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. 2025 Jul;45(7):e70169.
doi: 10.1111/liv.70169.

Prognostic Value of the TLM3 Biomarker Panel for Early Fibrosis Development in MASLD Within the General Population

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Prognostic Value of the TLM3 Biomarker Panel for Early Fibrosis Development in MASLD Within the General Population

Koen C van Son et al. Liver Int. 2025 Jul.

Abstract

Background & aims: Fibrotic MASLD is associated with increased morbidity and mortality, often remaining asymptomatic until advanced stages of disease. Predicting fibrosis onset and progression would improve risk stratification and treatment allocation. This study aims to investigate whether a previously identified fibrosis biomarker panel for active fibrogenesis (TLM3) can serve as a prognostic marker panel for fibrosis development in a population at cardiometabolic risk of fibrotic MASLD.

Methods: The temporal dynamics of a molecular fibrosis gene expression signature associated with histologically proven fibrosis development was investigated in a diet-induced MASLD mouse model (LDLr-/-.Leiden). The corresponding proteins were measured in baseline serum from individuals at risk of MASLD from the general population HELIUS-cohort and correlated with established fibrosis proxies (ELF, VCTE and FIB4) at 7 years follow-up.

Results: The molecular fibrosis gene expression signature was upregulated in a murine MASLD model before the onset of histopathological features of fibrosis. In humans, serum levels of IGFBP7, Ssc5D, Sema4D, VCAN, THBS1 and TNC at baseline correlated with fibrosis proxies at follow-up. IGFBP7 at baseline was able to predict new onset fibrosis, defined as ELF ≥ 9.8 at follow-up in participants with ELF < 9.8 at baseline, with an area under the curve (AUC) of 0.79 (95% CI: 0.64-0.94).

Conclusion: Together, these findings indicate the potential predictive capacity of the TLM3 biomarker panel in early stages of MASLD-fibrosis, both in a murine model as well as in individuals from the general population at risk of MASLD.

Keywords: MASH; biomarker; disease progression; fibrogenesis; non‐invasive.

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Conflict of interest statement

M.N. is on the Scientific Advisory Board of Caelus Pharmaceuticals and Advanced Microbiome Interventions, the Netherlands. However, none of these bear direct relevance to the current manuscript. Other authors have no conflicts of interest.

Figures

FIGURE 1
FIGURE 1
Preclinical mouse model. Histochemically obtained data on hepatic fibrosis and gene expression of genes encoding the proteins in the fibrosis biomarker panel (A) and Sirius Red staining and H&E staining of HDF and Chow‐diet mouse at 12‐ and 24‐weeks (B). *p < 0.05. H&E = haematoxylin and eosin; HFD = high‐fat‐diet.
FIGURE 2
FIGURE 2
Flowchart of inclusions. APRI = AST to platelet ratio; BMI = body mass index; FIB4 = fibrosis‐4 score; LSM = liver stiffness measurement; MASLD = metabolic dysfunction‐associated steatotic liver disease; T2DM = type 2 diabetes mellitus; WHR = waist‐to‐hip circumference.
FIGURE 3
FIGURE 3
Correlogram. Correlogram showing significant Spearman's R correlation between fibrosis biomarkers at baseline and established liver NITs (FIB4, LSM and ELF) at follow‐up. ELF = enhanced liver fibrosis score; FIB4 = fibrosis‐4 score; LSM = liver stiffness measurement.
FIGURE 4
FIGURE 4
IGFBP7 for the detection of new onset fibrosis. Boxplot of the concentration of IGFBP7 at baseline stratified for ELF at follow up in participants with ELF < 9.8 at baseline (A) and ROC curve of IGFBP7 for the detection of ELF ≥ 9.8 in participants with ELF < 9.8 at baseline (B) (n = 70 participants). ***p < 0.005. ELF = enhanced liver fibrosis score; ROC curve = receiver operating characteristic curve.

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References

    1. Estes C., Razavi H., Loomba R., Younossi Z., and Sanyal A. J., “Modeling the Epidemic of Nonalcoholic Fatty Liver Disease Demonstrates an Exponential Increase in Burden of Disease,” Hepatology 67, no. 1 (2018): 123–133. - PMC - PubMed
    1. Thiagarajan P. and Aithal G. P., “Drug Development for Nonalcoholic Fatty Liver Disease: Landscape and Challenges,” Journal of Clinical and Experimental Hepatology 9, no. 4 (2019): 515–521. - PMC - PubMed
    1. Younossi Z. M., Golabi P., Paik J. M., Henry A., Van Dongen C., and Henry L., “The Global Epidemiology of Nonalcoholic Fatty Liver Disease (NAFLD) and Nonalcoholic Steatohepatitis (NASH): A Systematic Review,” Hepatology 77, no. 4 (2023): 1335–1347. - PMC - PubMed
    1. Hardy T., Oakley F., Anstee Q. M., and Day C. P., “Nonalcoholic Fatty Liver Disease: Pathogenesis and Disease Spectrum,” Annual Review of Pathology 11 (2016): 451–496. - PubMed
    1. Nabi O., Lacombe K., Boursier J., Mathurin P., Zins M., and Serfaty L., “Prevalence and Risk Factors of Nonalcoholic Fatty Liver Disease and Advanced Fibrosis in General Population: The French Nationwide NASH‐CO Study,” Gastroenterology 159, no. 2 (2020): 791–793.e2. - PubMed