Hepatology through the crystal ball

The heterogeneity of cirrhosis - systemically assessed endotypes described by fibrosis, apoptosis, and immunoregulatory-related biomarkers

BACKGROUND

Given the heterogeneity of advanced chronic liver disease, assessing disease activity-related biomarkers could aid in classifying cirrhosis endotypes for better patient monitoring and treatment selection.

AIM

To investigate cirrhosis endotypes described by disease activity biomarkers related to fibrogenesis, immune cell activity, apoptosis, and systemic inflammation.

METHODS

The study included plasma EDTA samples from 106 participants with mild, moderate, and severe liver cirrhosis undergoing hepatic venous pressure gradient (HVPG) measurements and 39 healthy control participants. The biomarkers nordicPROC3™ (fibrogenesis), GDF-15, CK18 M30 (apoptosis), CRP (systemic inflammation), nordicCPa9-HNE™ (neutrophil activity), and nordicVICM™ (macrophage activity) were measured.

RESULTS

PROC3, GDF-15, CK18 M30, and CRP increased with cirrhosis severity (p < 0.05-p < 0.0001) and the degree of portal hypertension (p < 0.05-p < 0.01). CPa9-HNE decreased from mild to moderate and mild to severe cirrhosis (p < 0.01-0.0001) and correlated with HVPG (r=-0.53, p < 0.0001). VICM decreased from mild to severe cirrhosis (p < 0.01). A heatmap clustered analysis revealed four potential cirrhosis endotypes, reflecting underlying biological processes.

CONCLUSION

Assessing markers related to active fibrogenesis, apoptosis, immune cell activity, and systemic inflammation revealed distinct molecular patterns among patients with cirrhosis. These findings suggest the presence of potential disease endotypes that could inform future strategies for patient monitoring, treatment selection, and prognostic assessment in cirrhosis management.

Addressing the heterogeneity in liver diseases using biological networks

The abnormalities in human metabolism have been implicated in the progression of several complex human diseases, including certain cancers. Hence, deciphering the underlying molecular mechanisms associated with metabolic reprogramming in a disease state can greatly assist in elucidating the disease aetiology. An invaluable tool for establishing connections between global metabolic reprogramming and disease development is the genome-scale metabolic model (GEM). Here, we review recent work on the reconstruction of cell/tissue-type and cancer-specific GEMs and their use in identifying metabolic changes occurring in response to liver disease development, stratification of the heterogeneous disease population and discovery of novel drug targets and biomarkers. We also discuss how GEMs can be integrated with other biological networks for generating more comprehensive cell/tissue models. In addition, we review the various biological network analyses that have been employed for the development of efficient treatment strategies. Finally, we present three case studies in which independent studies converged on conclusions underlying liver disease.