Blood metabolic panels for identifying significant fibrosis and inflammation in patients with MASLD
Metabolic dysfunction-associated steatotic liver disease (MASLD) remains a prevalent condition with limited diagnostic and therapeutic options. This study aims to identify metabolic signatures of disease progression and develop non-invasive diagnostic models through three independent cohorts (including two cohorts confirmed by biopsy and one cohort confirmed by ultrasound) involving 293 participants for detecting significant fibrosis (>F2) and mild to severe inflammatory activity (>I2) using multiple machine learning. Fibrosis Panel shows AUROCs of 0.928 (95%CI 0.835-0.978), 0.829 (0.732-0.902), and 0.806 (0.724-0.872) in Discovery Cohort, Validation Cohort 1 and Validation Cohort 2, respectively, outperforming the FIB-4, APRI, NFS, LSM and MACK-3. Inflammation Panel achieves AUROCs of 0.894 (0.791-0.957) and 0.776 (0.673-0.859) in Discovery Cohort and Validation Cohort 1, respectively. Key metabolites guanidinoacetic acid (GAA) and sebacic acid (SA) demonstrate therapeutic efficacy in mice. These validated panels provide accurate stratification of MASLD severity, and GAA/SA offer therapeutic potential, advancing both diagnosis and treatment strategies.