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SOMAscan Proteomics Identifies Serum Biomarkers Associated With Liver Fibrosis in Patients With NASH

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 diff...

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Detalles Bibliográficos
Autores principales: Luo, Yi, Wadhawan, Samir, Greenfield, Alex, Decato, Benjamin E., Oseini, Abdul M., Collen, Rebecca, Shevell, Diane E., Thompson, John, Jarai, Gabor, Charles, Edgar D., Sanyal, Arun J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8122380/
https://www.ncbi.nlm.nih.gov/pubmed/34027267
http://dx.doi.org/10.1002/hep4.1670
Descripción
Sumario: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.