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

Lars Verschuren; Anne Linde Mak; Arianne van Koppen; Serdar Özsezen; Sonia Difrancesco; Martien P.M. Caspers; Jessica Snabel; David van der Meer; Anne Marieke van Dijk; Elias Badal Rashu; Puria Nabilou; Mikkel Parsberg Werge; Koen van 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; Roeland Hanemaaijer

doi:10.1038/s41467-024-48956-0

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

Lars Verschuren^*, Anne Linde Mak, Arianne van Koppen, Serdar Özsezen, Sonia Difrancesco, Martien P.M. Caspers, Jessica Snabel, David van der Meer, Anne Marieke van Dijk, Elias Badal Rashu, Puria Nabilou, Mikkel Parsberg Werge, Koen van Son, Robert Kleemann, Amanda J. Kiliaan, Eric J. Hazebroek, André Boonstra, Willem P. Brouwer, Michail Doukas, Saurabh GuptaCornelis Kluft, Max Nieuwdorp, Joanne Verheij, Lise Lotte Gluud, Adriaan G. Holleboom, Maarten E. Tushuizen, Roeland Hanemaaijer

^*Corresponding author for this work

Nutrition and Disease

Research output: Contribution to journal › Article › Academic › peer-review

36 Citations (Scopus)

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.

Original language	English
Article number	4564
Journal	Nature Communications
Volume	15
DOIs	https://doi.org/10.1038/s41467-024-48956-0
Publication status	Published - 29 May 2024

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Verschuren, L., Mak, A. L., van Koppen, A., Özsezen, S., Difrancesco, S., Caspers, M. P. M., Snabel, J., van der Meer, D., van Dijk, A. M., Rashu, E. B., Nabilou, P., Werge, M. P., van Son, K., Kleemann, R., Kiliaan, A. J., Hazebroek, E. J., Boonstra, A., Brouwer, W. P., Doukas, M., ... Hanemaaijer, R. (2024). Development of a novel non-invasive biomarker panel for hepatic fibrosis in MASLD. Nature Communications, 15, Article 4564. https://doi.org/10.1038/s41467-024-48956-0

@article{3032f245c5b6414aab042b08bb44e7d5,

title = "Development of a novel non-invasive biomarker panel for hepatic fibrosis in MASLD",

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.",

author = "Lars Verschuren and Mak, \{Anne Linde\} and \{van Koppen\}, Arianne and Serdar {\"O}zsezen and Sonia Difrancesco and Caspers, \{Martien P.M.\} and Jessica Snabel and \{van der Meer\}, David and \{van Dijk\}, \{Anne Marieke\} and Rashu, \{Elias Badal\} and Puria Nabilou and Werge, \{Mikkel Parsberg\} and \{van Son\}, Koen and Robert Kleemann and Kiliaan, \{Amanda J.\} and Hazebroek, \{Eric J.\} and Andr{\'e} Boonstra and Brouwer, \{Willem P.\} and Michail Doukas and Saurabh Gupta and Cornelis Kluft and Max Nieuwdorp and Joanne Verheij and Gluud, \{Lise Lotte\} and Holleboom, \{Adriaan G.\} and Tushuizen, \{Maarten E.\} and Roeland Hanemaaijer",

year = "2024",

month = may,

day = "29",

doi = "10.1038/s41467-024-48956-0",

language = "English",

volume = "15",

journal = "Nature Communications",

issn = "2041-1723",

publisher = "Nature",

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Verschuren, L, Mak, AL, van Koppen, A, Özsezen, S, Difrancesco, S, Caspers, MPM, Snabel, J, van der Meer, D, van Dijk, AM, Rashu, EB, Nabilou, P, Werge, MP, van Son, K, Kleemann, R, Kiliaan, AJ, Hazebroek, EJ, Boonstra, A, Brouwer, WP, Doukas, M, Gupta, S, Kluft, C, Nieuwdorp, M, Verheij, J, Gluud, LL, Holleboom, AG, Tushuizen, ME & Hanemaaijer, R 2024, 'Development of a novel non-invasive biomarker panel for hepatic fibrosis in MASLD', Nature Communications, vol. 15, 4564. https://doi.org/10.1038/s41467-024-48956-0

TY - JOUR

T1 - Development of a novel non-invasive biomarker panel for hepatic fibrosis in MASLD

AU - Verschuren, Lars

AU - Mak, Anne Linde

AU - van Koppen, Arianne

AU - Özsezen, Serdar

AU - Difrancesco, Sonia

AU - Caspers, Martien P.M.

AU - Snabel, Jessica

AU - van der Meer, David

AU - van Dijk, Anne Marieke

AU - Rashu, Elias Badal

AU - Nabilou, Puria

AU - Werge, Mikkel Parsberg

AU - van Son, Koen

AU - Kleemann, Robert

AU - Kiliaan, Amanda J.

AU - Hazebroek, Eric J.

AU - Boonstra, André

AU - Brouwer, Willem P.

AU - Doukas, Michail

AU - Gupta, Saurabh

AU - Kluft, Cornelis

AU - Nieuwdorp, Max

AU - Verheij, Joanne

AU - Gluud, Lise Lotte

AU - Holleboom, Adriaan G.

AU - Tushuizen, Maarten E.

AU - Hanemaaijer, Roeland

PY - 2024/5/29

Y1 - 2024/5/29

N2 - 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.

AB - 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.

U2 - 10.1038/s41467-024-48956-0

DO - 10.1038/s41467-024-48956-0

M3 - Article

C2 - 38811591

AN - SCOPUS:85194898730

SN - 2041-1723

VL - 15

JO - Nature Communications

JF - Nature Communications

M1 - 4564

ER -

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

Abstract

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