Babaodan alleviates MAFLD through hepatic glycerophospholipid metabolism and PPARγ/RXRA/GPAT3 based on spatial metabolomics and proteomics analysis.

Babaodan (BBD), a traditional Chinese medicine formula with a history of clinical use, has been extensively applied in the treatment of various hepatic disorders, but its multi-target mechanisms of metabolic dysfunction-associated fatty liver disease (MAFLD) remain unclear and limit its scientific development. This study aimed to reveal the systems pharmacology of BBD in MAFLD, going beyond phenomenological descriptions to identify its key mechanistic axis and tissue-level therapeutic effects. We employed an integrative multi-omics strategy in a high-fat diet-induced murine MAFLD model. Sequential untargeted metabolomics, quantitative proteomics, and spatially resolved Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI) characterized the disease pathological landscape and BBD's effects. Datasets were integrated via correlation (Mantel test) and joint pathway analysis, with key targets validated by Western blot. BBD systemically reversed dyslipidemia, steatosis, and inflammation. Multi-omics analysis revealed its normalization of dysregulated glycerophospholipid metabolism and PPAR signaling. Proteomics identified the enzyme GPAT3 and nuclear receptor RXRA as key network hubs. Spatial metabolomics visualized BBD's unique capacity to restore the metabolite gradients across liver tissue. Integration converged on a key axis which BBD therapeutically regulates the PPARγ/RXRA/GPAT3. Strong correlations linked GPAT3 to phospholipid PE(34:2) and RXRA to the oxidized lipid, functionally connecting this axis to metabolic regulation. We elucidate that BBD regulates a multi-target, systems-level restoration of hepatic homeostasis primarily via the PPARγ/RXRA/GPAT3. This axis coordinates lipid metabolism and inflammatory signaling, focusing on the repair of both molecular networks and tissue metabolic architecture. Our work provides a mechanistic blueprint for BBD and a novel, network-targeting strategy for complex metabolic diseases.