Reliable detection of stochastic epigenetic mutations and associations with cardiovascular aging.

Stochastic epigenetic mutations (SEMs) have been proposed as novel aging biomarkers to capture heterogeneity in age-related DNA methylation changes. SEMs are defined as outlier methylation patterns at cytosine-guanine dinucleotide sites, categorized as hypermethylated (hyperSEM) or hypomethylated (hypoSEM) relative to a reference. Because SEMs are defined by their outlier status, it is critical to differentiate extreme values due to technical noise or data artifacts from those due to real biology. Using technical replicate data, we found SEM detection is not reliable: across 3 datasets, 24 to 39% of hypoSEM and 46 to 67% of hyperSEM are not shared between replicates. We identified factors influencing SEM reliability-including blood cell type composition, probe beta-value statistics, genomic location, and presence of SNPs. We used these factors in a training dataset to build a machine learning-based filter that removes unreliable SEMs, and found this filter enhances reliability in two independent validation datasets. We assessed associations between SEM loads and aging phenotypes in the Framingham Heart Study and discovered that associations with aging outcomes were in large part driven by hypoSEMs at baseline methylated probes and hyperSEMs at baseline unmethylated probes, which are the same subsets that demonstrate highest technical reliability. These aging associations were preserved after filtering out unreliable SEMs and were enhanced after adjusting for blood cell composition. Finally, we utilized these insights to formulate best practices for SEM detection and introduce a novel R package, SEMdetectR, which uses parallel programming for efficient SEM detection with comprehensive options for detection, filtering, and analysis.

Prognostic significance of growth differentiation factor-15 across age in chronic heart failure.

AIMS: Growth differentiation factor-15 (GDF15), a cytokine in the transforming growth factor family, is up-regulated in stress and inflammatory conditions and is elevated in patients with heart failure (HF). However, the age-specific attributes and prognostic significance of GDF15 across age remain unknown in chronic HF (CHF). METHODS AND RESULTS: Serum levels of GDF15 were examined in 942 hypertensive patients (median 68 years) with CHF from the SUPPORT trial across the four age groups [under 50 (n = 73), 51-59 (n = 158), 60-69 (n = 296), and 70-79 years (n = 415)] and in the continuous spectrum. Clinical correlates of GDF15 were explored using the classic stepwise and LASSO (least absolute shrinkage and selection operator) regression approaches. Interaction terms with age were tested in the LASSO regression approach. The associations with the composite outcome of HF hospitalization or all-cause death were investigated across ages. Median GDF15 levels (pg/mL) increased along with aging, from 691 in under 50 years to 855 in 51-59 years, 1114 in 60-69 years, and 1516 in 70-79 years (trend P < 0.001). Age, sex, systolic blood pressure, history of diabetes, ischaemic heart disease, left ventricular (LV) end-systolic dimension, LV ejection fraction, estimated glomerular filtration rate, haemoglobin, N-terminal pro-brain natriuretic peptide (NT-proBNP), troponin, C-reactive protein, and the use of angiotensin-converting enzyme inhibitors, diuretics, and statins were mutually selected as clinical covariates of GDF15. The LASSO regression analysis identified significant interactions between age and the history of diabetes and NT-proBNP, with particularly robust associations in patients aged between 60 and 70 years. During the mean follow-up of 8.6 years, 474 composite endpoints of HF hospitalization or death occurred. GDF15 was associated with a higher risk of HF hospitalization or all-cause death [adjusted hazard ratio 1.84 (95% confidence interval 1.45-2.33)], with a particularly heightened risk in patients aged around 70 years (Pinteraction = 0.0008). The model with GDF15 on top of other established risk factors yielded marginally higher C-statistics compared with the model without GDF15 (0.803 and 0.796, P = 0.045). The additive value of GDF15 on top of other established risk factors appeared similar across ages. A universal cut-off value of 1400 pg/mL performed well in discriminating between those with and without HF hospitalization or death. CONCLUSIONS: Some clinical correlates of GDF15 have an interaction with age. GDF15 is an important determinant of cardiovascular endpoints, particularly in patients aged around 70 years. The additive value of GDF15 appeared consistent across ages, suggesting the use of a universal cut-off value.

Telomere length and dynamics in Astyanax mexicanus cave and surface morphs.

Background: Telomeres are non-coding DNA repeats at the chromosome ends and their shortening is considered one of the major causes of aging. However, they also serve as a biomarker of environmental exposures and their length and attrition is affected by various stressors. In this study, we examined the average telomere length in Astyanax mexicanus, a species that has both surface-dwelling and cave-adapted populations. The cave morph descended from surface ancestors and adapted to a markedly different environment characterized by specific biotic and abiotic stressors, many of which are known to affect telomere length. Our objective was to explore whether telomere length differs between the two morphs and whether it serves as a biological marker of aging or correlates with the diverse environments the morphs are exposed to. Methods: We compared telomere length and shortening between laboratory-reared Pachón cavefish and Rio Choy surface fish of A. mexicanus across different tissues and ages. Results: Astyanax mexicanus surface fish exhibited longer average telomere length compared to cavefish. In addition, we did not observe telomere attrition in either cave or surface form as a result of aging in adults up to 9 years old, suggesting that efficient mechanisms prevent telomere-mediated senescence in laboratory stocks of this species, at least within this time frame. Our results suggest that telomere length in Astyanax may be considered a biomarker of environmental exposures. Cavefish may have evolved shorter and energetically less costly telomeres due to the absence of potential stressors known to affect surface species, such as predator pressure and ultra-violet radiation. This study provides the first insights into telomere dynamics in Astyanax morphs and suggests that shorter telomeres may have evolved as an adaptation to caves.

Small immunological clocks identified by deep learning and gradient boosting.

Background: The aging process affects all systems of the human body, and the observed increase in inflammatory components affecting the immune system in old age can lead to the development of age-associated diseases and systemic inflammation. Results: We propose a small clock model SImAge based on a limited number of immunological biomarkers. To regress the chronological age from cytokine data, we first use a baseline Elastic Net model, gradient-boosted decision trees models, and several deep neural network architectures. For the full dataset of 46 immunological parameters, DANet, SAINT, FT-Transformer and TabNet models showed the best results for the test dataset. Dimensionality reduction of these models with SHAP values revealed the 10 most age-associated immunological parameters, taken to construct the SImAge small immunological clock. The best result of the SImAge model shown by the FT-Transformer deep neural network model has mean absolute error of 6.94 years and Pearson ρ = 0.939 on the independent test dataset. Explainable artificial intelligence methods allow for explaining the model solution for each individual participant. Conclusions: We developed an approach to construct a model of immunological age based on just 10 immunological parameters, coined SImAge, for which the FT-Transformer deep neural network model had proved to be the best choice. The model shows competitive results compared to the published studies on immunological profiles, and takes a smaller number of features as an input. Neural network architectures outperformed gradient-boosted decision trees, and can be recommended in the further analysis of immunological profiles.

Periostin Plasma Levels and Changes on Physical and Cognitive Capacities in Community-Dwelling Older Adults.

Periostin, involved in extracellular matrix development and support, has been shown to be elevated in senescent tissues and fibrotic states, transversal signatures of aging. We aimed to explore associations between plasma periostin and physical and cognitive capacity evolution among older adults. Our hypothesis was that higher levels of plasma periostin will be associated with worse physical and mental capacities along time. Analyses included 1 096 participants (mean age = 75.3 years ± 4.4; 63.9% women) from the Multidomain Alzheimer Preventive Trial. Periostin levels (pg/mL) were measured in plasma collected at year 1. Periostin was used in continuous variable, and as a dichotomous variable highest quartile (POSTN+) versus lowest 3 quartiles (POSTN-) were used. Outcomes were measured annually over 4 years and included: gait speed (GS), short physical performance battery (SPPB) score, 5-times sit-to-stand test (5-STS), and handgrip strength (HS) as physical and cognitive composite z-score (CCS) and the Mini-Mental State Examination (MMSE) as cognitive endpoints. Plasma periostin as a continuous variable was associated with the worsening of physical and cognitive capacities over 4 years of follow-up, specifically the SPPB score, the 5-STS, and CCS in full-adjusted models. POSTN+ was associated with worse evolution in the physical (GS: [ß = -0.057, 95% confidence interval (CI) = -0.101, -0.013], SPPB score [ß = -0.736, 95% CI = -1.091, -0.381], 5-STS [ß = 1.681, 95% CI = 0.801, 2.561]) as well as cognitive (CCS [ß = -0.215, 95% CI = -0.335, -0.094]) domains compared to POSTN- group. No association was found with HS or the MMSE score. Our study showed for the first time that increased plasma periostin levels were associated with declines in both physical and cognitive capacities in older adults over a 4-year follow-up. Further research is needed to evaluate whether periostin might be used as a predictive biomarker of functional decline at an older age.

[The relationship between the relative length of leukocyte telomeres and mtDNA copy number and acute coronary syndrome in a 15-year follow-up.]

OBJECTIVE: to study the association of relative leukocyte DNA telomere length with death from natural causes during a 15-year follow-up in a middle-aged and elderly Siberian population. Study of the association of the relative length of leukocyte telomeres (LTL) with fatal outcomes during a 15-year follow-up of a random population sample formed in 2003-2005 (n=9 360, 45-69 years old, Novosibirsk, HAPIEE project). The main group included the persons died from natural causes (except external) without a previous history of CVD and cancer (n=609); controls were stratified by sex and age (n=799). The analysis of relative LTL at baseline was performed using quantitative real-time PCR. We estimated the odds ratio of all-cause death per 1 decile shortening of LTD as a continuous variable in a multivariable-adjusted logistic regression. The carriers of shorter telomere carriers had an increased risk of death from natural causes over the next 15 years (OR=1,37, 95% CI 1,31-1,44) per decile of LTL decrease, regardless of other factors. The risk coefficients were similar for death from CVD (1,39), cancer (1,42), and other non-external causes (1,51). In studied middle-aged and elderly Siberian (Caucasoid) population cohort the LTL was an independent inverse predictor of the 15-year risk of death from natural causes.

DNA methylation-based measures of biological aging and cognitive decline over 16-years: preliminary longitudinal findings in midlife.

DNA methylation-based (DNAm) measures of biological aging associate with increased risk of morbidity and mortality, but their links with cognitive decline are less established. This study examined changes over a 16-year interval in epigenetic clocks (the traditional and principal components [PC]-based Horvath, Hannum, PhenoAge, GrimAge) and pace of aging measures (Dunedin PoAm, Dunedin PACE) in 48 midlife adults enrolled in the longitudinal arm of the Adult Health and Behavior project (56% Female, baseline AgeM = 44.7 years), selected for discrepant cognitive trajectories. Cognitive Decliners (N = 24) were selected based on declines in a composite score derived from neuropsychological tests and matched with participants who did not show any decline, Maintainers (N = 24). Multilevel models with repeated DNAm measures within person tested the main effects of time, group, and group by time interactions. DNAm measures significantly increased over time generally consistent with elapsed time between study visits. There were also group differences: overall, Cognitive Decliners had an older PC-GrimAge and faster pace of aging (Dunedin PoAm, Dunedin PACE) than Cognitive Maintainers. There were no significant group by time interactions, suggesting accelerated epigenetic aging in Decliners remained constant over time. Older PC-GrimAge and faster pace of aging may be particularly sensitive to cognitive decline in midlife.

Epigenetic age predictors in community-dwelling adults with high impact knee pain.

Gerontological research reveals considerable interindividual variability in aging phenotypes, and emerging evidence suggests that high impact chronic pain may be associated with various accelerated biological aging processes. In particular, epigenetic aging is a robust predictor of health-span and disability compared to chronological age alone. The current study aimed to determine whether several epigenetic aging biomarkers were associated with high impact chronic pain in middle to older age adults (44-78 years old). Participants (n = 213) underwent a blood draw, demographic, psychosocial, pain and functional assessments. We estimated five epigenetic clocks and calculated the difference between epigenetic age and chronological age, which has been previously reported to predict overall mortality risk, as well as included additional derived variables of epigenetic age previously associated with pain. There were significant differences across Pain Impact groups in three out of the five epigenetic clocks examined (DNAmAge, DNAmPhenoAge and DNAmGrimAge), indicating that pain-related disability during the past 6 months was associated with markers of epigenetic aging. Only DNAmPhenoAge and DNAmGrimAge were associated with higher knee pain intensity during the past 48 h. Finally, pain catastrophizing, depressive symptomatology and more neuropathic pain symptoms were significantly associated with an older epigenome in only one of the five epigenetic clocks (i.e. DNAmGrimAge) after correcting for multiple comparisons (corrected p's < 0.05). Given the scant literature in relation to epigenetic aging and the complex experience of pain, additional research is needed to understand whether epigenetic aging may help identify people with chronic pain at greater risk of functional decline and poorer health outcomes.

Large-scale chromatin reorganization reactivates placenta-specific genes that drive cellular aging.

Nuclear deformation, a hallmark frequently observed in senescent cells, is presumed to be associated with the erosion of chromatin organization at the nuclear periphery. However, how such gradual changes in higher-order genome organization impinge on local epigenetic modifications to drive cellular mechanisms of aging has remained enigmatic. Here, through large-scale epigenomic analyses of isogenic young, senescent, and progeroid human mesenchymal progenitor cells (hMPCs), we delineate a hierarchy of integrated structural state changes that manifest as heterochromatin loss in repressive compartments, euchromatin weakening in active compartments, switching in interfacing topological compartments, and increasing epigenetic entropy. We found that the epigenetic de-repression unlocks the expression of pregnancy-specific beta-1 glycoprotein (PSG) genes that exacerbate hMPC aging and serve as potential aging biomarkers. Our analyses provide a rich resource for uncovering the principles of epigenomic landscape organization and its changes in cellular aging and for identifying aging drivers and intervention targets with a genome-topology-based mechanism.

Distinct biological ages of organs and systems identified from a multi-omics study.

Biological age (BA) has been proposed to evaluate the aging status instead of chronological age (CA). Our study shows evidence that there might be multiple "clocks" within the whole-body system: systemic aging drivers/clocks overlaid with organ/tissue-specific counterparts. We utilize multi-omics data, including clinical tests, immune repertoire, targeted metabolomic molecules, gut microbiomes, physical fitness examinations, and facial skin examinations, to estimate the BA of different organs (e.g., liver, kidney) and systems (immune and metabolic system). The aging rates of organs/systems are diverse. People's aging patterns are different. We also demonstrate several applications of organs/systems BA in two independent datasets. Mortality predictions are compared among organs' BA in the dataset of the United States National Health and Nutrition Examination Survey. Polygenic risk score of BAs constructed in the Chinese Longitudinal Healthy Longevity Survey cohort can predict the possibility of becoming centenarian.

Heritability of the glycan clock of biological age.

Immunoglobulin G is posttranslationally modified by the addition of complex N-glycans affecting its function and mediating inflammation at multiple levels. IgG glycome composition changes with age and health in a predictive pattern, presumably due to inflammaging. As a result, a novel biological aging biomarker, glycan clock of age, was developed. Glycan clock of age is the first of biological aging clocks for which multiple studies showed a possibility of clock reversal even with simple lifestyle interventions. However, none of the previous studies determined to which extent the glycan clock can be turned, and how much is fixed by genetic predisposition. To determine the contribution of genetic and environmental factors to phenotypic variation of the glycan clock, we performed heritability analysis on two TwinsUK female cohorts. IgG glycans from monozygotic and dizygotic twin pairs were analyzed by UHPLC and glycan age was calculated using the glycan clock. In order to determine additive genetic, shared, and unique environmental contributions, a classical twin design was applied. Heritability of the glycan clock was calculated for participants of one cross-sectional and one longitudinal cohort with three time points to assess the reliability of measurements. Heritability estimate for the glycan clock was 39% on average, suggesting a moderate contribution of additive genetic factors (A) to glycan clock variation. Remarkably, heritability estimates remained approximately the same in all time points of the longitudinal study, even though IgG glycome composition changed substantially. Most environmental contributions came from shared environmental factors (C), with unique environmental factors (E) having a minor role. Interestingly, heritability estimates nearly doubled, to an average of 71%, when we included age as a covariant. This intervention also inflated the estimates of unique environmental factors contributing to glycan clock variation. A complex interplay between genetic and environmental factors defines alternative IgG glycosylation during aging and, consequently, dictates the glycan clock's ticking. Apparently, environmental factors (including lifestyle choices) have a strong impact on the biological age measured with the glycan clock, which additionally clarifies why this aging clock is one of the most potent biomarkers of biological aging.

Global, cell non-autonomous gene regulation drives individual lifespan among isogenic C. elegans.

Across species, lifespan is highly variable among individuals within a population. Even genetically identical Caenorhabditis elegans reared in homogeneous environments are as variable in lifespan as outbred human populations. We hypothesized that persistent inter-individual differences in expression of key regulatory genes drives this lifespan variability. As a test, we examined the relationship between future lifespan and the expression of 22 microRNA promoter::GFP constructs. Surprisingly, expression of nearly half of these reporters, well before death, could effectively predict lifespan. This indicates that prospectively long- vs. short-lived individuals have highly divergent patterns of transgene expression and transcriptional regulation. The gene-regulatory processes reported on by two of the most lifespan-predictive transgenes do not require DAF-16, the FOXO transcription factor that is a principal effector of insulin/insulin-like growth factor (IGF-1) signaling. Last, we demonstrate a hierarchy of redundancy in lifespan-predictive ability among three transgenes expressed in distinct tissues, suggesting that they collectively report on an organism-wide, cell non-autonomous process that acts to set each individual's lifespan.

Aging biomarkers and the measurement of health and risk.

Prevention of age-related disorders is increasingly in focus of health policies, and it is hoped that early intervention on processes of deterioration can promote healthier and longer lives. New opportunities to slow down the aging process are emerging with new fields such as personalized nutrition. Data-intensive research has the potential to improve the precision of existing risk factors, e.g., to replace coarse-grained markers such as blood cholesterol with more detailed multivariate biomarkers. In this paper, we follow an attempt to develop a new aging biomarker. The vision among the project consortium, comprising both research and industrial partners, is that the new biomarker will be predictive of a range of age-related conditions, which may be preventable through personalized nutrition. We combine philosophical analysis and ethnographic fieldwork to explore the possibilities and challenges of managing aging through bodily signs that are not straightforwardly linked to symptomatic disease. We document how the improvement of measurement brings about new conceptual challenges of demarcating healthy and unhealthy states. Moreover, we highlight that the reframing of aging as risk has social and ethical implications, as it is generative of normative notions of what constitutes successful aging and good citizenship.

Analysis of Epigenetic Age Predictors in Pain-Related Conditions.

Chronic pain prevalence is high worldwide and increases at older ages. Signs of premature aging have been associated with chronic pain, but few studies have investigated aging biomarkers in pain-related conditions. A set of DNA methylation (DNAm)-based estimates of age, called "epigenetic clocks," has been proposed as biological measures of age-related adverse processes, morbidity, and mortality. The aim of this study is to assess if different pain-related phenotypes show alterations in DNAm age. In our analysis, we considered three cohorts for which whole-blood DNAm data were available: heat pain sensitivity (HPS), including 20 monozygotic twin pairs discordant for heat pain temperature threshold; fibromyalgia (FM), including 24 cases and 20 controls; and headache, including 22 chronic migraine and medication overuse headache patients (MOH), 18 episodic migraineurs (EM), and 13 healthy subjects. We used the Horvath's epigenetic age calculator to obtain DNAm-based estimates of epigenetic age, telomere length, levels of 7 proteins in plasma, number of smoked packs of cigarettes per year, and blood cell counts. We did not find differences in epigenetic age acceleration, calculated using five different epigenetic clocks, between subjects discordant for pain-related phenotypes. Twins with high HPS had increased CD8+ T cell counts (nominal p = 0.028). HPS thresholds were negatively associated with estimated levels of GDF15 (nominal p = 0.008). FM patients showed decreased naive CD4+ T cell counts compared with controls (nominal p = 0.015). The severity of FM manifestations expressed through various evaluation tests was associated with decreased levels of leptin, shorter length of telomeres, and reduced CD8+ T and natural killer cell counts (nominal p < 0.05), while the duration of painful symptoms was positively associated with telomere length (nominal p = 0.034). No differences in DNAm-based estimates were detected for MOH or EM compared with controls. In summary, our study suggests that HPS, FM, and MOH/EM do not show signs of epigenetic age acceleration in whole blood, while HPS and FM are associated with DNAm-based estimates of immunological parameters, plasma proteins, and telomere length. Future studies should extend these observations in larger cohorts.

Association of Epigenetic Age and p16INK4a With Markers of T-Cell Composition in a Healthy Cohort.

How the measurement of aging biomarkers in peripheral blood T-lymphocytes (PBTLs) is influenced by cell composition is unclear. Here, we collected peripheral blood and isolated CD3+ PBTLs from 117 healthy couples between the ages of 21 and 72. Each sample was profiled for Horvath epigenetic clock (DNAm), p16INK4a expression, cytomegalovirus (CMV) seropositivity and 74 mRNA markers of PBTL subtype, differentiation, immune checkpoints, and cytokine production. Correlations between individual aging biomarkers (DNAm or p16INK4a) and PBTL mRNAs were corrected for chronological age, sex, and couple. DNAm measurements correlated with CMV seropositivity as well as PBTL mRNAs indicative of effector function (CD8A, EOMES, TBX21, GZMB), poor proliferative capacity (KLRG1, CD57), differentiation (CD45RO, CD45RA), and immune checkpoints (PDCD1, TIGIT, LAG3, CD160, CD244). In contrast, only three PBTL mRNAs, CD28, CD244, and p14ARF, showed a significant association with p16INK4a. p16INK4a expression also showed a weaker association with immunosenescent PBTL subsets than DNAm in flow cytometry analyses. These data suggest that PBTL composition has a greater influence on DNAm than p16INK4a and link accelerated epigenetic aging to immunosenescent phenotypes.

Impact of age-related T cell dynamics on the identification of biomarkers predictive of immunotherapy discontinuation: a prospective cohort study.

BACKGROUND: The impact of biologic aging on immune checkpoint inhibitor (ICI) toxicity and efficacy is underexplored in metastatic melanoma (MM). In peripheral blood T-lymphocytes (PBTLs), biologic aging is characterized by changes in T-cell composition and cellular senescence. Whether indicators of PBTL biologic aging vary in MM patients or can be used to predict premature ICI discontinuation (pID) is unknown. METHODS: We prospectively collected PBTLs from 117 cancer-free controls and 46 MM patients scheduled to begin pembrolizumab or nivolumab monotherapy. 74 mRNAs indicative of T-cell subsets, activation, co-stimuation/inhibition and cellular senescence were measured by Nanostring. Relationships between each mRNA and chronologic age were assessed in patients and controls. Candidate biomarkers were identified by calculating the hazard ratio (HR) for pID in patients divided into low and high groups based on log-transformed mRNA levels or the magnitude by which each mRNA measurement deviated from the control trend (Δage). Area under the curve (AUC) analyses explored the ability of each biomarker to discriminate between patients with and without pID at 6 months and 1 year. RESULTS: Fifteen mRNAs correlated with chronologic age in controls, including markers of T-cell subsets, differentiation, cytokine production and co-stimulation/inhibition. None of these mRNAs remained correlated with age in patients. Median follow-up was 94.8 (1.6-195.7) weeks and 35 of 46 patients discontinued therapy (23 progression, 7 toxicity, 5 comorbidity/patient preference). Elevated pre-therapy CD8A (HR 2.2[1.1-4.9]), CD45RB (HR 2.9[1.4-5.8]) and TNFRSF14 (HR 2.2[1.1-4.5]) levels predicted pID independent of Δage-correction. CD3ε, CD27 and FOXO1 predicted pID only after Δage-correction (HR 2.5[1.3-5.1]; 3.7[1.8-7.8]; 2.1[1.1-4.3]). AUC analysis identified Δage-CD3ε and -CD27 as candidate predictors of pID (AUC=0.73; 0.75). CONCLUSIONS: Correlations between transcriptional markers of PBTL composition and chronologic age are disrupted in MM. Correcting for normal, age-related trends in biomarker expression unveils new biomarker candidates predictive of ICI outcomes.

Brain Age Prediction With Morphological Features Using Deep Neural Networks: Results From Predictive Analytic Competition 2019.

Morphological changes in the brain over the lifespan have been successfully described by using structural magnetic resonance imaging (MRI) in conjunction with machine learning (ML) algorithms. International challenges and scientific initiatives to share open access imaging datasets also contributed significantly to the advance in brain structure characterization and brain age prediction methods. In this work, we present the results of the predictive model based on deep neural networks (DNN) proposed during the Predictive Analytic Competition 2019 for brain age prediction of 2638 healthy individuals. We used FreeSurfer software to extract some morphological descriptors from the raw MRI scans of the subjects collected from 17 sites. We compared the proposed DNN architecture with other ML algorithms commonly used in the literature (RF, SVR, Lasso). Our results highlight that the DNN models achieved the best performance with MAE = 4.6 on the hold-out test, outperforming the other ML strategies. We also propose a complete ML framework to perform a robust statistical evaluation of feature importance for the clinical interpretability of the results.

Chromosomal stability in buccal cells was linked to age but not affected by exercise and nutrients - Vienna Active Ageing Study (VAAS), a randomized controlled trial.

The purpose of this study was to investigate the effect of six months strength training with or without supplementing protein and vitamins, on chromosomal integrity of buccal cells in institutionalized elderly. One hundred seventeen women and men (65-98 years) performed either resistance training (RT), RT combined with a nutritional supplement (RTS) or cognitive training (CT) twice per week for six months. Participants' fitness was measured using the 6 min walking, the chair rise, and the handgrip strength test. Genotoxicity and cytotoxicity parameters were investigated with the Buccal Micronucleus Cytome (BMcyt) assay. Six minutes walking and chair rise performance improved significantly, however, no changes of the parameters of the BMcyt were detected. Age and micronuclei (MN) frequency correlated significantly, for both women (r = 0.597, p = 0.000) and men (r = 0.508, p = 0.000). Squared regressions revealed a significant increase in the MN frequency of buccal cells with age (R2 = 0.466, p = 0.000). Interestingly and contrary to what was shown in blood lymphocytes, chromosomal damage in buccal cells increases until very old age, which might qualify them as a valid biomarker for aging. Unexpectedly, in this group of institutionalized elderly, resistance training using elastic bands had no effect on chromosomal damage in buccal cells.

Aging Biomarkers and Novel Targets for Anti-Aging Interventions.

The aging population worldwide is expanding at an increasing rate. By 2050, approximately a quarter of the world population will consist of the elderly. To slow down the aging process, exploration of aging biomarkers and the search for novel antiaging targets have attracted much interest. Nonetheless, because aging research is costly and time-consuming and the aging process is complicated, aging research is considered one of the most difficult biological fields. Here, providing a broader definition of aging biomarkers, we review cutting-edge research on aging biomarkers at the molecular, cellular, and organismal levels, thus shedding light on the relations between aging and telomeres, longevity proteins, a senescence-associated secretory phenotype, the gut microbiota and metabolic patterns. Furthermore, we evaluate the suitability of these aging biomarkers for the development of novel antiaging targets on the basis of the most recent research on this topic. We also discuss the possible implications and some controversies regarding these biomarkers for therapeutic interventions in aging and age-related disease processes. We have attempted to cover all of the latest research on aging biomarkers in our review but there are countless studies on aging biomarkers, and the topic of aging interventions will continue to deepen even further. We hope that our review can serve as a reference for better characterization of aging and as inspiration for the screening of antiaging drugs as well as give some clues to further research into aging biomarkers and antiaging targets.