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Background <p>Sinusoidal cells are central drivers of chronic liver disease (CLD) progression, yet current biomarkers fail to capture their phenotypic states. We aimed to develop sinusoidal cell-specific biomarkers for the diagnosis and prognosis of CLD.</p> Methods <p>Single-cell RNA sequencing data were analyzed to identify cell-type-specific signatures for liver sinusoidal endothelial cell capillarization, hepatic stellate cell activation, and macrophage polarization. These signatures were integrated into three sinusoidal scores (endothelial, mesenchymal, and macrophage) reflecting dedifferentiation of each cell type. Scores were evaluated in an internal cohort (<i>n</i> = 108) and validated in three independent cohorts (total <i>n</i> = 1008), including patients with 2-year follow-up. Gene expression was quantified in routine or previously archived liver biopsy samples, allowing assessment without additional invasiveness to patients and ensuring global feasibility.</p> Results <p>The sinusoidal scores were significantly elevated in patients with advanced disease and correlated with key clinical endpoints: decompensation (AUROC = 0.896), portal hypertension (HVPG &gt; 12&#xa0;mmHg, AUROC = 0.788), and impaired liver function (MELD &gt; 10, AUROC = 0.898, Child–Pugh B, AUROC = 0.920; Child–Pugh C, AUROC = 0.894). At baseline, scores predicted both fibrosis progression from F3 to F4 (AUROC = 0.827) and clinical decompensation (AUROC = 0.971), as well as fibrosis regression (AUROC = 0.893) and HVPG improvement (AUROC = 0.838) during follow-up.</p> Conclusions <p>Sinusoidal cell-derived scores capture biologically relevant pathways of CLD progression and regression and can be measured from existing biopsy material available in most centers worldwide. Despite their retrospective derivation, these scores hold strong promise for prospective validation and clinical implementation as tools for patient stratification, monitoring, and therapeutic guidance.</p>

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Sinusoidal cell–derived biomarker scores predict diagnosis and prognosis in chronic liver disease

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年2月28日

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  • Sergi Guixé-Muntet,
  • Anabel Fernández-Iglesias,
  • David Lopez,
  • Emilio Tonina,
  • Yiliam Fundora,
  • Anna Zagorska,
  • Jordi Gracia-Sancho

摘要

Background

Sinusoidal cells are central drivers of chronic liver disease (CLD) progression, yet current biomarkers fail to capture their phenotypic states. We aimed to develop sinusoidal cell-specific biomarkers for the diagnosis and prognosis of CLD.

Methods

Single-cell RNA sequencing data were analyzed to identify cell-type-specific signatures for liver sinusoidal endothelial cell capillarization, hepatic stellate cell activation, and macrophage polarization. These signatures were integrated into three sinusoidal scores (endothelial, mesenchymal, and macrophage) reflecting dedifferentiation of each cell type. Scores were evaluated in an internal cohort (n = 108) and validated in three independent cohorts (total n = 1008), including patients with 2-year follow-up. Gene expression was quantified in routine or previously archived liver biopsy samples, allowing assessment without additional invasiveness to patients and ensuring global feasibility.

Results

The sinusoidal scores were significantly elevated in patients with advanced disease and correlated with key clinical endpoints: decompensation (AUROC = 0.896), portal hypertension (HVPG > 12 mmHg, AUROC = 0.788), and impaired liver function (MELD > 10, AUROC = 0.898, Child–Pugh B, AUROC = 0.920; Child–Pugh C, AUROC = 0.894). At baseline, scores predicted both fibrosis progression from F3 to F4 (AUROC = 0.827) and clinical decompensation (AUROC = 0.971), as well as fibrosis regression (AUROC = 0.893) and HVPG improvement (AUROC = 0.838) during follow-up.

Conclusions

Sinusoidal cell-derived scores capture biologically relevant pathways of CLD progression and regression and can be measured from existing biopsy material available in most centers worldwide. Despite their retrospective derivation, these scores hold strong promise for prospective validation and clinical implementation as tools for patient stratification, monitoring, and therapeutic guidance.