Molecular characterization of chronic liver disease dynamics: From liver fibrosis to acute-on-chronic liver failure

Abstract

Background & aims: The molecular mechanisms driving the progression from early-chronic liver disease (CLD) to cirrhosis and, finally, acute-on-chronic liver failure (ACLF) are largely unknown. Our aim was to develop a protein network-based approach to investigate molecular pathways driving progression from early-CLD to ACLF.

Methods: Transcriptome analysis was performed on liver biopsies from patients at different liver disease stages, including fibrosis, compensated cirrhosis, decompensated cirrhosis and ACLF, and control healthy livers. We created 9 liver-specific disease-related protein-protein interaction networks capturing key pathophysiological processes potentially related to CLD. We used these networks as a framework and performed gene set-enrichment analysis (GSEA) to identify dynamic gene profiles of disease progression.

Results: Principal component analyses revealed that samples clustered according to the disease stage. GSEA of the defined processes showed an upregulation of inflammation, fibrosis and apoptosis networks throughout disease progression. Interestingly, we did not find significant gene expression differences between compensated and decompensated cirrhosis, while ACLF showed acute expression changes in all the defined liver disease-related networks. The analyses of disease progression patterns identified ascending and descending expression profiles associated with ACLF onset. Functional analyses showed that ascending profiles were associated with inflammation, fibrosis, apoptosis, senescence and carcinogenesis networks, while descending profiles were mainly related to oxidative stress and genetic factors. We confirmed by qPCR the upregulation of genes of the ascending profile and validated our findings in an independent patient cohort.

Conclusion: ACLF is characterized by a specific hepatic gene expression pattern related to inflammation, fibrosis, apoptosis, senescence and carcinogenesis. Moreover, the observed profile is significantly different from that of compensated and decompensated cirrhosis, supporting the hypothesis that ACLF should be considered a distinct entity.

Lay summary: By using transjugular biopsies obtained from patients at different stages of chronic liver disease, we unveil the molecular pathogenic mechanisms implicated in the progression of chronic liver disease to cirrhosis and acute-on-chronic liver failure. The most relevant finding in this study is that patients with acute-on-chronic liver failure present a specific hepatic gene expression pattern distinct from that of patients at earlier disease stages. This gene expression pattern is mostly related to inflammation, fibrosis, angiogenesis, and senescence and apoptosis pathways in the liver.

Keywords: ACLF; ACLF, acute-on-chronic liver failure; CC, compensated cirrhosis; CLD, chronic liver disease; CRP, C-reactive protein; DC, decompensated cirrhosis; DEGs, differentially expressed genes; GSEA, gene set-enrichment analyses; HCC, hepatocellular carcinoma; HSC, hepatic stellate cells; KRT-18, keratin-18; LDRN, liver disease-related protein-protein interaction network; NAFLD, non-alcoholic fatty liver disease; PCA, principal component analysis; biomarker; chronic liver disease; network biology; temporal gene expression profile.

Graphical abstract

Fig. 1

Transcriptome analysis of patients with distinct liver chronic disease stages and ACLF. (A) PCA plots are presented for all 39 samples after including batch effects as covariates in the linear model. The first PC is displayed on the X axis and the second PC on the Y axis, with the corresponding percentage of total variance explained by each PC. Dots in the plot represent individual samples colored by disease condition: green for liver donors (healthy), pink early-CLD, orange compensated cirrhosis, blue decompensated cirrhosis and green ACLF, and shape indicating the sample processing date. (B) Unsupervised hierarchical clustering analysis of the 39 samples after normalization and batch adjustment. Each leave in the tree represents a liver sample from an individual and each color the disease condition. ACLF, acute-on-chronic liver failure; eCLD, early chronic liver disease; PC, principal component; PCA, principal component analysis.

Fig. 2

Differentially expressed genes across liver disease stages and ACLF. DEGs in each disease condition at 1.5-fold change and adjusted p value <0.05. (A) Total number of up- and downregulated genes between all pairs of comparisons are shown as a graph where nodes are sample groups and edges represent the number of DEGs between them. Disease conditions compared with healthy donors are highlighted in red and green for up and downregulated genes respectively and the edge width corresponding to the change magnitude. ACLF compared to the other disease conditions is colored in black. (B) The Venn diagram represents the overlap between sets of DEGs in each disease condition compared with liver donors. ACLF, acute-on-chronic liver failure; CC, compensated cirrhosis; DC, decompensated cirrhosis; DEGs, differentially expressed genes; eCLD, early chronic liver disease.

Fig. 3

Enrichment analyses of liver disease-related networks. Gene set enrichment analysis using as gene sets: i) the list of disease-related processes defined in the seeds or ii) the extended networks and as a dataset the pairwise comparisons between disease stages. Significantly enriched gene sets are colored ranked on NES showing only NES for tests with p value ≤0.05 and FDR ≤0.25. Significantly up- and downregulated gene sets are highlighted in red and blue respectively. The number in the orange circles represent the number of genes included in the gene sets (seeds or Extended networks) significantly overrepresented (p value ≤0.05) while the number within the green circles indicate the number of genes found significantly under-represented. ACLF, acute-on-chronic liver failure; CC, compensated cirrhosis; DC, decompensated cirrhosis; eCLD, early chronic liver disease; FDR, false discovery rate; HCC, hepatocellular carcinoma; HSC, hepatic stellate cell; NES, normalized enrichment scores

Fig. 4

Disease signatures. Temporal expression profiles were grouped into 4 signatures (top) ascending profiles, (bottom) descending profiles, (left) profiles associated with progressive disease progression and (right) profiles related to acute progression or related to ACLF development. Word Clouds between profiles visualize the most significantly enriched GO terms, KEGG and Reactome pathways using as input the ascending and descending signatures constructed. In the middle of the figure, we represent the curated disease-related processes significantly overrepresented by the ascending (red) and descending signatures (cyan), analyzing only the lists of disease-related genes (seeds) or the high-confidence binary subnetworks (wordcloud plot generated with rquery.wordcloud function from http://www.sthda.com). ACLF, acute-on-chronic liver failure; GO, gene ontology; HCC, hepatocellular carcinoma; HSC, hepatic stellate cell.

Fig. 5

Hepatic gene expression of selected genes from the ascending and descending ACLF profiles along disease progression. Hepatic gene expression levels of genes included in the ascending signature: CXCL6, ITGA2, KRT 18, SPINK-1 and the descending signature: AKRD1D1, DGAT2, F3B, GSTA were assessed by qPCR. The analysis includes patients with early-CLD (n = 5), CC (n = 8), DC (n = 12), ACLF (n = 8) and healthy controls (n = 6). Data are represented as as mean ± SEM. Levels of significance: ∗p <0.05; (Mann-Whitney U test). ACLF, acute-on-chronic liver failure; CC, compensated cirrhosis; DC, decompensated cirrhosis; eCLD, early chronic liver disease.

Fig. 6

Histological analysis of the presence of ductular reaction, inflammation, angiogenesis and fibrosis along disease progression. (A) KRT7, MPO, VWF and collagen staining from a representative liver section obtained from patients with eCLD, DC and ACLF and control. (B) Quantification of stained area per field of view. Patients included in the analysis presented early-CLD (n = 4), CC (n = 4), ACLF (n = 4) and healthy controls (n = 4). The bars of all graphs represent the mean ± SEM. Levels of significance: ∗p <0.05; (Mann-Whitney U test). ACLF, acute-on-chronic liver failure; CLD, chronic liver disease; DC, decompensated cirrhosis; eCLD, early chronic liver disease; KRT7, keratin-7; MPO, myeloperoxidase; VWF, von Willebrand factor.