Population stratification using MASLD polygenic risk score improves severe liver disease prediction by clinical fibrosis scores.

Background and aim: Existing polygenic risk scores (PRS) for severe liver disease (SLD) have limited predictive ability, highlighting a possible reorientation for PRS application in clinical practice.

Methods: Using non-overlapping subsets of the UK Biobank cohort, we first conducted a genome-wide association study of magnetic resonance imaging-derived hepatic fat content (HFC; n = 12,838), and then constructed a polygenic risk score to capture genetically predicted HFC (gHFC), which was applied in an independent sample (n = 426,529) to stratify individuals and evaluate the performance of clinical fibrosis scores.

Results: Among 426,529 participants, 4417 developed SLD during follow-up. gHFC alone showed limited predictive power for SLD, and adding it to fibrosis scores did not improve AUROC. However, population stratification by gHFC substantially improved the performance of Fibrosis-4 (FIB-4), Forns, and Aspartate aminotransferase-to-Platelet Ratio Index (APRI), particularly for hepatocellular carcinoma (HCC). In the highest gHFC quintile, the areas under the receiver operating characteristic curve for HCC were 0.819 (FIB-4), 0.877 (Forns), and 0.851 (APRI), significantly higher than in the lowest quintile. Similar trends were observed using two alternative HFC PRSs.

Conclusion: Stratifying the population by PRS before using clinical fibrosis scores to predict SLD is a more effective approach than considering PRS as an alternative or an addition to clinical risk models.