Table1.XLSX

<p>Introduction: It is generally accepted that metabolic inflammation in the liver is an important driver of disease progression in NASH and associated matrix remodeling/fibrosis. However, the exact molecular inflammatory mechanisms are poorly defined in human studies. Investigation of key pathogenic mechanisms requires the use of pre-clinical models, for instance for time-resolved studies. Such models must reflect molecular disease processes of importance in patients. Herein we characterized inflammation in NASH patients on the molecular level by transcriptomics and investigated whether key human disease pathways can be recapitulated experimentally in Ldlr^−/−.Leiden mice, an established pre-clinical model of NASH.</p><p>Methods: Human molecular inflammatory processes were defined using a publicly available NASH gene expression profiling dataset (GSE48452) allowing the comparison of biopsy-confirmed NASH patients with normal controls. Gene profiling data from high-fat diet (HFD)-fed Ldlr^−/−.Leiden mice (GSE109345) were used for assessment of the translational value of these mice.</p><p>Results: In human NASH livers, we observed regulation of 65 canonical pathways of which the majority was involved in inflammation (32%), lipid metabolism (16%), and extracellular matrix/remodeling (12%). A similar distribution of pathways across these categories, inflammation (36%), lipid metabolism (24%) and extracellular matrix/remodeling (8%) was observed in HFD-fed Ldlr^−/−.Leiden mice. Detailed evaluation of these pathways revealed that a substantial proportion (11 out of 13) of human NASH inflammatory pathways was recapitulated in Ldlr^−/−.Leiden mice. Furthermore, the activation state of identified master regulators of inflammation (i.e., specific transcription factors, cytokines, and growth factors) in human NASH was largely reflected in Ldlr^−/−.Leiden mice, further substantiating its translational value.</p><p>Conclusion: Human NASH is characterized by upregulation of specific inflammatory processes (e.g., “Fcγ Receptor-mediated Phagocytosis in Macrophages and Monocytes,” “PI3K signaling in B Lymphocytes”) and master regulators (e.g., TNF, CSF2, TGFB1). The majority of these processes and regulators are modulated in the same direction in Ldlr^−/−.Leiden mice fed HFD with a human-like macronutrient composition, thus demonstrating that specific experimental conditions recapitulate human disease on the molecular level of disease pathways and upstream/master regulators.</p

The effect of the interventions on hallmarks and complications of T2DM.

<p>Body weight, epidydimal adipose tissue weight, fasting plasma concentrations of glucose, insulin, cholesterol and triglycerides (TG) of the experimental groups are shown together with the intrahepatic TG concentrations, the urinary albumin/creatinine ratio and the atherosclerotic lesion area. Data represent the effects of drug intervention or dietary lifestyle intervention (DLI) at 16 weeks, <i>i.e.</i> the end of study. One group was sacrificed earlier and prior to the start of the interventions at 9 weeks (HFD 9w).</p>*<p>P<0.05 compared to HFD 16w,</p>#<p>P<0.05 for within subject change from 9 weeks to 16 weeks compared to HFD. Data are shown as mean ± SEM.</p

Effect of drug and dietary lifestyle interventions on protein and metabolite profiles in plasma.

<p>Shown are 67 proteins and metabolites with significantly different concentrations compared to HFD control group in at least one of the experimental conditions. The numbers of parameters (metabolites/proteins) with significantly different concentration compared to HFD control group in each experimental condition are provided above the heatmap. Log₂ ratios of a particular group vs. mean of HFD control group are plotted in a heatmap. Each vertical lane within a treatment group represents a response of one mouse in that treatment group. The cluster tree (Pearson correlation, complete linkage) is based on average log₂ ratios of a particular group vs. HFD. The upper part of the heatmap (1) represents proteins and metabolites that are significantly changed in the comparison chow control vs. HFD control group and defines thus changes that are associated with developing disease. The lower part of the heatmap (2) represents proteins and metabolites that are significantly changed in at least one of the interventions (i.e. dietary lifestyle (DLI) or one of the drug interventions) compared to HFD. The protein/metabolite profiles demonstrate a remarkable similarity between molecular signatures of chow control and DLI.</p

Molecular network of genes related to atherosclerosis signaling and hepatic fibrosis signaling pathway.

<p>Genes differentially expressed in dietary lifestyle intervention (DLI), compared to HFD were subjected to network analysis (Ingenuity Pathway Analysis). The network of genes associated with processes “Cellular Growth and Proliferation”, “Connective Tissue Development and Function” and “Hepatic System Development and Function” (network score 32) is represented in the figure. Genes or gene products are represented as nodes, and the biological relationships between two nodes are represented as edges (lines). The nodes of the network are colored according to log₂ gene expression changes in the DLI vs. HFD comparison (red: upregulation, green: downregulation). The bar graph associated with each node represents log₂ expression changes in chow (1st bar) and DLI groups (2nd bar) vs. HFD group, highlighting that all represented genes change in equivalent direction in chow and DLI conditions. The function “Overlay: Canonical Pathway” was used to highlight network genes associated with “atherosclerosis signaling” (11 genes, top enriched pathway) and “hepatic fibrosis/hepatic stellate cell activation” (9 genes, 3rd enriched pathway). All genes associated with these pathways, as well as majority of genes in the network are downregulated in DLI group, indicating withdrawal of pathogenic signals upon dietary lifestyle intervention.</p

Effect of drug and dietary lifestyle interventions on hepatic transcriptome and metabolite concentration changes.

<p>The changes in expression (transcripts, A) or concentration (metabolites, B) that are significantly different in at least one of 12 experimental conditions compared to HFD group are plotted in a heatmap (log₂ ratios vs. mean of HFD group). The number of significantly different transcripts or metabolites in each experimental condition is provided above the heatmap. The cluster tree (Pearson correlation, complete linkage) is based on average log₂ ratios vs. HFD values per intervention group. The upper part of the heatmap (1) represents transcripts and metabolites that are significantly changed in chow control vs. HFD control and defines changes that are associated with developing disease. The lower part of the heatmap (2) represents transcripts/metabolites that are significantly changed in at least one of interventions (dietary lifestyle (DLI) or one of drug interventions) compared to HFD. The transcript/metabolite profiles demonstrate high similarity between molecular signatures of chow and DLI groups and pronounced effects of fenofibrate and T0901317. (A) The expression changes of 4286 transcripts that are significantly different in at least one of 12 experimental conditions, compared to HFD group. (B) The concentration changes of 75 metabolites that are significantly different in at least one of 12 experimental conditions, compared to HFD group.</p

Risk factors of developing T2DM induced by 9 weeks of HFD in LDLr−/− mice.

*<p>P<0.05 compared to T = 0.</p

Identification of key biological processes based on significant changes in hepatic metabolites.

<p>The significantly changed hepatic metabolites in at least one of 12 conditions subdivided in biological processes (molecules with an unknown identity were excluded). Each lane represents the response of a treatment group expressed as mean log₂ ratio vs. HFD group. Red indicates higher and blue indicates lower concentrations of the hepatic metabolite after treatment compared to HFD group. * indicates significantly changed metabolite concentrations after treatment as compared to HFD group with a p-value<0.05 after FDR correction.</p

The effect of rosiglitazone, fenofibrate and T090131 on key hepatic processes required for the reversal of HFD-induced disorders.

<p>The Gene Ontology biological processes “glucose metabolic process”, “fatty acid metabolic process”, “oxidation reduction”, “immune response”, “apoptosis”, “cell cycle” and “wound healing” were selected for a detailed analysis to investigate whether the hepatic transcriptome changes induced by the drugs with marked hepatic effects (fenofibrate, T090131 and rosiglitazone) are in line with the changes induced by DLI, i.e. a “return to healthy” profile. The heatmaps show the mean log₂ expression ratio of each treatment vs. HFD group for genes involved in these processes (red: upregulation, blue: downregulation). Both fenofibrate and T090131 show many additionally and oppositely changing genes compared to DLI and/or chow group. Rosiglitazone has minor effects all of which were in line with the changes in chow/DLI groups.</p

Representative biological network based on differentially expressed genes of the HC group using MetaCore™ network software and the Analyze Network algorithm

Two representative networks are shown: the C/EBPβ c-jun network and the NF-κB network. A legend for the biological networks is provided in Additional data file 7d. Red dots in the right corner of a gene indicate up-regulation and blue dots down-regulation.<p><b>Copyright information:</b></p><p>Taken from "Atherosclerosis and liver inflammation induced by increased dietary cholesterol intake: a combined transcriptomics and metabolomics analysis"</p><p>http://genomebiology.com/2007/8/9/R200</p><p>Genome Biology 2007;8(9):R200-R200.</p><p>Published online 24 Sep 2007</p><p>PMCID:PMC2375038.</p><p></p

Venn diagram of significantly differentially expressed genes in the LC and HC groups compared to the Con group

ANOVA < 0.01 and FDR (predicted) <p><b>Copyright information:</b></p><p>Taken from "Atherosclerosis and liver inflammation induced by increased dietary cholesterol intake: a combined transcriptomics and metabolomics analysis"</p><p>http://genomebiology.com/2007/8/9/R200</p><p>Genome Biology 2007;8(9):R200-R200.</p><p>Published online 24 Sep 2007</p><p>PMCID:PMC2375038.</p><p></p