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

Lars Verschuren (), Anne Linde Mak, Arianne Koppen, Serdar Özsezen, Sonia Difrancesco, Martien P. M. Caspers, Jessica Snabel, David Meer, Anne-Marieke Dijk, Elias Badal Rashu, Puria Nabilou, Mikkel Parsberg Werge, Koen Son, Robert Kleemann, Amanda J. Kiliaan, Eric J. Hazebroek, André Boonstra, Willem P. Brouwer, Michail Doukas, Saurabh Gupta, Cornelis Kluft, Max Nieuwdorp, Joanne Verheij, Lise Lotte Gluud, Adriaan G. Holleboom, Maarten E. Tushuizen and Roeland Hanemaaijer
Additional contact information
Lars Verschuren: TNO Healthy Living & Work
Anne Linde Mak: Amsterdam University Medical Centers
Arianne Koppen: TNO Healthy Living & Work
Serdar Özsezen: TNO Healthy Living & Work
Sonia Difrancesco: TNO Healthy Living & Work
Martien P. M. Caspers: TNO Healthy Living & Work
Jessica Snabel: TNO Healthy Living & Work
David Meer: GenomeScan
Anne-Marieke Dijk: Amsterdam University Medical Centers
Elias Badal Rashu: University of Copenhagen
Puria Nabilou: University of Copenhagen
Mikkel Parsberg Werge: University of Copenhagen
Koen Son: Amsterdam University Medical Centers
Robert Kleemann: TNO Healthy Living & Work
Amanda J. Kiliaan: Radboud University Medical Center, Donders Institute for Brain, Cognition, and Behavior
Eric J. Hazebroek: Wageningen University
André Boonstra: Erasmus MC University Medical Center
Willem P. Brouwer: Erasmus MC University Medical Center
Michail Doukas: Erasmus MC Cancer Institute
Saurabh Gupta: Bristol Meyers Squibb
Cornelis Kluft: Good Biomarker Sciences
Max Nieuwdorp: Amsterdam University Medical Centers
Joanne Verheij: Amsterdam University Medical Centers
Lise Lotte Gluud: University of Copenhagen
Adriaan G. Holleboom: Amsterdam University Medical Centers
Maarten E. Tushuizen: Leiden University Medical Center
Roeland Hanemaaijer: TNO Healthy Living & Work

Nature Communications, 2024, vol. 15, issue 1, 1-14

Abstract: Abstract Accurate 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.

Date: 2024
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DOI: 10.1038/s41467-024-48956-0

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