Advancing biological understanding of cellular senescence with computational multiomics.
Document Type
Article
Publication Date
10-1-2025
Original Citation
Li S,
Agudelo Garcia P,
Aliferis C,
Becich M,
Calyeca J,
Cosgrove B,
Elisseeff J,
Farzad N,
Fertig E,
Glass C,
Gu L,
Hu Q,
Ji Z,
Königshoff M,
LeBrasseur N,
Li D,
Ma A,
Ma Q,
Menon V,
Mitchell J,
Mora A,
Nagaraj S,
Nelson A,
Niedernhofer L,
Rojas M,
Taha H,
Wang J,
Wang S,
Wu P,
Xie J,
Xu M,
Yu M,
Zhang X,
Zhao Y,
Adams P,
Aguayo-Mazzucato C,
Baker D,
Benz C,
Bernlohr D,
Bueno M,
Chen J,
Childs B,
Chuang J,
Chung D,
Dileepan M,
Ding L,
Dong M,
Duncan F,
Enninful A,
Flynn W,
Franco A,
Furman D,
Garovic V,
Halene S,
Herman A,
Hertzel A,
Iwasaki K,
Jeon H,
Kang J,
Karmakar S,
Kirkland J,
Korstanje R,
Kummerfeld E,
Lee J,
Liu Y,
Lu Y,
Lugo-Martinez J,
Martini H,
Melov S,
Musi N,
Passos J,
Peters S,
Rahman I,
Ramasamy R,
Rindone A,
Robbins P,
Robson P,
Rodriguez-Lopez J,
Rosas L,
Rosenthal N,
Schafer M,
Schilling B,
Schmidt E,
Schneider K,
Sengupta K,
Shu J,
So P,
Sun L,
Tchkonia T,
Teneche M,
Vanegas N,
Wang J,
Xie J,
Yin S,
Zhang K,
Zhu Q,
Fan R,
.
Advancing biological understanding of cellular senescence with computational multiomics. Nat Genet. 2025;57(10):2381–94.
Keywords
JGM, JMG, Cellular Senescence, Humans, Computational Biology, Aging, Animals, Genomics, Proteomics, Multiomics
JAX Source
Nat Genet. 2025;57(10):2381–94.
ISSN
1546-1718
PMID
40954249
DOI
https://doi.org/10.1038/s41588-025-02314-y
Grant
This work was supported by SenNet grants, including U54AG079753 (S.L., W.F.F., R.K., N.R., R.R., P.R.), U54AG076041 (C.A., A.C.N., L.J.N., Z.J., E.J.F., E.K., E.L.S., M.D., P.R., S.T.P., M.D.), S.L. is a recipient of a Career Development Award (1398-25) of the Leukemia & Lymphoma Society (2024–2029).
Abstract
Cellular senescence is a complex biological process that plays a pathophysiological role in aging and age-related diseases. The biological understanding of senescence at the cellular and tissue levels remains incomplete due to the lack of specific biomarkers as well as the relative rarity of senescent cells, their phenotypic heterogeneity and dynamic features. This Review provides a comprehensive overview of multiomic approaches for the characterization and biological understanding of cellular senescence. The technical capability and challenges of each approach are discussed, and practical guidelines are provided for selecting tools for identifying, characterizing and spatially mapping senescent cells. The importance of computational analyses in multiomics research, including senescent cell identification, signature detection and interactions of senescent cells with microenvironments, is highlighted. Moreover, tissue-specific case studies and experimental design considerations for individual organs are presented. Finally, future directions and the potential impact of multiomic approaches on the biological understanding of cellular senescence are discussed.