Biological Age Research Articles

Features of the impact of production factors on the processes of premature aging and changes in biological age

Features of the impact of production factors on the processes of premature aging and changes in biological age

A critical review of biochar as an environmental functional material in soil ecosystems for migration and transformation mechanisms and ecological risk assessment.

At present, biochar has a large application potential in soil amelioration, pollution remediation, carbon sequestration and emission reduction, and research on the effect of biochar on soil ecology and environment has made positive progress. However, under natural and anthropogenic perturbations, biochar may undergo a series of environmental behaviors such as migratory transformation, mineralization and decomposition, and synergistic transport, thus posing certain potential risks. This paper outlines the multi-interfacial migration pathway of biochar in "air-soil-plant-animal-water", and analyzes the migration process and mechanism at different interfaces during the preparation, transportation and application of biochar. The two stages of the biochar mineralization process (mineralization of easily degradable aliphatic carbon components in the early stage and mineralization of relatively stable aromatic carbon components in the later stage) were described, the self-influencing factors and external environmental factors of biochar mineralization were analyzed, and the mineral stabilization mechanism and positive/negative excitation effects of biochar into the soil were elucidated. The proximity between field natural and artificially simulated aging of biochar were analyzed, and the change of its properties showed a trend of biological aging>chemical aging>physical aging>natural aging, and in order to improve the simulation and prediction, the artificially simulated aging party needs to be changed from a qualitative method to a quantitative method. The technical advantages, application scope and potential drawbacks of different biochar modification methods were compared, and biological modification can create new materials with enhanced environmental application. The stability performance of modified biochar was compared, indicating that raw materials, pyrolysis temperature and modification method were the key factors affecting the stability of biochar. The potential risks to the soil environment from different pollutants carried by biochar were summarized, the levels of pollutants released from biochar in the soil environment were highlighted, and a comprehensive selection of ecological risk assessment methods was suggested in terms of evaluation requirements, data acquisition and operation difficulty. Dynamic tracing of migration decomposition behavior, long-term assessment of pollution remediation effects, and directional design of modified composite biochar materials were proposed as scientific issues worthy of focused attention. The results can provide a certain reference basis for the theoretical research and technological development of biochar.

Early-life tobacco smoke exposure and stroke risk: a prospective study of 341,783 and 352,737 UK Biobank participants.

Stroke is a life-threatening condition that causes a major medical burden globally. The currently used methods for the prevention or prediction of stroke have certain limitations. Exposure to tobacco in early life, including smoking during adolescence and maternal smoking during pregnancy, can affect adolescent development and lead to several negative outcomes. However, the association between early-life tobacco exposure and stroke is not known. In this prospective cohort study, for the analyses involving exposure to maternal smoking during pregnancy and age of smoking initiation, we included 304,984 and 342,893 participants, respectively., respectively from the UK Biobank. Cox proportional hazard regression model and subgroup analyses were performed to investigate the association between early-life tobacco exposure and stroke. Mediation analyses were performed to identify the mediating role of biological aging in the association between early tobacco exposure and stroke. Compared with participants whose mothers did not smoke during pregnancy, participants whose mothers smoked during pregnancy showed an 11% increased risk of stroke (HR: 1.11, 95% CI: 1.05-1.18, P < 0.001). Compared with participants who never smoked, participants who smoked during adulthood, adolescence and childhood showed a 22%, 24%, and 38% increased risk of stroke during their adulthood, respectively. Mediation analysis indicated that early-life tobacco exposure can cause stroke by increasing biological aging. This study reveals that exposure to tobacco during early life is associated with an increased risk of experiencing a stroke, and increased biological aging can be the underlying mechanism.

Clinical biomarker-based biological age predicts deaths in Brazilian adults: the ELSA-Brasil study.

Biological age is a construct that seeks to evaluate the biological wear and tear process of the organism that cannot be observed by chronological age. We estimate individuals' biological age based on biomarkers from multiple systems and validate it through its association with mortality from natural causes. Biological age was estimated in 12,109 participants (6621 women and 5488 men) from the first visit of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) who had valid data for the biomarkers used in the analyses. Biological age was estimated using the Klemera and Doubal method. The difference between chronological age and biological age (Δage) was computed. Cox proportional hazard models stratified by sex were used to assess whether Δage was associated with mortality risk after a median follow-up of 9.1years. The accuracy of the models was estimated by the area under the curve (AUC). Δage had equal mean for men and women, with greater variability for men. Cox models showed that every 1-year increase in Δage was associated with increased mortality in men (HR (95% CI) 1.21; 1.17-1.25) and women (HR (95% CI) 1.24; 1.15-1.34), independently of chronological age. Results of the AUC demonstrated that the predictive power of models that only included chronological age (AUC chronological age = 0.7396) or Δage (AUC Δage = 0.6842) was lower than those that included both, chronological age and Δage (AUC chronological age + Δage = 0.802), in men. This difference was not observed in women. We demonstrate that biological age is strongly related to mortality in both genders and is a valid predictor of death in Brazilian adults, especially among men.

Association of Biological Age Acceleration with Cardiac Morphology, Function, and Incident Heart Failure: Insights from UK Biobank Participants.

Advanced age is associated with an increased risk of adverse cardiovascular events. The relationship between biological age acceleration (BAA), cardiac size, cardiac function, and heart failure (HF) is not well-defined. Utilizing the UK Biobank cohort, we assessed biological age using the Klemera-Doubal and PhenoAge method. BAA was quantified by residual analysis compared to chronological age. Cardiovascular magnetic resonance (CMR) imaging provided detailed insights into cardiac structure and function. We employed multivariate regression to examine links between BAA and CMR-derived cardiac phenotypes. Cox proportional hazard regression models analyses was applied to explore the causative relationship between BAA and HF. Additionally, Mendelian randomization was used to investigate the genetic underpinnings of these associations. A significant correlation was found between increased BAA and deleterious changes in cardiac structure, such as diminished left ventricular mass, lower overall ventricular volume, and reduced stroke volumes across ventricles and atria. Throughout a median follow-up of 13.8 years, participants with greater biological aging showed a heightened risk of HF (26% per standard deviation [SD] increase in KDM-BA acceleration, 95% confidence intervals [CI]: 23%-28%; 33% per SD increase in PhenoAge acceleration, 95% CI: 32%-35%). Mendelian randomization analysis suggests a likely causal link between BAA, vital cardiac metrics, and HF risk. In this cohort, accelerated biological aging may serve as a risk indicator for altered cardiac dimensions, functionality, and the onset of heart failure among middle-aged and elderly adults. It holds promise as a focal point for evaluating risk and developing targeted interventions.

Proteomic aging clock (PAC) predicts age-related outcomes in middle-aged and older adults.

Beyond mere prognostication, optimal biomarkers of aging provide insights into qualitative and quantitative features of biological aging and might, therefore, offer useful information for the testing and, ultimately, clinical use of gerotherapeutics. We aimed to develop a proteomic aging clock (PAC) for all-cause mortality risk as a proxy of biological age. Data were from the UK Biobank Pharma Proteomics Project, including 53,021 participants aged between 39 and 70 years and 2923 plasma proteins assessed using the Olink Explore 3072 assay®. 10.9% of the participants died during a mean follow-up of 13.3 years, with the mean age at death of 70.1 years. The Spearman correlation between PAC proteomic age and chronological age was 0.77. PAC showed robust age-adjusted associations and predictions for all-cause mortality and the onset of various diseases in general and disease-free participants. The proteins associated with PAC proteomic age deviation were enriched in several processes related to the hallmarks of biological aging. Our results expand previous findings by showing that biological age acceleration, based on PAC, strongly predicts all-cause mortality and several incident disease outcomes. Particularly, it facilitates the evaluation of risk for multiple conditions in a disease-free population, thereby, contributing to the prevention of initial diseases, which vary among individuals and may subsequently lead to additional comorbidities.

Physical training and external load management for young athletes

Football today is more intense and demanding than ever before and these increasing physical demands have a direct impact on grassroots players, leading to ever greater interest in determining the external load variables using GPS in lower categories. The objective of this study is to observe and analyse the mean figures for the variables Distance(m), High Acc(m) and High Dec(m), HSR Abs(m), HMLD(m) and MAX Speed (km·h-1) per player aged 15, 16 and 17 based on their position in a competitive match. We also aim to determine if U16 players are able to compete in a U17 and U18 category team. A total of 57 male players, between 15 and 17 years old, participated in the study, divided by team corresponding to their age, and members of farm teams of a professional football club in the Community of Madrid. The results obtained for the mentioned variables show that some players could play at a higher category, specifically U16 Centre-Backs and Forwards and U17 Wing-Backs, Midfielders and Wingers. However, it must be noted that these results may be influenced by factors such as biological age of the players, the minutes of play, the style of play, the rival in the match, the pitch conditions and weather. Keywords: Grassroots Football, External Load, GPS, Distance(m), High Acc(m)/Dec(m), HSR Abs(m), HMLD(m), MAX Speed(km·h-1)

Childhood obesity accelerates biological ageing: is oxidative stress a link?

Obesity is multifactorial pathophysiological condition with an imbalance in biochemical, immunochemical, redox status and genetic parameters values. We aimed estimate connection between relative leukocyte telomere lengths (rLRL) - biomarker of cellular aging with metabolic and redox status biomarkers values in a group of obese and lean children. The study includes 110 obese and 42 lean children and adolescents, both genders. The results suggested that rLTL are significantly shorter in obese, compared to lean group (p<0,01). Negative correlation of rLTL with total oxidant status, TOS (Spearman's ρ = -0.365, p<0.001) as well as with C reactive protein (Spearman's ρ= -0,363, p<0.001) were observed. Principal component analysis (PCA) extracted three distinct factors (i.e. principal components) entitled as: prooxidant factor with 35% of total variability; antioxidant factor with 30% of total variability and lipid antioxidant - biological ageing factor with 12% of the total variability. The most important predictor of body mass index (BMI) >30kg/m2 according to logistic regression analysis was PCA derived antioxidant factor's score (OR: 1.66, 95th Cl: 1.05-2.6, p=0.029). PCA analysis confirmed oxidative stress importance in biological ageing caused by obesity and its multiple consequences related to prooxidants augmentation and antioxidants exhaustion and gave us clear signs of disturbed cellular homeostasis deepness, even before any overt disease occurrence.

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

Heterogeneity in ageing rates drives the need for research into lifestyle secrets of successful agers. Biological age, predicted by epigenetic clocks, has been shown to be a more reliable measure of ageing than chronological age. Dietary habits are known to affect the ageing process. However, much remains to be learnt about specific dietary habits that may directly affect the biological process of ageing. To identify food groups that are directly related to biological ageing, using Copula Graphical Models. We performed a preregistered analysis of 3,990 postmenopausal women from the Women's Health Initiative, based in North America. Biological age acceleration was calculated by the epigenetic clock PhenoAge using whole-blood DNA methylation. Copula Graphical Modelling, a powerful data-driven exploratory tool, was used to examine relations between food groups and biological ageing whilst adjusting for an extensive amount of confounders. Two food group-age acceleration networks were established: one based on the MyPyramid food grouping system and another based on item-level food group data. Intake of eggs, organ meat, sausages, cheese, legumes, starchy vegetables, added sugar and lunch meat was associated with biological age acceleration, whereas intake of peaches/nectarines/plums, poultry, nuts, discretionary oil and solid fat was associated with decelerated ageing. We identified several associations between specific food groups and biological ageing. These findings pave the way for subsequent studies to ascertain causality and magnitude of these relationships, thereby improving the understanding of biological mechanisms underlying the interplay between food groups and biological ageing.

Quantifying the stochastic component of epigenetic aging.

DNA methylation clocks can accurately estimate chronological age and, to some extent, also biological age, yet the process by which age-associated DNA methylation (DNAm) changes are acquired appears to be quasi-stochastic, raising a fundamental question: how much of an epigenetic clock's predictive accuracy could be explained by a stochastic process of DNAm change? Here, using DNAm data from sorted immune cells, we build realistic simulation models, subsequently demonstrating in over 22,770 sorted and whole-blood samples from 25 independent cohorts that approximately 66-75% of the accuracy underpinning Horvath's clock could be driven by a stochastic process. This fraction increases to 90% for the more accurate Zhang's clock, but is lower (63%) for the PhenoAge clock, suggesting that biological aging is reflected by nonstochastic processes. Confirming this, we demonstrate that Horvath's age acceleration in males and PhenoAge's age acceleration in severe coronavirus disease 2019 cases and smokers are not driven by an increased rate of stochastic change but by nonstochastic processes. These results significantly deepen our understanding and interpretation of epigenetic clocks.

What Is a Plant Cell Type in the Age of Single-Cell Biology? It's Complicated.

One of the fundamental questions in developmental biology is how a cell is specified to differentiate as a specialized cell type. Traditionally, plant cell types were defined based on their function, location, morphology, and lineage. Currently, in the age of single-cell biology, researchers typically attempt to assign plant cells to cell types by clustering them based on their transcriptomes. However, because cells are dynamic entities that progress through the cell cycle and respond to signals, the transcriptome also reflects the state of the cell at a particular moment in time, raising questions about how to define a cell type. We suggest that these complexities and dynamics of cell states are of interest and further consider the roles signaling, stochasticity, cell cycle, and mechanical forces play in plant cell fate specification. Once established, cell identity must also be maintained. With the wealth of single-cell data coming out, the field is poised to elucidate both the complexity and dynamics of cell states.

Aging clocks based on accumulating stochastic variation.

Aging clocks have provided one of the most important recent breakthroughs in the biology of aging, and may provide indicators for the effectiveness of interventions in the aging process and preventive treatments for age-related diseases. The reproducibility of accurate aging clocks has reinvigorated the debate on whether a programmed process underlies aging. Here we show that accumulating stochastic variation in purely simulated data is sufficient to build aging clocks, and that first-generation and second-generation aging clocks are compatible with the accumulation of stochastic variation in DNA methylation or transcriptomic data. We find that accumulating stochastic variation is sufficient to predict chronological and biological age, indicated by significant prediction differences in smoking, calorie restriction, heterochronic parabiosis and partial reprogramming. Although our simulations may not explicitly rule out a programmed aging process, our results suggest that stochastically accumulating changes in any set of data that have a ground state at age zero are sufficient for generating aging clocks.

New Directions in Geroscience: Integrating Social and Behavioral Drivers of Biological Aging.

The "geroscience hypothesis" posits that slowing the physiological processes of aging would lead to delayed disease onset and longer healthspan and lifespan. This shift from a focus on solely treating existing disease to slowing the aging process is a shift toward prevention, including a focus on risk factors found in the social environment. While geroscience traditionally has focused on the molecular and cellular drivers of biological aging, more fundamental causes of aging may be found in the social exposome - the complex array of human social environmental exposures that shape health and disease. The social exposome may interact with physiological processes to accelerate aging biology. In this commentary, we review the potential of these insights to shape the emerging field of translational geroscience. The articles in this special issue highlight how social stress and social determinants of health are associated with biomarkers of aging such as inflammation, epigenetic clocks, and telomeres, and spotlight promising interventions to mitigate stress-related inflammation. For geroscience to incorporate the social exposome into its translational agenda, studies are needed that elucidate and quantify the effects of social exposures on aging and that consider social exposures as intervention targets. The life course perspective allows us to measure both exposures and aging biology over time including sensitive periods of development and major social transitions. In addition, given rapid changes in the measurement of aging biology, which include machine learning techniques, multisystem phenotypes of aging are being developed to better reflect whole body aging, replacing reliance on single system biomarkers. In this expanded and more integrated field of translational geroscience, strategies targeting factors in the social exposome hold promise for achieving aging health equity and extending healthy longevity.

Conditional independence as a statistical assessment of evidence integration processes.

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

Corrigendum: Assessing causal associations between neurodegenerative diseases and neurological tumors with biological aging: a bidirectional Mendelian randomization study

Corrigendum: Assessing causal associations between neurodegenerative diseases and neurological tumors with biological aging: a bidirectional Mendelian randomization study

Evaluation of DNAmAge in paired fresh, frozen, and formalin-fixed paraffin-embedded heart tissues.

The continued development in methylome analysis has enabled a more precise assessment of DNA methylation, but treatment of target tissue prior to analysis may affect DNA analysis. Prediction of age based on methylation levels in the genome (DNAmAge) has gained much interest in disease predisposition (biological age estimation), but also in chronological donor age estimation in crime case samples. Various epigenetic clocks were designed to predict the age. However, it remains unknown how the storage of the tissues affects the DNAmAge estimation. In this study, we investigated the storage method impact of DNAmAge by the comparing the DNAmAge of the two commonly used storage methods, freezing and formalin-fixation and paraffin-embedding (FFPE) to DNAmAge of fresh tissue. This was carried out by comparing paired heart tissue samples of fresh tissue, samples stored by freezing and FFPE to chronological age and whole blood samples from the same individuals. Illumina EPIC beadchip array was used for methylation analysis and the DNAmAge was evaluated with the following epigenetic clocks: Horvath, Hannum, Levine, Horvath skin+blood clock (Horvath2), PedBE, Wu, BLUP, EN, and TL. We observed differences in DNAmAge among the storage conditions. FFPE samples showed a lower DNAmAge compared to that of frozen and fresh samples. Additionally, the DNAmAge of the heart tissue was lower than that of the whole blood and the chronological age. This highlights caution when evaluating DNAmAge for FFPE samples as the results were underestimated compared with fresh and frozen tissue samples. Furthermore, the study also emphasizes the need for a DNAmAge model based on heart tissue samples for an accurate age estimation.

Muscle Steatosis and Fibrosis in Older Adults, From the AJR Special Series on Imaging of Fibrosis.

The purpose of this article is to review steatosis and fibrosis of skeletal muscle, focusing on older adults. Although CT, MRI, and ultrasound are commonly used to image skeletal muscle and provide diagnoses for a variety of medical conditions, quantitative assessment of muscle steatosis and fibrosis is uncommon. This review provides radiologists with a broad perspective on muscle steatosis and fibrosis in older adults by considering the public health impact, biologic mechanisms, and evaluation with CT, MRI, and ultrasound. Promising directions in clinical research that entail artificial intelligence algorithms and the imaging assessment of biologic age are also reviewed. The imaging methods presented hold promise for improving the evaluation of common conditions affecting older adults, including sarcopenia, frailty, and cachexia.

Association between biological aging and the risk of mortality in individuals with non-alcoholic fatty liver disease: A prospective cohort study

BackgroundThe biological process of aging plays an important role in nonalcoholic fatty liver disease (NAFLD) development. However, epidemiological evidence about the association of biological aging with mortality risk among people with NAFLD is limited. MethodsA total of 2199 participants with NAFLD from the National Health and Nutrition Examination Surveys (NHANES) III were included. The outcomes were all-cause and cause-specific (cardiovascular disease [CVD], cancer, and diabetes) mortality. We computed three BA measures, the Klemera-Doubal method (KDM) age, Phenotypic age, and homeostatic dysregulation (HD), by using 18 age-associated clinical biomarkers, and assessed their associations with mortality risk using Cox proportional hazards (CPH) models. ResultsAfter a median follow-up of 16 years, a total of 1077 deaths occurred. People with NAFLD who died during follow-up period exhibited higher baseline biological age (BA) and biological age accelerations (BAAs). The multivariate-adjusted CPH suggested that a one-standard deviation (SD) increase in KDM age acceleration, Phenotypic age acceleration, or HD was associated with a 3 %, 7 %, or 39 % elevated risk of all-cause mortality, respectively. The results of age-varying HRs showed that the associations of KDM age accelerations (AAs) and Phenotypic AAs with all-cause mortality appeared to be stronger in people with NAFLD younger than 45 years. ConclusionsBiological aging was positively associated with both all-cause and cause-specific mortality among people with NAFLD, particularly among younger individuals.

Food insecurity and epigenetic aging in middle-aged and older adults

BackgroundFood insecurity is recognized as a key social determinant of health for older adults. While food insecurity has been associated with morbidity and mortality, few studies have examined how it may contribute to accelerated biological aging. A potential mechanism by which food insecurity may contribute to aging is via epigenetic alterations. We examined the relationship between food insecurity and epigenetic aging, a novel measure of biological aging, in a nationally representative sample of middle-aged and older adults in the United States. MethodsCross-sectional analysis of adults 50 years of age and older from the 2016 Health and Retirement Study (HRS). Financial food insecurity was self-reported via two questions that ascertained having enough money for food or eating less than they felt they should. Epigenetic aging was measured via epigenetic clocks based on DNA methylation patterns that predict aging correlates of morbidity and mortality. Linear regressions were performed to test for differences in the epigenetic clocks, adjusting for biological, socioeconomic, and behavioral factors. ResultsThe analysis consisted of 3875 adults with mean age of 68.5 years. A total of 8.1% reported food insecurity. Food insecurity was associated with several characteristics, including younger age, race/ethnic minority, lower income, total wealth, and educational attainment, higher BMI, and less physical activity. Food insecurity was associated with accelerated epigenetic aging compared to food security, as measured via second (Zhang, PhenoAge, GrimAge) and third (DunedinPoAm) generation epigenetic clocks. In particular, food insecurity remained significantly associated with accelerated Zhang (B = 0.09, SE = 0.03, p = 0.011) and GrimAge (B = 0.57, SE = 0.24, p = 0.022) in the fully adjusted models. ConclusionsFood insecurity is associated with accelerated epigenetic aging among middle-aged and older adults in the United States. Food insecurity may contribute to DNA methylation alterations across the genome and biological age acceleration. These findings add to a growing understanding of the influence of socioeconomic status on the epigenome and health in aging.

Glucose Targets Using Continuous Glucose Monitoring Metrics in Older Adults With Diabetes: Are We There Yet?

The older population is increasing worldwide and up to 30% of older adults have diabetes. Older adults with diabetes are at risk of glucose-related acute and chronic complications. Recently, mostly in type 1 diabetes (T1D), continuous glucose monitoring (CGM) devices have proven beneficial in improving time in range (TIR glucose, 70-180 mg/dL or glucose 3.9-10 mmol/L), glycated hemoglobin (HbA1c), and in lowering hypoglycemia (time below range [TBR] glucose <70 mg/dL or glucose <3.9 mmol/L). The international consensus group formulated CGM glycemic targets relating to older adults with diabetes based on very limited data. Their recommendations, based on expert opinion, were aimed at mitigating hypoglycemia in all older adults. However, older adults with diabetes are a heterogeneous group, ranging from healthy to very complex frail individuals based on chronological, biological, and functional aging. Recent clinical trial and real-world data, mostly from healthy older adults with T1D, demonstrated that older adults often achieve CGM targets, including TIR recommended for non-vulnerable groups, but less often meet the recommended TBR <1%. Existing data also support that hypoglycemia avoidance may be more strongly related to minimization of glucose variability (coefficient of variation [CV]) rather than lower TIR. Very limited data are available for glucose goals in older adults adjusted for the complexity of their health status. Herein, we review the bidirectional associations between glucose and health status in older adults with diabetes; use of diabetes technologies, and their impact on glucose control; discuss current guidelines; and propose a new set of CGM targets for older adults with insulin-treated diabetes that are individualized for health and living status.