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PreprintCited by 28Telomeres, Telomerase, and SenescenceGenetics, Aging, and Longevity in Model OrganismsSingle-cell and spatial transcriptomics

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Robust senescence evaluation by transcriptome-based hUSI to facilitate characterizing cellular senescence under various conditions

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Ni, Ting, Wang, Jing, Wang, Weixu, Yao, Jun, Zhou, Xiaolan, Wei, Gang·2024·Nature Aging
DOI 10.21203/rs.3.rs-3920908/v1PMC PMC12176644

Preprint — published as 10.1038/s43587-025-00886-2 · Paper page

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Abstract

Despite the manifestation and contribution of cellular senescence to tissue aging and aging-related disease, the identification of in vivo senescent cells and the recognition of senescence-specific communication still remain challenging. Current senescence evaluation methods rely greatly on expression level of well-known senescence markers, enrichment of aging-related gene sets or weighted sum of curated genes. However, focusing on limited senescence aspects, these methods could not adequately capture the comprehensive senescence features. To evaluate senescence in a more general and unbiased way from the most common and easily accessible transcriptome data, we developed human universal senescence index (hUSI) to quantify human cellular senescence based on a series of weighted genes learned from representative senescence RNA-seq profiles using a machine learning algorithm. hUSI demonstrated its superior performance in distinguishing senescent samples under various conditions and robustness in handling batch effects and sparse profiles. hUSI could uncover the accumulation of senescent cells of various cell types in complex pathological conditions, and reflected the increasing senescence burden of patients and provided potential senotherapeutic targets. Furthermore, combined with gaussian mixture model, hUSI successfully inferred senescent tumor cells in melanoma and identified key target signaling pathways that are beneficial for patient prognosis. Overall, hUSI provides a valuable choice to improve our ability in characterizing cellular senescence under various conditions, illustrating promising implications in aging studies and clinical situations.

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Metadata

Authors
Ni, T., Wang, J., Wang, W., Yao, J., Zhou, X., & Wei, G.
Affiliations
Fudan University (CN)
Corresponding author
  • Ni, Ting
  • Wang, Weixu
  • Wei, Gang
ORCID
Venue
Nature Aging
Publisher
Springer Science and Business Media LLC
Published
2024-02-13
Volume
5
Issue
6
Pages
1159-1175
ISSN
2662-8465 (ISSN-L)
DOI
10.21203/rs.3.rs-3920908/v1
PMC
PMC12176644
OpenAlex
W4410866579
Cited by
28
References
6
Citations by year
2026: 21 · 2025: 7
FWCI
18.02
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Aging (publishedVersion, cc-by-nc-nd)
  • Research Square (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
Funders
  • National Natural Science Foundation of China (92249302, 32370592)
  • National Key Research and Development Program of China ([2021YFA0909300], 2023YFC3603300)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Telomeres, Telomerase, and Senescence
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
Keywords
cellular senescence, transcriptome, senescent cell accumulation, COVID-19 pandemic, melanoma, prognosis, aging, senescence heterogeneity
MeSH terms
COVID-19, SARS-CoV-2, Aging, Humans, Melanoma, Cellular Senescence, Gene Expression Profiling, Transcriptome

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