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.