Biological Aging In Humans Research Articles

Methylation of Selected CpG-Sites of the Gene CSF1 as a Factor in Regulation of Its Expression and a Marker of Human Biological Aging

—Age-associated transformation of methylation patterns is considered to be an important predictor of human biological age. Changes in the level of CpG-dinucleotide methylation contribute to a shift in the function of a number of genes, including those associated with the functioning of the immune system. One such gene is CSF1. The protein product of this gene is associated with inflammatory aging, making it an important biomarker of age-related diseases. We studied the methylation profile of the promoter-associated CpG island of the CSF1 gene by MALDI-TOF mass spectrometry. Dependences between the character of CpG-site methylation within the investigated regions and the relative level of the gene mRNA and its protein product in people of different age groups were sought. For two CpG sites, a high level of correlation with the studied parameters is shown. A search for the landing sites of transcription factor binding sites associated with gene transcription showed that these CpG dinucleotides are part of motifs for the NFI family transcription factors and the EGR1 factor. We hypothesize that these CpG sites play an important role in the regulation of CSF1 gene expression.

Aging related changes in cardiovascular system in healthy female population: photoplethysmography method and DFA analysis

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Ministry of Science Technological Development and Innovation Background The cardiovascular system undergoes dynamic changes during the biological aging in humans, leading to chronic cardiovascular and cerebrovascular diseases. Purpose Developing the novel method for non-invasive monitoring of age induced changes in arterial vessels. Methodology The pilot study was performed on 58 women, in good health, non-smokers, between the ages of 20 and 70, divided into three age groups. All subjects underwent arterial blood pressure measurement using a photoplethysmography sensor. Recordings were performed in left carotid artery and the left index finger area. Arterial blood flow waveform was then analyzed using DFA analysis, calculating the values of the scalar coefficients α1 and α2. Based on the waveform time interval shift between the standing and supine positions, the pulse wave velocity (PWV) ratio was determined. Results Systolic and diastolic arterial pressure showed a slight linear increase with the age, but without significant difference between the three age categories (p > 0.5). Also, the PWV ratio between the supine and standing positions did not show a statistically significant increase between the age groups. Only scalar coefficients ratio α1/α2 demonstrated a significant difference in value between all age categories. Conclusion In subjects included in this pilot study, only the scalar coefficients ratio varied significantly with the age, indicating the occurrence of structural changes in the cardiovascular system caused by biological aging.

Global Research on Centenarians: A Historical and Comprehensive Bibliometric Analysis from 1887 to 2023.

Centenarians are considered the most successful human biological aging model. However, the characteristics and patterns of research among centenarians have not been described or analyzed. Thus, this study aimed to disclose the historical landscape of global research on centenarians. This bibliometric study investigated historical evidence on centenarian research published in the Scopus database. The bibliometrix package in R was used to perform visual and quantitative analyses of research metrics, trends, and patterns. Of the 2,061 documents included between 1887 and 2023, 84.2% (n=1,736) were published as articles with primary data. We identified international collaboration and annual growth rates of 21.4% and 3.15%, respectively. The United States published the highest number of papers on centenarians (n=786), whereas the publications from Italy had the highest impact (h-index of 90). Based on the frequency of keywords, mortality, genetics, dementia, Alzheimer's disease, and immunosenescence are a few of the most studied topics among centenarians, with emerging research related to mitochondrial DNA and comparison of results between nonagenarians and centenarians. Italy, the United States, and China lead the global research collaboration network, collaborating most frequently with Japan and European countries. Global research on centenarians has grown over the last 20 years, primarily led by Italy, the United States, and China. Latin American and African countries have conducted little or no research on centenarians. The most widely studied topics include mortality, cognition, immunosenescence, and genetics.

LensAge index as a deep learning-based biological age for self-monitoring the risks of age-related diseases and mortality

Age is closely related to human health and disease risks. However, chronologically defined age often disagrees with biological age, primarily due to genetic and environmental variables. Identifying effective indicators for biological age in clinical practice and self-monitoring is important but currently lacking. The human lens accumulates age-related changes that are amenable to rapid and objective assessment. Here, using lens photographs from 20 to 96-year-olds, we develop LensAge to reflect lens aging via deep learning. LensAge is closely correlated with chronological age of relatively healthy individuals (R2 > 0.80, mean absolute errors of 4.25 to 4.82 years). Among the general population, we calculate the LensAge index by contrasting LensAge and chronological age to reflect the aging rate relative to peers. The LensAge index effectively reveals the risks of age-related eye and systemic disease occurrence, as well as all-cause mortality. It outperforms chronological age in reflecting age-related disease risks (p < 0.001). More importantly, our models can conveniently work based on smartphone photographs, suggesting suitability for routine self-examination of aging status. Overall, our study demonstrates that the LensAge index may serve as an ideal quantitative indicator for clinically assessing and self-monitoring biological age in humans.

Environment, Epigenetics, and the Pace of Human Aging

The trajectory of human aging varies widely from one individual to the next due to complex interactions between the genome and the environment that influence the aging process. Such differences in age-specific mortality and disease risk among same-aged individuals reflect variation in the pace of biological aging. Certain mechanisms involved in the progression of biological aging originate in the epigenome, where chemical modifications to the genome are able to alter gene expression without modifying the underlying DNA sequence. The epigenome serves as an interface for environmental signals, which are able to “get under the skin” to influence health and aging. A number of the molecular mechanisms involved in the aging process have been identified, although few aging phenotypes have been definitively traced to their underlying molecular causes thus far. In this review, we discuss variation in human biological aging and the epigenome's role in promoting heterogeneity in human longevity and healthspan.

The lipidomic correlates of epigenetic aging across the adult lifespan: A population-based study.

Lipid signaling is involved in longevity regulation, but which specific lipid molecular species affect human biological aging remains largely unknown. We investigated the relation between complex lipids and DNA methylation-based metrics of biological aging among 4181 participants (mean age 55.1 years (range 30.0-95.0)) from the Rhineland Study, an ongoing population-based cohort study in Bonn, Germany. The absolute concentration of 14 lipid classes, covering 964 molecular species and 267 fatty acid composites, was measured by Metabolon Complex Lipid Panel. DNA methylation-based metrics of biological aging (AgeAccelPheno and AgeAccelGrim) were calculated based on published algorithms. Epigenome-wide association analyses (EWAS) of biological aging-associated lipids and pathway analysis were performed to gain biological insights into the mechanisms underlying the effects of lipidomics on biological aging. We found that higher levels of molecular species belonging to neutral lipids, phosphatidylethanolamines, phosphatidylinositols, and dihydroceramides were associated with faster biological aging, whereas higher levels of lysophosphatidylcholine, hexosylceramide, and lactosylceramide species were associated with slower biological aging. Ceramide, phosphatidylcholine, and lysophosphatidylethanolamine species with odd-numbered fatty acid tail lengths were associated with slower biological aging, whereas those with even-numbered chain lengths were associated with faster biological aging. EWAS combined with functional pathway analysis revealed several complex lipids associated with biological aging as important regulators of known longevity and aging-related pathways.

Genetic impact of aging on periodontal disease: A scoping review

One of the factors that related to biological aging in humans is genetic. The aging process can occur due to genetic accumulation and epigenetic modification that lead to progressive cellular damage and weakened tissue functions that causing limitation of abilities to maintain the homeostasis. Increased vulnerability to a number of inflammations due to the aging process is closely related to rising in prevalence and severity of periodontitis. The purpose of this paper is to analyze immunity of the aging process and its relation to periodontal disease in genetic aspect. Biological aging is affected by genetic variation that changes several genes that causing changes of several cell functions. Changes in DNA methylation are one of the mechanisms that contribute to the aging process, including the body immune system. Aging process influences both adaptive and innate body immune system. Changes in an immune and genetic system in the aging process could increase the severity of periodontal disease. As a conclusion, periodontal disease is an inflammation that related to aging. In the aging process, there are changes in the immune system that causes elder people more susceptible to periodontal infection. In addition, genetic and epigenetic factors also play a role in periodontal changes in elderly.

HUMAN AGING INTERVENTIONS

Abstract Biological aging is the greatest risk factor for multiple non-communicable diseases affecting multiple organ systems. Evidence from animal studies suggest that the rate of biological aging is modifiable and that slowing the rate of biological aging may decrease the incidence of age-related morbidity and mortality. Based on these findings, several approaches are currently being studied to slow the rate of biological aging in humans. This symposium features internationally renowned aging research scientists whose work focuses on clinical interventions to modify biological aging in humans. We will hear from Rajagopal Sekhar from the Baylor College of Medicine who will present his research on “Improving oxidative stress, mitochondrial dysfunction, inflammaging, aging hallmarks and muscle strength in older adults: the novel role of GlyNAC and the 'Power of 3'”; Jamie Justice from the Wake Forest School of Medicine will present her work on “Response to dietary restriction interventions in older adults: biomarkers of cellular senescence and biological aging”; Reem Waziry from the Columbia University Mailman School of Public Health will present her work “Does Caloric Restriction Slow the Process of Biological Aging in Non-Obese Healthy Adults? Evidence from the CALERIE™ Trial”; and Daniel Parker from the Duke University School of Medicine will present his work “Does APOE genotype moderate the impact of diet modification and exercise training on age-related outcomes?”. Attendees will learn about recent advances in interventions targeting human aging.

DOES CALORIC RESTRICTION SLOW THE PROCESS OF BIOLOGICAL AGING? EVIDENCE FROM THE CALERIE TRIAL

Abstract Calorie restriction (CR) slows aging and increases healthy lifespan in model organisms. We tested if CR slowed biological aging in humans using DNA methylation analysis of blood samples from N=197 participants in the Comprehensive Assessment of Long-term Effects ofReducing Intake of Energy (CALERIE™) randomized controlled trial. We quantified CR effects on biological aging by comparing change scores for six epigenetic-clock and Pace-of-Aging measures between n=128 CR-group and n=69 ad-libitum-control-group participants at 12- and24-month follow-ups. CR effects were strongest for DunedinPACE Pace of Aging (12-month Cohen’s d=0.3; 24-month Cohen’s d=0.2, p&amp;lt;0.01 for both), followed by DunedinPoAm and the GrimAge epigenetic clock, although effects for these measures were not statistically differentfrom zero (p&amp;gt;0.08). CR effects for other epigenetic clocks were in the opposite direction (all p&amp;gt;0.15). CALERIE intervention slowed Pace of Aging but showed minimal effect on epigenetic clocks hypothesized to reflect longer term accumulation of aging burden.

The tumor suppression theory of aging

Despite continued increases in human life expectancy, the factors determining the rate of human biological aging remain unknown. Without understanding the molecular mechanisms underlying aging, efforts to prevent aging are unlikely to succeed. The tumor suppression theory of aging introduced here proposes somatic mutation as the proximal cause of aging, but postulates that oncogenic transformation and clonal expansion, not functional impairment, are the relevant consequences of somatic mutation. Obesity and caloric restriction accelerate and decelerate aging due to their effect on cell proliferation, during which most mutations arise. Most phenotypes of aging are merely tumor-suppressive mechanisms that evolved to limit malignant growth, the dominant age-related cause of death in early and middle life. Cancer limits life span for most long-lived mammals, a phenomenon known as Peto’s paradox. Its conservation across species demonstrates that mutation is a fundamental but hard limit on mammalian longevity. Cell senescence and apoptosis and differentiation induced by oncogenes, telomere shortening or DNA damage evolved as a second line of defense to limit the tumorigenic potential of clonally expanding cells, but accumulating senescent cells, senescence-associated secretory phenotypes and stem cell exhaustion eventually cause tissue dysfunction and the majority, if not most, phenotypes of aging.

Probing the Relationship Between Declining Renal Glomerular Filtration Over the Life Span and General Biological Aging: Does the Former Provide Means to Estimate the Latter?

Background: While a consistent, gradual decline in the renal glomerular filtration rate (GFR) is a characteristic occurrence over the human life span, the exact pathophysiology behind this event remains unresolved. Evidence to date suggests that the endogenous glucose-insulin system could be involved at some level. Diabetic-induced nephropathy, one of the most prevalent chronic renal diseases, is closely linked to a severe form of insulin resistance (IR). Nevertheless, it is less certain that the ubiquitous milder forms of IR in nondiabetics ascribed customarily to routine, poor choices in diet and exercise management can over time diminish GFR and adversely influence other renal functions to any perceptible extent. Methodology: Baseline data for cross-sectional analyses were obtained from a cohort of healthy, nondiabetic volunteers (fasting blood glucose [FBG] ≤ 125 mg/dL) involved in prior clinical studies. Slope-based rather than threshold analyses were mainly employed. These measurements were applied for the most part to correlate age, FBG levels used as an estimate of IR activity, and systolic blood pressure (SBP) to a variety of metabolic parameters during aging with a primary focus on GFR. Results: Considering cause and effect, FBG and SBP correlate positively with the diminishing GFR over a major part of the life span. The decline in GFR begins somewhere around the mid-20s and coincides with key temporal increases in FBG and SBP levels. Conclusions: A close time-based setting suggests that IR plays a prominent role in the declining GFR that occurs over the life span. This is perhaps due in part through deleterious effects of rising levels of insulin, glucose, and SBP individually or combined that are also popular proposed causative factors for human aging in general. On the philosophical side, the latter fact suggests that the declining GFR might provide a practical way to estimate the rate of overall human biological aging.

Neuroprotective effects of exercise on the aging human neuromuscular system.

Human biological aging from maturity to senescence is associated with a gradual loss of muscle mass and neuromuscular function. It is not until very old age (>80years) however, that these changes often manifest into functional impairments. A driving factor underlying the age-related loss of muscle mass and function is the reduction in the number and quality of motor units (MUs). A MU consists of a single motoneuron, located either in the spinal cord or the brain stem, and all of the muscle fibres it innervates via its peripheral axon. Throughout the adult lifespan, MUs are slowly, but progressively lost. The compensatory process of collateral reinnervation attempts to recapture orphaned muscle fibres following the death of a motoneuron. Whereas this process helps mitigate loss of muscle mass during the latter decades of adult aging, the neuromuscular system has fewer and larger MUs, which have lower quality connections between the axon terminal and innervated muscle fibres. Whether this process of MU death and degradation can be attenuated with habitual physical activity has been a challenging question of great interest. This review focuses on age-related alterations of the human neuromuscular system, with an emphasis on the MU, and presents findings on the potential protective effects of lifelong physical activity. Although there is some discrepancy across studies of masters athletes, if one considers all experimental limitations as well as the available literature in animals, there is compelling evidence of a protective effect of chronic physical training on human MUs. Our tenet is that high-levels of physical activity can mitigate the natural trajectory of loss of quantity and quality of MUs in old age.

The Importance of Age in the Prediction of Mortality by a Frailty Index: A Machine Learning Approach in the Irish Longitudinal Study on Ageing.

The quantification of biological age in humans is an important scientific endeavor in the face of ageing populations. The frailty index (FI) methodology is based on the accumulation of health deficits and captures variations in health status within individuals of the same age. The aims of this study were to assess whether the addition of age to an FI improves its mortality prediction and whether the associations of the individual FI items differ in strength. We utilized data from The Irish Longitudinal Study on Ageing to conduct, by sex, machine learning analyses of the ability of a 32-item FI to predict 8-year mortality in 8174 wave 1 participants aged 50 or more years. By wave 5, 559 men and 492 women had died. In the absence of age, the FI was an acceptable predictor of mortality with AUCs of 0.7. When age was included, AUCs improved to 0.8 in men and 0.9 in women. After age, deficits related to physical function and self-rated health tended to have higher importance scores. Not all FI variables seemed equally relevant to predict mortality, and age was by far the most relevant feature. Chronological age should remain an important consideration when interpreting the prognostic significance of an FI.

Exercise reduces circulating biomarkers of cellular senescence in humans.

Cellular senescence has emerged as a significant and potentially tractable mechanism of aging and multiple aging‐related conditions. Biomarkers of senescent cell burden, including molecular signals in circulating immune cells and the abundance of circulating senescence‐related proteins, have been associated with chronological age and clinical parameters of biological age in humans. The extent to which senescence biomarkers are affected by interventions that enhance health and function has not yet been examined. Here, we report that a 12‐week structured exercise program drives significant improvements in several performance‐based and self‐reported measures of physical function in older adults. Impressively, the expression of key markers of the senescence program, including p16, p21, cGAS, and TNFα, were significantly lowered in CD3+ T cells in response to the intervention, as were the circulating concentrations of multiple senescence‐related proteins. Moreover, partial least squares discriminant analysis showed levels of senescence‐related proteins at baseline were predictive of changes in physical function in response to the exercise intervention. Our study provides first‐in‐human evidence that biomarkers of senescent cell burden are significantly lowered by a structured exercise program and predictive of the adaptive response to exercise.

Chronological and biological aging of the human left ventricular myocardium: Analysis of microRNAs contribution.

Aging is the main risk factor for cardiovascular diseases. In humans, cardiac aging remains poorly characterized. Most studies are based on chronological age (CA) and disregard biological age (BA), the actual physiological age (result of the aging rate on the organ structure and function), thus yielding potentially imperfect outcomes. Deciphering the molecular basis of ventricular aging, especially by BA, could lead to major progresses in cardiac research. We aim to describe the transcriptome dynamics of the aging left ventricle (LV) in humans according to both CA and BA and characterize the contribution of microRNAs, key transcriptional regulators. BA is measured using two CA‐associated transcriptional markers: CDKN2A expression, a cell senescence marker, and apparent age (AppAge), a highly complex transcriptional index. Bioinformatics analysis of 132 LV samples shows that CDKN2A expression and AppAge represent transcriptomic changes better than CA. Both BA markers are biologically validated in relation to an aging phenotype associated with heart dysfunction, the amount of cardiac fibrosis. BA‐based analyses uncover depleted cardiac‐specific processes, among other relevant functions, that are undetected by CA. Twenty BA‐related microRNAs are identified, and two of them highly heart‐enriched that are present in plasma. We describe a microRNA‐gene regulatory network related to cardiac processes that are partially validated in vitro and in LV samples from living donors. We prove the higher sensitivity of BA over CA to explain transcriptomic changes in the aging myocardium and report novel molecular insights into human LV biological aging. Our results can find application in future therapeutic and biomarker research.

Quantification of the pace of biological aging in humans through a blood test, the DunedinPoAm DNA methylation algorithm.

Biological aging is the gradual, progressive decline in system integrity that occurs with advancing chronological age, causing morbidity and disability. Measurements of the pace of aging are needed as surrogate endpoints in trials of therapies designed to prevent disease by slowing biological aging. We report a blood-DNA-methylation measure that is sensitive to variation in pace of biological aging among individuals born the same year. We first modeled change-over-time in 18 biomarkers tracking organ-system integrity across 12 years of follow-up in n = 954 members of the Dunedin Study born in 1972-1973. Rates of change in each biomarker over ages 26-38 years were composited to form a measure of aging-related decline, termed Pace-of-Aging. Elastic-net regression was used to develop a DNA-methylation predictor of Pace-of-Aging, called DunedinPoAm for Dunedin(P)ace(o)f(A)ging(m)ethylation. Validation analysis in cohort studies and the CALERIE trial provide proof-of-principle for DunedinPoAm as a single-time-point measure of a person's pace of biological aging.

Deep learning for biological age estimation.

Modern machine learning techniques (such as deep learning) offer immense opportunities in the field of human biological aging research. Aging is a complex process, experienced by all living organisms. While traditional machine learning and data mining approaches are still popular in aging research, they typically need feature engineering or feature extraction for robust performance. Explicit feature engineering represents a major challenge, as it requires significant domain knowledge. The latest advances in deep learning provide a paradigm shift in eliciting meaningful knowledge from complex data without performing explicit feature engineering. In this article, we review the recent literature on applying deep learning in biological age estimation. We consider the current data modalities that have been used to study aging and the deep learning architectures that have been applied. We identify four broad classes of measures to quantify the performance of algorithms for biological age estimation and based on these evaluate the current approaches. The paper concludes with a brief discussion on possible future directions in biological aging research using deep learning. This study has significant potentials for improving our understanding of the health status of individuals, for instance, based on their physical activities, blood samples and body shapes. Thus, the results of the study could have implications in different health care settings, from palliative care to public health.

Aging Fits the Disease Criteria of the International Classification of Diseases

The disease criteria used by the World Health Organization (WHO) were applied to human biological aging in order to assess whether aging can be classified as a disease. These criteria were developed for the 11th revision of the International Classification of Diseases (ICD) and included disease diagnostics, mechanisms, course and outcomes, known interventions, and linkage to genetic and environmental factors. ResultsBiological aging can be diagnosed with frailty indices, functional, blood-based biomarkers. A number of major causal mechanisms of human aging involved in various organs have been described, such as inflammation, replicative cellular senescence, immune senescence, proteostasis failures, mitochondrial dysfunctions, fibrotic propensity, hormonal aging, body composition changes, etc. We identified a number of clinically proven interventions, as well as genetic and environmental factors of aging. Therefore, aging fits the ICD-11 criteria and can be considered a disease. Our proposal was submitted to the ICD-11 Joint Task force, and this led to the inclusion of the extension code for “Ageing-related” (XT9T) into the “Causality” section of the ICD-11. This might lead to greater focus on biological aging in global health policy and might provide for more opportunities for the new therapy developers.

Measuring biological aging in humans: A quest.

The global population of individuals over the age of 65 is growing at an unprecedented rate and is expected to reach 1.6 billion by 2050. Most older individuals are affected by multiple chronic diseases, leading to complex drug treatments and increased risk of physical and cognitive disability. Improving or preserving the health and quality of life of these individuals is challenging due to a lack of well‐established clinical guidelines. Physicians are often forced to engage in cycles of “trial and error” that are centered on palliative treatment of symptoms rather than the root cause, often resulting in dubious outcomes. Recently, geroscience challenged this view, proposing that the underlying biological mechanisms of aging are central to the global increase in susceptibility to disease and disability that occurs with aging. In fact, strong correlations have recently been revealed between health dimensions and phenotypes that are typical of aging, especially with autophagy, mitochondrial function, cellular senescence, and DNA methylation. Current research focuses on measuring the pace of aging to identify individuals who are “aging faster” to test and develop interventions that could prevent or delay the progression of multimorbidity and disability with aging. Understanding how the underlying biological mechanisms of aging connect to and impact longitudinal changes in health trajectories offers a unique opportunity to identify resilience mechanisms, their dynamic changes, and their impact on stress responses. Harnessing how to evoke and control resilience mechanisms in individuals with successful aging could lead to writing a new chapter in human medicine.

The plasma metabolome as a predictor of biological aging in humans

Chronological age is an important predictor of morbidity and mortality; however, it is unable to account for heterogeneity in the decline of physiological function and health with advancing age. Several attempts have been made to instead define a "biological age" using multiple physiological parameters in order to account for variation in the trajectory of human aging; however, these methods require technical expertise and are likely too time-intensive and costly to be implemented into clinical practice. Accordingly, we sought to develop a metabolomic signature of biological aging that could predict changes in physiological function with the convenience of a blood sample. A weighted model of biological age was generated based on multiple clinical and physiological measures in a cohort of healthy adults and was then applied to a group of healthy older adults who were tracked longitudinally over a 5-10-year timeframe. Plasma metabolomic signatures were identified that were associated with biological age, including some that could predict whether individuals would age at a faster or slower rate. Metabolites most associated with the rate of biological aging included amino acid, fatty acid, acylcarnitine, sphingolipid, and nucleotide metabolites. These results not only have clinical implications by providing a simple blood-based assay of biological aging, but also provide insight into the molecular mechanisms underlying human healthspan.