Biology subjects

Gladyshev, V. N.

Publications and source records attributed to Gladyshev, V. N..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Methionine sulfoxide reductase B3 antioxidant activity is indispensable for mouse inner ear cuticular plate structure and hair bundle integrity

Methionine sulfoxide reductases (MSR) are enzymes responsible for catalyzing the reduction of methionine-sulfoxides. We previously demonstrated that variants in human MSRB3, a member of the MSR family, are associated with profound autosomal recessive prelingual non-syndromic hearing loss DFNB74. To better understand the role of MSRB3 in the auditory pathway, we generated a complete MsrB3 gene knock-out mouse model of human DFNB74 deafness. The MsrB3 deficient mouse showed profound hearing loss by postnatal day 16 (P16), which was accompanied by hair cell morphological abnormalities including altered stereocilia bundle shape and cuticular plate degeneration followed by hair cell apoptotic death. Although the absence of MSRB3 primarily affected the actin cytoskeleton, rootlets were present, and the expression and localization of major F-actin stereocilia-core proteins were unaltered. Biochemical assays demonstrated that wild-type MSRB3, but not MSRB3 harboring p.Cys89Gly, the same variant reported for human deafness DFNB74, can repolymerize oxidized actin. Consistent with these in vitro data, we observed a decreased ratio of reduced/total actin in the inner ears of Msrb3 knock-out mice. These data suggest a protective role of MSRB3 in the maintenance and maturation of stereocilia and hair cells, a conserved mechanism aimed at maintaining actin redox dynamics in these sensory cells.

genetics↗

bioRxiv2024

A compact protein panel for organ-specific age and chronic disease prediction

Recent advances in plasma proteomics have led to a surge of computational models that accurately predict chronological age, mortality, and diseases from a simple blood draw. We leverage the data of [~]50,000 participants in the UK Biobank to investigate the predictive power of such models compared to individual proteins and metabolites by assessing disease risk and organ aging. We find that, with the exception of brain-related diseases, individual protein levels often match or surpass the predictive power of elaborate clocks trained on chronological age or mortality risk. Certain proteins effectively predict multiple diseases affecting specific organs. We show that in most cases, proteins predict diseases better than polygenic risk scores, and identify novel associations between human plasma protein levels and diseases, including LAMP3 and COPD, CHHR2 and liver disease, FAMC3 and kidney disease, and TMED1 and gout. We present a focused panel of 21 protein biomarkers that reveals the health state of the six organs associated with major age-related diseases. Our panel predicts common age-related diseases, including liver cirrhosis and fibrosis, dementia, kidney failure, and type II diabetes better than established blood panels and aging models. Through its vast coverage of age-related diseases, our compact panel offers a cost-effective alternative to full-scale proteomic analyses, making it a prime candidate for the non-invasive clinical detection and management of numerous age-related diseases simultaneously.

bioinformatics↗

bioRxiv2024

Profiling Epigenetic Aging at Cell-Type Resolution Through Long-Read Sequencing

DNA methylation can give rise to robust biomarkers of aging, yet most studies profile it at the bulk tissue level, which masks cell type-specific alterations that may follow distinct aging trajectories. Long-read sequencing technology enables methylation profiling of extended DNA fragments, which allows mapping to their cell type of origin. In this study, we introduce a framework for evaluating cell type-specific aging using long-read sequencing data, without the need for cell sorting. Leveraging cell type-specific methylation patterns, we map long-read fragments to individual cell types and generate cell type-specific methylation profiles, which are used as input to a newly developed probabilistic aging model, LongReadAge, capable of predicting epigenetic age at the cell-type level. We apply LongReadAge to track aging of myeloid cells and lymphocytes from bulk leukocyte data as well as circulating cell-free DNA, demonstrating robust performance in predicting age despite limited shared features across samples. This approach provides a novel method for profiling the dynamics of epigenetic aging at cell-type resolution.

bioinformatics↗

bioRxiv2024

An Open Competition for Biomarkers of Aging

Open scientific competitions have successfully driven biomedical advances but remain underutilized in aging research, where biological complexity and heterogeneity require methodological innovations. Here, we present the results from Phase I of the Biomarkers of Aging Challenge, an open competition designed to drive innovation in aging biomarker development and validation. The challenge leverages a unique DNA methylation dataset and aging outcomes from 500 individuals, aged 18 to 99. Participants are asked to develop novel models to predict chronological age, mortality, and multi-morbidity. Results from the chronological age prediction phase show important advances in biomarker accuracy and innovation compared to existing models. The winning models feature improved predictive power and employ advanced machine learning techniques, innovative data preprocessing, and the integration of biological knowledge. These approaches have led to the identification of novel age-associated methylation sites and patterns. This challenge establishes a paradigm for collaborative aging biomarker development, potentially accelerating the discovery of clinically relevant predictors of aging-related outcomes. This supports personalized medicine, clinical trial design, and the broader field of geroscience, paving the way for more targeted and effective longevity interventions.

bioinformatics↗

bioRxiv2024

MethylGPT: a foundation model for the DNA methylome

DNA methylation serves as a powerful biomarker for disease diagnosis and biological age assessment. However, current analytical approaches often rely on linear models that cannot capture the complex, context-dependent nature of methylation regulation. Here we present MethylGPT, a transformer-based foundation model trained on 226,555 (154,063 after QC and deduplication) human methylation profiles spanning diverse tissue types from 5,281 datasets, curated 49,156 CpG sites, and 7.6 billion training tokens. MethylGPT learns biologically meaningful representations of CpG sites, capturing both local genomic context and higher-order chromosomal features without external supervision. The model demonstrates robust methylation value prediction (Pearson R=0.929) and maintains stable performance in downstream tasks with up to 70% missing data. Applied to age prediction across multiple tissue types, MethylGPT achieves superior accuracy compared to existing methods. Analysis of the models attention patterns reveals distinct methylation signatures between young and old samples, with differential enrichment of developmental and aging-associated pathways. When finetuned to mortality and disease prediction across 60 major conditions using 18,859 samples from Generation Scotland, MethylGPT achieves robust predictive performance and enables systematic evaluation of intervention effects on disease risks, demonstrating potential for clinical applications. Our results demonstrate that transformer architectures can effectively model DNA methylation patterns while preserving biological interpretability, suggesting broad utility for epigenetic analysis and clinical applications.

systems biology↗

bioRxiv2024

The mitochondrial-targeted peptide therapeutic elamipretide improves cardiac and skeletal muscle function during aging without detectable changes in tissue epigenetic or transcriptomic age

Aging-related decreases in cardiac and skeletal muscle function are strongly associated with various comorbidities. Elamipretide (ELAM), a novel mitochondrial-targeted peptide, has demonstrated broad therapeutic efficacy in ameliorating disease conditions associated with mitochondrial dysfunction across both clinical and pre-clinical models. ELAM is proposed to restore mitochondrial bioenergetic function by stabilizing inner membrane structure and increasing oxidative phosphorylation coupling and efficiency. Although ELAM treatment effectively attenuates physiological declines in multiple tissues in rodent aging models, it remains unclear whether these functional improvements correlate with favorable changes in molecular biomarkers of aging. Herein, we investigated the impact of 8-week ELAM treatment on pre- and post-measures of C57BL/6J mice frailty, skeletal muscle, and cardiac muscle function, coupled with post-treatment assessments of biological age and affected molecular pathways. We found that health status, as measured by frailty index, cardiac strain, diastolic function, and skeletal muscle force are significantly diminished with age, with skeletal muscle force changing in a sex-dependent manner. Conversely, ELAM mitigated frailty accumulation and was able to partially reverse these declines, as evidenced by treatment-induced increases in cardiac strain and muscle fatigue resistance. Despite these improvements, we did not detect statistically significant changes in gene expression or DNA methylation profiles indicative of molecular reorganization or reduced biological age in most ELAM-treated groups. However, pathway analyses revealed that ELAM treatment showed pro-longevity shifts in gene expression such as upregulation of genes involved in fatty acid metabolism, mitochondrial translation and oxidative phosphorylation, and downregulation of inflammation. Together, these results indicate that ELAM treatment is effective at mitigating signs of sarcopenia and heart failure in an aging mouse model, but that these functional improvements occur independently of detectable changes in epigenetic and transcriptomic age. Thus, some age-related changes in function may be uncoupled from changes in molecular biological age.

molecular biology↗

bioRxiv2024

High-dimensional Ageome Representations of Biological Aging across Functional Modules

The aging process involves numerous molecular changes that lead to functional decline and increased disease and mortality risk. While epigenetic aging clocks have shown accuracy in predicting biological age, they typically provide single estimates for the samples and lack mechanistic insights. In this study, we challenge the paradigm that aging can be sufficiently described with a single biological age estimate. We describe Ageome, a computational framework for measuring the epigenetic age of thousands of molecular pathways simultaneously in mice and humans. Ageome is based on the premise that an organisms overall biological age can be approximated by the collective ages of its functional modules, which may age at different rates and have different biological ages. We show that, unlike conventional clocks, Ageome provides a high-dimensional representation of biological aging across cellular functions, enabling comprehensive assessment of aging dynamics within an individual, in a population, and across species. Application of Ageome to longevity intervention models revealed distinct patterns of pathway-specific age deceleration. Notably, cell reprogramming, while rejuvenating cells, also accelerated aging of some functional modules. When applied to human cohorts, Ageome demonstrated heterogeneity in predictive power for mortality risk, and some modules showed better performance in predicting the onset of age-related diseases, especially cancer, compared to existing clocks. Together, the Ageome framework offers a comprehensive and interpretable approach for assessing aging, providing insights into mechanisms and targets for intervention.

systems biology↗

bioRxiv2024

Imputed DNA methylation outperforms measured loci associations with smoking and chronological age

Multi-locus signatures of blood-based DNA methylation are well-established biomarkers for lifestyle and health outcomes. Here, we focus on two CpGs that are strongly associated with age and smoking behaviour. Imputing these loci via epigenome-wide CpGs results in stronger associations with outcomes in external datasets compared to directly measured CpGs. If extended epigenome-wide, CpG imputation could augment historic arrays and recently-released, inexpensive but lower-content arrays, thereby yielding better-powered association studies.

genetics↗

bioRxiv2024

Precious3GPT: Multimodal Multi-Species Multi-Omics Multi-Tissue Transformer for Aging Research and Drug Discovery

We present a multimodal multi-species multi-omics multi-tissue transformer for aging research and drug discovery capable of performing multiple tasks such as age prediction across species, target discovery, tissue, sex, and disease sample classification, drug sensitivity prediction, replication of omics response and prediction of biological and phenotypic response to compound treatment. This model combines textual, tabular, and knowledge graph-derived representations of biological experiments to provide insights into molecular-level biological processes. We demonstrate that P3GPT has developed an intuition for the interactions between compounds, pathologies, and gene regulation in the context of multiple species and tissues. In these areas, it outperforms existing LLMs and we highlight its utility in diverse case studies. P3GPT is a general model that may be used as a target identification tool, aging clock, digital laboratory, and scientific assistant. The model is intended as a community resource available open source as well as via a Discord server.

bioinformatics↗

bioRxiv2024

Transcriptomic Hallmarks of Mortality Reveal Universal and Specific Mechanisms of Aging, Chronic Disease, and Rejuvenation

Health is strongly affected by aging and lifespan-modulating interventions, but the molecular mechanisms of mortality regulation remain unclear. Here, we conducted an RNA-seq analysis of mice subjected to 20 compound treatments in the Interventions Testing Program (ITP). By integrating it with the data from over 4,000 rodent tissues representing aging and responses to genetic, pharmacological, and dietary interventions with established survival data, we developed robust multi-tissue transcriptomic biomarkers of mortality, capable of quantifying aging and change in lifespan in both short-lived and long-lived models. These tools were further extended to single-cell and human data, demonstrating common mechanisms of molecular aging across cell types and species. Via a network analysis, we identified and annotated 26 co-regulated modules of aging and longevity across tissues, and developed interpretable module-specific clocks that capture aging- and mortality-associated phenotypes of functional components, including, among others, inflammatory response, mitochondrial function, lipid metabolism, and extracellular matrix organization. These tools captured and characterized acceleration of biological age induced by progeria models and chronic diseases in rodents and humans. They also revealed rejuvenation induced by heterochronic parabiosis, early embryogenesis, and cellular reprogramming, highlighting universal signatures of mortality, shared across models of rejuvenation and age-related disease. They included Cdkn1a and Lgals3, whose human plasma levels further demonstrated a strong association with all-cause mortality, disease incidence and risk factors, such as obesity and hypertension. Overall, this study uncovers molecular hallmarks of mammalian mortality shared across organs, cell types, species and models of disease and rejuvenation, exposing fundamental mechanisms of aging and longevity.

systems biology↗

bioRxiv2024

Integrative epigenetics and transcriptomics identify aging genes in human blood

Recent epigenome-wide studies have identified a large number of genomic regions that consistently exhibit changes in their methylation status with aging across diverse populations, but the functional consequences of these changes are largely unknown. On the other hand, transcriptomic changes are more easily interpreted than epigenetic alterations, but previously identified age-related gene expression changes have shown limited replicability across populations. Here, we develop an approach that leverages high-resolution multi-omic data for an integrative analysis of epigenetic and transcriptomic age-related changes and identify genomic regions associated with both epigenetic and transcriptomic age-dependent changes in blood. Our results show that these "multi-omic aging genes" in blood are enriched for adaptive immune functions, replicate more robustly across diverse populations and are more strongly associated with aging-related outcomes compared to the genes identified using epigenetic or transcriptomic data alone. These multi-omic aging genes may serve as targets for epigenetic editing to facilitate cellular rejuvenation.

systems biology↗

bioRxiv2024

The 18S rRNA Methyltransferase DIMT-1 Regulates Lifespan in the Germline Later in Life

Ribosome heterogeneity has emerged as an important regulatory control feature for determining which proteins are synthesized, however, the influence of age on ribosome heterogeneity is not fully understood. Whether mRNA transcripts are selectively translated in young versus old cells and whether dysregulation of this process drives organismal aging is unknown. Here we examined the role of ribosomal RNA (rRNA) methylation in maintaining appropriate translation as organisms age. In a directed RNAi screen, we identified the 18S rRNA N6-dimethyl adenosine (m6,2A) methyltransferase, dimt-1, as a regulator of C. elegans lifespan and stress resistance. Lifespan extension induced by dimt-1 deficiency required a functional germline and was dependent on the known regulator of protein translation, the Rag GTPase, raga- 1, which links amino acid sensing to the mechanistic target of rapamycin complex (mTORC)1. Using an auxin-inducible degron tagged version of dimt-1, we demonstrate that DIMT-1 functions in the germline after mid-life to regulate lifespan. We further found that knock-down of dimt-1 leads to selective translation of transcripts important for stress resistance and lifespan regulation in the C. elegans germline in mid-life including the cytochrome P450 daf-9, which synthesizes a steroid that signals from the germline to the soma to regulate lifespan. We found that dimt-1 induced lifespan extension was dependent on the daf-9 signaling pathway. This finding reveals a new layer of proteome dysfunction, beyond protein synthesis and degradation, as an important regulator of aging. Our findings highlight a new role for ribosome heterogeneity, and specific rRNA modifications, in maintaining appropriate translation later in life to promote healthy aging.

genetics↗

bioRxiv2024

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, Alzheimers 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 that the 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. Considering the lack of an AD mouse model that recapitulates the physiological hallmarks of brain aging, the characterization of a short-lived NPC mouse model will further accelerate the research in these fields and offer a unique model for understanding the molecular mechanisms of AD from a perspective of accelerated brain aging.

genetics↗

bioRxiv2024

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.

genomics↗

bioRxiv2024

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.

physiology↗

bioRxiv2024

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.

developmental biology↗

bioRxiv2023

Biolearn, an open-source library for biomarkers of aging

Aging biomarkers are essential for understanding and quantifying the aging process and developing targeted longevity interventions. However, validation of these tools has been hindered by the lack of standardized approaches for cross-population validation, disparate biomarker designs, and inconsistencies in dataset structures. To address these challenges, we developed Biolearn, an open-source library that provides a unified framework for the curation, harmonization, and systematic evaluation of aging biomarkers. Leveraging Biolearn, we conducted a comprehensive evaluation of various aging biomarkers across multiple datasets. Our systematic approach involved three key steps: (1) harmonizing existing and novel aging biomarkers in standardized formats; (2) unifying public datasets to ensure coherent structuring and formatting; and (3) applying computational methodologies to assess the harmonized biomarkers against the unified datasets. This evaluation yielded valuable insights into the performance, robustness, and generalizability of aging biomarkers across different populations and datasets. The Biolearn python library, which forms the foundation of this systematic evaluation, is freely available at https://Bio-Learn.github.io. Our work establishes a unified framework for the curation and evaluation of aging biomarkers, paving the way for more efficient and effective clinical validation and application in the field of longevity research.

bioinformatics↗

bioRxiv2023

Epigenetic predictors of species maximum lifespan and other life history traits in mammals

Maximum lifespan is an intrinsic characteristic of a biological species and is defined as the longest time an individual of a species has been reported to survive. By analyzing 15K samples derived from 348 mammalian species representing 25 taxonomic orders we previously identified CpG methylation sites associated with maximum lifespan. Here we present accurate DNA methylation-based (DNAm) predictors of maximum lifespan (r=0.89), average gestation time (r=0.96), and age at sexual maturity (r=0.85). Our DNAm maximum lifespan predictor indicates a potential innate longevity advantage for females over males in 17 mammalian species such as humans, red deer, and cattle. The DNAm maximum lifespan predictions do not vary significantly by caloric restriction and partial reprogramming. Genetic disruptions in the somatotropic axis, which includes growth hormone, IGF-1, and their related receptors, have an impact on DNAm maximum lifespan only in select mouse tissues. Cancer mortality rates in major mammalian orders show no correlation with our epigenetic estimates of life history traits. The DNAm maximum lifespan predictor does not detect variation in lifespan between individuals of the same species, such as between the breeds of dogs. We also present the first prototypes of accurate pan mammalian DNAm predictors of sex and tissue type. Collectively, our findings indicate that maximum lifespan is determined, at least in part, by an epigenetic signature that is an intrinsic property of each species and is distinct from the signatures that relate to individual lifespan, which is unaffected by interventions influencing the mortality risk of individuals.

evolutionary biology↗