Biology subjects

Niedernhofer, L. J.

Publications and source records attributed to Niedernhofer, L. J..

13 recordsLinked to original sources

bioRxiv2026

Identification of an Endothelial Senotype Predicted by Ion Channel Expression in Aged Murine Perigonadal Adipose Tissue

Adipose tissue plays a key role in metabolic health, contributing to systemic dysfunction upon obesity or aging. A major driving factor of adipose-driven dysfunction is the accumulation of senescent cells (SnCs), but identification and characterization of specific SnCs is limited. To identify age-dependent SnCs, we performed snRNA-Seq on young and old adipose using two independent analytical strategies. The first, a SenMayo-based approach and the second, dependent on SEAC guidelines and Pearson correlation identified senescent nuclei in endothelial clusters. Subsequent subclustering and cell-to-cell communication analyses identified endothelial capillary nuclei that overexpress macrophage migration inhibitory factor (Mif), which exemplifies the specific characteristics and microenvironment of SnCs. Finally, rank analysis identified ion channel transport genes as the most predictive of the SnCs. Overall, these results highlight new defining features of senescence in endothelial adipose tissue and provide novel age-dependent biomarkers.

cell biology↗

bioRxiv2026

Cellular senescence is associated with age-related loss of liver zonation and hepatocyte function

The liver is organized into tightly regulated zones with distinct metabolic functions but zonation erodes with age. Cellular senescence contributes to aging and liver diseases, however, its impact on aging biology is ill-defined. As part of The Cellular Senescence Network Consortium, we used multiple spatial transcriptomics approaches (GeoMx, Visium, CosMx) with snRNA-seq to profile senescence signatures, zonation markers, and metabolic pathways in livers from wild-type (WT) mice of multiple ages. We observed a loss of canonical zone signatures in aged mouse livers characterized by "expansion" of midlobular (zone 2) marker gene expression, accompanied by diminished expression of zone 3 marker genes by middle-age (18 months), indicative of loss of cell identity. Multiple analytic approaches identified distinct age-, zone- and sex-specific senescence signatures, which were significantly associated with zonation markers changes. This was recapitulated in Ercc1 mutant models of accelerated senescence, supporting a causal role of senescent cells in liver aging. A "no-zone" hepatocyte-like cluster expanded with age and with the strongest Senescence-Associated Secretory Phenotype (SASP) profile. Gene expression profiles from senescent hepatocytes implicate decreased WNT signaling and increased BMP as contributing to age-related loss of zonation. Together, these data elucidate the role of senescent cells in driving aging biology in non-diseased liver through disruption of cell:cell signaling and the loss of metabolic and cell identity gene expression necessary for hepatocyte function.

cell biology↗

bioRxiv2026

Cyclin D1 regulates the hepatic response to feeding: Evidence for non-cell cycle roles in the liver

ObjectivesPrior studies have shown that cyclin D1 regulates diverse aspects of liver metabolism during cell cycle progression. Interestingly, this protein is induced in hepatocytes by feeding, but its function in modulating hepatic postprandial physiology is poorly characterized. The aim of this study was to evaluate the contribution of cyclin D1 to the hepatic response to feeding and to gain insight into its potential non-proliferative roles in other conditions. MethodsMice with or without hepatocyte cyclin D1 (D1fl/fl or D1{Delta}Hep) were fasted and refed a high-carbohydrate diet. Mouse and human liver in the setting of aging and MASLD were analyzed. The C. elegans model was used to evaluate the role of cyclin D1 (CYD-1) in response to overnutrition. ResultsCyclin D1 regulated hepatic gene networks involved in glucose and lipid metabolism, protein synthesis, immune response, and other pathways after feeding. Induction of acute phase response proteins was markedly inhibited in D1{Delta}Hep mice, which was associated with corresponding changes in histone acetylation on key genes. In aged liver, hepatocyte cyclin D1 was induced without associated proliferation; this was markedly pronounced in progeroid Ercc1-deficient mice. Cyclin D1 was upregulated in MASLD and diminished with successful treatment. CYD-1 was induced by overnutrition in the intestine of Caenorhabditis elegans (which performs metabolic functions similar to liver) and regulates key nutrient-responsive proteins. CYD-1 inhibition prolonged lifespan in this setting. ConclusionsCyclin D1 regulates nutrient-mediated physiology in the liver and C. elegans, indicating that it has unexpected and highly conserved metabolic functions. Further study is warranted to define its role in hepatic disease and aging. HighlightsO_LICyclin D1 is induced in hepatocytes with feeding and broadly regulates hepatic gene expression. C_LIO_LIAcute phase response (APR) and senescence-associated secretory phenotype (SASP) proteins are markedly regulated by cyclin D1. C_LIO_LIHepatocyte expression of cyclin D1 is substantially upregulated in aging, premature aging, and MASLD without associated proliferation. C_LIO_LICyclin D1 (CYD-1) regulates nutrient-mediated signaling and lifespan in response to overnutrition in C. elegans. C_LI

physiology↗

bioRxiv2026

Dissecting the coordinated progression of cell states in spatial transcriptomics with CoPro

Spatial transcriptomics enables the study of how cells coordinate their molecular states within tissue, providing insight into both normal function and disease processes. A key challenge is to identify gene expression programs that vary continuously across space and are coordinated between cell types. We present CoPro, a computational framework for detecting the spatially coordinated progression of cellular states. CoPro can operate in both supervised and unsupervised modes to identify gene programs that co-vary within or between cell types, and to disentangle multiple overlapping spatial patterns. CoPro can be applied to single-cell-level spatial transcriptomics datasets, including MERFISH, SeqFISH+, Xenium, and histology-imputed transcriptomic data. We demonstrate the utility of CoPro with data collected from colon, brain, liver, and kidney tissues. In the colon, CoPro separates epithelial differentiation along the crypt axis from spatially localized inflammatory signals. In the aging liver, it identifies multiple aging-associated cellular programs superimposed on anatomical zonation. In the brain, the flexible kernel design enables the decoupling of the gene expression gradient along the dorsal-ventral and medial-lateral axes. In the kidney, CoPro identifies tubule-vasculature coordination that is essential in nephron function. These results demonstrate CoPros utility for analyzing spatial coordination of gene expression in complex tissues and disentangling overlapping biological processes, such as anatomical organization and disease-associated variation.

bioinformatics↗

bioRxiv2026

Age-associated increases in inter-individual gene expression variability across human tissues

Aging involves progressive physiological decline, yet the underlying transcriptomic patterns remain poorly understood. Although differentially expressed genes (DEGs) have been the primary focus of previous studies, here we investigate differentially variable genes (DVGs) using a novel Gene Stability Score (GSS). In 30 tissue types from nearly 1,000 individuals in the Genotype-Tissue Expression (GTEx) project, age- and sex-related DVGs account for approximately 15% of overall expression variability between samples of the same tissue, with age-related DVGs specifically contributing 7.7%. We further show that DEGs and DVGs affect distinct biological pathways, and that inter-individual instability is significantly correlated with cell-to-cell transcriptional noise. Moreover, gene regulatory network analysis reveals that this variability is not random but is shaped by local network architecture. Finally, we identify robust reference genes, including TBP, PUM1, and TMEM199, for RT-qPCR experiments in studying age-related gene expression changes in humans. Together, our findings suggest that aging involves both coordinated transcriptional programs and increased stochasticity across individuals and cells.

genomics↗

bioRxiv2026

STEVE: Single-cell Transcriptomics Expression Visualization and Evaluation

Single-cell RNA sequencing (scRNA-seq) has become a key technology for characterizing cell-type heterogeneity in complex tissues. However, its utility depends on accurate and reproducible cell-type annotation, which remains a major analytical challenge. Although hundreds of computational tools have been developed for automated annotation, there is currently no systematic framework to evaluate annotation robustness in a dataset-specific manner or within the context of complete analytical pipelines. Here, we present STEVE (Single-cell Transcriptomics Expression Visualization and Evaluation), a quantitative framework designed to assess the accuracy, robustness, and reproducibility of cell-type annotation in scRNA-seq studies. STEVE implements three complementary in silico evaluation modules: (i) Subsampling Evaluation to quantify annotation stability under varying reference sizes and data partitions; (ii) Novel Cell Evaluation to assess the ability to detect previously unseen cell types; and (iii) Annotation Benchmarking to compare alternative annotation tools against ground-truth labels. In addition, STEVE includes a Reference Transfer Annotation module that enables cross-dataset cell-type mapping using external reference datasets. All modules are built upon a unified probabilistic framework that provides consistent confidence estimation across evaluation scenarios. We evaluated STEVE across four independent scRNA-seq datasets with experimentally defined or expert-curated cell-type labels. Our results show that annotation robustness is strongly influenced by the annotation method, biological separability, dataset complexity, and batch effects. STEVE provides a practical framework for quantifying annotation uncertainty and improving reproducibility in single-cell transcriptomic analyses. STEVE is freely available at GitHub (https://github.com/XiaoDongLab/STEVE).

bioinformatics↗

bioRxiv2025

Comprehensive healthspan assessments and influence of sex as a biological variable in aging rats

Rats share a significant amount of genetic and physiological similarity with humans. Many biological processes and pathways are conserved between rats and humans, making rats a suitable model for studying various aspects of human health and disease. Using rats as an aging model offers a more ethical alternative to using larger, longer-lived animals like primates. Rats are easier to handle in laboratory settings, as compared to non-human primates, both of which have physiological functions like humans. To date, there are very few studies which have comprehensively studied age-related changes in rat physiology. Here we present a longitudinal assessment of several aspects of Brown-Norway rat physiology and histopathology using molecular and functional assessments at 6-, 17- and 27 months of age. Our studies thus provide age-related healthspan parameters, which can be used as reference for genetic or pharmacological rat models of aging.

animal behavior and cognition↗

bioRxiv2025

Uniquely high spontaneous mutational load in blood cells of XP-C patients

We discovered a uniquely high spontaneous somatic mutational load in peripheral blood mononuclear cells (PBMCs) of Xeroderma Pigmentosum group C (XP-C) patients, characterized by elevated single nucleotide variants associated with mutation signatures SBS8 and SBS32, as well as an enrichment of single-nucleotide cytosine deletions. This hypermutability was markedly lower in fibroblasts, suggesting a replication-dependent mechanism of mutagenesis due to deficient global genome nucleotide excision repair (GG-NER). Our findings reveal distinct molecular subtypes within XP defined by spontaneous mutational load in normal blood cells and demonstrate that the exceptionally high mutation burden in XP-C leukemia originates from mutations already present prior to malignant transformation.

genomics↗

bioRxiv2025

Fucoidans are senotherapeutics that enhance SIRT6-dependent DNA repair

Aging is marked by the accumulation of senescent cells (SnCs), which contribute to tissue dysfunction and age-related diseases. Senotherapeutics, including senolytics which specifically induce lysis of SnCs and senomorphics, which suppress the senescence phenotype, represent promising therapeutic interventions for mitigating age-related pathologies and extending healthspan. Using a phenotypic-based senescent cell screening assay, we identified fucoidans, a class of sulfated polysaccharides derived from brown algae and seaweed, as novel senotherapeutics. In particular, fucoidan from Fucus vesiculosus (Fucoidan-FV) displayed potent senomorphic activity in different types of SnCs, reduced senescence in multiple tissues in aged mice, and extended healthspan in a mouse model of accelerated aging. Fucoidan-FV also enhanced the deacetylation and mono-ADP-ribosylation (mADPr) activity of SIRT6 and improved DNA repair and reduced senescence, in part, through SIRT6-dependent pathways. In addition, Fucoidan-FV downregulated genes associated with inflammation, Wnt signaling, and ECM remodeling pathways in SnCs and increased expression of genes involved with DNA repair. These findings support the translational potential of fucoidans as novel senotherapeutics that also are able to improve SIRT6-mediated DNA repair.

cell biology↗

bioRxiv2024

Development of novel flavonoid senolytics through phenotypic drug screening and drug design

Accumulation of senescent cells drives aging and age-related diseases. Senolytics, which selectively kill senescent cells, offer a promising approach for treating many age-related diseases. Using a senescent cell-based phenotypic drug discovery approach that combines drug screening and drug design, we developed two novel flavonoid senolytics, SR29384 and SR31133, derived from the senolytic fisetin. These compounds demonstrated enhanced senolytic activities, effectively eliminating multiple senescent cell types, reducing tissue senescence in vivo, and extending healthspan in a mouse model of accelerated aging. Mechanistic studies utilizing RNA-Seq, machine learning, network pharmacology, and computational simulation suggest that these novel flavonoid senolytics target PARP1, BCL-xL, and CDK2 to induce selective senescent cell death. This phenotype-based discovery of novel flavonoid senolytics, coupled with mechanistic insights, represents a key advancement in developing next-generation senolyticss with potential clinical applications in treating aging and age-related diseases.

cell biology↗

bioRxiv2024

Identification of lipid senolytics targeting senescent cells through ferroptosis induction

Cellular senescence is a key driver of the aging process and contributes to tissue dysfunction and age-related pathologies. Senolytics have emerged as a promising therapeutic intervention to extend healthspan and treat age-related diseases. Through a senescent cell-based phenotypic drug screen, we identified a class of conjugated polyunsaturated fatty acids, specifically -eleostearic acid and its methyl ester derivative, as novel senolytics that effectively killed a broad range of senescent cells, reduced tissue senescence, and extended healthspan in mice. Importantly, these novel lipids induced senolysis through ferroptosis, rather than apoptosis or necrosis, by exploiting elevated iron, cytosolic PUFAs and ROS levels in senescent cells. Mechanistic studies and computational analyses further revealed their key targets in the ferroptosis pathway, ACSL4, LPCAT3, and ALOX15, important for lipid-induced senolysis. This new class of ferroptosis-inducing lipid senolytics provides a novel approach to slow aging and treat age-related disease, targeting senescent cells that are primed for ferroptosis.

cell biology↗

bioRxiv2024

Clonal dynamics and somatic evolution of haematopoiesis in mouse

Haematopoietic stem cells maintain blood production throughout life. While extensively characterised using the laboratory mouse, little is known about how the population is sustained and evolves with age. We isolated stem cells and progenitors from young and old mice, identifying 221,890 somatic mutations genome-wide in 1845 single cell-derived colonies, and used phylogenetic analysis to infer the ontogeny and population dynamics of the stem cell pool. Mouse stem cells and progenitors accrue [~]45 somatic mutations per year, a rate only about 2-fold greater than human progenitors despite the vastly different organismal sizes and lifespans. Phylogenetic patterns reveal that stem and multipotent progenitor cell pools are both established during embryogenesis, after which they independently self-renew in parallel over life. The stem cell pool grows steadily over the mouse lifespan to approximately 70,000 cells, self-renewing about every six weeks. Aged mice did not display the profound loss of stem cell clonal diversity characteristic of human haematopoietic ageing. However, targeted sequencing revealed small, expanded clones in the context of murine ageing, which were larger and more numerous following haematological perturbations and exhibited a selection landscape similar to humans. Our data illustrate both conserved features of population dynamics of blood and distinct patterns of age-associated somatic evolution in the short-lived mouse.

genomics↗

bioRxiv2021

PodoCount: A robust, fully automated whole-slide podocyte quantification tool

BackgroundPodocyte depletion is an established indicator of glomerular injury and predicts clinical outcomes. The semi-quantitative nature of existing podocyte estimation methods or podometrics hinders incorporation of such analysis into experimental and clinical pathologic workflows. Computational image analysis offers a robust approach to automate podometrics through objective quantification of cell and tissue structure. Toward this goal, we developed PodoCount, a computational tool for quantitative analysis of podocytes, and validated the generalizability of the tool across a diverse dataset. MethodsPodocyte nuclei and glomerular boundaries were labeled in murine whole kidney sections, n = 135, from six disease models and human kidney biopsies, n = 45, from diabetic nephropathy (DN) patients. Digital whole slide images (WSIs) of tissues were then acquired. Classical image analysis was applied to obtain podocyte nuclear and glomerular morphometrics. Statistically significant morphometric features, which correlated with each murine disease, were identified. Engineered features were also assessed for their ability to predict outcomes in human DN. PodoCount has been disbursed for other researchers as an open-source, cloud-based computational tool. ResultsPodoCount offers highly accurate quantification of podocytes. Engineered podometric features were benchmarked against routine glomerular histopathology and were found to be significant predictors of disease diagnosis, proteinuria level, and clinical outcomes. ConclusionsPodoCount offers high quantification performance in diverse murine disease models as well as in human DN. Resultant podometric features offers significant correlation with associated metadata as well as outcome. Our cloud-based end-user tool will provide a standardized approach for podometric analysis from gigapixel size WSIs in basic research and clinical practice.

pathology↗