Combined stem cell and predictive models reveal flavin cofactors as targets in metabolic liver dysfunction

Abstract

Drug discovery for multifactorial diseases like metabolic dysfunction-associated steatotic liver disease (MASLD) remains challenging due to inadequate models and untargeted drug screenings. We combined stem-cell-based modeling with computational drug predictions identifying flavin pathways as therapeutic targets in MASLD. For disease stage-specific discovery, we established a MASLD testing model, compounding metabolic triggers to intensify mitochondrial crisis. In vitro injuries included adipo- and myokines, immune cell co-culture, and genomic risk factors. Benchmarking experiments revealed similarities with advanced human MASLD. To query therapeutic compounds, protein-protein-interaction networks, weighted gene co-expression, and knowledge graph-based analyses independently predicted flavin adenine dinucleotide (FAD) as an anti-MASLD factor. Dysregulated flavoproteomes in vitro and in vivo-in pediatric and adult MASLD patients- supported our flavin network-focused strategy. We established therapeutic FAD concentrations to mitigate metabolic injury and fibro-inflammation in human multicellular liver organoids and other assays. We enhanced therapeutic FAD effects through genetic mitochondrial biogenic augmentation and identified orally available flavo-active compounds--including Aspirin--restoring mitochondrial respiration. Our study demonstrates how integrating stem cell-derived disease modeling with computed drug predictions can expedite therapeutic discovery.