A disease similarity approach identifies short-lived Niemann-Pick type C disease mice with accelerated brain aging as a novel mouse model for Alzheimer's disease and aging research.

Since its first description in 1906 by Dr. Alois Alzheimer, Alzheimer's disease (AD) has been the most common type of dementia. Initially thought to be caused by age-associated accumulation of plaques, in recent years, research has increasingly associated AD with lysosomal storage and metabolic disorders, and the explanation of its pathogenesis has shifted from amyloid and tau accumulation to oxidative stress and impaired lipid and glucose metabolism aggravated by hypoxic conditions. However, the underlying mechanisms linking those cellular processes and conditions to disease progression have yet to be defined. Here, we applied a disease similarity approach to identify unknown molecular targets of AD by using transcriptomic data from congenital diseases known to increase AD risk, namely Down Syndrome, Niemann Pick Disease Type C (NPC), and Mucopolysaccharidoses I. We uncovered common pathways, hub genes, and miRNAs across in vitro and in vivo models of these diseases as potential molecular targets for neuroprotection and amelioration of AD pathology, many of which have never been associated with AD. We then investigated common molecular alterations in brain samples from an NPC disease mouse model by juxtaposing them with brain samples of both human and mouse models of AD. Detailed phenotypic and molecular analyses revealed NPCmut mouse as a novel, short-lived in vivo model of AD characterized by accelerated brain aging, concluding that NPCmut mouse model can serve as a potential short-lived in vivo model for AD research and for understanding molecular factors affecting brain aging. This research represents the first comprehensive approach to congenital disease association with neurodegeneration and a new perspective on AD research while highlighting shortcomings and lack of correlation in diverse in vitro models. Our findings provide a foundation for future animal and clinical studies and will lead to a better understanding of the molecular mechanisms underpinning the observed association between neurological congenital diseases and AD, thus has the potential to accelerate diagnostic and therapeutic applications against common types of dementia.

The beginning of becoming a human.

According to birth certificates, the life of a child begins once their body comes out of the mother's womb. But when does their organismal life begin? Science holds a palette of answers-depending on how one defines a human life. In 1984, a commission on the regulatory framework for human embryo experimentation opted not to answer this question, instead setting a boundary, 14 days post-fertilization, beyond which any experiments were forbidden. Recently, as the reproductive technologies developed and the demand for experimentation grew stronger, this boundary may be set aside leaving the ultimate decision to local oversight committees. While science has not come closer to setting a zero point for human life, there has been significant progress in our understanding of early mammalian embryogenesis. It has become clear that the 14-day stage does in fact possess features, which make it a foundational time point for a developing human. Importantly, this stage defines the separation of soma from the germline and marks the boundary between rejuvenation and aging. We explore how different levels of life organization emerge during human development and suggest a new meaning for the 14-day stage in organismal life that is grounded in recent mechanistic advances and insights from aging studies.

Nature of epigenetic aging from a single-cell perspective.

Age-related changes in DNA methylation (DNAm) form the basis of the most robust predictors of age-epigenetic clocks-but a clear mechanistic understanding of exactly which aspects of aging are quantified by these clocks is lacking. Here, to clarify the nature of epigenetic aging, we juxtapose the dynamics of tissue and single-cell DNAm in mice. We compare these changes during early development with those observed during adult aging in mice, and corroborate our analyses with a single-cell RNA sequencing analysis within the same multiomics dataset. We show that epigenetic aging involves co-regulated changes as well as a major stochastic component, and this is consistent with transcriptional patterns. We further support the finding of stochastic epigenetic aging by direct tissue and single-cell DNAm analyses and modeling of aging DNAm trajectories with a stochastic process akin to radiocarbon decay. Finally, we describe a single-cell algorithm for the identification of co-regulated and stochastic CpG clusters showing consistent transcriptomic coordination patterns. Together, our analyses increase our understanding of the basis of epigenetic clocks and highlight potential opportunities for targeting aging and evaluating longevity interventions.

A torpor-like state (TLS) in mice slows blood epigenetic aging and prolongs healthspan.

Torpor and hibernation are extreme physiological adaptations of homeotherms associated with pro-longevity effects. Yet the underlying mechanisms of how torpor affects aging, and whether hypothermic and hypometabolic states can be induced to slow aging and increase health span, remain unknown. We demonstrate that the activity of a spatially defined neuronal population in the avMLPA, which has previously been identified as a torpor-regulating brain region, is sufficient to induce a torpor like state (TLS) in mice. Prolonged induction of TLS slows epigenetic aging across multiple tissues and improves health span. We isolate the effects of decreased metabolic rate, long-term caloric restriction, and decreased core body temperature (Tb) on blood epigenetic aging and find that the pro-longevity effect of torpor-like states is mediated by decreased Tb. Taken together, our findings provide novel mechanistic insight into the pro-longevity effects of torpor and hibernation and support the growing body of evidence that Tb is an important mediator of aging processes.

A single cell atlas of the mouse seminal vesicle.

During mammalian reproduction, sperm are delivered to the female reproductive tract bathed in a complex medium known as seminal fluid, which plays key roles in signaling to the female reproductive tract and in nourishing sperm for their onwards journey. Along with minor contributions from the prostate and the epididymis, the majority of seminal fluid is produced by a somewhat understudied organ known as the seminal vesicle. Here, we report the first single-cell RNA-seq atlas of the mouse seminal vesicle, generated using tissues obtained from 23 mice of varying ages, exposed to a range of dietary challenges. We define the transcriptome of the secretory cells in this tissue, identifying a relatively homogeneous population of the epithelial cells which are responsible for producing the majority of seminal fluid. We also define the immune cell populations - including large populations of macrophages, dendritic cells, T cells, and NKT cells - which have the potential to play roles in producing various immune mediators present in seminal plasma. Together, our data provide a resource for understanding the composition of an understudied reproductive tissue with potential implications for paternal control of offspring development and metabolism.

Sendai virus persistence questions the transient naive reprogramming method for iPSC generation.

Since the revolutionary discovery of induced pluripotent stem cells (iPSCs) by Shinya Yamanaka, the comparison between iPSCs and embryonic stem cells (ESCs) has revealed significant differences in their epigenetic states and developmental potential. A recent compelling study published in Nature by Buckberry et al.1 demonstrated that a transient-naive-treatment (TNT) could facilitate epigenetic reprogramming and improve the developmental potential of human iPSCs (hiPSCs). However, the study characterized bulk hiPSCs instead of isolating clonal lines and overlooked the persistent expression of Sendai virus carrying exogenous Yamanaka factors. Our analyses revealed that Sendai genes were expressed in most control PSC samples, including hESCs, which were not intentionally infected. The highest levels of Sendai expression were detected in samples continuously treated with naive media, where it led to overexpression of exogenous MYC, SOX2, and KLF4, altering both the expression levels and ratios of reprogramming factors. Our findings call for further research to verify the effectiveness of the TNT method in the context of delivery methods that ensure prompt elimination of exogenous factors, leading to the generation of bona fide transgene-independent iPSCs.

Selenium, diabetes, and their intricate sex-specific relationship.

Selenium (Se) is an essential trace element, which is inserted as selenocysteine (Sec) into selenoproteins during biosynthesis, orchestrating their expression and activity. Se is associated with both beneficial and detrimental health effects; deficient supply or uncontrolled supplementation raises concerns. In particular, Se was associated with an increased incidence of type 2 diabetes (T2D) in a secondary analysis of a randomized controlled trial (RCT). In this review, we discuss the intricate relationship between Se and diabetes and the limitations of the available clinical and experimental studies. Recent evidence points to sexual dimorphism and an association of Se deficiency with gestational diabetes mellitus (GDM). We highlight the emerging evidence linking high Se status with improved prognosis in patients with T2D and lower risk of macrovascular complications.

AgeMeta: Quantitative Gene Expression Database of Mammalian Aging.

AgeMeta is a database that provides systemic and quantitative description of mammalian aging at the level of gene expression. It encompasses transcriptomic changes with age across various tissues of humans, mice, and rats, based on a comprehensive meta-analysis of 122 publicly available gene expression datasets from 26 studies. AgeMeta provides an intuitive visual interface for quantification of aging-associated transcriptomics at the level of individual genes and functional groups of genes, allowing easy comparison among various species and tissues. Additionally, all the data in the database can be downloaded and analyzed independently. Overall, this work contributes to the understanding of the complex network of biological processes underlying mammalian aging and supports future advancements in this field. AgeMeta is freely available at: https://age-meta.com/.

Multi-omics characterization of partial chemical reprogramming reveals evidence of cell rejuvenation.

Partial reprogramming by cyclic short-term expression of Yamanaka factors holds promise for shifting cells to younger states and consequently delaying the onset of many diseases of aging. However, the delivery of transgenes and potential risk of teratoma formation present challenges for in vivo applications. Recent advances include the use of cocktails of compounds to reprogram somatic cells, but the characteristics and mechanisms of partial cellular reprogramming by chemicals remain unclear. Here, we report a multi-omics characterization of partial chemical reprogramming in fibroblasts from young and aged mice. We measured the effects of partial chemical reprogramming on the epigenome, transcriptome, proteome, phosphoproteome, and metabolome. At the transcriptome, proteome, and phosphoproteome levels, we saw widescale changes induced by this treatment, with the most notable signature being an upregulation of mitochondrial oxidative phosphorylation. Furthermore, at the metabolome level, we observed a reduction in the accumulation of aging-related metabolites. Using both transcriptomic and epigenetic clock-based analyses, we show that partial chemical reprogramming reduces the biological age of mouse fibroblasts. We demonstrate that these changes have functional impacts, as evidenced by changes in cellular respiration and mitochondrial membrane potential. Taken together, these results illuminate the potential for chemical reprogramming reagents to rejuvenate aged biological systems and warrant further investigation into adapting these approaches for in vivo age reversal.

The long and winding road of reprogramming-induced rejuvenation.

Organismal aging is inherently connected to the aging of its constituent cells and systems. Reducing the biological age of the organism may be assisted by reducing the age of its cells - an approach exemplified by partial cell reprogramming through the expression of Yamanaka factors or exposure to chemical cocktails. It is crucial to protect cell type identity during partial reprogramming, as cells need to retain or rapidly regain their functions following the treatment. Another critical issue is the ability to quantify biological age as reprogrammed older cells acquire younger states. We discuss recent advances in reprogramming-induced rejuvenation and offer a critical review of this procedure and its relationship to the fundamental nature of aging. We further comparatively analyze partial reprogramming, full reprogramming and transdifferentiation approaches, assess safety concerns and emphasize the importance of distinguishing rejuvenation from dedifferentiation. Finally, we highlight translational opportunities that the reprogramming-induced rejuvenation approach offers.

Validation of biomarkers of aging.

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

Causality-enriched epigenetic age uncouples damage and adaptation.

Machine learning models based on DNA methylation data can predict biological age but often lack causal insights. By harnessing large-scale genetic data through epigenome-wide Mendelian randomization, we identified CpG sites potentially causal for aging-related traits. Neither the existing epigenetic clocks nor age-related differential DNA methylation are enriched in these sites. These CpGs include sites that contribute to aging and protect against it, yet their combined contribution negatively affects age-related traits. We established a new framework to introduce causal information into epigenetic clocks, resulting in DamAge and AdaptAge-clocks that track detrimental and adaptive methylation changes, respectively. DamAge correlates with adverse outcomes, including mortality, while AdaptAge is associated with beneficial adaptations. These causality-enriched clocks exhibit sensitivity to short-term interventions. Our findings provide a detailed landscape of CpG sites with putative causal links to lifespan and healthspan, facilitating the development of aging biomarkers, assessing interventions, and studying reversibility of age-associated changes.

TIME-seq reduces time and cost of DNA methylation measurement for epigenetic clock construction.

Epigenetic 'clocks' based on DNA methylation have emerged as the most robust and widely used aging biomarkers, but conventional methods for applying them are expensive and laborious. Here we develop tagmentation-based indexing for methylation sequencing (TIME-seq), a highly multiplexed and scalable method for low-cost epigenetic clocks. Using TIME-seq, we applied multi-tissue and tissue-specific epigenetic clocks in over 1,800 mouse DNA samples from eight tissue and cell types. We show that TIME-seq clocks are accurate and robust, enriched for polycomb repressive complex 2-regulated loci, and benchmark favorably against conventional methods despite being up to 100-fold less expensive. Using dietary treatments and gene therapy, we find that TIME-seq clocks reflect diverse interventions in multiple tissues. Finally, we develop an economical human blood clock (R > 0.96, median error = 3.39 years) in 1,056 demographically representative individuals. These methods will enable more efficient epigenetic clock measurement in larger-scale human and animal studies.

Downregulation of mitochondrial metabolism is a driver for fast skeletal muscle loss during mouse aging.

Skeletal muscle aging is characterized by the loss of muscle mass, strength and function, mainly attributed to the atrophy of glycolytic fibers. Underlying mechanisms driving the skeletal muscle functional impairment are yet to be elucidated. To unbiasedly uncover its molecular mechanisms, we recurred to gene expression and metabolite profiling in a glycolytic muscle, Extensor digitorum longus (EDL), from young and aged C57BL/6JRj mice. Employing multi-omics approaches we found that the main age-related changes are connected to mitochondria, exhibiting a downregulation in mitochondrial processes. Consistent is the altered mitochondrial morphology. We further compared our mouse EDL aging signature with human data from the GTEx database, reinforcing the idea that our model may recapitulate muscle loss in humans. We are able to show that age-related mitochondrial downregulation is likely to be detrimental, as gene expression signatures from commonly used lifespan extending interventions displayed the opposite direction compared to our EDL aging signature.

Senolytic therapy alleviates physiological human brain aging and COVID-19 neuropathology.

Aging is a major risk factor for neurodegenerative diseases, and coronavirus disease 2019 (COVID-19) is linked to severe neurological manifestations. Senescent cells contribute to brain aging, but the impact of virus-induced senescence on neuropathologies is unknown. Here we show that senescent cells accumulate in aged human brain organoids and that senolytics reduce age-related inflammation and rejuvenate transcriptomic aging clocks. In postmortem brains of patients with severe COVID-19 we observed increased senescent cell accumulation compared with age-matched controls. Exposure of human brain organoids to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) induced cellular senescence, and transcriptomic analysis revealed a unique SARS-CoV-2 inflammatory signature. Senolytic treatment of infected brain organoids blocked viral replication and prevented senescence in distinct neuronal populations. In human-ACE2-overexpressing mice, senolytics improved COVID-19 clinical outcomes, promoted dopaminergic neuron survival and alleviated viral and proinflammatory gene expression. Collectively our results demonstrate an important role for cellular senescence in driving brain aging and SARS-CoV-2-induced neuropathology, and a therapeutic benefit of senolytic treatments.

Intersection clock reveals a rejuvenation event during human embryogenesis.

Recent research revealed a rejuvenation event during early development of mice. Here, by examining epigenetic age dynamics of human embryogenesis, we tested whether a similar event exists in humans. For this purpose, we developed an epigenetic clock method, the intersection clock, that utilizes bisulfite sequencing in a way that maximizes the use of informative CpG sites with no missing clock CpG sites in test samples and applied it to human embryo development data. We observed no changes in the predicted epigenetic age between cleavage stage and blastocyst stage embryos; however, a significant decrease was observed between blastocysts and cells representing the epiblast. Additionally, by applying the intersection clock to datasets spanning pre and postimplantation, we found no significant change in the epigenetic age during preimplantation stages; however, the epigenetic age of postimplantation samples was lower compared to the preimplantation stages. We further investigated the epigenetic age of primed (representing early postimplantation) and naïve (representing preimplantation) pluripotent stem cells and observed that in all cases the epigenetic age of primed cells was significantly lower than that of naïve cells. Together, our data suggest that human embryos are rejuvenated during early embryogenesis. Hence, the rejuvenation event is conserved between the mouse and human, and it occurs around the gastrulation stage in both species. Beyond this advance, the intersection clock opens the way for other epigenetic age studies based on human bisulfite sequencing datasets as opposed to methylation arrays.

OMICmAge: An integrative multi-omics approach to quantify biological age with electronic medical records.

Biological aging is a multifactorial process involving complex interactions of cellular and biochemical processes that is reflected in omic profiles. Using common clinical laboratory measures in ~30,000 individuals from the MGB-Biobank, we developed a robust, predictive biological aging phenotype, EMRAge, that balances clinical biomarkers with overall mortality risk and can be broadly recapitulated across EMRs. We then applied elastic-net regression to model EMRAge with DNA-methylation (DNAm) and multiple omics, generating DNAmEMRAge and OMICmAge, respectively. Both biomarkers demonstrated strong associations with chronic diseases and mortality that outperform current biomarkers across our discovery (MGB-ABC, n=3,451) and validation (TruDiagnostic, n=12,666) cohorts. Through the use of epigenetic biomarker proxies, OMICmAge has the unique advantage of expanding the predictive search space to include epigenomic, proteomic, metabolomic, and clinical data while distilling this in a measure with DNAm alone, providing opportunities to identify clinically-relevant interconnections central to the aging process.

18S rRNA methyltransferases DIMT1 and BUD23 drive intergenerational hormesis.

Heritable non-genetic information can regulate a variety of complex phenotypes. However, what specific non-genetic cues are transmitted from parents to their descendants are poorly understood. Here, we perform metabolic methyl-labeling experiments to track the heritable transmission of methylation from ancestors to their descendants in the nematode Caenorhabditis elegans (C. elegans). We find heritable methylation in DNA, RNA, proteins, and lipids. We find that parental starvation elicits reduced fertility, increased heat stress resistance, and extended longevity in fed, naïve progeny. This intergenerational hormesis is accompanied by a heritable increase in N6'-dimethyl adenosine (m6,2A) on the 18S ribosomal RNA at adenosines 1735 and 1736. We identified DIMT-1/DIMT1 as the m6,2A and BUD-23/BUD23 as the m7G methyltransferases in C. elegans that are both required for intergenerational hormesis, while other rRNA methyltransferases are dispensable. This study labels and tracks heritable non-genetic material across generations and demonstrates the importance of rRNA methylation for regulating epigenetic inheritance.

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.