Metformin decelerates aging clock in male monkeys.

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

Biomarkers of aging for the identification and evaluation of longevity interventions.

With the rapid expansion of aging biology research, the identification and evaluation of longevity interventions in humans have become key goals of this field. Biomarkers of aging are critically important tools in achieving these objectives over realistic time frames. However, the current lack of standards and consensus on the properties of a reliable aging biomarker hinders their further development and validation for clinical applications. Here, we advance a framework for the terminology and characterization of biomarkers of aging, including classification and potential clinical use cases. We discuss validation steps and highlight ongoing challenges as potential areas in need of future research. This framework sets the stage for the development of valid biomarkers of aging and their ultimate utilization in clinical trials and practice.

Transposon-triggered innate immune response confers cancer resistance to the blind mole rat.

Blind mole rats (BMRs) are small rodents, characterized by an exceptionally long lifespan (>21 years) and resistance to both spontaneous and induced tumorigenesis. Here we report that cancer resistance in the BMR is mediated by retrotransposable elements (RTEs). Cells and tissues of BMRs express very low levels of DNA methyltransferase 1. Following cell hyperplasia, the BMR genome DNA loses methylation, resulting in the activation of RTEs. Upregulated RTEs form cytoplasmic RNA-DNA hybrids, which activate the cGAS-STING pathway to induce cell death. Although this mechanism is enhanced in the BMR, we show that it functions in mice and humans. We propose that RTEs were co-opted to serve as tumor suppressors that monitor cell proliferation and are activated in premalignant cells to trigger cell death via activation of the innate immune response. Activation of RTEs is a double-edged sword, serving as a tumor suppressor but contributing to aging in late life via the induction of sterile inflammation.

Single-cell transcriptome analyses reveal signals to activate dormant neural stem cells.

The scarcity of tissue-specific stem cells and the complexity of their surrounding environment have made molecular characterization of these cells particularly challenging. Through single-cell transcriptome and weighted gene co-expression network analysis (WGCNA), we uncovered molecular properties of CD133(+)/GFAP(-) ependymal (E) cells in the adult mouse forebrain neurogenic zone. Surprisingly, prominent hub genes of the gene network unique to ependymal CD133(+)/GFAP(-) quiescent cells were enriched for immune-responsive genes, as well as genes encoding receptors for angiogenic factors. Administration of vascular endothelial growth factor (VEGF) activated CD133(+) ependymal neural stem cells (NSCs), lining not only the lateral but also the fourth ventricles and, together with basic fibroblast growth factor (bFGF), elicited subsequent neural lineage differentiation and migration. This study revealed the existence of dormant ependymal NSCs throughout the ventricular surface of the CNS, as well as signals abundant after injury for their activation.

Increased hyaluronan by naked mole-rat Has2 improves healthspan in mice.

Abundant high-molecular-mass hyaluronic acid (HMM-HA) contributes to cancer resistance and possibly to the longevity of the longest-lived rodent-the naked mole-rat1,2. To study whether the benefits of HMM-HA could be transferred to other animal species, we generated a transgenic mouse overexpressing naked mole-rat hyaluronic acid synthase 2 gene (nmrHas2). nmrHas2 mice showed an increase in hyaluronan levels in several tissues, and a lower incidence of spontaneous and induced cancer, extended lifespan and improved healthspan. The transcriptome signature of nmrHas2 mice shifted towards that of longer-lived species. The most notable change observed in nmrHas2 mice was attenuated inflammation across multiple tissues. HMM-HA reduced inflammation through several pathways, including a direct immunoregulatory effect on immune cells, protection from oxidative stress and improved gut barrier function during ageing. These beneficial effects were conferred by HMM-HA and were not specific to the nmrHas2 gene. These findings demonstrate that the longevity mechanism that evolved in the naked mole-rat can be exported to other species, and open new paths for using HMM-HA to improve lifespan and healthspan.

Making sense of the ageing methylome.

Over time, the human DNA methylation landscape accrues substantial damage, which has been associated with a broad range of age-related diseases, including cardiovascular disease and cancer. Various age-related DNA methylation changes have been described, including at the level of individual CpGs, such as differential and variable methylation, and at the level of the whole methylome, including entropy and correlation networks. Here, we review these changes in the ageing methylome as well as the statistical tools that can be used to quantify them. We detail the evidence linking DNA methylation to ageing phenotypes and the longevity strategies aimed at altering both DNA methylation patterns and machinery to extend healthspan and lifespan. Lastly, we discuss theories on the mechanistic causes of epigenetic ageing.

Integrative functional genomic analyses implicate specific molecular pathways and circuits in autism.

Genetic studies have identified dozens of autism spectrum disorder (ASD) susceptibility genes, raising two critical questions: (1) do these genetic loci converge on specific biological processes, and (2) where does the phenotypic specificity of ASD arise, given its genetic overlap with intellectual disability (ID)? To address this, we mapped ASD and ID risk genes onto coexpression networks representing developmental trajectories and transcriptional profiles representing fetal and adult cortical laminae. ASD genes tightly coalesce in modules that implicate distinct biological functions during human cortical development, including early transcriptional regulation and synaptic development. Bioinformatic analyses suggest that translational regulation by FMRP and transcriptional coregulation by common transcription factors connect these processes. At a circuit level, ASD genes are enriched in superficial cortical layers and glutamatergic projection neurons. Furthermore, we show that the patterns of ASD and ID risk genes are distinct, providing a biological framework for further investigating the pathophysiology of ASD.

Epigenome-wide meta-analysis of BMI in nine cohorts: Examining the utility of epigenetically predicted BMI.

This study sought to examine the association between DNA methylation and body mass index (BMI) and the potential of BMI-associated cytosine-phosphate-guanine (CpG) sites to provide information about metabolic health. We pooled summary statistics from six trans-ethnic epigenome-wide association studies (EWASs) of BMI representing nine cohorts (n = 17,034), replicated these findings in the Women's Health Initiative (WHI, n = 4,822), and developed an epigenetic prediction score of BMI. In the pooled EWASs, 1,265 CpG sites were associated with BMI (p < 1E-7) and 1,238 replicated in the WHI (FDR < 0.05). We performed several stratified analyses to examine whether these associations differed between individuals of European and African descent, as defined by self-reported race/ethnicity. We found that five CpG sites had a significant interaction with BMI by race/ethnicity. To examine the utility of the significant CpG sites in predicting BMI, we used elastic net regression to predict log-normalized BMI in the WHI (80% training/20% testing). This model found that 397 sites could explain 32% of the variance in BMI in the WHI test set. Individuals whose methylome-predicted BMI overestimated their BMI (high epigenetic BMI) had significantly higher glucose and triglycerides and lower HDL cholesterol and LDL cholesterol compared to accurately predicted BMI. Individuals whose methylome-predicted BMI underestimated their BMI (low epigenetic BMI) had significantly higher HDL cholesterol and lower glucose and triglycerides. This study confirmed 553 and identified 685 CpG sites associated with BMI. Participants with high epigenetic BMI had poorer metabolic health, suggesting that the overestimation may be driven in part by cardiometabolic derangements characteristic of metabolic syndrome.

AESurv: autoencoder survival analysis for accurate early prediction of coronary heart disease.

Coronary heart disease (CHD) is one of the leading causes of mortality and morbidity in the United States. Accurate time-to-event CHD prediction models with high-dimensional DNA methylation and clinical features may assist with early prediction and intervention strategies. We developed a state-of-the-art deep learning autoencoder survival analysis model (AESurv) to effectively analyze high-dimensional blood DNA methylation features and traditional clinical risk factors by learning low-dimensional representation of participants for time-to-event CHD prediction. We demonstrated the utility of our model in two cohort studies: the Strong Heart Study cohort (SHS), a prospective cohort studying cardiovascular disease and its risk factors among American Indians adults; the Women's Health Initiative (WHI), a prospective cohort study including randomized clinical trials and observational study to improve postmenopausal women's health with one of the main focuses on cardiovascular disease. Our AESurv model effectively learned participant representations in low-dimensional latent space and achieved better model performance (concordance index-C index of 0.864 ± 0.009 and time-to-event mean area under the receiver operating characteristic curve-AUROC of 0.905 ± 0.009) than other survival analysis models (Cox proportional hazard, Cox proportional hazard deep neural network survival analysis, random survival forest, and gradient boosting survival analysis models) in the SHS. We further validated the AESurv model in WHI and also achieved the best model performance. The AESurv model can be used for accurate CHD prediction and assist health care professionals and patients to perform early intervention strategies. We suggest using AESurv model for future time-to-event CHD prediction based on DNA methylation features.

Reprogramming to recover youthful epigenetic information and restore vision.

Ageing is a degenerative process that leads to tissue dysfunction and death. A proposed cause of ageing is the accumulation of epigenetic noise that disrupts gene expression patterns, leading to decreases in tissue function and regenerative capacity1-3. Changes to DNA methylation patterns over time form the basis of ageing clocks4, but whether older individuals retain the information needed to restore these patterns-and, if so, whether this could improve tissue function-is not known. Over time, the central nervous system (CNS) loses function and regenerative capacity5-7. Using the eye as a model CNS tissue, here we show that ectopic expression of Oct4 (also known as Pou5f1), Sox2 and Klf4 genes (OSK) in mouse retinal ganglion cells restores youthful DNA methylation patterns and transcriptomes, promotes axon regeneration after injury, and reverses vision loss in a mouse model of glaucoma and in aged mice. The beneficial effects of OSK-induced reprogramming in axon regeneration and vision require the DNA demethylases TET1 and TET2. These data indicate that mammalian tissues retain a record of youthful epigenetic information-encoded in part by DNA methylation-that can be accessed to improve tissue function and promote regeneration in vivo.

Accelerated epigenetic aging and DNA methylation alterations in Berardinelli-Seip congenital lipodystrophy.

Berardinelli-Seip congenital lipodystrophy type 2 (CGL2) is a very rare human genetic disorder with potential significance to the understanding of the pathobiology of aging. CGL2 patients display characteristic progeroid features and suffer from type 2 diabetes, insulin resistance and fatty liver. In this study, we profiled genome-wide DNA methylation levels in CGL2 patients with BSCL2 mutations to study epigenetic age acceleration and DNA methylation alterations. This analysis revealed significant age acceleration in blood DNA of CGL2 patients using both first- and second-generation epigenetic clocks. We also observed a shortened lifespan of Caenorhabditis elegans following knockdown of the BSCL2 homolog seip-1 on a daf-16/forkhead box, class O mutant background. DNA methylation analysis revealed significant differentially methylated sites enriched for lyase activity, kinase regulator activity, protein kinase regulator activity and kinase activator activity. We could also observe significant hypomethylation in the promoter of the dual specificity phosphatase 22 gene when comparing CGL2 patients versus controls. We conclude that in line with the observed progeroid features, CGL2 patients exhibit significant epigenetic age acceleration and DNA methylation alterations that might affect pathways/genes of potential relevance to the disease.

Comparative epigenome analysis using Infinium DNA methylation BeadChips.

The arrival of the Infinium DNA methylation BeadChips for mice and other nonhuman mammalian species has outpaced the development of the informatics that supports their use for epigenetics study in model organisms. Here, we present informatics infrastructure and methods to allow easy DNA methylation analysis on multiple species, including domesticated animals and inbred laboratory mice (in SeSAMe version 1.16.0+). First, we developed a data-driven analysis pipeline covering species inference, genome-specific data preprocessing and regression modeling. We targeted genomes of 310 species and 37 inbred mouse strains and showed that genome-specific preprocessing prevents artifacts and yields more accurate measurements than generic pipelines. Second, we uncovered the dynamics of the epigenome evolution in different genomic territories and tissue types through comparative analysis. We identified a catalog of inbred mouse strain-specific methylation differences, some of which are linked to the strains' immune, metabolic and neurological phenotypes. By streamlining DNA methylation array analysis for undesigned genomes, our methods extend epigenome research to broad species contexts.

MammalMethylClock R package: software for DNA methylation-based epigenetic clocks in mammals.

MOTIVATION: Epigenetic clocks are prediction methods based on DNA methylation levels in a given species or set of species. Defined as multivariate regression models, these DNA methylation-based biomarkers of age or mortality risk are useful in species conservation efforts and in preclinical studies. RESULTS: We present an R package called MammalMethylClock for the construction, assessment, and application of epigenetic clocks in different mammalian species. The R package includes the utility for implementing pre-existing mammalian clocks from the Mammalian Methylation Consortium. AVAILABILITY AND IMPLEMENTATION: The source code and documentation manual for MammalMethylClock, and clock coefficient .csv files that are included within this software package, can be found on Zenodo at https://doi.org/10.5281/zenodo.10971037.

Atherosclerotic Plaque Epigenetic Age Acceleration Predicts a Poor Prognosis and Is Associated With Endothelial-to-Mesenchymal Transition in Humans.

BACKGROUND: Epigenetic age estimators (clocks) are predictive of human mortality risk. However, it is not yet known whether the epigenetic age of atherosclerotic plaques is predictive for the risk of cardiovascular events. METHODS: Whole-genome DNA methylation of human carotid atherosclerotic plaques (n=485) and of blood (n=93) from the Athero-Express endarterectomy cohort was used to calculate epigenetic age acceleration (EAA). EAA was linked to clinical characteristics, plaque histology, and future cardiovascular events (n=136). We studied whole-genome DNA methylation and bulk and single-cell transcriptomics to uncover molecular mechanisms of plaque EAA. We experimentally confirmed our in silico findings using in vitro experiments in primary human coronary endothelial cells. RESULTS: Male and female patients with severe atherosclerosis had a median chronological age of 69 years. The median epigenetic age was 65 years in females (median EAA, -2.2 [interquartile range, -4.3 to 2.2] years) and 68 years in males (median EAA, -0.3 [interquartile range, -2.9 to 3.8] years). Patients with diabetes and a high body mass index had higher plaque EAA. Increased EAA of plaque predicted future events in a 3-year follow-up in a Cox regression model (univariate hazard ratio, 1.7; P=0.0034) and adjusted multivariate model (hazard ratio, 1.56; P=0.02). Plaque EAA predicted outcome independent of blood EAA (hazard ratio, 1.3; P=0.018) and of plaque hemorrhage (hazard ratio, 1.7; P=0.02). Single-cell RNA sequencing in plaque samples from 46 patients in the same cohort revealed smooth muscle and endothelial cells as important cell types in plaque EAA. Endothelial-to-mesenchymal transition was associated with EAA, which was experimentally confirmed by TGFß-triggered endothelial-to-mesenchymal transition inducing rapid epigenetic aging in coronary endothelial cells. CONCLUSIONS: Plaque EAA is a strong and independent marker of poor outcome in patients with severe atherosclerosis. Plaque EAA was linked to mesenchymal endothelial and smooth muscle cells. Endothelial-to-mesenchymal transition was associated with EAA, which was experimentally validated. Epigenetic aging mechanisms may provide new targets for treatments that reduce atherosclerosis complications.

DNA methylation clocks for dogs and humans.

DNA methylation profiles have been used to develop biomarkers of aging known as epigenetic clocks, which predict chronological age with remarkable accuracy and show promise for inferring health status as an indicator of biological age. Epigenetic clocks were first built to monitor human aging, but their underlying principles appear to be evolutionarily conserved, as they have now been successfully developed for many mammalian species. Here, we describe reliable and highly accurate epigenetic clocks shown to apply to 93 domestic dog breeds. The methylation profiles were generated using the mammalian methylation array, which utilizes DNA sequences that are conserved across all mammalian species. Canine epigenetic clocks were constructed to estimate age and also average time to death. We also present two highly accurate human­dog dual species epigenetic clocks (R = 0.97), which may facilitate the ready translation from canine to human use (or vice versa) of antiaging treatments being developed for longevity and preventive medicine. Finally, epigenome-wide association studies here reveal individual methylation sites that may underlie the inverse relationship between breed weight and lifespan. Overall, we describe robust biomarkers to measure aging and, potentially, health status in canines.

Methylome-proteome integration after late-life voluntary exercise training reveals regulation and target information for improved skeletal muscle health.

Exercise is a potent stimulus for combatting skeletal muscle ageing. To study the effects of exercise on muscle in a preclinical setting, we developed a combined endurance-resistance training stimulus for mice called progressive weighted wheel running (PoWeR). PoWeR improves molecular, biochemical, cellular and functional characteristics of skeletal muscle and promotes aspects of partial epigenetic reprogramming when performed late in life (22-24 months of age). In this investigation, we leveraged pan-mammalian DNA methylome arrays and tandem mass-spectrometry proteomics in skeletal muscle to provide detailed information on late-life PoWeR adaptations in female mice relative to age-matched sedentary controls (n = 7-10 per group). Differential CpG methylation at conserved promoter sites was related to transcriptional regulation genes as well as Nr4a3, Hes1 and Hox genes after PoWeR. Using a holistic method of -omics integration called binding and expression target analysis (BETA), methylome changes were associated with upregulated proteins related to global and mitochondrial translation after PoWeR (P = 0.03). Specifically, BETA implicated methylation control of ribosomal, mitoribosomal, and mitochondrial complex I protein abundance after training. DNA methylation may also influence LACTB, MIB1 and UBR4 protein induction with exercise - all are mechanistically linked to muscle health. Computational cistrome analysis predicted several transcription factors including MYC as regulators of the exercise trained methylome-proteome landscape, corroborating prior late-life PoWeR transcriptome data. Correlating the proteome to muscle mass and fatigue resistance revealed positive relationships with VPS13A and NPL levels, respectively. Our findings expose differential epigenetic and proteomic adaptations associated with translational regulation after PoWeR that could influence skeletal muscle mass and function in aged mice. KEY POINTS: Late-life combined endurance-resistance exercise training from 22-24 months of age in mice is shown to improve molecular, biochemical, cellular and in vivo functional characteristics of skeletal muscle and promote aspects of partial epigenetic reprogramming and epigenetic age mitigation. Integration of DNA CpG 36k methylation arrays using conserved sites (which also contain methylation ageing clock sites) with exploratory proteomics in skeletal muscle extends our prior work and reveals coordinated and widespread regulation of ribosomal, translation initiation, mitochondrial ribosomal (mitoribosomal) and complex I proteins after combined voluntary exercise training in a sizeable cohort of female mice (n = 7-10 per group and analysis). Multi-omics integration predicted epigenetic regulation of serine ß-lactamase-like protein (LACTB - linked to tumour resistance in muscle), mind bomb 1 (MIB1 - linked to satellite cell and type 2 fibre maintenance) and ubiquitin protein ligase E3 component N-recognin 4 (UBR4 - linked to muscle protein quality control) after training. Computational cistrome analysis identified MYC as a regulator of the late-life training proteome, in agreement with prior transcriptional analyses. Vacuolar protein sorting 13 homolog A (VPS13A) was positively correlated to muscle mass, and the glycoprotein/glycolipid associated sialylation enzyme N-acetylneuraminate pyruvate lyase (NPL) was associated to in vivo muscle fatigue resistance.

DNA methylation-based biomarkers and the epigenetic clock theory of ageing.

Identifying and validating molecular targets of interventions that extend the human health span and lifespan has been difficult, as most clinical biomarkers are not sufficiently representative of the fundamental mechanisms of ageing to serve as their indicators. In a recent breakthrough, biomarkers of ageing based on DNA methylation data have enabled accurate age estimates for any tissue across the entire life course. These 'epigenetic clocks' link developmental and maintenance processes to biological ageing, giving rise to a unified theory of life course. Epigenetic biomarkers may help to address long-standing questions in many fields, including the central question: why do we age?

Role of the murine reprogramming factors in the induction of pluripotency.

Induced pluripotent stem (iPS) cells can be obtained from fibroblasts upon expression of Oct4, Sox2, Klf4, and c-Myc. To understand how these factors induce pluripotency, we carried out genome-wide analyses of their promoter binding and expression in iPS and partially reprogrammed cells. We find that target genes of the four factors strongly overlap in iPS and embryonic stem (ES) cells. In partially reprogrammed cells, many genes co-occupied by c-Myc and any of the other three factors already show an ES cell-like binding and expression pattern. In contrast, genes that are specifically co-bound by Oct4, Sox2, and Klf4 in ES cells and encode pluripotency regulators severely lack binding and transcriptional activation. Among the four factors, c-Myc promotes the most ES cell-like transcription pattern when expressed individually in fibroblasts. These data uncover temporal and separable contributions of the four factors during the reprogramming process and indicate that ectopic c-Myc predominantly acts before pluripotency regulators are activated.

Author Correction: Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism.

Change history: In this Letter, the labels for splicing events A3SS and A5SS were swapped in column D of Supplementary Table 3a and b. This has been corrected online.

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

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