Identifying Molecular Targets for Reverse Aging Using Integrated Network Analysis of Transcriptomic and Epigenomic Changes During Aging

In this study, researchers analyzed DNA methylation and RNA sequencing data from 51 healthy adults aged 20 to 74 to identify aging-related epigenetic and transcriptomic biomarkers. They reconstructed a gene regulatory network model and performed signal flow analysis to find candidate molecular targets that could reverse these biomarkers. Curcumin was identified as a potential therapeutic agent, as it was found to bind and inhibit JUN, a candidate target. The study demonstrated the utility of network models for integrative omics analysis, which could aid in understanding regulatory mechanisms and developing anti-aging therapies.