Predicting and finding geroprotective compounds through modulating conserved longevity–associated aging modules

Currently, no generalizable tools exist for predicting the impact of interventions on aging using gene expression changes. Here, we build a model for predicting potential geroprotectors by deconstructing the aging transcriptome into coexpression modules and identifying those modulated by life span–extending interventions in Caenorhabditis elegans ( C. elegans ). Many of these modules exhibited adaptive changes during aging that are linked to longevity. Using these longevity-associated modules, we predicted and validated 10 compounds (7 previously unreported) that significantly extended life span in C. elegans . RNA sequencing analysis of two top candidates also showed targeted modulation of our longevity-associated modules. We identified conservation of several modules in mice that were also correlated with frailty. Together, our findings demonstrate that beneficial transcriptomic adaptations occur during aging and that targeting longevity-associated modules offers a framework for geroprotector discovery.

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Publication Details

Journal
Science Advances
Published
2026-09-30
DOI
https://doi.org/10.1126/sciadv.aee3657
Primary Topic
Genetics, Aging, and Longevity in Model Organisms
Type
article
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article

Predicting and finding geroprotective compounds through modulating conserved longevity–associated aging modules

Brian Keith Kennedy, Esther S.P. Wong, Diogo Barardo, Zhuangli Yee et al.
Science Advances
Genetics, Aging, and Longevity in Model Organisms
article

Predicting and finding geroprotective compounds through modulating conserved longevity–associated aging modules

Brian Keith Kennedy, Esther S.P. Wong, Diogo Barardo, Zhuangli Yee, Weihan Huai, Sharah Mae Capinpin, Qingyun Wang, Jasinda H. Lee, Shermaine Thein, Kamil Pabis, Angelica Faye Ga, Jan Gruber, Zongmin Liu, Jun Tan, Stephen D. Raj, Qing Zhang, Shou-Ping Guan, Li-Fang Ng, Shivaanisha Raventhiran
article en

Abstract

Currently, no generalizable tools exist for predicting the impact of interventions on aging using gene expression changes. Here, we build a model for predicting potential geroprotectors by deconstructing the aging transcriptome into coexpression modules and identifying those modulated by life span–extending interventions in Caenorhabditis elegans ( C. elegans ). Many of these modules exhibited adaptive changes during aging that are linked to longevity. Using these longevity-associated modules, we predicted and validated 10 compounds (7 previously unreported) that significantly extended life span in C. elegans . RNA sequencing analysis of two top candidates also showed targeted modulation of our longevity-associated modules. We identified conservation of several modules in mice that were also correlated with frailty. Together, our findings demonstrate that beneficial transcriptomic adaptations occur during aging and that targeting longevity-associated modules offers a framework for geroprotector discovery.

Science AdvancesVol. 12(40)
National University of Singapore (SG), Yale-NUS College (SG), National University Health System (SG)
Openalex Percentile: Top 16%
Genetics, Aging, and Longevity in Model Organisms
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