Exploring metabolic space of advanced chronic liver disease regression

Mendoza, Yuly; Tsouka, Sofia; Bosch, Jaime; Berzigotti, Annalisa; Masoodi, Mojgan (2022). Exploring metabolic space of advanced chronic liver disease regression. Journal of hepatology, 77((S1)), pp. 363-364. Elsevier

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Background and aims: Liver fibrosis is the main determinant of
clinical outcomes in advanced chronic liver disease (ACLD) of any
etiology. Regression of bridging fibrosis and cirrhosis can take place
after effective etiological treatment, but not in all cases, suggesting
that factors other than the etiology play a role in the modulation of
this important outcome. In patients achieving regression of ACLD,
liver function markedly improves, suggesting that several metabolic
pathways are influenced by regression of fibrosis. However, the
metabolic pathways associated with fibrosis regression in ACLD have
not been characterized. We hypothesize that thorough assessment of
liver metabolism could provide evidence-based data for better
characterization of cirrhosis patients with regression following
effective etiological treatment, thus providing a rational basis for
personalized interventions.
Method: We performed a case-control pilot study of 60 patients with
ACLD of different etiologies, 30 with histological and/or clinical
evidence of regression of ACLD (Regressors) and 30 without any
improvement (Non-regressors) after a minimum of 24 months of
successful etiological therapy. We used the combination of metabolic
modelling and metabolic profiling to define metabolic pathways and
associated signature that differentiate Regressors from Non-regres-
sors. We have developed a transcriptomics-driven metabolic model-
ling approach to assess the regression of ACLD. We further
investigated the associated metabolic signature using mass spec-
trometry-based metabolomics.
Results: Although Regressors and Non-regressors showed similar
profiles at baseline, our observation is pointing to fatty acid β-
oxidation and arachidonic acid metabolism (associated to inflamma-
tion and oxidative stress) as key metabolic pathways differentiating
Regressors from Non-regressors after therapy, suggesting that lipid
metabolism plays a central role in the modulation of the extracellular
matrix in ACLD. In addition, Using Least Absolute Shrinkage and
Selection Operator (LASSO) analyses, the Regressor phenotype was
predicted with 80% accuracy based on the levels of identified lipid
markers after etiologic therapy.

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