关键词: Machine learning Mitochondria NASH

Mesh : Non-alcoholic Fatty Liver Disease / genetics pathology Humans Machine Learning Algorithms Mitochondria / genetics metabolism Lipid Metabolism / genetics Aldo-Keto Reductases / genetics metabolism Genes, Mitochondrial

来  源:   DOI:10.1186/s12944-024-02122-z   PDF(Pubmed)

Abstract:
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.
CONCLUSIONS: These three genes are pivotal mitochondrial genes implicated in NASH progression.
摘要:
背景:证据表明肝细胞线粒体功能障碍导致脂质代谢异常,氧化还原不平衡,和程序性细胞死亡,驱动非酒精性脂肪性肝炎(NASH)的发病和进展。识别与NASH相关的中枢线粒体基因可能揭示潜在的治疗靶标。
方法:通过使用134种算法的分析鉴定了与NASH有关的线粒体hub基因。
结果:随机森林算法(RF),134种算法中最有效的,确定了三个基因:Aldo-keto还原酶家族1成员B10(AKR1B10),胸苷酸合成酶(TYMS),和在骨髓细胞2(TREM2)中表达的触发受体。它们被上调,并与促进炎症的基因呈正相关,参与脂质合成的基因,纤维化,NASH患者的非酒精性脂肪性肝炎活动评分。此外,利用这三个基因,NASH患者被准确地归类为第1组,表现出疾病严重程度升高,和集群2,以轻度疾病活动为特征。
结论:这三个基因是与NASH进展有关的关键线粒体基因。
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