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Research Paper|Volume 17, Issue 11|pp 2844—2858

REVIVE: a computational platform for systematically identifying rejuvenating chemical and genetic perturbations

Sascha Jung1, Javier Arcos Hodar1,2, Tejwasi Venkata S. Badam3, Antonio del Sol1,3,4
  • 1Computational Biology Group, CIC bioGUNE-BRTA (Basque Research and Technology Alliance), Bizkaia Technology Park, Derio 48160, Spain
  • 2Department of Biochemistry and Molecular Biology, University of the Basque Country, UPV/EHU, Leioa, Spain
  • 3Computational Biology Group, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette L-4362, Luxembourg
  • 4Ikerbasque, Basque Foundation for Science, Bilbao, Bizkaia 48012, Spain
* Equal contribution
Received: January 28, 2025Accepted: November 10, 2025Published: November 25, 2025
https://doi.org/10.18632/aging.206342

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.