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

Area of Science:

• Computational biology
• Aging research
• Genomics

Background:

• Discovering rejuvenation strategies to counteract age-related decline is crucial.
• Current methods rely heavily on expert knowledge and significant resources.
• There is a need for systematic and efficient approaches to identify interventions that restore youthful cellular function.

Purpose of the Study:

• To introduce REVIVE, the first computational framework for predicting chemical and genetic perturbations that promote cellular rejuvenation.
• To systematically identify interventions that restore a youthful transcriptional state using gene expression data.
• To quantify the impact of perturbations on aging hallmarks and facilitate drug repurposing.

Main Methods:

• REVIVE utilizes gene expression data to predict age-related functional decline.
• It employs age predictions to identify rejuvenating effects of perturbations.
• The framework quantifies the impact on hallmarks of aging and screens compounds/genetic perturbations computationally.

Main Results:

• REVIVE successfully recapitulated known rejuvenation interventions in silico.
• The framework identified 477 novel compounds capable of restoring a youthful transcriptional state.
• These compounds were shown to improve multiple aging hallmarks, demonstrating broad efficacy.

Conclusions:

• REVIVE offers a novel computational approach for discovering rejuvenation strategies.
• The framework can systematically predict effective chemical and genetic perturbations.
• REVIVE has the potential to accelerate anti-aging research and drug repurposing efforts.