Research Paper Advance Articles
REVIVE: a computational platform for systematically identifying rejuvenating chemical and genetic perturbations
- 1 Computational Biology Group, CIC bioGUNE-BRTA (Basque Research and Technology Alliance), Bizkaia Technology Park, Derio 48160, Spain
- 2 Department of Biochemistry and Molecular Biology, University of the Basque Country, UPV/EHU, Leioa, Spain
- 3 Computational Biology Group, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette L-4362, Luxembourg
- 4 Ikerbasque, Basque Foundation for Science, Bilbao, Bizkaia 48012, Spain
Received: January 28, 2025 Accepted: November 10, 2025 Published: November 25, 2025
https://doi.org/10.18632/aging.206342How to Cite
Copyright: © 2025 Jung et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Great efforts have been devoted to discovering rejuvenation strategies that counteract age-related functional decline and improve cellular functions in humans. However, new discoveries are currently driven by expert knowledge and require large amounts of resources. Here, we present REVIVE (Rejuvenation Estimation Via Insightful Virtual Experiments), the first computational framework for systematically predicting chemical and genetic perturbations that can restore a youthful transcriptional state based on gene expression data. REVIVE leverages age predictions to detect significant rejuvenating effects and quantifies the impact of perturbations on the hallmarks of aging. When applied to a large-scale in silico screen of more than 10000 compounds and genetic perturbations, REVIVE recapitulates known interventions as well as 477 novel compounds that restore a more youthful transcriptional state improving multiple aging hallmarks. Finally, we demonstrate the utility of REVIVE for repurposing perturbations to revert aged transcriptional states.