Quantification of biological aging in young adults

Stress-induced biological aging: A review and guide for research priorities

Exposure to chronic adverse conditions, and the resultant activation of the neurobiological response cascade, has been associated with an increased risk of early onset of age-related disease and, recently, with an older biological age. This body of research has led to the hypothesis that exposure to stressful life experiences, when occurring repeatedly or over a prolonged period, may accelerate the rate at which the body ages. The mechanisms through which chronic psychosocial stress influences distinct biological aging pathways to alter rates of aging likely involve multiple layers in the physiological-molecular network. In this review, we integrate research using animal, human, and in vitro models to begin to delineate the distinct pathways through which chronic psychosocial stress may impact biological aging, as well as the neuroendocrine mediators (i.e., norepinephrine, epinephrine, and glucocorticoids) that may drive these effects. Findings highlight key connections between stress and aging, namely cellular metabolic activity, DNA damage, telomere length, cellular senescence, and inflammatory response patterns. We conclude with a guiding framework and conceptual model that outlines the most promising biological pathways by which chronic adverse conditions could accelerate aging and point to key missing gaps in knowledge where future research could best answer these pressing questions.

Modeling biological age and its link with the aging process

Differences in health status at older ages are a result of genetic predispositions and physiological responses to exposure accumulation over the lifespan. These vary across individuals and lead to health status heterogeneity as people age. Chronological age (CA) is a standard indicator that reflects overall risks of morbidity and mortality. However, CA is only a crude proxy for individuals' latent physiological deterioration. An alternative to CA is biological age (BA), an indicator of accumulated age-related biological change reflected in markers of major physiological systems. We propose and validate two BA estimators that improve upon existing ones. These estimators (i) are based on a structural equation model (SEM) that represents the relation between BA and CA, (ii) circumvent the need to impose arbitrary assumptions about the relation between CA and BA, and (iii) provide tools to empirically test the validity of assumptions the researcher may wish to invoke. We use the US National Health and Nutrition Examination Survey 1988-1994 and compare results with three commonly used methods to compute BA (principal components-PCA, multiple regression-MLR, and Klemera-Doubal's method-KD). We show that SEM-based estimates of BA differ significantly from those generated by PCA and MLR and are comparable to, but have better predictive power than KD's. The proposed estimators are flexible, allow testing of assumptions about functional forms relating BA and CA, and admit a rich interpretation as indicators of accelerated aging.

Biological Age Prediction From Wearable Device Movement Data Identifies Nutritional and Pharmacological Interventions for Healthy Aging

Intervening in aging processes is hypothesized to extend healthy years of life and treat age-related disease, thereby providing great benefit to society. However, the ability to measure the biological aging process in individuals, which is necessary to test for efficacy of these interventions, remains largely inaccessible to the general public. Here we used NHANES physical activity accelerometer data from a wearable device and machine-learning algorithms to derive biological age predictions for individuals based on their movement patterns. We found that accelerated biological aging from our “MoveAge” predictor is associated with higher all-cause mortality. We further searched for nutritional or pharmacological compounds that associate with decelerated aging according to our model. A number of nutritional components peak in their association to decelerated aging later in life, including fiber, magnesium, and vitamin E. We additionally identified one FDA-approved drug associated with decelerated biological aging: the alpha-blocker doxazosin. We show that doxazosin extends healthspan and lifespan in C. elegans. Our work demonstrates how a biological aging score based on relative mobility can be accessible to the wider public and can potentially be used to identify and determine efficacy of geroprotective interventions.

The MitoAging Project: Single nucleotide polymorphisms (SNPs) in mitochondrial genes and their association to longevity

Mitochondrial dysfunction is a major hallmark of aging. Mitochondrial DNA (mtDNA) mutations (inherited or acquired) may cause a malfunction of the respiratory chain (RC), and thus negatively affect cell metabolism and function. In contrast, certain mtDNA single nucleotide polymorphisms (SNPs) may be beneficial to mitochondrial electron transport chain function and the extension of cellular health as well as lifespan. The goal of the MitoAging project is to detect key physiological characteristics and mechanisms that improve mitochondrial function and use them to develop therapies to increase longevity and a healthy lifespan. We chose to perform a systematic literature review (SLR) as a tool to collect key mtDNA SNPs associated with an increase in lifespan. Then validated our results by comparing them to the MitoMap database. Next, we assessed the effect of relevant SNPs on protein stability. A total of 28 SNPs were found in protein coding regions. These SNPs were reported in Japan, China, Turkey, and India. Among the studied SNPs, the C5178A mutation in the ND2 gene of Complex I of the RC was detected in all the reviewed reports except in Uygur Chinese centenarians. Then, we found that G9055A (ATP6 gene) and A10398G (ND3 gene) polymorphisms have been associated with a protective effect against Parkinson's disease (PD). Additionally, C8414T in ATP8 was significantly associated with longevity in three Japanese reports. Interestingly, using MitoMap we found that G9055A (ATP6 gene) was the only SNP promoting longevity not associated with any pathology. The identification of SNPs associated with an increase in lifespan opens the possibility to better understand individual differences regarding a decrease in illness susceptibility and find strategies that contribute to healthy aging.

Biomarkers of aging in real life: three questions on aging and the comprehensive geriatric assessment

Measuring intrinsic, biological age is a central question in medicine, which scientists have been trying to answer for decades. Age manifests itself differently in different individuals, and chronological age often does not reflect such heterogeneity of health and function. We discuss here the value of measuring age and aging using the comprehensive geriatric assessment (CGA), cornerstone of geriatric medicine, and operationalized assessment tools for prognosis. Specifically, we review the benefits of employing the multidimensional prognostic index (MPI), which collects information about eight domains relevant for the global assessment of the older person (functional and cognitive status, nutrition, mobility and risk of pressure sores, multi-morbidity, polypharmacy, and co-habitation), in the evaluation of the functional status, and in the prediction of health outcomes for older adults. Further integration of biological markers of aging into multidimensional prognostic tools is warranted, as well as actions which could facilitate prognostic assessments for older persons in all healthcare settings.

Precise Metabolomics Reveals a Diversity of Aging-Associated Metabolic Features

Mass spectrometry-based metabolomics has emerged as a powerful technique for biomedical research, although technical issues with its analytical precision and structural characterization remain. Herein, a robust non-targeted strategy for accurate quantitation and precise profiling of metabolomes is developed and applied to investigate plasma metabolic features associated with human aging. A comprehensive set of isotope-labeled standards (ISs) covering major metabolic pathways is incorporated to quantify polar metabolites. Matching rules to select ISs for calibration follow a primary criterion of minimal coefficients of variations (COVs). If minimal COVs between specific ISs for a particular metabolite fall within 5% window, a further selection of ISs is conducted based on structural similarities and proximity in retention time. The introduction and refined selection of appropriate ISs for quantitation reduces the COVs of 480 identified metabolites in quality control samples from 14.3% to 9.8% and facilitates identification of additional metabolite. Finally, the precise metabolomics approach reveals perturbations in a diverse array of metabolic pathways across aging that principally implicate steroid metabolism, amino acid metabolism, lipid metabolism, and purine metabolism, which allows the authors to draw correlates to the pathology of various age-related diseases. These findings provide clues for the prevention and treatment of these age-related diseases.

Associations between epigenetic age acceleration and infertility

STUDY QUESTION

Is the use of ART, a proxy for infertility, associated with epigenetic age acceleration?

SUMMARY ANSWER

The epigenetic age acceleration measured by Dunedin Pace of Aging methylation (DunedinPoAm) differed significantly between non-ART and ART mothers.

WHAT IS KNOWN ALREADY

Among mothers who used ART, epigenetic age acceleration may be associated with low oocyte yield and poor ovarian response. However, the difference in epigenetic age acceleration between non-ART and ART mothers (or even fathers) has not been examined.

STUDY DESIGN, SIZE, DURATION

The Norwegian Mother, Father and Child Cohort Study (MoBa) recruited pregnant women and their partners across Norway at around 18 gestational weeks between 1999 and 2008. Approximately 95 000 mothers, 75 000 fathers and 114 000 children were included. Peripheral blood samples were taken from mothers and fathers at ultrasound appointments or from mothers at childbirth, and umbilical cord blood samples were collected from the newborns at birth.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Among the MoBa participants, we selected 1000 couples who conceived by coitus and 894 couples who conceived by IVF (n = 525) or ICSI (n = 369). We measured their DNA methylation (DNAm) levels using the Illumina MethylationEPIC array and calculated epigenetic age acceleration. A linear mixed model was used to examine the differences in five different epigenetic age accelerations between non-ART and ART parents.

MAIN RESULTS AND THE ROLE OF CHANCE

We found a significant difference in the epigenetic age acceleration calculated by DunedinPoAm between IVF and non-ART mothers (0.021 years, P-value = 2.89E−06) after adjustment for potential confounders. Further, we detected elevated DunedinPoAm in mothers with tubal factor infertility (0.030 years, P-value = 1.34E−05), ovulation factor (0.023 years, P-value = 0.0018) and unexplained infertility (0.023 years, P-value = 1.39E−04) compared with non-ART mothers. No differences in epigenetic age accelerations between non-ART and ICSI fathers were found. DunedinPoAm also showed stronger associations with smoking, education and parity than the other four epigenetic age accelerations.

LIMITATIONS, REASONS FOR CAUTION

We were not able to determine the directionality of the causal pathway between the epigenetic age accelerations and infertility. Since parents’ peripheral blood samples were collected after conception, we cannot rule out the possibility that the epigenetic profile of ART mothers was influenced by the ART treatment. Hence, the results should be interpreted with caution, and our results might not be generalizable to non-pregnant women.

WIDER IMPLICATIONS OF THE FINDINGS

A plausible biological mechanism behind the reported association is that IVF mothers could be closer to menopause than non-ART mothers. The pace of decline of the ovarian reserve that eventually leads to menopause varies between females yet, in general, accelerates after the age of 30, and some studies show an increased risk of infertility in females with low ovarian reserve.

STUDY FUNDING/COMPETING INTEREST(S)

This study was partly funded by the Research Council of Norway (Women’s fertility, project no. 320656) and through its Centres of Excellence Funding Scheme (project no. 262700). M.C.M. has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement number 947684). The authors declare no conflict of interest.

TRIAL REGISTRATION NUMBER

N/A.

A Computational Framework to Characterize the Cancer Drug Induced Effect on Aging Using Transcriptomic Data

Cancer treatments such as chemotherapies may change or accelerate aging trajectories in cancer patients. Emerging evidence has shown that “omics” data can be used to study molecular changes of the aging process. Here, we integrated the drug-induced and normal aging transcriptomic data to computationally characterize the potential cancer drug-induced aging process in patients. Our analyses demonstrated that the aging-associated gene expression in the GTEx dataset can recapitulate the well-established aging hallmarks. We next characterized the drug-induced transcriptomic changes of 28 FDA approved cancer drugs in brain, kidney, muscle, and adipose tissues. Further drug-aging interaction analysis identified 34 potential drug regulated aging events. Those events include aging accelerating effects of vandetanib (Caprelsa®) and dasatinib (Sprycel®) in brain and muscle, respectively. Our result also demonstrated aging protective effect of vorinostat (Zolinza®), everolimus (Afinitor®), and bosutinib (Bosulif®) in brain.

Counteracting aged DNA methylation states to combat ageing and age-related diseases

DNA methylation (DNAm) overwrites information about multiple extrinsic factors on the genome. Age is one of these factors. Age causes characteristic DNAm changes that are thought to be not only major drivers of normal ageing but also precursors to diseases, cancer being one of these. Although there is still much to learn about the relationship between ageing, age-related diseases and DNAm, we now know how to interpret some of the effects caused by age in the form of changes in methylation marks at specific loci. In fact, these changes form the basis of the so called "epigenetic clocks", which translate the genomic methylation profile into an "epigenetic age". Epigenetic age does not only estimate chronological age but can also predict the risk of chronic diseases and mortality. Epigenetic age is believed to be one of the most accurate metrics of biological age. Initial evidence has recently been gathered pointing to the possibility that the rate of epigenetic ageing can be slowed down or even reversed. In this review, we discuss some of the most relevant advances in this field. Expected outcome is that this approach can provide insights into how to preserve health and reduce the impact of ageing diseases in humans.

Biological ageing and the risks of all-cause and cause-specific mortality among people with diabetes: a prospective cohort study

BACKGROUND

The aetiology of diabetes is complex with limited treatment strategies. Growing animal studies have shown that targeted antiageing can improve the outcomes of diabetes. However, population evidence is limited. This study aims to evaluate the associations of biological ageing with all-cause and cause-specific mortality among people with diabetes.

METHODS

A total of 5278 people with diabetes from the National Health and Nutrition Examination Survey 1999-2014 were included. Biological ageing was measured from different perspectives, including phenotypic age, biological age, telomere length and klotho concentration. Phenotypic/biological age acceleration was the residual resulting from a linear model when regressing phenotypic/biological age on chronological age. Cox proportional hazards models were used to examine the relationships between ageing and all-cause, cardiovascular disease (CVD), and cancer mortality.

RESULTS

Over median follow-up for 7.3 years, 1355 diabetics died. There was a positive and linear association of mortality with phenotypic age acceleration (HR_all-cause 1.04; HR_CVD 1.04; HR_cancer 1.04, p<0.001) and biological age acceleration (HR_all-cause 1.03; HR_CVD 1.04; HR_cancer 1.03, p<0.001). Telomere length was inversely associated with all-cause mortality (tertile (T)3 vs T1: HR 0.67, p<0.05). The concentration of klotho had a U-shaped relationship with mortality (T2 vs T1: HR_all-cause 0.62; HR_CVD 0.48; HR_cancer 0.47, p<0.05). Further, stratified analysis by age and sex found that the associations of ageing-related markers with mortality were more significant in the aged and female subgroup.

CONCLUSIONS

Biological ageing was positively associated with mortality among people with diabetes, indicating therapies targeting antiageing could be encouraged to halt the progression of diabetes.

Biological aging for risk prediction of first-ever intracerebral hemorrhage and cerebral infarction in advanced age

BACKGROUND AND OBJECTIVES

successful interventions to prevent cerebrovascular disease and stroke require early identification of persons at risk before clinical manifestation of disease. The literature remains to be sparse on accessible plasma-based biomarkers for monitoring brain health and cerebrovascular disease in advanced age. We assessed the predictive value of biological age (BA) as an early indicator for cerebrovascular disease and risk of first-ever intracerebral hemorrhage (ICH) and cerebral infarction (CI) in advanced age and compared these relationships with chronological age (CA) and commonly used biomarkers including tau and Aβ40 and Aβ42.

METHODS

The study included Individuals who consented for blood draw and follow-up. We computed biological age using structural equation modelling. The criteria for the biomarkers included their representability of the various body systems; their availability in the Rotterdam study and their pre-hypothesized reflection of aging in other populations. The algorithm integrates biomarkers that represent six body systems involved in overall cerebrovascular health including metabolic function, cardiac function, lung function, kidney function, liver function, immunity, and inflammation. Time to event analysis was conducted using Cox-regression models. Prediction analysis was conducted using Harrel's C and Area under the receiver operating characteristic curve.

RESULTS

The sample included a total of 1699 individuals at baseline followed up over a median of 11 years. During a period of 15, 780 and 16, 172 person-years, a total of 17 first-ever intracerebral hemorrhage and 83 cerebral infarction cases occurred. In time-to-event analysis, BA showed higher magnitude of associations with ICH compared to CA (HR_BA-ICH: 2.30, 95% CI: 1.20, 4.30; HR_CA-ICH: 1.40, 95% CI: 0.76, 2.53) and higher precision with CI (HR_BA-CI: 1.30, 95% CI: 1.01,1.75; HR_CA-CI:1.90, 95% CI: 1.48, 2.66). BA outperformed CA for prediction of ICH (AUC: 0.68 vs 0.53; Harrel's C: 0.72 vs 0.53) and for CI (AUC:0.63 vs 0.62; Harrel's C: 0.68 vs 0.67).

CONCLUSIONS

Biological aging (delta biological aging) based on integrated physiology biomarkers provides a novel tool for monitoring and identification of persons at highest risk of cerebrovascular disease in advanced age with varying degrees of precision and magnitude for stroke subtypes. These variations are likely related to differences in pathophysiology of intracerebral hemorrhage and cerebral infarction. Wider validation and applicability require extension of these findings in other comparable samples and in clinical settings.

Early-life stress exposure and large-scale covariance brain networks in extremely preterm-born infants

The stressful extrauterine environment following premature birth likely has far-reaching and persistent adverse consequences. The effects of early "third-trimester" ex utero stress on large-scale brain networks' covariance patterns may provide a potential avenue to understand how early-life stress following premature birth increases risk or resilience. We evaluated the impact of early-life stress exposure (e.g., quantification of invasive procedures) on maturational covariance networks (MCNs) between 30 and 40 weeks of gestational age in 180 extremely preterm-born infants (<28 weeks of gestation; 43.3% female). We constructed MCNs using covariance of gray matter volumes between key nodes of three large-scale brain networks: the default mode network (DMN), executive control network (ECN), and salience network (SN). Maturational coupling was quantified by summating the number of within- and between-network connections. Infants exposed to high stress showed significantly higher SN but lower DMN maturational coupling, accompanied by DMN-SN decoupling. Within the SN, the insula, amygdala, and subthalamic nucleus all showed higher maturational covariance at the nodal level. In contrast, within the DMN, the hippocampus, parahippocampal gyrus, and fusiform showed lower coupling following stress. The decoupling between DMN-SN was observed between the insula/anterior cingulate cortex and posterior parahippocampal gyrus. Early-life stress showed longitudinal network-specific maturational covariance patterns, leading to a reprioritization of developmental trajectories of the SN at the cost of the DMN. These alterations may enhance the ability to cope with adverse stimuli in the short term but simultaneously render preterm-born individuals at a higher risk for stress-related psychopathology later in life.

Perceived facial age and biochemical indicators of glycemia in adult men and women

Glycemia is linked with one of the key mechanisms underlying the aging process and inter-individual differences in biological age. Previous research showed that glucose level is linked with perceived age in elder individuals. This study aimed to verify if glycemia is related to perceived facial age in healthy adult individuals as interventions in younger and healthy cohorts are crucial for preventing the onset of age-related diseases. The study sample consisted of 116 healthy men of mean age 35.53 ± 3.54 years (29.95–44.29) and 163 healthy women of mean age 28.38 ± 2.40 (24.25–34.17) years. Glycemia was evaluated by fasting glucose, insulin, HOMA-IR, and glycated hemoglobin level. BMI, facial sexual dimorphism, estradiol, testosterone, and hsCRP levels were controlled. Perceived age was evaluated based on standardized facial photos in an online survey. Additionally perceived facial aging was calculated as a difference between perceived age and chronological age. No relationship between the levels of biochemical indicators of glycemia and perceived facial age or aging was found both in men and women, also when controlled for possible confounders. This study shows that perceived facial age in adult individuals is rather linked with body adiposity of sexual dimorphism but not with glycemic markers.

Longitudinal Study of DNA Methylation and Epigenetic Clocks Prior to and Following Test-Confirmed COVID-19 and mRNA Vaccination

The host epigenetic landscape rapidly changes during SARS-CoV-2 infection, and evidence suggest that severe COVID-19 is associated with durable scars to the epigenome. Specifically, aberrant DNA methylation changes in immune cells and alterations to epigenetic clocks in blood relate to severe COVID-19. However, a longitudinal assessment of DNA methylation states and epigenetic clocks in blood from healthy individuals prior to and following test-confirmed non-hospitalized COVID-19 has not been performed. Moreover, the impact of mRNA COVID-19 vaccines upon the host epigenome remains understudied. Here, we first examined DNA methylation states in the blood of 21 participants prior to and following test-confirmed COVID-19 diagnosis at a median time frame of 8.35 weeks; 756 CpGs were identified as differentially methylated following COVID-19 diagnosis in blood at an FDR adjusted p-value < 0.05. These CpGs were enriched in the gene body, and the northern and southern shelf regions of genes involved in metabolic pathways. Integrative analysis revealed overlap among genes identified in transcriptional SARS-CoV-2 infection datasets. Principal component-based epigenetic clock estimates of PhenoAge and GrimAge significantly increased in people over 50 following infection by an average of 2.1 and 0.84 years. In contrast, PCPhenoAge significantly decreased in people fewer than 50 following infection by an average of 2.06 years. This observed divergence in epigenetic clocks following COVID-19 was related to age and immune cell-type compositional changes in CD4+ T cells, B cells, granulocytes, plasmablasts, exhausted T cells, and naïve T cells. Complementary longitudinal epigenetic clock analyses of 36 participants prior to and following Pfizer and Moderna mRNA-based COVID-19 vaccination revealed that vaccination significantly reduced principal component-based Horvath epigenetic clock estimates in people over 50 by an average of 3.91 years for those who received Moderna. This reduction in epigenetic clock estimates was significantly related to chronological age and immune cell-type compositional changes in B cells and plasmablasts pre- and post-vaccination. These findings suggest the potential utility of epigenetic clocks as a biomarker of COVID-19 vaccine responses. Future research will need to unravel the significance and durability of short-term changes in epigenetic age related to COVID-19 exposure and mRNA vaccination.

Relationship intervention indirectly buffers financial strain's effect on biological aging among Black adults

Black adults in the rural South experience elevated financial strain and other contextual stressors, increasing their risk for poor health. Supportive relationships, particularly positive romantic relationships, have been shown to offset these risks. The present study aims to provide experimental evidence of the buffering effect of supportive relationships by testing whether participation in a relationship enhancement program (ProSAAF) that improves couple functioning (Barton, Beach, Wells, et al., 2018) subsequently buffers the effect of cumulative financial strain on biological aging (weathering). Postintervention financial strain was assessed four times. Deoxyribonucleic acid (DNA) was extracted from peripheral whole blood collected 6 years after baseline (n = 348 individuals), and patterns of methylation were used to index accelerated pace of aging. Couple functioning was treated as a latent construct comprising four self-report indicators: effective communication, relationship confidence, relationship satisfaction, and perceived partner support. Results indicated that cumulative financial strain was associated with accelerated pace of aging with a medium to large effect size. This effect was moderated by change in couple functioning such that individuals with greater improvement in couple functioning showed less epigenetic aging in response to cumulative financial strain. Additionally, there was a significant indirect buffering effect of ProSAAF on the association between cumulative financial strain and accelerated pace of aging. This is the first study to demonstrate that a couple-focused preventive intervention can reduce the impact of financial strain on rate of aging by enhancing couple functioning. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Multi-system trajectories and the incidence of heart failure in the Framingham Offspring Study

BACKGROUND

Heart failure is a multi-system disease, with non-cardiac systems playing a key role in disease pathogenesis.

OBJECTIVE

Investigate whether longitudinal multi-system trajectories incrementally predict heart failure risk compared to single-occasion traits.

METHODS

We evaluated 3,412 participants from the Framingham Heart Study Offspring cohort, free of heart failure, who attended examination cycle 5 and at least one examination between 1995-2008 (mean age 67 years, 54% women). We related trajectories for the following organ systems and metabolic functions to heart failure risk using Cox regression: kidney (estimated glomerular filtration rate), lung (forced vital capacity and the ratio of forced expiratory volume in one second/forced vital capacity), neuromotor (gait time), muscular (grip strength), cardiac (left ventricular mass index and heart rate), vascular function (pulse pressure), cholesterol (ratio of total/high-density lipoprotein), adiposity (body mass index), inflammation (C-reactive protein) and glucose homeostasis (hemoglobin A1c). Using traits selected via forward selection, we derived a trajectory risk score and related it to heart failure risk.

RESULTS

We observed 276 heart failure events during a median follow up of 10 years. Participants with the 'worst' multi-system trajectory profile had the highest heart failure risk. A one-unit increase in the trajectory risk score was associated with a 2.72-fold increase in heart failure risk (95% CI 2.21-3.34; p<0.001). The mean c-statistics for models including the trajectory risk score and single-occasion traits were 0.87 (95% CI 0.83-0.91) and 0.83 (95% CI 0.80-0.86), respectively.

CONCLUSION

Incorporating multi-system trajectories reflective of the aging process may add incremental information to heart failure risk assessment when compared to using single-occasion traits.

Making sense of the ageing methylome

Over time, the human DNA methylation landscape accrues substantial damage, which has been associated with a broad range of age-related diseases, including cardiovascular disease and cancer. Various age-related DNA methylation changes have been described, including at the level of individual CpGs, such as differential and variable methylation, and at the level of the whole methylome, including entropy and correlation networks. Here, we review these changes in the ageing methylome as well as the statistical tools that can be used to quantify them. We detail the evidence linking DNA methylation to ageing phenotypes and the longevity strategies aimed at altering both DNA methylation patterns and machinery to extend healthspan and lifespan. Lastly, we discuss theories on the mechanistic causes of epigenetic ageing.

What can we learn from physical capacity about biological age? A systematic review

OBJECTIVE

To systematically investigate the relationship between objective measures of physical capacity (e.g., cardio-respiratory fitness or daily step count) and biological age, measured in different ways.

DATA SOURCE

PubMed; SCOPUS - Elsevier API; and Web of Science - ISI 1984-present, as well as contextual search engines used to identify additional relevant publications.

STUDY SELECTION

Cross-sectional and longitudinal studies that assessed the association between objectively measured physical capacity and biological aging in adult individuals (age>18).

RESULTS

Analysis of 28 studies demonstrated that physical capacity is positively associated with biological aging; the most dominant measures of physical capacity are muscular strength or gait speed. The majority of the studies estimated biological aging by a single methodology - either Leukocyte Telomere Length or DNA methylation levels.

CONCLUSIONS

This systematic review of the objective physical capacity measures used to estimate aging finds that the current literature is limited insofar as it overlooks the potential contribution of many feasible markers. We recommend measuring physical capacity in the context of aging using a wide range of modifiable behavioral markers, beyond simple muscle strength or simple gait speed. Forming a feasible and diversified method for estimating physical capacity through which it will also be possible to estimate biological aging in wide population studies is essential for the development of interventions that may alleviate the burden of age-related disease.

Immunosenescence and Altered Vaccine Efficiency in Older Subjects: A Myth Difficult to Change

Organismal ageing is associated with many physiological changes, including differences in the immune system of most animals. These differences are often considered to be a key cause of age-associated diseases as well as decreased vaccine responses in humans. The most often cited vaccine failure is seasonal influenza, but, while it is usually the case that the efficiency of this vaccine is lower in older than younger adults, this is not always true, and the reasons for the differential responses are manifold. Undoubtedly, changes in the innate and adaptive immune response with ageing are associated with failure to respond to the influenza vaccine, but the cause is unclear. Moreover, recent advances in vaccine formulations and adjuvants, as well as in our understanding of immune changes with ageing, have contributed to the development of vaccines, such as those against herpes zoster and SARS-CoV-2, that can protect against serious disease in older adults just as well as in younger people. In the present article, we discuss the reasons why it is a myth that vaccines inevitably protect less well in older individuals, and that vaccines represent one of the most powerful means to protect the health and ensure the quality of life of older adults.

All-Subset Analysis Improves the Predictive Accuracy of Biological Age for All-Cause Mortality in Chinese and U.S. Populations

BACKGROUND

Klemera-Doubal's method (KDM) is an advanced and widely applied algorithm for estimating biological age (BA), but it has no uniform paradigm for biomarker processing. This article proposed all subsets of biomarkers for estimating BAs and assessed their association with mortality to determine the most predictive subset and BA.

METHODS

Clinical biomarkers, including those from physical examinations and blood assays, were assessed in the China Health and Nutrition Survey (CHNS) 2009 wave. Those correlated with chronological age (CA) were combined to produce complete subsets, and BA was estimated by KDM from each subset of biomarkers. A Cox proportional hazards regression model was used to examine and compare each BA's effect size and predictive capacity for all-cause mortality. Validation analysis was performed in the Chinese Longitudinal Healthy Longevity Survey (CLHLS) and National Health and Nutrition Examination Survey (NHANES). KD-BA and Levine's BA were compared in all cohorts.

RESULTS

A total of 130 918 panels of BAs were estimated from complete subsets comprising 3-17 biomarkers, whose Pearson coefficients with CA varied from 0.39 to 1. The most predictive subset consisted of 5 biomarkers, whose estimated KD-BA had the most predictive accuracy for all-cause mortality. Compared with Levine's BA, the accuracy of the best-fitting KD-BA in predicting death varied among specific populations.

CONCLUSION

All-subset analysis could effectively reduce the number of redundant biomarkers and significantly improve the accuracy of KD-BA in predicting all-cause mortality.

Association of Treatable Health Conditions During Adolescence With Accelerated Aging at Midlife

IMPORTANCE

Biological aging is a distinct construct from health; however, people who age quickly are more likely to experience poor health. Identifying pediatric health conditions associated with accelerated aging could help develop treatment approaches to slow midlife aging and prevent poor health in later life.

OBJECTIVE

To examine the association between 4 treatable health conditions in adolescence and accelerated aging at midlife.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study analyzed data from participants in the Dunedin Study, a longitudinal investigation of health and behavior among a birth cohort born between April 1, 1972, and March 31, 1973, in Dunedin, New Zealand, and followed up until age 45 years. Participants underwent an assessment at age 45 years and had data for at least 1 adolescent health condition (asthma, smoking, obesity, and psychological disorders) and outcome measure (pace of aging, gait speed, brain age, and facial age). Data analysis was performed from February 11 to September 27, 2021.

EXPOSURES

Asthma, cigarette smoking, obesity, and psychological disorders were assessed at age 11, 13, and 15 years.

MAIN OUTCOMES AND MEASURES

The outcome was a midlife aging factor composite score comprising 4 measures of biological aging: pace of aging, gait speed, brain age (specifically, BrainAGE score), and facial age.

RESULTS

A total of 910 participants (459 men [50.4%]) met the inclusion criteria, including an assessment at age 45 years. Participants who had smoked daily (0.61 [95% CI, 0.43-0.79] SD units), had obesity (0.82 [95% CI, 0.59-1.06] SD units), or had a psychological disorder diagnosis (0.43 [95% CI, 0.29-0.56] SD units) during adolescence were biologically older at midlife compared with participants without these conditions. Participants with asthma were not biologically older at midlife (0.02 [95% CI, -0.14 to 0.19] SD units) compared with those without asthma. These results remained unchanged after adjusting for childhood risk factors such as poor health, socioeconomic disadvantage, and adverse experiences.

CONCLUSIONS AND RELEVANCE

This study found that adolescent smoking, obesity, and psychological disorder diagnoses were associated with older biological age at midlife. These health conditions could be treated during adolescence to reduce the risk of accelerated biological aging later in life.

The 90 plus: longevity and COVID-19 survival

The world population is getting older and studies aiming to enhance our comprehension of the underlying mechanisms responsible for health span are of utmost interest for longevity and as a measure for health care. In this review, we summarized previous genetic association studies (GWAS) and next-generation sequencing (NGS) of elderly cohorts. We also present the updated hypothesis for the aging process, together with the factors associated with healthy aging. We discuss the relevance of studying older individuals and build databanks to characterize the presence and resistance against late-onset disorders. The identification of about 2 million novel variants in our cohort of more than 1000 elderly Brazilians illustrates the importance of studying highly admixed populations of non-European ancestry. Finally, the ascertainment of nonagenarians and particularly of centenarians who were recovered from COVID-19 or remained asymptomatic opens new avenues of research aiming to enhance our comprehension of biological mechanisms associated with resistance against pathogens.

Utilization of Host and Microbiome Features in Determination of Biological Aging

The term ‘old age’ generally refers to a period characterized by profound changes in human physiological functions and susceptibility to disease that accompanies the final years of a person’s life. Despite the conventional definition of old age as exceeding the age of 65 years old, quantifying aging as a function of life years does not necessarily reflect how the human body ages. In contrast, characterizing biological (or physiological) aging based on functional parameters may better reflect a person’s temporal physiological status and associated disease susceptibility state. As such, differentiating ‘chronological aging’ from ‘biological aging’ holds the key to identifying individuals featuring accelerated aging processes despite having a young chronological age and stratifying them to tailored surveillance, diagnosis, prevention, and treatment. Emerging evidence suggests that the gut microbiome changes along with physiological aging and may play a pivotal role in a variety of age-related diseases, in a manner that does not necessarily correlate with chronological age. Harnessing of individualized gut microbiome data and integration of host and microbiome parameters using artificial intelligence and machine learning pipelines may enable us to more accurately define aging clocks. Such holobiont-based estimates of a person’s physiological age may facilitate prediction of age-related physiological status and risk of development of age-associated diseases.

Indoor air pollution and frailty: A cross-sectional and follow-up study among older Chinese adults

BACKGROUND

Previous studies have suggested that ambient air pollution negatively affects frailty, but whether indoor air pollution exposure affects frailty is unknown.

METHOD

This study was conducted on 4946 older adults (≥60 years) followed from baseline to 4 years in the Chinese Longitudinal Healthy Longevity Survey. Household fuel types and frailty were assessed with self-rated questionnaires and physical examination. The relationships between indoor air pollution and frailty via phenotypic frailty and a frailty index were explored with logistic regression models and Cox proportional hazard regression models in both a cross-sectional and follow-up design. Additionally, the effects of indoor air pollution on phenotypic frailty together with mild cognitive impairment (MCI) were further investigated.

RESULTS

In the cross-sectional study, the adjusted ORs (95% CIs) for frailty assessment with the frailty index and phenotypic frailty were 1.28 (1.12, 1.46) and 1.36 (1.18, 1.57), respectively. Solid fuel use was a risk factor in prefrail/frail patients with [OR and 95% CI, 1.88 (1.41, 2.50)], or without MCI [OR and 95% CI, 1.37 (1.17, 1.61)], as compared with the groups with no phenotypic prefrailty/frailty and no MCI. Moreover, solid cooking fuel use was positively associated with the incidence of phenotypic prefrailty and frailty. The adjusted HRs (95% CIs) for phenotypic prefrailty and frailty were 1.26 (1.03, 1.55).

CONCLUSIONS

Solid cooking fuels can be regarded as a risk factor for frailty. Moreover, our findings suggest that more attention should be paid to solid cooking fuel using as it relates to phenotypic frailty together with MCI.

Born to Age: When Adult Congenital Heart Disease Converges With Geroscience

Advances in imaging, catheter-based interventions, congenital heart disease surgery, and clinical management of congenital heart disease (CHD) have yielded a dramatic change in age distribution of the CHD population. This implores clinicians and researchers to gain a better understanding of aging, as this will be the cornerstone to how we plan and manage this rapidly evolving group of patients. In this article, we first review the demographic changes in the CHD population and then describe the systemic complications of disease observed in young patients with CHD, following which we discuss general concepts in aging that may be transferable to the CHD population. Finally, we review inflammation and its potential impact on aging. We provide a new lens on aging in CHD and its functional consequences in CHD, with the goal of stimulating an exchange of knowledge between geroscientists and CHD.

Integrating DNA Methylation Measures of Biological Aging into Social Determinants of Health Research

PURPOSE OF REVIEW

Acceleration of biological processes of aging is hypothesized to drive excess morbidity and mortality in socially disadvantaged populations. DNA methylation measures of biological aging provide tools for testing this hypothesis.

RECENT FINDINGS

Next-generation DNA methylation measures of biological aging developed to predict mortality risk and physiological decline are more predictive of morbidity and mortality than the original epigenetic clocks developed to predict chronological age. These new measures show consistent evidence of more advanced and faster biological aging in people exposed to socioeconomic disadvantage and may be able to record the emergence of socially determined health inequalities as early as childhood. Next-generation DNA methylation measures of biological aging also indicate race/ethnic disparities in biological aging. More research is needed on these measures in samples of non-Western and non-White populations. New DNA methylation measures of biological aging open opportunities for refining inference about the causes of social disparities in health and devising policies to eliminate them. Further refining measures of biological aging by including more diversity in samples used for measurement development is a critical priority for the field.

Quantifying self-rated age

Chronological age, in conjunction with population life tables, is widely used for estimating future life expectancy. The aims of this study are to estimate a subjective ageing indicator, namely self-rated age, and to evaluate its concurrent validity in comparison with other age indicators: subjective survival probabilities, subjective age, and biological age. We use data from the Wave 6 of the Survey of Health, Ageing and Retirement in Europe, Wave 12 of the Health and Retirement Study in the United States, and life tables from the Human Mortality Database. For the statistical analysis we use multinomial regression models. Our results indicate that health status and frequency of physical activities imply similar patterns of self- rated age, subjective survival probabilities, subjective age, and biological age. However, the impact of cognitive function differs by geographical region. Self-rated age can be interpreted as a subjective adjustment that better reflects the ageing process.

The metabolome as a biomarker of aging in Drosophila melanogaster

Many biomarkers have been shown to be associated not only with chronological age but also with functional measures of biological age. In human populations, it is difficult to show whether variation in biological age is truly predictive of life expectancy, as such research would require longitudinal studies over many years, or even decades. We followed adult cohorts of 20 Drosophila Genetic Reference Panel (DGRP) strains chosen to represent the breadth of lifespan variation, obtain estimates of lifespan, baseline mortality, and rate of aging, and associate these parameters with age‐specific functional traits including fecundity and climbing activity and with age‐specific targeted metabolomic profiles. We show that activity levels and metabolome‐wide profiles are strongly associated with age, that numerous individual metabolites show a strong association with lifespan, and that the metabolome provides a biological clock that predicts not only sample age but also future mortality rates and lifespan. This study with 20 genotypes and 87 metabolites, while relatively small in scope, establishes strong proof of principle for the fly as a powerful experimental model to test hypotheses about biomarkers and aging and provides further evidence for the potential value of metabolomic profiles as biomarkers of aging.

Does Real Age Feedback Really Motivate Us to Change our Lifestyle? Results from an Online Experiment

We set out to research the causal impact of Real Age feedback, a popular tool on health and lifestyle platforms, on health behaviors. We ran an online experiment where participants were randomly assigned a Real Age that differed in both direction (older or younger) and magnitude (much or slightly) from their passport age, or to a control condition where they received no Real Age feedback. We measured the impact of Real Age feedback on motivation to begin a healthier lifestyle, interest in taking a Real Age test, and percentage click-rate on an optional health link. We found that younger Real Age feedback was associated with higher interest. In addition, participants who received a slightly older Real Age were significantly less motivated to begin a healthier lifestyle compared to not only those who received a much younger or much older Real Age, but also to those in the control condition, suggesting a backfire effect. This effect remained even after accounting for participant health, demographics, and other psychological correlates to motivation. Real Age tests may backfire and demotivate people, and the positive effects they may have on psychological states may not outweigh the negative effects. Though promising, we caution using Real Age tests in their current form as stand-alone interventions to get people motivated.

Comparing qPCR and DNA methylation-based measurements of telomere length in a high-risk pediatric cohort

Various approaches exist to assess population differences in biological aging. Telomere length (TL) is one such measure, and is associated with disease, disability and early mortality. Yet, issues surrounding precision and reproducibility are a concern for TL measurement. An alternative method to estimate TL using DNA methylation (DNAmTL) was recently developed. Although DNAmTL has been characterized in adult and elderly cohorts, its utility in pediatric populations remains unknown. We examined the comparability of leukocyte TL measurements generated using qPCR (absolute TL; aTL) to those estimated using DNAmTL in a high-risk pediatric cohort (N = 269; age: 8–13 years, 83% investigated for maltreatment). aTL and DNAmTL measurements were correlated with one another (r = 0.20, p = 0.001), but exhibited poor measurement agreement and were significantly different in paired-sample t-tests (Cohen’s d = 0.77, p < 0.001). Shorter DNAmTL was associated with older age (r = −0.25, p < 0.001), male sex (β = −0.27, p = 0.029), and White race (β = −0.74, p = 0.008). By contrast, aTL was less strongly associated with age (r = −0.13, p = 0.040), was longer in males (β = 0.31, p = 0.012), and was not associated with race (p = 0.820). These findings highlight strengths and limitations of high-throughput measures of TL; although DNAmTL replicated hypothesized associations, aTL measurements were positively skewed and did not replicate associations with external validity measures. These results also extend previous research in adults and suggest that DNAmTL is a sensitive TL measure for use in pediatric populations.

DunedinPACE, a DNA methylation biomarker of the pace of aging

Background

Measures to quantify changes in the pace of biological aging in response to intervention are needed to evaluate geroprotective interventions for humans. Previously, we showed that quantification of the pace of biological aging from a DNA-methylation blood test was possible (Belsky et al., 2020). Here, we report a next-generation DNA-methylation biomarker of Pace of Aging, DunedinPACE (for Pace of Aging Calculated from the Epigenome).

Methods

We used data from the Dunedin Study 1972-1973 birth cohort tracking within-individual decline in 19 indicators of organ-system integrity across four time points spanning two decades to model Pace of Aging. We distilled this two-decade Pace of Aging into a single-time-point DNA-methylation blood-test using elastic-net regression and a DNA-methylation dataset restricted to exclude probes with low test-retest reliability. We evaluated the resulting measure, named DunedinPACE, in five additional datasets.

Results

DunedinPACE showed high test-retest reliability, was associated with morbidity, disability, and mortality, and indicated faster aging in young adults with childhood adversity. DunedinPACE effect-sizes were similar to GrimAge Clock effect-sizes. In analysis of incident morbidity, disability, and mortality, DunedinPACE and added incremental prediction beyond GrimAge.

Conclusions

DunedinPACE is a novel blood biomarker of the pace of aging for gerontology and geroscience.

Funding

This research was supported by US-National Institute on Aging grants AG032282, AG061378, AG066887, and UK Medical Research Council grant MR/P005918/1.

Ayurvedic formulations amalaki rasayana and rasa sindoor improve age-associated memory deficits in mice by modulating dendritic spine densities

BACKGROUND

Emerging reports indicate that age-associated cognitive decline begins with the transition from young to middle-aged, and this neurological condition manifests mainly due to the progressive impairment in the adaptive homeostasis process. Moreover, cognitive decline is associated with neurodegenerative changes in older adults.

OBJECTIVE

Previous studies have shown that the administration of Ayurvedic formulations restores the homeostatic pathways and ameliorates neurodegeneration in animal models of neurodegenerative diseases. Therefore, we wanted to check whether Ayurvedic formulations can rescue or delay the age-associated cognitive decline in middle-aged mice.

MATERIAL AND METHODS

We fed two-month-old mice with amalaki aasayana (AR, 1025 mg/kg per day) or rasa sindoor (RS, 41 mg/kg per day) mixed in a gelatin-based jelly for six months. Mice eating regular chow or blank jelly served as control. Subsequently, we looked at the improvements in the cognitive and behavioural traits of the treated animals. We have also analysed the effect of these formulations on the dendritic processes of neurons, glial activation, and the formation of corpora amylacea.

RESULTS

We found a significant improvement in episodic, working- and reference-spatiotemporal memory in animals fed on AR or RS. Microscopic analyses revealed a significant increase in the dendritic spine density in the apical dendrites of the hippocampal pyramidal neurons. The treatment, however, did not significantly affect gliosis and corpora amylacea in the brains.

CONCLUSIONS

Both AR and RS showed beneficial effects on memory functions of the middle-aged mice, possibly due to their effect on the dendritic spine densities. Our findings provide strong evidence to conclude that formulations AR and RS can prevent or delay the onset of age-associated cognitive decline.

Urinary Biomarkers of Oxidative Stress in Aging: Implications for Prediction of Accelerated Biological Age in Prospective Cohort Studies

Background

Aging is a major risk factor for a range of chronic diseases. Oxidative stress theory of aging has been previously proposed as one of the mechanisms responsible for the age-related decline in organ/tissue function and the development of age-related diseases. Urine contains rich biological information on the health status of every major organ system and can be an important noninvasive source for biomarkers of systemic oxidative stress in aging.

Aims

The objective of this cross-sectional study was to validate a novel panel of urinary oxidative stress biomarkers.

Methods

Nucleic acid oxidation adducts and oxidative damage markers of lipids and proteins were assessed in urine samples from nondiabetic and currently nonsmoking subjects (n = 198) across different ages (20 to 89 years old). Urinary parameters and chronological age were correlated then the biological age of enrolled individuals was determined from the urinary oxidative stress markers using the algorithm of Klemera and Doubal.

Results

Our findings showed that 8-oxo-7,8-deoxyguanosine (8-oxoG), 8-oxo-7,8-dihydroguanosine (8-OHdG), and dityrosine (DTyr) positively correlated with chronological age, while the level of an F₂-isoprostane (iPF₂ α-VI) correlated negatively with age. We found that 8-oxoG, DTyr, and iPF₂ α-VI were significantly higher among accelerated agers compared to nonaccelerated agers and that a decision tree model could successfully identify accelerated agers with an accuracy of >92%. Discussion. Our results indicate that 8-oxoG and iPF₂ α-VI levels in the urine reveal biological aging.

Conclusion

Assessing urinary biomarkers of oxidative stress may be an important approach for the evaluation of biological age by identifying individuals at accelerated risk for the development of age-related diseases.

Unstable Childhood, Adult Adversity, and Smoking Accelerate Biological Aging Among Middle-Age African Americans: Similar Findings for GrimAge and PoAm

Objectives: The recent biological clocks GrimAge and PoAm are robust predictors of morbidity and mortality. Little research, however, has investigated the factors that influence their ticking speed. No study has used multivariate analyses to examine whether childhood adversity, adult hardship, lifestyle practices, or some combination of these factors best explains acceleration of these indices. Methods: Using a sample of 506 middle-age African Americans, the present study investigated the extent to which childhood instability, adult adversity, and lifestyle predict accelerated GrimAge and PoAm. Results: The two clocks were highly correlated and the pattern of findings was very similar for the two measures. Childhood instability, adult financial hardship, and smoking were significant predictors of both clocks. Discussion: The findings support a life course perspective where both the long arm of childhood as well as later life conditions influence speed of aging. Similar results across the two clocks enhance confidence in the findings.

Integrated Multi-Omics for Novel Aging Biomarkers and Antiaging Targets

Aging is closely related to the occurrence of human diseases; however, its exact biological mechanism is unclear. Advancements in high-throughput technology provide new opportunities for omics research to understand the pathological process of various complex human diseases. However, single-omics technologies only provide limited insights into the biological mechanisms of diseases. DNA, RNA, protein, metabolites, and microorganisms usually play complementary roles and perform certain biological functions together. In this review, we summarize multi-omics methods based on the most relevant biomarkers in single-omics to better understand molecular functions and disease causes. The integration of multi-omics technologies can systematically reveal the interactions among aging molecules from a multidimensional perspective. Our review provides new insights regarding the discovery of aging biomarkers, mechanism of aging, and identification of novel antiaging targets. Overall, data from genomics, transcriptomics, proteomics, metabolomics, integromics, microbiomics, and systems biology contribute to the identification of new candidate biomarkers for aging and novel targets for antiaging interventions.

Associations between life course socioeconomic conditions and the Pace of Aging

BACKGROUND

Socioeconomic disadvantage is a well-established predictor of morbidity and mortality, and is thought to accelerate the aging process. This study examined associations between life course socioeconomic conditions and the Pace of Aging, a longitudinal measure of age-related physiological decline.

METHODS

Data were drawn from a Swiss population-based cohort of individuals originally recruited between 2003 and 2006, and followed up for 11 years (2834 women, 2475 men aged 35 - 75 years (mean 52)). Pace of Aging was measured using three repeated assessments of 12 biomarkers reflecting multiple body systems. Analysis tested associations of socioeconomic conditions with physiological status at baseline and with the Pace of Aging.

RESULTS

Participants with more life course socioeconomic disadvantage were physiologically older at baseline and experienced faster Pace of Aging. Effect-sizes (β) for associations of childhood socioeconomic disadvantage with baseline physiological status ranged from 0.1-0.2; for adulthood socioeconomic disadvantage, effect-sizes ranged from 0.2-0.3. Effect-sizes were smaller for associations with the Pace of Aging (< 0.05 for childhood disadvantage, 0.05-0.1 for adulthood disadvantage). Those who experienced disadvantaged socioeconomic conditions from childhood to adulthood aged 10% faster over the 11 years of follow-up as compared with those who experienced consistently advantaged socioeconomic conditions. Covariate adjustment for health behaviors attenuated associations, but most remained statistically significant.

CONCLUSIONS

Socioeconomic inequalities contribute to a faster Pace of Aging, partly through differences in health behaviors. Intervention to slow aging in at risk individuals is needed by midlife, before aetiology of aging-related diseases become established.

From Model Organisms to Humans, the Opportunity for More Rigor in Methodologic and Statistical Analysis, Design, and Interpretation of Aging and Senescence Research

This review identifies frequent design and analysis errors in aging and senescence research and discusses best practices in study design, statistical methods, analyses, and interpretation. Recommendations are offered for how to avoid these problems. The following issues are addressed: (a) errors in randomization, (b) errors related to testing within-group instead of between-group differences, (c) failing to account for clustering, (d) failing to consider interference effects, (e) standardizing metrics of effect size, (f) maximum life-span testing, (g) testing for effects beyond the mean, (h) tests for power and sample size, (i) compression of morbidity versus survival curve squaring, and (j) other hot topics, including modeling high-dimensional data and complex relationships and assessing model assumptions and biases. We hope that bringing increased awareness of these topics to the scientific community will emphasize the importance of employing sound statistical practices in all aspects of aging and senescence research.

The effect of lactoferrin in aging: role and potential

Aging is frequently accompanied by various types of physiological deterioration, which increases the risk of human pathologies. Global public health efforts to increase human lifespan have increasingly focused on lowering the risk of aging-related diseases, such as diabetes, neurodegenerative diseases, cardiovascular disease, and cancers. Dietary intervention is a promising approach to maintaining human health during aging. Lactoferrin (LF) is known for its physiologically pleiotropic properties. Anti-aging interventions of LF have proven to be safe and effective for various pharmacological activities, such as anti-oxidation, anti-cellular senescence, anti-inflammation, and anti-carcinogenic. Moreover, LF has a pivotal role in modulating the major signaling pathways that influence the longevity of organisms. Thus, LF is expected to be able to attenuate the process of aging and greatly ameliorate its effects.

T Cell Fitness and Autologous CAR T Cell Therapy in Haematologic Malignancy

A range of emerging therapeutic approaches for the treatment of cancer aim to induce or augment endogenous T cell responses. Chimeric antigen receptor (CAR) T cell therapy (CTT) is one such approach that utilises the patient’s own T cells, engineered ex vivo to target cell surface antigens, to eliminate haematological malignancies. Despite mediating high rates of responses in some clinical trials, this approach can be limited by dysfunctional T cells if they are present at high frequencies either in the starting material from the patient or the CAR T cell product. The fitness of an individual’s T cells, driven by age, chronic infection, disease burden and cancer treatment, is therefore likely to be a crucial limiting factor of CTT. Currently, T cell dysfunction and its impact on CTT is not specifically quantified when patients are considering the therapy. Here, we review our current understanding of T cell fitness for CTT, how fitness may be impacted by age, chronic infection, malignancy, and treatment. Finally, we explore options to specifically tailor clinical decision-making and the CTT protocol for patients with more extensive dysfunction to improve treatment efficacy. A greater understanding of T cell fitness throughout a patient’s treatment course could ultimately be used to identify patients likely to achieve favourable CTT outcomes and improve methods for T cell collection and CTT delivery.

GPCRs Are Optimal Regulators of Complex Biological Systems and Orchestrate the Interface between Health and Disease

GPCRs arguably represent the most effective current therapeutic targets for a plethora of diseases. GPCRs also possess a pivotal role in the regulation of the physiological balance between healthy and pathological conditions; thus, their importance in systems biology cannot be underestimated. The molecular diversity of GPCR signaling systems is likely to be closely associated with disease-associated changes in organismal tissue complexity and compartmentalization, thus enabling a nuanced GPCR-based capacity to interdict multiple disease pathomechanisms at a systemic level. GPCRs have been long considered as controllers of communication between tissues and cells. This communication involves the ligand-mediated control of cell surface receptors that then direct their stimuli to impact cell physiology. Given the tremendous success of GPCRs as therapeutic targets, considerable focus has been placed on the ability of these therapeutics to modulate diseases by acting at cell surface receptors. In the past decade, however, attention has focused upon how stable multiprotein GPCR superstructures, termed receptorsomes, both at the cell surface membrane and in the intracellular domain dictate and condition long-term GPCR activities associated with the regulation of protein expression patterns, cellular stress responses and DNA integrity management. The ability of these receptorsomes (often in the absence of typical cell surface ligands) to control complex cellular activities implicates them as key controllers of the functional balance between health and disease. A greater understanding of this function of GPCRs is likely to significantly augment our ability to further employ these proteins in a multitude of diseases.

Inflammaging and Cannabinoids

Aging is a complex phenomenon associated with a wide spectrum of physical and physiological changes affecting every part of all metazoans, if they escape death prior to reaching maturity. Critical to survival, the immune system evolved as the principal component of response to injury and defense against pathogen invasions. Because how significantly immune system affects and is affected by aging, several neologisms now appear to encapsulate these reciprocal relationships, such as Immunosenescence. The central part of Immunosenescence is Inflammaging -a sustained, low-grade, sterile inflammation occurring after reaching reproductive prime. Once initiated, the impact of Inflammaging and its adverse effects determine the direction and magnitudes of further Inflammaging. In this article, we review the nature of this vicious cycle, we will propose that phytocannabinoids as immune regulators may possess the potential as effective adjunctive therapies to slow and, in certain cases, reverse the pathologic senescence to permit a more healthy aging.

Promoting brain health through physical activity among adults exposed to early life adversity: Potential mechanisms and theoretical framework

Adverse childhood experiences such as abuse, neglect, and poverty, profoundly alter neurobehavioral development in a manner that negatively impacts health across the lifespan. Adults who have been exposed to such adversities exhibit premature and more severe age-related declines in brain health. Unfortunately, it remains unclear whether the negative effects of early life adversity (ELA) on brain health can be remediated through intervention in adulthood. Physical activity may represent a low-cost behavioral approach to address the long-term consequences of ELA on brain health. However, there has been limited research examining the impact of physical activity on brain health among adults with a history of ELA. Accordingly, the purpose of this review is to (1) review the influence of ELA on brain health in adulthood and (2) highlight evidence for the role of neurotrophic factors, hypothalamic-adrenal-pituitary axis regulation, inflammatory processes, and epigenetic modifications in mediating the effects of both ELA and physical activity on brain health outcomes in adulthood. We then propose a theoretical framework to guide future research in this area.

Phenotype correlations reveal the relationships of physiological systems underlying human ageing

Ageing is characterized by degeneration and loss of function across multiple physiological systems. To study the mechanisms and consequences of ageing, several metrics have been proposed in a hierarchical model, including biological, phenotypic and functional ageing. In particular, phenotypic ageing and interconnected changes in multiple physiological systems occur in all ageing individuals over time. Recently, phenotypic age, a new ageing measure, was proposed to capture morbidity and mortality risk across diverse subpopulations in US cohort studies. Although phenotypic age has been widely used, it may overlook the complex relationships among phenotypic biomarkers. Considering the correlation structure of these phenotypic biomarkers, we proposed a composite phenotype analysis (CPA) strategy to analyse 71 biomarkers from 2074 individuals in the Rugao Longitudinal Ageing Study. CPA grouped these biomarkers into 18 composite phenotypes according to their internal correlation, and these composite phenotypes were mostly consistent with prior findings. In addition, compared with prior findings, this strategy exhibited some different yet important implications. For example, the indicators of kidney and cardiovascular functions were tightly connected, implying internal interactions. The composite phenotypes were further verified through associations with functional metrics of ageing, including disability, depression, cognitive function and frailty. Compared to age alone, these composite phenotypes had better predictive performances for functional metrics of ageing. In summary, CPA could reveal the hidden relationships of physiological systems and identify the links between physiological systems and functional ageing metrics, thereby providing novel insights into potential mechanisms underlying human ageing.

Sulfur mustard and biological ageing: A multisystem biological health score approach as an extension of the allostatic load in Sardasht chemical veterans

BACKGROUND

Mustard gas as a chemical weapon has been used in wars and its long-term side effects are substantial in the human body. This study was aimed to apply an extension of allostatic load, known as synthetic biological health score (BHS), including the wear-and-tear of four physiological systems (endocrine, inflammatory, cardiovascular and metabolic systems) and two organs (liver and kidney) to estimate biological aging caused by sulfur mustard (SM) gas poisoning.

METHODS

The plasma samples were prepared from two following groups of people; 1) 446 individuals exposed to SM gas in 1987. 2) 115 healthy members, at the same range of age and residence, as the non-exposed group. These people were chosen from the same patients' families and have not had any exposure to SM or pulmonary dysfunction. To estimate BHS, 18 blood-derived biomarkers of the mentioned systems and organs were measured and the relative contribution of many social and body parameters across the age groups was explored.

RESULTS

It was revealed, in BHS calculation, the cardiovascular system had the most effect. Also, in the SM group, BHS was significantly higher than in the control group. This feature has a positive correlation with physical parameter (BMI) and a negative correlation with social parameters (salary and educational levels).

CONCLUSION

The multisystem BHS could be useful in the evaluation of biological aging due to SM exposure. Social (education, good-paying job) and physical (BMI) parameters could influence BHS and the higher BHS indicates the progress of biological aging due to mustard gas.

Cross-species Association Between Telomere Length and Glucocorticoid Exposure

CONTEXT

Chronic exposure to glucocorticoids (GCs) or stress increases the risk of medical disorders, including cardiovascular and neuropsychiatric disorders. GCs contribute to accelerated aging; however, while the link between chronic GC exposure and disease onset is well established, the underpinning mechanisms are not clear.

OBJECTIVE

We explored the potential nexus between GCs or stress exposure and telomere length.

METHODS

In addition to rats exposed to 3 weeks of chronic stress, an iatrogenic mouse model of Cushing syndrome (CS), and a mouse neuronal cell line, we studied 32 patients with CS and age-matched controls and another cohort of 75 healthy humans.

RESULTS

(1) Exposure to stress in rats was associated with a 54.5% (P = 0.036) reduction in telomere length in T cells. Genomic DNA (gDNA) extracted from the dentate gyrus of stressed and unstressed rats showed 43.2% reduction in telomere length (P = 0.006). (2) Mice exposed to corticosterone had a 61.4% reduction in telomere length in blood gDNA (P = 5.75 × 10-5) and 58.8% reduction in telomere length in the dentate gyrus (P = 0.002). (3) We observed a 40.8% reduction in the telomere length in patients with active CS compared to healthy controls (P = 0.006). There was a 17.8% reduction in telomere length in cured CS patients, which was not different from that of healthy controls (P = 0.08). For both cured and active CS, telomere length correlated significantly with duration of hypercortisolism (R2 = 0.22, P = 0.007). (4) There was a 27.6% reduction in telomere length between low and high tertiles in bedtime cortisol levels of healthy participants (P = 0.019).

CONCLUSION

Our findings demonstrate that exposure to stress and/or GCs is associated with shortened telomeres, which may be partially reversible.

Adherence to Healthy Lifestyle and Attenuation of Biological Aging in Middle-Aged and Older Chinese Adults

BACKGROUND

Little is known about the effects of lifestyle modification on biological aging in population-based studies of middle-aged and older adults.

METHOD

We examined the individual and joint associations of multiple lifestyle factors with accelerated biological aging measured by change in frailty index (FI) over 8 years in a prospective study of Chinese adults. Data were obtained on 24 813 participants in the China Kadoorie Biobank on lifestyle factors and frailty status at baseline and at 8 years after baseline. Adherence to healthy lifestyle factors included nonsmoking or quitting smoking for reasons other than illness, avoidance of heavy alcohol consumption, daily intake of fruit and vegetables, being physically active, body mass index of 18.5-23.9 kg/m2, and waist-to-hip ratio of <0.90 (men)/0.85 (women). FI was constructed separately at baseline and resurvey using 25 age- and health-related items.

RESULTS

Overall, 8 760 (35.3%) individuals had a worsening frailty status. In multivariable-adjusted logistic regression analyses, adherence to healthy lifestyle was associated with a lower risk of worsening frailty status. Compared with robust participants maintaining 0-1 healthy lifestyle factors, the corresponding odds ratios (95% CIs) were 0.93 (0.83-1.03), 0.75 (0.67-0.84), 0.68 (0.60-0.77), and 0.55 (0.46-0.65) for robust participants with 2, 3, 4, and 5-6 healthy lifestyle factors. The decreased risk of frailty status worsening by adherence to healthy lifestyle factors was similar in both middle-aged and older adults, and in both robust and prefrail participants at baseline.

CONCLUSIONS

Adherence to a healthy lifestyle may attenuate the rate of change in biological aging in middle-aged and older Chinese adults.

Cardiometabolic Risk Trajectory Among Older Americans: Findings From the Health and Retirement Study

BACKGROUND

Cardiometabolic risk (CMR) is a key indicator of physiological decline with age, but age-related declines in a nationally representative older US population have not been previously examined.

METHODS

We examined the trajectory of CMR over 8 years of aging, from 2006/2008 to 2014/2016, among 3528 people older than age 50 in the Health and Retirement Study. We used growth curve models to examine change in total CMR as well as in individual cardiometabolic biomarkers to understand how baseline differences and rates of change vary across sociodemographic characteristics, by smoking status, and medication use.

RESULTS

Total CMR did not change among respondents who survived over 8 years. Despite significant differences in CMR across demographic and education groups at baseline, the pace of change with age did not differ by these characteristics. Among individual biomarkers, risk levels of diastolic blood pressure, resting heart rate, and total cholesterol decreased over 8 years while glycosylated hemoglobin, waist circumference, and pulse pressure increased over that time. Both the statistical significance levels and the magnitudes of the reduction over time with age in diastolic blood pressure, resting heart rate, and total cholesterol in models adjusted for age, race/ethnicity, gender, smoking, and education were reduced after controlling for blood pressure and cholesterol medication.

CONCLUSIONS

The relatively constant total CMR level over 8 years occurred because some indicators improved with age while some deteriorated in this period. Medication use contributed to the improvement in blood pressure, resting heart rate, and total cholesterol.

Diabetes mellitus correlates with increased biological age as indicated by clinical biomarkers

Chronological age (CA) is determined by time of birth, whereas biological age (BA) is based on changes on a cellular level and strongly correlates with morbidity, mortality, and longevity. Type 2 diabetes (T2D) associates with increased morbidity and mortality; thus, we hypothesized that BA would be increased and calculated it from biomarkers collected at routine clinical visits. Deidentified data was obtained from three cohorts of patients (20–80 years old)—T2D, type 1 diabetes (T1D), and prediabetes—and compared to gender- and age-matched non-diabetics. Eight clinical biomarkers that correlated with CA in people without diabetes were used to calculate BA using the Klemera and Doubal method 1 (KDM1) and multiple linear regression (MLR). The phenotypic age (PhAge) formula was used with its predetermined biomarkers. BA of people with T2D was, on average, 12.02 years higher than people without diabetes (p < 0.0001), while BA in T1D was 16.32 years higher (p < 0.0001). Results were corroborated using MLR and PhAge. The biomarkers with the strongest correlation to increased BA in T2D using KDM were A1c (R² = 0.23, p < 0.0001) and systolic blood pressure (R² = 0.21, p < 0.0001). BMI had a positive correlation to BA in non-diabetes subjects but disappeared in those with diabetes. Mortality data using the ACCORD trial was used to validate our results and showed a significant correlation between higher BA and decreased survival. In conclusion, BA is increased in people with diabetes, irrespective of pathophysiology, and to a lesser extent in prediabetes.

A toolkit for quantification of biological age from blood chemistry and organ function test data: BioAge

Methods to quantify biological aging are emerging as new measurement tools for epidemiology and population science and have been proposed as surrogate measures for healthy lifespan extension in geroscience clinical trials. Publicly available software packages to compute biological aging measurements from DNA methylation data have accelerated dissemination of these measures and generated rapid gains in knowledge about how different measures perform in a range of datasets. Biological age measures derived from blood chemistry data were introduced at the same time as the DNA methylation measures and, in multiple studies, demonstrate superior performance to these measures in prediction of healthy lifespan. However, their dissemination has been slow by comparison, resulting in a significant gap in knowledge. We developed a software package to help address this knowledge gap. The BioAge R package, available for download at GitHub ( http://github.com/dayoonkwon/BioAge ), implements three published methods to quantify biological aging based on analysis of chronological age and mortality risk: Klemera-Doubal biological age, PhenoAge, and homeostatic dysregulation. The package allows users to parametrize measurement algorithms using custom sets of biomarkers, to compare the resulting measurements to published versions of the Klemera-Doubal method and PhenoAge algorithms, and to score the measurements in new datasets. We applied BioAge to safety lab data from the CALERIE™ randomized controlled trial, the first-ever human trial of long-term calorie restriction in healthy, non-obese adults, to test effects of intervention on biological aging. Results contribute evidence that CALERIE intervention slowed biological aging. BioAge is a toolkit to facilitate measurement of biological age for geroscience.