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      Modeling Steatohepatitis in Humans with Pluripotent Stem Cell-Derived Organoids

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          Abstract

          Human organoid systems recapitulate in vivo organ architecture, yet fail to capture complex pathologies such as inflammation and fibrosis. Here, using 11 different healthy and diseased pluripotent stem cell lines, we developed a reproducible method to derive multi-cellular human liver organoids composed of hepatocyte-, stellate- and Kupffer-like cells that exhibit transcriptomic resemblance to in vivo derived tissues. Under free fatty acid treatment, organoids, but not reaggregated cocultured spheroids, recapitulated key features of steatohepatitis including steatosis, inflammation and fibrosis phenotypes in a successive manner. Interestingly, an organoid-level biophysical readout with atomic force microscopy demonstrated that organoid stiffening reflects the fibrosis severity. Furthermore, organoids from patients with genetic dysfunction of lysosomal acid lipase phenocopied severe steatohepatitis, rescued by FXR agonism-mediated reactive oxygen species suppression. The presented key methodology and preliminary results offer a new approach for studying personalized basis for inflammation and fibrosis in human, thus facilitating the discovery of effective treatments. Ouchi et al. develop a reproducible method to generate multi-cellular human liver organoids from iPSC/ESCs. The organoids recapitulate progressive features of steatohepatitis including steatosis, inflammation and fibrosis. A patient-derived organoid with lysosomal acid lipase deficiency exhibits the exaggerated steatohepatitis phenotype, as seen in vivo , and can be rescued by FGF19.

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          Author and article information

          Journal
          Cell Metabolism
          Cell Metabolism
          Elsevier BV
          15504131
          May 2019
          May 2019
          Article
          10.1016/j.cmet.2019.05.007
          6687537
          31155493
          8f5db256-264c-42fe-917c-e532da9e4532
          © 2019

          https://www.elsevier.com/tdm/userlicense/1.0/

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