceeded chronological age, the odds of EOCRC increased by 7%, while odds of LOCRC only increased by 1%.

CONCLUSIONS

Within this study, we find that genetic risk variants are a significant driver of EOCRC risk. Accelerated aging appears to be associated with increased risk of both EOCRC and LOCRC, and measures such as PhenoAge warrant continued study.

Complementary value of molecular, phenotypic, and functional aging biomarkers in dementia prediction

DNA methylation age (MA), brain age (BA), and frailty index (FI) are putative aging biomarkers linked to dementia risk. We investigated their relationship and combined potential for prediction of cognitive impairment and future dementia risk using the ADNI database. Of several MA algorithms, DunedinPACE and GrimAge2, associated with memory, were combined in a composite MA alongside BA and a data-driven FI in predictive analyses. Pairwise correlations between age- and sex-adjusted measures for MA (aMA), aBA, and aFI were low. FI outperformed BA and MA in all diagnostic tasks. A model including age, sex, and aFI achieved an area under the curve (AUC) of 0.94 for differentiating cognitively normal controls (CN) from dementia patients in a held-out test set. When combined with clinical biomarkers (apolipoprotein E ε4 allele count, memory, executive function), a model including aBA and aFI predicted 5-year dementia risk among MCI patients with an out-of-sample AUC of 0.88. In the prognostic model, BA and FI offered complementary value (both βs 0.50). The tested MAs did not improve predictions. Results were consistent across FI algorithms, with data-driven health deficit selection yielding the best performance. FI had a stronger adverse effect on prognosis in males, while BA's impact was greater in females. Our findings highlight the complementary value of BA and FI in dementia prediction. The results support a multidimensional view of dementia, including an intertwined relationship between the biomarkers, sex, and prognosis. The tested MA's limited contribution suggests caution in their use for individual risk assessment of dementia.

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.

Associations of combined accelerated biological aging and genetic susceptibility with incidence of heart failure in a population-based cohort study

The global aging population raises concerns about heart failure (HF), yet its association with accelerated biological age (BA) remains inadequately understood. We aimed to examine the longitudinal association between BA acceleration and incident HF risk, assess its modifying effect on genetic susceptibility, and how much BA acceleration mediates the impact of modifiable health behaviors on incident HF. We analyzed 274,608 UK Biobank participants without HF at baseline. Two BA accelerations (Biological Age Acceleration [BioAgeAccel] and Phenotypic Age Acceleration [PhenoAgeAccel]) were calculated by regressing clinical biomarker-based BA on chronological age, with higher values indicating accelerated aging. Health behavior scores were computed based on diet, physical activity, tobacco/nicotine, sleep, and BMI. Genetic risk scores (GRS) were calculated by 12 HF-associated loci. During a median follow-up of 13.5 years, 8915 HF cases were documented. Each standard deviation increase in BioAgeAccel and PhenoAgeAccel was associated with an increased incident HF risk, yielding HRs of 1.45 (95% CI, 1.42-1.48) and 1.42 (95% CI, 1.40-1.45), respectively. Participants with high GRS and highest quartile of BioAgeAccel had an HR of 2.69 (95% CI, 2.42-2.99), and for PhenoAgeAccel, an HR of 2.83 (95% CI, 2.52-3.18), compared to those with low GRS, and lowest quartile. Additive interactions were observed between GRS and BA accelerations. Health behaviors reduced HF risk, with 21.1% (95% CI, 19.5%-22.8%) mediated by decreased BioAgeAccel and 20.9% (95% CI, 19.5%-22.6%) by decreased PhenoAgeAccel. Accelerated BA is associated with an increased incident HF risk, with an additive effect when combined with genetic susceptibility. Maintaining health behaviors may help mitigate BA aging and reduce HF risk.

Dynamic neurocognitive adaptation: A follow-up exposome investigation in aging

INTRODUCTION

Forty-five percent of Alzheimer's disease (AD) cases may be preventable. Validated tools for measuring environmental factors, with precision equal to that of current biological and genetic assessment tools, are currently lacking.

METHODS

We used the dynamic Neurocognitive Adaptation (dNA) scale, our validated tool to explore protective factors in AD, in 410 older adult participants (50% women). The dNA asks participants to recall cognitive, creative, physical, and social activities that they engaged in at seven different time periods in their lives. We examined associations among engagement in these domains using distance correlations and tested differences in domain engagement over time with repeated-measures analysis of variance. We calculated within-subjects comparisons for time and all interactions among time, sex, and education. We examined between-subjects factors for sex, education, and their interaction. From these models, we constructed visualizations of estimated marginal means against time to assess potential patterns of interest.

RESULTS

Physical and creative domain engagements were significantly correlated (p < 0.001) in the full sample, and social engagement correlated with physical (p < 0.001) and creative (p = 0.047) domains among females. Cognitive engagement increased over time (p < 0.001) for the full sample, while physical and creative engagement increased from childhood to adolescence, then decreased over time (p < 0.001). In contrast, social engagement increased from childhood to adolescence, declined through the senior years, and then sharply increased in old age. Overall, women showed higher cognitive engagement (p = 0.024) and men showed higher physical engagement (p = 0.011). Education was positively related to higher scores in all domains.

DISCUSSION

Our scale provides new insight into the correlation of environmental factors with education, suggests areas for lifestyle intervention, and highlights the importance of sex differences and middle age as a potential transition stage.

Highlights

Physical activity decreases and cognitive activity increases through time.Higher involvement in physical activities is correlated with creative and social dimensions.Men are more involved in physical and women in cognitive activities.Higher education is associated with higher involvement in all the dimensions explored.

Associations of clinical parameter-based accelerated aging, genetic predisposition with risk of chronic kidney disease and associated life expectancy: A prospective cohort study

Little evidence exists regarding the associations between clinical parameter-based biological aging and the incidence and outcome of chronic kidney disease (CKD). Thus, we aimed to assess the associations between biological aging, genetic risk, and the risk of CKD, as well as investigate the impact of accelerated biological aging on life expectancy. 281,363 participants free of kidney diseases from the UK Biobank were included in this prospective study. Biological age was measured from clinical traits using the KDM-BA and PhenoAge algorithms, and the discrepancies from chronological age were defined as biological age accelerations. A polygenic score was calculated to indicate the genetic predisposition of the estimated glomerular filtration rate (eGFR). A cause-specific competing risk model was used to estimate hazard ratios (HRs) and the corresponding confidence intervals (CIs) of incident CKD. We found that individuals with more pronounced accelerations in biological age exhibited an elevated risk of developing CKD (HRQuartile 4 vs. Quartile 1, 1.90; 95% CI, 1.77-2.05 for KDM-BA acceleration and HRQuartile 4 vs. Quartile 1, 2.79; 95% CI, 2.58-3.01 for PhenoAge acceleration), with nonlinear relationships. Notably, there were positive additive interactions between biological aging and genetic risk on CKD risk. Among the CKD population, accelerated biological aging was associated with a further decline in life expectancy. Advanced biological aging may potentially increase the vulnerability to developing CKD in individuals aged midlife and beyond, particularly among those with high genetic risk for abnormal kidney function, and could reduce the life expectancy of CKD patients.

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

BACKGROUND

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

METHODS

Three waves of clinical indicators (2004/05-2012/13) drawn from the English Longitudinal Study of Ageing (ages 50-100 years) were used to estimate PA, which was internally validated by confirming associations with incident chronic conditions, functional limitations and memory impairment after adjustment for chronological age and sex. Joint models were used to construct PA trajectories in 8891 English Longitudinal Study of Ageing participants to examine sex and educational disparities in PA.

FINDINGS

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

INTERPRETATION

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

Biological age construction for prediction of mortality in the Chinese population

Efforts to increase health span bring to light the necessity of constructing biological age (BA) for measuring aging. However, universally adaptive BA needs further investigation, especially among the Chinese population. Therefore, this study aimed to construct BA using routine clinical markers for the Chinese population. Included were two Chinese prospective cohorts, the Kailuan Study I (n = 83,571) for developing BA and the Kailuan Study II (n = 21,229) for validation. Leveraging baseline age-related clinical markers, we developed phenotypic BA (Pheno-Age) using Levine's methods and Klemera-Doubal BA (KDM-Age) using KDM methods and calculated the residuals of regressions of the two BA measured at baseline and during follow-up on chronological age, namely BA acceleration. The predictive performance of baseline, cumulative average, and updated BAs on mortality was evaluated using the area under the curve (AUC) and calibration plots. COX regressions were used to estimate hazard rations (HRs) and 95% confidence intervals (CIs) for the BA acceleration and risk of mortality. During 1,443,857 person-years of follow-up, 12,679 deaths were recorded in the two cohorts. Baseline Pheno-Age and KDM-Age produced desirable predictions for mortality in both the Kailuan Study I (AUC, 0.810 and 0.806, respectively) and the Kailuan Study II (AUC, 0.867 and 0.819, respectively). Calibration plots showed reasonable agreement between predicted and observed probabilities. The pooled multivariable-adjusted HRs (95% CIs) for per standard deviation increment of baseline Pheno-Age acceleration and mortality was 1.24 (1.18, 1.30), and for KDM-Age acceleration was 1.16 (1.10, 1.21). Similar predictive performance and association were observed when using cumulative average or updated BA. The associations were stronger in the adults aged ≤60 years, smokers, and drinkers, relative to their counterparts (P for interaction <0.05 for all). Pheno-Age and KDM-Age, developed and validated in the two large prospective cohorts, could predict mortality, independent of chronological age and other potential confounders, in Chinese populations.

Predicting cardiovascular morbidity and mortality with SCORE2 (OP) and Framingham risk estimates in combination with indicators of biological ageing

BACKGROUND AND OBJECTIVE

Previous research assessing whether biological ageing (BA) indicators can enhance the risk assessment of cardiovascular disease (CVD) outcomes beyond established CVD risk indicators, such as Framingham Risk Score (FRS) and Systematic Coronary Risk Evaluation (SCORE2)/SCORE2-Older Persons (OP), is scarce. We explored whether BA indicators, namely the Rockwood Frailty Index (FI) and leukocyte telomere length (TL), improve predictive accuracy of CVD outcomes beyond the traditional CVD risk indicators in general population of middle-aged and older CVD-free individuals.

METHODS

Data included 14 118 individuals from three population-based cohorts: TwinGene, Health 2000 (H2000), and the Helsinki Birth Cohort Study, grouped by baseline age (<70, 70+). The outcomes were incident CVD and CVD mortality with 10-year follow-up. Risk estimations were assessed using Cox regression and predictive accuracies with Harrell's C-index.

RESULTS

Across the three study cohorts and age groups: (i) a higher FI, but not TL, was associated with a higher occurrence of incident CVD (P < .05), (ii) also when considering simultaneously the baseline CVD risk according to FRS or SCORE2/SCORE2-OP (P < .05) (iii) adding FI to the FRS or SCORE2/SCORE2-OP model improved the predictive accuracy of incident CVD. Similar findings were seen for CVD mortality, but less consistently across the cohorts.

CONCLUSIONS

We show robust evidence that a higher FI value at baseline is associated with an increased risk of incident CVD in middle-aged and older CVD-free individuals, also when simultaneously considering the risk according to the FRS or SCORE2/SCORE2-OP. The FI improved the predictive accuracy of CVD outcomes beyond the traditional CVD risk indicators and demonstrated satisfactory predictive accuracy even when used independently.

Healthy dietary patterns, biological aging, and kidney stones: evidence from NHANES 2007-2018

Background

This study aims to investigate the comprehensive association between healthy dietary patterns, biological aging, and kidney stones in a large population-based cohort.

Methods

We analyzed data from 6 cycles of NHANES surveys from 2007 to 2018 and included a total of 26,755 participants. The association was examined using logistic regression, restricted cubic splines, and a mediation model. Machine learning with Shapley Additive Explanations (SHAP) was used to determine the relative importance of dietary factors. Sensitivity analysis was conducted to validate the stability of the results.

Results

A higher healthy dietary score was significantly associated with a reduced risk of kidney stone prevalence, as indicated by the Alternative Healthy Eating Index (AHEI) (OR = 0.76, 95% CI 0.69-0.84), the Dietary Approaches to Stop Hypertension Index (DASHI) (OR = 0.67, 95% CI 0.58-0.77), the Healthy Eating Index 2020 (HEI-2020) (OR = 0.80, 95% CI 0.72-0.89), and the Mediterranean Diet Index (MEDI) (OR = 0.81, 95% CI 0.73-0.89). Conversely, higher aging indicators were associated with an increased risk of kidney stones, including the following: Klemera-Doubal Method Age (KDMAge) (OR = 2.40, 95% CI 1.70-3.37) and Phenotypic Age (PhenoAge) (OR = 2.36, 95% CI 1.75-3.19). Mediation analyses suggested that aging indicators significantly mediated the relationship between healthy dietary patterns and kidney stones. Machine learning with SHAP revealed the relative importance of dietary patterns and specific dietary components in this association. The sensitivity analysis was largely consistent with the primary analyses.

Conclusion

These findings provide valuable insights into the complex interplay between dietary patterns, biological aging, and the risk of kidney stone. Promoting healthy dietary patterns may be an effective strategy for kidney stone prevention, potentially through the modulation of biological aging processes.

Elevated urinary phytoestrogens are associated with delayed biological aging: a cross-sectional analysis of NHANES data

Dietary phytoestrogens have been suggested to provide protection against numerous age-related diseases. However, their effects on biological aging remain unclear. In this study, we cross-sectionally investigated the relationship between urinary phytoestrogen levels and indicators of biological aging using data from 7,981 adults who participated in the National Health and Nutrition Examination Survey 1999-2010. Urinary concentrations of six phytoestrogens, including four isoflavones and two enterolignans, were measured using high-performance liquid chromatography (HPLC)-tandem mass spectrometry (MS) or HPLC-atmospheric pressure photoionization-tandem MS, and standardized using urinary creatinine. Three indicators of biological age (BA), namely the Klemera-Doubal method biological age (KDM-BA), phenotypic age (PA), and homeostatic dysregulation (HD), were derived from 12 clinical biomarkers, advanced-BAs were calculated to quantify the differences between individuals' BAs and chronological age, and individuals with all positive advanced-BAs were defined as accelerated-aging. Weighted linear regression analysis showed that after adjusting for demographic and lifestyle factors and history of chronic diseases, elevated urinary total phytoestrogen and enterolignans were significantly associated with less advanced-KDM, advanced-PA, and advanced-HD, whereas elevated urinary isoflavones was significantly associated with less advanced-KDM and advanced-PA but not with advanced-HD. Weighted logistic regression showed that higher urinary levels of total phytoestrogen (highest Q4 vs. lowest Q1: OR = 0.60, 95%CI: 0.44, 0.80; P-trend = 0.002) and enterolignans (Q4 vs. Q1: OR = 0.59, 95%CI: 0.45, 0.76; P-trend < 0.001) were significantly associated with lower odds of accelerated-aging, but this was not significant for isoflavones (Q4 vs. Q1: OR = 0.78, 95%CI: 0.60, 1.08; P-trend = 0.05). Subgroup analyses showed that negative associations were attenuated in non-overweight/obese participants and current cigarette smokers. In conclusion, higher levels of urinary phytoestrogens are related to markers of slower biological aging, suggesting an anti-aging effect of higher dietary phytoestrogen consumption, which warrants further investigations in longitudinal or interventional settings.

Lifestyles and their relative contribution to biological aging across multiple-organ systems: Change analysis from the China Multi-Ethnic Cohort study

Background

Biological aging exhibits heterogeneity across multi-organ systems. However, it remains unclear how is lifestyle associated with overall and organ-specific aging and which factors contribute most in Southwest China.

Methods

This study involved 8396 participants who completed two surveys from the China Multi-Ethnic Cohort (CMEC) study. The healthy lifestyle index (HLI) was developed using five lifestyle factors: smoking, alcohol, diet, exercise, and sleep. The comprehensive and organ-specific biological ages (BAs) were calculated using the Klemera-Doubal method based on longitudinal clinical laboratory measurements, and validation were conducted to select BA reflecting related diseases. Fixed effects model was used to examine the associations between HLI or its components and the acceleration of validated BAs. We further evaluated the relative contribution of lifestyle components to comprehension and organ systems BAs using quantile G-computation.

Results

About two-thirds of participants changed HLI scores between surveys. After validation, three organ-specific BAs (the cardiopulmonary, metabolic, and liver BAs) were identified as reflective of specific diseases and included in further analyses with the comprehensive BA. The health alterations in HLI showed a protective association with the acceleration of all BAs, with a mean shift of -0.19 (95% CI -0.34, -0.03) in the comprehensive BA acceleration. Diet and smoking were the major contributors to overall negative associations of five lifestyle factors, with the comprehensive BA and metabolic BA accounting for 24% and 55% respectively.

Conclusions

Healthy lifestyle changes were inversely related to comprehensive and organ-specific biological aging in Southwest China, with diet and smoking contributing most to comprehensive and metabolic BA separately. Our findings highlight the potential of lifestyle interventions to decelerate aging and identify intervention targets to limit organ-specific aging in less-developed regions.

Funding

This work was primarily supported by the National Natural Science Foundation of China (Grant No. 82273740) and Sichuan Science and Technology Program (Natural Science Foundation of Sichuan Province, Grant No. 2024NSFSC0552). The CMEC study was funded by the National Key Research and Development Program of China (Grant No. 2017YFC0907305, 2017YFC0907300). The sponsors had no role in the design, analysis, interpretation, or writing of this article.

Protein epigenetic scores and overall mortality in the longitudinal Swedish Adoption/Twin Study of Aging (SATSA)

INTRODUCTION

DNA methylation (DNAm) has a functional role in gene regulation, and it has been used to estimate various human characteristics. Variation in DNAm is associated with aging and variability of the proteome. Therefore, understanding the relationship between blood circulating proteins, aging, and mortality is critical to identify disease-causing pathways. We aimed to estimate the association between protein epigenetic scores (EpiScores) and overall mortality in the Swedish Adoption/Twin Study of Aging (SATSA).

METHODS

We included information from 374 individuals collected between 1992 and 2014. Our exposures were 109 protein EpiScores generated using DNAm data and prediction models by the MethylDetectR shiny app. All-cause mortality was the outcome of interest. To estimate the protein EpiScores associations with all-cause mortality, we fitted Cox proportional hazard models adjusted for age, sex, education, smoking status, body mass index, and occupation. We also conducted co-twin control analyses to control for shared familial factors.

RESULTS

The mean age of participants at the first assessment was 68.6 years. In total, nine protein EpiScores (e.g., Stanniocalcin 1) were associated with a higher risk for all-cause mortality. In contrast, five protein EpiScores (e.g., Prolyl endopeptidase) were associated with a lower risk for all-cause mortality.

CONCLUSION

The protein EpiScores associated with an increased mortality risk represent proteins involved in metabolic functions, immune response, and inflammation. Conversely, those associated with a lower risk represent proteins involved in neurogenesis and cellular functions. Overall, it is possible to predict protein levels from DNAm data that could have clinical relevance.

Association of phenotypic age acceleration with all-cause and cause-specific mortality among U.S. cancer survivors: a retrospective cohort study

BACKGROUND

Cancer survivors may experience accelerated biological aging, increasing their risk of mortality. However, the association between phenotypic age acceleration (PAA) and mortality among cancer survivors remains unclear. This study aimed to evaluate the relationship between PAA and all-cause mortality, cancer-specific mortality, and non-cancer mortality among adult cancer survivors in the United States.

METHODS

We utilized data from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018, including 2,643 (unweighted) cancer patients aged ≥ 20 years. Phenotypic age was calculated using ten physiological biomarkers, and the residuals from regressing phenotypic age on chronological age (age acceleration residuals, AAR) were used to determine PAA status. Participants were divided into PAA and without PAA groups based on the sign of the residuals. Weighted Cox proportional hazards regression models were used to assess the association between PAA and mortality, adjusting for demographic characteristics, lifestyle factors, and comorbidities. Restricted cubic spline (RCS) models were employed to explore the dose-response relationship between AAR and mortality.

RESULTS

Over a median follow-up of 9.16 years, 991 (unweighted) participants died. After adjusting for multiple covariates, PAA was significantly associated with increased risks of all-cause mortality (HR = 2.07; 95% CI: 1.69-2.54), cancer-specific mortality (HR = 2.15; 95% CI: 1.52-3.04), and non-cancer mortality (HR = 2.06; 95% CI: 1.66-2.57). Each one-unit increase in AAR was associated with a 4% increase in the risk of all-cause, cancer-specific, and non-cancer mortality (HR = 1.04; 95% CI: 1.03-1.05). RCS models indicated a linear dose-response relationship between AAR and mortality.

CONCLUSIONS

Among U.S. adult cancer survivors, PAA is significantly associated with all-cause, cancer-specific, and non-cancer mortality. PAA may serve as an important biomarker for predicting prognosis in cancer survivors.

Biological aging of different blood cell types

Biological age (BA) captures detrimental age-related changes. The best-known and most-used BA indicators include DNA methylation-based epigenetic clocks and telomere length (TL). The most common biological sample material for epidemiological aging studies, whole blood, is composed of different cell types. We aimed to compare differences in BAs between blood cell types and assessed the BA indicators' cell type-specific associations with chronological age (CA). An analysis of DNA methylation-based BA indicators, including TL, methylation level at cg16867657 in ELOVL2, as well as the Hannum, Horvath, DNAmPhenoAge, and DunedinPACE epigenetic clocks, was performed on 428 biological samples of 12 blood cell types. BA values were different in the majority of the pairwise comparisons between cell types, as well as in comparison to whole blood (p < 0.05). DNAmPhenoAge showed the largest cell type differences, up to 44.5 years and DNA methylation-based TL showed the lowest differences. T cells generally had the "youngest" BA values, with differences across subsets, whereas monocytes had the "oldest" values. All BA indicators, except DunedinPACE, strongly correlated with CA within a cell type. Some differences such as DNAmPhenoAge-difference between naïve CD4 + T cells and monocytes were constant regardless of the blood donor's CA (range 20-80 years), while for DunedinPACE they were not. In conclusion, DNA methylation-based indicators of BA exhibit cell type-specific characteristics. Our results have implications for understanding the molecular mechanisms underlying epigenetic clocks and underscore the importance of considering cell composition when utilizing them as indicators for the success of aging interventions.

Elevated Circulating Sclerostin Levels in Frail Older Adults: Implications beyond Bone Health

BACKGRUOUND

Sclerostin, initially recognized for its pivotal role in bone metabolism, has gained attention for its multifaceted impact on overall human health. However, its influence on frailty-a condition that best reflects biological age-has not been thoroughly investigated.

METHODS

We collected blood samples from 244 older adults who underwent comprehensive geriatric assessments. Sclerostin levels were quantified using an enzyme-linked immunosorbent assay. Frailty was assessed using two validated approaches: the phenotypic model by Fried and the deficit accumulation frailty index (FI) by Rockwood.

RESULTS

After controlling for sex, age, and body mass index, we found that serum sclerostin levels were significantly elevated in frail individuals compared to their robust counterparts (P<0.001). There was a positive correlation between serum sclerostin concentrations and the FI (P<0.001). Each standard deviation increase in serum sclerostin was associated with an odds ratio of 1.87 for frailty (P=0.003). Moreover, participants in the highest quartile of sclerostin levels had a significantly higher FI and a 9.91-fold increased odds of frailty compared to those in the lowest quartile (P=0.003 and P=0.039, respectively).

CONCLUSION

These findings, which for the first time explore the association between circulating sclerostin levels and frailty, have significant clinical implications, positioning sclerostin as one of potential blood-based biomarkers for frailty that captures the comprehensive physical, mental, and social aspects of the elderly, extending beyond its traditional role in bone metabolism.

Centenarians-the way to healthy vascular ageing and longevity: a review from VascAgeNet

The prevalence of centenarians, people who lived 100 years and longer, is steadily growing in the last decades. This exceptional longevity is based on multifaceted processes influenced by a combination of intrinsic and extrinsic factors such as sex, (epi-)genetic factors, gut microbiota, cellular metabolism, exposure to oxidative stress, immune status, cardiovascular risk factors, environmental factors, and lifestyle behavior. Epidemiologically, the incidence rate of cardiovascular diseases is reduced in healthy centenarians along with late onset of age-related diseases compared with the general aged population. Understanding the mechanisms that affect vascular ageing in centenarians and the underlying factors could offer valuable insights for developing strategies to improve overall healthy life span in the elderly. This review discusses these key factors influencing vascular ageing and how their modulation could foster healthy longevity.

Epigenetic age acceleration in hematopoietic stem cell transplantation

Not available.

Associations between inflammation and striatal dopamine D2-receptor availability in aging

BACKGROUND

Normal brain aging is associated with dopamine decline, which has been linked to age-related cognitive decline. Factors underlying individual differences in dopamine integrity at older ages remain, however, unclear. Here we aimed at investigating: (i) whether inflammation is associated with levels and 5-year changes of in vivo dopamine D2-receptor (DRD2) availability, (ii) if DRD2-inflammation associations differ between men and women, and (iii) whether inflammation and cerebral small-vessel disease (white-matter lesions) serve as two independent predictors of DRD2 availability.

METHODS

Analyses were performed in a sample of healthy adults > 60 years assessed at two measurement occasions separated by 5 years. At both occasions, DRD2 availability was estimated by 11C-raclopride PET, and white-matter lesions by MRI. Inflammation was assessed by two C-reactive protein-associated DNA methylation scores at study baseline.

RESULTS

Individuals with higher DNA methylation scores at baseline showed reduced striatal DRD2 availability. An interaction was found between DNA methylation scores and sex in relation to striatal DRD2 availability, such that associations were found in men but not in women. DNA methylation scores at study entrance were not significantly associated with 5-year striatal DRD2 decline rates. No significant association was found between DNA methylation scores and white-matter lesions, but higher scores as well as higher lesion burden were independently associated with reduced striatal DRD2 availability in men.

CONCLUSIONS

These findings suggest negative associations between one proxy of inflammation and DRD2 availability in older adults, selectively for men who had higher DNA methylation scores. Future studies should investigate other inflammatory markers in relation to dopamine integrity.

Epigenetic Mechanisms Underlying Sex Differences in Neurodegenerative Diseases

Neurodegenerative diseases are characterized by profound differences between females and males in terms of incidence, clinical presentation, and disease progression. Furthermore, there is evidence suggesting that differences in sensitivity to medical treatments may exist between the two sexes. Although the role of sex hormones and sex chromosomes in driving differential susceptibility to these diseases is well-established, the molecular alterations underlying these differences remain poorly understood. Epigenetic mechanisms, including DNA methylation, histone tail modifications, and the activity of non-coding RNAs, are strongly implicated in the pathogenesis of neurodegenerative diseases. While it is known that epigenetic mechanisms play a crucial role in sexual differentiation and that distinct epigenetic patterns characterize females and males, sex-specific epigenetic patterns have been largely overlooked in studies aiming to identify epigenetic alterations associated with neurodegenerative diseases. This review aims to provide an overview of sex differences in epigenetic mechanisms, the role of sex-specific epigenetic processes in the central nervous system, and the main evidence of sex-specific epigenetic alterations in three neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis. Understanding the sex-related differences of these diseases is essential for developing personalized treatments and interventions that account for the unique epigenetic landscapes of each sex.

Dietary carotenoid intakes and biological aging among US adults, NHANES 1999-2018

BACKGROUND

Carotenoids 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.

METHODS

This 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.

RESULTS

Associations 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.

CONCLUSIONS

Increased dietary intakes of various carotenoids were associated with lower biological aging indices, which was possibly and mainly driven by lutein/zeaxanthin and β-carotene.

Marital and living status and biological ageing trajectories: a longitudinal cohort study with a 20-year follow-up

Biomarkers of ageing (BA) can predict health risks beyond chronological age, but little is known about how marital/living status affects longitudinal changes in BA. We examined the association between marital/living status and BA over time using the-Swedish-Adoption/Twin-Study-of-Aging (SATSA) cohort. Four BAs were analyzed: telomere length (TL) (638 individuals; 1603 measurements), DNAmAge (535 individuals; 1392 measurements), cognition (823 individuals; 3218 measurements), and frailty index (FI) (1828 individuals; 9502 measurements). Individuals were born between 1900 and 1948, and data on marital/living status, BAs, and covariates were collected through nine waves of questionnaires and in-person testing from 1986 to 2014. Mixed linear regression with random effects at twin-pair and individual levels were used to assess BA changes for constant marital/living status. Conditional generalized estimating equation assessed within-individual BA changes for varying marital/living status. Results showed that individuals who were consistently unmarried/non-cohabiting (β = 0.291, 95%CI = 0.189-0.393) or living alone (β = 0.203, 95%CI = 0.090-0.316) were more frail, and experienced accelerated frailty (p-for-interaction with age < 0.001 for marital status; p-for-interaction = 0.002 for living status) and cognitive decline (p-for-interaction < 0.001), compared to those married/cohabiting or living with someone Among individuals whose marital/living status changed, frailty was higher when living alone (β = 0.089, 95%CI = 0.017-0.162) and frailty accelerated when they became unmarried/non-cohabiting or were living alone (p-for-interaction < 0.001). Cognitive decline also accelerated when living alone (p-for-interaction = 0.020). No associations were observed for TL and DNAmAge. In conclusion, being unmarried/non-cohabiting or living alone from mid-to-old age is linked to accelerated cognitive decline and frailty. These findings highlight the potential importance of social support networks and living arrangements for healthy ageing.

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

Background

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

Methods

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

Findings

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

Interpretation

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

Negotiating a physically active life in tune with ageing: a grounded theory study of older persons' experiences of participating in high-intensity interval training

BACKGROUND

Physical activity and exercise are promoted worldwide as effective interventions for healthy ageing. Various exercise initiatives have been developed and evaluated for their efficacy and effectiveness among older populations. However, a deeper understanding of participants' experiences with these initiatives is crucial to foster long-term activity and exercise among older persons.

METHODS

A constructivist grounded theory study was conducted to explore the experiences of older persons participating in a supervised group supramaximal high-intensity training (HIT) programme. Four focus groups were held, involving 28 persons aged 65 to 78. The focus groups were analysed inductively, followed by an iterative process of abstraction, abduction, and theory generation using a constant comparative method. A conceptual framework comprising three theoretical concepts-stereotype embodiment, ageist practices, and self-efficacy-was employed during the abductive phase as an analytical lens.

RESULTS

The core category of our grounded theory, Negotiating a physically active life in tune with ageing, encapsulates the complex processes and actions influencing older persons as they engage in physical activities in their daily lives and in relation to HIT. This core category was created from the conceptual framework and the four categories: Grit in the moment and overall life, Empowered by the training group, Navigating one's physically active self, and Committing to exercise for duty and pleasure. Participants reported feeling invigorated by the exercise, enjoying the challenge, and valuing the group setup for its social connectedness and structure. The generated theory illustrates how participants' engagement with physical activity and exercise is shaped by various perspectives accumulated over their lifespan. The findings provide a plausible explanation of how participation in HIT groups can challenge negative age stereotypes and ageist practices while enhancing self-efficacy for high-intensity exercise.

CONCLUSIONS

Our grounded theory underscores that physical activity and exercise should be regarded as multifaceted processes, which must be considered when promoting physical activity initiatives for older persons. By considering the older person and societal norms and values, we can gather knowledge to design physical exercise interventions that are not only effective but also enjoyable and capable of transforming how individuals perceive themselves as exercising persons.

Epigenetic Clocks: Beyond Biological Age, Using the Past to Predict the Present and Future

Predicting health trajectories and accurately measuring aging processes across the human lifespan remain profound scientific challenges. Assessing the effectiveness and impact of interventions targeting aging is even more elusive, largely due to the intricate, multidimensional nature of aging-a process that defies simple quantification. Traditional biomarkers offer only partial perspectives, capturing limited aspects of the aging landscape. Yet, over the past decade, groundbreaking advancements have emerged. Epigenetic clocks, derived from DNA methylation patterns, have established themselves as powerful aging biomarkers, capable of estimating biological age and assessing aging rates across diverse tissues with remarkable precision. These clocks provide predictive insights into mortality and age-related disease risks, effectively distinguishing biological age from chronological age and illuminating enduring questions in gerontology. Despite significant progress in epigenetic clock development, substantial challenges remain, underscoring the need for continued investigation to fully unlock their potential in the science of aging.

A prospective study of associations between accelerated biological aging and twenty musculoskeletal disorders

BACKGROUND

Musculoskeletal disorders pose major public health challenges, and accelerated biological aging may increase their risk. This study investigates the association between biological aging and musculoskeletal disorders, with a focus on sex-related differences.

METHODS

We analyzed data from 172,332 UK Biobank participants (mean age of 56.03 ± 8.10 years). Biological age was calculated using the KDM-BA and PhenoAge algorithms based on blood biomarkers. Musculoskeletal disorders were diagnosed using the ICD-10 criteria, with sample sizes ranging from 1,182 to 23,668. Logistic regression assessed cross-sectional associations between age acceleration (AA) metrics and musculoskeletal disorders. Accelerated Failure Time (AFT) model was used for survival analysis to evaluate the relationships between AAs and musculoskeletal disorders onset. Models were adjusted for demographic, lifestyle, and socio-economic covariates. The threshold of P-values were set by the Holm-Bonferroni correction.

RESULTS

Cross-sectional analyses reveal significant associations between AAs and fourteen musculoskeletal disorders. Survival analyses indicate that AAs significantly accelerate the onset of nine musculoskeletal disorders, including inflammatory polyarthropathies (RTKDM-BA = 0.993; RTPhenoAge = 0.983), systemic connective tissue disorders (RTKDM-BA = 0.987; RTPhenoAge = 0.980), spondylopathies (RTPhenoAge= 0.994), disorders of bone density and structure (RTPhenoAge= 0.991), gout (RTPhenoAge= 0.968), arthritis (RTPhenoAge= 0.991), pain in joint (RTPhenoAge= 0.989), low back pain (RTPhenoAge= 0.986), and osteoporosis (RTPhenoAge= 0.994). Sensitivity analyses are consistent with the primary findings. Sex-specific variations are observed, with AAs accelerating spondylopathies, arthritis, and low back pain in females, while osteoporosis is accelerated in males.

CONCLUSION

Accelerated biological aging is significantly associated with the incidence of several musculoskeletal disorders. These insights highlight the importance of biological age assessments in gauging musculoskeletal disorder risk, aiding early detection, prevention, and management.

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

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

Self-rated health, epigenetic ageing, and long-term mortality in older Australians

Self-rated health (SRH) is a subjective indicator of overall health based on a single questionnaire item. Previous evidence found that it is a strong predictor of mortality, although the underlying mechanism is poorly understood. Epigenetic age is an objective, emerging biomarker of health, estimated using DNA methylation data at hundreds of sites across the genome. This study aimed to assess the overlap and interaction between SRH and epigenetic ageing in predicting mortality risk. We used DNA methylation data from 1059 participants in the Melbourne Collaborative Cohort Study (mean age: 69 years) to calculate three age-adjusted measures of epigenetic ageing: GrimAge, PhenoAge, and DunedinPACE. SRH was assessed using a five-category questionnaire item ("excellent, very good, good, fair, poor"). Cox models were used to assess the associations of SRH, epigenetic ageing, and their interaction, with all-cause mortality over up to 17 years of follow-up (Ndeaths = 345). The association of SRH with mortality per category increase was HR = 1.29; 95%CI: 1.14-1.46. The association was slightly attenuated after adjusting for all three epigenetic ageing measures (HR = 1.25, 95%CI: 1.10-1.41). A strong gradient was observed in the association of GrimAge (Pinteraction = 0.006) and DunedinPACE (Pinteraction = 0.002) with mortality across worsening SRH strata. For example, the association between DunedinPACE and mortality in participants with "excellent" SRH was HR = 1.02, 95%CI: 0.73-1.43 and for "fair/poor" HR = 1.72, 95%CI: 1.35-2.20. SRH and epigenetic ageing were synergistic risk factors of mortality in our study. These findings suggest that consideration of subjective and objective factors may improve general health assessment, which has implications for the ongoing development of molecular markers of ageing.

Invariances in relations between aging, exposure to external hazards, and mortality reflected in life table aging rate (LAR) patterns examined through the lens of generalized Gompertz-Makeham law

According to the Gompertz law, the age-dependent change in the logarithm of mortality (life-table aging rate, LAR) is equal to the population-averaged age-independent biological aging rate (γ), and LAR would be constant if aging were the only cause of mortality increase. However, LAR is influenced by population exposures to the external hazards. If they were constant, according to the Gompertz-Makeham law (GML), LAR would be below γ at lower ages and asymptotically and monotonically approach γ with increasing age. Actually, LAR trajectories derived from data on mortality in different countries and historical periods feature systematic undulations. In the present investigation, mortality-vs.-age trajectories were modeled based on a generalized GML (gGML). Unlike the canonical GML terms, which are population-specific constants, the respective terms of the gGML are represented with some population-specific functions of age. Invariant in gGML are the modes of translation of these functions into the dependency of mortality on age: linear for population exposure to the irresistible external hazards or exponential for population-averaged ability to withstand the resistible external and internal hazards. Modeling suggests that, at earlier ages, LAR undulations are attributable to changes in population exposures to the former hazards. However, only their unrealistically high levels can produce the transient increase in LAR at about 65 to 90 years. This pervasive undulation of LAR-vs.-age trajectory is rather caused by an increment in γ. Reasons to regard gGML as a genuine natural law, which defines relations between mortality, aging and environment, are discussed.

Influence of physical activity on the epigenetic clock: evidence from a Japanese cross-sectional study

BACKGROUND

Biological age, especially epigenetic age derived from the epigenetic clock, is a significant measure of aging, considering the differences in aging rates among individuals. The epigenetic clock, a machine learning-based algorithm, uses DNA methylation states to estimate biological age. Previous studies have reported inconsistent associations between physical activity (PA) and the epigenetic clock, especially second-generation clocks such as PhenoAge and GrimAge. This study aimed to clarify this relationship using cross-sectional data from Japanese participants aged 40-69.

METHODS

We used two datasets from the Saga J-MICC study, of which 867 samples were available for analysis. DNA methylation data from peripheral blood samples were used to calculate the epigenetic age using the epigenetic clocks PhenoAge and GrimAge. PA and sedentary time were measured using a single-axis accelerometer, while self-reported PA, sedentary time, and covariates were assessed using a self-administered questionnaire. The association between PA or sedentary time and epigenetic age acceleration was assessed using multiple linear regression.

RESULTS

Pearson's correlation coefficients between accelerometer-based and self-reported PA variables ranged from 0.09 to 0.20. Multivariable regression analysis showed that accelerometer-based PA and sedentary time were associated with epigenetic age decelerations and accelerations, respectively. However, self-reported PA was not associated with the epigenetic age accelerations.

CONCLUSIONS

These results indicate that reducing sedentary time and increasing PA were associated with slowing both PhenoAge and GrimAge, even in East Asian populations with different exercise habits, body shapes, and lifestyles. This study highlights the potential of objective second-generation epigenetic age acceleration as an outcome index for healthcare interventions and clinical applications.

Lagged effects of childhood depressive symptoms on adult epigenetic aging

BACKGROUND

Cross-sectional studies have identified health risks associated with epigenetic aging. However, it is unclear whether these risks make epigenetic clocks 'tick faster' (i.e. accelerate biological aging). The current study examines concurrent and lagged within-person changes of a variety of health risks associated with epigenetic aging.

METHODS

Individuals from the Great Smoky Mountains Study were followed from age 9 to 35 years. DNA methylation profiles were assessed from blood, at multiple timepoints (i.e. waves) for each individual. Health risks were psychiatric, lifestyle, and adversity factors. Concurrent (N = 539 individuals; 1029 assessments) and lagged (N = 380 individuals; 760 assessments) analyses were used to determine the link between health risks and epigenetic aging.

RESULTS

Concurrent models showed that BMI (r = 0.15, PFDR < 0.01) was significantly correlated to epigenetic aging at the subject-level but not wave-level. Lagged models demonstrated that depressive symptoms (b = 1.67 months per symptom, PFDR = 0.02) in adolescence accelerated epigenetic aging in adulthood, also when models were fully adjusted for BMI, smoking, and cannabis and alcohol use.

CONCLUSIONS

Within-persons, changes in health risks were unaccompanied by concurrent changes in epigenetic aging, suggesting that it is unlikely for risks to immediately 'accelerate' epigenetic aging. However, time lagged analyses indicated that depressive symptoms in childhood/adolescence predicted epigenetic aging in adulthood. Together, findings suggest that age-related biological embedding of depressive symptoms is not instant but provides prognostic opportunities. Repeated measurements and longer follow-up times are needed to examine stable and dynamic contributions of childhood experiences to epigenetic aging across the lifespan.

Mediating role of accelerated aging in the association between depression and mortality risk: findings from NHANES

OBJECTIVE

To investigate the association between depression, accelerated biological aging, and mortality risk, and to assess whether accelerated aging mediates the relationship between major depression and mortality risk.

METHODS

A prospective cohort of 12,761 participants aged 20 years or older from the 2005-2010 cycle of the National Health and Nutrition Examination Survey (NHANES) was analyzed. Depression was assessed using the Patient Health Questionnaire-9 (PHQ-9), with scores of ≥ 10 indicating major depression. Accelerated biological aging was measured using phenotypic age acceleration (PhenoAgeAccel). Multivariable linear regression models and subgroup analyses were used to examine the association between depression and accelerated aging, while weighted multivariable Cox proportional hazards regression models and subgroup analyses assessed the impact of major depression on mortality risk. Mediation analysis was performed to assess whether PhenoAgeAccel mediated the relationship between major depression and mortality outcomes.

RESULTS

Among the 12,761 adults, the weighted mean age was 46.6 years, with 48.8% being male, and 6.9% experiencing major depression. The results showed a positive association between major depression and PhenoAgeAccel (β: 0.61, 95% CI: 0.06-1.16). Over a median follow-up duration of 11.3 years (interquartile range: 9.9-13.1), major depression was associated with increased all-cause mortality (HR: 1.35, 95% CI: 1.13-1.62) and cardiovascular mortality (HR: 1.73, 95% CI: 1.18-2.54). However, the relationship with cancer mortality was not statistically significant after full adjustment for confounding factors. The mediation analysis further revealed that PhenoAgeAccel accounted for 10.32% and 5.12% of the associations between major depression and all-cause mortality, and cardiovascular mortality, respectively.

CONCLUSION

Depression is associated with accelerated aging and contributes to increased all-cause and cardiovascular mortality. Accelerated aging partially mediates the association between major depression and mortality risk. Our findings highlight the urgent need to incorporate mental health care into public health strategies to delay population aging and reduce mortality risk.

Dynamical Network Stability Analysis of Multiple Biological Ages Provides a Framework for Understanding the Aging Process

Widespread interest in nondestructive biomarkers of aging has led to a multitude of biological ages that each proffers a "true" health-adjusted individual age. Although each measure provides salient information on the aging process, they are each univariate, in contrast to the "hallmark" and "pillar" theories of aging, which are explicitly multidimensional, multicausal, and multiscale. Fortunately, multiple biological ages can be systematically combined into a multidimensional network representation. The interaction network between these biological ages permits analysis of the multidimensional effects of aging, as well as quantification of causal influences during both natural aging and, potentially, after anti-aging intervention. The behavior of the system as a whole can then be explored using dynamical network stability analysis, which identifies new, efficient biomarkers that quantify long-term resilience scores on the timescale between measurements (years). We demonstrate this approach using a set of 8 biological ages from the longitudinal Swedish Adoption/Twin Study of Aging (SATSA). After extracting an interaction network between these biological ages, we observed that physiological age, a proxy for cardiometabolic health, serves as a central node in the network, implicating it as a key vulnerability for slow, age-related decline. We furthermore show that while the system as a whole is stable, there is a weakly stable direction along which recovery is slow-on the timescale of a human lifespan. This slow direction provides an aging biomarker, which correlates strongly with chronological age and predicts longitudinal decline in health-suggesting that it estimates an important driver of age-related changes.

Associations between epigenetic aging and diabetes mellitus in a Swedish longitudinal study

Diabetes mellitus type 2 (T2D) is associated with accelerated biological aging and the increased risk of onset of other age-related diseases. Epigenetic changes in DNA methylation levels have been found to serve as reliable biomarkers for biological aging. This study explores the relationship between various epigenetic biomarkers of aging and diabetes risk using longitudinal data. Data from the Swedish Adoption/Twin Study of Aging (SATSA) was collected from 1984 to 2014 and included 536 individuals with at least one epigenetic measurement. The following epigenetic biomarkers of aging were employed: DNAm PAI-1, DNAmTL, DunedinPACE, PCHorvath1, PCHorvath2, PCHannum, PCPhenoAge, and PCGrimAge. Firstly, longitudinal analysis of biomarker trajectories was done. Secondly, linear correlations between the biomarkers and time to diabetes were studied within individuals developing diabetes. Thirdly, Cox proportional hazards (PH) models were used to assess the associations between these biomarkers and time of diabetes diagnosis, with adjustments for chronological age, sex, education, smoking, blood glucose, and BMI. The longitudinal trajectories of the biomarkers revealed differences between individuals with and without diabetes. Smoothened average curves for DunedinPACE and DNAm PAI-1 were higher for individuals with diabetes around the age 60-70, compared to controls. Likewise, DunedinPACE and DNAm PAI-1 were higher closer to diabetes onset. However, no significant associations were found between the epigenetic biomarkers of aging and risk of diabetes in Cox PH models. Our findings suggest the potential value of developing epigenetic biomarkers specifically tailored to T2D, should we wish to model and explore the potential for predicting the disease.

Relationship of dietary natural folate and synthetic folic acid co-exposure patterns with biological aging: findings from NHANES 2003-2018

Background: The mandatory folic acid fortification program in the United States has inevitably exposed most Americans to both natural folate and synthetic folic acid. We aim to examine the association of dietary folate co-exposure patterns with biological aging indicators. Methods: A total of 18 889 participants were enrolled from 2003 to 2018. Dietary intake of folate from diverse sources was evaluated by 24-hour dietary recall. Biological aging indicators were developed based on age-related clinical indicators, including the phenotypic age (PA), Klemera-Doubal method (KDM), homeostatic dysregulation (HD), and allostatic load (AL). The unsupervised K-means clustering method, logistic regression model, and restricted cubic spline (RCS) regression model were used to explore the relationship of natural folate and synthetic folic acid co-exposure with biological aging indicators. Results: The results indicated that higher intake of total folate, dietary folate, and food natural folate was associated with lower PA [OR = 0.75 (0.64, 0.88); OR = 0.79 (0.70, 0.90); OR = 0.65 (0.57, 0.75)], KDM [OR = 0.63 (0.53, 0.75); OR = 0.80 (0.65, 0.98); OR = 0.62 (0.49, 0.77)], HD [OR = 0.69 (0.56, 0.84); OR = 0.78 (0.67, 0.92); OR = 0.78 (0.68, 0.90)], and AL [OR = 0.69 (0.58, 0.82); OR = 0.73 (0.63, 0.85); OR = 0.74 (0.62, 0.90)], consistently. Four co-exposure patterns were generated based on the intake of folate from diverse sources, as follows: "low folate exposure group" to cluster 1, "dietary folate exposure group" to cluster 2, "mixed source high folate exposure group" to cluster 3, and "mixed source excessive folate exposure group" to cluster 4. Compared with cluster 1, participants in cluster 2 are associated with lower biological age indicators (ORPA = 0.82 [0.72, 0.93]; ORKDM = 0.58 [0.47, 0.70]; ORHD = 0.85 [0.75, 0.97]; ORAL = 0.87 [0.77, 0.98]), while participants in cluster 3 and cluster 4 are not. Conclusion: For individuals subjected to folic acid fortification programs, a higher intake of dietary folate, especially natural folate, coupled with a lower consumption of folic acid supplements, was found to be associated with lower biological age indicators.

Associations of daily eating frequency and nighttime fasting duration with biological aging in National Health and Nutrition Examination Survey (NHANES) 2003-2010 and 2015-2018

BACKGROUND

Information on the influences of daily eating frequency (DEF) and nighttime fasting duration (NFD) on biological aging is minimal. Our study investigated the potential associations of DEF and NFD with accelerated aging.

METHODS

Out of 24212 participants in NHANES 2003-2010 and 2015-2018, 4 predicted age metrics [homeostatic dysregulation (HD), Klemera-Doubal method (KDM), phenoAge (PA), and allostatic load (AL)] were computed based on 12 blood chemistry parameters. Utilizing 24-h dietary recall, DEF was measured by the frequency of eating occurrences, while NFD was determined by assessing the timing of the initial and final meals throughout the day. Weighted multivariate linear regression models and restricted cubic spline (RCS) were utilized to examine the associations.

RESULTS

Compared to DEF of ≤ 3.0 times, subjects with DEF ≥ 4.6 times demonstrated lower KDM residual [β: -0.57, 95% confidence-interval (CI): (-0.97, -0.17)] and PA residual [β: -0.47, 95% CI: (-0.69, -0.25)]. In comparison to NFD between 10.1 and 12.0 h, individuals with NFD ≤ 10.0 h were at higher HD [β: 0.03, 95% CI: (0.01, 0.04)], KDM residual [β: 0.34, 95% CI: (0.05, 0.63)], and PA residual [β: 0.38, 95% CI: (0.18, 0.57)]. Likewise, those with NFD ≥ 14.1 h also had higher HD [β: 0.02, 95% CI: (0.01, 0.04)] and KDM residual [β: 0.33, 95% CI: (0.03, 0.62)]. The results were confirmed by the dose-response relationships of DEF and NFD with predicted age metrics. Lactate dehydrogenase (LDH) and globulin (Glo) were acknowledged as implicated in and mediating the relationships.

CONCLUSIONS

DEF below 3.0 times and NFD less than 10.0 or more than 14.1 h were independently associated with higher predicted age metrics.

Senotherapy preserves resilience in aging

In aging societies, social and economic burdens of aging-related diseases are increasing significantly. Senotherapy, which targets aging by eliminating senescent cells (senolytics) or removing sources of chronic inflammation (senostatics), are proposed as novel strategies for aging-related diseases. Aged or frail people suffer a decline of tissue reserve capacity during aging. Resilience, which is much reduced in older people, is essential for recovery from diseases, stresses or crises. Impaired resilience is one of the reasons why aged people experience a gradual waning of their daily activity and an increase of multimorbidity. Calorie restriction results in senostatic alleviation of chronic inflammation, whereas senolytic drugs induce apoptosis of senescent cells, which exacerbate aging by excreting inflammatory factors. Thus, both senolytics and senostatics are expected to reduce sterile inflammation, originating from senescent cells. Geriatr Gerontol Int 2024; 24: 845-849.

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

OBJECTIVE

Older adults have heterogeneous aging rates. Here, we explored the impact of biological age (BA) and accelerated aging on frailty in community-dwelling older adults.

METHODS

We assessed 735 community-dwelling older adults from the Coyocan Cohort. BA was measured using AnthropoAge, accelerated aging with AnthropoAgeAccel, and frailty using both 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 impact of both on body composition and physical function. We also explored accelerated aging as a risk factor for frailty progression after 3-years of follow-up.

RESULTS

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 a sexual dimorphism in body composition and physical function linked to accelerated aging in non-frail participants; however, this dimorphism was 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).

CONCLUSIONS

Despite being intertwined, biological accelerated aging is largely independent of frailty in community-dwelling older adults.

Development of an epigenetic clock resistant to changes in immune cell composition

Epigenetic clocks are age predictors that use machine-learning models trained on DNA CpG methylation values to predict chronological or biological age. Increases in predicted epigenetic age relative to chronological age (epigenetic age acceleration) are connected to aging-associated pathologies, and changes in epigenetic age are linked to canonical aging hallmarks. However, epigenetic clocks rely on training data from bulk tissues whose cellular composition changes with age. Here, we found that human naive CD8+ T cells, which decrease in frequency during aging, exhibit an epigenetic age 15-20 years younger than effector memory CD8+ T cells from the same individual. Importantly, homogenous naive T cells isolated from individuals of different ages show a progressive increase in epigenetic age, indicating that current epigenetic clocks measure two independent variables, aging and immune cell composition. To isolate the age-associated cell intrinsic changes, we created an epigenetic clock, the IntrinClock, that did not change among 10 immune cell types tested. IntrinClock shows a robust predicted epigenetic age increase in a model of replicative senescence in vitro and age reversal during OSKM-mediated reprogramming.