open access publication

Article, 2024

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

Nature Communications, ISSN 2041-1723, Volume 15, 1, 10.1038/s41467-024-48956-0

Contributors

Verschuren L. 0000-0002-7847-9037 (Corresponding author) Mak A.L. 0000-0002-2101-161X [1] van Koppen A. 0000-0001-9588-8863 Ozsezen S. Difrancesco S. 0000-0001-7254-3686 Caspers M.P.M. 0000-0002-0248-4008 Snabel J. van der Meer D. 0009-0001-0127-9336 van Dijk A.-M. 0000-0003-0831-527X [1] Rashu E.B. 0000-0002-9958-9024 [2] Nabilou P. 0000-0002-4764-4423 [2] Werge M.P. 0000-0002-9980-1072 [2] van Son K. [1] Kleemann R. Kiliaan A.J. 0000-0002-2158-6210 [3] Hazebroek E.J. [4] Boonstra A. 0000-0001-8607-1616 [5] Brouwer W.P. 0000-0001-8713-1481 [5] Doukas M. 0000-0002-8611-840X [6] Gupta S. Kluft C. [7] Nieuwdorp M. 0000-0002-1926-7659 [1] Verheij J. [1] Gluud L.L. 0000-0002-9462-4468 [2] Holleboom A.G. 0000-0002-2911-2917 [1] Tushuizen M.E. [8] Hanemaaijer R.

Affiliations

  1. [1] Academic Medical Center
  2. [NORA names: Netherlands; Europe, EU; OECD];
  3. [2] Copenhagen University Hospital Hvidovre
  4. [NORA names: Capital Region of Denmark; Hospital; Denmark; Europe, EU; Nordic; OECD];
  5. [3] Radboud University Medical Center
  6. [NORA names: Netherlands; Europe, EU; OECD];
  7. [4] Rijnstate Hospital
  8. [NORA names: Netherlands; Europe, EU; OECD];
  9. [5] Erasmus MC
  10. [NORA names: Netherlands; Europe, EU; OECD];

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.

Funders

  • European-Latin American
  • ZonMw
  • Stichting voor Lever- en Maag-Darm Onderzoek
  • EU Horizon 2020 program
  • Rijnstate-Radboudumc Promotion Fund
  • Health~Holland

Data Provider: Elsevier