XGBoost-SHAP Interpretable Modeling Identifies and Validates an Eight-Gene Biomarker for Hepatic Encephalopathy Risk...

Cirrhosis, accounting for 2.4% of global mortality in 2019, represents a leading cause of death in chronic liver disease. Hepatic encephalopathy (HE), a decompensated complication of cirrhosis, is associated with a median survival of only 0.92 years post-diagnosis. Current screening methods relying on neuropsychological tests (e.g., Psychometric Hepatic Encephalopathy Score, PHES) have limitations such as time-consuming procedures and subjective interpretation, potentially delaying diagnosis. To address this, we integrated four cirrhotic transcriptomic cohorts (GSE41919, GSE57193, GSE139602, and GSE15654) and employed an integrated algorithm (LASSO [Least Absolute Shrinkage and Selection Operator]-RFE [Recursive Feature Elimination]-random forest) to identify HE-specific biomarker genes. Ultimately, we developed an HE risk-prediction system centered on eight HE-specific marker genes, namely, PRB2, TUBA1C, NPC2, LRRC32, TLN1, SOX9, SERPINA3 and RNASE4. Based on these genes, an XGBoost (eXtreme Gradient Boosting)-based HE risk stratification model was constructed, and SHAP (SHapley Additive exPlanations) analysis was further introduced to address the "black-box" limitation of conventional machine learning models and to improve the interpretability. The finalized eight-gene system enables accurate, efficient, and interpretable HE risk assessment in patients with cirrhosis. Functional characterization through gene set enrichment analysis and structural equation modeling further revealed that these marker genes converge on four interconnected biological processes, namely, metabolic homeostasis, synaptic and neural transmission, immune inflammatory signaling, and hepatic detoxification, which collectively reflect the gut-liver-brain axis disruption central to HE pathogenesis. This dual-model system, incorporating both cirrhosis progression and survival prognosis, provides a reliable and clinically applicable tool for early HE risk warning and stratification, reducing the limitations of traditional neuropsychological screening and offering a translational foundation for timely intervention and prognostic optimization in high-risk cirrhotic patients.