A Multi-omics and Machine Learning Framework Identifies Plasma SBDS as a Causal Biomarker and Therapeutic Target in Primary Sclerosing Cholangitis (IMAGE)
Caption
Our integrated multi-omics and machine learning framework makes two key, interconnected contributions. First, it establishes a robust nine-gene expression signature with high accuracy for PSC diagnosis and stratification, offering a readily accessible molecular tool. Second, it profoundly advances our mechanistic understanding by establishing disrupted ribosome homeostasis as a causal pathway in PSC, specifically nominating plasma SBDS protein as a key protective factor and a high-priority therapeutic target through genetic causal inference. This work therefore not only provides a powerful biomarker panel for clinical use but also moves beyond genetic associations to reveal a druggable, causal mechanism. The strategy outlined here provides a generalizable blueprint for translating complex disease genetics into causal biomarkers and mechanistic therapeutic hypotheses.
Credit
Guangming Li, Yabo Ouyang
Usage Restrictions
Credit must be given to the creator. Only noncommercial uses of the work are permitted.
License
CC BY-NC