Aging Biomarkers: From Functional Tests to Multi‐Omics Approaches

Advances in clinical application of lipidomics in healthy ageing and healthy longevity medicine

It is imperative to optimise health and healthspan across the lifespan. The accumulation of reactive oxygen species (ROS) has been implicated in the hallmarks of ageing and inhibiting ROS production can potentially delay ageing whilst increasing healthy longevity. Lipids and lipid mediators (derivatives of lipids) are becoming increasingly recognized as central molecule in tissue and cellular function and are susceptible to peroxidation; hence linked with ageing. Lipid classes implicated in the ageing process include sterols, glycerophospholipids, sphingolipids and the oxidation products of polyunsaturated fatty acids but these are not yet translated into the clinic. Further mechanistic studies are required for the understanding of lipid classes in the ageing process. Lipidomics, the system level characterisation of lipid species with respect to metabolism and function, might provide a significant and useful biological age profiling tool through longitudinal studies. Lipid profiles in different ages among healthy individuals could be harnessed as lipid biomarkers of healthy ageing with potential integration for the development of lipid-based ageing clock (lipid clock). The potential of a lipid clock includes the prediction of future morbidity or mortality, which will promote precision and healthy longevity medicine.

Mitochondrial Oxidative Stress Regulates FOXP3+ T-Cell Activity and CD4-Mediated Inflammation in Older Adults with Frailty

In healthy older adults, the immune system generally preserves its response and contributes to a long, healthy lifespan. However, rapid deterioration in immune regulation can lead to chronic inflammation, termed inflammaging, which accelerates pathological aging and diminishes the quality of life in older adults with frailty. A significant limitation in current aging research is the predominant focus on comparisons between young and older populations, often overlooking the differences between healthy older adults and those experiencing pathological aging. Our study elucidates the intricate immunological dynamics of the CD4/Treg axis in frail older adults compared to comparable age-matched healthy older adults. By utilizing publicly available RNA sequencing and single-cell RNA sequencing (scRNAseq) data from peripheral blood mononuclear cells (PBMCs), we identified a specific Treg cell subset and transcriptional landscape contributing to the dysregulation of CD4+ T-cell responses. We explored the molecular mechanisms underpinning Treg dysfunction, revealing that Tregs from frail older adults exhibit reduced mitochondrial protein levels, impairing mitochondrial oxidative phosphorylation. This impairment is driven by the TNF/NF-kappa B pathway, leading to cumulative inflammation. Further, we gained a deeper understanding of the CD4/Treg axis by predicting the effects of gene perturbations on cellular signaling networks. Collectively, these findings highlight the age-related relationship between mitochondrial dysfunction in the CD4/Treg axis and its role in accelerating aging and frailty in older adults. Targeting Treg dysfunction offers a critical basis for developing tailored therapeutic strategies aimed at improving the quality of life in older adults.

A multi-omics study to monitor senescence-associated secretory phenotypes of Alzheimer's disease

OBJECTIVE

Alzheimer's disease (AD) is characterized by the progressive degeneration and damage of neurons in the brain. However, developing an accurate diagnostic assay using blood samples remains a challenge in clinic practice. The aim of this study was to explore senescence-associated secretory phenotypes (SASPs) in peripheral blood using mass spectrometry based multi-omics approach and to establish diagnostic assays for AD.

METHODS

This retrospective study included 88 participants, consisting of 29 AD patients and 59 cognitively normal (CN) individuals. Plasma and serum samples were examined using high-resolution mass spectrometry to identify proteomic and metabolomic profiles. Receiver operating characteristic (ROC) analysis was employed to screen biomarkers with diagnostic potential. K-nearest neighbors (KNN) algorithm was utilized to construct a multi-dimensional model for distinguishing AD from CN.

RESULTS

Proteomics analysis revealed upregulation of five plasma proteins in AD, including RNA helicase aquarius (AQR), zinc finger protein 587B (ZNF587B), C-reactive protein (CRP), fibronectin (FN1), and serum amyloid A-1 protein (SAA1), indicating their potential for AD classification. Interestingly, KNN-based three-dimensional model, comprising AQR, ZNF587B, and CRP, demonstrated its high accuracy in AD recognition, with evaluation possibilities of 0.941, 1.000, and 1.000 for the training, testing, and validation datasets, respectively. Besides, metabolomics analysis suggested elevated levels of serum phenylacetylglutamine (PAGIn) in AD.

INTERPRETATION

The multi-omics outcomes highlighted the significance of the SASPs, specifically AQR, ZNF587B, CRP, and PAGIn, in terms of their potential for diagnosing AD and suggested neuronal aging-associated pathophysiology.

Organ-specific biological clocks: Ageotyping for personalized anti-aging medicine

Aging is a complex multidimensional, progressive remodeling process affecting multiple organ systems. While many studies have focused on studying aging across multiple organs, assessment of the contribution of individual organs to overall aging processes is a cutting-edge issue. An organ's biological age might influence the aging of other organs, revealing a multiorgan aging network. Recent data demonstrated a similar yet asynchronous inter-organs and inter-individuals progression of aging, thereby providing a foundation to track sources of declining health in old age. The integration of multiple omics with common clinical parameters through artificial intelligence has allowed the building of organ-specific aging clocks, which can predict the development of specific age-related diseases at high resolution. The peculiar individual aging-trajectory, referred to as ageotype, might provide a novel tool for a personalized anti-aging, preventive medicine. Here, we review data relative to biological aging clocks and omics-based data, suggesting different organ-specific aging rates. Additional research on longitudinal data, including young subjects and analyzing sex-related differences, should be encouraged to apply ageotyping analysis for preventive purposes in clinical practice.

Metabolic biomarkers using nuclear magnetic resonance metabolomics assay for the prediction of aging-related disease risk and mortality: a prospective, longitudinal, observational, cohort study based on the UK Biobank

The identification of metabolic biomarkers for aging-related diseases and mortality is of significant interest in the field of longevity. In this study, we investigated the associations between nuclear magnetic resonance (NMR) metabolomics biomarkers and aging-related diseases as well as mortality using the UK Biobank dataset. We analyzed NMR samples from approximately 110,000 participants and used multi-head machine learning classification models to predict the incidence of aging-related diseases. Cox regression models were then applied to assess the relevance of NMR biomarkers to the risk of death due to aging-related diseases. Additionally, we conducted survival analyses to evaluate the potential improvements of NMR in predicting survival and identify the biomarkers most strongly associated with negative health outcomes by dividing participants into health, disease, and death groups for all age groups. Our analysis revealed specific metabolomics profiles that were associated with the incidence of age-related diseases, and the most significant biomarker was intermediate density lipoprotein cholesteryl (IDL-CE). In addition, NMR biomarkers could provide additional contributions to relevant mortality risk prediction when combined with conventional risk factors, by improving the C-index from 0.813 to 0.833, with 17 NMR biomarkers significantly contributing to disease-related death, such as monounsaturated fatty acids (MUFA), linoleic acid (LA), glycoprotein acetyls (GlycA), and omega-3. Moreover, the value of free cholesterol in very large HDL particles (XL-HDL-FC) in the healthy control group demonstrated significantly higher values than the disease and death group across all age groups. This study highlights the potential of NMR metabolomics profiling as a valuable tool for identifying metabolic biomarkers associated with aging-related diseases and mortality risk, which could have practical implications for aging-related disease risk and mortality prediction.

Validation of biomarkers of aging

The search for biomarkers that quantify biological aging (particularly 'omic'-based biomarkers) has intensified in recent years. Such biomarkers could predict aging-related outcomes and could serve as surrogate endpoints for the evaluation of interventions promoting healthy aging and longevity. However, no consensus exists on how biomarkers of aging should be validated before their translation to the clinic. Here, we review current efforts to evaluate the predictive validity of omic biomarkers of aging in population studies, discuss challenges in comparability and generalizability and provide recommendations to facilitate future validation of biomarkers of aging. Finally, we discuss how systematic validation can accelerate clinical translation of biomarkers of aging and their use in gerotherapeutic clinical trials.

Development of an epigenetic clock to predict visual age progression of human skin

Aging is a complex process characterized by the gradual decline of physiological functions, leading to increased vulnerability to age-related diseases and reduced quality of life. Alterations in DNA methylation (DNAm) patterns have emerged as a fundamental characteristic of aged human skin, closely linked to the development of the well-known skin aging phenotype. These changes have been correlated with dysregulated gene expression and impaired tissue functionality. In particular, the skin, with its visible manifestations of aging, provides a unique model to study the aging process. Despite the importance of epigenetic age clocks in estimating biological age based on the correlation between methylation patterns and chronological age, a second-generation epigenetic age clock, which correlates DNAm patterns with a particular phenotype, specifically tailored to skin tissue is still lacking. In light of this gap, we aimed to develop a novel second-generation epigenetic age clock explicitly designed for skin tissue to facilitate a deeper understanding of the factors contributing to individual variations in age progression. To achieve this, we used methylation patterns from more than 370 female volunteers and developed the first skin-specific second-generation epigenetic age clock that accurately predicts the skin aging phenotype represented by wrinkle grade, visual facial age, and visual age progression, respectively. We then validated the performance of our clocks on independent datasets and demonstrated their broad applicability. In addition, we integrated gene expression and methylation data from independent studies to identify potential pathways contributing to skin age progression. Our results demonstrate that our epigenetic age clock, VisAgeX, specifically predicting visual age progression, not only captures known biological pathways associated with skin aging, but also adds novel pathways associated with skin aging.

CAT Bridge: an efficient toolkit for gene-metabolite association mining from multiomics data

BACKGROUND

With advancements in sequencing and mass spectrometry technologies, multiomics data can now be easily acquired for understanding complex biological systems. Nevertheless, substantial challenges remain in determining the association between gene-metabolite pairs due to the nonlinear and multifactorial interactions within cellular networks. The complexity arises from the interplay of multiple genes and metabolites, often involving feedback loops and time-dependent regulatory mechanisms that are not easily captured by traditional analysis methods.

FINDINGS

Here, we introduce Compounds And Transcripts Bridge (abbreviated as CAT Bridge, available at https://catbridge.work), a free user-friendly platform for longitudinal multiomics analysis to efficiently identify transcripts associated with metabolites using time-series omics data. To evaluate the association of gene-metabolite pairs, CAT Bridge is a pioneering work benchmarking a set of statistical methods spanning causality estimation and correlation coefficient calculation for multiomics analysis. Additionally, CAT Bridge features an artificial intelligence agent to assist users interpreting the association results.

CONCLUSIONS

We applied CAT Bridge to experimentally obtained Capsicum chinense (chili pepper) and public human and Escherichia coli time-series transcriptome and metabolome datasets. CAT Bridge successfully identified genes involved in the biosynthesis of capsaicin in C. chinense. Furthermore, case study results showed that the convergent cross-mapping method outperforms traditional approaches in longitudinal multiomics analyses. CAT Bridge simplifies access to various established methods for longitudinal multiomics analysis and enables researchers to swiftly identify associated gene-metabolite pairs for further validation.

Uterine microbial communities and their potential role in the regulation of epithelium cell cycle and apoptosis in aged hens

BACKGROUND

Alterations of the uterine microbiome are closely associated with various intrauterine diseases and physiological conditions, which are well-established in mammals. However, as representative oviparous animals, the research on the uterine microbial ecosystem and its functions with physiological homeostasis is limited in chickens. Additionally, continuous egg-laying disrupts the oviducal immune defenses of aged hens, susceptible to pathogen invasion, causing poor egg quality and food-borne infections in humans. Here, we investigated aging-related changes in the oviduct microbial colonization and transmission from the gut to eggs and their roles in a hen model.

RESULTS

The results of 16S rDNA sequencing showed significant differences in the oviduct microbial composition between young (38 weeks) and aged (77 weeks) laying hens. SourceTracker analysis further revealed differences in the effects of microbial transmission on the oviducal microbiota between young and aged hens. Enhanced barrier defense with cell apoptosis suppression and cell cycle arrest of the uterus were observed in aged hens reducing microbial transmission from the lower to upper reproductive tract. In addition, a total of 361 significantly differential metabolites were identified using metabolomics in the aged uterine microbiota, especially in products of amino acid metabolism and biosynthesis of various secondary metabolites, which might have essential effects on cell apoptosis by regulating immune responses and cell cycle. Notably, antibiotics disrupted uterine microbiota by dietary intervention and direct perfusion did not retard aging-related physiological changes but further aggravated aging processes by disrupting the cell cycle and apoptosis.

CONCLUSIONS

The microbiota continuum along the reproductive tract in aged birds differs from that in young birds, especially with a significant shift in the uterus. The aged uterine microbiota probably contributes to the regulation of cell cycle and apoptosis by microbial metabolites primarily involved in amino acid metabolism and biosynthesis of various secondary metabolites. These findings provide new insights into the roles of the reproductive tract microbiota in regulating the cell programming of the aged host, contributing to the exploration of the microbiome as a target for diagnosing aging health status and therapy for gynecological diseases in women. Video Abstract.

Caenorhabditis elegans as an in vivo model for the identification of natural antioxidants with anti-aging actions

Natural antioxidants have recently emerged as a highly exciting and significant topic in anti-aging research. Diverse organism models present a viable protocol for future research. Notably, many breakthroughs on natural antioxidants have been achieved in the nematode Caenorhabditis elegans, an animal model frequently utilized for the study of aging research and anti-aging drugs in vivo. Due to the conservation of signaling pathways on oxidative stress resistance, lifespan regulation, and aging disease between C. elegans and multiple high-level organisms (humans), as well as the low and controllable cost of time and labor, it gradually develops into a trustworthy in vivo model for high-throughput screening and validation of natural antioxidants with anti-aging actions. First, information and models on free radicals and aging are presented in this review. We also describe indexes, detection methods, and molecular mechanisms for studying the in vivo antioxidant and anti-aging effects of natural antioxidants using C. elegans. It includes lifespan, physiological aging processes, oxidative stress levels, antioxidant enzyme activation, and anti-aging pathways. Furthermore, oxidative stress and healthspan improvement induced by natural antioxidants in humans and C. elegans are compared, to understand the potential and limitations of the screening model in preclinical studies. Finally, we emphasize that C. elegans is a useful model for exploring more natural antioxidant resources and uncovering the mechanisms underlying aging-related risk factors and diseases.

Dynamics of redox signaling in aging via autophagy, inflammation, and senescence

Review paper attempts to explain the dynamic aspects of redox signaling in aging through autophagy, inflammation, and senescence. It begins with ROS source in the cell, then states redox signaling in autophagy, and regulation of autophagy in aging. Next, we discuss inflammation and redox signaling with various pathways involved: NOX pathway, ROS production via TNF-α, IL-1β, xanthine oxidase pathway, COX pathway, and myeloperoxidase pathway. Also, we emphasize oxidative damage as an aging marker and the contribution of pathophysiological factors to aging. In senescence-associated secretory phenotypes, we link ROS with senescence, aging disorders. Relevant crosstalk between autophagy, inflammation, and senescence using a balanced ROS level might reduce age-related disorders. Transducing the context-dependent signal communication among these three processes at high spatiotemporal resolution demands other tools like multi-omics aging biomarkers, artificial intelligence, machine learning, and deep learning. The bewildering advancement of technology in the above areas might progress age-related disorders diagnostics with precision and accuracy.

Challenges in anti-aging medicine-trends in biomarker discovery and therapeutic interventions for a healthy lifespan

We are facing a growing aging population, along with increasing pressure on health systems, caused by the impact of chronic co-morbidities (i.e. cancer, cardiovascular and neurodegenerative diseases) and functional disabilities as people age. Relatively simple preventive lifestyle interventions, such as dietary restriction and physical exercise, are important contributors to active and healthy aging in the general population. However, as shown in model organisms or in 'in vitro' conditions, lifestyle-independent interventions may have additional health benefits and can even be conceived as possible reversers of the aging process. Thus, pharmaceutical laboratories, research institutes, and universities are putting more and more effort into finding new molecular pathways and druggable targets to develop gerotherapeutics. One approach is to target the driving mechanisms of aging, some of which, like cellular senescence and impaired autophagy, we discussed in an update on the biology of aging at AgingFit 2023 in Lille, France. We underline the importance of carefully and extensively testing senotherapeutics, given the pleiotropism and heterogeneity of targeted senescent cells within different organs, at different time frames. Other druggable targets emerging from new putative mechanisms, like those based on transcriptome imbalance, nucleophagy, protein phosphatase depletion, glutamine metabolism, or seno-antigenicity, have been evidenced by recent preclinical studies in classical models of aging but need to be validated in humans. Finally, we highlight several approaches in the discovery of biomarkers of healthy aging, as well as for the prediction of neurodegenerative diseases and the evaluation of rejuvenation strategies.

Physiologically based pharmacokinetic (PBPK) modelling of oral drug absorption in older adults - an AGePOP review

The older population consisting of persons aged 65 years or older is the fastest-growing population group and also the major consumer of pharmaceutical products. Due to the heterogenous ageing process, this age group shows high interindividual variability in the dose-exposure-response relationship and, thus, a prediction of drug safety and efficacy is challenging. Although physiologically based pharmacokinetic (PBPK) modelling is a well-established tool to inform and confirm drug dosing strategies during drug development for special population groups, age-related changes in absorption are poorly accounted for in current PBPK models. The purpose of this review is to summarise the current state-of-knowledge in terms of physiological changes with increasing age that can influence the oral absorption of dosage forms. The capacity of common PBPK platforms to incorporate these changes and describe the older population is also discussed, as well as the implications of extrinsic factors such as drug-drug interactions associated with polypharmacy on the model development process. The future potential of this field will rely on addressing the gaps identified in this article, which can subsequently supplement in-vitro and in-vivo data for more robust decision-making on the adequacy of the formulation for use in older adults and inform pharmacotherapy.

Druggability of Targets for Diagnostic Radiopharmaceuticals

Targets play an indispensable and pivotal role in the development of radiopharmaceuticals. However, the initial stages of drug discovery projects are often plagued by frequent failures due to inadequate information on druggability and suboptimal target selection. In this context, we aim to present a comprehensive review of the factors that influence target druggability for diagnostic radiopharmaceuticals. Specifically, we explore the crucial determinants of target specificity, abundance, localization, and positivity rate and their respective implications. Through a detailed analysis of existing protein targets, we elucidate the significance of each factor. By carefully considering and balancing these factors during the selection of targets, more efficacious and targeted radiopharmaceuticals are expected to be designed for the diagnosis of a wide range of diseases in the future.

Glycemic status and its association with retinal age gap: Insights from the UK biobank study

OBJECTIVE

To investigate associations between different glycemic status and biological age indexed by retinal age gap.

METHODS

A total of 28,919 participants from the UK Biobank study with available glycemic status and qualified retinal imaging data were included in the present analysis. Glycemic status included type 2 diabetes mellitus (T2D) disease status and glycemic indicators of plasma glycated hemoglobin (HbA1c) and glucose. Retinal age gap was defined as the difference between the retina-predicted age and chronological age. Linear regression models estimated the association of different glycemic status with retinal age gap.

RESULTS

Prediabetes and T2D was significantly associated with higher retinal age gaps compared to normoglycemia (regression coefficient [β] = 0.25, 95% confidence interval [CI]: 0.11-0.40, P = 0.001; β = 1.06, 95% CI: 0.83-1.29, P < 0.001; respectively). Multi-variable linear regressions further found an increase of HbA1c was independently associated with higher retinal age gaps among all subjects or subjects without T2D. Significant positive associations were noted across the increasing HbA1c and glucose groups with retinal age gaps compared to the normal level group. These findings remained significant after excluding diabetic retinopathy.

CONCLUSIONS

Dysglycemia was significantly associated with accelerated ageing indexed by retinal age gaps, highlighting the importance of maintaining glycemic status.

Aging Hallmarks and the Role of Oxidative Stress

Aging is a complex biological process accompanied by a progressive decline in the physical function of the organism and an increased risk of age-related chronic diseases such as cardiovascular diseases, cancer, and neurodegenerative diseases. Studies have established that there exist nine hallmarks of the aging process, including (i) telomere shortening, (ii) genomic instability, (iii) epigenetic modifications, (iv) mitochondrial dysfunction, (v) loss of proteostasis, (vi) dysregulated nutrient sensing, (vii) stem cell exhaustion, (viii) cellular senescence, and (ix) altered cellular communication. All these alterations have been linked to sustained systemic inflammation, and these mechanisms contribute to the aging process in timing not clearly determined yet. Nevertheless, mitochondrial dysfunction is one of the most important mechanisms contributing to the aging process. Mitochondria is the primary endogenous source of reactive oxygen species (ROS). During the aging process, there is a decline in ATP production and elevated ROS production together with a decline in the antioxidant defense. Elevated ROS levels can cause oxidative stress and severe damage to the cell, organelle membranes, DNA, lipids, and proteins. This damage contributes to the aging phenotype. In this review, we summarize recent advances in the mechanisms of aging with an emphasis on mitochondrial dysfunction and ROS production.

Systematic estimation of biological age of in vitro cell culture systems by an age-associated marker panel

Aging is a process that affects almost all multicellular organisms and since our population ages with increasing prevalence of age-related diseases, it is important to study basic processes involved in aging. Many studies have been published so far using different and often single age markers to estimate the biological age of organisms or different cell culture systems. However, comparability of studies is often hampered by the lack of a uniform panel of age markers. Consequently, we here suggest an easy-to-use biomarker-based panel of classical age markers to estimate the biological age of cell culture systems that can be used in standard cell culture laboratories. This panel is shown to be sensitive in a variety of aging conditions. We used primary human skin fibroblasts of different donor ages and additionally induced either replicative senescence or artificial aging by progerin overexpression. Using this panel, highest biological age was found for artificial aging by progerin overexpression. Our data display that aging varies depending on cell line and aging model and even from individual to individual showing the need for comprehensive analyses.

Data-driven identification and classification of nonlinear aging patterns reveals the landscape of associations between DNA methylation and aging

BACKGROUND

Aging affects the incidence of diseases such as cancer and dementia, so the development of biomarkers for aging is an important research topic in medical science. While such biomarkers have been mainly identified based on the assumption of a linear relationship between phenotypic parameters, including molecular markers, and chronological age, numerous nonlinear changes between markers and aging have been identified. However, the overall landscape of the patterns in nonlinear changes that exist in aging is unknown.

RESULT

We propose a novel computational method, Data-driven Identification and Classification of Nonlinear Aging Patterns (DICNAP), that is based on functional data analysis to identify biomarkers for aging and potential patterns of change during aging in a data-driven manner. We applied the proposed method to large-scale, public DNA methylation data to explore the potential patterns of age-related changes in methylation intensity. The results showed that not only linear, but also nonlinear changes in DNA methylation patterns exist. A monotonous demethylation pattern during aging, with its rate decreasing at around age 60, was identified as the candidate stable nonlinear pattern. We also analyzed the age-related changes in methylation variability. The results showed that the variability of methylation intensity tends to increase with age at age-associated sites. The representative variability pattern is a monotonically increasing pattern that accelerates after middle age.

CONCLUSION

DICNAP was able to identify the potential patterns of the changes in the landscape of DNA methylation during aging. It contributes to an improvement in our theoretical understanding of the aging process.

Ageing at Molecular Level: Role of MicroRNAs

The progression of age triggers a vast number of diseases including cardiovascular, cancer, and neurodegenerative disorders. Regardless of our plentiful knowledge about age-related diseases, little is understood about molecular pathways that associate the ageing process with various diseases. Several cellular events like senescence, telomere dysfunction, alterations in protein processing, and regulation of gene expression are common between ageing and associated diseases. Accumulating information on the role of microRNAs (miRNAs) suggests targeting miRNAs can aid our understanding of the interplay between ageing and associated diseases. In the present chapter, we have attempted to explore the information available on the role of miRNAs in ageing of various tissues/organs and diseases and understand the molecular mechanism of ageing.

Female APOE ɛ4 Carriers with Slow Rates of Biological Aging Have Better Memory Performances Compared to Female ɛ4 Carriers with Accelerated Aging

BACKGROUND

Evidence suggests that APOE ɛ4 carriers have worse memory performances compared to APOE ɛ4 non-carriers and effects may vary by sex and age. Estimates of biological age, using DNA methylation may enhance understanding of the associations between sex and APOE ɛ4 on cognition.

OBJECTIVE

To investigate whether associations between APOE ɛ4 status and memory vary according to rates of biological aging, using a DNA methylation age biomarker, in older men and women without dementia.

METHODS

Data were obtained from 1,771 adults enrolled in the 2016 wave of the Health and Retirement Study. A series of ANCOVAs were used to test the interaction effects of APOE ɛ4 status and aging rates (defined as 1 standard deviation below (i.e., slow rate), or above (i.e., fast rate) their sex-specific mean rate of aging on a composite measure of verbal learning and memory.

RESULTS

APOE ɛ4 female carriers with slow rates of GrimAge had significantly better memory performances compared to fast and average aging APOE ɛ4 female carriers. There was no effect of aging group rate on memory in the female non-carriers and no significant differences in memory according to age rate in either male APOE ɛ4 carriers or non-carriers.

CONCLUSION

Slower rates of aging in female APOE ɛ4 carriers may buffer against the negative effects of the ɛ4 allele on memory. However, longitudinal studies with larger sample sizes are needed to evaluate risk of dementia/memory impairment based on rates of aging in female APOE ɛ4 carriers.

Untargeted Metabolomic Approach to Study the Impact of Aging on Salivary Metabolome in Women

Despite the growing interest in salivary metabolomics, few studies have investigated the impact of aging on the salivary metabolome. The alterations in metabolic pathways that occur with aging are likely to be observed in pathologies affecting older people and may interfere with the search for salivary biomarkers. It is therefore important to investigate the age-related changes occurring in the salivary metabolome. Using reversed phase liquid chromatography and hydrophilic interaction chromatography coupled to mass spectrometry used in positive and negative ionization modes, the salivary metabolic profiles of young (22 to 45 years old) and older people (55 to 92 years old) were obtained. Those profiles were compared with the use of XCMS online to highlight the under or overexpression of some metabolites with aging. A total of 60 metabolites showed differential expression with age. The identification of 26 of them was proposed by the METLIN database and, among them, 17 were validated by standard injections. Aging seemed to affect most of the main metabolic pathways (amino acid metabolism, Krebs cycle, fatty acid synthesis, and nucleic acid synthesis). Moreover, most of the metabolites that were over- or under-expressed with age in this study have already been identified as being potential biomarkers of diseases affecting older people, such as in Alzheimer's disease. Special attention should be paid in the search for biomarkers of pathologies affecting the elderly to differentiate age-related changes from disease-related changes.

We are all aging, and here's why

Here, through this review, we aim to serve this purpose by first discussing the statistics and aging demographics, including the life expectancy of the world and India, along with the gender life expectancy gap observed throughout the world, followed by explaining the hallmarks and integral causes of aging, along with the role played by senescent cells in controlling inflammation and the effect of senescence associated secretory phenotype on longevity. A few of the molecular pathways which are crucial in modulating the process of aging, such as the nutrient-sensing mTOR pathway, insulin signaling, Nrf2, FOXO, PI3-Akt, Sirtuins, and AMPK, and their effects are also covered in paramount detail. A diverse number of ingenious research methodologies are used in the modern era of longevity exploration. We have attempted to cover these methods under the umbrella of three broad categories: in vitro, in vivo, and in silico techniques. The drugs developed to attenuate the aging process, such as rapamycin, metformin, resveratrol, etc. and their interactions with the above-mentioned molecular pathways along with their toxicity have also been reviewed in detail.

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.

Identification of Key Biomarkers and Pathways for Maintaining Cognitively Normal Brain Aging Based on Integrated Bioinformatics Analysis

Background

Given the arrival of the aging population has caused a series of social and economic problems, we aimed to explore the key genes underlying cognitively normal brain aging and its potential molecular mechanisms.

Methods

GSE11882 was downloaded from Gene Expression Omnibus (GEO). The data from different brain regions were divided into aged and young groups for analysis. Co-expressed differentially expressed genes (DEGs) were screened. Functional analysis, protein–protein interaction (PPI) network, microRNA (miRNA)-gene, and transcription factor (TF)-gene networks were performed to identify hub genes and related molecular mechanisms. AlzData database was used to elucidate the expression of DEGs and hub genes in the aging brain. Animal studies were conducted to validate the hub genes.

Results

Co-expressed DEGs contained 7 upregulated and 87 downregulated genes. The enrichment analysis indicated DEGs were mainly involved in biological processes and pathways related to immune-inflammatory responses. From the PPI network, 10 hub genes were identified: C1QC, C1QA, C1QB, CD163, FCER1G, VSIG4, CD93, CD14, VWF, and CD44. CD44 and CD93 were the most targeted DEGs in the miRNA-gene network, and TIMP1, HLA-DRA, VWF, and FGF2 were the top four targeted DEGs in the TF-gene network. In AlzData database, the levels of CD44, CD93, and CD163 in patients with Alzheimer’s disease (AD) were significantly increased than those in normal controls. Meanwhile, in the brain tissues of cognitively normal mice, the expression of CD44, CD93, and CD163 in the aged group was significantly lower than those in the young group.

Conclusion

The underlying molecular mechanisms for maintaining healthy brain aging are related to the decline of immune-inflammatory responses. CD44, CD93, and CD 163 are considered as potential biomarkers. This study provides more molecular evidence for maintaining cognitively normal brain aging.

Rejuvant®, a potential life-extending compound formulation with alpha-ketoglutarate and vitamins, conferred an average 8 year reduction in biological aging, after an average of 7 months of use, in the TruAge DNA methylation test

The search continues for possible interventions that delay and/or reverse biological aging, resulting in extended healthspan and lifespan. Interventions delaying aging in animal models are well established; however, most lack validation in humans. The length of human lifespan makes it impractical to perform survival analysis. Instead, aging biomarkers, such as DNA methylation (DNAm) clocks, have been developed to monitor biological age. Herein we report a retrospective analysis of DNA methylation age in 42 individuals taking Rejuvant®, an alpha-ketoglutarate based formulation, for an average period of 7 months. DNAm testing was performed at baseline and by the end of treatment with Rejuvant® supplementation. Remarkably, individuals showed an average decrease in biological aging of 8 years (p-value=6.538x10^-12). Furthermore, the supplementation with Rejuvant® is robust to individual differences, as indicated by the fact that a large majority of participants decreased their biological age. Moreover, we found that Rejuvant® is of additional benefit to chronologically and biologically older individuals. While continued testing, particularly in a placebo-controlled design, is required, the nearly 8-year reversal in the biological age of individuals taking Rejuvant® for 4 to 10 months is noteworthy, making the natural product cocktail an intriguing candidate to affect human aging.

A Metabolomic Aging Clock Using Human Cerebrospinal Fluid

Quantifying the physiology of aging is essential for improving our understanding of age-related disease and the heterogeneity of healthy aging. Recent studies have shown that, in regression models using "-omic" platforms to predict chronological age, residual variation in predicted age is correlated with health outcomes, and suggest that these "omic clocks" provide measures of biological age. This paper presents predictive models for age using metabolomic profiles of cerebrospinal fluid (CSF) from healthy human subjects and finds that metabolite and lipid data are generally able to predict chronological age within 10 years. We use these models to predict the age of a cohort of subjects with Alzheimer's and Parkinson's disease and find an increase in prediction error, potentially indicating that the relationship between the metabolome and chronological age differs with these diseases. However, evidence is not found to support the hypothesis that our models will consistently overpredict the age of these subjects. In our analysis of control subjects, we find the carnitine shuttle, sucrose, biopterin, vitamin E metabolism, tryptophan, and tyrosine to be the most associated with age. We showcase the potential usefulness of age prediction models in a small data set (n = 85) and discuss techniques for drift correction, missing data imputation, and regularized regression, which can be used to help mitigate the statistical challenges that commonly arise in this setting. To our knowledge, this work presents the first multivariate predictive metabolomic and lipidomic models for age using mass spectrometry analysis of CSF.

Elementary Laboratory Assays as Biomarkers of Ageing: Support for Treatment of COVID-19?

Youth, working age and the elderly: On a timeline, chronological age (CA) and biological age (BA) may dissociate; nosological entities manifest themselves at different BAs. In determining which disease corresponds to a given age decade, statistical registries of causes of death are unreliable and this does not change with SARS CoV-2 infection. Beyond adolescence, ageing metrics involve estimations of changes in fitness, including prediction models to estimate the number of remaining years left to live. A substantial disparity in biomarker levels and health status of ageing can be observed: the difference in CA and BA in the large cohorts under consideration is glaring. Here, we focus more closely on ageing and senescence metrics in order to make information available for risk analysis non the least with COVID-19, including the most recent risk factors of ABO blood type and 3p21.31 chromosome cluster impacting on C5a and SC5b-9 plasma levels. From the multitude of routine medical laboratory assays, a potentially meaningful set of assays aimed to best reflect the stage of individual senescence; hence risk factors the observational prospective SENIORLABOR study of 1,467 healthy elderly performed since 2009 and similar approaches since 1958 can be instantiated as a network to combine a set of elementary laboratory assays quantifying senescence.

Ranking Biomarkers of Aging by Citation Profiling and Effort Scoring

Aging affects most living organisms and includes the processes that reduce health and survival. The chronological and the biological age of individuals can differ remarkably, and there is a lack of reliable biomarkers to monitor the consequences of aging. In this review we give an overview of commonly mentioned and frequently used potential aging-related biomarkers. We were interested in biomarkers of aging in general and in biomarkers related to cellular senescence in particular. To answer the question whether a biological feature is relevant as a potential biomarker of aging or senescence in the scientific community we used the PICO strategy known from evidence-based medicine. We introduced two scoring systems, aimed at reflecting biomarker relevance and measurement effort, which can be used to support study designs in both clinical and research settings.

An update in toxicology of ageing

The field of ageing research has been rapidly advancing in recent decades and it had provided insight into the complexity of ageing phenomenon. However, as the organism-environment interaction appears to significantly affect the organismal pace of ageing, the systematic approach for gerontogenic risk assessment of environmental factors has yet to be established. This puts demand on development of effective biomarker of ageing, as a relevant tool to quantify effects of gerontogenic exposures, contingent on multidisciplinary research approach. Here we review the current knowledge regarding the main endogenous gerontogenic pathways involved in acceleration of ageing through environmental exposures. These include inflammatory and oxidative stress-triggered processes, dysregulation of maintenance of cellular anabolism and catabolism and loss of protein homeostasis. The most effective biomarkers showing specificity and relevancy to ageing phenotypes are summarized, as well. The crucial part of this review was dedicated to the comprehensive overview of environmental gerontogens including various types of radiation, certain types of pesticides, heavy metals, drugs and addictive substances, unhealthy dietary patterns, and sedentary life as well as psychosocial stress. The reported effects in vitro and in vivo of both recognized and potential gerontogens are described with respect to the up-to-date knowledge in geroscience. Finally, hormetic and ageing decelerating effects of environmental factors are briefly discussed, as well.

CDKN2A Gene Expression as a Potential Aging Biomarker in Dogs

Describing evolutionary conserved physiological or molecular patterns, which can reliably mark the age of both model organisms and humans or predict the onset of age-related pathologies has become a priority in aging research. The age-related gene-expression changes of the Cyclin Dependent Kinase Inhibitor 2A (CDKN2A) gene have been well-documented in humans and rodents. However, data is lacking from other relevant species, including dogs. Therefore, we quantified the CDKN2A mRNA abundance in dogs of different ages, in four tissue types: the frontal cortex of the brain, temporal muscle, skin, and blood. We found a significant, positive correlation between CDKN2A relative expression values and age in the brain, muscle, and blood; however, no correlation was detected in the skin. The strongest correlation was detected in the brain tissue (CDKN2A/GAPDH: r = 0.757, p < 0.001), similarly to human findings, while the muscle and blood showed weaker, but significant correlation. Our results suggest that CDKN2A might be a potential blood-borne biomarker of aging in dogs, although the validation and optimization will require further, more focused research. Our current results also clearly demonstrate that the role of CDKN2A in aging is conserved in dogs, regarding both tissue specificity and a pivotal role of CDKN2A in brain aging.

Multi-Omics Approaches and Radiation on Lipid Metabolism in Toothed Whales

Lipid synthesis pathways of toothed whales have evolved since their movement from the terrestrial to marine environment. The synthesis and function of these endogenous lipids and affecting factors are still little understood. In this review, we focused on different omics approaches and techniques to investigate lipid metabolism and radiation impacts on lipids in toothed whales. The selected literature was screened, and capacities, possibilities, and future approaches for identifying unusual lipid synthesis pathways by omics were evaluated. Omics approaches were categorized into the four major disciplines: lipidomics, transcriptomics, genomics, and proteomics. Genomics and transcriptomics can together identify genes related to unique lipid synthesis. As lipids interact with proteins in the animal body, lipidomics, and proteomics can correlate by creating lipid-binding proteome maps to elucidate metabolism pathways. In lipidomics studies, recent mass spectroscopic methods can address lipid profiles; however, the determination of structures of lipids are challenging. As an environmental stress, the acoustic radiation has a significant effect on the alteration of lipid profiles. Radiation studies in different omics approaches revealed the necessity of multi-omics applications. This review concluded that a combination of many of the omics areas may elucidate the metabolism of lipids and possible hazards on lipids in toothed whales by radiation.

RIFS2D: A two-dimensional version of a randomly restarted incremental feature selection algorithm with an application for detecting low-ranked biomarkers

The era of big data introduces both opportunities and challenges for biomedical researchers. One of the inherent difficulties in the biomedical research field is to recruit large cohorts of samples, while high-throughput biotechnologies may produce thousands or even millions of features for each sample. Researchers tend to evaluate the individual correlation of each feature with the class label and use the incremental feature selection (IFS) strategy to select the top-ranked features with the best prediction performance. Recent experimental data showed that a subset of continuously ranked features randomly restarted from a low-ranked feature (an RIFS block) may outperform the subset of top-ranked features. This study proposed a feature selection Algorithm RIFS2D by integrating multiple RIFS blocks. A comprehensive comparative experiment was conducted with the IFS, RIFS and existing feature selection algorithms and demonstrated that a subset of low-ranked features may also achieve promising prediction performance. This study suggested that a prediction model with promising performance may be trained by low-ranked features, even when top-ranked features did not achieve satisfying prediction performance. Further comparative experiments were conducted between RIFS2D and t-tests for the detection of early-stage breast cancer. The data showed that the RIFS2D-recommended features achieved better prediction accuracy and were targeted by more drugs than the t-test top-ranked features.

Health and longevity studies in C. elegans: the "healthy worm database" reveals strengths, weaknesses and gaps of test compound-based studies

Several biogerontology databases exist that focus on genetic or gene expression data linked to health as well as survival, subsequent to compound treatments or genetic manipulations in animal models. However, none of these has yet collected experimental results of compound-related health changes. Since quality of life is often regarded as more valuable than length of life, we aim to fill this gap with the “Healthy Worm Database” (http://healthy-worm-database.eu). Literature describing health-related compound studies in the aging model Caenorhabditis elegans was screened, and data for 440 compounds collected. The database considers 189 publications describing 89 different phenotypes measured in 2995 different conditions. Besides enabling a targeted search for promising compounds for further investigations, this database also offers insights into the research field of studies on healthy aging based on a frequently used model organism. Some weaknesses of C. elegans-based aging studies, like underrepresented phenotypes, especially concerning cognitive functions, as well as the convenience-based use of young worms as the starting point for compound treatment or phenotype measurement are discussed. In conclusion, the database provides an anchor for the search for compounds affecting health, with a link to public databases, and it further highlights some potential shortcomings in current aging research.

ARDD 2020: from aging mechanisms to interventions

Aging is emerging as a druggable target with growing interest from academia, industry and investors. New technologies such as artificial intelligence and advanced screening techniques, as well as a strong influence from the industry sector may lead to novel discoveries to treat age-related diseases. The present review summarizes presentations from the 7th Annual Aging Research and Drug Discovery (ARDD) meeting, held online on the 1st to 4th of September 2020. The meeting covered topics related to new methodologies to study aging, knowledge about basic mechanisms of longevity, latest interventional strategies to target the aging process as well as discussions about the impact of aging research on society and economy. More than 2000 participants and 65 speakers joined the meeting and we already look forward to an even larger meeting next year. Please mark your calendars for the 8th ARDD meeting that is scheduled for the 31st of August to 3rd of September, 2021, at Columbia University, USA.

Molecular Chaperones and Proteolytic Machineries Regulate Protein Homeostasis In Aging Cells

Throughout their life cycles, cells are subject to a variety of stresses that lead to a compromise between cell death and survival. Survival is partially provided by the cell proteostasis network, which consists of molecular chaperones, a ubiquitin-proteasome system of degradation and autophagy. The cooperation of these systems impacts the correct function of protein synthesis/modification/transport machinery starting from the adaption of nascent polypeptides to cellular overcrowding until the utilization of damaged or needless proteins. Eventually, aging cells, in parallel to the accumulation of flawed proteins, gradually lose their proteostasis mechanisms, and this loss leads to the degeneration of large cellular masses and to number of age-associated pathologies and ultimately death. In this review, we describe the function of proteostasis mechanisms with an emphasis on the possible associations between them.