Article ; Online: Integration of deep learning-based histopathology and transcriptomics reveals key genes associated with fibrogenesis in patients with advanced NASH.
Cell reports. Medicine
2023 Volume 4, Issue 4, Page(s) 101016
Abstract: Nonalcoholic steatohepatitis (NASH) is the most common chronic liver disease globally and a leading cause for liver transplantation in the US. Its pathogenesis remains imprecisely defined. We combined two high-resolution modalities to tissue samples from ...
| Abstract | Nonalcoholic steatohepatitis (NASH) is the most common chronic liver disease globally and a leading cause for liver transplantation in the US. Its pathogenesis remains imprecisely defined. We combined two high-resolution modalities to tissue samples from NASH clinical trials, machine learning (ML)-based quantification of histological features and transcriptomics, to identify genes that are associated with disease progression and clinical events. A histopathology-driven 5-gene expression signature predicted disease progression and clinical events in patients with NASH with F3 (pre-cirrhotic) and F4 (cirrhotic) fibrosis. Notably, the Notch signaling pathway and genes implicated in liver-related diseases were enriched in this expression signature. In a validation cohort where pharmacologic intervention improved disease histology, multiple Notch signaling components were suppressed. |
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| MeSH term(s) | Humans ; Non-alcoholic Fatty Liver Disease/complications ; Transcriptome/genetics ; Deep Learning ; Disease Progression ; Liver Cirrhosis/genetics ; Liver Cirrhosis/drug therapy |
| Language | English |
| Publishing date | 2023-06-01 |
| Publishing country | United States |
| Document type | Journal Article ; Research Support, Non-U.S. Gov't |
| ISSN | 2666-3791 |
| ISSN (online) | 2666-3791 |
| DOI | 10.1016/j.xcrm.2023.101016 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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