期刊
HEPATOLOGY COMMUNICATIONS
卷 5, 期 5, 页码 760-773出版社
JOHN WILEY & SONS LTD
DOI: 10.1002/hep4.1670
关键词
-
资金
- Bristol Myers Squibb
NASH is a major cause of liver-related morbidity and mortality, with liver fibrosis stage linked to mortality risk. Current noninvasive diagnostics are unable to differentiate fibrosis stages in NASH patients, highlighting the need for noninvasive biomarkers to identify high-risk individuals. An exploratory classifier based on proteomics showed promising results in distinguishing advanced fibrosis in NASH patients, performing similarly or better than other existing models.
Nonalcoholic steatohepatitis (NASH) is a major cause of liver-related morbidity and mortality worldwide. Liver fibrosis stage, a key component of NASH, has been linked to the risk of mortality and liver-related clinical outcomes. Currently there are no validated noninvasive diagnostics that can differentiate between fibrosis stages in patients with NASH; many existing tests do not reflect underlying disease pathophysiology. Noninvasive biomarkers are needed to identify patients at high-risk of NASH with advanced fibrosis. This was a retrospective study of patients with histologically proven NASH with fibrosis stages 0-4. The SOMAscan proteomics platform was used to quantify 1,305 serum proteins in a discovery cohort (n = 113). In patients with advanced (stages 3-4) versus early fibrosis (stages 0-2), 97 proteins with diverse biological functions were differentially expressed. Next, fibrosis-stage classification models were explored using a machine learning-based approach to prioritize the biomarkers for further evaluation. A four-protein model differentiated patients with stage 0-1 versus stage 2-4 fibrosis (area under the receiver operating characteristic curve [AUROC] = 0.74), while a 12-protein classifier differentiated advanced versus early fibrosis (AUROC = 0.83). Subsequently, the model's performance was validated in two independent cohorts (n = 71 and n = 32) with similar results (AUROC = 0.74-0.78). Our advanced fibrosis model performed similarly to or better than Fibrosis-4 index, aspartate aminotransferase-to-platelet ratio index, and nonalcoholic fatty liver disease (NAFLD) fibrosis score-based models for all three cohorts. Conclusion: A SOMAscan proteomics-based exploratory classifier for advanced fibrosis, consisting of biomarkers that reflect the complexity of NASH pathophysiology, demonstrated similar performance in independent validation cohorts and performed similarly or better than Fibrosis-4 index, aspartate aminotransferase-to-platelet ratio index, and NAFLD fibrosis score. Further studies are warranted to evaluate the clinical utility of these biomarker panels in patients with NAFLD.
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