Biology subjects

Poganik, J. R.

Publications and source records attributed to Poganik, J. R..

18 recordsLinked to original sources

bioRxiv2026

Systemic control and inter-organ communication of ovarian aging

Whether ovarian aging is intrinsic and unidirectional or dynamically regulated by systemic context remains an open question for fertility and women's healthspan. To address it, we developed a mouse ovarian transcriptomic aging clock (OvaAge) and applied it, together with published transcriptomic, epigenetic and pathway-resolved DNA methylation (PathAge) clocks, multi-omic analyses and reproductive outcomes, to new reciprocal heterochronic ovary transplantation and parabiosis experiments. Ovarian molecular age shifted in both directions: aged ovaries became younger in young hosts and young ovaries became older in aged hosts, and in each case the shift was partial across transcriptomic, epigenetic and pathway-resolved measures. Ovaries from 13-month-old C57BL/6J donors supported full-term pregnancies and live births at 17-18 months of age when transplanted into young hosts, but not when transplanted into old hosts, and young ovaries supported live births in 17-18-month-old recipients. Donor ovary age altered the transcriptomic age of the uterus in both directions, while young ovaries also lowered the transcriptomic age of aged liver and brain, identifying the ovary as an active node within an inter-organ aging network. Across unilateral and bilateral transplantation and parabiosis, an older environment increased inflammatory gene expression in the ovary, whereas a younger environment reduced it and increased mitochondrial and biosynthetic programs. Integration of methylation, expression and cell-type markers linked these changes to declining oocyte-associated programs and an expanding stromal compartment enriched for multinucleated giant cells (MNGCs). MNGC-rich regions formed a reversibly remodeled, focally aged niche with distinct spatial metabolic features, and a related macrophage expression signature was detected in human ovaries. Together, these findings identify ovarian aging as a modular, bidirectionally plastic process that is regulated by the systemic environment and point to tractable intervention points.

systems biology↗

bioRxiv2026

Transplanted hearts assimilate the recipient's biological age

Background. Despite the growing demand for transplantation, a shortage of donor organs persists, limiting access to this lifesaving procedure. To meet the increasing demand, organs are frequently transplanted across an age discrepancy between donor and recipients. Methods. We delineated biological age dynamics in heterochronic heart transplants performed in both mice and patients. We carried out multiomic profiling and applied advanced biomarkers of aging to understand the interactions between the transplanted organ and the host. Results. We show that the biological age of experimental heart transplants rapidly assimilates the age of recipients. Interestingly, this effect was limited to the grafted tissue without reciprocal effects on systemic biological age of the recipient. These effects were confirmed at the level of DNA methylation and gene expression. Extending our findings clinically using both omics and functional analyses, we show that the biological age of heterochronically transplanted hearts is strongly associated with the age of the recipient, rather than the donor, confirming the clinical relevance of our experimental findings. Conclusions. These data identify the systemic environment as a driving force on tissue biological age. The rejuvenation of older organs in young recipients suggests novel approaches to organ allocation that may expand the pool of transplantable organs.

systems biology↗

bioRxiv2025

Rejuvenation of white adipose tissue in a longitudinal heterochronic transplantation model

Exposure to a younger system can induce organismal rejuvenation, yet whether all tissues can be rejuvenated and by what mechanisms remains understudied. We performed heterochronic and isochronic transplantation of subcutaneous white adipose tissue (WAT) between young and old mice and longitudinally tracked changes in biological age. Transplantation accelerated tissue aging, and the molecular age of grafts shifted toward that of the host. Most importantly, old WAT was rejuvenated in a young body. Epigenetic and transcriptomic clocks revealed a reduction of predicted age, accompanied by coordinated activation of canonical and previously unrecognized thermogenic pathways. Molecular rejuvenation was further supported by architectural changes toward a youthful state, including reduced lipid droplet size and decreased cellular heterogeneity. Mitochondrial abundance and morphology remained unchanged, while collagen deposition increased. These results demonstrate that WAT biological age is partially reversible and identify molecular and cellular features underlying its rejuvenation

systems biology↗

bioRxiv2025

DNA Methylation Ageing Atlas Across 17 Human Tissues

Aging involves widespread epigenetic remodeling across tissues, yet the nature and consistency of these changes remain unclear. We conducted a meta-analysis of more than 15,000 human methylomes spanning 17 tissues, identifying both conserved and tissue-specific aging signatures. We examined linear changes via differentially methylated positions, variability shifts via variably methylated positions, and Shannon-entropy to capture methylation disorder. Network analysis revealed fragile co-methylation modules largely resistant to beneficial perturbation. Key disruptors, including PCDHGA1, MEST, HDAC4, and HOX genes, exacerbated aging signals across tissues. Notably, a resilient module enriched for NAD{square} salvage metabolism supports therapeutic targeting of NAD{square} in aging. PCDHGA1 emerged as a conserved cross-tissue driver, suggesting protocadherin-mediated adhesion plays a broader role in maintaining structural and signaling stability in multiple organ systems. Our open-access atlas provides a foundational resource for dissecting the molecular architecture of human aging and identifying testable targets for intervention, biomarkers, and translational epigenetic therapies.

bioinformatics↗

bioRxiv2025

Molecular signatures of longevity identify compounds that extendmouse lifespan and healthspan

Longevity interventions in mammals are typically discovered on a case-by-case basis, hindering systematic geroprotector development. We developed a platform for the identification of longevity interventions integrating longevity gene expression biomarkers within and across species, in silico chemical screening, analyses of selected compounds in cell culture, short-term dietary interventions coupled with omics profiling, and ultimately lifespan studies in mice. This approach identified compounds (selumetinib, vorinostat, celastrol, AZD-8055, LY-294002) that extended lifespan and/or healthspan in aged C57BL/6JN male mice, with limited effects in females. In addition, selumetinib and vorinostat increased lifespan when administered to young, genetically heterogeneous UM-HET3 mice. Our biomarker-driven platform accelerates geroprotector discovery, offering a scalable approach to target conserved longevity pathways.

systems biology↗

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

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

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↗

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↗

bioRxiv2022

Z-REX uncovers a bifurcation in function of Keap1 paralogs

Studying electrophile signaling is marred by difficulties in parsing changes in pathway flux attributable to on-target, vis-a-vis off-target, modifications. By combining bolus dosing, knockdown, and Z-REX--a tool investigating on-target/on-pathway electrophile signaling, we document that electrophile labeling of one zebrafish-Keap1-paralog (zKeap1b) stimulates Nrf2-driven antioxidant response (AR) signaling (like the human-ortholog). Conversely, zKeap1a is a dominant-negative regulator of electrophile-promoted Nrf2-signaling, and itself is nonpermissive for electrophile-induced Nrf2-upregulation. This behavior is recapitulated in human cells, wherein following electrophile treatment: (1) zKeap1b-transfected cells are permissive for augmented AR-signaling through reduced zKeap1b-Nrf2 binding; (2) zKeap1a-transfected cells are non-permissive for AR-upregulation, as zKeap1a-Nrf2 binding capacity remains unaltered; (3) 1:1 ZKeap1a:zKeap1b-transfected cells show no Nrf2-release from the Keap1-complex, rendering these cells unable to upregulate AR. We identified a zKeap1a-specific point-mutation (C273I) responsible for zKeap1as behavior. Human-Keap1(C273I), of known diminished Nrf2-regulatory capacity, dominantly muted electrophile-induced Nrf2-signaling. These studies highlight divergent and interdependent electrophile signaling behaviors, despite conserved electrophile sensing. Impact statementHow electrophile-sensing versus -signaling marshal stress responses: two zebrafish Keap1-paralogs are equally adept at electrophile-sensing but manifest divergent and co-regulatory electrophile-signaling behaviors.

pharmacology and toxicology↗

bioRxiv2022

Z-REX: Shepherding Reactive Electrophiles to Specific Proteins Expressed either Tissue-Specifically or Ubiquitously, and Recording the Resultant Functional Electrophile-Induced Redox Responses in Larval Fish

Summary of the Protocol ExtensionThis Protocol Extension describes the adaptation of an existing Nature Protocol detailing the use of T-REX (targetable reactive electrophiles and oxidants)--an on-demand redox targeting toolset in cultured cells. The adaptation described here is for use of REX technologies in live zebrafish embryos (Z-REX). Zebrafish embryos expressing a Halo-tagged protein of interest (POI)--either ubiquitously or tissue-specifically--are treated with a HaloTag-specific small-molecule probe housing a photocaged reactive electrophile (either natural electrophiles or synthetic electrophilic drug-like fragments). The reactive electrophile is then photouncaged at a user-defined time, enabling proximity-assisted electrophile-modification of a POI. Functional and phenotypic ramifications of POI-specific modification can then be monitored, by coupling to standard downstream assays, such as, Click chemistry-based POI-labeling and target-occupancy quantification; immunofluorescence or live imaging; RNA-Seq and qRT-PCR analyses of downstream-transcript modulations. Transient expression of requisite Halo-POI in zebrafish embryos is achieved by mRNA injection. Procedures associated with generation of transgenic zebrafish expressing a tissue-specific Halo-POI are also described. The Z-REX experiments can be completed in <1-week using standard techniques. To successfully execute Z-REX, researchers should have basic skills in fish husbandry, imaging, and pathway analysis. Experience with protein or proteome manipulation is useful. This protocol extension is aimed at helping chemical biologists study precision redox events in a model organism and fish biologists perform redox chemical biology.

biochemistry↗

bioRxiv2022

Epigenetic profiling and incidence of disrupted development point to gastrulation as aging ground zero in Xenopus laevis

Recent studies suggest the existence of a natural rejuvenation event during early embryonic development of mice, followed by epigenetic aging. Here, by profiling embryonic DNA methylation in the African clawed frog, Xenopus laevis, we found that the epigenetic entropy basepoint maps to the gastrulation stage of embryogenesis and corresponds to a rapid increase in embryo transcript abundance. We further developed a frog aging clock, revealing that this species epigenetically ages. Application of this clock to developmental stages identified a decrease in epigenetic age during early embryogenesis, with the minimal age reached around gastrulation. By examining individual developmental trajectories of 6,457 embryos, we found that this stage is also accompanied by a higher incidence of disrupted development. Taken together, our data point to gastrulation as a critical stage for aging and natural rejuvenation, characterized by the lowest epigenetic age, increased mortality, nadir of DNA methylation entropy and rapid increase in embryo transcript abundance, defining aging ground zero as the basepoint where rejuvenation ends and the aging process begins.

genetics↗

bioRxiv2022

Biological age is increased by stress and restored upon recovery

Aging is classically conceptualized as an ever-increasing trajectory of damage accumulation and loss of function, leading to increases in morbidity and mortality. However, recent in vitro studies have raised the possibility of age reversal. Here, we report that biological age is fluid and exhibits rapid changes in both directions. By applying advanced epigenetic aging clocks, we find that the biological age of young mice is increased by heterochronic parabiosis and restored following surgical detachment of animals. We also identify transient changes in biological age during major surgery, pregnancy, and severe COVID-19 in humans and/or mice. Together, these data show that biological age undergoes a rapid increase in response to diverse forms of stress, which is reversed following recovery from stress. Our study uncovers a new layer of aging dynamics that should be considered in future studies. Elevation of biological age by stress may be a quantifiable and actionable target for future interventions.

systems biology↗

bioRxiv2022

Rapamycin treatment during development extends lifespan and healthspan

The possibility that pace of development is tightly connected to aging is supported by the fact that the onset of reproduction is associated with lifespan and that many longevity interventions target growth and development. However, it has been unknown whether targeting development with pharmacological intervention can lead to a longer lifespan. To test this possibility, we subjected genetically diverse UMHET3 mice to the mTOR inhibitor rapamycin for the first 45 days of life and followed them up until death. Treated mice grew slower, with most of the deceleration occurring in the first week, and remained smaller for their entire lives. Their reproductive age was delayed but without affecting offspring numbers. The treatment was sufficient to extend the median lifespan by 10%, with the most effect in males, and to preserve better health as measured by frailty index, gait speed, and glucose and insulin tolerance tests. Mechanistically, the liver transcriptome of treated mice was younger at the completion of treatment and stayed younger into the old ages in males. Rapamycin initially reduced DNA methylation age of livers, however, that effect was lost with aging. Analogous to mice, rapamycin exposure only during development robustly extended the lifespan of Daphnia magna as well as reduced their body size, suggesting evolutionary conserved mechanisms of this early life effect. Overall, the results demonstrate that short-term rapamycin treatment during early life is a novel longevity intervention that establishes causality between pace of development and longevity in evolutionary distant organisms.

developmental biology↗

bioRxiv2020

The mRNA-binding protein HuR is a kinetically-privileged electrophile sensor

The key mRNA-binding proteins HuR and AUF1 are reported stress sensors in mammals. Intrigued by recent reports of sensitivity of these proteins to the electrophilic lipid prostaglandin A2 and other redox signals, we here examined their sensing abilities to a prototypical redox-linked lipid-derived electrophile, 4-hydroxynonenal (HNE). Leveraging our T-REX electrophile delivery platform, we found that only HuR, and not AUF1, is a kinetically-privileged sensor of HNE in HEK293T cells, and sensing functions through a specific cysteine, C13. Cells depleted of HuR, upon treatment with HNE, manifest unique alterations in cell viability and Nrf2-transcription-factor-driven antioxidant response (AR), which our recent work shows is regulated by HuR at the Nrf2-mRNA level. Mutagenesis studies showed that C13-specific sensing alone is not sufficient to explain HuR-dependent stress responsivities, further highlighting a complex context-dependent layer of Nrf2/AR regulation through HuR.

biochemistry↗

bioRxiv2019

Post-transcriptional regulation of Nrf2-mRNA by the mRNA-binding proteins HuR and AUF1

The Nrf2-driven antioxidant response (AR) is a target of covalent drugs and bioactive native electrophiles. However, much of our understanding of AR has centered on protein-level regulation of Nrf2. Here we report a post-transcriptional modality to directly regulate Nrf2-mRNA. Our initial studies focused on the effects of the key mRNA-binding protein (mRBP) HuR on global transcriptomic changes incurred upon oxidant or electrophile stimulation. These data led us to discover a novel role of HuR in regulating Nrf2/AR, and in the process we further identified the related mRBP AUF1 as an additional novel Nrf2/AR regulator. Both mRBPs regulate AR by direct interaction with the Nrf2 transcript. Our data showed that HuR enhances Nrf2-mRNA maturation and promotes its nuclear export; whereas AUF1 stabilizes Nrf2-mRNA. Both mRBPs target the 3'-UTR of Nrf2-mRNA. Using an AR-reporter zebrafish strain, we document that this post-transcriptional control of AR is conserved at the whole-vertebrate level.

biochemistry↗