Increased cell-to-cell variation in gene expression in ageing mouse heart

Somatic mutations in aging and disease

Time always leaves its mark, and our genome is no exception. Mutations in the genome of somatic cells were first hypothesized to be the cause of aging in the 1950s, shortly after the molecular structure of DNA had been described. Somatic mutation theories of aging are based on the fact that mutations in DNA as the ultimate template for all cellular functions are irreversible. However, it took until the 1990s to develop the methods to test if DNA mutations accumulate with age in different organs and tissues and estimate the severity of the problem. By now, numerous studies have documented the accumulation of somatic mutations with age in normal cells and tissues of mice, humans, and other animals, showing clock-like mutational signatures that provide information on the underlying causes of the mutations. In this review, we will first briefly discuss the recent advances in next-generation sequencing that now allow quantitative analysis of somatic mutations. Second, we will provide evidence that the mutation rate differs between cell types, with a focus on differences between germline and somatic mutation rate. Third, we will discuss somatic mutational signatures as measures of aging, environmental exposure, and activities of DNA repair processes. Fourth, we will explain the concept of clonally amplified somatic mutations, with a focus on clonal hematopoiesis. Fifth, we will briefly discuss somatic mutations in the transcriptome and in our other genome, i.e., the genome of mitochondria. We will end with a brief discussion of a possible causal contribution of somatic mutations to the aging process.

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.

Gene regulatory networks in disease and ageing

The precise control of gene expression is required for the maintenance of cellular homeostasis and proper cellular function, and the declining control of gene expression with age is considered a major contributor to age-associated changes in cellular physiology and disease. The coordination of gene expression can be represented through models of the molecular interactions that govern gene expression levels, so-called gene regulatory networks. Gene regulatory networks can represent interactions that occur through signal transduction, those that involve regulatory transcription factors, or statistical models of gene-gene relationships based on the premise that certain sets of genes tend to be coexpressed across a range of conditions and cell types. Advances in experimental and computational technologies have enabled the inference of these networks on an unprecedented scale and at unprecedented precision. Here, we delineate different types of gene regulatory networks and their cell-biological interpretation. We describe methods for inferring such networks from large-scale, multi-omics datasets and present applications that have aided our understanding of cellular ageing and disease mechanisms.

Six drivers of aging identified among genes differentially expressed with age

Many studies have compared gene expression in young and old samples to gain insights on aging, the primary risk factor for most major chronic diseases. However, these studies only describe associations, failing to distinguish drivers of aging from compensatory geroprotective responses and incidental downstream effects. Here, we introduce a workflow to characterize the causal effects of differentially expressed genes on lifespan. First, we performed a meta-analysis of 25 gene expression datasets comprising samples of various tissues from healthy, untreated adult mammals (humans, dogs, and rodents) at two distinct ages. We ranked each gene according to the number of distinct datasets in which the gene was differentially expressed with age in a consistent direction. The top age-upregulated genes were TMEM176A, EFEMP1, CP, and HLA-A; the top age-downregulated genes were CA4, SIAH, SPARC, and UQCR10. Second, the effects of the top ranked genes on lifespan were measured by applying post-developmental RNA interference of the corresponding ortholog in the nematode C. elegans (two trials, with roughly 100 animals per genotype per trial). Out of 10 age-upregulated and 9 age-downregulated genes that were tested, two age-upregulated genes (csp-3/CASP1 and spch-2/RSRC1) and four age-downregulated genes (C42C1.8/DIRC2, ost-1/SPARC, fzy-1/CDC20, and cah-3/CA4) produced significant and reproducible lifespan extension. Notably, the data do not suggest that the direction of differential expression with age is predictive of the effect on lifespan. Our study provides novel insight into the relationship between differential gene expression and aging phenotypes, pilots an unbiased workflow that can be easily repeated and expanded, and pinpoints six genes with evolutionarily conserved, causal roles in the aging process for further study.

Histone deacetylase Hos2 regulates protein expression noise by potentially modulating the protein translation machinery

Non-genetic variations derived from expression noise at transcript or protein levels can result in cell-to-cell heterogeneity within an isogenic population. Although cells have developed strategies to reduce noise in some cellular functions, this heterogeneity can also facilitate varying levels of regulation and provide evolutionary benefits in specific environments. Despite several general characteristics of cellular noise having been revealed, the detailed molecular pathways underlying noise regulation remain elusive. Here, we established a dual-fluorescent reporter system in Saccharomyces cerevisiae and performed experimental evolution to search for mutations that increase expression noise. By analyzing evolved cells using bulk segregant analysis coupled with whole-genome sequencing, we identified the histone deacetylase Hos2 as a negative noise regulator. A hos2 mutant down-regulated multiple ribosomal protein genes and exhibited partially compromised protein translation, indicating that Hos2 may regulate protein expression noise by modulating the translation machinery. Treating cells with translation inhibitors or introducing mutations into several Hos2-regulated ribosomal protein genes-RPS9A, RPS28B and RPL42A-enhanced protein expression noise. Our study provides an effective strategy for identifying noise regulators and also sheds light on how cells regulate non-genetic variation through protein translation.

Methylation entropy landscape of Chinese long-lived individuals reveals lower epigenetic noise related to human healthy aging

The transition from ordered to noisy is a significant epigenetic signature of aging and age-related disease. As a paradigm of healthy human aging and longevity, long-lived individuals (LLI, >90 years old) may possess characteristic strategies in coping with the disordered epigenetic regulation. In this study, we constructed high-resolution blood epigenetic noise landscapes for this cohort by a methylation entropy (ME) method using whole genome bisulfite sequencing (WGBS). Although a universal increase in global ME occurred with chronological age in general control samples, this trend was suppressed in LLIs. Importantly, we identified 38,923 genomic regions with LLI-specific lower ME (LLI-specific lower entropy regions, for short, LLI-specific LERs). These regions were overrepresented in promoters, which likely function in transcriptional noise suppression. Genes associated with LLI-specific LERs have a considerable impact on SNP-based heritability of some aging-related disorders (e.g., asthma and stroke). Furthermore, neutrophil was identified as the primary cell type sustaining LLI-specific LERs. Our results highlight the stability of epigenetic order in promoters of genes involved with aging and age-related disorders within LLI epigenomes. This unique epigenetic feature reveals a previously unknown role of epigenetic order maintenance in specific genomic regions of LLIs, which helps open a new avenue on the epigenetic regulation mechanism in human healthy aging and longevity.

Living in a noisy world-origins of gene expression noise and its impact on cellular decision-making

The expression level of a gene can vary between genetically identical cells under the same environmental condition-a phenomenon referred to as gene expression noise. Several studies have now elucidated a central role of transcription factors in the generation of expression noise. Transcription factors, as the key components of gene regulatory networks, drive many important cellular decisions in response to cellular and environmental signals. Therefore, a very relevant question is how expression noise impacts gene regulation and influences cellular decision-making. In this Review, we summarize the current understanding of the molecular origins of expression noise, highlighting the role of transcription factors in this process, and discuss the ways in which noise can influence cellular decision-making. As advances in single-cell technologies open new avenues for studying expression noise as well as gene regulatory circuits, a better understanding of the influence of noise on cellular decisions will have important implications for many biological processes.

Aging clocks based on accumulating stochastic variation

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

Molecular mechanisms of aging and anti-aging strategies

Aging is a complex and multifaceted process involving a variety of interrelated molecular mechanisms and cellular systems. Phenotypically, the biological aging process is accompanied by a gradual loss of cellular function and the systemic deterioration of multiple tissues, resulting in susceptibility to aging-related diseases. Emerging evidence suggests that aging is closely associated with telomere attrition, DNA damage, mitochondrial dysfunction, loss of nicotinamide adenine dinucleotide levels, impaired macro-autophagy, stem cell exhaustion, inflammation, loss of protein balance, deregulated nutrient sensing, altered intercellular communication, and dysbiosis. These age-related changes may be alleviated by intervention strategies, such as calorie restriction, improved sleep quality, enhanced physical activity, and targeted longevity genes. In this review, we summarise the key historical progress in the exploration of important causes of aging and anti-aging strategies in recent decades, which provides a basis for further understanding of the reversibility of aging phenotypes, the application prospect of synthetic biotechnology in anti-aging therapy is also prospected.

Reduction in metabolic noise reveals rejuvenation following transient severe caloric restriction

Among land vertebrates, the laying hen stands out due to its great reproductive efficiency: producing an egg daily all year long. This production rate makes the laying hen a special model animal to study the general process of reproduction and aging. One unique aspect of hens is their ability to undergo reproductive plasticity and to rejuvenate their reproductive tract during molting, a standard industrial feed restriction protocol for transiently pausing reproduction, followed by improved laying efficiency almost to peak production. Here we use longitudinal metabolomics, immunology, and physiological assays to show that molting promotes reproduction, compresses morbidity, and restores youthfulness when applied to old hens. We identified circulating metabolic biomarkers that quantitatively predict the reproduction and age of individuals. Lastly, we introduce metabolic noise, a robust, unitless, and quantifiable measure for heterogeneity of the complete metabolome as a general marker that can indicate the rate of aging of a population. Indeed, metabolic noise increased with age in control hens, whereas molted hens exhibited reduced noise following molting, indicating systemic rejuvenation. Our results suggest that metabolic noise can be used as a quick and universal proxy for assessing successful aging treatments, accelerating the timeline for drug development.

Application of a mathematical model to clarify the statistical characteristics of a pan-tissue DNA methylation clock

DNA methylation clocks estimate biological age based on DNA methylation profiles. This study developed a mathematical model to describe DNA methylation aging and the establishment of a pan-tissue DNA methylation clock. The model simulates the aging dynamics of DNA methylation profiles based on passive demethylation as well as the process of cross-sectional bulk data acquisition. As a result, this study identified two conditions under which the pan-tissue DNA methylation clock can successfully predict biological age: one condition is that the target tissues are sufficiently well represented in the training dataset, and the other condition is that the target sample contains cell subsets that are common among different tissues. When either of these conditions is met, the clock performs well. It is also suggested that the epigenetic age of all samples in the target tissue tends to be either over or underestimated when biological age prediction fails. The model can reveal the statistical characteristics of DNA methylation clocks.

Subcellular structure, heterogeneity, and plasticity of senescent cells

Cellular senescence is a state of permanent growth arrest. It can be triggered by telomere shortening (replicative senescence) or prematurely induced by stresses such as DNA damage, oncogene overactivation, loss of tumor suppressor genes, oxidative stress, tissue factors, and others. Advances in techniques and experimental designs have provided new evidence about the biology of senescent cells (SnCs) and their importance in human health and disease. This review aims to describe the main aspects of SnCs phenotype focusing on alterations in subcellular compartments like plasma membrane, cytoskeleton, organelles, and nuclei. We also discuss the heterogeneity, dynamics, and plasticity of SnCs' phenotype, including the SASP, and pro-survival mechanisms. We advance on the multiple layers of phenotypic heterogeneity of SnCs, such as the heterogeneity between inducers, tissues and within a population of SnCs, discussing the relevance of these aspects to human health and disease. We also raise the main challenges as well alternatives to overcome them. Ultimately, we present open questions and perspectives in understanding the phenotype of SnCs from the perspective of basic and applied questions.

Single-worm quantitative proteomics reveals aging heterogeneity in isogenic Caenorhabditis elegans

The heterogeneity of aging has been investigated at cellular and organic levels in the mouse model and human, but the exploration of aging heterogeneity at whole-organism level is lacking. C. elegans is an ideal model organism for studying this question as they are self-fertilized and cultured in the same chamber. Despite the tremendous progress made in single-cell proteomic analysis, there is few single-worm proteomics studies about aging. Here, we apply single-worm quantitative mass spectrometry to quantify the heterogenous proteomic changes during aging across individuals, a total of 3524 proteins from 157 C. eleagns individuals were quantified. A reconstructed C. elegans aging trajectory and proteomic landscape of fast-aging individuals were used to analyze the heterogeneity of C. elegans aging. We characterized inter-individual proteomic variation during aging and revealed contributing factors that distinguish fast-aging individuals from their siblings.

Genome Instability and DNA Repair in Somatic and Reproductive Aging

Genetic material is constantly subjected to genotoxic insults and is critically dependent on DNA repair. Genome maintenance mechanisms differ in somatic and germ cells as the soma only requires maintenance during an individual's lifespan, while the germline indefinitely perpetuates its genetic information. DNA lesions are recognized and repaired by mechanistically highly diverse repair machineries. The DNA damage response impinges on a vast array of homeostatic processes and can ultimately result in cell fate changes such as apoptosis or cellular senescence. DNA damage causally contributes to the aging process and aging-associated diseases, most prominently cancer. By causing mutations, DNA damage in germ cells can lead to genetic diseases and impact the evolutionary trajectory of a species. The mechanisms ensuring tight control of germline DNA repair could be highly instructive in defining strategies for improved somatic DNA repair. They may provide future interventions to maintain health and prevent disease during aging.

FOXO transcription factors as mediators of stress adaptation

The forkhead box protein O (FOXO, consisting of FOXO1, FOXO3, FOXO4 and FOXO6) transcription factors are the mammalian orthologues of Caenorhabditis elegans DAF-16, which gained notoriety for its capability to double lifespan in the absence of daf-2 (the gene encoding the worm insulin receptor homologue). Since then, research has provided many mechanistic details on FOXO regulation and FOXO activity. Furthermore, conditional knockout experiments have provided a wealth of data as to how FOXOs control development and homeostasis at the organ and organism levels. The lifespan-extending capabilities of DAF-16/FOXO are highly correlated with their ability to induce stress response pathways. Exogenous and endogenous stress, such as cellular redox stress, are considered the main drivers of the functional decline that characterizes ageing. Functional decline often manifests as disease, and decrease in FOXO activity indeed negatively impacts on major age-related diseases such as cancer and diabetes. In this context, the main function of FOXOs is considered to preserve cellular and organismal homeostasis, through regulation of stress response pathways. Paradoxically, the same FOXO-mediated responses can also aid the survival of dysfunctional cells once these eventually emerge. This general property to control stress responses may underlie the complex and less-evident roles of FOXOs in human lifespan as opposed to model organisms such as C. elegans.

Cellular age explains variation in age-related cell-to-cell transcriptome variability

Organs and tissues age at different rates within a single individual. Such asynchrony in aging has been widely observed at multiple levels, from functional hallmarks, such as anatomical structures and physiological processes, to molecular endophenotypes, such as the transcriptome and metabolome. However, we lack a conceptual framework to understand why some components age faster than others. Just as demographic models explain why aging evolves, here we test the hypothesis that demographic differences among cell types, determined by cell-specific differences in turnover rate, can explain why the transcriptome shows signs of aging in some cell types but not others. Through analysis of mouse single-cell transcriptome data across diverse tissues and ages, we find that cellular age explains a large proportion of the variation in the age-related increase in transcriptome variance. We further show that long-lived cells are characterized by relatively high expression of genes associated with proteostasis and that the transcriptome of long-lived cells shows greater evolutionary constraint than short-lived cells. In contrast, in short-lived cell types, the transcriptome is enriched for genes associated with DNA repair. Based on these observations, we develop a novel heuristic model that explains how and why aging rates differ among cell types.

Spatial and single-cell profiling of the metabolome, transcriptome and epigenome of the aging mouse liver

Tissues within an organism and even cell types within a tissue can age with different velocities. However, it is unclear whether cells of one type experience different aging trajectories within a tissue depending on their spatial location. Here, we used spatial transcriptomics in combination with single-cell ATAC-seq and RNA-seq, lipidomics and functional assays to address how cells in the male murine liver are affected by age-related changes in the microenvironment. Integration of the datasets revealed zonation-specific and age-related changes in metabolic states, the epigenome and transcriptome. The epigenome changed in a zonation-dependent manner and functionally, periportal hepatocytes were characterized by decreased mitochondrial fitness, whereas pericentral hepatocytes accumulated large lipid droplets. Together, we provide evidence that changing microenvironments within a tissue exert strong influences on their resident cells that can shape epigenetic, metabolic and phenotypic outputs.

Hallmarks of cardiovascular ageing

Normal circulatory function is a key determinant of disease-free life expectancy (healthspan). Indeed, pathologies affecting the cardiovascular system, which are growing in prevalence, are the leading cause of global morbidity, disability and mortality, whereas the maintenance of cardiovascular health is necessary to promote both organismal healthspan and lifespan. Therefore, cardiovascular ageing might precede or even underlie body-wide, age-related health deterioration. In this Review, we posit that eight molecular hallmarks are common denominators in cardiovascular ageing, namely disabled macroautophagy, loss of proteostasis, genomic instability (in particular, clonal haematopoiesis of indeterminate potential), epigenetic alterations, mitochondrial dysfunction, cell senescence, dysregulated neurohormonal signalling and inflammation. We also propose a hierarchical order that distinguishes primary (upstream) from antagonistic and integrative (downstream) hallmarks of cardiovascular ageing. Finally, we discuss how targeting each of the eight hallmarks might be therapeutically exploited to attenuate residual cardiovascular risk in older individuals.

Rh flow cytometry: An updated methodology for D antigen density applied to weak D types 164 and 165

BACKGROUND

An original methodology for determining the D antigen density on red cells was published in 2000 and has been applied in many publications since. This flow cytometry-based assay remained largely unrevised utilizing monoclonal anti-Ds that are not readily available anymore. We updated the methodology to quantify erythrocyte D antigen sites using microspheres and monoclonal anti-Ds that are commercially available today.

METHODS

The absolute D antigen density of a frozen standard CcDEe cell, drawn in 2003, a fresh blood donation from the same individual, drawn in 2022, and an internal control CcDEe cell, was quantified by flow cytometry using fluorescence-labeled microspheres. The internal control CcDEe cell was used in conjunction with 9 commercial anti-Ds to determine D antigen densities of 7 normal D, 4 partial D, and 11 weak D type samples, including 2 novel alleles.

RESULTS

The reproducibility of the updated assay was evaluated with red cells of published D antigen densities. The current results matched the known ones closely. The new weak D types 164 and 165 carried 4500 and 1505 D antigens/red cell, respectively. The absolute D antigen density decreased from 27,231 to 26,037 in an individual over 19 years.

DISCUSSION

The updated assay gave highly reproducible results for the D antigen densities of Rh phenotypes. Readily available anti-Ds allowed for the determination of the D antigen densities of 7 weak D types. The assay is suitable to evaluate the effects of distinct amino acid substitutions on the RhD phenotype.

Smurfness-based two-phase model of ageing helps deconvolve the ageing transcriptional signature

Ageing is characterised at the molecular level by six transcriptional 'hallmarks of ageing', that are commonly described as progressively affected as time passes. By contrast, the 'Smurf' assay separates high-and-constant-mortality risk individuals from healthy, zero-mortality risk individuals, based on increased intestinal permeability. Performing whole body total RNA sequencing, we found that Smurfness distinguishes transcriptional changes associated with chronological age from those associated with biological age. We show that transcriptional heterogeneity increases with chronological age in non-Smurf individuals preceding the other five hallmarks of ageing that are specifically associated with the Smurf state. Using this approach, we also devise targeted pro-longevity genetic interventions delaying entry in the Smurf state. We anticipate that increased attention to the evolutionary conserved Smurf phenotype will bring about significant advances in our understanding of the mechanisms of ageing.

Measuring cell-to-cell expression variability in single-cell RNA-sequencing data: a comparative analysis and applications to B cell aging

BACKGROUND

Single-cell RNA-sequencing (scRNA-seq) technologies enable the capture of gene expression heterogeneity and consequently facilitate the study of cell-to-cell variability at the cell type level. Although different methods have been proposed to quantify cell-to-cell variability, it is unclear what the optimal statistical approach is, especially in light of challenging data structures that are unique to scRNA-seq data like zero inflation.

RESULTS

We systematically evaluate the performance of 14 different variability metrics that are commonly applied to transcriptomic data for measuring cell-to-cell variability. Leveraging simulations and real datasets, we benchmark the metric performance based on data-specific features, sparsity and sequencing platform, biological properties, and the ability to recapitulate true levels of biological variability based on known gene sets. Next, we use scran, the metric with the strongest all-round performance, to investigate changes in cell-to-cell variability that occur during B cell differentiation and the aging processes. The analysis of primary cell types from hematopoietic stem cells (HSCs) and B lymphopoiesis reveals unique gene signatures with consistent patterns of variable and stable expression profiles during B cell differentiation which highlights the significance of these methods. Identifying differentially variable genes between young and old cells elucidates the regulatory changes that may be overlooked by solely focusing on mean expression changes and we investigate this in the context of regulatory networks.

CONCLUSIONS

We highlight the importance of capturing cell-to-cell gene expression variability in a complex biological process like differentiation and aging and emphasize the value of these findings at the level of individual cell types.

Single-cell metabolic profiling reveals subgroups of primary human hepatocytes with heterogeneous responses to drug challenge

BACKGROUND

Xenobiotics are primarily metabolized by hepatocytes in the liver, and primary human hepatocytes are the gold standard model for the assessment of drug efficacy, safety, and toxicity in the early phases of drug development. Recent advances in single-cell genomics demonstrate liver zonation and ploidy as main drivers of cellular heterogeneity. However, little is known about the impact of hepatocyte specialization on liver function upon metabolic challenge, including hepatic metabolism, detoxification, and protein synthesis.

RESULTS

Here, we investigate the metabolic capacity of individual human hepatocytes in vitro. We assess how chronic accumulation of lipids enhances cellular heterogeneity and impairs the metabolisms of drugs. Using a phenotyping five-probe cocktail, we identify four functional subgroups of hepatocytes responding differently to drug challenge and fatty acid accumulation. These four subgroups display differential gene expression profiles upon cocktail treatment and xenobiotic metabolism-related specialization. Notably, intracellular fat accumulation leads to increased transcriptional variability and diminishes the drug-related metabolic capacity of hepatocytes.

CONCLUSIONS

Our results demonstrate that, upon a metabolic challenge such as exposure to drugs or intracellular fat accumulation, hepatocyte subgroups display different and heterogeneous transcriptional responses.

Reappraisal of the Concept of Accelerated Aging in Neurodegeneration and Beyond

BACKGROUND

Genetic and epigenetic changes, oxidative stress and inflammation influence the rate of aging, which diseases, lifestyle and environmental factors can further accelerate. In accelerated aging (AA), the biological age exceeds the chronological age.

OBJECTIVE

The objective of this study is to reappraise the AA concept critically, considering its weaknesses and limitations.

METHODS

We reviewed more than 300 recent articles dealing with the physiology of brain aging and neurodegeneration pathophysiology.

RESULTS

(1) Application of the AA concept to individual organs outside the brain is challenging as organs of different systems age at different rates. (2) There is a need to consider the deceleration of aging due to the potential use of the individual structure-functional reserves. The latter can be restored by pharmacological and/or cognitive therapy, environment, etc. (3) The AA concept lacks both standardised terminology and methodology. (4) Changes in specific molecular biomarkers (MBM) reflect aging-related processes; however, numerous MBM candidates should be validated to consolidate the AA theory. (5) The exact nature of many potential causal factors, biological outcomes and interactions between the former and the latter remain largely unclear.

CONCLUSIONS

Although AA is commonly recognised as a perspective theory, it still suffers from a number of gaps and limitations that assume the necessity for an updated AA concept.

Serum Response Factor Reduces Gene Expression Noise and Confers Cell State Stability

The role of serum response factor (Srf), a central mediator of actin dynamics and mechanical signaling, in cell identity regulation is debated to be either a stabilizer or a destabilizer. We investigated the role of Srf in cell fate stability using mouse pluripotent stem cells. Despite the fact that serum-containing cultures yield heterogeneous gene expression, deletion of Srf in mouse pluripotent stem cells leads to further exacerbated cell state heterogeneity. The exaggerated heterogeneity is detectible not only as increased lineage priming but also as the developmentally earlier 2C-like cell state. Thus, pluripotent cells explore more variety of cellular states in both directions of development surrounding naïve pluripotency, a behavior that is constrained by Srf. These results support that Srf functions as a cell state stabilizer, providing rationale for its functional modulation in cell fate intervention and engineering.

IFNγ-Stat1 axis drives aging-associated loss of intestinal tissue homeostasis and regeneration

The influence of aging on intestinal stem cells and their niche can explain underlying causes for perturbation in their function observed during aging. Molecular mechanisms for such a decrease in the functionality of intestinal stem cells during aging remain largely undetermined. Using transcriptome-wide approaches, our study demonstrates that aging intestinal stem cells strongly upregulate antigen presenting pathway genes and over-express secretory lineage marker genes resulting in lineage skewed differentiation into the secretory lineage and strong upregulation of MHC class II antigens in the aged intestinal epithelium. Mechanistically, we identified an increase in proinflammatory cells in the lamina propria as the main source of elevated interferon gamma (IFNγ) in the aged intestine, that leads to the induction of Stat1 activity in intestinal stem cells thus priming the aberrant differentiation and elevated antigen presentation in epithelial cells. Of note, systemic inhibition of IFNγ-signaling completely reverses these aging phenotypes and reinstalls regenerative capacity of the aged intestinal epithelium.

clrDV: a differential variability test for RNA-Seq data based on the skew-normal distribution

Background

Pathological conditions may result in certain genes having expression variance that differs markedly from that of the control. Finding such genes from gene expression data can provide invaluable candidates for therapeutic intervention. Under the dominant paradigm for modeling RNA-Seq gene counts using the negative binomial model, tests of differential variability are challenging to develop, owing to dependence of the variance on the mean.

Methods

Here, we describe clrDV, a statistical method for detecting genes that show differential variability between two populations. We present the skew-normal distribution for modeling gene-wise null distribution of centered log-ratio transformation of compositional RNA-seq data.

Results

Simulation results show that clrDV has false discovery rate and probability of Type II error that are on par with or superior to existing methodologies. In addition, its run time is faster than its closest competitors, and remains relatively constant for increasing sample size per group. Analysis of a large neurodegenerative disease RNA-Seq dataset using clrDV successfully recovers multiple gene candidates that have been reported to be associated with Alzheimer's disease.

Differential variability analysis of single-cell gene expression data

The advent of single-cell RNA sequencing (scRNA-seq) technologies has enabled gene expression profiling at the single-cell resolution, thereby enabling the quantification and comparison of transcriptional variability among individual cells. Although alterations in transcriptional variability have been observed in various biological states, statistical methods for quantifying and testing differential variability between groups of cells are still lacking. To identify the best practices in differential variability analysis of single-cell gene expression data, we propose and compare 12 statistical pipelines using different combinations of methods for normalization, feature selection, dimensionality reduction and variability calculation. Using high-quality synthetic scRNA-seq datasets, we benchmarked the proposed pipelines and found that the most powerful and accurate pipeline performs simple library size normalization, retains all genes in analysis and uses denSNE-based distances to cluster medoids as the variability measure. By applying this pipeline to scRNA-seq datasets of COVID-19 and autism patients, we have identified cellular variability changes between patients with different severity status or between patients and healthy controls.

Genomic Instability and Epigenetic Changes during Aging

Aging is considered the deterioration of physiological functions along with an increased mortality rate. This scientific review focuses on the central importance of genomic instability during the aging process, encompassing a range of cellular and molecular changes that occur with advancing age. In particular, this revision addresses the genetic and epigenetic alterations that contribute to genomic instability, such as telomere shortening, DNA damage accumulation, and decreased DNA repair capacity. Furthermore, the review explores the epigenetic changes that occur with aging, including modifications to histones, DNA methylation patterns, and the role of non-coding RNAs. Finally, the review discusses the organization of chromatin and its contribution to genomic instability, including heterochromatin loss, chromatin remodeling, and changes in nucleosome and histone abundance. In conclusion, this review highlights the fundamental role that genomic instability plays in the aging process and underscores the need for continued research into these complex biological mechanisms.

The epithelial-mesenchymal plasticity landscape: principles of design and mechanisms of regulation

Epithelial-mesenchymal plasticity (EMP) enables cells to interconvert between several states across the epithelial-mesenchymal landscape, thereby acquiring hybrid epithelial/mesenchymal phenotypic features. This plasticity is crucial for embryonic development and wound healing, but also underlies the acquisition of several malignant traits during cancer progression. Recent research using systems biology and single-cell profiling methods has provided novel insights into the main forces that shape EMP, which include the microenvironment, lineage specification and cell identity, and the genome. Additionally, key roles have emerged for hysteresis (cell memory) and cellular noise, which can drive stochastic transitions between cell states. Here, we review these forces and the distinct but interwoven layers of regulatory control that stabilize EMP states or facilitate epithelial-mesenchymal transitions (EMTs) and discuss the therapeutic potential of manipulating the EMP landscape.

Individual cell types in C. elegans age differently and activate distinct cell-protective responses

Aging is characterized by a global decline in physiological function. However, by constructing a complete single-cell gene expression atlas, we find that Caenorhabditis elegans aging is not random in nature but instead is characterized by coordinated changes in functionally related metabolic, proteostasis, and stress-response genes in a cell-type-specific fashion, with downregulation of energy metabolism being the only nearly universal change. Similarly, the rates at which cells age differ significantly between cell types. In some cell types, aging is characterized by an increase in cell-to-cell variance, whereas in others, variance actually decreases. Remarkably, multiple resilience-enhancing transcription factors known to extend lifespan are activated across many cell types with age; we discovered new longevity candidates, such as GEI-3, among these. Together, our findings suggest that cells do not age passively but instead react strongly, and individualistically, to events that occur during aging. This atlas can be queried through a public interface.

Methylation across the central dogma in health and diseases: new therapeutic strategies

The proper transfer of genetic information from DNA to RNA to protein is essential for cell-fate control, development, and health. Methylation of DNA, RNAs, histones, and non-histone proteins is a reversible post-synthesis modification that finetunes gene expression and function in diverse physiological processes. Aberrant methylation caused by genetic mutations or environmental stimuli promotes various diseases and accelerates aging, necessitating the development of therapies to correct the disease-driver methylation imbalance. In this Review, we summarize the operating system of methylation across the central dogma, which includes writers, erasers, readers, and reader-independent outputs. We then discuss how dysregulation of the system contributes to neurological disorders, cancer, and aging. Current small-molecule compounds that target the modifiers show modest success in certain cancers. The methylome-wide action and lack of specificity lead to undesirable biological effects and cytotoxicity, limiting their therapeutic application, especially for diseases with a monogenic cause or different directions of methylation changes. Emerging tools capable of site-specific methylation manipulation hold great promise to solve this dilemma. With the refinement of delivery vehicles, these new tools are well positioned to advance the basic research and clinical translation of the methylation field.

Out-of-equilibrium gene expression fluctuations in the presence of extrinsic noise

Cell-to-cell variability in protein concentrations is strongly affected by extrinsic noise, especially for highly expressed genes. Extrinsic noise can be due to fluctuations of several possible cellular factors connected to cell physiology and to the level of key enzymes in the expression process. However, how to identify the predominant sources of extrinsic noise in a biological system is still an open question. This work considers a general stochastic model of gene expression with extrinsic noise represented as fluctuations of the different model rates, and focuses on the out-of-equilibrium expression dynamics. Combining analytical calculations with stochastic simulations, we characterize how extrinsic noise shapes the protein variability during gene activation or inactivation, depending on the prevailing source of extrinsic variability, on its intensity and timescale. In particular, we show that qualitatively different noise profiles can be identified depending on which are the fluctuating parameters. This indicates an experimentally accessible way to pinpoint the dominant sources of extrinsic noise using time-coarse experiments.

Intrinsic and environmental basis of aging: A narrative review

Longevity has been a topic of interest since the beginnings of humanity, yet its aetiology and precise mechanisms remain to be elucidated. Aging is currently viewed as a physiological phenomenon characterized by the gradual degeneration of organic physiology and morphology due to the passage of time where both external and internal stimuli intervene. The influence of intrinsic factors, such as progressive telomere shortening, genome instability due to mutation buildup, the direct or indirect actions of age-related genes, and marked changes in epigenetic, metabolic, and mitochondrial patterns constitute a big part of its underlying endogenous mechanisms. On the other hand, several psychosocial and demographic factors, such as diet, physical activity, smoking, and drinking habits, may have an even more significant impact on shaping the aging process. Consequentially, implementing dietary and exercise patterns has been proposed as the most viable alternative strategy for attenuating the most typical degenerative aging changes, thus increasing the likelihood of prolonging lifespan and achieving successful aging.

Transcriptomic reprogramming for neuronal age reversal

Aging is a progressive multifaceted functional decline of a biological system. Chronic age-related conditions such as neurodegenerative diseases are leading causes of death worldwide, and they are becoming a pressing problem for our society. To address this global challenge, there is a need for novel, safe, and effective rejuvenation therapies aimed at reversing age-related phenotypes and improving human health. With gene expression being a key determinant of cell identity and function, and in light of recent studies reporting rejuvenation effects through genetic perturbations, we propose an age reversal strategy focused on reprogramming the cell transcriptome to a youthful state. To this end, we suggest using transcriptomic data from primary human cells to predict rejuvenation targets and develop high-throughput aging assays, which can be used in large perturbation screens. We propose neural cells as particularly relevant targets for rejuvenation due to substantial impact of neurodegeneration on human frailty. Of all cell types in the brain, we argue that glutamatergic neurons, neuronal stem cells, and oligodendrocytes represent the most impactful and tractable targets. Lastly, we provide experimental designs for anti-aging reprogramming screens that will likely enable the development of neuronal age reversal therapies, which hold promise for dramatically improving human health.

Genomic Instability Evolutionary Footprints on Human Health: Driving Forces or Side Effects?

In this work, we propose a comprehensive perspective on genomic instability comprising not only the accumulation of mutations but also telomeric shortening, epigenetic alterations and other mechanisms that could contribute to genomic information conservation or corruption. First, we present mechanisms playing a role in genomic instability across the kingdoms of life. Then, we explore the impact of genomic instability on the human being across its evolutionary history and on present-day human health, with a particular focus on aging and complex disorders. Finally, we discuss the role of non-coding RNAs, highlighting future approaches for a better living and an expanded healthy lifespan.

DNA damage-induced stalling of transcription drives aging through gene expression imbalance

Age-related changes in gene expression have long been examined to understand the biology of aging. The hallmarks of aging are biological processes known to be associated with aging, but whether there is a unifying driver of these attributes, is not well understood. With the advent of technology over the last few years, it is quite clear that aging leads to global decline in transcription. In this Perspective, we highlight a new study in Nature Genetics that aimed to determine why global transcription rate reduces with age and how this phenomenon is the driver that interconnects multiple hallmarks of aging. This study recognizes that age-related accumulation of DNA damage, particularly transcription-blocking lesions, stalls RNA polymerase. This phenomenon affects longer genes leading to a gradual loss of transcription and skewing the transcriptome. In order to design a successful aging intervention, future work will be needed to test how some promising therapies in pre-clinical trials target affect transcriptional rate.

Spurious intragenic transcription is a feature of mammalian cellular senescence and tissue aging

Mammalian aging is characterized by the progressive loss of tissue function and increased risk for disease. Accumulation of senescent cells in aging tissues partly contributes to this decline, and targeted depletion of senescent cells in vivo ameliorates many age-related phenotypes. The fundamental molecular mechanisms responsible for the decline of cellular health and fitness during senescence and aging are largely unknown. In this study, we investigated whether chromatin-mediated loss of transcriptional fidelity, known to contribute to fitness and survival in yeast and worms, also occurs during human cellular senescence and mouse aging. Our findings reveal aberrant transcription initiation inside genes during senescence and aging that co-occurs with changes in the chromatin landscape. Interventions that alter these spurious transcripts have profound consequences on cellular health, primarily affecting intracellular signal transduction pathways. We propose that age-related spurious transcription promotes a noisy transcriptome and degradation of coherent transcriptional networks.

Rapid emergence of transcriptional heterogeneity upon molecular stress predisposes cells to two distinct states of senescence

Slowing aging can reduce the risk of chronic diseases. In particular, eliminating senescent cells is a promising approach to slow aging. Previous studies found that both cells from older animals and senescent cells have noisy gene expression. Here, we performed a large-scale single-cell RNA-sequencing time course to understand how transcriptional heterogeneity develops among senescent cells. We found that cells experiencing senescence-inducing oxidative stress rapidly adopt one of two major transcriptional states. One senescent cell state is associated with stress response, and the other is associated with tissue remodeling. We did not observe increased stochastic gene expression. This data is consistent with the idea that reproducible, limited, distinct, and coherent transcriptional states exist in senescent cell populations. These physiologically distinct senescent cell subtypes may each affect the aging process in unique ways and constitute a source of heterogeneity in aging.

Progress in Discovering Transcriptional Noise in Aging

Increasing stochasticity is a key feature in the aging process. At the molecular level, in addition to genome instability, a well-recognized hallmark of aging, cell-to-cell variation in gene expression was first identified in mouse hearts. With the technological breakthrough in single-cell RNA sequencing, most studies performed in recent years have demonstrated a positive correlation between cell-to-cell variation and age in human pancreatic cells, as well as mouse lymphocytes, lung cells, and muscle stem cells during senescence in vitro. This phenomenon is known as the "transcriptional noise" of aging. In addition to the increasing evidence in experimental observations, progress also has been made to better define transcriptional noise. Traditionally, transcriptional noise is measured using simple statistical measurements, such as the coefficient of variation, Fano factor, and correlation coefficient. Recently, multiple novel methods have been proposed, e.g., global coordination level analysis, to define transcriptional noise based on network analysis of gene-to-gene coordination. However, remaining challenges include a limited number of wet-lab observations, technical noise in single-cell RNA sequencing, and the lack of a standard and/or optimal data analytical measurement of transcriptional noise. Here, we review the recent technological progress, current knowledge, and challenges to better understand transcriptional noise in aging.

Genome-wide RNA polymerase stalling shapes the transcriptome during aging

Gene expression profiling has identified numerous processes altered in aging, but how these changes arise is largely unknown. Here we combined nascent RNA sequencing and RNA polymerase II chromatin immunoprecipitation followed by sequencing to elucidate the underlying mechanisms triggering gene expression changes in wild-type aged mice. We found that in 2-year-old liver, 40% of elongating RNA polymerases are stalled, lowering productive transcription and skewing transcriptional output in a gene-length-dependent fashion. We demonstrate that this transcriptional stress is caused by endogenous DNA damage and explains the majority of gene expression changes in aging in most mainly postmitotic organs, specifically affecting aging hallmark pathways such as nutrient sensing, autophagy, proteostasis, energy metabolism, immune function and cellular stress resilience. Age-related transcriptional stress is evolutionary conserved from nematodes to humans. Thus, accumulation of stochastic endogenous DNA damage during aging deteriorates basal transcription, which establishes the age-related transcriptome and causes dysfunction of key aging hallmark pathways, disclosing how DNA damage functionally underlies major aspects of normal aging.

Defining the age-dependent and tissue-specific circadian transcriptome in male mice

Cellular circadian clocks direct a daily transcriptional program that supports homeostasis and resilience. Emerging evidence has demonstrated age-associated changes in circadian functions. To define age-dependent changes at the systems level, we profile the circadian transcriptome in the hypothalamus, lung, heart, kidney, skeletal muscle, and adrenal gland in three age groups. We find age-dependent and tissue-specific clock output changes. Aging reduces the number of rhythmically expressed genes (REGs), indicative of weakened circadian control. REGs are enriched for the hallmarks of aging, adding another dimension to our understanding of aging. Analyzing differential gene expression within a tissue at four different times of day identifies distinct clusters of differentially expressed genes (DEGs). Increased variability of gene expression across the day is a common feature of aged tissues. This analysis extends the landscape for understanding aging and highlights the impact of aging on circadian clock function and temporal changes in gene expression.

Selective Destabilization of Transcripts by mRNA Decapping Regulates Oocyte Maturation and Innate Immunity Gene Expression during Ageing in C. elegans

Removal of the 5' cap structure of RNAs (termed decapping) is a pivotal event in the life of cytoplasmic mRNAs mainly catalyzed by a conserved holoenzyme, composed of the catalytic subunit DCP2 and its essential cofactor DCP1. While decapping was initially considered merely a step in the general 5'-3' mRNA decay, recent data suggest a great degree of selectivity that plays an active role in the post-transcriptional control of gene expression, and regulates multiple biological functions. Studies in Caenorhabditis elegans have shown that old age is accompanied by the accumulation of decapping factors in cytoplasmic RNA granules, and loss of decapping activity shortens the lifespan. However, the link between decapping and ageing remains elusive. Here, we present a comparative microarray study that was aimed to uncover the differences in the transcriptome of mid-aged dcap-1/DCP1 mutant and wild-type nematodes. Our data indicate that DCAP-1 mediates the silencing of spermatogenic genes during late oogenesis, and suppresses the aberrant uprise of immunity gene expression during ageing. The latter is achieved by destabilizing the mRNA that encodes the transcription factor PQM-1 and impairing its nuclear translocation. Failure to exert decapping-mediated control on PQM-1 has a negative impact on the lifespan, but mitigates the toxic effects of polyglutamine expression that are involved in human disease.

Single-cell transcriptomics of peripheral blood in the aging mouse

Compositional and transcriptional changes in the hematopoietic system have been used as biomarkers of immunosenescence and aging. Here, we use single-cell RNA-sequencing to study the aging peripheral blood in mice and characterize the changes in cell-type composition and transcriptional profiles associated with age. We identified 17 clusters from a total of 14,588 single cells. We detected a general upregulation of antigen processing and presentation and chemokine signaling pathways and a downregulation of genes involved in ribosome pathways with age. In old peripheral blood, we also observed an increased percentage of cells expressing senescence markers (Cdkn1a, and Cdkn2a). In addition, we detected a cluster of activated T cells exclusively found in old blood, with lower expression of Cd28 and higher expression of Bcl2 and Cdkn2a, suggesting that the cells are senescent and resistant to apoptosis.

AgeAnno: a knowledgebase of single-cell annotation of aging in human

Aging is a complex process that accompanied by molecular and cellular alterations. The identification of tissue-/cell type-specific biomarkers of aging and elucidation of the detailed biological mechanisms of aging-related genes at the single-cell level can help to understand the heterogeneous aging process and design targeted anti-aging therapeutics. Here, we built AgeAnno (https://relab.xidian.edu.cn/AgeAnno/#/), a knowledgebase of single cell annotation of aging in human, aiming to provide comprehensive characterizations for aging-related genes across diverse tissue-cell types in human by using single-cell RNA and ATAC sequencing data (scRNA and scATAC). The current version of AgeAnno houses 1 678 610 cells from 28 healthy tissue samples with ages ranging from 0 to 110 years. We collected 5580 aging-related genes from previous resources and performed dynamic functional annotations of the cellular context. For the scRNA data, we performed analyses include differential gene expression, gene variation coefficient, cell communication network, transcription factor (TF) regulatory network, and immune cell proportionc. AgeAnno also provides differential chromatin accessibility analysis, motif/TF enrichment and footprint analysis, and co-accessibility peak analysis for scATAC data. AgeAnno will be a unique resource to systematically characterize aging-related genes across diverse tissue-cell types in human, and it could facilitate antiaging and aging-related disease research.

Early cardiac aging linked to impaired stress-resistance and transcriptional control of stress response, quality control and mitochondrial pathways

Phenotypic and transcriptomic evidence of early cardiac aging, and associated mechanisms, were investigated in young to middle-aged male mice (C57Bl/6; ages 8, 16, 32, 48 wks). Left ventricular gene expression (profiled via Illumina MouseWG-6 BeadChips), contractile and coronary function, and stress-resistance were assessed in Langendorff perfused hearts under normoxic conditions and following ischemic insult (20 min global ischemia-45 min reperfusion; I-R). Baseline or normoxic contractile function was unaltered by age, while cardiac and coronary 'reserves' (during β-adrenoceptor stimulation; 1 μM isoproterenol) declined by 48 wks. Resistance to I-R injury fell from 16 to 32 wks. Age-dependent transcriptional changes In un-stressed hearts were limited to 104 genes (>1.3-fold; 0.05 FDR), supporting: up-regulated innate defenses (glutathione and xenobiotic metabolism, chemotaxis, interleukins) and catecholamine secretion; and down-regulated extracellular matrix (ECM), growth factor and survival (PI3K/Akt) signaling. In stressed (post-ischemic) myocardium, ∼15-times as many genes (1528) were age-dependent, grouped into 6 clusters (>1.3-fold change; 0.05 FDR): most changing from 16 wks (45 % up/44 % down), a further 5 % declining from 32 wks. Major age-dependent Biological Processes in I-R hearts reveal: declining ATP metabolism, oxidative phosphorylation, cardiac contraction and morphogenesis, phospholipid metabolism and calcineurin signaling; increasing proteolysis and negative control of MAPK; and mixed changes in nuclear transport and angiogenic genes. Pathway analysis supports reductions in: autophagy, stress response, ER protein processing, mRNA surveillance and ribosome/translation genes; with later falls in mitochondrial biogenesis, oxidative phosphorylation and proteasome genes in I-R hearts. Summarizing, early cardiac aging is evident from 16 to 32 wks in male mice, characterized by: declining cardiovascular reserve and stress-resistance, transcriptomic evidence of constitutive stress and altered catecholamine and survival/growth signaling in healthy hearts; and declining stress response, quality control, mitochondrial energy metabolism and cardiac modeling processes in stressed hearts. These very early changes, potentially key substrate for advanced aging, may inform approaches to healthy aging and cardioprotection in the adult heart.

Cell-type-specific aging clocks to quantify aging and rejuvenation in neurogenic regions of the brain

The diversity of cell types is a challenge for quantifying aging and its reversal. Here we develop 'aging clocks' based on single-cell transcriptomics to characterize cell-type-specific aging and rejuvenation. We generated single-cell transcriptomes from the subventricular zone neurogenic region of 28 mice, tiling ages from young to old. We trained single-cell-based regression models to predict chronological age and biological age (neural stem cell proliferation capacity). These aging clocks are generalizable to independent cohorts of mice, other regions of the brains, and other species. To determine if these aging clocks could quantify transcriptomic rejuvenation, we generated single-cell transcriptomic datasets of neurogenic regions for two interventions-heterochronic parabiosis and exercise. Aging clocks revealed that heterochronic parabiosis and exercise reverse transcriptomic aging in neurogenic regions, but in different ways. This study represents the first development of high-resolution aging clocks from single-cell transcriptomic data and demonstrates their application to quantify transcriptomic rejuvenation.

Advanced Maternal Age Differentially Affects Embryonic Tissues with the Most Severe Impact on the Developing Brain

Advanced maternal age (AMA) poses the single greatest risk to a successful pregnancy. Apart from the impact of AMA on oocyte fitness, aged female mice often display defects in normal placentation. Placental defects in turn are tightly correlated with brain and cardiovascular abnormalities. It therefore follows that placenta, brain and heart development may be particularly susceptible to the impact of AMA. In the current study, we compared global transcriptomes of placentas, brains, hearts, and facial prominences from mid-gestation mouse conceptuses developed in young control (7-13 wks) and aging (43-50 wks) females. We find that AMA increases transcriptional heterogeneity in all tissues, but particularly in fetal brain. Importantly, even overtly normally developed embryos from older females display dramatic expression changes in neurodevelopmental genes. These transcriptomic alterations in the brain are likely induced by defects in placental development. Using trophoblast stem cells (TSCs) as a model, we show that exposure to aging uterine stromal cell-conditioned medium interferes with normal TSC proliferation and causes precocious differentiation, recapitulating many of the defects observed in placentas from aged females. These data highlight the increased risk of AMA on reproductive outcome, with neurodevelopment being the most sensitive to such early perturbations and with potential for lifelong impact.

Telomeres, Telomerase and Cancer

Telomeres and telomerase play a crucial role in human aging and cancer. Three "drivers" of human aging can be identified. The developmental program encoded in DNA is the primary determinant of lifespan. Faithful execution of the developmental program requires stability of the (epi-)genome which is challenged throughout life by damage to DNA as well as epigenetic 'scars' from error-free DNA repair and stochastic errors made during the establishment and maintenance of the "epigenome". Over time (epi-)mutations accumulate, compromising cellular function and causing (pre-)malignant alterations. Damage to the genome and epigenome can be considered the second "driver" of aging. A third driver of the aging process, important to suppress tumors in long-lived animals, is caused by progressive loss of telomeric DNA. Telomere erosion protects against cancer early in life but limits cell renewal late in life, in agreement with the Antagonistic Pleiotropy theory on the evolutionary origin of aging. Malignant tumors arise when mutations and/or epimutations in cells (clock 2) corrupt the developmental program (clock 1) as well as tumor suppression by telomere erosion (clock 3). In cancer cells clock 3 is typically inactivated by loss of p53 as well as increased expression of telomerase. Taken together, aging in humans can be described by the ticking of three clocks: the clock that directs development, the accumulation of (epi-)mutations over time and the telomere clock that limits the number of cell divisions in normal stem and immune cells.

Epigenetic clock: A promising biomarker and practical tool in aging

As a complicated process, aging is characterized by various changes at the cellular, subcellular and nuclear levels, one of which is epigenetic aging. With increasing awareness of the critical role that epigenetic alternations play in aging, DNA methylation patterns have been employed as a measure of biological age, currently referred to as the epigenetic clock. This review provides a comprehensive overview of the epigenetic clock as a biomarker of aging and a useful tool to manage healthy aging. In this burgeoning scientific field, various kinds of epigenetic clocks continue to emerge, including Horvath's clock, Hannum's clock, DNA PhenoAge, and DNA GrimAge. We hereby present the most classic epigenetic clocks, as well as their differences. Correlations of epigenetic age with morbidity, mortality and other factors suggest the potential of epigenetic clocks for risk prediction and identification in the context of aging. In particular, we summarize studies on promising age-reversing interventions, with epigenetic clocks employed as a practical tool in the efficacy evaluation. We also discuss how the lack of higher-quality information poses a major challenge, and offer some suggestions to address existing obstacles. Hopefully, our review will help provide an appropriate understanding of the epigenetic clocks, thereby enabling novel insights into the aging process and how it can be manipulated to promote healthy aging.