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Adipose tissue dysfunction signals progression of hepatic steatosis towards nonalcoholic steatohepatitis in C57BL/6 mice.

Duval C, Thissen U, Keshtkar S, Accart B, Stienstra R, Boekschoten MV, Roskams T, Kersten S, Müller M - Diabetes (2010)

Bottom Line: Multivariate analysis indicated that in addition to leptin, plasma CRP, haptoglobin, eotaxin, and MIP-1α early in the intervention were positively associated with liver triglycerides.Intermediate prognostic markers of liver triglycerides included IL-18, IL-1β, MIP-1γ, and MIP-2, whereas insulin, TIMP-1, granulocyte chemotactic protein 2, and myeloperoxidase emerged as late markers.Our data support the existence of a tight relationship between adipose tissue dysfunction and NASH pathogenesis and point to several novel potential predictive biomarkers for NASH.

View Article: PubMed Central - PubMed

Affiliation: Nutrition, Metabolism and Genomics Group, Division of Human Nutrition, Wageningen University, Wageningen, The Netherlands.

ABSTRACT

Objective: Nonalcoholic fatty liver disease (NAFLD) is linked to obesity and diabetes, suggesting an important role of adipose tissue in the pathogenesis of NAFLD. Here, we aimed to investigate the interaction between adipose tissue and liver in NAFLD and identify potential early plasma markers that predict nonalcoholic steatohepatitis (NASH).

Research design and methods: C57Bl/6 mice were chronically fed a high-fat diet to induce NAFLD and compared with mice fed a low-fat diet. Extensive histological and phenotypical analyses coupled with a time course study of plasma proteins using multiplex assay were performed.

Results: Mice exhibited pronounced heterogeneity in liver histological scoring, leading to classification into four subgroups: low-fat low (LFL) responders displaying normal liver morphology, low-fat high (LFH) responders showing benign hepatic steatosis, high-fat low (HFL) responders displaying pre-NASH with macrovesicular lipid droplets, and high fat high (HFH) responders exhibiting overt NASH characterized by ballooning of hepatocytes, presence of Mallory bodies, and activated inflammatory cells. Compared with HFL responders, HFH mice gained weight more rapidly and exhibited adipose tissue dysfunction characterized by decreased final fat mass, enhanced macrophage infiltration and inflammation, and adipose tissue remodeling. Plasma haptoglobin, IL-1β, TIMP-1, adiponectin, and leptin were significantly changed in HFH mice. Multivariate analysis indicated that in addition to leptin, plasma CRP, haptoglobin, eotaxin, and MIP-1α early in the intervention were positively associated with liver triglycerides. Intermediate prognostic markers of liver triglycerides included IL-18, IL-1β, MIP-1γ, and MIP-2, whereas insulin, TIMP-1, granulocyte chemotactic protein 2, and myeloperoxidase emerged as late markers.

Conclusions: Our data support the existence of a tight relationship between adipose tissue dysfunction and NASH pathogenesis and point to several novel potential predictive biomarkers for NASH.

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Upregulation of inflammatory and fibrotic gene expression in HFH responder mice. A: Number of genes up- or downregulated in the various subgroups in comparison with the LFL mice as determined by Affymetrix GeneChip analysis. Genes with a P value <0.05 were considered significantly regulated. B: Heat map showing changes in expression of selected genes involved in lipid metabolism, inflammation, and fibrosis in liver. Mean expression in LFL mice was set at 1. Gene expression changes in individual mice within the HFH group are shown on the right. C: Changes in gene expression of selected genes as determined by real-time quantitative PCR. Mean expression in LFL mice was set at 100%. Error bars reflect SD. Bars with different letters are statistically different (P < 0.05 according to Student's t test). Number of mice per group: n = 4 for the LFL, HFL, and HFH groups and n = 6 for the LFH group.
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Figure 2: Upregulation of inflammatory and fibrotic gene expression in HFH responder mice. A: Number of genes up- or downregulated in the various subgroups in comparison with the LFL mice as determined by Affymetrix GeneChip analysis. Genes with a P value <0.05 were considered significantly regulated. B: Heat map showing changes in expression of selected genes involved in lipid metabolism, inflammation, and fibrosis in liver. Mean expression in LFL mice was set at 1. Gene expression changes in individual mice within the HFH group are shown on the right. C: Changes in gene expression of selected genes as determined by real-time quantitative PCR. Mean expression in LFL mice was set at 100%. Error bars reflect SD. Bars with different letters are statistically different (P < 0.05 according to Student's t test). Number of mice per group: n = 4 for the LFL, HFL, and HFH groups and n = 6 for the LFH group.

Mentions: To correlate changes in liver functions with gene expression, expression profiling was performed on individual mouse livers. Microarray data were processed according to subgroups, with LFL mice serving as the reference group for calculation of fold change and P values. The most dramatic effects were observed in HFH responders as shown by changes in expression of >3,000 genes (Fig. 2A). To identify genes regulated exclusively in HFH responders, we selected genes that were statistically significantly regulated in HFH versus all subgroups but unchanged in other comparisons. This HFH responder gene expression signature comprised 388 upregulated and 319 downregulated genes. One dominant pathway within the HFH expression signature was lipid metabolism, illustrated by the marked induction of Cidec and Mogat1 (Fig. 2B). Other lipid metabolism genes such as Cd36 and Pparγ increased gradually from LFL to HFH, correlating with hepatic triglycerides (Fig. 1F and Fig. 2B). Another pathway well represented within the HFH expression signature was inflammation, as shown by marked and specific induction of acute phase genes encoding orosomucoid, serum amyloid-A, and lipocalin-2 in the HFH subgroup (Fig. 2B), and confirmed by quantitative PCR (Fig. 2C). Finally, many genes in the HFH expression signature were related to fibrosis, including Ctgf, collagens, metalloproteases, and Timp1 (Fig. 2B and C). Expression analysis of individual mice within the HFH group showed uniform induction of genes involved in the above-mentioned pathways (Fig. 2B). Gene set enrichment analysis indicated that while pathways related to lipid metabolism were upregulated in all subgroups when compared with LFL mice, with most prominent effects observed in HFH mice, numerous pathways of inflammation, cell cycle, and oxidative stress were specifically induced in HFH mice (supplemental Table 1, available in an online appendix [available at http://diabetes.diabetesjournals.org/cgi/content/full/db10-0224/DC1]). The complete microarray dataset is available at http://humannutrition2.wur.nl/duval2010.


Adipose tissue dysfunction signals progression of hepatic steatosis towards nonalcoholic steatohepatitis in C57BL/6 mice.

Duval C, Thissen U, Keshtkar S, Accart B, Stienstra R, Boekschoten MV, Roskams T, Kersten S, Müller M - Diabetes (2010)

Upregulation of inflammatory and fibrotic gene expression in HFH responder mice. A: Number of genes up- or downregulated in the various subgroups in comparison with the LFL mice as determined by Affymetrix GeneChip analysis. Genes with a P value <0.05 were considered significantly regulated. B: Heat map showing changes in expression of selected genes involved in lipid metabolism, inflammation, and fibrosis in liver. Mean expression in LFL mice was set at 1. Gene expression changes in individual mice within the HFH group are shown on the right. C: Changes in gene expression of selected genes as determined by real-time quantitative PCR. Mean expression in LFL mice was set at 100%. Error bars reflect SD. Bars with different letters are statistically different (P < 0.05 according to Student's t test). Number of mice per group: n = 4 for the LFL, HFL, and HFH groups and n = 6 for the LFH group.
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Figure 2: Upregulation of inflammatory and fibrotic gene expression in HFH responder mice. A: Number of genes up- or downregulated in the various subgroups in comparison with the LFL mice as determined by Affymetrix GeneChip analysis. Genes with a P value <0.05 were considered significantly regulated. B: Heat map showing changes in expression of selected genes involved in lipid metabolism, inflammation, and fibrosis in liver. Mean expression in LFL mice was set at 1. Gene expression changes in individual mice within the HFH group are shown on the right. C: Changes in gene expression of selected genes as determined by real-time quantitative PCR. Mean expression in LFL mice was set at 100%. Error bars reflect SD. Bars with different letters are statistically different (P < 0.05 according to Student's t test). Number of mice per group: n = 4 for the LFL, HFL, and HFH groups and n = 6 for the LFH group.
Mentions: To correlate changes in liver functions with gene expression, expression profiling was performed on individual mouse livers. Microarray data were processed according to subgroups, with LFL mice serving as the reference group for calculation of fold change and P values. The most dramatic effects were observed in HFH responders as shown by changes in expression of >3,000 genes (Fig. 2A). To identify genes regulated exclusively in HFH responders, we selected genes that were statistically significantly regulated in HFH versus all subgroups but unchanged in other comparisons. This HFH responder gene expression signature comprised 388 upregulated and 319 downregulated genes. One dominant pathway within the HFH expression signature was lipid metabolism, illustrated by the marked induction of Cidec and Mogat1 (Fig. 2B). Other lipid metabolism genes such as Cd36 and Pparγ increased gradually from LFL to HFH, correlating with hepatic triglycerides (Fig. 1F and Fig. 2B). Another pathway well represented within the HFH expression signature was inflammation, as shown by marked and specific induction of acute phase genes encoding orosomucoid, serum amyloid-A, and lipocalin-2 in the HFH subgroup (Fig. 2B), and confirmed by quantitative PCR (Fig. 2C). Finally, many genes in the HFH expression signature were related to fibrosis, including Ctgf, collagens, metalloproteases, and Timp1 (Fig. 2B and C). Expression analysis of individual mice within the HFH group showed uniform induction of genes involved in the above-mentioned pathways (Fig. 2B). Gene set enrichment analysis indicated that while pathways related to lipid metabolism were upregulated in all subgroups when compared with LFL mice, with most prominent effects observed in HFH mice, numerous pathways of inflammation, cell cycle, and oxidative stress were specifically induced in HFH mice (supplemental Table 1, available in an online appendix [available at http://diabetes.diabetesjournals.org/cgi/content/full/db10-0224/DC1]). The complete microarray dataset is available at http://humannutrition2.wur.nl/duval2010.

Bottom Line: Multivariate analysis indicated that in addition to leptin, plasma CRP, haptoglobin, eotaxin, and MIP-1α early in the intervention were positively associated with liver triglycerides.Intermediate prognostic markers of liver triglycerides included IL-18, IL-1β, MIP-1γ, and MIP-2, whereas insulin, TIMP-1, granulocyte chemotactic protein 2, and myeloperoxidase emerged as late markers.Our data support the existence of a tight relationship between adipose tissue dysfunction and NASH pathogenesis and point to several novel potential predictive biomarkers for NASH.

View Article: PubMed Central - PubMed

Affiliation: Nutrition, Metabolism and Genomics Group, Division of Human Nutrition, Wageningen University, Wageningen, The Netherlands.

ABSTRACT

Objective: Nonalcoholic fatty liver disease (NAFLD) is linked to obesity and diabetes, suggesting an important role of adipose tissue in the pathogenesis of NAFLD. Here, we aimed to investigate the interaction between adipose tissue and liver in NAFLD and identify potential early plasma markers that predict nonalcoholic steatohepatitis (NASH).

Research design and methods: C57Bl/6 mice were chronically fed a high-fat diet to induce NAFLD and compared with mice fed a low-fat diet. Extensive histological and phenotypical analyses coupled with a time course study of plasma proteins using multiplex assay were performed.

Results: Mice exhibited pronounced heterogeneity in liver histological scoring, leading to classification into four subgroups: low-fat low (LFL) responders displaying normal liver morphology, low-fat high (LFH) responders showing benign hepatic steatosis, high-fat low (HFL) responders displaying pre-NASH with macrovesicular lipid droplets, and high fat high (HFH) responders exhibiting overt NASH characterized by ballooning of hepatocytes, presence of Mallory bodies, and activated inflammatory cells. Compared with HFL responders, HFH mice gained weight more rapidly and exhibited adipose tissue dysfunction characterized by decreased final fat mass, enhanced macrophage infiltration and inflammation, and adipose tissue remodeling. Plasma haptoglobin, IL-1β, TIMP-1, adiponectin, and leptin were significantly changed in HFH mice. Multivariate analysis indicated that in addition to leptin, plasma CRP, haptoglobin, eotaxin, and MIP-1α early in the intervention were positively associated with liver triglycerides. Intermediate prognostic markers of liver triglycerides included IL-18, IL-1β, MIP-1γ, and MIP-2, whereas insulin, TIMP-1, granulocyte chemotactic protein 2, and myeloperoxidase emerged as late markers.

Conclusions: Our data support the existence of a tight relationship between adipose tissue dysfunction and NASH pathogenesis and point to several novel potential predictive biomarkers for NASH.

Show MeSH
Related in: MedlinePlus