ArticleCell reports2023
Integration of transcriptomes of senescent cell models with multi-tissue patient samples reveals reduced COL6A3 as an inducer of senescence.
Article in Cell reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 20 citations in OpenAlex.
- SenFlag gene signature identifies senescent cells in mouse and human tissues through a conserved core transcriptional program.The EMBO journal · 2026Article
- Substrate Stiffness and Viscoelasticity Influence Fibroblast Senescence.Journal of biomedical materials research. Part A · 2026Article
- A conserved regulatory architecture stabilizes cellular senescence across distinct triggers in human fibroblasts.GeroScience · 2026Article
- Exploring molecular signatures of senescence with marker, an R Toolkit for evaluating gene sets as phenotypic markers.NAR genomics and bioinformatics · 2026Article
- Regenerative Approaches to Enhance the Skin Microenvironment and Boost Aesthetic Efficacy: A Narrative Review.International journal of molecular sciences · 2026Review
- Senescence profiling and biomarker identification in cell product based on adipose tissue-derived mesenchymal stromal cells.Stem cells translational medicine · 2026Article
- Integrated analysis of differential m6A methylation and transcriptome profiles in ovaries of young and aged Qira black sheep.BMC genomics · 2026Article
- Genetic associations of circulating plasma proteins with cardiometabolic diseases.Genome biology · 2026Article
- SARS-CoV-2 uptake and inflammatory response in senescent endothelial cells are regulated by the BSG/VEGFR2 pathway.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Oncogene-Induced Senescence Transcriptomes Signify Premalignant Colorectal Adenomas.Current issues in molecular biology · 2025Article
- Revealing age-related changes in the intraocular microenvironment and senescence modulators using aqueous humor proteomics and machine learning.Frontiers in cell and developmental biology · 2025Article
- Identification of potential biomarkers for atrial fibrillation and stable coronary artery disease based on WGCNA and machine algorithms.BMC cardiovascular disorders · 2024Article
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Authors and funding
21 authors at 6 institutions in 5 countries.
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Abstract
Senescent cells are a major contributor to age-dependent cardiovascular tissue dysfunction, but knowledge of their in vivo cell markers and tissue context is lacking. To reveal tissue-relevant senescence biology, we integrate the transcriptomes of 10 experimental senescence cell models with a 224 multi-tissue gene co-expression network based on RNA-seq data of seven tissues biopsies from ∼600 coronary artery disease (CAD) patients. We identify 56 senescence-associated modules, many enriched in CAD GWAS genes and correlated with cardiometabolic traits-which supports universality of senescence gene programs across tissues and in CAD. Cross-tissue network analyses reveal 86 candidate senescence-associated secretory phenotype (SASP) factors, including COL6A3. Experimental knockdown of COL6A3 induces transcriptional changes that overlap the majority of the experimental senescence models, with cell-cycle arrest linked to modulation of DREAM complex-targeted genes. We provide a transcriptomic resource for cellular senescence and identify candidate biomarkers, SASP factors, and potential drivers of senescence in human tissues.
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