Genetic Evidence for Causal Effects of Socioeconomic, Lifestyle, and Cardiometabolic Factors on Epigenetic-Age Acceleration

Causal effects of cardiovascular health on five epigenetic clocks

BACKGROUND

This work delves into the relationship between cardiovascular health (CVH) and aging. Previous studies have shown an association of ideal CVH with a slower aging rate, measured by epigenetic age acceleration (EAA). However, the causal relationship between CVH and EAA has remained unexplored.

METHODS AND RESULTS

We performed genome-wide association studies (GWAS) on the (12-point) CVH score and its components using the Taiwan Biobank data, in which weighted genetic risk scores were treated as instrumental variables. Subsequently, we conducted a one-sample Mendelian Randomization (MR) analysis with the two-stage least-squares method on 2383 participants to examine the causal relationship between the (12-point) CVH score and EAA. As a result, we observed a significant causal effect of the CVH score on GrimAge acceleration (GrimEAA) (β [SE]: - 0.993 [0.363] year; p = 0.0063) and DNA methylation-based plasminogen activator inhibitor-1 (DNAmPAI-1) (β [SE]: - 0.294 [0.099] standard deviation (sd) of DNAmPAI-1; p = 0.0030). Digging individual CVH components in depth, the ideal total cholesterol score (0 [poor], 1 [intermediate], or 2 [ideal]) was causally associated with DNAmPAI-1 (β [SE]: - 0.452 [0.150] sd of DNAmPAI-1; false discovery rate [FDR] q = 0.0102). The ideal body mass index (BMI) score was causally associated with GrimEAA (β [SE]: - 2.382 [0.952] years; FDR q = 0.0498) and DunedinPACE (β [SE]: - 0.097 [0.030]; FDR q = 0.0044). We also performed a two-sample MR analysis using the summary statistics from European GWAS. We observed that the (12-point) CVH score exhibits a significant causal effect on Horvath's intrinsic epigenetic age acceleration (β [SE]: - 0.389 [0.186] years; p = 0.036) and GrimEAA (β [SE]: - 0.526 [0.244] years; p = 0.031). Furthermore, we detected causal effects of BMI (β [SE]: 0.599 [0.081] years; q = 2.91E-12), never smoking (β [SE]: - 2.981 [0.524] years; q = 1.63E-7), walking (β [SE]: - 4.313 [1.236] years; q = 0.004), and dried fruit intake (β [SE]: - 1.523 [0.504] years; q = 0.013) on GrimEAA in the European population.

CONCLUSIONS

Our research confirms the causal link between maintaining an ideal CVH and epigenetic age. It provides a tangible pathway for individuals to improve their health and potentially slow aging.

Age estimation of burnt human remains through DNA methylation analysis

The identification of human fire victims is a challenging task in forensic medicine. The heat-induced alterations of biological tissues can make the conventional anthropological analyses difficult. Even if the DNA profile of the victim is achieved, it is possible that no match can be found in a forensic DNA database, thus hindering positive identification. In such cases, any information useful to nail down a possible identity should be collected, such as DNA methylation analysis which could provide useful investigative leads. In the present study, five age-related epigenetic markers (ELOVL2, FHL2, KLF14, C1orf132, and TRIM59) were initially analysed in blood samples of 72 living Italian individuals of known age, using a Single Base Extension (SBE) assay. An age prediction model was built by multiple linear regression including all the markers (Mean Absolute Error, MAE: 3.15 years). This model was tested on 29 blood samples collected during autopsies from burnt human remains, already identified through DNA analysis, providing a MAE of 6.92 years. The model allowed a correct prediction in 79.3% of the cases (95% prediction interval), while six cases were associated with inaccurate predictions (min-max prediction error: 9.8-37.3 years). Among the different sample variables considered to explain these results, only the DNA degradation index was a relevant factor affecting the reliability of the predictions. In conclusion, the SBE typing of blood from burnt remains proved to be a reliable tool to estimate chronological age of most of the samples, also in consideration of its cost-effectiveness and the availability of CE sequencers in every forensic genetics laboratory.

Causal effects of denture wearing on epigenetic age acceleration and the mediating pathways: a mendelian randomization study

BACKGROUND

The epigenetic-age acceleration (EAA) represents the difference between chronological age and epigenetic age, reflecting accelerated biological aging. Observational studies suggested that oral disorders may impact DNA methylation patterns and aging, but their causal relationship remains largely unexplored. This study aimed to investigate potential causal associations between dental traits and EAA, as well as to identify possible mediators.

METHODS

Using summary statistics of genome-wide association studies of predominantly European ancestry, we conducted univariable and multivariable Mendelian randomization (MR) to estimate the overall and independent effects of ten dental traits (dentures, bleeding gums, painful gums, loose teeth, toothache, ulcers, periodontitis, number of teeth, and two measures of caries) on four EAA subtypes (GrimAge acceleration [GrimAA], PhenoAge acceleration [PhenoAA], HannumAge acceleration [HannumAA] and intrinsic EAA [IEAA]), and used two-step Mendelian randomization to evaluate twelve potential mediators of the associations. Comprehensive sensitivity analyses were used to verity the robustness, heterogeneity, and pleiotropy.

RESULTS

Univariable inverse variance weighted MR analyses revealed a causal effect of dentures on greater GrimAA (β: 2.47, 95% CI: 0.93-4.01, p = 0.002), PhenoAA (β: 3.00, 95% CI: 1.15-4.85, p = 0.001), and HannumAA (β: 1.96, 95% CI: 0.58-3.33, p = 0.005). In multivariable MR, the associations remained significant after adjusting for periodontitis, caries, number of teeth and bleeding gums. Three out of 12 aging risk factors were identified as mediators of the association between dentures and EAA, including body mass index, body fat percentage, and waist circumference. No evidence for reverse causality and pleiotropy were detected (p > 0.05).

CONCLUSIONS

Our findings supported the causal effects of genetic liability for denture wearing on epigenetic aging, with partial mediation by obesity. More attention should be paid to the obesity-monitoring and management for slowing EAA among denture wearers.

Association between biological ageing and periodontitis: Evidence from a cross-sectional survey and multi-omics Mendelian randomization analysis

AIM

To investigate the relationship and potential causality between biological ageing and periodontitis.

MATERIALS AND METHODS

We obtained the National Health and Nutrition Examination Survey (NHANES) and genome-wide association study (GWAS) summary statistics as well as single-cell sequencing data. Multivariate regression analysis based on cross-sectional data, Mendelian randomization (MR) and multi-omics integration analysis were employed to explore the causal association and potential molecular mechanisms between biological ageing and periodontitis. Additionally, two-step MR mediation analysis explored the risk factors in biological ageing-mediated periodontitis.

RESULTS

We analysed data from 3189 participants in the NHANES data and found that higher biological age was associated with increased risk of periodontitis. MR analyses revealed causal associations between biological age measures and periodontitis risk. Frailty (odds ratio [OR] = 2.08, 95% confidence interval [CI]: 1.04-4.18, p = .039) and GrimAge acceleration (OR = 1.16, 95% CI: 1.01-1.32, p = .033) were causally associated with periodontitis risk, and these results were validated in a large-scale meta-periodontitis GWAS dataset. Additionally, the risk effects of body mass index, waist circumference and lifetime smoking on periodontitis were partially mediated by frailty and GrimAge acceleration.

CONCLUSIONS

Evidence from cross-sectional survey and MR analysis suggests that biological ageing increases the risk of periodontitis. Additionally, improving the associated risk factors can help prevent both ageing and periodontitis.

Obesity and risk of diseases associated with hallmarks of cellular ageing: a multicohort study

BACKGROUND

Ageing hallmarks, characterising features of cellular ageing, have a role in the pathophysiology of many age-related diseases. We examined whether obesity is associated with an increased risk of developing such hallmark-related diseases.

METHODS

In this multicohort study, we included people aged 38-72 years with data on weight, height, and waist circumference measured during a clinical examination at baseline between March 13, 2006, and Oct 1, 2010, from the UK Biobank with follow-up until Nov 12, 2021. To test reproducibility of the findings (replication analysis), we used data from people aged 40 years or older included in the Finnish Public Sector study and the Finnish Health and Social Support study who responded to the study surveys, had data on BMI, and were successfully linked to electronic health records from national registers up to Dec 31, 2016. Obesity and clinical characteristics were assessed at baseline. Via linkage to national health records, participants were followed up for 83 diseases related to nine ageing hallmarks (genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, deregulated nutrient sensing, mitochondrial dysfunction, cellular senescence, stem cell exhaustion, and altered intercellular communication). Outcomes were the first instance of hallmark-related disease, in addition to co-occurrence of three or more hallmark-related diseases and mortality.

FINDINGS

496 530 adults (mean age 57·0 years [SD 8·1]) from the UK Biobank were included in the primary analysis, and 83 249 (mean age 48·2 years [6·4]) adults from the Finnish cohorts were included in the replication analysis. Median follow-up was 12·7 years (IQR 12·0-13·4) in the UK Biobank and 14·0 years (8·0-15·0) in the Finnish cohorts. After adjusting for demographic characteristics, lifestyle factors, and depression, UK Biobank participants with obesity (BMI ≥30·0 kg/m2) had a 1·40 (95% CI 1·38-1·41) times higher hazard ratio for the first hallmark-related disease than those with a healthy weight (BMI 18·5-24·9 kg/m2). The corresponding hazard ratios for three co-occurring diseases were 2·92 (95% CI 2·64-3·22) for deregulated nutrient sensing, 2·73 (2·46-3·02) for telomere attrition, 2·33 (2·10-2·60) for epigenetic alterations, 2·30 (2·14-2·48) for mitochondrial dysfunction, 2·23 (2·04-2·45) for stem cell exhaustion, 2·02 (1·89-2·16) for altered intercellular communication, 2·01 (1·89-2·15) for cellular senescence, 1·83 (1·67-2·00) for loss of proteostasis, and 1·39 (1·27-1·52) for genomic instability. These findings were replicated in the Finnish cohorts. In both studies, the associations between other risk factors (low education, unhealthy dietary factors [available only in the UK Biobank], smoking, high alcohol consumption, physical inactivity, and depression) and hallmark-related diseases were weaker than those with obesity. 45-60% of the excess mortality in people with obesity was attributable to hallmark-related diseases.

INTERPRETATION

Obesity might have an important role in the development of diseases associated with cellular ageing. Tackling ageing mechanisms could potentially help to reduce the disease and mortality burden resulting from the obesity epidemic.

FUNDING

Wellcome Trust, UK Medical Research Council, US National Institute on Aging, Academy of Finland, and Finnish Foundation for Cardiovascular Research.

TRANSLATIONS

For the German and Finnish translations of the abstract see Supplementary Materials section.

Associations between epigenetic age acceleration and longitudinal measures of psychosocioeconomic stress and status

Relationships between epigenetic aging markers and psychosocial variables such as socioeconomic status and stress have been well-documented, but are often examined cross-sectionally or retrospectively, and have tended to focus on objective markers of SES or major life events. Here, we examined associations between psychosocial variables, including measures of socioeconomic status and social stress, and epigenetic aging markers in adulthood, using longitudinal data spanning three decades from the Midlife in the United States (MIDUS) study. The largest effects were observed for epigenetic markers of change in health, such as DunedinPACE and GrimAge, and for associations involving education, income, net assets, general social stress, inequality-related stress, and financial stress. Analyses of polygenic indices suggests that at least in the case of education, the link to epigenetic aging cannot be accounted for by common genetic variants.

Association between epigenetic age and type 2 diabetes mellitus or glycemic traits: A longitudinal twin study

Epigenetic clocks based on DNA methylation have been known as biomarkers of aging, including principal component (PC) clocks representing the degree of aging and DunedinPACE representing the pace of aging. Prior studies have shown the associations between epigenetic aging and T2DM, but the results vary by epigenetic age metrics and people. This study explored the associations between epigenetic age metrics and T2DM or glycemic traits, based on 1070 twins (535 twin pairs) from the Chinese National Twin Registry. It also explored the temporal relationships of epigenetic age metrics and glycemic traits in 314 twins (157 twin pairs) who participated in baseline and follow-up visits after a mean of 4.6 years. DNA methylation data were used to calculate epigenetic age metrics, including PCGrimAge acceleration (PCGrimAA), PCPhenoAge acceleration (PCPhenoAA), DunedinPACE, and the longitudinal change rate of PCGrimAge/PCPhenoAge. Mixed-effects and cross-lagged modelling assessed the cross-sectional and temporal relationships between epigenetic age metrics and T2DM or glycemic traits, respectively. In the cross-sectional analysis, positive associations were identified between DunedinPACE and glycemic traits, as well as between PCPhenoAA and fasting plasma glucose, which may be not confounded by shared genetic factors. Cross-lagged models revealed that glycemic traits (fasting plasma glucose, HbA1c, and TyG index) preceded DunedinPACE increases, and TyG index preceded PCGrimAA increases. Glycemic traits are positively associated with epigenetic age metrics, especially DunedinPACE. Glycemic traits preceded the increases in DunedinPACE and PCGrimAA. Lowering the levels of glycemic traits may reduce DunedinPACE and PCGrimAA, thereby mitigating age-related comorbidities.

Analysis of epigenetic clocks links yoga, sleep, education, reduced meat intake, coffee, and a SOCS2 gene variant to slower epigenetic aging

DNA methylation (DNAm) clocks hold promise for measuring biological age, useful for guiding clinical interventions and forensic identification. This study compared the commonly used DNAm clocks, using DNA methylation and SNP data generated from nearly 1000 human blood or buccal swab samples. We evaluated different preprocessing methods for age estimation, investigated the association of epigenetic age acceleration (EAA) with various lifestyle and sociodemographic factors, and undertook a series of novel genome-wide association analyses for different EAA measures to find associated genetic variants. Our results highlighted the Skin&Blood clock with ssNoob normalization as the most accurate predictor of chronological age. We provided novel evidence for an association between the practice of yoga and a reduction in the pace of aging (DunedinPACE). Increased sleep and physical activity were associated with lower mortality risk score (MRS) in our dataset. University degree, vegetable consumption, and coffee intake were associated with reduced levels of epigenetic aging, whereas smoking, higher BMI, meat consumption, and manual occupation correlated well with faster epigenetic aging, with FitAge, GrimAge, and DunedinPACE clocks showing the most robust associations. In addition, we found a novel association signal for SOCS2 rs73218878 (p = 2.87 × 10-8) and accelerated GrimAge. Our study emphasizes the importance of an optimized DNAm analysis workflow for accurate estimation of epigenetic age, which may influence downstream analyses. The results support the influence of genetic background on EAA. The associated SOCS2 is a member of the suppressor of cytokine signaling family known for its role in human longevity. The reported association between various risk factors and EAA has practical implications for the development of health programs to improve quality of life and reduce premature mortality associated with age-related diseases.

Better Life's Essential 8 contributes to slowing the biological aging process: a cross-sectional study based on NHANES 2007-2010 data

Objective

To investigate the relationship between Life's Essential 8 (LE8) and Phenotypic Age Acceleration (PhenoAgeAccel) in United States adults and to explore the impact of LE8 on phenotypic biological aging, thereby providing references for public health policies and health education.

Methods

Utilizing data from the National Health and Nutrition Examination Survey (NHANES) conducted between 2007 and 2010, this cross-sectional study analyzed 7,339 adults aged 20 and above. Comprehensive assessments of LE8, PhenoAgeAccel, and research covariates were achieved through the integration of Demographics Data, Dietary Data, Laboratory Data, and Questionnaire Data derived from NHANES. Weighted generalized linear regression models and restricted cubic spline plots were employed to analyze the linear and non-linear associations between LE8 and PhenoAgeAccel, along with gender subgroup analysis and interaction effect testing.

Results

(1) Dividing the 2007-2010 NHANES cohort into quartiles based on LE8 unveiled significant disparities in age, gender, race, body mass index, education level, marital status, poverty-income ratio, smoking and drinking statuses, diabetes, hypertension, hyperlipidemia, phenotypic age, PhenoAgeAccel, and various biological markers (p < 0.05). Mean cell volume demonstrated no intergroup differences (p > 0.05). (2) The generalized linear regression weighted models revealed a more pronounced negative correlation between higher quartiles of LE8 (Q2, Q3, and Q4) and PhenoAgeAccel compared to the lowest LE8 quartile in both crude and fully adjusted models (p < 0.05). This trend was statistically significant (p < 0.001) in the full adjustment model. Gender subgroup analysis within the fully adjusted models exhibited a significant negative relationship between LE8 and PhenoAgeAccel in both male and female participants, with trend tests demonstrating significant results (p < 0.001 for males and p = 0.001 for females). (3) Restricted cubic spline (RCS) plots elucidated no significant non-linear trends between LE8 and PhenoAgeAccel overall and in gender subgroups (p for non-linear > 0.05). (4) Interaction effect tests denoted no interaction effects between the studied stratified variables such as age, gender, race, education level, and marital status on the relationship between LE8 and PhenoAgeAccel (p for interaction > 0.05). However, body mass index and diabetes manifested interaction effects (p for interaction < 0.05), suggesting that the influence of LE8 on PhenoAgeAccel might vary depending on an individual's BMI and diabetes status.

Conclusion

This study, based on NHANES data from 2007-2010, has revealed a significant negative correlation between LE8 and PhenoAgeAccel, emphasizing the importance of maintaining a healthy lifestyle in slowing down the biological aging process. Despite the limitations posed by the study's design and geographical constraints, these findings provide a scientific basis for the development of public health policies focused on healthy lifestyle practices. Future research should further investigate the causal mechanisms underlying the relationship between LE8 and PhenoAgeAccel and consider cross-cultural comparisons to enhance our understanding of healthy aging.

Causal association of obesity with epigenetic aging and telomere length: a bidirectional mendelian randomization study

BACKGROUND

In observational studies, there exists an association between obesity and epigenetic age as well as telomere length. However, varying and partially conflicting outcomes have notably arisen from distinct studies on this topic. In the present study, two-way Mendelian randomization was used to identify potential causal associations between obesity and epigenetic age and telomeres.

METHODS

A genome-wide association study was conducted using data from individuals of European ancestry to investigate bidirectional Mendelian randomization (MR) regarding the causal relationships between obesity, as indicated by three obesity indicators (body mass index or BMI, waist circumference adjusted for BMI or WCadjBMI, and waist-to-hip ratio adjusted for BMI or WHRadjBMI), and four epigenetic age measures (HannumAge, HorvathAge, GrimAge, PhenoAge), as well as telomere length. To assess these causal associations, various statistical methods were employed, including Inverse Variance Weighted (IVW), Weighted Median, MR Egger, Weighted Mode, and Simple Mode. To address the issue of multiple testing, we applied the Bonferroni correction. These methods were used to determine whether there is a causal link between obesity and epigenetic age, as well as telomere length, and to explore potential bidirectional relationships. Forest plots and scatter plots were generated to show causal associations between exposures and outcomes. For a comprehensive visualization of the results, leave-one-out sensitivity analysis plots, individual SNP-based forest plots for MR analysis, and funnel plots were included in the presentation of the results.

RESULTS

A strong causal association was identified between obesity and accelerated HannumAge, GrimAge, PhenoAge and telomere length shrinkage. The causal relationship between WCadjBMI and PhenoAge acceleration (OR: 2.099, 95%CI: 1.248-3.531, p = 0.005) was the strongest among them. However, only the p-values for the causal associations of obesity with GrimAge, PhenoAge, and telomere length met the criteria after correction using the Bonferroni multiple test. In the reverse MR analysis, there were statistically significant causal associations between HorvathAge, PhenoAge and GrimAge and BMI, but these associations exhibited lower effect sizes, as indicated by their Odds Ratios (ORs). Notably, sensitivity analysis revealed the robustness of the study results.

CONCLUSIONS

The present findings reveal a causal relationship between obesity and the acceleration of epigenetic aging as well as the reduction of telomere length, offering valuable insights for further scientific investigations aimed at developing strategies to mitigate the aging process in humans.

Associations of combined phenotypic ageing and genetic risk with incidence of chronic respiratory diseases in the UK Biobank: a prospective cohort study

BACKGROUND

Accelerated biological ageing has been associated with an increased risk of several chronic respiratory diseases. However, the associations between phenotypic age, a new biological age indicator based on clinical chemistry biomarkers, and common chronic respiratory diseases have not been evaluated.

METHODS

We analysed data from 308 592 participants at baseline in the UK Biobank. The phenotypic age was calculated from chronological age and nine clinical chemistry biomarkers, including albumin, alkaline phosphatase, creatinine, glucose, C-reactive protein, lymphocyte percent, mean cell volume, red cell distribution width and white blood cell count. Furthermore, phenotypic age acceleration (PhenoAgeAccel) was calculated by regressing phenotypic age on chronological age. The associations of PhenoAgeAccel with incident common chronic respiratory diseases and cross-sectional lung function were investigated. Moreover, we constructed polygenic risk scores and evaluated whether PhenoAgeAccel modified the effect of genetic susceptibility on chronic respiratory diseases and lung function.

RESULTS

The results showed significant associations of PhenoAgeAccel with increased risk of idiopathic pulmonary fibrosis (IPF) (hazard ratio (HR) 1.52, 95% CI 1.45-1.59), COPD (HR 1.54, 95% CI 1.51-1.57) and asthma (HR 1.18, 95% CI 1.15-1.20) per 5-year increase and decreased lung function. There was an additive interaction between PhenoAgeAccel and the genetic risk for IPF and COPD. Participants with high genetic risk and who were biologically older had the highest risk of incident IPF (HR 5.24, 95% CI 3.91-7.02), COPD (HR 2.99, 95% CI 2.66-3.36) and asthma (HR 2.07, 95% CI 1.86-2.31). Mediation analysis indicated that PhenoAgeAccel could mediate 10∼20% of the associations between smoking and chronic respiratory diseases, while ∼10% of the associations between particulate matter with aerodynamic diameter <2.5 µm and the disorders were mediated by PhenoAgeAccel.

CONCLUSION

PhenoAgeAccel was significantly associated with incident risk of common chronic respiratory diseases and decreased lung function and could serve as a novel clinical biomarker.

Opposite causal effects of birthweight on myocardial infarction and atrial fibrillation and the distinct mediating pathways: a Mendelian randomization study

BACKGROUND

Previous observational studies have documented an inverse association of birthweight with myocardial infarction (MI) but a positive association with atrial fibrillation (AF). However, the causality of these associations and the underlying mediating pathways remain unclear. We aimed to investigate the causal effects of birthweight, incorporating both fetal and maternal genetic effects, on MI and AF, and identify potential mediators in their respective pathways.

METHODS

We performed Mendelian randomization (MR) analyses using genome-wide association study summary statistics for birthweight (N = 297,356 for own birthweight and 210,248 for offspring birthweight), MI (Ncase=61,000, Ncontrol=577,000), AF (Ncase=60,620, Ncontrol=970,216), and 52 candidate mediators (N = 13,848-1,295,946). Two-step MR was employed to identify and assess the mediation proportion of potential mediators in the associations of birthweight with MI and AF, respectively. As a complement, we replicated analyses for fetal-specific birthweight and maternal-specific birthweight.

RESULTS

Genetically determined each 1-SD lower birthweight was associated with a 40% (95% CI: 1.22-1.60) higher risk of MI, whereas each 1-SD higher birthweight was causally associated with a 29% (95% CI: 1.16-1.44) higher risk of AF. Cardiometabolic factors, including lipids and lipoproteins, glucose and insulin, blood pressure, and fatty acids, each mediated 4.09-23.71% of the total effect of birthweight on MI, followed by body composition and strength traits (i.e., appendicular lean mass, height, and grip strength) and socioeconomic indicators (i.e., education and household income), with the mediation proportion for each factor ranging from 8.08 to 16.80%. By contrast, appendicular lean mass, height, waist circumference, childhood obesity, and body mass index each mediated 15.03-45.12% of the total effect of birthweight on AF. Both fetal-specific birthweight and maternal-specific birthweight were inversely associated with MI, while only fetal-specific birthweight was positively associated with AF. Psychological well-being and lifestyle factors conferred no mediating effect in either association.

CONCLUSIONS

Cardiometabolic factors mainly mediated the association between lower birthweight and MI, while body composition and strength traits mediated the association between higher birthweight and AF. These findings provide novel evidence for the distinct pathogenesis of MI and AF and advocate adopting a life-course approach to improving fetal development and subsequent causal mediators to mitigate the prevalence and burden of cardiovascular diseases.

Daytime napping, biological aging and cognitive function among middle-aged and older Chinese: insights from the China health and retirement longitudinal study

Objective

The complicated association of daytime napping, biological aging and cognitive function remains inconclusive. We aimed to evaluate the cross-sectional and longitudinal associations of daytime napping and two aging measures with cognition and to examine whether napping affects cognition through a more advanced state of aging.

Methods

Data was collected from the China Health and Retirement Longitudinal Study. Napping was self-reported. We calculated two published biological aging measures: Klemera and Doubal biological age (KDM-BA) and physiological dysregulation (PD), which derived information from clinical biomarkers. Cognitive z-scores were calculated at each wave. Linear mixed models were used to explore the longitudinal association between napping, two aging measures, and cognitive decline. Mediation analyses were performed to assess the mediating effects of biological age acceleration on the association between napping and cognition.

Results

Participants aged over 45 years were included in the analyses. Non-nappers had greater KDM-BA and PD [LS means (LSM) = 0.255, p = 0.007; LSM = 0.085, p = 0.011] and faster cognitive decline (LSM = -0.061, p = 0.005)compared to moderate nappers (30-90 min/nap). KDM-BA (β = -0.007, p = 0.018) and PD (β = -0.034, p < 0.001) showed a negative association with overall cognitive z scores. KDM-BA and PD partially mediated the effect of napping on cognition.

Conclusion

In middle-aged and older Chinese, compared to moderate nappers, non-nappers seem to experience a more advanced state of aging and increased rates of cognitive decline. The aging status possibly mediates the association between napping and cognition. Moderate napping shows promise in promoting healthy aging and reducing the burden of cognitive decline in Chinese middle-aged and older adults.

The Longevity Protein Klotho: A Promising Tool to Monitor Lifestyle Improvements

Aging is not a disease; it is a natural evolution of human physiology. Medical advances have extended our life expectancy, but chronic diseases and geriatric syndrome continue to affect the increasingly aging population. Yet modern medicine perpetuates an approach based on treatment rather than prevention and education. In order to help solve this ever-growing problem, a new discipline has emerged: lifestyle medicine. Nutrition, physical activity, stress management, restorative sleep, social connection, and avoidance of risky substances are the pillars on which lifestyle medicine is founded. The aim of this discipline is to increase healthspan and reduce the duration of morbidity by making changes to our lifestyle. In this review, we propose the use of klotho protein as a novel biomarker for lifestyle medicine in order to quantify and monitor the health status of individuals, as no integrative tool currently exists.

The impact of life stress on hallmarks of aging and accelerated senescence: Connections in sickness and in health

Chronic stress is a risk factor for numerous aging-related diseases and has been shown to shorten lifespan in humans and other social mammals. Yet how life stress causes such a vast range of diseases is still largely unclear. In recent years, the impact of stress on health and aging has been increasingly associated with the dysregulation of the so-called hallmarks of aging. These are basic biological mechanisms that influence intrinsic cellular functions and whose alteration can lead to accelerated aging. Here, we review correlational and experimental literature (primarily focusing on evidence from humans and murine models) on the contribution of life stress - particularly stress derived from adverse social environments - to trigger hallmarks of aging, including cellular senescence, sterile inflammation, telomere shortening, production of reactive oxygen species, DNA damage, and epigenetic changes. We also evaluate the validity of stress-induced senescence and accelerated aging as an etiopathological proposition. Finally, we highlight current gaps of knowledge and future directions for the field, and discuss perspectives for translational geroscience.