A Quantitative Systems Pharmacology Platform Reveals NAFLD Pathophysiological States and Targeting Strategies

• Published in: Metabolites Vol. 12; no. 6; p. 528
• Main Authors: Lefever, Daniel E, Miedel, Mark T, Pei, Fen, DiStefano, Johanna K, Debiasio, Richard, Shun, Tong Ying, Saydmohammed, Manush, Chikina, Maria, Vernetti, Lawrence A, Soto-Gutierrez, Alejandro, Monga, Satdarshan P, Bataller, Ramon, Behari, Jaideep, Yechoor, Vijay K, Bahar, Ivet, Gough, Albert, Stern, Andrew M, Taylor, D Lansing
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 07.06.2022; MDPI
• Subjects: Biomarkers; Clinical trials; Diabetes; Drugs; Fatty liver; Fibrosis; Gene expression; Health risk assessment; Inflammation; liver; Liver diseases; MAFLD; metabolic-associated fatty liver disease; Metabolism; microphysiology systems; NAFLD; non-alcoholic fatty liver disease; Nuclear receptors; Pathogenesis; Pathophysiology; Patients; Precision medicine; Steatosis; NAFLD; non-alcoholic fatty liver disease; network proximity; liver; lobular inflammation; CMap; targeting disease states; NASH; QSP; drug combinations; MAFLD; MPS; microphysiology systems; drug repurposing; drug discovery; quantitative systems pharmacology; connectivity map; fibrosis; metabolic-associated fatty liver disease; steatosis; non-alcoholic steatohepatitis
• ISSN: 2218-1989; 2218-1989
• DOI: 10.3390/metabo12060528

Non-alcoholic fatty liver disease (NAFLD) has a high global prevalence with a heterogeneous and complex pathophysiology that presents barriers to traditional targeted therapeutic approaches. We describe an integrated quantitative systems pharmacology (QSP) platform that comprehensively and unbiasedly defines disease states, in contrast to just individual genes or pathways, that promote NAFLD progression. The QSP platform can be used to predict drugs that normalize these disease states and experimentally test predictions in a human liver acinus microphysiology system (LAMPS) that recapitulates key aspects of NAFLD. Analysis of a 182 patient-derived hepatic RNA-sequencing dataset generated 12 gene signatures mirroring these states. Screening against the LINCS L1000 database led to the identification of drugs predicted to revert these signatures and corresponding disease states. A proof-of-concept study in LAMPS demonstrated mitigation of steatosis, inflammation, and fibrosis, especially with drug combinations. Mechanistically, several structurally diverse drugs were predicted to interact with a subnetwork of nuclear receptors, including pregnane X receptor (PXR; NR1I2), that has evolved to respond to both xenobiotic and endogenous ligands and is intrinsic to NAFLD-associated transcription dysregulation. In conjunction with iPSC-derived cells, this platform has the potential for developing personalized NAFLD therapeutic strategies, informing disease mechanisms, and defining optimal cohorts of patients for clinical trials.