Development of a novel non-invasive biomarker panel for hepatic fibrosis in MASLD

Author:

Verschuren LarsORCID,Mak Anne LindeORCID,van Koppen ArianneORCID,Özsezen Serdar,Difrancesco SoniaORCID,Caspers Martien P. M.ORCID,Snabel Jessica,van der Meer DavidORCID,van Dijk Anne-MariekeORCID,Rashu Elias BadalORCID,Nabilou PuriaORCID,Werge Mikkel Parsberg,van Son Koen,Kleemann Robert,Kiliaan Amanda J.ORCID,Hazebroek Eric J.,Boonstra AndréORCID,Brouwer Willem P.,Doukas MichailORCID,Gupta Saurabh,Kluft Cornelis,Nieuwdorp MaxORCID,Verheij Joanne,Gluud Lise LotteORCID,Holleboom Adriaan G.,Tushuizen Maarten E.,Hanemaaijer Roeland

Abstract

AbstractAccurate non-invasive biomarkers to diagnose metabolic dysfunction-associated steatotic liver disease (MASLD)-related fibrosis are urgently needed. This study applies a translational approach to develop a blood-based biomarker panel for fibrosis detection in MASLD. A molecular gene expression signature identified from a diet-induced MASLD mouse model (LDLr−/−.Leiden) is translated into human blood-based biomarkers based on liver biopsy transcriptomic profiles and protein levels in MASLD patient serum samples. The resulting biomarker panel consists of IGFBP7, SSc5D and Sema4D. LightGBM modeling using this panel demonstrates high accuracy in predicting MASLD fibrosis stage (F0/F1: AUC = 0.82; F2: AUC = 0.89; F3/F4: AUC = 0.87), which is replicated in an independent validation cohort. The overall accuracy of the model outperforms predictions by the existing markers Fib-4, APRI and FibroScan. In conclusion, here we show a disease mechanism-related blood-based biomarker panel with three biomarkers which is able to identify MASLD patients with mild or advanced hepatic fibrosis with high accuracy.

Publisher

Springer Science and Business Media LLC

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