BMI is positively associated with accelerated epigenetic aging in twin pairs discordant for body mass index

Bridging the gap in obesity research: A consensus statement from the European Society for Clinical Investigation

BACKGROUND

Most forms of obesity are associated with chronic diseases that remain a global public health challenge.

AIMS

Despite significant advancements in understanding its pathophysiology, effective management of obesity is hindered by the persistence of knowledge gaps in epidemiology, phenotypic heterogeneity and policy implementation.

MATERIALS AND METHODS

This consensus statement by the European Society for Clinical Investigation identifies eight critical areas requiring urgent attention. Key gaps include insufficient long-term data on obesity trends, the inadequacy of body mass index (BMI) as a sole diagnostic measure, and insufficient recognition of phenotypic diversity in obesity-related cardiometabolic risks. Moreover, the socio-economic drivers of obesity and its transition across phenotypes remain poorly understood.

RESULTS

The syndemic nature of obesity, exacerbated by globalization and environmental changes, necessitates a holistic approach integrating global frameworks and community-level interventions. This statement advocates for leveraging emerging technologies, such as artificial intelligence, to refine predictive models and address phenotypic variability. It underscores the importance of collaborative efforts among scientists, policymakers, and stakeholders to create tailored interventions and enduring policies.

DISCUSSION

The consensus highlights the need for harmonizing anthropometric and biochemical markers, fostering inclusive public health narratives and combating stigma associated with obesity. By addressing these gaps, this initiative aims to advance research, improve prevention strategies and optimize care delivery for people living with obesity.

CONCLUSION

This collaborative effort marks a decisive step towards mitigating the obesity epidemic and its profound impact on global health systems. Ultimately, obesity should be considered as being largely the consequence of a socio-economic model not compatible with optimal human health.

Twin pair analysis uncovers links between DNA methylation, mitochondrial DNA quantity and obesity

Alterations in mitochondrial metabolism in obesity may indicate disrupted communication between mitochondria and nucleus, and DNA methylation may influence this interplay. Here, we leverage data from the Finnish Twin Cohort study subcohort (n = 173; 86 full twin pairs, 1 singleton), including comprehensive measurements of obesity-related outcomes, mitochondrial DNA quantity and nuclear DNA methylation levels in adipose and muscle tissue, to identify one CpG at SH3BP4 significantly associated with mitochondrial DNA quantity in adipose tissue (FDR < 0.05). We also show that SH3BP4 methylation correlates with its gene expression. Additionally, we find that 14 out of the 35 obesity-related traits display significant associations with both SH3BP4 methylation and mitochondrial DNA quantity in adipose tissue. We use data from TwinsUK and the Scandinavian T2D-discordant monozygotic twin cohort, to validate the observed associations. Further analysis using ICE FALCON suggests that mitochondrial DNA quantity, insulin sensitivity and certain body fat measures are causal to SH3BP4 methylation. Examining mitochondrial DNA quantity and obesity-related traits suggests causation from mitochondrial DNA quantity to obesity, but unmeasured within-individual confounding cannot be ruled out. Our findings underscore the impact of mitochondrial DNA quantity on DNA methylation and expression of the SH3BP4 gene within adipose tissue, with potential implications for obesity.

Multi-Omic Associations of Epigenetic Age Acceleration Are Heterogeneously Shaped by Genetic and Environmental Influences

Connections between the multi-ome and epigenetic age acceleration (EAA), and especially whether these are influenced by genetic or environmental factors, remain underexplored. We therefore quantified associations between the multi-ome comprising four layers-the proteome, metabolome, external exposome (here, sociodemographic factors), and specific exposome (here, lifestyle)-with six different EAA estimates. Two twin cohorts were used in a discovery-replication scheme, comprising, respectively, young (N = 642; mean age = 22.3) and older (N = 354; mean age = 62.3) twins. Within-pair twin designs were used to assess genetic and environmental effects on associations. We identified 40 multi-omic factors, of which 28 were proteins, associated with EAA in the young twins while adjusting for sex, smoking, and body mass index. Within-pair analyses revealed that genetic confounding influenced these associations heterogeneously, with six multi-omic factors -matrix metalloproteinase 9, complement component C6, histidine, glycoprotein acetyls, lactate, and neighborhood percentage of nonagenarians- remaining significantly associated with EAA, independent of genetic effects. Replication analyses showed that some associations assessed in young twins were consistent in older twins. Our study highlights the differential influence of genetic effects on the associations between the multi-ome and EAA and shows that some, but not all, of the associations persist into adulthood.

Sexual minority stress and epigenetic aging

Lesbian, gay, bisexual, transgender, and queer/questioning (LGBTQ + ) individuals have poorer mental and physical health than heterosexuals, and bisexuals fare worse than individuals who identify as lesbian and gay. However, data on stress biology among sexual minorities are critically insufficient. The current pilot study utilized data from 32 bisexual women - a subset of the National Couples' Health and Time Study - who completed questionnaires and provided blood samples to index biological aging from DNA methylation data (DunedinPACE, GrimAge2). The mean DunedinPACE score was 1.13 (SD = 0.18), which outpaced chronological aging by 13 % (p < 0.001). Likewise, bisexual women in this sample were, on average, 8.67 (SD = 5.96) years older biologically per GrimAge2 as compared to their chronological age. In covariate adjusted models, those reporting greater internalized homonegativity exhibited significantly greater epigenetic age acceleration (GrimAge2: p = 0.01; DunedinPACE: p = 0.041). Those who reported more frequent anti-bisexual experiences also showed accelerated GrimAge2 (p = 0.023). In contrast, those who reported stronger identity centrality (p = 0.017), stronger identity affirmation (p = 0.029), and more friend support (p = 0.018) - a critical type of support for LGBTQ + individuals - had slower GrimAge2. Depressive symptoms, anxiety and loneliness were not associated with GrimAge2 or DunedinPACE. Results suggest that bisexual women are at risk for accelerated aging, and those who have less internal and external affirmation of their sexual identity may be most at risk.

Genetic determinants of proteomic aging

Changes in the proteome and its dysregulation have long been known to be a hallmark of aging. We derived a proteomic aging trait using data on 1459 plasma proteins from 44,435 UK Biobank individuals measured using an antibody-based assay. This metric is strongly associated with four age-related disease outcomes, even after adjusting for chronological age. Survival analysis showed that one-year older proteomic age, relative to chronological age, increases all-cause mortality hazard by 13 percent. We performed a genome-wide association analysis of proteomic age acceleration (proteomic aging trait minus chronological age) to identify its biological determinants. Proteomic age acceleration showed modest genetic correlations with four epigenetic clocks (Rg = 0.17 to 0.19) and telomere length (Rg = -0.2). Once we removed associations that were explained by a single pQTL, we were left with three signals mapping to BRCA1, POLR2A and TET2 with apparent widespread effects on plasma proteomic aging. Genetic variation at these three loci has been shown to affect other omics-related aging measures. Mendelian randomisation analyses showed causal effects of higher BMI and type 2 diabetes on faster proteomic age acceleration. This supports the idea that obesity and other features of metabolic syndrome have an adverse effect on the processes of human aging.

Influence of Body Mass Index (BMI) and Waist-Hip Ratio (WHR) on Selected Semen Parameters

Because male obesity may result in reproductive failure, we aimed to examine the possible links among body mass index (BMI), the waist-hip ratio (WHR), and basic semen parameters, the oxidation-reduction potential of semen, the total antioxidant capacity of seminal plasma, the ability of sperm to bind hyaluronic acid, and sperm DNA fragmentation (SDF). This study was performed on semen (n = 543) collected from volunteers classified as follows: normal weight (BMI 18.5-24.9 kg/m2), overweight (BMI 25.0-29.9 kg/m2), obese (BMI ≥ 30.0 kg/m2), with a normal WHR (<1) or abnormal WHR (≥1). No significant differences in standard semen parameters were found between men with a normal BMI and those with overweight/obesity. However, compared with overweight men, obese men had a higher SDF index prevalence and risk for an SDF index > 20%. Compared with men with WHR < 1, those with WHR ≥ 1 had significantly lower sperm motility, morphology, and vitality and an increased SDF index, prevalence and risk for an SDF index > 20%. In conclusion, abnormal WHR had a greater negative impact on conventional semen parameters than abnormal BMI. Both BMI ≥ 30.0 and WHR ≥ 1 negatively influenced sperm chromatin integrity only. Obesity is a potential risk factor for sperm DNA damage.

Epigenetic Aging Acceleration in Obesity Is Slowed Down by Nutritional Ketosis Following Very Low-Calorie Ketogenic Diet (VLCKD): A New Perspective to Reverse Biological Age

Background/Objectives: Epigenetic clocks have emerged as a tool to quantify biological age, providing a more accurate estimate of an individual's health status than chronological age, helping to identify risk factors for accelerated aging and evaluating the reversibility of therapeutic strategies. This study aimed to evaluate the potential association between epigenetic acceleration of biological age and obesity, as well as to determine whether nutritional interventions for body weight loss could slow down this acceleration. Methods: Biological age was estimated using three epigenetic clocks (Horvath (Hv), Hannum (Hn), and Levine (Lv)) based on the leukocyte methylome analysis of individuals with normal weight (n = 20), obesity (n = 24), and patients with obesity following a VLCKD (n = 10). We analyzed differences in biological age estimates, the relationship between age acceleration and obesity, and the impact of VLCKD. Correlations were assessed between age acceleration, BMI, and various metabolic parameters. Results: Analysis of the epigenetic clocks revealed an acceleration of biological age in individuals with obesity (Hv = +3.4(2.5), Hn = +5.7(3.2), Lv = +3.9(2.7)) compared to a slight deceleration in individuals with normal weight. This epigenetic acceleration correlated with BMI (p < 0.0001). Interestingly, patients with obesity following a VLCKD showed a deceleration in estimated biological age, both in nutritional ketosis (Hv = -3.3(4.0), Hn = -6.3(5.3), Lv = -8.8(4.5)) and at endpoint (Hv = -1.1(4.3), Hn = -7.4(5.6), Lv = -8.2(5.3)). Relevantly, this slowdown in age is associated with BMI (p < 0.0001), ketonemia (p ≤ 0.001), and metabolic parameters (p < 0.05). Conclusions: Our findings highlight the applicability of epigenetic clocks to monitor obesity-related biological aging in precision medicine and show the potential efficacy of the VLCKD in slowing obesity-related epigenetic aging.

Early menarche and childbirth accelerate aging-related outcomes and age-related diseases: Evidence for antagonistic pleiotropy in humans

Aging can be understood as a consequence of the declining force of natural selection with age. Consistent with this, the antagonistic pleiotropy theory of aging proposes that aging arises from trade-offs that favor early growth and reproduction. However, evidence supporting antagonistic pleiotropy in humans remains limited. Using Mendelian Randomization (MR), we demonstrated that later ages of menarche or first childbirth were genetically associated with longer parental lifespan, decreased frailty index, slower epigenetic aging, later menopause, and reduced facial aging. Moreover, later menarche or first childbirth were also genetically associated with a lower risk of several age-related diseases, including late-onset Alzheimer's disease (LOAD), type 2 diabetes, heart disease, essential hypertension, and chronic obstructive pulmonary disease (COPD). We validated the associations between the age of menarche, childbirth, and the number of childbirths with several age-related outcomes in the UK Biobank by conducting regression analysis of nearly 200,000 subjects. Our results demonstrated that menarche before the age 11 and childbirth before 21 significantly accelerated the risk of several diseases, and almost doubled the risk for diabetes, heart failure, and quadrupled the risk of obesity, supporting the antagonistic pleiotropy theory. We identified 126 significant single nucleotide polymorphisms (SNPs) that influenced age-related outcomes, some of which were involved in known longevity pathways, including IGF1, growth hormone, AMPK, and mTOR signaling. Our study also identified higher BMI as a mediating factor in causing the increased risk of certain diseases, such as type 2 diabetes and heart failure, in women with early menarche or early pregnancy, emphasizing the importance of the thrifty gene hypothesis in explaining in part the mechanisms behind antagonistic pleiotropy. Our study highlights the complex relationship between genetic legacies and modern diseases, emphasizing the need for gender-sensitive healthcare strategies that consider the unique connections between female reproductive health and aging.

Epigenetic Mechanisms in Aging: Extrinsic Factors and Gut Microbiome

BACKGROUND/OBJECTIVES

Aging is a natural physiological process involving biological and genetic pathways. Growing evidence suggests that alterations in the epigenome during aging result in transcriptional changes, which play a significant role in the onset of age-related diseases, including cancer, cardiovascular disease, diabetes, and neurodegenerative disorders. For this reason, the epigenetic alterations in aging and age-related diseases have been reviewed, and the major extrinsic factors influencing these epigenetic alterations have been identified. In addition, the role of the gut microbiome and its metabolites as epigenetic modifiers has been addressed.

RESULTS

Long-term exposure to extrinsic factors such as air pollution, diet, drug use, environmental chemicals, microbial infections, physical activity, radiation, and stress provoke epigenetic changes in the host through several endocrine and immune pathways, potentially accelerating the aging process. Diverse studies have reported that the gut microbiome plays a critical role in regulating brain cell functions through DNA methylation and histone modifications. The interaction between genes and the gut microbiome serves as a source of adaptive variation, contributing to phenotypic plasticity. However, the molecular mechanisms and signaling pathways driving this process are still not fully understood.

CONCLUSIONS

Extrinsic factors are potential inducers of epigenetic alterations, which may have important implications for longevity. The gut microbiome serves as an epigenetic effector influencing host gene expression through histone and DNA modifications, while bidirectional interactions with the host and the underexplored roles of microbial metabolites and non-bacterial microorganisms such as fungi and viruses highlight the need for further research.

Time is encoded by methylation changes at clustered CpG sites

Age-dependent changes in DNA methylation allow chronological and biological age inference, but the underlying mechanisms remain unclear. Using ultra-deep sequencing of >300 blood samples from healthy individuals, we show that age-dependent DNA methylation changes are regional and occur at multiple adjacent CpG sites, either stochastically or in a coordinated block-like manner. Deep learning analysis of single-molecule patterns in two genomic loci achieved accurate age prediction with a median error of 1.46-1.7 years on held-out human blood samples, dramatically improving current epigenetic clocks. Factors such as gender, BMI, smoking and other measures of biological aging do not affect chronological age inference. Longitudinal 10-year samples revealed that early deviations from epigenetic age are maintained throughout life and subsequent changes faithfully record time. Lastly, the model inferred chronological age from as few as 50 DNA molecules, suggesting that age is encoded by individual cells. Overall, DNA methylation changes in clustered CpG sites illuminate the principles of time measurement by cells and tissues, and facilitate medical and forensic applications.

Epigenetic aging and fecundability: the Norwegian Mother, Father and Child Cohort Study

STUDY QUESTION

Is there an association between male or female epigenetic age acceleration (EAA) or deceleration (EAD) and fecundability?

SUMMARY ANSWER

We do not find compelling evidence of an association between EAA or EAD and fecundability.

WHAT IS KNOWN ALREADY

Prior research has shown that female accelerated epigenetic aging is associated with unfavorable clinical fecundity outcomes and use of in vitro fertilization, and that epigenetic aging in sperm cells is associated with unfavorable sperm parameters. Studies of epigenetic aging and fecundability among individuals who conceive naturally are lacking.

STUDY DESIGN, SIZE, DURATION

This study is based on the Norwegian Mother, Father and Child Cohort Study (MoBa), a population-based pregnancy cohort which recruited pregnant couples between 1999 and 2008. We used data from 1657 couples (women and men) with planned naturally conceived pregnancies and available blood samples.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Methylation levels were measured in DNA from blood samples taken recruitment (at ∼18 gestational weeks) from pregnant women and their partners using the Illumina Methylation EPIC Array. To obtain a measure of EAA/EAD, we performed a linear regression of each of seven different established epigenetic biomarkers (DNAmAge by Horvath, DNAmAge by Hannum et al., PhenoAge by Levine et al., DunedinPoAm by Belsky et al., DunedinPACE by Belsky et al., DNAmTL by Lu et al., and GrimAge by Lu et al.) against chronological age. We fitted proportional probability regression models to obtain fecundability ratios (FRs) for each standard deviation increase in epigenetic aging, and obtained crude and adjusted (for body mass index, smoking, and education level) estimates. Results were evaluated at a false discovery rate (FDR) of 5%. We evaluated all models for non-linear associations using categories of epigenetic age where appropriate.

MAIN RESULTS AND THE ROLE OF CHANCE

Although the DunedinPACE clock in males demonstrated slightly increasing fecundability with increasing EAA (adjusted FR 1.05 per one standard deviation increase in EAA, 95% CI 1.00-1.10), this was not robust when evaluated at an FDR of 5%. We found evidence of non-linearity between biological aging and fecundability in two models in females and three models in males, but non-linear associations were weak and conflicting.

LIMITATIONS, REASONS FOR CAUTION

As MoBa is a pregnancy cohort, our findings may not be generalizable to all couples attempting conception. Fecundability is a couple-level measure, and any impacts of epigenetic aging in each partner may be obscured by effects of the other partner.

WIDER IMPLICATIONS OF THE FINDINGS

Our findings contrast with those of prior studies, which have indicated an association between EAA and unfavorable clinical fertility outcomes in populations using fertility treatments, possibly due to less important effects of epigenetic aging among couples who conceive naturally. More research is needed on the association between blood-based EAA and clinical fertility parameters in both sexes.

STUDY FUNDING/COMPETING INTEREST(S)

The study was supported by the Research Council of Norway through its Medical Student Research Program funding scheme (project number 271555/F20), its Centres of Excellence funding scheme (project number 262700), and a grant from the Women's Health Program (320656). Co-funding was also received from the Strategic Research Council (SRC), FLUX consortium, decision numbers 345130 and 345131; the National Institute on Aging (R01AG075208); grants to the Max Planck-University of Helsinki Center from the Max Planck Society (decision number 5714240218), Jane and Aatos Erkko Foundation, Faculty of Social Sciences at the University of Helsinki, and Cities of Helsinki, Vantaa, and Espoo; and the European Research Council; and the European Research Council (ERC Synergy, BIOSFER, grant number 101071773, and the Horizon 2020 research and innovation program, grant number 947684). The authors declare no conflicts of interest.

TRIAL REGISTRATION NUMBER

N/A.

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

Purpose

It is crucial to identify biomarkers that influence the aging process and associated health risks, given the growing severity of the global population aging issue. The objectives of our research were to evaluate cardiac metabolic index (CMI) as a novel biomarker for identifying individuals at increased risk of accelerated biological aging and to assess its use in guiding preventive strategies for aging-related health risks.

Methods

The National Health and Nutrition Examination Survey (NHANES) provided cross-sectional data on participants with complete information on CMI, phenotypic age (PA), and other variables. Analyses of variance and weighted χ2 tests were conducted to assess differences between groups. The relationship between CMI and biological aging was investigated using a weighted multivariate logistic regression model, restricted cubic spline (RCS) regression analysis, subgroup analysis, and interaction testing.

Results

A positive correlation between CMI and biological aging was observed in 6,272 participants. RCS regression analysis confirmed the non-linear relationship, identifying significant inflection point at 1.10. In the crude or adjusted models, the OR (95% CI), for the highest group versus the reference were 3.608 (3.108, 4.188), 3.397 (2.920, 3.952), and 1.550 (1.299, 1.850), respectively, when categorizing CMI into different groups. Subgroup analyses and interaction tests indicate that the association between CMI and biological aging remained consistent across different subgroups. Gender, race, education level, marital status, poverty income ratio (PIR), drinking status and diabetes had an interaction with CMI in relation to biological aging.

Conclusion

An elevated CMI is linked to increased risk for biological aging. This relationship may inform more effective prevention and treatment strategies for biological aging in the future. CMI be integrated into routine health screenings or aging assessments by healthcare professionals.

Lifestyle differences between co-twins are associated with decreased similarity in their internal and external exposome profiles

Whether differences in lifestyle between co-twins are reflected in differences in their internal or external exposome profiles remains largely underexplored. We therefore investigated whether within-pair differences in lifestyle were associated with within-pair differences in exposome profiles across four domains: the external exposome, proteome, metabolome and epigenetic age acceleration (EAA). For each domain, we assessed the similarity of co-twin profiles using Gaussian similarities in up to 257 young adult same-sex twin pairs (54% monozygotic). We additionally tested whether similarity in one domain translated into greater similarity in another. Results suggest that a lower degree of similarity in co-twins' exposome profiles was associated with greater differences in their behavior and substance use. The strongest association was identified between excessive drinking behavior and the external exposome. Overall, our study demonstrates how social behavior and especially substance use are connected to the internal and external exposomes, while controlling for familial confounders.

DNA Methylation Mediates the Association Between Cardiometabolic Risk Factors and Cognition: Findings From the Health and Retirement Study

The association between cardiometabolic risk factors and cognitive function has been well documented, but the underlying mechanisms are not fully understood. This longitudinal study aimed to investigate the potential mediating role of DNA methylation in this association. We conducted the analyses in 3 708 participants (mean [standard deviation {SD}] age: 67.3 [9.5], women: 57.9%) from the Health and Retirement Study who were assessed in the 2014-2020 waves, had Infinium Methylation EPIC BeadChip methylation assays from the 2016 Venous Blood Study, and had cognitive assessment between 2016 and 2020. Causal mediation analyses were used to test the mediation role of DNA methylation in the associations between cardiometabolic risk factors and cognition, adjusting for demographic, socioeconomic, and lifestyle factors. Hypertension (-0.061 in composite cognitive z-score; 95% confidence interval [CI: -0.119, -0.004]) and diabetes (-0.134; 95% CI: [-0.198, -0.071]) were significantly associated with worse cognitive function while abnormal body weight and hypercholesterolemia were not. An increased number of cardiometabolic risk factors was associated with worse cognitive function (p = .002). DNA methylation significantly mediated the association of hypertension (mediated effect on composite cognitive z-score: -0.023; 95% CI: -0.033, -0.014), diabetes (-0.022; 95% CI: -0.032, -0.014), and obesity (-0.021; 95% CI: -0.033, -0.011) with cognitive function, whereas the mediation effect was not observed for having hypercholesterolemia. The estimated proportions mediated were 37.4% for hypertension and 16.7% for diabetes. DNA methylation may be an important mediator linking cardiometabolic risk factors to worse cognition and might even provide a potential target for dementia prevention.

Body mass index mediates the association between four dietary indices and phenotypic age acceleration in adults: a cross-sectional study

Background: Diet and body mass index (BMI) are widely recognized as being closely associated with aging. However, it remains unclear which dietary indices are associated with aging, and the extent to which BMI mediates the relationship between diet and aging. Therefore, this study investigates the mediating role of BMI in the association between various dietary indices and phenotypic age acceleration (PhenoAgeAccel). Methods: Data were sourced from the National Health and Nutrition Examination Survey (NHANES), using two 24 hour recall interviews to compute four dietary indices: the Dietary Inflammatory Index (DII), Healthy Eating Index-2020 (HEI-2020), Alternative Healthy Eating Index-2010 (AHEI-2010), and Composite Dietary Antioxidant Index (CDAI). Linear regression analyses and mediation analyses assessed the associations between dietary indices and PhenoAgeAccel and the mediating effects of BMI. Z-score transformations (zDII, zHEI-2020, zAHEI-2010, and zCDAI) were used to ensure comparability between different dietary indices. Results: After adjusting for covariates, the zHEI-2020, zAHEI-2010, and zCDAI were negatively associated with PhenoAgeAccel (P < 0.05), with β values being -0.36, -0.40, and -0.41, respectively. The zDII was positively associated with PhenoAgeAccel (P < 0.001) with a β value of 0.70. Mediation analyses suggested that BMI significantly mediated the relationships between these dietary indices and PhenoAgeAccel. The mediation proportions were 23.7% for zDII, 43.3% for zHEI-2020, 24.5% for zAHEI-2010, and 23.6% for zCDAI. Conclusions: This study indicates that all dietary indices and BMI were significantly associated with PhenoAgeAccel. In addition, BMI exhibited the highest mediation proportion in the relationship between HEI-2020 and PhenoAgeAccel.

Five years of change in adult twins: longitudinal changes of genetic and environmental influence on epigenetic clocks

BACKGROUND

Epigenetic clocks were known as promising biomarkers of aging, including original clocks trained by individual CpG sites and principal component (PC) clocks trained by PCs of CpG sites. The effects of genetic and environmental factors on epigenetic clocks are still unclear, especially for PC clocks.

METHODS

We constructed univariate twin models in 477 same-sex twin pairs from the Chinese National Twin Registry (CNTR) to estimate the heritability of five epigenetic clocks (GrimAge, PhenoAge, DunedinPACE, PCGrimAge, and PCPhenoAge). Besides, we investigated the longitudinal changes of genetic and environmental influences on epigenetic clocks across 5 years in 134 same-sex twin pairs.

RESULTS

Heritability of epigenetic clocks ranged from 0.45 to 0.70, and those for PC clocks were higher than those for original clocks. For five epigenetic clocks, the longitudinal stability was moderate to high and was largely due to genetic effects. The genetic correlations between baseline and follow-up epigenetic clocks were moderate to high. Special unique environmental factors emerged both at baseline and at follow-up. PC clocks showed higher longitudinal stability and unique environmental correlations than original clocks.

CONCLUSIONS

For five epigenetic clocks, they have the potential to identify aging interventions. High longitudinal stability is mainly due to genetic factors, and changes of epigenetic clocks over time are primarily due to changes in unique environmental factors. Given the disparities in genetic and environmental factors as well as longitudinal stability between PC and original clocks, the results of studies with original clocks need to be further verified with PC clocks.

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.

Metabolic syndrome and epigenetic aging: a twin study

BACKGROUND

Metabolic syndrome (MetS) is associated with premature aging, but whether this association is driven by genetic or lifestyle factors remains unclear.

METHODS

Two independent discovery cohorts, consisting of twins and unrelated individuals, were examined (N = 268, aged 23-69 years). The findings were replicated in two cohorts from the same base population. One consisted of unrelated individuals (N = 1 564), and the other of twins (N = 293). Participants' epigenetic age, estimated using blood DNA methylation data, was determined using the epigenetic clocks GrimAge and DunedinPACE. The individual-level linear regression models for investigating the associations of MetS and its components with epigenetic aging were followed by within-twin-pair analyses using fixed-effects regression models to account for genetic factors.

RESULTS

In individual-level analyses, GrimAge age acceleration was higher among participants with MetS (N = 56) compared to participants without MetS (N = 212) (mean 2.078 [95% CI = 0.996,3.160] years vs. -0.549 [-1.053,-0.045] years, between-group p = 3.5E-5). Likewise, the DunedinPACE estimate was higher among the participants with MetS compared to the participants without MetS (1.032 [1.002,1.063] years/calendar year vs. 0.911 [0.896,0.927] years/calendar year, p = 4.8E-11). An adverse profile in terms of specific MetS components was associated with accelerated aging. However, adjustments for lifestyle attenuated these associations; nevertheless, for DunedinPACE, they remained statistically significant. The within-twin-pair analyses suggested that genetics explains these associations fully for GrimAge and partly for DunedinPACE. The replication analyses provided additional evidence that the association between MetS components and accelerated aging is independent of the lifestyle factors considered in this study, however, suggesting that genetics is a significant confounder in this association.

CONCLUSIONS

The results of this study suggests that MetS is associated with accelerated epigenetic aging, independent of physical activity, smoking or alcohol consumption, and that the association may be explained by genetics.

Identifying the relation between food groups and biological ageing: a data-driven approach

BACKGROUND

Heterogeneity in ageing rates drives the need for research into lifestyle secrets of successful agers. Biological age, predicted by epigenetic clocks, has been shown to be a more reliable measure of ageing than chronological age. Dietary habits are known to affect the ageing process. However, much remains to be learnt about specific dietary habits that may directly affect the biological process of ageing.

OBJECTIVE

To identify food groups that are directly related to biological ageing, using Copula Graphical Models.

METHODS

We performed a preregistered analysis of 3,990 postmenopausal women from the Women's Health Initiative, based in North America. Biological age acceleration was calculated by the epigenetic clock PhenoAge using whole-blood DNA methylation. Copula Graphical Modelling, a powerful data-driven exploratory tool, was used to examine relations between food groups and biological ageing whilst adjusting for an extensive amount of confounders. Two food group-age acceleration networks were established: one based on the MyPyramid food grouping system and another based on item-level food group data.

RESULTS

Intake of eggs, organ meat, sausages, cheese, legumes, starchy vegetables, added sugar and lunch meat was associated with biological age acceleration, whereas intake of peaches/nectarines/plums, poultry, nuts, discretionary oil and solid fat was associated with decelerated ageing.

CONCLUSION

We identified several associations between specific food groups and biological ageing. These findings pave the way for subsequent studies to ascertain causality and magnitude of these relationships, thereby improving the understanding of biological mechanisms underlying the interplay between food groups and biological ageing.

Perivascular fat tissue and vascular aging: A sword and a shield

The understanding of the function of perivascular adipose tissue (PVAT) in vascular aging has significantly changed due to the increasing amount of information regarding its biology. Adipose tissue surrounding blood vessels is increasingly recognized as a key regulator of vascular disorders. It has significant endocrine and paracrine effects on the vasculature and is mediated by the production of a variety of bioactive chemicals. It also participates in a number of pathological regulatory processes, including oxidative stress, immunological inflammation, lipid metabolism, vasoconstriction, and dilation. Mechanisms of homeostasis and interactions between cells at the local level tightly regulate the function and secretory repertoire of PVAT, which can become dysregulated during vascular aging. The PVAT secretion group changes from being reducing inflammation and lowering cholesterol to increasing inflammation and increasing cholesterol in response to systemic or local inflammation and insulin resistance. In addition, the interaction between the PVAT and the vasculature is reciprocal, and the biological processes of PVAT are directly influenced by the pertinent indicators of vascular aging. The architectural and biological traits of PVAT, the molecular mechanism of crosstalk between PVAT and vascular aging, and the clinical correlation of vascular age-related disorders are all summarized in this review. In addition, this paper aims to elucidate and evaluate the potential benefits of therapeutically targeting PVAT in the context of mitigating vascular aging. Furthermore, it will discuss the latest advancements in technology used for targeting PVAT.

Associations of Epigenetic Age Acceleration With CVD Risks Across the Lifespan: The Bogalusa Heart Study

Although epigenetic age acceleration (EAA) might serve as a molecular signature of childhood cardiovascular disease (CVD) risk factors and further promote midlife subclinical CVD, few studies have comprehensively examined these life course associations. This study sought to test whether childhood CVD risk factors predict EAA in adulthood and whether EAA mediates the association between childhood CVD risks and midlife subclinical disease. Among 1,580 Bogalusa Heart Study participants, we estimated extrinsic EAA, intrinsic EAA, PhenoAge acceleration (PhenoAgeAccel), and GrimAge acceleration (GrimAgeAccel) during adulthood. We tested prospective associations of longitudinal childhood body mass index (BMI), blood pressure, lipids, and glucose with EAAs using linear mixed effects models. After confirming EAAs with midlife carotid intima-media thickness and carotid plaque, structural equation models examined mediating effects of EAAs on associations of childhood CVD risk factors with subclinical CVD measures. After stringent multiple testing corrections, each SD increase in childhood BMI was significantly associated with 0.6-, 0.9-, and 0.5-year increases in extrinsic EAA, PhenoAgeAccel, and GrimAgeAccel, respectively (P < 0.001 for all 3 associations). Likewise, each SD increase in childhood log-triglycerides was associated with 0.5- and 0.4-year increases in PhenoAgeAccel and GrimAgeAccel (P < 0.001 for both), respectively, whereas each SD increase in childhood high-density lipoprotein cholesterol was associated with a 0.3-year decrease in GrimAgeAccel (P = 0.002). Our findings indicate that PhenoAgeAccel mediates an estimated 27.4% of the association between childhood log-triglycerides and midlife carotid intima-media thickness (P = 0.022). Our data demonstrate that early life CVD risk factors may accelerate biological aging and promote subclinical atherosclerosis.

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.

Lifestyle differences between co-twins are associated with decreased similarity in their internal and external exposome profiles

Whether differences in lifestyle between co-twins are reflected in differences in their internal or external exposome profiles remains largely underexplored. We therefore investigated whether within-pair differences in lifestyle were associated with within-pair differences in exposome profiles across four domains: the external exposome, proteome, metabolome and epigenetic age acceleration (EAA). For each domain, we assessed the similarity of co-twin profiles using Gaussian similarities in up to 257 young adult same-sex twin pairs (54% monozygotic). We additionally tested whether similarity in one domain translated into greater similarity in another. Results suggest that a lower degree of similarity in co-twins' exposome profiles was associated with greater differences in their behavior and substance use. The strongest association was identified between excessive drinking behavior and the external exposome. Overall, our study demonstrates how social behavior and especially substance use are connected to the internal and external exposomes, while controlling for familial confounders.

Epigenetic and Metabolomic Biomarkers for Biological Age: A Comparative Analysis of Mortality and Frailty Risk

Biological age captures a person's age-related risk of unfavorable outcomes using biophysiological information. Multivariate biological age measures include frailty scores and molecular biomarkers. These measures are often studied in isolation, but here we present a large-scale study comparing them. In 2 prospective cohorts (n = 3 222), we compared epigenetic (DNAm Horvath, DNAm Hannum, DNAm Lin, DNAm epiTOC, DNAm PhenoAge, DNAm DunedinPoAm, DNAm GrimAge, and DNAm Zhang) and metabolomic-based (MetaboAge and MetaboHealth) biomarkers in reflection of biological age, as represented by 5 frailty measures and overall mortality. Biomarkers trained on outcomes with biophysiological and/or mortality information outperformed age-trained biomarkers in frailty reflection and mortality prediction. DNAm GrimAge and MetaboHealth, trained on mortality, showed the strongest association with these outcomes. The associations of DNAm GrimAge and MetaboHealth with frailty and mortality were independent of each other and of the frailty score mimicking clinical geriatric assessment. Epigenetic, metabolomic, and clinical biological age markers seem to capture different aspects of aging. These findings suggest that mortality-trained molecular markers may provide novel phenotype reflecting biological age and strengthen current clinical geriatric health and well-being assessment.

How does loneliness "get under the skin" to become biologically embedded?

Loneliness is linked to declining physical health across cardiovascular, inflammatory, metabolic, and cognitive domains. As a result, loneliness is increasingly being recognized as a public health threat, though the mechanisms that have been studied do not yet explain all loneliness-related health risk. Potential mechanisms include loneliness having 1.) direct, causal impacts on health, possibly maintained by epigenetic modification, 2.) indirect effects mediated through health-limiting behaviors, and 3.) artifactual associations perhaps related to genetic overlap and reverse causation. In this scoping review, we examine the evidence surrounding each of these pathways, with a particular emphasis on emerging research on epigenetic effects, in order to evaluate how loneliness becomes biologically embedded. We conclude that there are significant gaps in our knowledge of how psychosocial stress may lead to physiological changes, so more work is needed to understand if, how, and when loneliness has a direct influence on health. Hypothalamic-pituitary adrenocortical axis disruptions that lead to changes in gene expression through methylation and the activity of transcription factor proteins are one promising area of research but are confounded by a number of unmeasured factors. Therefore, wok is needed using causally informative designs, such as twin and family studies and intensively longitudinal diary studies.

Effect of women's fertility and sexual development on epigenetic clock: Mendelian randomization study

BACKGROUND AND OBJECTIVES

In observational studies, women's fertility and sexual development traits may have implications for DNA methylation patterns, and pregnancy-related risk factors can also affect maternal DNA methylation patterns. The aim of our study is to disentangle any potential causal associations between women's fertility and sexual development traits and epigenetic clocks, as well as to search for probable mediators by using the Mendelian randomization (MR) method.

METHODS

Instrumental variables for exposures, mediators, and outcomes were adopted from genome-wide association studies data of European ancestry individuals. The potential causal relationship between women's fertility and sexual development traits and four epigenetic clocks were evaluated by inverse variance weighted method and verified by other two methods. Furthermore, we employed multivariable MR (MVMR) adjusting for hypertension, hyperglycemia, BMI changes, and insomnia. Then, combining the MVMR results and previous research, we performed two-step MR to explore the mediating effects of BMI, AFS, and AFB. Multiple sensitivity analyses were further performed to verify the robustness of our findings.

RESULTS

Leveraging two-sample MR analysis, we observed statistically significant associations between earlier age at first birth (AFB) with a higher HannumAge, PhenoAge and GrimAge acceleration(β = - 0.429, 95% CI [- 0.781 to - 0.077], p = 0.017 for HannumAge; β = - 0.571, 95% CI [- 1.006 to - 0.136], p = 0.010 for PhenoAge, and β = - 1.136, 95% CI [- 1.508 to - 0.765], p = 2.03E-09 for GrimAge respectively) and age at first sexual intercourse (AFS) with a higher HannumAge and GrimAge acceleration(β = - 0.175, 95% CI [- 0.336 to - 0.014], p = 0.033 for HannumAge; β = - 0.210, 95% CI [- 0.350 to - 0.070], p = 0.003 for GrimAge, respectively). Further analyses indicated that BMI, AFB and AFS played mediator roles in the path from women's fertility and sexual development traits to epigenetic aging.

CONCLUSIONS

Our study suggested that AFS and AFB are associated with epigenetic aging. These findings may prove valuable in informing the development of prevention strategies and interventions targeted towards women's fertility and sexual development experiences and their relationship with epigenetic aging-related diseases.

Could long-term dialysis vintage and abnormal calcium, phosphorus and iPTH control accelerate aging among the maintenance hemodialysis population?

OBJECTIVE

Aging is a complex process of physiological dysregulation of the body system and is common in hemodialysis patients. However, limited studies have investigated the links between dialysis vintage, calcium, phosphorus, and iPTH control and aging. The purpose of the current study was to examine these associations.

METHODS

During 2020, a cross-sectional study was conducted in 3025 hemodialysis patients from 27 centers in Anhui Province, China. Biological age was calculated by a formula using chronological age and clinical indicators. The absence of the target range for serum phosphorus (0.87-1.45 mmol/L), corrected calcium (2.1-2.5 mmol/L) and iPTH (130-585 pg/mL) were identified as abnormal calcium, phosphorus, and iPTH control.

RESULTS

A total of 1131 hemodialysis patients were included, 59.2% of whom were males (669/1131). The mean (standard deviation) of actual age and biological age were 56.07 (12.79) years and 66.94 (25.88), respectively. The median of dialysis vintage was 4.3 years. After adjusting for the confounders, linear regression models showed patients with abnormal calcium, phosphorus, and iPTH control and on hemodialysis for less than 4.3 years (B = 0.211, p = .002) or on hemodialysis for 4.3 years or more (B = 0.302, p < .001), patients with normal calcium, phosphorus, and iPTH control and on hemodialysis for 4.3 years or more (B = 0.087, p = .013) had a higher biological age.

CONCLUSION

Our findings support the hypothesis that long-term hemodialysis and abnormal calcium, phosphorus, and iPTH control may accelerate aging in the hemodialysis population. Further studies are warrant to verify the significance of maintaining normal calcium-phosphorus metabolism in aging.

Triglyceride-glucose index and cervical vascular function: outpatient-based cohort study

OBJECTIVES

The purpose of this study was to investigate the correlation between triglyceride-glucose (TyG) index and cervical vascular function parameters in the general population without cerebrovascular disease.

MATERIALS AND METHODS

This was a cross-sectional study that recruited a total of 1996 participants without cerebrovascular disease. TyG index was calculated based on fasting triglycerides and glucose. All patients were divided into two groups based on the median TyG index: the high TyG group and the low TyG group. The differences in basic clinical characteristics and neck vascular function parameters between the two groups of participants were compared, and then the correlation between TyG index and neck vascular function parameters was investigated.

RESULTS

Participants with a high TyG index had lower systolic, diastolic, and mean flow velocities in the basilar, vertebral, and internal carotid arteries compared with those with a low TyG index. Participants with a high TyG index had higher pulsatility index in the left vertebral artery and right internal carotid artery, but this difference was not observed in the basilar artery. In addition, TyG index was significantly negatively correlated with systolic, diastolic, and mean flow velocities in the basilar, vertebral, and internal carotid arteries, and the correlation remained after adjusting for confounding factors.

CONCLUSION

In the general population, there was a well-defined correlation between TyG index and cervical vascular function parameters, and increased TyG index was independently associated with reduced cervical vascular blood flow velocity.

Accelerated aging in bipolar disorders: An exploratory study of six epigenetic clocks

Bipolar disorder (BD) is a chronic and severe psychiatric disorder associated with significant medical morbidity and reduced life expectancy. In this study, we assessed accelerated epigenetic aging in individuals with BD using various DNA methylation (DNAm)-based markers. For this purpose, we used five epigenetic clocks (Horvath, Hannum, EN, PhenoAge, and GrimAge) and a DNAm-based telomere length clock (DNAmTL). DNAm profiles were obtained using Infinium MethylationEPIC Arrays from whole-blood samples of 184 individuals with BD. We also estimated blood cell counts based on DNAm levels for adjustment. Significant correlations between chronological age and each epigenetic age estimated using the six different clocks were observed. Following adjustment for blood cell counts, we found that the six epigenetic AgeAccels (age accelerations) were significantly associated with the body mass index. GrimAge AgeAccel was significantly associated with male sex, smoking status and childhood maltreatment. DNAmTL AgeAccel was significantly associated with smoking status. Overall, this study showed that distinct epigenetic clocks are sensitive to different aspects of aging process in BD. Further investigations with comprehensive epigenetic clock analyses and large samples are required to confirm our findings of potential determinants of an accelerated epigenetic aging in BD.

Greater stress and trauma mediate race-related differences in epigenetic age between Black and White young adults in a community sample

Black Americans suffer lower life expectancy and show signs of accelerated aging compared to other Americans. While previous studies observe these differences in children and populations with chronic illness, whether these pathologic processes exist or how these pathologic processes progress has yet to be explored prior to the onset of significant chronic illness, within a young adult population. Therefore, we investigated race-related differences in epigenetic age in a cross-sectional sample of young putatively healthy adults and assessed whether lifetime stress and/or trauma mediate those differences. Biological and psychological data were collected from self-reported healthy adult volunteers within the local New Haven area (399 volunteers, 19.8% Black, mean age: 29.28). Stress and trauma data was collected using the Cumulative Adversity Inventory (CAI) interview, which assessed specific types of stressors, including major life events, traumatic events, work, financial, relationship and chronic stressors cumulatively over time. GrimAge Acceleration (GAA), determined from whole blood collected from participants, measured epigenetic age. In order to understand the impact of stress and trauma on GAA, exploratory mediation analyses were then used. We found cumulative stressors across all types of events (mean difference of 6.9 p = 2.14e-4) and GAA (β = 2.29 years [1.57-3.01, p = 9.70e-10] for race, partial η2 = 0.091, model adjusted R2 = 0.242) were significantly greater in Black compared to White participants. Critically, CAI total score (proportion mediated: 0.185 [0.073-0.34, p = 6e-4]) significantly mediated the relationship between race and GAA. Further analysis attributed this difference to more traumatic events, particularly assaultive traumas and death of loved ones. Our results suggest that, prior to development of significant chronic disease, Black individuals have increased epigenetic age compared to White participants and that increased cumulative stress and traumatic events may contribute significantly to this epigenetic aging difference.

DNA methylation accelerated age as captured by epigenetic clocks influences breast cancer risk

Introduction

Breast cancer continues to be the leading form of cancer among women in the United States. Additionally, disparities across the breast cancer continuum continue to increase for women of historically marginalized populations. The mechanism driving these trends are unclear, however, accelerated biological age may provide key insights into better understanding these disease patterns. Accelerated age measured by DNA methylation using epigenetic clocks is to date the most robust method for estimating accelerated age. Here we synthesize the existing evidence on epigenetic clocks measurement of DNA methylation based accelerated age and breast cancer outcomes.

Methods

Our database searches were conducted from January 2022 to April 2022 and yielded a total of 2,908 articles for consideration. We implemented methods derived from guidance of the PROSPERO Scoping Review Protocol to assess articles in the PubMed database on epigenetic clocks and breast cancer risk.

Results

Five articles were deemed appropriate for inclusion in this review. Ten epigenetic clocks were used across the five articles demonstrating statistically significant results for breast cancer risk. DNA methylation accelerated age varied by sample type. The studies did not consider social factors or epidemiological risk factors. The studies lacked representation of ancestrally diverse populations.

Discussion

DNA methylation based accelerated age as captured by epigenetic clocks has a statistically significant associative relationship with breast cancer risk, however, important social factors that contribute to patterns of methylation were not comprehensively considered in the available literature. More research is needed on DNA methylation based accelerated age across the lifespan including during menopausal transition and in diverse populations. This review demonstrates that DNA methylation accelerated age may provide key insights for tackling increasing rates of U.S. breast cancer incidence and overall disease disparities experienced by women from minoritized backgrounds.

The role of adolescent lifestyle habits in biological aging: A prospective twin study

Background:

Adolescence is a stage of fast growth and development. Exposures during puberty can have long-term effects on health in later life. This study aims to investigate the role of adolescent lifestyle in biological aging.

Methods:

The study participants originated from the longitudinal FinnTwin12 study (n = 5114). Adolescent lifestyle-related factors, including body mass index (BMI), leisure-time physical activity, smoking, and alcohol use, were based on self-reports and measured at ages 12, 14, and 17 years. For a subsample, blood-based DNA methylation (DNAm) was used to assess biological aging with six epigenetic aging measures in young adulthood (21–25 years, n = 824). A latent class analysis was conducted to identify patterns of lifestyle behaviors in adolescence, and differences between the subgroups in later biological aging were studied. Genetic and environmental influences on biological aging shared with lifestyle behavior patterns were estimated using quantitative genetic modeling.

Results:

We identified five subgroups of participants with different adolescent lifestyle behavior patterns. When DNAm GrimAge, DunedinPoAm, and DunedinPACE estimators were used, the class with the unhealthiest lifestyle and the class of participants with high BMI were biologically older than the classes with healthier lifestyle habits. The differences in lifestyle-related factors were maintained into young adulthood. Most of the variation in biological aging shared with adolescent lifestyle was explained by common genetic factors.

Conclusions:

These findings suggest that an unhealthy lifestyle during pubertal years is associated with accelerated biological aging in young adulthood. Genetic pleiotropy may largely explain the observed associations.

Funding:

This work was supported by the Academy of Finland (213506, 265240, 263278, 312073 to J.K., 297908 to M.O. and 341750, 346509 to E.S.), EC FP5 GenomEUtwin (J.K.), National Institutes of Health/National Heart, Lung, and Blood Institute (grant HL104125), EC MC ITN Project EPITRAIN (J.K. and M.O.), the University of Helsinki Research Funds (M.O.), Sigrid Juselius Foundation (J.K. and M.O.), Yrjö Jahnsson Foundation (6868), Juho Vainio Foundation (E.S.) and Päivikki and Sakari Sohlberg foundation (E.S.).

For most animals, events that occur early in life can have a lasting impact on individuals’ health. In humans, adolescence is a particularly vulnerable time when rapid growth and development collide with growing independence and experimentation. An unhealthy lifestyle during this period of rapid cell growth can contribute to later health problems like heart disease, lung disease, and premature death. This is due partly to accelerated biological aging, where the body deteriorates faster than what would be expected for an individual’s chronological age.

One way to track the effects of lifestyle on biological aging is by measuring epigenetic changes. Epigenetic changes consist on adding or removing chemical ‘tags’ on genes. These tags can switch the genes on or off without changing their sequences. Scientists can measure certain epigenetic changes by measuring the levels of methylated DNA – DNA with a chemical ‘tag’ known as a methyl group – in blood samples. Several algorithms – known as ‘epigenetic clocks’ – are available that estimate how fast an individual is aging biologically based on DNA methylation.

Kankaanpää et al. show that unhealthy lifestyles during adolescence may lead to accelerated aging in early adulthood. For their analysis, Kankaanpää et al. used data on the levels of DNA methylation in blood samples from 824 twins between 21 and 25 years old. The twins were participants in the FinnTwin12 study and had completed a survey about their lifestyles at ages 12, 14, and 17.

Kankaanpää et al. classified individuals into five groups depending on their lifestyles. The first three groups, which included most of the twins, contained individuals that led relatively healthy lives. The fourth group contained individuals with a higher body mass index based on their height and weight. Finally, the last group included individuals with unhealthy lifestyles who binge drank, smoked and did not exercise.

After estimating the biological ages for all of the participants, Kankaanpää et al. found that both the individuals with higher body mass indices and those in the group with unhealthy lifestyles aged faster than those who reported healthier lifestyles. However, the results varied depending on which epigenetic clock Kankaanpää et al. used to measure biological aging: clocks that had been developed earlier showed fewer differences in aging between groups; while newer clocks consistently found that individuals in the higher body mass index and unhealthy groups were older. Kankaanpää et al. also showed that shared genetic factors explained both unhealthy lifestyles and accelerated biological aging.

The experiments performed by Kankaanpää et al. provide new insights into the vital role of an individual’s genetics in unhealthy lifestyles and cellular aging. These insights might help scientists identify at risk individuals early in life and try to prevent accelerated aging.