aging; computational modeling; drug repurposing; machine learning; rejuvenation
Abstract :
[en] 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.
Disciplines :
Life sciences: Multidisciplinary, general & others
Author, co-author :
Jung, Sascha; Computational Biology Group, CIC bioGUNE-BRTA (Basque Research and Technology Alliance), Bizkaia Technology Park, Derio 48160, Spain
Hodar, Javier Arcos; Computational Biology Group, CIC bioGUNE-BRTA (Basque Research and Technology Alliance), Bizkaia Technology Park, Derio 48160, Spain ; Department of Biochemistry and Molecular Biology, University of the Basque Country, UPV/EHU, Leioa, Spain
Badam, Tejwasi Venkata S; Computational Biology Group, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette L-4362, Luxembourg
Del Sol, Antonio; Computational Biology Group, CIC bioGUNE-BRTA (Basque Research and Technology Alliance), Bizkaia Technology Park, Derio 48160, Spain ; Computational Biology Group, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette L-4362, Luxembourg ; Ikerbasque, Basque Foundation for Science, Bilbao, Bizkaia 48012, Spain
DEL SOL MESA, Antonio ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Computational Biology
External co-authors :
yes
Language :
English
Title :
REVIVE: a computational platform for systematically identifying rejuvenating chemical and genetic perturbations.
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