Identification of potential biomarkers and therapeutic targets for liver cirrhosis based on Mendelian randomization and machine learning - PubMed
4 hours ago
- #biomarkers
- #machine-learning
- #liver-cirrhosis
- Identified five hub genes (ENPP2, FAM134B, PPARGC1A, SLFN11, TRIM22) associated with liver cirrhosis (LC).
- Constructed a nomogram risk prediction model with strong predictive performance (AUC = 0.944 in training set, 0.909 in validation set).
- Gene set enrichment analysis linked hub genes to antigen processing, cell adhesion, and immune regulation.
- Abnormal immune cell levels (NK cells, M2 macrophages, dendritic cells, neutrophils) observed in LC.
- Predicted potential therapeutic compounds, including valproic acid and tamoxifen, for LC treatment.