Advancing biological understanding of cellular senescence with computational multiomics

Sheng Li^{1

2

3}, Paula A Agudelo Garcia⁴, Constantin Aliferis⁵, Michael J Becich⁶, Jazmin Calyeca⁴, Benjamin D Cosgrove⁷, Jennifer Elisseeff⁸, Negin Farzad⁹, Elana J Fertig¹⁰, Carolyn Glass¹¹, Liangcai Gu¹², Qianjiang Hu¹³, Zhicheng Ji¹⁴, Melanie Königshoff¹³, Nathan K LeBrasseur¹⁵, Dongmei Li¹⁶, Anjun Ma¹⁷, Qin Ma¹⁷, Vilas Menon¹⁸, Jacob T Mitchell¹⁹, Ana L Mora⁴, Sushma Nagaraj¹⁹, Andrew C Nelson²⁰, Laura J Niedernhofer²¹, Mauricio Rojas⁴, Hash Brown Taha²², Jinhua Wang²³, Siyuan Wang²⁴, Pei-Hsun Wu²⁵, Jichun Xie²⁶, Ming Xu^{27

28}, Miao Yu^{29

30}, Xu Zhang^{15

31}, Yue Zhao^{29

30}, Peter D Adams³², Cristina Aguayo-Mazzucato³³, Darren J Baker³⁴, Christopher Benz³⁵, David A Bernlohr²¹, Marta Bueno¹³, Jin Chen¹⁸, Bennett G Childs³⁴, Jeffrey H Chuang^{29

30}, Dongjun Chung¹⁷, Mythili Dileepan²¹, Li Ding³⁶, Mingze Dong⁹, Francesca Duncan³⁷, Archibald Enninful⁹, William F Flynn^{29

30}, Ana Catarina Franco¹⁵, David Furman³⁵, Vesna Garovic³⁸, Stephanie Halene⁹, Allison B Herman³⁹, Ann V Hertzel²¹, Kanako Iwasaki³³, Hyeongseon Jeon¹⁷, Jeon Woong Kang⁴⁰, Shilpita Karmakar^{29

30}, James L Kirkland⁴¹, Ron Korstanje^{29

30}, Erich Kummerfeld⁴², Jun Hee Lee⁴³, Yang Liu²², Yao Lu⁹, Jose Lugo-Martinez⁴⁴, Helene Martini¹⁵, Simon Melov³⁵, Nicolas Musi⁴¹, João F Passos¹⁵, Samuel T Peters²¹, Irfan Rahman¹⁶, Ramalakshmi Ramasamy^{29

30}, Alexandra N Rindone²⁵, Paul D Robbins²¹, Paul Robson^{29

30}, Jhonny Rodriguez-Lopez⁴, Lorena Rosas⁴, Nadia Rosenthal^{29

30}, Marissa J Schafer¹⁵, Birgit Schilling³⁵, Elizabeth L Schmidt²¹, Kevin Schneider³⁵, Kaustav Sengupta^{29

30}, Jian Shu⁴⁵, Peter T C So⁴⁶, Li Sun¹², Tamar Tchkonia⁴¹, Marcos G Teneche³², Natalia Vanegas⁴, Julia Wang³⁶, Juan Xie¹⁷, Shanshan Yin³², Ke Zhang⁴⁵, Quan Zhu⁴⁷, Rong Fan⁹; SenNet Consortium

Affiliations

¹ Department of Cancer Biology, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA. sheng.li@med.usc.edu.
² The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA. sheng.li@med.usc.edu.
³ The Jackson Laboratory, Maine, ME, USA. sheng.li@med.usc.edu.
⁴ Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, the Ohio State University, Columbus, OH, USA.
⁵ Medical School and Institute for Health Informatics, University of Minnesota, Minneapolis, MN, USA.
⁶ Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
⁷ Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, USA.
⁸ Johns Hopkins University, Baltimore, MD, USA.
⁹ Department of Biomedical Engineering, Yale University, New Haven, CT, USA.
¹⁰ Institute for Genome Sciences, School of Medicine, University of Maryland, College Park, MD, USA.
¹¹ Department of Pathology, Duke University, Durham, NC, USA.
¹² Department of Biochemistry, School of Medicine, University of Washington, Seattle, WA, USA.
¹³ Center for Lung Aging and Regeneration, Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
¹⁴ Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC, USA.
¹⁵ Robert and Arlene Kogod Center on Aging, Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, USA.
¹⁶ Department of Clinical and Translational Research, University of Rochester Medical Center, Rochester, NY, USA.
¹⁷ Department of Biomedical Informatics, the Ohio State University, Columbus, OH, USA.
¹⁸ Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA.
¹⁹ Department of Oncology, Johns Hopkins University, Baltimore, MD, USA.
²⁰ Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA.
²¹ Masonic Institute on the Biology of Aging and Metabolism, Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, MN, USA.
²² Department of Cancer Biology, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
²³ Masonic Cancer Center and Institute for Health Informatics, University of Minnesota, Minneapolis, MN, USA.
²⁴ Department of Genetics, Department of Cell Biology, Yale School of Medicine, Yale University, New Haven, CT, USA.
²⁵ Institute for NanoBioTechnology, Johns Hopkins University, Baltimore, MD, USA.
²⁶ Department of Biostatistics and Bioinformatics, Department of Mathematics, Duke University, Durham, NC, USA.
²⁷ Institute on the Biology of Aging and Metabolism, University of Minnesota, Minneapolis, MN, USA.
²⁸ Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, MN, USA.
²⁹ The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA.
³⁰ The Jackson Laboratory, Maine, ME, USA.
³¹ Department of Biochemistry and Molecular Biology, Mayo Clinic, Rochester, MN, USA.
³² Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA.
³³ Islet Cell Biology and Regenerative Medicine, Joslin Diabetes Center, Boston, MA, USA.
³⁴ Department of Biochemistry and Molecular Biology, Department of Pediatrics, Mayo Clinic, Rochester, MN, USA.
³⁵ Buck Institute for Research on Aging, Novato, CA, USA.
³⁶ Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA.
³⁷ Department of Obstetrics and Gynecology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
³⁸ Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, USA.
³⁹ Laboratory of Cardiovascular Science, National Institute on Aging, Baltimore, MD, USA.
⁴⁰ Laser Biomedical Research Center, Massachusetts Institute of Technology, Cambridge, MA, USA.
⁴¹ Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
⁴² Institute for Health Informatics, University of Minnesota, Minneapolis, MN, USA.
⁴³ Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, MI, USA.
⁴⁴ Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.
⁴⁵ Cutaneous Biology Research Center, Massachusetts General Hospital, Boston, MA, USA.
⁴⁶ Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
⁴⁷ Department of Cellular and Molecular Medicine, University of California San Diego, San Diego, CA, USA.

PMID: 40954249
DOI: 10.1038/s41588-025-02314-y

Review

Advancing biological understanding of cellular senescence with computational multiomics

Sheng Li et al. Nat Genet. 2025 Oct.

. 2025 Oct;57(10):2381-2394.

doi: 10.1038/s41588-025-02314-y. Epub 2025 Sep 15.

Authors

Affiliations

¹ Department of Cancer Biology, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA. sheng.li@med.usc.edu.
² The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA. sheng.li@med.usc.edu.
³ The Jackson Laboratory, Maine, ME, USA. sheng.li@med.usc.edu.
⁴ Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, the Ohio State University, Columbus, OH, USA.
⁵ Medical School and Institute for Health Informatics, University of Minnesota, Minneapolis, MN, USA.
⁶ Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
⁷ Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, USA.
⁸ Johns Hopkins University, Baltimore, MD, USA.
⁹ Department of Biomedical Engineering, Yale University, New Haven, CT, USA.
¹⁰ Institute for Genome Sciences, School of Medicine, University of Maryland, College Park, MD, USA.
¹¹ Department of Pathology, Duke University, Durham, NC, USA.
¹² Department of Biochemistry, School of Medicine, University of Washington, Seattle, WA, USA.
¹³ Center for Lung Aging and Regeneration, Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
¹⁴ Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC, USA.
¹⁵ Robert and Arlene Kogod Center on Aging, Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, USA.
¹⁶ Department of Clinical and Translational Research, University of Rochester Medical Center, Rochester, NY, USA.
¹⁷ Department of Biomedical Informatics, the Ohio State University, Columbus, OH, USA.
¹⁸ Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA.
¹⁹ Department of Oncology, Johns Hopkins University, Baltimore, MD, USA.
²⁰ Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA.
²¹ Masonic Institute on the Biology of Aging and Metabolism, Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, MN, USA.
²² Department of Cancer Biology, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
²³ Masonic Cancer Center and Institute for Health Informatics, University of Minnesota, Minneapolis, MN, USA.
²⁴ Department of Genetics, Department of Cell Biology, Yale School of Medicine, Yale University, New Haven, CT, USA.
²⁵ Institute for NanoBioTechnology, Johns Hopkins University, Baltimore, MD, USA.
²⁶ Department of Biostatistics and Bioinformatics, Department of Mathematics, Duke University, Durham, NC, USA.
²⁷ Institute on the Biology of Aging and Metabolism, University of Minnesota, Minneapolis, MN, USA.
²⁸ Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, MN, USA.
²⁹ The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA.
³⁰ The Jackson Laboratory, Maine, ME, USA.
³¹ Department of Biochemistry and Molecular Biology, Mayo Clinic, Rochester, MN, USA.
³² Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA.
³³ Islet Cell Biology and Regenerative Medicine, Joslin Diabetes Center, Boston, MA, USA.
³⁴ Department of Biochemistry and Molecular Biology, Department of Pediatrics, Mayo Clinic, Rochester, MN, USA.
³⁵ Buck Institute for Research on Aging, Novato, CA, USA.
³⁶ Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA.
³⁷ Department of Obstetrics and Gynecology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
³⁸ Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, USA.
³⁹ Laboratory of Cardiovascular Science, National Institute on Aging, Baltimore, MD, USA.
⁴⁰ Laser Biomedical Research Center, Massachusetts Institute of Technology, Cambridge, MA, USA.
⁴¹ Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
⁴² Institute for Health Informatics, University of Minnesota, Minneapolis, MN, USA.
⁴³ Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, MI, USA.
⁴⁴ Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.
⁴⁵ Cutaneous Biology Research Center, Massachusetts General Hospital, Boston, MA, USA.
⁴⁶ Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
⁴⁷ Department of Cellular and Molecular Medicine, University of California San Diego, San Diego, CA, USA.

PMID: 40954249
DOI: 10.1038/s41588-025-02314-y

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.

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Conflict of interest statement

Competing interests: L.G. is a cofounder of TopoGene; N.K.L. and Mayo Clinic have intellectual property related to this research, which has been reviewed by the Mayo Clinic Conflict of Interest Review Board and was conducted in compliance with its policies; S.W. is a co-inventor of the MERFISH technology patented by Harvard University; D.J.B. has a potential financial interest related to this research as a co-inventor on patents held by Mayo Clinic and patent applications licensed to or filed by Unity Biotechnology and is also a shareholder in Unity Biotechnology, with research reviewed and conducted in compliance with Mayo Clinic Conflict of Interest policies; B.G.C. has similar financial interests as a co-inventor on Mayo Clinic patents and is a Unity Biotechnology shareholder; M.J.S. and Mayo Clinic have intellectual property related to this research, reviewed and conducted in compliance with Mayo Clinic Conflict of Interest policies; J.H.L. is an inventor on a patent and pending patent applications related to Seq-Scope; R.F. is a scientific cofounder and advisor for IsoPlexis, Singleron Biotechnologies and AtlasXomics. J.L.K. and T.T. have financial interest related to this research, including patents and pending patents covering senolytic drugs and their uses held by Mayo Clinic. This research has been reviewed by the Mayo Clinic Conflict of Interest Review Board and was conducted in compliance with Mayo Clinic and Cedars-Sinai conflict-of-interest policies. All other authors declare no competing interests.

References

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Advancing biological understanding of cellular senescence with computational multiomics

Affiliations

Advancing biological understanding of cellular senescence with computational multiomics

Authors

Affiliations

Abstract

Conflict of interest statement

References

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Grants and funding

LinkOut - more resources

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