Uncovering a Predictive Molecular Signature for the Onset of NASH-Related Fibrosis in a Translational NASH Mouse Model

Abstract

Background & aims: The incidence of nonalcoholic steatohepatitis (NASH) is increasing. The pathophysiological mechanisms of NASH and the sequence of events leading to hepatic fibrosis are incompletely understood. The aim of this study was to gain insight into the dynamics of key molecular processes involved in NASH and to rank early markers for hepatic fibrosis.

Methods: A time-course study in low-density lipoprotein-receptor knockout. Leiden mice on a high-fat diet was performed to identify the temporal dynamics of key processes contributing to NASH and fibrosis. An integrative systems biology approach was used to elucidate candidate markers linked to the active fibrosis process by combining transcriptomics, dynamic proteomics, and histopathology. The translational value of these findings were confirmed using human NASH data sets.

Results: High-fat-diet feeding resulted in obesity, hyperlipidemia, insulin resistance, and NASH with fibrosis in a time-dependent manner. Temporal dynamics of key molecular processes involved in the development of NASH were identified, including lipid metabolism, inflammation, oxidative stress, and fibrosis. A data-integrative approach enabled identification of the active fibrotic process preceding histopathologic detection using a novel molecular fibrosis signature. Human studies were used to identify overlap of genes and processes and to perform a network biology-based prioritization to rank top candidate markers representing the early manifestation of fibrosis.

Conclusions: An early predictive molecular signature was identified that marked the active profibrotic process before histopathologic fibrosis becomes manifest. Early detection of the onset of NASH and fibrosis enables identification of novel blood-based biomarkers to stratify patients at risk, development of new therapeutics, and help shorten (pre)clinical experimental time frames.

Keywords: ALT, alanine aminotransferase; AST, aspartate aminotransferase; DEG, differentially expressed genes; Diagnosis; ECM, extracellular matrix; HFD, high-fat diet; IPA, Ingenuity Pathway Analysis; LDLr-/-, low-density lipoprotein receptor knock out; Liver Disease; Metabolic Syndrome; NAFLD, nonalcoholic fatty liver disease; NASH, nonalcoholic steatohepatitis; Systems Biology; THBS1, thrombospontin-1.

Graphical abstract

Figure 1

Effect of HFD and chow on (A) body weight, and plasma levels of (B) cholesterol, (C) triglycerides, (D) insulin, and (E) glucose, and (F) HOMA index.Black solid squares indicate HFD; open circles indicate chow diet. *P < .05, **P < .01, ***P < .001 vs chow. HOMA-IR, HOmeostatic Model Assessment for Insulin Resistance.

Figure 2

Effect of HFD and chow diet on liver characteristics such as liver damage enzymes (A) ALT and (B) AST, (C) liver weight, and (D) liver lipids free cholesterol, (E) triglycerides, and (F) cholesteryl esters.Black solid squares indicate HFD; open circles indicate chow diet. **P < .01, ***P < .001 vs chow.

Figure 3

Histologic figures of H&E staining (top panels) and Picro-Sirius Red (PSR) staining (bottom panels)of relevant time points (t) shows the development of NASH and fibrosis in the HFD-fed LDLr-/-.Leiden mice.

Figure 4

Pathologic features of NASH after HFD and chow diet determined by the level of (A) microvesicular steatosis, (B) macrovesicular steatosis vacuolation, (C) hepatocellular hypertrophy, (D) hepatic inflammation, and the level of (E) perisinusoidal fibrosis.Black bars indicate HFD, white bars indicate chow diet. ***P < .001 vs chow.

Figure 5

(A) Effect of HFD on the number of differentially expressed genes as measured by RNA sequencing technology. Visualization of overlapping genes per time point represented in a (B) Venn diagram and (C) enrichment analysis of the top 25 enriched canonical pathways, values are expressed as -log(P value). Red stars indicate pathways related to lipid metabolism, green stars are related to inflammatory processes, blue stars are related to oxidative stress, and purple stars are related to extracellular matrix processes.

Figure 6

Graphic visualization of temporal dynamics of key processes involved in the development of NASH and fibrosis as determined by time-resolved enrichment analysis of the top canonical pathways.Red line, lipid metabolism; green line, inflammatory processes; blue line, oxidative stress; purple line, extracellular matrix processes.

Figure 7

Heatmap visualization of the effect of HFD on significant liver proteins synthesized the week before sacrifice as measured by dynamic protein profiling using deuterated water labeling technique. The black box with dashed lines indicates the set of ECM proteins. Green indicates down-regulation, red indicates up-regulation.

Figure 8

Heatmap visualization of individual genes compared with their controls. Human NASH indicates the gene response of human NASH patients compared with health control subjects. LDLr-/-.Leiden mice indicates the gene response of HFD-fed mice compared with chow at the corresponding time point. (A) Green indicates down-regulation, red indicates up-regulation. (B) Visualization of the enrichment analysis of the top 25 enriched canonical pathways, values are expressed as -log(P value). Red stars indicate pathways related to lipid metabolism, green stars are related to inflammatory processes, and purple stars are related to extracellular matrix processes.

Figure 9

(A) Network visualization of the direct link between features of the molecular signature associated with key processes, lipid metabolism, inflammation, oxidative stress, and fibrosis, and (B) the indirect link via induced-modules network.Yellow nodes indicate key processes, red nodes indicate genes and proteins from the signature, and green nodes indicate nodes from the induced modules network.