Quantification of biological aging in young adults

Relationship between fatty acid intake and aging: a Mendelian randomization study

BACKGROUND

Observational studies have previously shown a possible link between fatty acids and aging-related diseases, raising questions about its health implications. However, the causal relationship between the two remains uncertain.

METHODS

Univariable and multivariable Mendelian randomization (MR) was used to analyze the relationship between five types of fatty acids-polyunsaturated fatty acid (PUFA), monounsaturated fatty acid (MUFA), saturated fatty acid (SFA), Omega-6 fatty acid (Omega-6 FA), and Omega-3 fatty acid (Omega-3 FA) and three markers of aging: telomere length (TL), frailty index (FI), and facial aging (FclAg). The primary approach for Mendelian randomization (MR) analysis involved utilizing the inverse variance weighted (IVW) method, with additional supplementary methods employed.

RESULTS

Univariate MR analysis revealed that MUFA, PUFA, SFA, and Omega-6 fatty acids were positively associated with TL (MUFA OR: 1.019, 95% CI: 1.006-1.033; PUFA OR: 1.014, 95% CI: 1.002-1.026; SFA OR: 1.016, 95% CI: 1.002-1.031; Omega-6 FAs OR=1.031, 95% CI: 1.006-1.058). PUFA was also associated with a higher FI (OR: 1.033, 95% CI: 1.009-1.057). In multivariate MR analysis, after adjusting for mutual influences among the five fatty acids, MUFA and PUFA were positively independently associated with TL (MUFA OR: 1.1508, 95% CI = 1.0724-1.2350; PUFA OR: 1.1670, 95% CI = 1.0497-1.2973, while SFA was negatively correlated (OR: 0.8005, 95% CI: 0.7045-0.9096).

CONCLUSIONS

Our research presents compelling evidence of a causal association between certain fatty acids and indicators of the aging process. In particular, MUFA and PUFA may play a role in slowing down the aging process, while SFAs may contribute to accelerated aging. These findings could have significant implications for dietary recommendations aimed at promoting healthy aging.

Utilizing epigenetics to study the shared nature of development and biological aging across the lifespan

Recently, biological aging has been quantified in DNA-methylation samples of older adults and applied as so-called "methylation profile scores" (MPSs) in separate target samples, including samples of children. This nascent research indicates that (1) biological aging can be quantified early in the life course, decades before the onset of aging-related disease, (2) is affected by common environmental predictors of childhood development, and (3) shows overlap with "developmental processes" (e.g., puberty). Because the MPSs were computed using algorithms developed in adults, these studies indicate a molecular link between childhood environments, development, and adult biological aging. Yet, if MPSs can be used to connect development and aging, previous research has only traveled one way, deriving MPSs developed in adults and applying them to samples of children. Researchers have not yet quantified epigenetic measures that reflect the pace of child development, and tested whether resulting MPSs are associated with physical and psychological aging. In this perspective I posit that combining measures of biological aging with new quantifications of child development has the power to address fundamental questions about life span: How are development and experience in childhood related to biological aging in adulthood? And what is aging?

Association between sleep traits and biological aging risk: a Mendelian randomization study based on 157 227 cases and 179 332 controls

STUDY OBJECTIVES

To investigate whether sleep traits are associated with the risk of biological aging using a case-control design with Mendelian randomization (MR) analyses.

METHODS

We studied 336 559 participants in the UK Biobank cohort, including 157 227 cases of accelerated biological aging and 179 332 controls. PhenoAge, derived from clinical traits, estimated biological ages, and the discrepancies from chronological age were defined as age accelerations (PhenoAgeAccel). Sleep behaviors were assessed with a standardized questionnaire. propensity score matching matched control participants to age-accelerated participants, and a conditional multivariable logistic regression model estimated odds ratio (OR) and 95% confidence intervals (95% CI). Causal relationships between sleep traits and PhenoAgeAccel were explored using linear and nonlinear MR methods.

RESULTS

A U-shaped association was found between sleep duration and PhenoAgeAccel risk. Short sleepers had a 7% higher risk (OR = 1.07; 95% CI: 1.03 to 1.11), while long sleepers had an 18% higher risk (OR = 1.18; 95% CI: 1.15 to 1.22), compared to normal sleepers (6-8 hours/day). Evening chronotype was linked to higher PhenoAgeAccel risk than morning chronotype (OR = 1.14; 95% CI: 1.10 to 1.18), while no significant associations were found for insomnia or snoring. Morning chronotype had a protective effect on PhenoAgeAccel risk (OR = 0.87, 95% CI: 0.79 to 0.95) per linear MR analysis. Genetically predicted sleep duration showed a U-shaped relationship with PhenoAgeAccel, suggesting a nonlinear association (pnonlinear < 0.001).

CONCLUSIONS

The study suggests that improving sleep can slow biological aging, highlighting the importance of optimizing sleep as an intervention to mitigate aging's adverse effects.

The geriatric nutrition risk index is longitudinally associated with incident Sarcopenia: evidence from a 5-year prospective cohort

BACKGROUND

Previous studies investigating the association between the geriatric nutrition risk index (GNRI) and sarcopenia either lacked longitudinal evidence or narrowly focused on specific populations.

AIMS

We aimed to reveal longitudinal associations of GNRI with sarcopenia risk in community-dwelling Chinese. We also investigated interaction effects of potential factors on such associations.

METHODS

We included participants aged ≥ 50 years with sufficient data from the WCHAT study who did not have sarcopenia at baseline and completed sarcopenia assessment during follow-up. GNRI was calculated according to the formula based on serum albumin, height and weight. Sarcopenia was diagnosed according to the 2019 AWGS consensus. Longitudinal associations between GNRI and sarcopenia were estimated by logistic regression with GNRI as either a continuous or categorical variable by tertiles, using generalized estimating equations (GEE) as sensitivity analyses. Subgroup analyses by potential covariates were conducted to detect interaction effects.

RESULTS

A total of 1907 participants without baseline sarcopenia were finally included, of whom 327 (17.1%) developed incident sarcopenia during 5-year follow-up. After controlling for confounders, sarcopenia risk decreased with each one standard deviation increase in GNRI (ORadjusted=0.36, 95% CI 0.31-0.43), and it also decreased successively from the lowest (< 111.2) through middle (111.2-117.7) to the highest (≥ 117.8) tertile of the GNRI level (P for trend < 0.001). Similar results were yielded by GEE. Such associations generally remained robust across subgroups with distinct characteristics, while significant differences were observed between different age groups (≥ 65 vs. <65 years) (interaction P-value < 0.05).

CONCLUSION

GNRI is longitudinally associated with sarcopenia risk with possibly age-specific differences in association magnitude, which holds implications for policymakers to conduct population-based risk assessment.

Educational Mobility, Pace of Aging, and Lifespan Among Participants in the Framingham Heart Study

Importance

People who complete more education live longer lives with better health. New evidence suggests that these benefits operate through a slowed pace of biological aging. If so, measurements of the pace of biological aging could offer intermediate end points for studies of how interventions to promote education will affect healthy longevity.

Objective

To test the hypothesis that upward educational mobility is associated with a slower pace of biological aging and increased longevity.

Design, Setting, and Participants

This prospective cohort study analyzed data from 3 generations of participants in the Framingham Heart Study: (1) the original cohort, enrolled beginning in 1948; (2) the Offspring cohort, enrolled beginning in 1971; and (3) the Gen3 cohort, enrolled beginning in 2002. A 3-generation database was constructed to quantify intergenerational educational mobility. Mobility data were linked with blood DNA-methylation data collected from the Offspring cohort in 2005 to 2008 (n = 1652) and the Gen3 cohort in 2009 to 2011 (n = 1449). Follow-up is ongoing. Data analysis was conducted from June 2022 to November 2023 using data obtained from the National Institutes of Health database of Genotypes and Phenotypes (dbGaP).

Exposure

Educational mobility was measured by comparing participants' educational outcomes with those of their parents.

Main Outcomes and Measures

The pace of biological aging was measured from whole-blood DNA-methylation data using the DunedinPACE epigenetic clock. For comparison purposes, the analysis was repeated using 4 other epigenetic clocks. Survival follow-up was conducted through 2019.

Results

This study analyzed data from 3101 participants from the Framingham Heart Study; 1652 were in the Offspring cohort (mean [SD] age, 65.57 [9.22] years; 764 [46.2%] male) and 1449 were in the Gen3 cohort (mean [SD] age, 45.38 [7.83] years; 691 [47.7%] male). Participants who were upwardly mobile in educational terms tended to have slower pace of aging in later life (r = -0.18 [95% CI, -0.23 to -0.13]; P < .001). This pattern of association was similar across generations and held in within-family sibling comparisons. There were 402 Offspring cohort participants who died over the follow-up period. Upward educational mobility was associated with lower mortality risk (hazard ratio, 0.89 [95% CI, 0.81 to 0.98]; P = .01). Slower pace of aging accounted for approximately half of this association.

Conclusions and Relevance

This cohort study's findings support the hypothesis that interventions to promote educational attainment may slow the pace of biological aging and promote longevity. Epigenetic clocks have potential as near-term outcome measures of intervention effects on healthy aging. Experimental evidence is needed to confirm findings.

Dissipative scaling of development and aging in multicellular organisms

Evolution, self-replication and ontogenesis are highly dynamic, irreversible and self-organizing processes dissipating energy. While progress has been made to decipher the role of thermodynamics in cellular fission, it is not yet clear how entropic balances shape organism growth and aging. This paper derives a general dissipation theory for the life history of organisms. It implies a self-regulated energy dissipation facilitating exponential growth within a hierarchical and entropy lowering self-organization. The theory predicts ceilings in energy expenditures imposed by geometric constrains, which promote thermal optimality during development, and a dissipative scaling across organisms consistent with ecological scaling laws combining isometric and allometric terms. The theory also illustrates how growing organisms can tolerate damage through continuous extension and production of new dissipative structures low in entropy. However, when organisms reduce their rate of cell division and reach a steady adult state, they become thermodynamically unstable, increase internal entropy by accumulating damage, and age.

A late-life neurogenetic signature of exposure to combat stress - A monozygotic discordant twin study

Animal models suggest that experiencing high-stress levels induces changes in amygdalar circuitry and gene expression. In humans, combat exposure has been shown to alter amygdalar responsivity and connectivity, but abnormalities have been indicated to normalize at least partially upon the termination of stress exposure. In contrast, other evidence suggests that combat exposure continues to exert influence on exposed individuals well beyond deployment and homecoming, as indicated by longitudinal psychosocial evidence from veterans, and observation of greater health decline in veterans late in life. Accordingly, the experience of combat stress early in life may affect amygdalar responsivity late in life, a possibility requiring careful consideration of the confounding effects of aging, genetic factors, and symptoms of post-traumatic stress disorder. Here, we investigated amygdalar responsivity in a unique sample of 16 male monozygotic (MZ) twin pairs in their sixties, where one but not the other sibling had been exposed to combat stress in early adulthood. Forty years after combat experience, a generally blunted amygdalar response was observed in combat-exposed veterans compared to their non-exposed twin siblings. Spatial associations between these phenotypical changes and patterns of gene expression in the brain were found for genes involved in the synaptic organization and chromatin structure. Protein-protein interactions among the set of identified genes pointed to histone modification mechanisms. We conclude that exposure to combat stress early in life continues to impact brain function beyond the termination of acute stress and appears to exert prolonged effects on amygdalar function later in life via neurogenetic mechanisms.

Consequences of heterogeneity in aging: parental age at death predicts midlife all-cause mortality and hospitalization in a Swedish national birth cohort

BACKGROUND

The processes that underlie aging may advance at different rates in different individuals and an advanced biological age, relative to the chronological age, is associated with increased risk of disease and death. Here we set out to quantify the extent to which heterogeneous aging shapes health outcomes in midlife by following a Swedish birth-cohort and using parental age at death as a proxy for biological age in the offspring.

METHODS

We followed a nationwide Swedish birth cohort (N = 89,688) between the ages of 39 and 66 years with respect to hospitalizations and death. Cox regressions were used to quantify the association, in the offspring, between parental age at death and all-cause mortality, as well as hospitalization for conditions belonging to the 10 most common ICD-10 chapters.

RESULTS

Longer parental lifespan was consistently associated with reduced risks of hospitalization and all-cause mortality. Differences in risk were mostly evident from before the age of 50 and persisted throughout the follow-up. Each additional decade of parental survival decreased the risk of offspring all-cause mortality by 22% and risks of hospitalizations by 9 to 20% across the 10 diseases categories considered. The number of deaths and hospitalizations attributable to having parents not living until old age were 1500 (22%) and 11,000 (11%) respectively.

CONCLUSIONS

Our findings highlight that increased parental lifespan is consistently associated with health benefits in the offspring across multiple outcomes and suggests that heterogeneous aging processes have clinical implications already in midlife.

Cellular reprogramming as a tool to model human aging in a dish

The design of human model systems is highly relevant to unveil the underlying mechanisms of aging and to provide insights on potential interventions to extend human health and life span. In this perspective, we explore the potential of 2D or 3D culture models comprising human induced pluripotent stem cells and transdifferentiated cells obtained from aged or age-related disorder-affected donors to enhance our understanding of human aging and to catalyze the discovery of anti-aging interventions.

Fasting-mimicking diet causes hepatic and blood markers changes indicating reduced biological age and disease risk

In mice, periodic cycles of a fasting mimicking diet (FMD) protect normal cells while killing damaged cells including cancer and autoimmune cells, reduce inflammation, promote multi-system regeneration, and extend longevity. Here, we performed secondary and exploratory analysis of blood samples from a randomized clinical trial (NCT02158897) and show that 3 FMD cycles in adult study participants are associated with reduced insulin resistance and other pre-diabetes markers, lower hepatic fat (as determined by magnetic resonance imaging) and increased lymphoid to myeloid ratio: an indicator of immune system age. Based on a validated measure of biological age predictive of morbidity and mortality, 3 FMD cycles were associated with a decrease of 2.5 years in median biological age, independent of weight loss. Nearly identical findings resulted from  a second clinical study (NCT04150159). Together these results provide initial support for beneficial effects of the FMD on multiple cardiometabolic risk factors and biomarkers of biological age.

Self-perceptions of aging: A conceptual and empirical overview

This article defines self-perceptions of aging (SPA) as individuals' perceptions, expectations, and experiences regarding their own process of growing old(er). As such, SPA are considered a critically important element of the aging self. Furthermore, the authors present a heuristic model that positions adults' SPA within a lifespan developmental and cultural-societal context and elaborates distal and proximal antecedents, process modes, and developmental outcomes. The remainder of the article summarizes recent empirical findings and discusses future challenges and directions.

Educational patterning in biological health seven years apart: Findings from the Tromsø Study

BACKGROUND

Social-to-biological processes is one set of mechanisms underlying the relationship between social position and health. However, very few studies have focused on the relationship between social factors and biology at multiple time points. This work investigates the relationship between education and the dynamic changes in a composite Biological Health Score (BHS) using two time points seven years apart in a Norwegian adult population.

METHODS

We used data from individuals aged 30 years and above who participated in Tromsø6 (2007-2008) and Tromsø7 (2015-2016) (n = 8117). BHS was defined using ten biomarkers measured from blood samples and representing three physiological systems (cardiovascular, metabolic, inflammatory). The higher the BHS, the poorer the health status.

FINDINGS

Linear regression models carried out on BHS revealed a strong educational gradient at two distinct time points but also over time. People with lower educational attainment were at higher risk of poor biological health at a given time point (βlow education Tromsø6=0.30 [95 %-CI=0.18-0.43] and βlow education Tromsø7=0.30 [95 %-CI=0.17-0.42]). They also presented higher longitudinal BHS compared to people with higher education (βlow education = 0.89 [95 %-CI=0.56-1.23]). Certain biomarkers related to the cardiovascular system and the metabolic system were strongly socially distributed, even after adjustment for sex, age, health behaviours and body mass index.

CONCLUSION

This longitudinal analysis highlights that participants with lower education had their biological health deteriorated to a greater extent over time compared to people with higher education. Our findings provide added evidence of the biological embodiment of social position, particularly with respect to dynamic aspects for which little evidence exists.

Biological age as estimated by baseline circulating metabolites is associated with incident diabetes and mortality

OBJECTIVES

It is unclear how metabolomic assessment of biological aging performs in non-White populations and whether such an approach can predict future mortality. We aimed to evaluate the application of serum metabolomics combined with machine learning methodologies to predict incident diabetes and mortality in a Thai population.

DESIGN, SETTING AND PARTICIPANTS

We analyzed serum samples and mortality data over 11 years from among 454 participants with no previous history of diabetes and with a fasting plasma glucose ≥85th percentile (5.4 mmol/L) but <7 mmol/L.

MEASUREMENTS

Untargeted serum metabolomics were assessed using liquid chromatography/mass spectrometry. A deep artificial neural network was used to predict biological age based on serum metabolite profiles and chronological age.

RESULTS

The mean age of participants was 40.5 ± 6.4 years, and 70.8% were men. We found a significant positive correlation between metabolomic age and chronological age (r = 0.71, P < 0.001). After 5 years, 61 of 404 participants with available glycated hemoglobin status (15.1%) progressed to diabetes. Chronological age was associated with incident diabetes but was not significant (P = 0.08), after adjusting for BMI and sex. Metabolomic age was significantly related to incident diabetes after controlling for BMI and sex (P < 0.05). Over the 11-year follow-up, 10 participants died owing to non-accidental causes. When metabolomic age and chronological age were included together in the model, metabolomic age (but not chronological age) was associated with mortality, independent of age, sex, and BMI. Among all identifiable metabolites, beta-D-mannosylphosphodecaprenyl and phosphatidylserines were the five leading metabolites associated with mortality.

CONCLUSION

We concluded that serum metabolomic profile was associated with incident diabetes as well as mortality over our 11-year study period, which may render it potentially useful in assessing biological aging in humans.

The biological age model for evaluating the degree of aging in centenarians

BACKGROUND

Biological age (BA) has been used to assess individuals' aging conditions. However, few studies have evaluated BA models' applicability in centenarians.

METHODS

Important organ function examinations were performed in 1798 cases of the longevity population (80∼115 years old) in Hainan, China. Eighty indicators were selected that responded to nutritional status, cardiovascular function, liver and kidney function, bone metabolic function, endocrine system, hematological system, and immune system. BA models were constructed using multiple linear regression (MLR), principal component analysis (PCA), Klemera and Doubal method (KDM), random forest (RF), support vector machine (SVM), extreme gradient boosting (XGBoost), and light gradient boosting machine (lightGBM) methods. A tenfold crossover validated the efficacy of models.

RESULTS

A total of 1398 participants were enrolled, of whom centenarians accounted for 49.21%. Seven aging markers were obtained, including estimated glomerular filtration rate, albumin, pulse pressure, calf circumference, body surface area, fructosamine, and complement 4. Eight BA models were successfully constructed, namely MLR, PCA, KDM1, KDM2, RF, SVM, XGBoost and lightGBM, which had the worst R2 of 0.45 and the best R2 of 0.92. The best R2 for cross-validation was KDM2 (0.89), followed by PCA (0.62).

CONCLUSION

In this study, we successfully applied eight methods, including traditional methods and machine learning, to construct models of biological age, and the performance varied among the models.

Methodology Advances in Vertebrate Age Estimation

Age is a core metric in vertebrate management, and the correct estimation of the age of an individual plays a principal role in comprehending animal behavior, identifying genealogical information, and assessing the potential reproductive capacity of populations. Vertebrates have a vertebral column and a distinct head containing a developed brain; they have played an important role in the study of biological evolution. However, biological age estimations constantly exhibit large deviations due to the diversity of vertebrate taxon species, sample types, and determination methods. To systematically and comprehensively understand age estimation methods in different situations, we classify the degree of damage to vertebrates during sample collection, present the sample types and their applications, list commonly applied methods, present methodological recommendations based on the combination of accuracy and implementability, and, finally, predict future methods for vertebrate age assessments, taking into account the current level of research and requirements. Through comprehensive data gathering and compilation, this work serves as an introduction and summary for those who are eager to catch up on related fields and facilitates the rapid and accurate selection of an evaluation method for researchers engaged in related research. This is essential to promote animal conservation and guide the smooth implementation of conservation management plans.

The immunity and redox clocks in mice, markers of lifespan

Immune function and redox markers are used for estimating the aging rate, namely biological age (BA). However, it is unknown if this BA and its changes can be reflected in longevity. Thus, we must quantify BA in experimental animals. In peritoneal immune cells of 202 female mice (ICR/CD1) in different ages, 10 immune and 6 redox parameters were evaluated to construct two mathematical models for BA quantification in mice by multiple linear regression. Immune and redox parameters were selected as independent variables and chronological age as dependent, developing two models: the Immunity and the Redox Clocks, reaching both an adjusted R2 of 80.9% and a standard error of 6.38 and 8.57 weeks, respectively. Both models were validated in a different group of healthy mice obtaining a Pearson's correlation coefficient of 0.844 and 0.800 (p < 0.001) between chronological and BA. Furthermore, they were applied to adult prematurely aging mice, which showed a higher BA than non-prematurely aging mice. Moreover, after positive and negative lifestyle interventions, mice showed a lower and higher BA, respectively, than their age-matched controls. In conclusion, the Immunity and Redox Clocks allow BA quantification in mice and both the ImmunolAge and RedoxAge in mice relate to lifespan.

Human lifespan and sex-specific patterns of resilience to disease: a retrospective population-wide cohort study

BACKGROUND

Slower paces of aging are related to lower risk of developing diseases and premature death. Therefore, the greatest challenge of modern societies is to ensure that the increase in lifespan is accompanied by an increase in health span. To better understand the differences in human lifespan, new insight concerning the relationship between lifespan and the age of onset of diseases, and the ability to avoid them is needed. We aimed to comprehensively study, at a population-wide level, the sex-specific disease patterns associated with human lifespan.

METHODS

Observational data from the SIDIAP database of a cohort of 482,058 individuals that died in Catalonia (Spain) at ages over 50 years old between the 1st of January 2006 and the 30th of June 2022 were included. The time to the onset of the first disease in multiple organ systems, the prevalence of escapers, the percentage of life free of disease, and their relationship with lifespan were evaluated considering sex-specific traits.

RESULTS

In the study cohort, 50.4% of the participants were women and the mean lifespan was 83 years. The results show novel relationships between the age of onset of disease, health span, and lifespan. The key findings include: Firstly, the onset of both single and multisystem diseases is progressively delayed as lifespan increases. Secondly, the prevalence of escapers is lower in lifespans around life expectancy. Thirdly, the number of disease-free systems decreases until individuals reach lifespans around 87-88 years old, at which point it starts to increase. Furthermore, long-lived women are less susceptible to multisystem diseases. The associations between health span and lifespan are system-dependent, and disease onset and the percentage of life spent free of disease at the time of death contribute to explaining lifespan variability. Lastly, the study highlights significant system-specific disparities between women and men.

CONCLUSIONS

Health interventions focused on delaying aging and age-related diseases should be the most effective in increasing not only lifespan but also health span. The findings of this research highlight the relevance of Electronic Health Records in studying the aging process and open up new possibilities in age-related disease prevention that should assist primary care professionals in devising individualized care and treatment plans.

Posttraumatic stress disorder, trauma, and accelerated biological aging among post-9/11 veterans

People who experience trauma and develop posttraumatic stress disorder (PTSD) are at increased risk for poor health. One mechanism that could explain this risk is accelerated biological aging, which is associated with the accumulation of chronic diseases, disability, and premature mortality. Using data from 2309 post-9/11 United States military veterans who participated in the VISN 6 MIRECC's Post-Deployment Mental Health Study, we tested whether PTSD and trauma exposure were associated with accelerated rate of biological aging, assessed using a validated DNA methylation (DNAm) measure of epigenetic aging-DunedinPACE. Veterans with current PTSD were aging faster than those who did not have current PTSD, β = 0.18, 95% CI [0.11, 0.27], p < .001. This effect represented an additional 0.4 months of biological aging each year. Veterans were also aging faster if they reported more PTSD symptoms, β = 0.13, 95% CI [0.09, 0.16], p < 0.001, or higher levels of trauma exposure, β = 0.09, 95% CI [0.05, 0.13], p < 0.001. Notably, veterans with past PTSD were aging more slowly than those with current PTSD, β = -0.21, 95% CI [-0.35, -0.07], p = .003. All reported results accounted for age, gender, self-reported race/ethnicity, and education, and remained when controlling for smoking. Our findings suggest that an accelerated rate of biological aging could help explain how PTSD contributes to poor health and highlights the potential benefits of providing efficacious treatment to populations at increased risk of trauma and PTSD.

Associations between biological ageing and the risk of, genetic susceptibility to, and life expectancy associated with rheumatoid arthritis: a secondary analysis of two observational studies

BACKGROUND

Rheumatoid arthritis is a chronic autoimmune disorder that affects life expectancy. Accelerated biological ageing is thought to be a major risk factor for age-related diseases, but its role in rheumatoid arthritis remains uncertain. We aimed to assess the associations between biological ageing and risk of rheumatoid arthritis and genetic susceptibility to the disease. We also aimed to assess the effect of biological ageing on the life expectancy of people with rheumatoid arthritis.

METHODS

We calculated the chronological age-adjusted biological age-by both the Klemera-Doubal method (KDMAge) and phenotypic age (PhenoAge)-as a surrogate measure for biological ageing in participants from the US National Health and Nutrition Examination Survey (NHANES) and UK Biobank study. KDMAge or PhenoAge acceleration was defined as the residual of the regression of KDMAge or PhenoAge based on chronological age. Participants with accelerated biological ageing had KDMAge or PhenoAge acceleration values greater than 0, whereas those without accelerated ageing had values less than or equal to 0. We did cross-sectional analyses to assess the association between biological ageing and prevalent rheumatoid arthritis in both cohorts and prospective analyses to assess the association between biological ageing and incident rheumatoid arthritis in the UK Biobank. Logistic regression and Cox proportional hazards models were used to analyse these associations. Polygenic risk scores were used to establish genetic susceptibility to rheumatoid arthritis and to analyse the interaction between biological ageing and genetic risk. We also assessed the association between life expectancy and biological ageing status in people with rheumatoid arthritis.

FINDINGS

In the cross-sectional analyses, each 1-year increase in age-adjusted biological age was associated with an increase in the risk of rheumatoid arthritis of between 1% and 10%. In the NHANES, individuals with accelerated ageing had a higher risk of rheumatoid arthritis than non-accelerated ageing individuals, with odds ratios of 1·21 (95% CI 1·03-1·42; p=0·018) for KDMAge acceleration and 1·46 (1·26-1·69; p<0·0001) for PhenoAge acceleration. Similarly, in the UK Biobank, the risk of rheumatoid arthritis was increased in individuals with accelerated ageing compared with individuals with no accelerated ageing (KDMAge odds ratio 1·96 [95% CI 1·71-2·24]; PhenoAge 2·71 [2·51-2·92]). In the prospective analyses of the UK Biobank population, accelerated biological ageing was associated with an increased risk of incident rheumatoid arthritis as measured by both KDMAge (hazard ratio 1·27 [95% CI 1·03-1·55]) and PhenoAge (1·70 [1·52-1·92]). Among participants with high genetic predisposition to rheumatoid arthritis, accelerated biological ageing was associated with an increased risk of incident disease, and we noted significant additive interactions between accelerated biological ageing and genetic risk. At age 45 years, people with rheumatoid arthritis had reduced life expectancy compared with those without rheumatoid arthritis. Among people with rheumatoid arthritis, accelerated biological ageing was associated with reduced life expectancy compared with not having accelerated biological ageing.

INTERPRETATION

Accelerated biological ageing could increase the risk of rheumatoid arthritis, especially among people with high genetic risk, and could reduce the life expectancy of people with rheumatoid arthritis. The identification of populations with accelerated biological ageing has important implications for reducing the risk of rheumatoid arthritis and of lowered life expectancy.

FUNDING

National Natural Science Foundation of China.

Geroscience-Centric Perspective for Geriatric Psychiatry: Integrating Aging Biology With Geriatric Mental Health Research

The geroscience hypothesis asserts that physiological aging is caused by a small number of biological pathways. Despite the explosion of geroscience research over the past couple of decades, the research on how serious mental illnesses (SMI) affects the biological aging processes is still in its infancy. In this review, we aim to provide a critical appraisal of the emerging literature focusing on how we measure biological aging systematically, and in the brain and how SMIs affect biological aging measures in older adults. We will also review recent developments in the field of cellular senescence and potential targets for interventions for SMIs in older adults, based on the geroscience hypothesis.

Profiling an integrated network of cellular senescence and immune resilience measures in natural aging: a prospective multi-cohort study

Background

Biological aging begins decades before the onset of age-related clinical conditions and is mediated by both cellular senescence and declining adaptive immune function. These processes are functionally related with the rate of senescent cell accumulation dependent upon a balance between induction and immune clearance. We previously showed that biomarkers in these domains can identify patients at-risk of surgery-related adverse events. Here, we describe evidence of clinical relevance in early aging and metabolic phenotypes in a general adult population.

Methods

We enrolled a total of 482 participants (ages 25-90) into two prospective, cross-sectional healthy aging cohorts. Expression of biomarkers of adaptive immune function and cellular senescence (SapereX) was measured in CD3+ T cells isolated from peripheral blood.

Findings

We established a network of biomarkers of adaptive immune function that correlate with cellular senescence and associate with early aging phenotypes. SapereX immune components associated with a decrease in CD4+ T cells, an increase in cytotoxic CD8+ T cells, and a loss of CD8+ naïve T cells (Pearson correlation 0.3-0.6). These components also associated with a metric of immune resilience, an ability to withstand antigen challenge and inflammation. In contrast, SapereX components were only weakly associated with GlycanAge (Pearson correlation 0.03-0.15) and commonly used DNA methylation clocks (Pearson correlation 0-0.25). Finally, SapereX biomarkers, in particular p16, were associated with chronic inflammation and metabolic dysregulation.

Interpretation

Measurement of SapereX biomarkers may capture essential elements of the relationship between cellular senescence and dysregulated adaptive immune function and may provide a benchmark for clinically relevant health decisions.

Study protocol on effectiveness of yoga practice on composite biomarker age predictors (yBioAge) in an elderly Indian cohort- two-armed open label randomized controlled trial

INTRODUCTION

The recent development of robust indices to quantify biological aging, along with the dynamic epidemiological transitions of population aging generate the unmet need to examine the extent up to which potential interventions can delay, halt or temporarily modulate aging trajectories.

METHODS AND ANALYSIS

The study is a two-armed, open label randomised controlled trial. We aim to recruit 166 subjects, aged 60-75 years from the residential communities and old age clubs in Bangalore city, India, who will undergo randomisation into intervention or control arms (1:1). Intervention will include yoga sessions tailored for the older adults, 1 h per day for 5 days a week, spread for 12 months. Data would be collected at the baseline, 26th week and 52nd week. The primary outcome of the study is estimation in biological age with yoga practice. The secondary outcomes will include cardinal mechanistic indicators of aging- telomere length, interleukin-6 (IL-6), tumor necrosis factor receptor II (TNF-RII), high sensitivity c-reactive protein (hsCRP)], insulin signaling [insulin and IGF1], renal function [cystatin], senescence [growth differentiating factor 15 (GDF-15)] and cardiovascular function [N-terminal B-type natriuretic peptides (NT-proBNP)]. Analyses will be by intention-to-treat model.

ETHICS & DISSEMINATION

The study is approved by the Institutional Ethics Committee of Swami Vivekananda Yoga Anusandhana Samsthana University, Bangalore (ID:RES/IEC-SVYASA/242/2022). Written informed consent will be obtained from each participant prior to inclusion.

TRIAL REGISTRATION NUMBER

CTRI/2022/07/044442.

Biological Age in Congenital Heart Disease-Exploring the Ticking Clock

Over the past 50 years, there has been a major shift in age distribution of patients with congenital heart disease (CHD) thanks to significant advancements in medical and surgical treatment. Patients with CHD are, however, never cured and face unique challenges throughout their lives. In this review, we discuss the growing data suggesting accelerated aging in this population. Adults with CHD are more often and at a younger age confronted with age-related cardiovascular complications such as heart failure, arrhythmia, and coronary artery disease. These can be related to the original birth defect, complications of correction, or any residual defects. In addition, and less deductively, more systemic age-related complications are seen earlier, such as renal dysfunction, lung disease, dementia, stroke, and cancer. The occurrence of these complications at a younger age makes it imperative to further map out the aging process in patients across the spectrum of CHD. We review potential feasible markers to determine biological age and provide an overview of the current data. We provide evidence for an unmet need to further examine the aging paradigm as this stresses the higher need for care and follow-up in this unique, newly aging population. We end by exploring potential approaches to improve lifespan care.

Associations Between Longitudinal Loneliness, DNA Methylation Age Acceleration, and Cognitive Functioning

OBJECTIVES

Loneliness may influence aging biomarkers related to cognitive functioning, for example, through accelerated DNA methylation (DNAm) aging.

METHODS

In the present study, we tested whether six common DNAm age acceleration measures mediated the effects of baseline loneliness and five different longitudinal loneliness trajectories on general cognitive ability, immediate memory recall, delayed memory recall, and processing speed in 1,814 older adults in the Health and Retirement Study.

RESULTS

We found that baseline loneliness and individuals who belong to the highest loneliness trajectories had poorer general cognitive ability and memory scores. Only DNAm age acceleration measures that index physiological comorbidities, unhealthy lifestyle factors (e.g., smoking), and mortality risk-mediated effects of baseline loneliness on general cognitive ability and memory functioning but not processing speed. These same DNAm measures mediated effects of the moderate-but-declining loneliness trajectory on cognitive functioning. Additionally, immediate and delayed memory scores were mediated by GrimAge Accel in the lowest and two highest loneliness trajectory groups. Total and mediated effects of loneliness on cognitive functioning outcomes were mainly accounted for by demographic, social, psychological, and physiological covariates, most notably self-rated health, depressive symptomatology, objective social isolation, and body mass index.

DISCUSSION

Current findings suggest that DNAm biomarkers of aging, particularly GrimAge Accel, have promise for explaining the prospective association between loneliness and cognitive functioning outcomes.

Patterns and Life Course Determinants of Black-White Disparities in Biological Age Acceleration: A Decomposition Analysis

Despite the prominence of the weathering hypothesis as a mechanism underlying racialized inequities in morbidity and mortality, the life course social and economic determinants of Black-White disparities in biological aging remain inadequately understood. This study uses data from the Health and Retirement Study (n = 6,782), multivariable regression, and Kitagawa-Blinder-Oaxaca decomposition to assess Black-White disparities across three measures of biological aging: PhenoAge, Klemera-Doubal biological age, and homeostatic dysregulation. It also examines the contributions of racial differences in life course socioeconomic and stress exposures and vulnerability to those exposures to Black-White disparities in biological aging. Across the outcomes, Black individuals exhibited accelerated biological aging relative to White individuals. Decomposition analyses showed that racial differences in life course socioeconomic exposures accounted for roughly 27% to 55% of the racial disparities across the biological aging measures, and racial disparities in psychosocial stress exposure explained 7% to 11%. We found less evidence that heterogeneity in the associations between social exposures and biological aging by race contributed substantially to Black-White disparities in biological aging. Our findings offer new evidence of the role of life course social exposures in generating disparities in biological aging, with implications for understanding age patterns of morbidity and mortality risks.

Organ aging signatures in the plasma proteome track health and disease

Animal studies show aging varies between individuals as well as between organs within an individual1-4, but whether this is true in humans and its effect on age-related diseases is unknown. We utilized levels of human blood plasma proteins originating from specific organs to measure organ-specific aging differences in living individuals. Using machine learning models, we analysed aging in 11 major organs and estimated organ age reproducibly in five independent cohorts encompassing 5,676 adults across the human lifespan. We discovered nearly 20% of the population show strongly accelerated age in one organ and 1.7% are multi-organ agers. Accelerated organ aging confers 20-50% higher mortality risk, and organ-specific diseases relate to faster aging of those organs. We find individuals with accelerated heart aging have a 250% increased heart failure risk and accelerated brain and vascular aging predict Alzheimer's disease (AD) progression independently from and as strongly as plasma pTau-181 (ref. 5), the current best blood-based biomarker for AD. Our models link vascular calcification, extracellular matrix alterations and synaptic protein shedding to early cognitive decline. We introduce a simple and interpretable method to study organ aging using plasma proteomics data, predicting diseases and aging effects.

An examination of the validity of neuropsychological and physical testing batteries in Latin-American adults aged over 55 years

BACKGROUND

Valid and reliable measurements are necessary to understand and monitor age-related changes.

AIMS

To describe the factor structure and provide validity evidence of a neuropsychological and a physical testing batteries using factor analysis.

METHODS

We performed a secondary analysis of data from the Epidemiology and Development of Alzheimer's Disease (EDAD) project. Community-dwelling adults aged 55 to 85 years underwent comprehensive physical and neuropsychological assessments. An exploratory factor analysis was performed on both assessment batteries. The models were later confirmed with a random subsample using confirmatory factor analysis.

RESULTS

Data from 238 adults (163 females and 75 males) was included. The neuropsychological model revealed a four-factor structure formed by "Executive Functioning", "Verbal Memory", "Logical Memory", and "Labeling And Reading" (Extraction Sums of Squared Loadings [ESSL] = 56.41% explained variance; Standardized Root Mean Square Residual [SRMSR] = 0.06; Comparative Fit Index [CFI] = 0.98). The physical model was formed by a two-factor structure including "Health-related Fitness and "Functional Fitness" (ESSL = 50.54% explained variance; SRMSR = 0.07; CFI = 0.93).

DISCUSSION

To our knowledge, this is the first study to analyze the structure of comprehensive testing batteries for the Latin-American older adults. Our analysis contributes to the understanding of theoretical constructs that are evaluated in the EDAD project.

CONCLUSION

Our findings provide validity evidence for simplified and reduced testing batteries, which imply shorter testing times and fewer resources.

Association of Vascular Aging With Cardiovascular Disease in Middle-Aged Chinese People: A Prospective Cohort Study

Background

Whether middle-aged individuals with a greater difference between chronological age and vascular age show a lower cardiovascular disease risk remains to be clarified.

Objectives

This study sought to examine whether individuals with supernormal vascular aging (VA) have a lower cardiovascular disease risk than do individuals with normal VA.

Methods

This prospective cohort study included 20,917 middle-aged (40-60 years) participants from the Kailuan Study. VA was defined as the predicted age in a multivariate regression model, including classic cardiovascular risk factors and pulsed wave velocity. The chronological age minus the VA was defined as the Δ-age, and the 10th and 90th percentiles of the Δ-age were used as cutoffs to define early VA and supernormal VA, respectively. The outcome was a composite of myocardial infarction, hospital admission for heart failure, and stroke. The study used Cox proportional hazards regression to examine the association between the VA categories and the incident cardiovascular outcome.

Results

During the median 4.6-year follow-up period, 584 endpoint events were observed. After adjusting for potential variables, when compared with the normal VA group, the supernormal VA group had a decreased rate of cardiovascular events (HR: 0.47; 95% CI: 0.35-0.64), and the early VA group had an increased rate (HR: 1.90; 95% CI: 1.22-2.95) of cardiovascular events.

Conclusions

Individuals with supernormal VA are at a lower risk of cardiovascular events, and individuals with early VA are at a higher risk of cardiovascular events than individuals with normal VA. Further characterization may provide novel insight into future preventive strategies against cardiovascular disease.

Biological age and brain age in midlife: relationship to multimorbidity and mental health

Biological age and brain age estimated using biological and neuroimaging measures have recently emerged as surrogate aging biomarkers shown to be predictive of diverse health outcomes. As aging underlies the development of many chronic conditions, surrogate aging biomarkers capture health at the whole person level, having the potential to improve our understanding of multimorbidity. Our study investigates whether elevated biological age and brain age are associated with an increased risk of multimorbidity using a large dataset from the Midlife in the United States Refresher study. Ensemble learning is utilized to combine multiple machine learning models to estimate biological age using a comprehensive set of biological markers. Brain age is obtained using Gaussian processes regression and neuroimaging data. Our study is the first to examine the relationship between accelerated brain age and multimorbidity. Furthermore, it is the first attempt to explore how biological age and brain age are related to multimorbidity in mental health. Our findings hold the potential to advance the understanding of disease accumulation and their relationship with aging.

Advanced biological ageing predicts future risk for neurological diagnoses and clinical examination findings

Age is a dominant risk factor for some of the most common neurological diseases. Biological ageing encompasses interindividual variation in the rate of ageing and can be calculated from clinical biomarkers or DNA methylation data amongst other approaches. Here, we tested the hypothesis that a biological age greater than one's chronological age affects the risk of future neurological diagnosis and the development of abnormal signs on clinical examination. We analysed data from the Swedish Adoption/Twin Study of Aging (SATSA): a cohort with 3175 assessments of 802 individuals followed-up over several decades. Six measures of biological ageing were generated: two physiological ages (created from bedside clinical measurements and standard blood tests) and four blood methylation age measures. Their effects on future stroke, dementia or Parkinson's disease diagnosis, or development of abnormal clinical signs, were determined using survival analysis, with and without stratification by twin pairs. Older physiological ages were associated with ischaemic stroke risk; for example one standard deviation advancement in baseline PhenoAgePhys or KDMAgePhys residual increased future ischaemic stroke risk by 29.2% [hazard ratio (HR): 1.29, 95% confidence interval (CI) 1.06-1.58, P = 0.012] and 42.9% (HR 1.43, CI 1.18-1.73, P = 3.1 × 10-4), respectively. In contrast, older methylation ages were more predictive of future dementia risk, which was increased by 29.7% (HR 1.30, CI 1.07-1.57, P = 0.007) per standard deviation advancement in HorvathAgeMeth. Older physiological ages were also positively associated with future development of abnormal patellar or pupillary reflexes, and the loss of normal gait. Measures of biological ageing can predict clinically relevant pathology of the nervous system independent of chronological age. This may help to explain variability in disease risk between individuals of the same age and strengthens the case for trials of geroprotective interventions for people with neurological disorders.

The 24-h activity cycle and cardiovascular outcomes: establishing biological plausibility using arterial stiffness as an intermediate outcome

This review proposes a biologically plausible working model for the relationship between the 24-h activity cycle (24-HAC) and cardiovascular disease. The 24-HAC encompasses moderate-to-vigorous physical activity (MVPA), light physical activity, sedentary behavior (SB), and sleep. MVPA confers the greatest relative cardioprotective effect, when considering MVPA represents just 2% of the day if physical activity guidelines (30 min/day) are met. While we have well-established guidelines for MVPA, those for the remaining activity behaviors are vague. The vague guidelines are attributable to our limited mechanistic understanding of the independent and additive effects of these behaviors on the cardiovascular system. Our proposed biological model places arterial stiffness, a measure of vascular aging, as the key intermediate outcome. Starting with prolonged exposure to SB or static standing, we propose that the reported transient increases in arterial stiffness are driven by a cascade of negative hemodynamic effects following venous pooling. The subsequent autonomic, metabolic, and hormonal changes further impair vascular function. Vascular dysfunction can be offset by using mechanistic-informed interruption strategies and by engaging in protective behaviors throughout the day. Physical activity, especially MVPA, can confer protection by chronically improving endothelial function and associated protective mechanisms. Conversely, poor sleep, especially in duration and quality, negatively affects hormonal, metabolic, autonomic, and hemodynamic variables that can confound the physiological responses to next-day activity behaviors. Our hope is that the proposed biologically plausible working model will assist in furthering our understanding of the effects of these complex, interrelated activity behaviors on the cardiovascular system.

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

Objective

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

Methods

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

Results

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

Conclusion

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

Determining a multimodal aging clock in a cohort of Chinese women

BACKGROUND

Translating aging rejuvenation strategies into clinical practice has the potential to address the unmet needs of the global aging population. However, to successfully do so requires precise quantification of aging and its reversal in a way that encompasses the complexity and variation of aging.

METHODS

Here, in a cohort of 113 healthy women, tiled in age from young to old, we identified a repertoire of known and previously unknown markers associated with age based on multimodal measurements, including transcripts, proteins, metabolites, microbes, and clinical laboratory values, based on which an integrative aging clock and a suite of customized aging clocks were developed.

FINDINGS

A unified analysis of aging-associated traits defined four aging modalities with distinct biological functions (chronic inflammation, lipid metabolism, hormone regulation, and tissue fitness), and depicted waves of changes in distinct biological pathways peak around the third and fifth decades of life. We also demonstrated that the developed aging clocks could measure biological age and assess partial aging deceleration by hormone replacement therapy, a prevalent treatment designed to correct hormonal imbalances.

CONCLUSIONS

We established aging metrics that capture systemic physiological dysregulation, a valuable framework for monitoring the aging process and informing clinical development of aging rejuvenation strategies.

FUNDING

This work was supported by the National Natural Science Foundation of China (32121001), the National Key Research and Development Program of China (2022YFA1103700 and 2020YFA0804000), the National Natural Science Foundation of China (81502304), and the Quzhou Technology Projects (2022K46).

Socioeconomic Inequalities and Molecular Risk for Aging in Young Adulthood

Diverse manifestations of biological aging often reflect disparities in socioeconomic status (SES). In this paper, we examine associations between indicators of SES and an mRNA-based aging signature during young adulthood, before clinical indications of aging are common. We use data from wave V (2016-2018) of the National Longitudinal Study of Adolescent to Adult Health, a nationally representative study of adults aged 33-43 years, with transcriptomic data from a subset of 2,491 participants. Biological aging is measured using 1) a composite transcriptomic aging signature previously identified by Peters et al.'s out-of-sample meta-analysis (Nat Commun. 2015;6:8570) and 2) 9 subsets that represent functional pathways of coexpressed genes. SES refers to income, education, occupation, subjective social status, and a composite measure combining these 4 dimensions. We examine hypothesized mechanisms through which SES could affect aging: body mass index, smoking, health insurance status, difficulty paying bills, and psychosocial stress. We find that SES-especially the composite measure and income-is associated with transcriptomic aging and immune, mitochondrial, ribosomal, lysosomal, and proteomal pathways. Counterfactual mediational models suggest that the mediators partially account for these associations. The results thus reveal that numerous biological pathways associated with aging are already linked to SES in young adulthood.

Changes in methylation-based aging in women who do and do not develop breast cancer

BACKGROUND

Breast cancer survivors have increased incidence of age-related diseases, suggesting that some survivors may experience faster biological aging.

METHODS

Among 417 women enrolled in the prospective Sister Study cohort, DNA methylation data were generated on paired blood samples collected an average of 7.7 years apart and used to calculate 3 epigenetic metrics of biological aging (PhenoAgeAccel, GrimAgeAccel, and Dunedin Pace of Aging Calculated from the Epigenome [DunedinPACE]). Approximately half (n = 190) the women sampled were diagnosed and treated for breast cancer between blood draws, whereas the other half (n = 227) remained breast cancer-free. Breast tumor characteristics and treatment information were abstracted from medical records.

RESULTS

Among women who developed breast cancer, diagnoses occurred an average of 3.5 years after the initial blood draw and 4 years before the second draw. After accounting for covariates and biological aging metrics measured at baseline, women diagnosed and treated for breast cancer had higher biological aging at the second blood draw than women who remained cancer-free as measured by PhenoAgeAccel (standardized mean difference [β] = 0.13, 95% confidence interval [CI) = 0.00 to 0.26), GrimAgeAccel (β = 0.14, 95% CI = 0.03 to 0.25), and DunedinPACE (β = 0.37, 95% CI = 0.24 to 0.50). In case-only analyses assessing associations with different breast cancer therapies, radiation had strong positive associations with biological aging (PhenoAgeAccel: β = 0.39, 95% CI = 0.19 to 0.59; GrimAgeAccel: β = 0.29, 95% CI = 0.10 to 0.47; DunedinPACE: β = 0.25, 95% CI = 0.02 to 0.48).

CONCLUSIONS

Biological aging is accelerated following a breast cancer diagnosis and treatment. Breast cancer treatment modalities appear to differentially contribute to biological aging.

Accelerated biological aging six decades after prenatal famine exposure

To test the hypothesis that early-life adversity accelerates the pace of biological aging, we analyzed data from the Dutch Hunger Winter Families Study (DHWFS, N=951). DHWFS is a natural-experiment birth-cohort study of survivors of in-utero exposure to famine conditions caused by the German occupation of the Western Netherlands in Winter 1944-5, matched controls, and their siblings. We conducted DNA methylation analysis of blood samples collected when the survivors were aged 58 to quantify biological aging using the DunedinPACE, GrimAge, and PhenoAge epigenetic clocks. Famine survivors had faster DunedinPACE, as compared with controls. This effect was strongest among women. Results were similar for GrimAge, although effect-sizes were smaller. We observed no differences in PhenoAge between survivors and controls. Famine effects were not accounted for by blood-cell composition and were similar for individuals exposed early and later in gestation. Findings suggest in-utero undernutrition may accelerate biological aging in later life.

To promote healthy aging, focus on the environment

To build health equity for an aging world marked by dramatic disparities in healthy lifespan between countries, regions and population groups, research at the intersections of biology, toxicology and the social and behavioral sciences points the way: to promote healthy aging, focus on the environment. In this Perspective, we suggest that ideas and tools from the emerging field of geroscience offer opportunities to advance the environmental science of aging. Specifically, the capacity to measure the pace and progress of biological processes of aging within individuals from relatively young ages makes it possible to study how changing environments can change aging trajectories from early in life, in time to prevent or delay aging-related disease and disability and build aging health equity.

The role of nutrition in the prevention of sarcopenia

Sarcopenia is a common skeletal muscle disorder characterized by a loss of muscle mass and impaired muscle function that is associated with poor health outcomes. Although nutrition is considered an important factor in the etiology of sarcopenia, the preventive potential of diet, specifically the extent to which differences in habitual patterns of diet and/or nutrient intakes impact risk of its development, is poorly understood. This narrative review considered research evidence on dietary patterns and nutrient intakes in mid- (<60 y) and young-older (60-70 y) adulthood to evaluate how they relate to age-related changes in muscle mass and function. A key finding was that current evidence on adult diet and sarcopenia risk in older age is limited and fragmented, with different outcomes reported across studies (for example, lean mass, strength) and few reporting links to incident diagnosed sarcopenia. As these outcomes are not interchangeable, it challenges collation of the evidence, leaving many gaps in understanding. There is also limited information about adult (<70 y) diet and few longitudinal studies with repeated dietary assessments to enable definition of cumulative exposures across adulthood. However, despite these limitations, findings from studies of dietary patterns already provide reasonably consistent messages about the benefits of diets of higher quality in earlier adulthood for later physical performance, although whole-diet intervention trials are urgently needed to understand their potential. In comparison, there is little evidence of benefits of higher intakes of individual nutrients in earlier adulthood for later muscle mass and function. Although these gaps need to be addressed in future research, there may already be sufficient data to promote messages about diet quality more widely - that healthier diets of higher quality across adulthood, with known benefits for a range of health outcomes, are also linked to the effective preservation of muscle mass and function.

Biomarkers of aging in frailty and age-associated disorders: State of the art and future perspective

According to the Geroscience concept that organismal aging and age-associated diseases share the same basic molecular mechanisms, the identification of biomarkers of age that can efficiently classify people as biologically older (or younger) than their chronological (i.e. calendar) age is becoming of paramount importance. These people will be in fact at higher (or lower) risk for many different age-associated diseases, including cardiovascular diseases, neurodegeneration, cancer, etc. In turn, patients suffering from these diseases are biologically older than healthy age-matched individuals. Many biomarkers that correlate with age have been described so far. The aim of the present review is to discuss the usefulness of some of these biomarkers (especially soluble, circulating ones) in order to identify frail patients, possibly before the appearance of clinical symptoms, as well as patients at risk for age-associated diseases. An overview of selected biomarkers will be discussed in this regard, in particular we will focus on biomarkers related to metabolic stress response, inflammation, and cell death (in particular in neurodegeneration), all phenomena connected to inflammaging (chronic, low-grade, age-associated inflammation). In the second part of the review, next-generation markers such as extracellular vesicles and their cargos, epigenetic markers and gut microbiota composition, will be discussed. Since recent progresses in omics techniques have allowed an exponential increase in the production of laboratory data also in the field of biomarkers of age, making it difficult to extract biological meaning from the huge mass of available data, Artificial Intelligence (AI) approaches will be discussed as an increasingly important strategy for extracting knowledge from raw data and providing practitioners with actionable information to treat patients.

The relative effects of parental alcohol use disorder and maltreatment on offspring alcohol use: Unique pathways of risk

Childhood adversity represents a robust risk factor for the development of harmful substance use. Although a range of empirical studies have examined the consequences of multiple forms of adversity (i.e., childhood maltreatment, parental alcohol use disorder [AUD]), there is a dearth of information on the relative effects of each form of adversity when considered simultaneously. The current study utilizes structural equation modeling to investigate three unique and amplifying pathways from parental AUD and maltreatment exposure to offspring alcohol use as emerging adults: (1) childhood externalizing symptomatology, (2) internalizing symptomatology, and (3) affiliation with substance-using peers and siblings. Participants (N = 422) were drawn from a longitudinal follow-up study of emerging adults who participated in a research summer camp program as children. Wave 1 of the study included 674 school-aged children with and without maltreatment histories. Results indicated that chronic maltreatment, over and above the effect of parent AUD, was uniquely associated with greater childhood conduct problems and depressive symptomatology. Mother alcohol dependence was uniquely associated with greater affiliation with substance-using peers and siblings, which in turn predicted greater alcohol use as emerging adults. Results support peer and sibling affiliation as a key mechanism in the intergenerational transmission of substance use between mothers and offspring.

Discordant Biological and Chronological Age: Implications for Cognitive Decline and Frailty

BACKGROUND

Older adults with discordant biological and chronological ages (BA and CA) may vary in cognitive and physical function from those with concordant BA and CA.

METHODS

To make our approach clinically accessible, we created easy-to-interpret participant groups in the Health, Aging, and Body Composition Study (N = 2 458, 52% female participants, 65% White participants, age: 73.5 ± 2.8) based on medians of CA, and a previously validated BA index comprised of readily available clinical tests. Joint models estimated associations of BA-CA group with cognition (Modified Mini-Mental State Examination [3MS] and Digit Symbol Substitution Test [DSST]) and frailty over 10 years.

RESULTS

The sample included the following: 32%, Young group (BA and CA < median); 21%, Prematurely Aging group (BA ≥ median, CA < median), 27%, Old group (BA and CA ≥ median), and 20%, Resilient group (BA < median, CA ≥ median). In education-adjusted models of cognition, among those with CA < median, the Prematurely Aging group performed worse than the Young at baseline (3MS and DSST p < .0001), but among those with CA ≥ median, the Resilient group did not outperform the Old group (3MS p = .31; DSST p = .25). For frailty, the Prematurely Aging group performed worse than the Young group at baseline (p = .0001), and the Resilient group outperformed the Old group (p = .003). For all outcomes, groups did not differ on change over time based on the same pairwise comparisons (p ≥ .40).

CONCLUSIONS

Discordant BA and CA identify groups who have greater cognitive and physical functional decline or are more protected than their CA would suggest. This information can be used for risk stratification.

Biological age estimation using circulating blood biomarkers

Biological age captures physiological deterioration better than chronological age and is amenable to interventions. Blood-based biomarkers have been identified as suitable candidates for biological age estimation. This study aims to improve biological age estimation using machine learning models and a feature-set of 60 circulating biomarkers available from the UK Biobank (n = 306,116). We implement an Elastic-Net derived Cox model with 25 selected biomarkers to predict mortality risk (C-Index = 0.778; 95% CI [0.767-0.788]), which outperforms the well-known blood-biomarker based PhenoAge model (C-Index = 0.750; 95% CI [0.739-0.761]), providing a C-Index lift of 0.028 representing an 11% relative increase in predictive value. Importantly, we then show that using common clinical assay panels, with few biomarkers, alongside imputation and the model derived on the full set of biomarkers, does not substantially degrade predictive accuracy from the theoretical maximum achievable for the available biomarkers. Biological age is estimated as the equivalent age within the same-sex population which corresponds to an individual's mortality risk. Values ranged between 20-years younger and 20-years older than individuals' chronological age, exposing the magnitude of ageing signals contained in blood markers. Thus, we demonstrate a practical and cost-efficient method of estimating an improved measure of Biological Age, available to the general population.

Conditional independence as a statistical assessment of evidence integration processes

Intuitively, combining multiple sources of evidence should lead to more accurate decisions than considering single sources of evidence individually. In practice, however, the proper computation may be difficult, or may require additional data that are inaccessible. Here, based on the concept of conditional independence, we consider expressions that can serve either as recipes for integrating evidence based on limited data, or as statistical benchmarks for characterizing evidence integration processes. Consider three events, A , B , and C . We find that, if A and B are conditionally independent with respect to C , then the probability that C occurs given that both A and B are known, P C | A , B , can be easily calculated without the need to measure the full three-way dependency between A , B , and C . This simplified approach can be used in two general ways: to generate predictions by combining multiple (conditionally independent) sources of evidence, or to test whether separate sources of evidence are functionally independent of each other. These applications are demonstrated with four computer-simulated examples, which include detecting a disease based on repeated diagnostic testing, inferring biological age based on multiple biomarkers of aging, discriminating two spatial locations based on multiple cue stimuli (multisensory integration), and examining how behavioral performance in a visual search task depends on selection histories. Besides providing a sound prescription for predicting outcomes, this methodology may be useful for analyzing experimental data of many types.

A Scoping Review of Nutrition Health for Older Adults: Does Technology Help?

The technological developments in healthcare may help facilitate older adult nutritional care. This scoping review includes research in technology and nutrition to (1) explain how technology is used to manage nutrition needs and (2) describe the forms of technology used to manage nutrition. Five major databases were the foundation for papers published from January 2000 to December 2020. The most common type of technology used is software to (1) "track, plan, and execute" nutrition management and for (2) "assessing" technology use. "Track, plan, and execute" includes tracking food intake, planning for changes, and executing a plan. "Assessing" technology use is collecting nutrition data from a provider's or an older adult's self-use of technology to understand dietary intake. Hardware is the second most type of technology used, with tablet computers for software and internet access. The findings reveal that software for older adults lacks standardization, the Internet of Things is a promising area, the current device emphasis is the tablet computer, and broadband internet access is essential for nutrition care. Only 38 studies were published in the last five years, indicating that nutrition management for older adults with hardware or software has not reached a significant research mass.

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.

Associations between childhood maltreatment and physiological dysregulation in adulthood: Methodological decisions and implications

BACKGROUND

Childhood maltreatment is linked with health problems in adulthood. Theoretical models suggest that maltreatment leads to dysregulation in several bodily systems, and this has been corroborated using measures of physiological function (i.e., biomarkers). Methodological decisions involving the measurement of maltreatment and dimension reduction with respect to biomarkers (i.e., combining information across multiple measures) may influence research findings.

OBJECTIVE

The present study compares associations between childhood maltreatment and adult physiological dysregulation using multiple dimension reduction approaches and measures of maltreatment.

PARTICIPANTS AND SETTING

Participants were recruited, as children, to a prospective study of the correlates and consequences of childhood maltreatment. 253 participants were retained and provided biomarker data at midlife. Physiological dysregulation was operationalized with a conventional allostatic load approach and a novel statistical distance approach.

METHODS

Regression models were employed with allostatic load or statistical distance as the outcome and prospectively or retrospectively measured child maltreatment as the primary predictor.

RESULTS

When using allostatic load as the outcome, prospectively measured childhood maltreatment was positively associated with physiological dysregulation (b = 0.70, SE = 0.31, p = 0.02). When using statistical distance as the outcome, retrospectively measured childhood maltreatment was positively associated with physiological dysregulation (b = 0.69, SE = 0.19 p < 0.001).

CONCLUSIONS

We report a positive association between childhood maltreatment and physiological dysregulation at midlife. However, the significance and magnitude of effects varied with different maltreatment and physiological dysregulation measures. Further review of the methods used to study adult health conditions and their relation to childhood maltreatment is needed.

Is childhood oral health the 'canary in the coal mine' for poor adult general health? Findings from two New Zealand birth cohort studies

OBJECTIVES

This study aimed to investigate whether childhood dental caries was associated with self-reported general health in midlife.

METHODS

We used data on childhood oral health (caries experience) and adult self-reported general health from two New Zealand longitudinal birth cohorts, the Dunedin Multidisciplinary Health and Development Study (n = 922 and n = 931 at ages 5 and 45 years, respectively), and the Christchurch Health and Development Study (n = 1048 and n = 904 at ages 5 and 40 years, respectively). We used generalized estimating equations to examine associations between age-5 dental caries and self-rated general health and the number of self-reported physical health conditions at ages 45/40 (diagnosed by a doctor or health professional, n = 14 conditions among both cohorts). Covariates included known risk factors for poor health (SES, IQ, perinatal complications), and personality style, which is known to affect subjective health ratings.

RESULTS

Incidence rate ratios for 'Excellent' self-rated health were lower among those who had high experience of dental caries as children than those who had not in both, the Dunedin (IRR, 0.76; 95% CI, 0.50, 1.14) and Christchurch studies (IRR, 0.69; 95% CI, 0.47, 1.00). Childhood dental caries was not associated with the number of self-reported physical health conditions in midlife, in either cohort. Dunedin Study members who at age 5 were not caries-free or whose parents rated their own or their child's oral health as poor were less likely to report 'Excellent' self-rated general health at age 45 than those who were caries-free and whose parents did not give a 'poor' rating (IRR, 0.69; 95% CI, 0.49, 0.97).

CONCLUSIONS

Five-year-olds with greater caries experience were more likely to have poorer self-rated general health by midlife. Beyond this longitudinal association, future research should examine whether childhood dental caries is associated with objective/biological markers of physical health and whether it may have utility as an early indicator for poor general health in adulthood.

Transcriptomics age acceleration in prolonged treated HIV infection

Biological aging in people with HIV (PWH) with prolonged successful antiretroviral therapy (ART) is convoluted and poorly defined. Here, we aimed to investigate the transcriptomics age estimator (TAE) in a cohort of 178 PWH on prolonged successful ART with immune reconstitution and viral suppression from the Copenhagen Comorbidity (COCOMO) cohort. We also used 143 clinical, demographical, and lifestyle factors to identify the confounders potentially responsible or associated with age acceleration. Among the PWH, 43% had an accelerated aging process (AAP), and 21% had decelerated aging process (DAP). DAP is linked with older age, European ancestry, and higher use of tenofovir disoproxil/alafenamide fumarate. A directionally class-based gene set enrichment analysis identified the upregulation of inflammatory pathways (e.g., cytokine and Retinoic acid-inducible gene I (RIG-I)-like receptor signaling pathways) and immune response like T-cell receptor signaling, antigen processing, and presentation in AAP and the downregulation of metabolic processes like oxidative phosphorylation, pyruvate metabolism.

Natural Animal Populations as Model Systems for Understanding Early Life Adversity Effects on Aging

Adverse experiences in early life are associated with aging-related disease risk and mortality across many species. In humans, confounding factors, as well as the difficulty of directly measuring experiences and outcomes from birth till death, make it challenging to identify how early life adversity impacts aging and health. These challenges can be mitigated, in part, through the study of non-human animals, which are exposed to parallel forms of adversity and can age similarly to humans. Furthermore, studying the links between early life adversity and aging in natural populations of non-human animals provides an excellent opportunity to better understand the social and ecological pressures that shaped the evolution of early life sensitivities. Here, we highlight ongoing and future research directions that we believe will most effectively contribute to our understanding of the evolution of early life sensitivities and their repercussions.

Tangeretin Supplementation Mitigates the Aging Toxicity Induced by Dietary Benzo[a]pyrene Exposure with Aberrant Proteostasis and Heat Shock Responses in Caenorhabditis elegans

Benzo[a]pyrene (BaP) is a common food contaminant that can impair organismal aging. Tangeretin (TAN) may mitigate aging toxicities as a dietary supplement. This study used Caenorhabditis elegans to investigate the effects of chronic exposure to BaP on aging and to determine whether TAN supplementation could alleviate BaP-induced toxicity. Early life exposure to BaP (10 μM) significantly inhibited growth by 5%, and exposure to 0.1 to 10 μM BaP impaired C. elegans motility, resulting in a 3.4-6.5% reduction in motility. Chronic exposure to BaP (10 μM) age-dependently aggravated aberrant protein aggregation (7% increase) and shortened the median lifespan of the worms from 20 to 16 days. In addition, BaP worsened the age-dependent decline in motility and pharyngeal pumping, as well as the accumulation of reactive oxygen species. Furthermore, exposure to BaP resulted in significantly higher relative transcript levels of approximately 1.8-2.0-fold for the hsp-16.1, hsp-16.2, hsp-16.49, and hsp-70 genes. Stressed worms exposed to BaP exhibited significantly lower survival under heat stress. Dietary TAN supplementation alleviated the BaP-induced decline in motility, pumping, and poly-Q accumulation and restored heat shock proteins' transcript levels. Our findings suggest that chronic BaP exposure adversely affects aging and that TAN exposure mitigates the BaP-induced aging toxicity.