Am J Physiol Heart Circ Physiol. 2026 Apr 13. doi: 10.1152/ajpheart.00057.2026. Online ahead of print.
ABSTRACT
Background: Compared to men, women with similar coronary artery calcification (CAC) scores face higher cardiovascular disease (CVD) mortality. Objectives: We posited that circulatory factors, like blood-borne extracellular vesicles (EVs) and metabolites, may be associated with the development of CAC and subsequent CVD in postmenopausal women. Additionally, we hypothesized that a history of preeclampsia (PE), a sex-specific risk factor, might be a contributing factor. Methods: Clinical data were obtained from medical records for postmenopausal women (median age 60 years) free of cardiovascular events with (n=29) and without (n=29) CAC. EVs per µL plasma were quantified by digital flow cytometry, and plasma metabolites were measured using gas chromatography-mass spectrometry. CACs were measured by computer tomography and reported as Agatston score. Results: Patients with, versus those without, CAC demonstrated i) less favorable cardiovascular and metabolic profiles; ii) elevation in six EVs populations, including those positive for TF (tissue factor), CD3 (T-cells), SM22α (smooth muscle cells), Pref-1 (adipocytes), FABP4 (adipocytes/macrophages) and p16 (senescent cells); iii) significantly higher levels of proline, allothreonine (amino acid metabolism) and ribitol (carbohydrate metabolism), and lower levels of lactic acid (carbohydrate metabolism); and iv) significantly increased risk of developing CVD and chronic kidney disease (CKD) (P<0.05 for all). In the CAC positive group, women with PE vs those with normotensive pregnancy histories, demonstrated 4-times higher risk of developing cardiovascular events or CKD later in life (P=0.028). Conclusions: Selected plasma metabolites, EVs and PE history could serve as biomarkers of and potential therapeutic targets for CAC and CVD in postmenopausal women.
PMID:41973512 | DOI:10.1152/ajpheart.00057.2026
EMBO J. 2026 Apr 10. doi: 10.1038/s44318-026-00762-8. Online ahead of print.
ABSTRACT
Cellular senescence is defined as an irreversible growth arrest observed when cells are exposed to a variety of stressors, including DNA damage, oxidative stress, or nutrient deprivation. Although senescence is a well-established driver of aging and age-related diseases, it is a highly heterogeneous process with significant variations across organisms, tissues, and cell types. The relatively low abundance of senescent cells in healthy aged tissues poses a major challenge to the longitudinal study of senescence in specific organs, including the human lung. To overcome this limitation, we developed a positive-unlabeled learning framework to generate a comprehensive list of senescence marker genes in human lungs (termed SenSet) using the largest publicly available single-cell lung dataset, the Human Lung Cell Atlas (HLCA). We validated SenSet in a highly complex ex vivo human 3D lung tissue culture model subjected to the senescence inducers bleomycin, doxorubicin, or irradiation, and established its sensitivity and accuracy in characterizing senescence. Using SenSet, we identified and validated cell-type-specific senescence signatures in distinct lung cell populations upon aging and environmental exposure. Our study provides a comprehensive analysis of senescent cells in the healthy aging lung, presenting fundamental implications for our understanding of major lung diseases, including cancer, fibrosis, chronic obstructive pulmonary disease, or asthma.
PMID:41963555 | DOI:10.1038/s44318-026-00762-8
EMBO Mol Med. 2026 Apr 1. doi: 10.1038/s44321-026-00400-0. Online ahead of print.
ABSTRACT
Cellular senescence drives aging and age-related dysfunction across multiple tissues, including the brain. Through a high-content, senescent cell-based phenotypic screen of a small panel of natural products, we identified tomatidine, an aglycone of tomatine found in tomatoes, as a previously unrecognized senotherapeutic agent. In senescent human brain microvascular endothelial cells and fibroblasts, tomatidine selectively suppressed SASP expression without affecting p16Ink4a or p21Cip1 levels consistent with a senomorphic effect. In aged mice, tomatidine reduced frailty and improved motor coordination and cognitive performance. These functional benefits were accompanied by reduced senescence markers (p16 Ink4a, p21 Cip1, and telomere-associated DNA damage foci) in liver, skin, and hippocampal neurons, along with decreased neuroinflammation and microglial activation. Tomatidine also diminished brain endothelial cell senescence while enhancing tight junction protein expression, suggesting preserved blood-brain barrier integrity. Together, these findings identify tomatidine as a promising senescence-targeting compound with beneficial effects in aged mice and support its further evaluation in mechanistic and translational studies.
PMID:41922652 | DOI:10.1038/s44321-026-00400-0
Eur Respir J. 2026 Mar 12:2501272. doi: 10.1183/13993003.01272-2025. Online ahead of print.
ABSTRACT
Aging is a crucial factor in the development of chronic lung diseases, including chronic obstructive pulmonary disease (COPD), idiopathic pulmonary fibrosis (IPF), and lung cancer. Marking the 10th anniversary of the original "Hallmarks of the aging lung" published in this Journal, we present an updated review highlighting key cellular and molecular features of aging that drive the onset and progression of these conditions. Aging stands as the most significant risk factor for chronic lung diseases, which are characterised by structural and functional changes such as reduced elasticity, persistent inflammation, and impaired repair capacity. Recent evidence confirms that nearly all recognised hallmarks of aging play a role in the pathogenesis of these diseases. Notably, extracellular matrix (ECM) dysregulation - first proposed as a lung aging hallmark in 2015 - has become an integral aspect of aging in lung disease. Environmental exposures, such as cigarette or wildfire smoke, accelerate age-related changes by increasing oxidative stress, promoting cellular senescence, and disrupting tissue homeostasis. In lung cancer, aging contributes to genomic alterations, epigenetic dysregulation, immune evasion, and therapeutic resistance. Additionally, the roles of extracellular vesicles and microbiome changes in shaping these aging phenotypes are emerging areas of research. Early clinical studies are now targeting specific aging hallmarks, such as cellular senescence, with the goal of reducing age-related pathology and improving outcomes. Overall, integrating aging biology into lung disease research paves the way for innovative diagnostic and therapeutic strategies that address common molecular mechanisms across multiple chronic lung conditions.
PMID:41819537 | DOI:10.1183/13993003.01272-2025
Sci Adv. 2026 Mar 13;12(11):eaea1492. doi: 10.1126/sciadv.aea1492. Epub 2026 Mar 11.
ABSTRACT
Cell migration underlies immune surveillance, tissue repair, embryogenesis, and-when dysregulated-tumor metastasis. Yet unlike proliferation, which can be profiled at scale, migration studies remain limited by labor-intensive imaging and analysis. Existing assays often forfeit single-cell resolution, require phototoxic fluorescent labeling, or depend on tedious manual tracking, restricting the range of molecular perturbations and microenvironmental contexts that can be examined. We present Deep learning Brightfield Imaging and cell Tracking (DeepBIT), a high-throughput platform that captures live-cell behavior in multiwell plates and uses a convolutional neural network to detect and track individual cells in brightfield videos-without labels or user bias. Brightfield images are paired with nuclear fluorescence images to generate diverse ground-truth datasets, enabling automated training and eliminating manual annotation. This scalability supports a data-driven approach to systematically dissect the regulation of cell migration. Using breast cancer cells as a testbed, we tracked ~1500 cells per well across 840 conditions-including 96 FDA-approved drugs at multiple doses, a range of extracellular matrix and growth factor combinations, and CRISPR knockouts of cytoskeletal genes-yielding ~1.3 million trajectories in 30 hours (~2 minutes per condition). This dataset revealed previously unrecognized motility modulators among FDA-approved compounds and uncovered strong context dependence; for example, TNF-α and RhoA could either suppress or promote migration in the same cells depending on extracellular cues. Together, DeepBIT provides an unbiased, label-free platform for single-cell motility profiling at a scale compatible with modern drug libraries and genomic perturbation tools, enabling systematic exploration and therapeutic targeting of cell migration.
PMID:41811952 | PMC:PMC12978223 | DOI:10.1126/sciadv.aea1492