Human Aging Research Articles

Mathematical Modelling Approach for Administration of Palatable Diet to Quantify Blood Glucose Level – A Reference to Systolic Blood Pressure

The study concerns the Mathematical analysis of some variations that arise in systolic blood pressure (SBP) for different human age groups due to endocrine disorders (diabetes). An attempt has been made to improve the blood glucose levels (both pre-prandial and post prandial) associated with SBP by the suitable administration of palatable diet. Red portions (Protein and Fat) and Black Portions (Carbohydrates containing sugar and starch) have been considered with the assumption of “weight” of an individual as constant. A Mathematical model has been developed by using coupled nonlinear ordinary differential equations to study the behaviour of blood glucose levels. These equations involve the terms as, the change in glucose and the change in insulin with respect to time, the food intake sensitivity constants and the step function which can provide the quantification of normal blood glucose levels. The effectiveness in the variation of systolic blood pressure is analysed for various age groups. The response of men and women aged 25 years and above and the case of juvenile is studied using multiple linear regression model. The assumption that the weight of an individual as constant is confirmed by ANOVA for the determination of blood-Glucose levels. The palatable diet composed of Protein (P), Fat (F) and Carbohydrate (C) as PFC model is simulated with Joselin’s Principle.

Systemic low-dose anti-fibrotic treatment attenuates ovarian aging in the mouse.

The female reproductive system is one of the first to age in humans, resulting in infertility and endocrine disruptions. The aging ovary assumes a fibro-inflammatory milieu which negatively impacts gamete quantity and quality as well as ovulation. Here, we tested whether the systemic delivery of anti-inflammatory (Etanercept) or anti-fibrotic (Pirfenidone) drugs attenuates ovarian aging in mice. We first evaluated the ability of these drugs to decrease the expression of fibro-inflammatory genes in primary ovarian stromal cellstreated with a pro-fibrotic or a pro-inflammatory stimulus. Whereas Etanercept did not block Tnf expression in ovarian stromal cells, Pirfenidone significantly reduced Col1a1 expression. We then tested Pirfenidone in vivo where the drug was delivered systemically via mini-osmotic pumps for 6weeks. Pirfenidone mitigated the age-dependent increase in ovarian fibrosis without impacting overall health parameters. Ovarian function was improved in Pirfenidone-treated mice as evidenced by increased follicle and corpora lutea number, AMH levels, and improved estrous cyclicity. Transcriptomic analysis revealed that Pirfenidone treatment resulted in an upregulation of reproductive function-related genes at 8.5months and a downregulation of inflammatory genes at 12months of age. These findings demonstrate that reducing the fibroinflammatory ovarian microenvironment improves ovarian function, thereby supporting modulating the ovarian environment as a therapeutic avenue to extend reproductive longevity.

The biodemography of human aging (Gompertz-Makeham law) applied to surgical mortality modelling: a retrospective national cohort study.

The Gompertz-Makeham law describes a characteristic pattern of mortality in human populations where death rate is near constant between age 18 and 30 years (Makeham's Law) and rises exponentially thereafter (Gompertz Law). This pattern has not been described in surgical populations, but if true, would have important implications for understanding surgical risk and design and interpretation of surgical risk models. The aim of this study was to determine if the Gompertz-Makeham law applies to perioperative mortality risk and the conditions under which it may apply. We examined the relationship between age and 1-month postoperative all-cause mortality risk in a 10-year New Zealand administrative dataset comprising of 5,615,100 surgical procedures from 2007 to 2016. The dataset includes patient and surgical factors including procedures, American Society of Anesthesiologist's physical status score (ASA-PS), diagnoses and other relevant details. Semi-logarithmic graphs of mortality risk and age were plotted. Linear regression models were fitted, with regression line slope and Pearson's correlation coefficient calculated. The primary outcome occurred in 114,782 (2.0%) of 5,615,100 included participants. The Gompertz-Makeham law seems to apply to the national surgical population as a whole (slope = 0.0241, R2 = 0.971). The law applies in all subgroups studied including sex, ASA-PS, surgical acuity, surgical severity category, cancer status and ethnicity (slopes 0.0066 to 0.0307, R2 0.771 to 0.990). Important interactions were found between age, mortality risk and three high risk groups (cancer diagnosis, ASA-PS 4-5 and high surgical severity). The Gompertz-Makeham law seems to apply in a national cohort of surgical patients. The inflection point for increased 1-month risk is apparent at age 30 years. A strict exponential rise in mortality risk occurs thereafter. This finding improves our understanding of surgical risk and suggests a concept-driven approach to improve modelling of age and important interactions in future surgical risk models.

Longitudinal Multi-omic Immune Profiling Reveals Age-Related Immune Cell Dynamics in Healthy Adults.

The generation and maintenance of protective immunity is a dynamic interplay between host and environment that is impacted by age. Understanding fundamental changes in the healthy immune system that occur over a lifespan is critical in developing interventions for age-related susceptibility to infections and diseases. Here, we use multi-omic profiling (scRNA-seq, proteomics, flow cytometry) to examined human peripheral immunity in over 300 healthy adults, with 96 young and older adults followed over two years with yearly vaccination. The resulting resource includes scRNA-seq datasets of >16 million PBMCs, interrogating 71 immune cell subsets from our new Immune Health Atlas. This study allows unique insights into the composition and transcriptional state of immune cells at homeostasis, with vaccine perturbation, and across age. We find that T cells specifically accumulate age-related transcriptional changes more than other immune cells, independent from inflammation and chronic perturbation. Moreover, impaired memory B cell responses to vaccination are linked to a Th2-like state shift in older adults' memory CD4 T cells, revealing possible mechanisms of immune dysregulation during healthy human aging. This extensive resource is provided with a suite of exploration tools at https://apps.allenimmunology.org/aifi/insights/dynamics-imm-health-age/ to enhance data accessibility and further the understanding of immune health across age.

IRescue: uncertainty-aware quantification of transposable elements expression at single cell level.

Transposable elements (TEs) are mobile DNA repeats known to shape the evolution of eukaryotic genomes. In complex organisms, they exhibit tissue-specific transcription. However, understanding their role in cellular diversity across most tissues remains a challenge, when employing single-cell RNA sequencing (scRNA-seq), due to their widespread presence and genetic similarity. To address this, we present IRescue (Interspersed Repeats single-cell quantifier), a software capable of estimating the expression of TE subfamilies at the single-cell level. IRescue incorporates a unique UMI deduplication algorithm to rectify sequencing errors and employs an Expectation-Maximization procedure to effectively redistribute the counts of multi-mapping reads. Our study showcases the precision of IRescue through analysis of both simulated and real single cell and nuclei RNA-seq data from human colorectal cancer, brain, skin aging, and PBMCs during SARS-CoV-2 infection and recovery. By linking the expression patterns of TE signatures to specific conditions and biological contexts, we unveil insights into their potential roles in cellular heterogeneity and disease progression.

Regional patterns of human cortex development correlate with underlying neurobiology

Human brain morphology undergoes complex changes over the lifespan. Despite recent progress in tracking brain development via normative models, current knowledge of underlying biological mechanisms is highly limited. We demonstrate that human cortical thickness development and aging trajectories unfold along patterns of molecular and cellular brain organization, traceable from population-level to individual developmental trajectories. During childhood and adolescence, cortex-wide spatial distributions of dopaminergic receptors, inhibitory neurons, glial cell populations, and brain-metabolic features explain up to 50% of the variance associated with a lifespan model of regional cortical thickness trajectories. In contrast, modeled cortical thickness change patterns during adulthood are best explained by cholinergic and glutamatergic neurotransmitter receptor and transporter distributions. These relationships are supported by developmental gene expression trajectories and translate to individual longitudinal data from over 8000 adolescents, explaining up to 59% of developmental change at cohort- and 18% at single-subject level. Integrating neurobiological brain atlases with normative modeling and population neuroimaging provides a biologically meaningful path to understand brain development and aging in living humans.

Culture dependent and independent approaches reveal the role of specific bacteria in human skin aging

AbstractSkin aging is a dynamic process involving a spectrum of phenotypic changes, making it an attractive model for studying microbiome‐phenotype interactions. Therefore, 822 facial microbial samples and 14 skin phenotypes from corresponding areas were assessed in a Chinese cohort. Porphyrins and the chronological age exhibited the most significant microbial variability. We further profiled the dynamics of the skin microbiome associated with age and aging phenotypes. Using a multiple linear regression model, we predicted premature/delayed aging‐related microbial species, mainly Moraxella osloensis and Cutibacterium acnes. We also validated the biological functions of the host‐microbe interactions in vitro. Moraxella osloensis isolated from healthy skin regulates collagen metabolism and extracellular matrix assembly, and promotes cell senescence in human keratinocytes and fibroblasts, making it potentially applicable in the development of antiaging interventions.

Variant load of mitochondrial DNA in single human mesenchymal stem cells

Heteroplasmic mitochondrial DNA (mtDNA) variants accumulate as humans age, particularly in the stem-cell compartments, and are an important contributor to age-related disease. Mitochondrial dysfunction has been observed in osteoporosis and somatic mtDNA pathogenic variants have been observed in animal models of osteoporosis. However, this has never been assessed in the relevant human tissue. Mesenchymal stem cells (MSCs) are the progenitors to many cells of the musculoskeletal system and are critical to skeletal tissues and bone vitality. Investigating mtDNA in MSCs could provide novel insights into the role of mitochondrial dysfunction in osteoporosis. To determine if this is possible, we investigated the landscape of somatic mtDNA variation in MSCs through a combination of fluorescence-activated cell sorting and single-cell next-generation sequencing. Our data show that somatic heteroplasmic variants are present in individual patient-derived MSCs, can reach high heteroplasmic fractions and have the potential to be pathogenic. The identification of somatic heteroplasmic variants in MSCs of patients highlights the potential for mitochondrial dysfunction to contribute to the pathogenesis of osteoporosis.

Comparing cranial suture interdigitation in humans and non-human primates: unearthing links to osteopathic cranial concept.

Since William Garner Sutherland's inception of osteopathic cranial manipulative medicine (OCMM), osteopathic physicians have practiced with the knowledge that cranial sutures exhibit motion. We hypothesize that the complexity of suture interdigitation in humans may provide clues to elucidate the concept of OCMM. We compared the interdigitation of sagittal, coronal (left and right), and lambdoid (left and right) sutures in computed tomography (CT) scans of humans and five nonhuman primate species (Gorilla gorilla, Pongo pygmaeus, Pan troglodytes, Hylobates lar, and Nasalis larvatus). Human ages are evenly distributed between 10 and 65 years of age, with an equal number of males (n=16) and females (n=16) in the sample. Nonhuman primates are all females, and the sample includes juveniles (n=6) and adults (n=34). Sutures were evaluated on a scale ranging from 0 to 3 (0: fused sutures; 1: no interdigitation; 2: low complexity; and 3: representing the highest degree of interdigitation and complexity). Based on ordinary least squares linear regression, we found no significant relationship between suture interdigitation and age in humans. Chi-square tests were utilized to assess sex differences within humans, species-level differences, and differences between humans and nonhuman primates across all five sutures. Humans exhibited a statistically significant greater degree of suture complexity than all five nonhuman species across all five sutures. These findings indicate that human suture interdigitation is more complex than their closest living relatives (African apes) and other primates (Asian monkeys and apes). We theorize that this would enable subtle movement and serve to transmit forces at the cranial sutures from dietary or ethological behaviors, similar to the pattern observed in other mammals. While humans have a softer diet compared to other living primates, the uniqueness of human craniofacial growth and extended developmental period could contribute to the necessity for complex cranial sutures. More studies are needed to understand variation in human and nonhuman sutural complexity and its relationship to cranial motion.

Artificial intelligence for the study of human ageing: a systematic literature review

As society experiences accelerated ageing, understanding the complex biological processes of human ageing, which are affected by a large number of variables and factors, becomes increasingly crucial. Artificial intelligence (AI) presents a promising avenue for ageing research, offering the ability to detect patterns, make accurate predictions, and extract valuable insights from large volumes of complex, heterogeneous data. As ageing research increasingly leverages AI techniques, we present a timely systematic literature review to explore the current state-of-the-art in this field following a rigorous and transparent review methodology. As a result, a total of 77 articles have been identified, summarised, and categorised based on their characteristics. AI techniques, such as machine learning and deep learning, have been extensively used to analyse diverse datasets, comprising imaging, genetic, behavioural, and contextual data. Findings showcase the potential of AI in predicting age-related outcomes, developing ageing biomarkers, and determining factors associated with healthy ageing. However, challenges related to data quality, interpretability of AI models, and privacy and ethical considerations have also been identified. Despite the advancements, novel approaches suggest that there is still room for improvement to provide personalised AI-driven healthcare services and promote active ageing initiatives with the ultimate goal of enhancing the quality of life and well-being of older adults.Graphical abstractOverview of the literature review.

Loss of coordination between basic cellular processes in human aging.

Age-related loss of gene expression coordination has been reported for distinct cell types and may lead to impaired cellular function. Here we propose a method for quantifying age-related changes in transcriptional regulatory relationships between genes, based on a model learned from external data. We used this method to uncover age-related trends in gene-gene relationships across eight human tissues, which demonstrates that reduced co-expression may also result from coordinated transcriptional responses. Our analyses reveal similar numbers of strengthening and weakening gene-gene relationships with age, impacting both tissue-specific (for example, coagulation in blood) and ubiquitous biological functions. Regulatory relationships becoming weaker with age were established mostly between genes operating in distinct cellular processes. As opposed to that, regulatory relationships becoming stronger with age were established both within and between different cellular functions. Our work reveals that, although most transcriptional regulatory gene-gene relationships are maintained during aging, those with declining regulatory coupling result mostly from a loss of coordination between distinct cellular processes.

Age-related differences in human cortical microstructure depend on the distance to the nearest vein

Abstract Age-related differences in cortical microstructure are used to understand the neuronal mechanisms that underlie human brain ageing. The cerebral vasculature contributes to cortical ageing, but its precise interaction with cortical microstructure is poorly understood. In a cross-sectional study, we combine venous imaging with vessel distance mapping to investigate the interaction between venous distances and age-related differences in the microstructural architecture of the primary somatosensory cortex, the primary motor cortex and additional areas in the frontal cortex as non-sensorimotor control regions. We scanned 18 younger adults and 17 older adults using 7 Tesla MRI to measure age-related changes in longitudinal relaxation time (T1) and quantitative susceptibility mapping (QSM) values at 0.5 mm isotropic resolution. We modelled different cortical depths using an equi-volume approach and assessed the distance of each voxel to its nearest vein using vessel distance mapping. Our data reveal a dependence of cortical quantitative T1 values and positive QSM values on venous distance. In addition, there is an interaction between venous distance and age on quantitative T1 values, driven by lower quantitative T1 values in older compared to younger adults in voxels that are closer to a vein. Together, our data show that the local venous architecture explains a significant amount of variance in standard measures of cortical microstructure and should be considered in neurobiological models of human brain organisation and cortical ageing.

Metformin decelerates aging clock in male monkeys

In a rigorous 40-month study, we evaluated the geroprotective effects of metformin on adult male cynomolgus monkeys, addressing a gap in primate aging research. The study encompassed a comprehensive suite of physiological, imaging, histological, and molecular evaluations, substantiating metformin's influence on delaying age-related phenotypes at the organismal level. Specifically, we leveraged pan-tissue transcriptomics, DNA methylomics, plasma proteomics, and metabolomics to develop innovative monkey aging clocks and applied these to gauge metformin's effects on aging. The results highlighted a significant slowing of aging indicators, notably a roughly 6-year regression in brain aging. Metformin exerts a substantial neuroprotective effect, preserving brain structure and enhancing cognitive ability. The geroprotective effects on primate neurons were partially mediated by the activation of Nrf2, a transcription factor with anti-oxidative capabilities. Our research pioneers the systemic reduction of multi-dimensional biological age in primates through metformin, paving the way for advancing pharmaceutical strategies against human aging.

Multimodal Transformers and Their Applications in Drug Target Discovery for Aging and Age-Related Diseases.

Given the unprecedented rate of global aging, advancing aging research and drug discovery to support healthy and productive longevity is a pressing socioeconomic need. Holistic models of human and population aging that account for biomedical background, environmental context, and lifestyle choices are fundamental to address these needs, but integration of diverse data sources and large data sets into comprehensive models is challenging using traditional approaches. Recent advances in artificial intelligence and machine learning, and specifically multimodal transformer-based neural networks, have enabled the development of highly capable systems that can generalize across multiple data types. As such, multimodal transformers can generate systemic models of aging that can predict health status and disease risks, identify drivers, or breaks of physiological aging, and aid in target discovery against age-related disease. The unprecedented capacity of transformers to extract and integrate information from large and diverse data modalities, combined with the ever-increasing availability of biological and medical data, has the potential to revolutionize healthcare, promoting healthy longevity and mitigating the societal and economic impacts of global aging.

Curcumin Inhibits TORC1 and Prolongs the Lifespan of Cells with Mitochondrial Dysfunction.

Aging is an inevitable biological process that contributes to the onset of age-related diseases, often as a result of mitochondrial dysfunction. Understanding the mechanisms behind aging is crucial for developing therapeutic interventions. This study investigates the effects of curcumin on postmitotic cellular lifespan (PoMiCL) during chronological aging in yeast, a widely used model for human postmitotic cellular aging. Our findings reveal that curcumin significantly prolongs the PoMiCL of wildtype yeast cells, with the most pronounced effects observed at lower concentrations, indicating a hormetic response. Importantly, curcumin also extends the lifespan of postmitotic cells with mitochondrial deficiencies, although the hormetic effect is absent in these defective cells. Mechanistically, curcumin inhibits TORC1 activity, enhances ATP levels, and induces oxidative stress. These results suggest that curcumin has the potential to modulate aging and offer therapeutic insights into age-related diseases, highlighting the importance of context in its effects.

A systematic review of phenotypic and epigenetic clocks used for aging and mortality quantification in humans.

Aging is the leading driver of disease in humans and has profound impacts on mortality. Biological clocks are used to measure the aging process in the hopes of identifying possible interventions. Biological clocks may be categorized as phenotypic or epigenetic, where phenotypic clocks use easily measurable clinical biomarkers and epigenetic clocks use cellular methylation data. In recent years, methylation clocks have attained phenomenal performance when predicting chronological age and have been linked to various age-related diseases. Additionally, phenotypic clocks have been proven to be able to predict mortality better than chronological age, providing intracellular insights into the aging process. This review aimed to systematically survey all proposed epigenetic and phenotypic clocks to date, excluding mitotic clocks (i.e., cancer risk clocks) and those that were modeled using non-human samples. We reported the predictive performance of 33 clocks and outlined the statistical or machine learning techniques used. We also reported the most influential clinical measurements used in the included phenotypic clocks. Our findings provide a systematic reporting of the last decade of biological clock research and indicate possible avenues for future research.

The uniqueness of human vulnerability to brain aging in great ape evolution.

Aging is associated with progressive gray matter loss in the brain. This spatially specific, morphological change over the life span in humans is also found in chimpanzees, and the comparison between these great ape species provides a unique evolutionary perspective on human brain aging. Here, we present a data-driven, comparative framework to explore the relationship between gray matter atrophy with age and recent cerebral expansion in the phylogeny of chimpanzees and humans. In humans, we show a positive relationship between cerebral aging and cortical expansion, whereas no such relationship was found in chimpanzees. This human-specific association between strong aging effects and large relative cortical expansion is particularly present in higher-order cognitive regions of the ventral prefrontal cortex and supports the "last-in-first-out" hypothesis for brain maturation in recent evolutionary development of human faculties.

Adipose tissue–derived adipsin marks human aging in non-type 2 diabetes population

IntroductionAdipsin or complement factor D is an adipokine that augments insulin secretion, is altered in various degrees of obesity, and is involved in alternative complement pathway. However, whether adipsin has...

Particulate matter 2.5 accelerates aging: Exploring cellular senescence and age-related diseases

Exposure to Particulate matter 2.5 (PM2.5) accelerates aging, causing declines in tissue and organ function, and leading to diseases such as cardiovascular, neurodegenerative, and musculoskeletal disorders. PM2.5 is a major environmental pollutant and an exogenous pathogen in air pollution that is now recognized as an accelerator of human aging and a predisposing factor for several age-related diseases. In this paper, we seek to elucidate the mechanisms by which PM2.5 induces cellular senescence, such as genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, and mitochondrial dysfunction, and age-related diseases. Our goal is to increase awareness among researchers within the field of the toxicity of environmental pollutants and to advocate for personal and public health initiatives to curb their production and enhance population protection. Through these endeavors, we aim to promote longevity and health in older adults.

Genetic architecture of telomere length in 462,666 UK Biobank whole-genome sequences

Telomeres protect chromosome ends from damage and their length is linked with human disease and aging. We developed a joint telomere length metric, combining quantitative PCR and whole-genome sequencing measurements from 462,666 UK Biobank participants. This metric increased SNP heritability, suggesting that it better captures genetic regulation of telomere length. Exome-wide rare-variant and gene-level collapsing association studies identified 64 variants and 30 genes significantly associated with telomere length, including allelic series in ACD and RTEL1. Notably, 16% of these genes are known drivers of clonal hematopoiesis—an age-related somatic mosaicism associated with myeloid cancers and several nonmalignant diseases. Somatic variant analyses revealed gene-specific associations with telomere length, including lengthened telomeres in individuals with large SRSF2-mutant clones, compared with shortened telomeres in individuals with clonal expansions driven by other genes. Collectively, our findings demonstrate the impact of rare variants on telomere length, with larger effects observed among genes also associated with clonal hematopoiesis.