Robust Metabolomic Age Prediction Based on a Wide Selection of Metabolites

Chronological age is a major risk factor for numerous diseases. However, chronological age does not capture the complex biological aging process. The difference between chronological age and biologically driven aging could be more informative in reflecting health status. Here, we set out to develop a metabolomic age prediction model by applying ridge regression and bootstrapping with 826 metabolites (678 endogenous and 148 xenobiotics) measured by an untargeted platform in relatively healthy blood donors aged 18-75 years from the INTERVAL study (N = 11 977; 50.2% men). After bootstrapping internal validation, the metabolomic age prediction models demonstrated high performance with an adjusted R2 of 0.83 using all metabolites and 0.82 using only endogenous metabolites. The former was significantly associated with obesity and cardiovascular disease in the Netherlands Epidemiology of Obesity study (N = 599; 47.0% men; age range = 45-65) due to the contribution of medication-derived metabolites-namely salicylate and ibuprofen-and environmental exposures such as cotinine. Additional metabolomic age prediction models using all metabolites were developed for men and women separately. The models had high performance (R² = 0.85 and 0.86) but shared a moderate correlation of 0.72. Furthermore, we observed 163 sex-dimorphic metabolites, including threonine, glycine, cholesterol, and androgenic and progesterone-related metabolites. Our strongest predictors across all models were novel and included hydroxyasparagine (Model Endo + Xeno β = 4.74), vanillylmandelate (β = 4.07), and 5,6-dihydrouridine (β = -4.2). Our study presents a robust metabolomic age model that reveals distinct sex-based age-related metabolic patterns and illustrates the value of including xenobiotic to enhance metabolomic prediction accuracy.

Stress across the lifecourse and adult mental and physical health outcomes

INTRODUCTION

Economic, social, and traumatic stressors have been shown to impact mental and physical health. Few studies have considered whether different domains of stressors have a differential effect on health outcomes or have considered stressors across the lifecourse. We characterize stress cumulatively (life stress) and across different domains and examine their relation to adult mental and physical health using prospectively collected data from the DISPAR study.

METHODS

At 4 timepoints (birth, age 9, 15, and 50), economic, relational, and traumatic stressors were assessed, and interviews were conducted between 1959 and 2012. Experiences of major discrimination were assessed at age 50. Life stress scores and domain-specific stress scores, (occurring in either childhood or adulthood), were created. The Kessler distress scale, self-reported health, and objective measured allostatic load (AL) were assessed at age 50.

RESULTS

Adjusting for race and sex, life stress was associated with all 3 outcomes. Domain-specific analysis showed that only SES stressors impacted all outcomes (poorer self-rated health, higher distress, and higher AL). Relational stress was associated with distress only; experiences of discrimination were associated with poor self-rated health and distress.

CONCLUSION

Stressors across the lifecourse have been proposed to affect wear and tear on multiple bodily systems and to affect multiple health outcomes. Our empirical test supported this hypothesis in a 50-year old cohort and in particular the impact of economic stress across physical and mental health outcomes.

Association between plant and animal protein and biological aging: findings from the UK Biobank

PURPOSE

This study aimed to evaluate the relationship between plant protein, animal protein and biological aging through different dimensions of biological aging indices. Then explore the effects of substitution of plant protein, animal protein, and their food sources on biological aging.

METHODS

The data came from 79,294 participants in the UK Biobank who completed at least two 24-h dietary assessments. Higher Klemera-Doubal Method Biological Age (HKDM-BA), higher PhenoAge (HPA), higher allostatic load (HAL), and longer telomere length (LTL) were estimated to assess biological aging. Logistic regression was used to estimate protein-biological aging associations. Substitution model was performed to assess the effect of dietary protein substitutions.

RESULTS

Plant protein intake was inversely associated with HKDM-BA, HPA, HAL, and positively associated with LTL (odds ratios after fully adjusting and comparing the highest to the lowest quartile: 0.83 (0.79-0.88) for HKDM-BA, 0.86 (0.72-0.94) for HPA, 0.90 (0.85-0.95) for HAL, 1.06 (1.01-1.12) for LTL), while animal protein was not correlated with the four indices. Substituting 5% of energy intake from animal protein with plant protein, replacing red meat or poultry with whole grains, and replacing red or processed meat with nuts, were negatively associated with HKDM-BA, HPA, HAL and positively associated with LTL. However, an inverse association was found when legumes were substituted for yogurt. Gamma glutamyltransferase, alanine aminotransferase, and aspartate aminotransferase mediated the relationship between plant protein and HKDM-BA, HPA, HAL, and LTL (mediation proportion 11.5-24.5%; 1.9-6.7%; 2.8-4.5%, respectively).

CONCLUSION

Higher plant protein intake is inversely associated with biological aging. Although there is no association with animal protein, food with animal proteins displayed a varied correlation.

Sociodemographic and Lifestyle Factors and Epigenetic Aging in US Young Adults: NIMHD Social Epigenomics Program

Importance

Epigenetic clocks represent molecular evidence of disease risk and aging processes and have been used to identify how social and lifestyle characteristics are associated with accelerated biological aging. However, most research is based on samples of older adults who already have measurable chronic disease.

Objective

To investigate whether and how sociodemographic and lifestyle characteristics are associated with biological aging in a younger adult sample across a wide array of epigenetic clock measures.

Design, Setting, and Participants

This cohort study was conducted using data from the National Longitudinal Study of Adolescent to Adult Health, a US representative cohort of adolescents in grades 7 to 12 in 1994 followed up for 25 years to 2018 over 5 interview waves. Participants who provided blood samples at wave V (2016-2018) were analyzed, with samples tested for DNA methylation (DNAm) in 2021 to 2024. Data were analyzed from February 2023 to May 2024.

Exposure

Sociodemographic (sex, race and ethnicity, immigrant status, socioeconomic status, and geographic location) and lifestyle (obesity status by body mass index [BMI] in categories of reference range or underweight [<25], overweight [25 to <30], obesity [30 to <40], and severe obesity [≥40]; exercise level; tobacco use; and alcohol use) characteristics were assessed.

Main Outcome and Measure

Biological aging assessed from banked blood DNAm using 16 epigenetic clocks.

Results

Data were analyzed from 4237 participants (mean [SD] age, 38.4 [2.0] years; percentage [SE], 51.3% [0.01] female and 48.7% [0.01] male; percentage [SE], 2.7% [<0.01] Asian or Pacific Islander, 16.7% [0.02] Black, 8.7% [0.01] Hispanic, and 71.0% [0.03] White). Sociodemographic and lifestyle factors were more often associated with biological aging in clocks trained to estimate morbidity and mortality (eg, PhenoAge, GrimAge, and DunedinPACE) than clocks trained to estimate chronological age (eg, Horvath). For example, the β for an annual income less than $25 000 vs $100 000 or more was 1.99 years (95% CI, 0.45 to 3.52 years) for PhenoAgeAA, 1.70 years (95% CI, 0.68 to 2.72 years) for GrimAgeAA, 0.33 SD (95% CI, 0.17 to 0.48 SD) for DunedinPACE, and -0.17 years (95% CI, -1.08 to 0.74 years) for Horvath1AA. Lower education, lower income, higher obesity levels, no exercise, and tobacco use were associated with faster biological aging across several clocks; associations with GrimAge were particularly robust (no college vs college or higher: β = 2.63 years; 95% CI, 1.67-3.58 years; lower vs higher annual income: <$25 000 vs ≥$100 000: β = 1.70 years; 95% CI, 0.68-2.72 years; severe obesity vs no obesity: β = 1.57 years; 95% CI, 0.51-2.63 years; no weekly exercise vs ≥5 bouts/week: β = 1.33 years; 95% CI, 0.67-1.99 years; current vs no smoking: β = 7.16 years; 95% CI, 6.25-8.07 years).

Conclusions and Relevance

This study found that important social and lifestyle factors were associated with biological aging in a nationally representative cohort of younger adults. These findings suggest that molecular processes underlying disease risk may be identified in adults entering midlife before disease is manifest and inform interventions aimed at reducing social inequalities in heathy aging and longevity.

Adopting Mechanistic Molecular Biology Approaches in Exposome Research for Causal Understanding

Through investigating the combined impact of the environmental exposures experienced by an individual throughout their lifetime, exposome research provides opportunities to understand and mitigate negative health outcomes. While current exposome research is driven by epidemiological studies that identify associations between exposures and effects, new frameworks integrating more substantial population-level metadata, including electronic health and administrative records, will shed further light on characterizing environmental exposure risks. Molecular biology offers methods and concepts to study the biological and health impacts of exposomes in experimental and computational systems. Of particular importance is the growing use of omics readouts in epidemiological and clinical studies. This paper calls for the adoption of mechanistic molecular biology approaches in exposome research as an essential step in understanding the genotype and exposure interactions underlying human phenotypes. A series of recommendations are presented to make the necessary and appropriate steps to move from exposure association to causation, with a huge potential to inform precision medicine and population health. This includes establishing hypothesis-driven laboratory testing within the exposome field, supported by appropriate methods to read across from model systems research to human.

The Sociodemographic and Lifestyle Correlates of Epigenetic Aging in a Nationally Representative U.S. Study of Younger Adults

Importance

Epigenetic clocks represent molecular evidence of disease risk and aging processes and have been used to identify how social and lifestyle characteristics are associated with accelerated biological aging. However, most of this research is based on older adult samples who already have measurable chronic disease.

Objective

To investigate whether and how sociodemographic and lifestyle characteristics are related to biological aging in a younger adult sample across a wide array of epigenetic clock measures.

Design

Nationally representative prospective cohort study.

Setting

United States (U.S.).

Participants

Data come from the National Longitudinal Study of Adolescent to Adult Health, a national cohort of adolescents in grades 7-12 in U.S. in 1994 followed for 25 years over five interview waves. Our analytic sample includes participants followed-up through Wave V in 2016-18 who provided blood samples for DNA methylation (DNAm) testing (n=4237) at Wave V.

Exposure

Sociodemographic (sex, race/ethnicity, immigrant status, socioeconomic status, geographic location) and lifestyle (obesity status, exercise, tobacco, and alcohol use) characteristics.

Main Outcome

Biological aging assessed from blood DNAm using 16 epigenetic clocks when the cohort was aged 33-44 in Wave V.

Results

While there is considerable variation in the mean and distribution of epigenetic clock estimates and in the correlations among the clocks, we found sociodemographic and lifestyle factors are more often associated with biological aging in clocks trained to predict current or dynamic phenotypes (e.g., PhenoAge, GrimAge and DunedinPACE) as opposed to clocks trained to predict chronological age alone (e.g., Horvath). Consistent and strong associations of faster biological aging were found for those with lower levels of education and income, and those with severe obesity, no weekly exercise, and tobacco use.

Conclusions and Relevance

Our study found important social and lifestyle factors associated with biological aging in a nationally representative cohort of younger-aged adults. These findings indicate that molecular processes underlying disease risk can be identified in adults entering midlife before disease is manifest and represent useful targets for interventions to reduce social inequalities in heathy aging and longevity.

Key Points

Question: Are epigenetic clocks, measures of biological aging developed mainly on older-adult samples, meaningful for younger adults and associated with sociodemographic and lifestyle characteristics in expected patterns found in prior aging research?Findings: Sociodemographic and lifestyle factors were associated with biological aging in clocks trained to predict morbidity and mortality showing accelerated aging among those with lower levels of education and income, and those with severe obesity, no weekly exercise, and tobacco use.Meaning: Age-related molecular processes can be identified in younger-aged adults before disease manifests and represent potential interventions to reduce social inequalities in heathy aging and longevity.

Sex differences in epigenetic age in Mediterranean high longevity regions

Sex differences in aging manifest in disparities in disease prevalence, physical health, and lifespan, where women tend to have greater longevity relative to men. However, in the Mediterranean Blue Zones of Sardinia (Italy) and Ikaria (Greece) are regions of centenarian abundance, male-female centenarian ratios are approximately one, diverging from the typical trend and making these useful regions in which to study sex differences of the oldest old. Additionally, these regions can be investigated as examples of healthy aging relative to other populations. DNA methylation (DNAm)-based predictors have been developed to assess various health biomarkers, including biological age, Pace of Aging, serum interleukin-6 (IL-6), and telomere length. Epigenetic clocks are biological age predictors whose deviation from chronological age has been indicative of relative health differences between individuals, making these useful tools for interrogating these differences in aging. We assessed sex differences between the Horvath, Hannum, GrimAge, PhenoAge, Skin and Blood, and Pace of Aging predictors from individuals in two Mediterranean Blue Zones and found that men displayed positive epigenetic age acceleration (EAA) compared to women according to all clocks, with significantly greater rates according to GrimAge (β = 3.55; p = 1.22 × 10^-12), Horvath (β = 1.07; p = 0.00378) and the Pace of Aging (β = 0.0344; p = 1.77 × 10^-08). Other DNAm-based biomarkers findings indicated that men had lower DNAm-predicted serum IL-6 scores (β = -0.00301, p = 2.84 × 10^-12), while women displayed higher DNAm-predicted proportions of regulatory T cells than men from the Blue Zone (p = 0.0150, 95% Confidence Interval [0.00131, 0.0117], Cohen's d = 0.517). All clocks showed better correlations with chronological age in women from the Blue Zones than men, but all clocks showed large mean absolute errors (MAE >30 years) in both sexes, except for PhenoAge (MAE <5 years). Thus, despite their equal survival to older ages in these Mediterranean Blue Zones, men in these regions remain biologically older by most measured DNAm-derived metrics than women, with the exception of the IL-6 score and proportion of regulatory T cells.

Toxicoepigenetics and Environmental Health: Challenges and Opportunities

The rapidly growing field of toxicoepigenetics seeks to understand how toxicant exposures interact with the epigenome to influence disease risk. Toxicoepigenetics is a promising field of environmental health research, as integrating epigenetics into the field of toxicology will enable a more thorough evaluation of toxicant-induced disease mechanisms as well as the elucidation of the role of the epigenome as a biomarker of exposure and disease and possible mediator of exposure effects. Likewise, toxicoepigenetics will enhance our knowledge of how environmental exposures, lifestyle factors, and diet interact to influence health. Ultimately, an understanding of how the environment impacts the epigenome to cause disease may inform risk assessment, permit noninvasive biomonitoring, and provide potential opportunities for therapeutic intervention. However, the translation of research from this exciting field into benefits for human and animal health presents several challenges and opportunities. Here, we describe four significant areas in which we see opportunity to transform the field and improve human health by reducing the disease burden caused by environmental exposures. These include (1) research into the mechanistic role for epigenetic change in environment-induced disease, (2) understanding key factors influencing vulnerability to the adverse effects of environmental exposures, (3) identifying appropriate biomarkers of environmental exposures and their associated diseases, and (4) determining whether the adverse effects of environment on the epigenome and human health are reversible through pharmacologic, dietary, or behavioral interventions. We then highlight several initiatives currently underway to address these challenges.

The Socioeconomic Gradient in Epigenetic Ageing Clocks: Evidence from the Multi-Ethnic Study of Atherosclerosis and the Health and Retirement Study

Epigenetic clocks have been widely used to predict disease risk in multiple tissues or cells. Their success as a measure of biological ageing has prompted research on the connection between epigenetic pathways of ageing and the socioeconomic gradient in health and mortality. However, studies examining social correlates of epigenetic ageing have yielded inconsistent results. We conducted a comprehensive, comparative analysis of associations between various dimensions of socioeconomic status (SES) (education, income, wealth, occupation, neighbourhood environment, and childhood SES) and eight epigenetic clocks in two well-powered US ageing studies: The Multi-Ethnic Study of Atherosclerosis (MESA) (n = 1,211) and the Health and Retirement Study (HRS) (n = 4,018). In both studies, we found robust associations between SES measures in adulthood and the GrimAge and DunedinPoAm clocks (Bonferroni-corrected p-value < 0.01). In the HRS, significant associations with the Levine and Yang clocks were also evident. These associations were only partially mediated by smoking, alcohol consumption, and obesity, which suggests that differences in health behaviours alone cannot explain the SES gradient in epigenetic ageing in older adults. Further analyses revealed concurrent associations between polygenic risk for accelerated intrinsic epigenetic ageing, SES, and the Levine clock, indicating that genetic risk and social disadvantage may contribute additively to faster biological aging.

Accelerated epigenetic aging and inflammatory/immunological profile (ipAGE) in patients with chronic kidney disease

Chronic kidney disease (CKD) is defined by a reduced estimated glomerular filtration rate (eGFR). This failure can be related to a phenotype of accelerated aging. In this work, we considered 76 patients with end-stage renal disease (ESRD) and 83 healthy controls. We concomitantly evaluated for the first time two measures that can be informative of the rate of aging, i.e., whole blood DNA methylation using the Illumina Infinium EPIC array and plasma levels of a selection of inflammatory/immunological proteins using multiplex immunoassays. First of all, we demonstrated accelerated aging in terms of the most common epigenetic age estimators in CKD patients. Moreover, we developed a new clock/predictor of age based on the inflammatory/immunological profile (ipAGE) and identified the inflammatory/immunological biomarkers differentially expressed between cases and controls. IpAGE appeared to be more sensitive than epigenetic clocks in quantifying the accelerated aging phenotype of ESRD patients. Interestingly, we did not find any correlation between the age acceleration evaluated according to the epigenetic clocks and ipAGE in either the ESRD group or the control group. On the whole, our data show a consistent accelerated aging phenotype in ESRD patients, which is better appreciated by quantifying the underlying inflammatory processes (inflammaging) by ipAGE than by using epigenetic clocks.

GrimAge Outperforms Other Epigenetic Clocks in the Prediction of Age-Related Clinical Phenotypes and All-Cause Mortality

The aging process is characterized by the presence of high interindividual variation between individuals of the same chronical age prompting a search for biomarkers that capture this heterogeneity. Epigenetic clocks measure changes in DNA methylation levels at specific CpG sites that are highly correlated with calendar age. The discrepancy resulting from the regression of DNA methylation age on calendar age is hypothesized to represent a measure of biological aging with a positive/negative residual signifying age acceleration (AA)/deceleration, respectively. The present study examines the associations of 4 epigenetic clocks-Horvath, Hannum, PhenoAge, GrimAge-with a wide range of clinical phenotypes (walking speed, grip strength, Fried frailty, polypharmacy, Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MOCA), Sustained Attention Reaction Time, 2-choice reaction time), and with all-cause mortality at up to 10-year follow-up, in a sample of 490 participants in the Irish Longitudinal Study on Ageing (TILDA). HorvathAA and HannumAA were not predictive of health; PhenoAgeAA was associated with 4/9 outcomes (walking speed, frailty MOCA, MMSE) in minimally adjusted models, but not when adjusted for other social and lifestyle factors. GrimAgeAA by contrast was associated with 8/9 outcomes (all except grip strength) in minimally adjusted models, and remained a significant predictor of walking speed, .polypharmacy, frailty, and mortality in fully adjusted models. Results indicate that the GrimAge clock represents a step-improvement in the predictive utility of the epigenetic clocks for identifying age-related decline in an array of clinical phenotypes promising to advance precision medicine.

Associations of Age, Sex, Race/Ethnicity, and Education With 13 Epigenetic Clocks in a Nationally Representative U.S. Sample: The Health and Retirement Study

BACKGROUND

Many DNA methylation-based indicators have been developed as summary measures of epigenetic aging. We examine the associations between 13 epigenetic clocks, including 4 second generation clocks, as well as the links of the clocks to social, demographic, and behavioral factors known to be related to health outcomes: sex, race/ethnicity, socioeconomic status, obesity, and lifetime smoking pack-years.

METHODS

The Health and Retirement Study is the data source which is a nationally representative sample of Americans over age 50. Assessment of DNA methylation was based on the EPIC chip and epigenetic clocks were developed based on existing literature.

RESULTS

The clocks vary in the strength of their relationships with age, with each other and with independent variables. Second generation clocks trained on health-related characteristics tend to relate more strongly to the sociodemographic and health behaviors known to be associated with health outcomes in this age group.

CONCLUSIONS

Users of this publicly available data set should be aware that epigenetic clocks vary in their relationships to age and to variables known to be related to the process of health change with age.

Neighborhood environment, social cohesion, and epigenetic aging

Living in adverse neighborhood environments has been linked to risk of aging-related diseases and mortality; however, the biological mechanisms explaining this observation remain poorly understood. DNA methylation (DNAm), a proposed mechanism and biomarker of biological aging responsive to environmental stressors, offers promising insight into potential molecular pathways. We examined associations between three neighborhood social environment measures (poverty, quality, and social cohesion) and three epigenetic clocks (Horvath, Hannum, and PhenoAge) using data from the Detroit Neighborhood Health Study (n=158). Using linear regression models, we evaluated associations in the total sample and stratified by sex and social cohesion. Neighborhood quality was associated with accelerated DNAm aging for Horvath age acceleration (β = 1.8; 95% CI: 0.4, 3.1), Hannum age acceleration (β = 1.7; 95% CI: 0.4, 3.0), and PhenoAge acceleration (β = 2.1; 95% CI: 0.4, 3.8). In models stratified on social cohesion, associations of neighborhood poverty and quality with accelerated DNAm aging remained elevated for residents living in neighborhoods with lower social cohesion, but were null for those living in neighborhoods with higher social cohesion. Our study suggests that living in adverse neighborhood environments can speed up epigenetic aging, while positive neighborhood attributes may buffer effects.

Weight management intervention identifies association of decreased DNA methylation age with improved functional age measures in older adults with obesity

Background

Assessing functional ability is an important component of understanding healthy aging. Objective measures of functional ability include grip strength, gait speed, sit-to-stand time, and 6-min walk distance. Using samples from a weight loss clinical trial in older adults with obesity, we examined the association between changes in physical function and DNA-methylation-based biological age at baseline and 12 weeks in 16 individuals. Peripheral blood DNA methylation was measured (pre/post) with the Illumina HumanMethylationEPIC array and the Hannum, Horvath, and PhenoAge DNA methylation age clocks were used. Linear regression models adjusted for chronological age and sex tested the relationship between DNA methylation age and grip strength, gait speed, sit-to-stand, and 6-min walk.

Results

Participant mean weight loss was 4.6 kg, and DNA methylation age decreased 0.8, 1.1, and 0.5 years using the Hannum, Horvath, and PhenoAge DNA methylation clocks respectively. Mean grip strength increased 3.2 kg. Decreased Hannum methylation age was significantly associated with increased grip strength (β = −0.30, p = 0.04), and increased gait speed (β = 0.02, p = 0.05), in adjusted models. Similarly, decreased methylation age using the PhenoAge clock was associated with significantly increased gait speed (β = 0.02, p = 0.04). A decrease in Horvath DNA methylation age and increase in physical functional ability did not demonstrate a significant association.

Conclusions

The observed relationship between increased physical functional ability and decreased biological age using DNA methylation clocks demonstrate the potential utility of DNA methylation clocks to assess interventional approaches to improve health in older obese adults.

Trial registration: National Institute on Aging (NIA), NCT03104192. Posted April 7, 2017, https://clinicaltrials.gov/ct2/show/NCT03104192

Quest for a summary measure of biological age: the health and retirement study

Measures of biological age and its components have been shown to provide important information about individual health and prospective change in health as there is clear value in being able to assess whether someone is experiencing accelerated or decelerated aging. However, how to best assess biological age remains a question. We compare prediction of health outcomes using existing summary measures of biological age with a measure created by adding novel biomarkers related to aging to measures based on more conventional clinical chemistry and exam measures. We also compare the explanatory power of summary biological age measures compared to the individual biomarkers used to construct the measures. To accomplish this, we examine how well biological age, phenotypic age, and expanded biological age and five sets of individual biomarkers explain variability in four major health outcomes linked to aging in a large, nationally representative cohort of older Americans. We conclude that different summary measures of accelerated aging do better at explaining different health outcomes, and that chronological age has greater explanatory power for both cognitive dysfunction and mortality than the summary measures. In addition, we find that there is reduction in the variance explained in health outcomes when indicators are combined into summary measures, and that combining clinical indicators with more novel markers related to aging does best at explaining health outcomes. Finally, it is hard to define a set of assays that parsimoniously explains the greatest amount of variance across the range of health outcomes studied here. All of the individual markers considered were related to at least one of the health outcomes.

Aging and Allostasis: Using Bayesian Network Analytics to Explore and Evaluate Allostatic Markers in the Context of Aging

Allostatic load reflects the cumulative strain on organic functions that may gradually evolve into overt disease. Our aim was to evaluate the allostatic parameters in the context of aging, and identify the parameters that may be suitable for an allostatic load index for elderly people (>60 years). From previously published studies, 11 allostatic (bio)markers could be identified that sustain sufficient variability with aging to capture meaningful changes in health status. Based on reported statistics (prevalence of a biomarker and its associated outcome, and/or an odds/risk ratio relating these two), seven of these could be adopted in a Bayesian Belief Network (BBN), providing the probability of “disturbed” allostasis in any given elder. Additional statistical analyses showed that changes in IL-6 and BMI contributed the most to a “disturbed” allostasis, indicating their prognostic potential in relation to deteriorating health in otherwise generally healthy elderly. In this way, and despite the natural decline in variance that irrevocably alters the prognostic relevance of most allostatic (bio)markers with aging, it appeared possible to outline an allostatic load index specifically for the elderly. The allostatic parameters here identified might consequently be considered a useful basis for future quantitative modelling in the context of (healthy) aging.

Nutritional Epigenomics and Age-Related Disease

Recent advances in epigenetic research have enabled the development of epigenetic clocks, which have greatly enhanced our ability to investigate molecular processes that contribute to aging and age-related disease. These biomarkers offer the potential to measure the effect of environmental exposures linked to dynamic changes in DNA methylation, including nutrients, as factors in age-related disease. They also offer a compelling insight into how imbalances in the supply of nutrients, particularly B-vitamins, or polymorphisms in regulatory enzymes involved in 1-carbon metabolism, the key pathway that supplies methyl groups for epigenetic reactions, may influence epigenetic age and interindividual disease susceptibility. Evidence from recent studies is critically reviewed, focusing on the significant contribution of the epigenetic clock to nutritional epigenomics and its impact on health outcomes and age-related disease. Further longitudinal studies and randomized nutritional interventions are required to advance the field.

Childhood Adversity and Pubertal Development Among Puerto Rican Boys and Girls

OBJECTIVE

Evidence stemming largely from retrospective studies suggests that childhood adversity (CA) is associated with earlier age at menarche, a marker of pubertal timing, among girls. Little is known about associations with pubertal tempo among boys or racial/ethnic minorities. We examined the association between CA and timing and tempo of pubertal development among boys and girls.

METHODS

The Boricua Youth Study is a longitudinal study of Puerto Rican youth residing in the San Juan metro area in Puerto Rico and the South Bronx, New York. CA was based on caretaker reports of parental loss and parental maladjustment and youth reports of child maltreatment and exposure to violence. Youth completed the Pubertal Development Scale (PDS) yearly for 3 years. In linear mixed models stratified by sex, we examined the association between CA and pubertal timing and tempo, adjusting for site, socioeconomic status, and age.

RESULTS

Among the 1949 children who were 8 years or older by wave 3, cumulative CA was associated with higher PDS scores among girls compared with girls not exposed to CA (PDS score: 2.63 [95% confidence interval {CI} = 2.55-2.71] versus 2.48 [95% CI = 2.37-2.58]). In contrast, among boys, experiencing adversities was associated with lower pubertal developmental stage or later timing (PDS: 1.77 [95% CI = 1.67-1.87] versus 1.97 [95% CI = 1.85-2.10]) compared with those not exposed to adversities.

CONCLUSIONS

Associations between CA and pubertal development may vary by sex. Understanding the etiological role of adversities on pubertal development and identifying targets for intervention are of utmost importance in ameliorating the impact of CA on child health.