Scientific Reports (Feb 2024)

Multi-omics analysis of a fatty liver model using human hepatocyte chimeric mice

  • Akemi Ichikawa,
  • Daiki Miki,
  • C. Nelson Hayes,
  • Yuji Teraoka,
  • Hikaru Nakahara,
  • Chise Tateno,
  • Yuji Ishida,
  • Kazuaki Chayama,
  • Shiro Oka

DOI
https://doi.org/10.1038/s41598-024-53890-8
Journal volume & issue
Vol. 14, no. 1
pp. 1 – 14

Abstract

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Abstract We developed a fatty liver mouse model using human hepatocyte chimeric mice. As transplanted human hepatocytes do not respond to mouse growth hormone (GH) and tend to accumulate fat, we hypothesized that addition of human GH would alter lipid metabolism and reduce accumulation of fat in the liver even when fed a high-fat diet. Six uPA/SCID chimeric mice were fed a high-fat GAN diet to induce fatty liver while six were fed a normal CRF1 diet, and GH was administered to three mice in each group. The mice were euthanized at 8 weeks, and human hepatocytes were extracted for RNA-Seq, DIA proteomics, and metabolomics analysis. Abdominal echocardiography revealed that the degree of fatty liver increased significantly in mice fed GAN diet (p < 0.001) and decreased significantly in mice treated with GH (p = 0.026). Weighted gene correlation network analysis identified IGF1 and SEMA7A as eigengenes. Administration of GH significantly reduced triglyceride levels and was strongly associated with metabolism of amino acids. MiBiOmics analysis identified perilipin-2 as a co-inertia driver. Results from multi-omics analysis revealed distinct gene expression and protein/metabolite profiles in each treatment group when mice were fed a high-fat or normal diet with or without administration of GH.