Biology subjects

Furman, D.

Publications and source records attributed to Furman, D..

At least 19 recordsLinked to original sources

bioRxiv2026

Immuno-Proteomic Age of Cardiovascular Etiology (iPACE) Signature Predicts Cardiovascular Risk in Elderly Patients

Despite advances in clinical care, cardiovascular disease (CVD) remains the leading cause of disability and mortality worldwide. While age alone is a primary risk factor for CVD, accumulating evidence suggests the immune system influences the initiation and progression of CVD pathophysiology, particularly in heart failure with preserved ejection fraction (HFpEF) and atherosclerotic CVD (ASCVD). Here, using two independent cohorts of older adults, we develop a thirty-protein signature of age based on serum immune proteomics, which correlates with HFpEF and ASCVD risk and mortality (Immuno-Proteomic Age of Cardiovascular Etiology, iPACE). We find aging-related circulating immune proteins associated with ASCVD and HFpEF-specific resilience and susceptibility that may be used as potential prognostic, diagnostic, or therapeutic targets.

immunology↗

bioRxiv2026

Simulated microgravity induces aging phenotypes in human organoids

Simulated microgravity provides a controlled perturbation for testing how loss of mechanical load affects human tissues. After 24 hours in rotating-wall vessels, neural, cardiac and tonsil organoids developed tissue-specific transcriptional responses that overlapped published spaceflight datasets, accompanied by higher transcriptomic-age estimates in neural and cardiac models, altered cardiac-organoid contraction dynamics and modified tonsil-organoid antiviral gene-expression signatures. These findings establish a multi-organoid framework for studying acute responses to gravitational unloading.

molecular biology↗

bioRxiv2026

Inferring organ aging, hallmark of aging and senescence scores from blood and facial photographs

Aging progresses asynchronously across organs, motivating the development of organ-resolved aging clocks. Direct assessment of organ aging in living humans, however, is largely impractical. Here, we construct tissue-specific transcriptomic aging clocks and infer organ biological age from paired whole-blood (blood-organ age) and tissue RNA sequencing data in the GTEx project. We observe high variability both in the strength of aging signatures across organs and in the ability to predict organ age and organ scores from blood. Pathway analysis shows that organ aging clocks are dominated by biological processes that differ across tissues. Age-associated multi-organ modules identified in an aging multi-organ network correlation analysis and organ age features causally mediated through organ-blood-organ transcriptomic interactions support a role for systemic signaling in coupling organ aging processes. Given the established role of cellular senescence as a driver of tissue dysfunction and its tissue-specific accumulation during aging, we extend this framework to estimate burden of organ-level senescence and hallmarks of aging. Using senescence- and hallmark-associated gene sets, we derive tissue-specific senescence and hallmark scores (organ scores) and demonstrate that these burdens across multiple organs can be inferred from blood transcriptomes (blood-organ scores). Finally, in pursuit of extending these models to other blood omics and alternative non-invasive assessments, we evaluate whether blood methylation (methylation-blood-organ age and scores) and facial photographs (facial-blood-organ age and scores) can serve as proxies for blood-organ age and blood-organ scores in independent cohorts (Edifice Health and Health and Retirement Study). The methylation- and facial-blood-organ age and scores were associated with mortality in additional testing cohorts (Framingham Heart Study and IMDB-WIKI dataset). These results establish a cross-modal framework for inferring organ-specific aging and senescence from minimally invasive data.

bioinformatics↗

bioRxiv2026

An AI-ready compositional framework for mechanistic aging research and in silico intervention testing

Aging is a network-level phenomenon, with its hallmarks interacting through dense feedback loops across vastly different timescales. Decades of reductionist research have produced thousands of mechanistic models of narrow subsystems, but no straightforward way to integrate them into one comprehensive system. Consequently, whole-cell and multi-hallmark aging models remain rare, manually constructed, and relatively small, despite broad agreement on their importance. The emergence of autonomous research agents offers a way to distribute this modeling effort across humans and artificial intelligence and thereby greatly accelerate it, but only if the underlying substrate allows agents to readily compose and analyze models with built-in validation checks and modeling guidance, without extensive custom code. We present hallsim, a JAX-native compositional simulation framework designed as the mechanistic substrate for agent-orchestrated research. It provides composability, end-to-end differentiability, GPU execution, and automated analysis and model-selection tools that facilitate composite model construction and fine tuning. The framework makes it easier to propose a mechanistic hypothesis, integrate it into an existing composite, reparametrize it against observed data, and batch-test it across different initial conditions. We demonstrate the co-simulation and in silico perturbation of three independently published kinetic models spanning genomic instability, nutrient sensing, and proteostasis. The models are connected by four edges and calibrated against a public dataset. Additionally, we train a Neural ODE surrogate and compose it alongside the mechanistic modules in a hybrid composite, demonstrating that mechanistic and neural models can function as complementary components of the same system.

systems biology↗

bioRxiv2026

Decoherence via Demyelination Hypothesis (DDH): A Mechanism of Cognitive Decline During Aging

Progressive cognitive decline and loss of white matter integrity are observed during aging, but whether these two processes are connected remains unclear. We propose the Decoherence via Demyelination Hypothesis (DDH) as a mechanism linking non-uniform, tract-specific myelin loss during aging, which results in the degradation of conduction timing that is required to coordinate long-range neuronal assemblies. This impairs the dynamic assembly of task-dependent functional networks and promotes age-associated cognitive change. Axonal myelination determines conduction velocity as well as signal transmission fidelity, properties essential for phase-locked integration of long-distance inputs with local oscillations and for the assembly of mesoscale functional brain networks. If myelin loss is heterogeneous across tracts, the resulting timing perturbations should be heterogeneous as well, with disproportionate impact on networks supporting higher-order cognition. To test this, we analyzed structural and microstructural MRI in 638 individuals aged 40-99, quantifying fasciculation in different white matter pathways as well as neurite orientation dispersion and density imaging (NODDI) to the gray-white matter interface beneath cortical regions. We observed tract-specific, non-uniform myelin decline, with significant nonlinear losses in tracts serving high order cognition and memory (uncinate fasciculus, fornix, corpus callosum), consistent with accelerated late-life vulnerability in pathways implicated in cognitive aging and increased risk for neurodegenerative diseases. Tract-level degeneration tracked with age-related shifts in network organization and cognition. These findings may support DDH as a framework for age-associated cognitive change. Particularly, tract-specific timing perturbations drive the breakdown of coordinated network activity in aging.

neuroscience↗

bioRxiv2026

Cellular senescence dysregulates antiviral interferon responses in idiopathic pulmonary fibrosis

Patients with idiopathic pulmonary fibrosis (IPF) are highly vulnerable to respiratory virus infections, but the cellular mechanisms linking fibrotic remodeling to impaired local antiviral defense remain unclear. Here, we investigated how cellular senescence shapes the response of patient-derived healthy and IPF primary lung fibroblasts to influenza A virus (IAV) infection. Transcriptomic profiling identified infection as the driver of gene expression in both DNA damage-induced senescent healthy and IPF fibroblasts and revealed induction of canonical antiviral pathways in both cell states. However, senescent IPF fibroblasts adopted a distinct antiviral response state characterized by a broader set of uniquely induced genes and differential coordination of antiviral transcriptional networks. Functionally, senescence increased viral titers in healthy and IPF fibroblasts, while senescent IPF fibroblasts displayed an altered inflammatory response. Network analysis linked viral response- and cell cycle-associated modules specifically to the senescent healthy infected state, whereas these programs were weaker in senescent IPF fibroblasts. Transcription factor inference identified IRF3 and STAT1 as candidate regulators of this altered antiviral state in both senescent healthy and IPF fibroblasts. Consistent with the network and transcription factor analyses, siRNA-mediated depletion of IRF3 or STAT1 significantly reduced IFN-{beta} secretion in senescent healthy fibroblasts, whereas IPF fibroblasts showed only milder effects, indicating a disease-specific dependence on these pathways for antiviral control. Together, these findings show that the combination of cellular senescence and fibrotic fibroblast identity creates a dysfunctional antiviral state that may help explain the high susceptibility of IPF patients to virus-associated acute exacerbations and disease worsening.

cell biology↗

bioRxiv2026

Quantification of domain-specific intrinsic capacity using mortality data

Functional health is centered on five domains of Intrinsic Capacity (IC): locomotion, cognition, vitality, psychological and sensory capacity. Therefore, measuring IC at the domain-specific level is the cornerstone for developing preventive interventions to help individuals preserve their independence. In this study, we used 63 clinical features from the UK Biobank to develop IC age, an 18-year mortality risk estimator that approximates an individuals biological age associated with the decline of each IC domain. By establishing proteomic surrogates of IC age, we find immune system activation across domains and provide a proteomic framework that may facilitate scalable monitoring of functional health decline.

systems biology↗

bioRxiv2026

DNA damage drives a unique, Alzheimer's disease-relevant senescent state in neurons

Alzheimers disease (AD) shares molecular hallmarks with the canonical drivers of cellular senescence. Senescent cells have also been shown to accumulate in the brain with age, yet the mechanisms linking AD pathology to the accumulation of senescent cells in the brain remain unclear. Here, we demonstrate that DNA damage in patient-derived directly induced neurons (iNs) drives a senescent-like cell state with relevance to AD. DNA damage-induced senescent iNs show significant transcriptional concordance with human AD neurons and a weighted gene co-expression network analysis (WGCNA) uncovers candidate regulators associated with the senescent-like state in neurons. Direct comparison of iNs to the original patient fibroblasts reveals striking cell-type specific senescence signatures following DNA damage. iNs adopt a p21-associated senescent-like state characterized by a senescence-associated secretory phenotype (SASP) and predicted activation of NF-{kappa}1. In contrast, fibroblasts develop a p16-associated senescent state lacking a SASP phenotype and show a predicted repression of NF-{kappa}1. Early responses to DNA damage further reveal divergent DNA damage response (DDR), with neurons exhibiting higher accumulation of damage lesions relative to fibroblasts. Together, these findings demonstrate that DNA damage drives a unique senescent-like neuronal state that models molecular features of AD, while also revealing fundamental cell-type specific differences in senescent-like phenotypes and DDR.

cell biology↗

bioRxiv2026

Simulated Microgravity Recapitulates Aspects of Biological Aging in Humans

Spaceflight and microgravity profoundly affect human physiology and have been proposed to recapitulate key features of biological aging, yet the underlying mechanisms remain incompletely understood. Here, we performed whole-genome transcriptomic profiling to define immune cell alterations associated with both natural aging and simulated microgravity. Leveraging the longitudinal nature of the Stanford 1,000 immunomes Project, we compared peripheral blood mononuclear cells (PBMCs) exposed to rotating wall vessel bioreactor with matched samples collected up to 9 years later from the same individuals. We quantified changes across aging hallmarks, molecular pathways, gene modules, cellular energetics, disease risk and vaccine-response signatures. Microgravity-induced transcriptional closely tracked subject-level aging trajectories spanning across disease risk domains including those affecting the metabolic, musculoskeletal and circulatory systems, and multiple aging hallmarks involving nutrient sensing, intrinsic capacity, chronic inflammation, proteostasis, cellular senescence and metabolic regulation. Independent validation using Single-Cell Energetic Metabolism by Profiling Translation Inhibition (SCENITH) profiling confirmed these observed metabolic adaptations and revealed reduced mitochondrial dependence with minimal compensatory glucose dependence across immune cell subsets, features that strongly parallel aging biology. Consistent with previous findings, longitudinal changes indicated that close of 1/3 of participants do not follow population trajectories but these can be partly predicted with simulated microgravity exposure. Together, this within-donor framework establishes simulated microgravity as a scalable and experimentally tractable platform to model aspects of biological aging in humans and accelerating the prioritization of candidate countermeasures for spaceflight and aging on Earth.

immunology↗

bioRxiv2026

Proteogenomic Profiling Reveals a Distinct Endogenous p16INK4a-Associated Senescence Signature in the Human Ovary.

The tumor suppressor and cell cycle regulator, p16INK4a (p16), has been extensively linked to cellular senescence, and its accumulation can reflect endogenous senescence within ovarian tissue. However, gene and protein signatures associated with p16 have not been well defined in human tissue. We utilized immunohistochemical (IHC) staining for P16 to identify distinct positive (P16+) and negative (P16-) regions within the ovarian cortex and employed the GeoMx Digital Spatial Profiler for simultaneous proteomic and transcriptomic analyses on cortical tissue cores. Differential expression and translation between p16-positive and p16-negative cores identified genes and proteins that are cellular senescence related (e.g., CDKN1A, GADD45B, GADD45G, and MYC) or key regulators of the extracellular matrix (e.g., collagen I, ADAMTS4, and MMP11). Additionally, the transcriptomic signature identified here was significantly enriched for the spatially derived ovarian p16-associated signature, BuckSenOvary, but not for other senescence gene sets. Lastly, given the association between changes to the extracellular matrix in aged ovaries and ovarian cancer, we compared genes upregulated and downregulated in p16-positive regions relative to p16-negative regions against multiple ovarian cancer transcriptomic datasets. These findings provide new insight into the molecular landscape of naturally occurring ovarian senescence and its possible relationship to age-associated disease processes, including cancer development.

cell biology↗

bioRxiv2025

Senescence-Linked Fibrosis in the Aging Human Ovary Revealed by p16-Based Histological Profiling and Spatial Transcriptomics

Cellular senescence is implicated as a driver of ovarian aging, but senescent cells in the human postmenopausal ovary remain poorly defined. Using spatially resolved p16INK4a protein expression, a canonical senescence marker, we identified and mapped senescent cells in postmenopausal ovaries. We integrated p16 immunohistochemistry, multiplexed immunofluorescence, spatial transcriptomics, and AI-guided digital pathology to map senescent microenvironments. p16-positive cells formed discrete stromal, vascular, and cyst-associated clusters that increased with age and were enriched for macrophages and myofibroblast-like cells. Wholetranscriptome profiling of 92 spatial regions uncovered a 32-gene p16-associated signature, BuckSenOvary, that distinguished p16-positive regions across cortex and medulla. BuckSenOvary is characterized by suppression of cell-cycle regulators and activation of inflammatory and extracellular-matrix remodelling genes. AI-based collagen matrix analysis confirmed that p16-positive regions exhibit more architecturally complex collagen, demonstrating that focal senescent microenvironments are fibro-inflammatory. These findings position senescent ovarian niches as therapeutic targets to preserve ovarian function.

cell biology↗

bioRxiv2025

Uncovering senescent fibroblast heterogeneity connects DNA damage response to idiopathic pulmonary fibrosis

Cellular senescence is a largely heterogeneous state of cell stress that deleteriously accumulates with age. Many types of heterogeneity in senescence have been described; however, cellular senescence within the same cell type has only started to be documented. Here, we show primary, human lung fibroblasts from donors who are healthy or diagnosed with idiopathic pulmonary fibrosis (IPF) exhibit a subtle form of heterogeneity over time after DNA damage. Moreover, senescent IPF lung fibroblasts display a dysregulated transcriptional-protein DNA damage response (DDR). Weighted gene correlation network analysis (WGCNA) reveals unique and known targets linking senescent IPF lung fibroblast heterogeneity to genes associated with DNA damage and repair, cytokine and chemokine responses, and extracellular matrix (ECM) signaling. We combine our healthy and IPF senescent gene expression signatures to develop a novel gene set of senescence-associated genes that identify disease-relevant cells in human single-cell RNA-seq (scRNA-seq) data. Collectively, our results uncover human-relevant senescence signatures, highlight IPF-specific DDR, cytokine and chemokine, and ECM targets, and expand our understanding of how a dysregulated DDR contributes to senescent cell heterogeneity in IPF.

cell biology↗

bioRxiv2025

Facial photographs as proxies for inflammatory aging

Systemic chronic inflammation is a major determinant of aging and disease risk, yet current biomarkers such as the Inflammatory Age (iAge) clock and other proteomic assays remain costly, invasive, and poorly scalable. The skin, as both a visible marker and contributor to age-related inflammation ("inflammaging"), offers a potential non-invasive window into this health metric. Here, we developed Healthy Selfie, a digital predictor of iAge, from simple 2D frontal face photographs. We leveraged data from the Edifice Health Pre-Market trial, a clinical study of 750 participants aged 20 to 90 years, using a subset with available iAge measurements paired to facial images, demographic, clinical, and functional data. Facial embeddings from a pretrained deep learning image model were combined with chronological age, sex and other easily obtainable metadata, and mapped to blood-derived iAge using regression within a leave-one-out cross-validation framework. Photo-predicted iAge values were significantly correlated with blood iAge values (r = 0.536) and were used to identify increased iAge acceleration (accuracy 66.39%, sensitivity 65.61%, specificity 67.24%). Validation on an external dataset containing [~]100,000 images showed no significant demographic bias across ethnicities, including Asian, Black, Indian, Middle Eastern, and Latino populations. Beyond iAge, we also showed that facial features could predict blood levels of individual inflammaging proteins (CXCL9, CXCL1, CCL11, TNFSF10, and IFNG). Our findings suggest that ordinary facial photos can provide information on blood inflammation and can be used as a scalable, ultra low-cost tool for assessing biological aging and advancing precision health.

bioinformatics↗

bioRxiv2025

Pathogenic tau inhibits synaptic plasticity by blocking eIF4B-mediated local protein synthesis

Activity-dependent modulation of synaptic strength is critical for encoding memories and it is inhibited in tauopathies including Alzheimers disease (AD) and Frontotemporal lobar degeneration with tau inclusions (FTLD-tau). Pathogenic tau accumulates in neurons where it obstructs synaptic plasticity. How tau blocks synaptic plasticity leading to memory loss is unclear. Here, we show that FTLD-tau inhibits plasticity by blocking activity-dependent protein synthesis in dendrites. In the plasticity-associated translatome, we identified a subset of downregulated translated mRNAs in FTLD-tau neurons that encode postsynaptic plasticity regulators. Protein synthesis was blocked by FTLD-tau binding to eIF4B which caused eIF4B dissociation from the translation initiation complex and reduced dendritic eIF4B levels. Inhibiting the tau-eIF4B interaction or enhancing eIF4B levels in FTLD-tau neurons restored local protein synthesis and synaptic plasticity. Together, this suggests that pathogenic tau binding to eIF4B disables the local synthesis of plasticity-related proteins that drive synapse strengthening and memory formation.

neuroscience↗

bioRxiv2024

Blood Omics Models for System-Specific Mortality Risk Estimation

Traditional blood-based aging clocks provide an estimate of a persons overall biological age. However, physiological systems and organs age at different rates in an individual, and anti-aging interventions often target specific physiological systems. Therefore, there is a growing need for methods capable of assessing biological age at the level of specific physiological systems. Here, we used blood chemistry and cell count data from 456,180 individuals in the UK Biobank (UKB) to develop mortality-based predictors of biological age across 9 physiological systems matching WHOs International Classification of Disease (ICD-10) chapters (DiseaseAge). We applied DiseaseAge to the Health and Retirement Study (HRS) cohort and validated its ability to identify biologically older systems in individuals diagnosed or deceased from age-related diseases affecting those systems. For instance, individuals diagnosed with high blood pressure, heart attack, congestive heart failure, or angina exhibited a biologically older circulatory system than other systems. Similarly, individuals with accelerated aging in the circulatory, musculoskeletal, or respiratory systems displayed higher risk of mortality from conditions associated with these systems. Additionally, we showed that individuals within the top 5% biologically older metabolic, circulatory, respiratory and mental systems exhibited increased risk of developing diabetes, high blood pressure, lung disease and dementia, respectively. Finally, we used metabolomics and proteomics data in the UKB and epigenomics and transcriptomics in HRS to generate omics surrogates of DiseaseAge for all physiological systems and created an online resource for their calculation.

systems biology↗

bioRxiv2024

Substrate Stiffness Dictates Unique Doxorubicin-induced Senescence-associated Secretory Phenotypes and Transcriptomic Signatures in Human Pulmonary Fibroblasts

Cells are subjected to dynamic mechanical environments which impart forces and induce cellular responses. In age-related conditions like pulmonary fibrosis, there is both an increase in tissue stiffness and an accumulation of senescent cells. While senescent cells produce a senescence-associated secretory phenotype (SASP), the impact of physical stimuli on both cellular senescence and the SASP is not well understood. Here, we show that mechanical tension, modeled using cell culture substrate rigidity, influences senescent cell markers like SA-{beta}-gal and secretory phenotypes. Comparing human primary pulmonary fibroblasts (IMR-90) cultured on physiological (2 kPa), fibrotic (50 kPa), and plastic (approximately 3 GPa) substrates, followed by senescence induction using doxorubicin, we identified unique high-stiffness-driven secretory protein profiles using mass spectrometry and transcriptomic signatures, both showing an enrichment in collagen proteins. Consistently, clusters of p21+ cells are seen in fibrotic regions of bleomycin induced pulmonary fibrosis in mice. Computational meta-analysis of single-cell RNA sequencing datasets from human interstitial lung disease confirmed these stiffness SASP genes are highly expressed in disease fibroblasts and strongly correlate with mechanotransduction and senescence-related pathways. Thus, mechanical forces shape cell senescence and their secretory phenotypes.

cell biology↗

bioRxiv2024

A comprehensive multi-omics signature of doxorubicin-induced cellular senescence in the postmenopausal human ovary.

A major aging hallmark is the accumulation of cellular senescence burden. Over time senescent cells contribute to tissue deterioration through chronic inflammation and fibrosis driven by the Senescence-Associated Secretory Phenotype (SASP). The human ovary is one of the first organs to age, and prominent age-related fibroinflammation within the ovarian microenvironment is consistent with the presence of senescent cells, but these cells have not been characterized in the human ovary. We thus established a doxorubicin-induced model of cellular senescence to establish a "senotype" (gene/protein signature of a senescence cell state) for ovarian senescent cells. Explants of human postmenopausal ovarian cortex and medulla were treated with doxorubicin for 24 hours followed by culture for up to 10 days in a doxorubicin-free medium. Tissue viability was confirmed by histology, lack of apoptosis, and continued glucose consumption by explants. Single nuclei sequencing and proteomics revealed an unbiased signature of ovarian senescence. We identified distinct senescence profiles for the cortex and medulla, driven predominantly by epithelial and stromal cells. Proteomics uncovered subregional differences in addition to 120 proteins common to the cortex and medulla SASP. Integration of transcriptomic and proteomic analyses revealed 26 shared markers, defining a senotype of doxorubicin-induced senescence unique to the postmenopausal ovary. A subset of these proteins: Lumican, SOD2, MYH9, and Periostin were mapped onto native tissue to reveal compartment-specific localization. This senotype will help determine the role of cellular senescence in ovarian aging, inform biomarker development to identify, and therapeutic applications to slow or reverse ovarian aging, senescence, and cancer.

molecular biology↗

bioRxiv2024

A Novel Blood-Based Epigenetic Clock for Intrinsic Capacity Predicts Mortality and is Associated with Clinical, Immunological and Lifestyle Factors

Age-related decline in intrinsic capacity (IC), defined as the sum of an individuals physical and mental capacities, is a cornerstone for promoting healthy aging and longevity, as it emphasizes maximizing function throughout the aging process instead of merely treating diseases. However, accurate assessments of IC are resource-intensive, and the molecular and cellular basis of its decline are poorly understood. Herein, we used the INSPIRE-T cohort, consisting of 1,014 individuals aged 20 to 102, to construct the IC clock, a DNA methylation (DNAm)-based predictor of IC trained on the clinical evaluation of cognition, locomotion, psychological well-being, sensory abilities, and vitality. In the Framingham Heart Study, age-adjusted DNAm IC correlates with first- and second-generation epigenetic clocks, predicts all-cause mortality, and is strongly associated with changes in molecular and cellular immune and inflammatory biomarkers, functional and clinical endpoints, health risk factors, and diet.

genomics↗