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Updated: Aug 10, 2026
Determination of Fatty Acid Oxidation and Lipogenesis in Mouse Primary Hepatocytes
Published on: August 27, 2015
Machine learning-based algorithm identifies key mitochondria-related genes in non-alcoholic steatohepatitis
Longfei Dai1, Renao Jiang1, Zhicheng Zhan1
1Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, 230022, Anhui Province, China.
Background:
Evidence suggests that hepatocyte mitochondrial dysfunction leads to abnormal lipid metabolism, redox imbalance, and programmed cell death, driving the onset and progression of non-alcoholic steatohepatitis (NASH). Identifying hub mitochondrial genes linked to NASH may unveil potential therapeutic targets.
Methods:
Mitochondrial hub genes implicated in NASH were identified via analysis using 134 algorithms.
Results:
The Random Forest algorithm (RF), the most effective among the 134 algorithms, identified three genes: Aldo-keto reductase family 1 member B10 (AKR1B10), thymidylate synthase (TYMS), and triggering receptor expressed in myeloid cell 2 (TREM2). They were upregulated and positively associated with genes promoting inflammation, genes involved in lipid synthesis, fibrosis, and nonalcoholic steatohepatitis activity scores in patients with NASH. Moreover, using these three genes, patients with NASH were accurately categorized into cluster 1, exhibiting heightened disease severity, and cluster 2, distinguished by milder disease activity.
Conclusion:
These three genes are pivotal mitochondrial genes implicated in NASH progression.
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