original article adipose tissue dysfunction signals ...with macrovesicular lipid droplets, and high...

Adipose Tissue Dysfunction Signals Progression ofHepatic Steatosis Towards Nonalcoholic Steatohepatitisin C57Bl/6 MiceCaroline Duval,

1,2Uwe Thissen,

2,3Shohreh Keshtkar,

1,2Bertrand Accart,

1,2Rinke Stienstra,

1,2

Mark V. Boekschoten,1,2

Tania Roskams,4

Sander Kersten,1,2

and Michael Muller1,2

OBJECTIVE—Nonalcoholic fatty liver disease (NAFLD) islinked to obesity and diabetes, suggesting an important role ofadipose tissue in the pathogenesis of NAFLD. Here, we aimed toinvestigate the interaction between adipose tissue and liver inNAFLD and identify potential early plasma markers that predictnonalcoholic steatohepatitis (NASH).

RESEARCH DESIGN AND METHODS—C57Bl/6 mice werechronically fed a high-fat diet to induce NAFLD and comparedwith mice fed a low-fat diet. Extensive histological and pheno-typical analyses coupled with a time course study of plasmaproteins using multiplex assay were performed.

RESULTS—Mice exhibited pronounced heterogeneity in liverhistological scoring, leading to classification into four subgroups:low-fat low (LFL) responders displaying normal liver morphol-ogy, low-fat high (LFH) responders showing benign hepaticsteatosis, high-fat low (HFL) responders displaying pre-NASHwith macrovesicular lipid droplets, and high fat high (HFH)responders exhibiting overt NASH characterized by ballooning ofhepatocytes, presence of Mallory bodies, and activated inflam-matory cells. Compared with HFL responders, HFH mice gainedweight more rapidly and exhibited adipose tissue dysfunctioncharacterized by decreased final fat mass, enhanced macrophageinfiltration and inflammation, and adipose tissue remodeling.Plasma haptoglobin, IL-1�, TIMP-1, adiponectin, and leptin weresignificantly changed in HFH mice. Multivariate analysis indi-cated that in addition to leptin, plasma CRP, haptoglobin,eotaxin, and MIP-1� early in the intervention were positivelyassociated with liver triglycerides. Intermediate prognosticmarkers of liver triglycerides included IL-18, IL-1�, MIP-1�, andMIP-2, whereas insulin, TIMP-1, granulocyte chemotactic protein2, and myeloperoxidase emerged as late markers.

CONCLUSIONS—Our data support the existence of a tightrelationship between adipose tissue dysfunction and NASHpathogenesis and point to several novel potential predictivebiomarkers for NASH. Diabetes 59:3181–3191, 2010

Obesity is associated with a number of metabolicperturbations that increase risk for type 2 dia-betes, coronary heart disease, and liver dys-function. These metabolic perturbations,

collectively referred to as the metabolic syndrome, includehypertension, dyslipidemia, and insulin resistance. Addi-tionally, metabolic syndrome is often characterized bynonalcoholic fatty liver disease (NAFLD) (1).

It is evident that obesity represents a state of chroniclow-grade inflammation that likely originates in the adi-pose tissue. Upon fat expansion, macrophages and otherleukocytes infiltrate the adipose tissue and account forsecretion of various cytokines and adipokines (2,3). Be-cause many of these cytokines reduce insulin sensitivity,the elevated inflammatory status may provide a mechanis-tic explanation for the well-established link betweenobesity and insulin resistance (4). Alternatively, the com-plications of obesity may be traced to aberrant storage oflipids in nonadipose tissues, which can profoundly disturborgan function (5).

Excess storage of fat in liver is the hallmark of NAFLD,which refers to a wide histological spectrum of liverdiseases ranging from hepatic steatosis to pathologicalnonalcoholic steatohepatitis (NASH) and fibrotic compli-cations (6). Steatosis alone is considered relatively innoc-uous, but prognosis is much more grim for NASH, whichmight progress to cirrhosis and liver cancer (7). Severaltheories have been proposed to explain why steatosisoccasionally progresses to NASH. One popular model isthe two-hit hypothesis, in which the first hit is the accu-mulation of fat in the hepatocytes that renders the livermore susceptible to second hits comprised of inflamma-tory insults or oxidative stress (7). Alternatively, progres-sion of steatosis to NASH may be stimulated by cellularlipotoxicity mediated by lipotoxic fatty acids, cholesterol,and/or ceramides (8).

Since NAFLD is strongly linked to obesity, an importantrole of adipose tissue in the pathogenesis of NAFLD issuspected. Indeed, growing evidence indicates that pro-teins secreted from adipose tissue may be implicated inNAFLD (9). To gain insight into the nature of the interac-tion between adipose tissue and liver in the context ofobesity-related NAFLD and to identify potential earlyplasma markers that predict steatosis and/or NASH, wesubjected C57Bl/6 mice to a chronic high-fat diet to induceNAFLD and coupled extensive histological and phenotyp-ical analyses with a time course study of plasma proteinsusing multiplex assay. The results indicate a tight relation-ship between adipose tissue dysfunction and NASH patho-

From the 1Nutrition, Metabolism and Genomics Group, Division of HumanNutrition, Wageningen University, Wageningen, the Netherlands; the 2Nu-trigenomics Consortium, Top Institute Food & Nutrition, Wageningen, theNetherlands; 3TNO Quality of Life, Zeist, the Netherlands; the 4LiverResearch Unit, Department of Morphology and Molecular Pathology, Uni-versity of Leuven, Leuven, Belgium.

Corresponding author: Sander Kersten, [email protected] 13 February 2010 and accepted 12 September 2010. Published ahead

of print at http://diabetes.diabetesjournals.org on 21 September 2010. DOI:10.2337/db10-0224.

© 2010 by the American Diabetes Association. Readers may use this article aslong as the work is properly cited, the use is educational and not for profit,and the work is not altered. See http://creativecommons.org/licenses/by-nc-nd/3.0/ for details.

The costs of publication of this article were defrayed in part by the payment of page

charges. This article must therefore be hereby marked “advertisement” in accordance

with 18 U.S.C. Section 1734 solely to indicate this fact.

ORIGINAL ARTICLE

diabetes.diabetesjournals.org DIABETES, VOL. 59, DECEMBER 2010 3181

genesis and point to several novel potential predictivebiomarkers for NASH.

RESEARCH DESIGN AND METHODS

Twenty male C57BL/6JOlaHsd (C57Bl/6) mice at 8 weeks of age were purchasedfrom Harlan (Horst, the Netherlands) and housed individually. Detailed informa-tion about the mouse strain is available at the following Web site: http://www.harlan.com/research_models_and_services/research_models_by_product_type/inbred_mice/c57bl6j_inbred_mice.hl. After 3 weeks on a low-fat diet (LFD),mice were divided into two weight-matched groups. One group continued onthe LFD while the other group switched to a high fat diet (HFD) containing 10or 45% energy as triglycerides, respectively (D12450B and D12451; ResearchDiets) for 21 weeks. Lard in these diets was replaced by palm oil. Palm oil isdevoid of cholesterol, which may have proinflammatory properties. Foodintake was measured by weighing the pellets once per week. Mice werehoused individually, allowing for assessment of food consumption of individ-ual mice. Food intake was averaged over the 20-week intervention andmultiplied by the caloric value of the feed to determine energy intake in kcal� mouse�1 � day�1. Numbers were subsequently averaged per group. At weeks0, 2, 4, 8, 12, 16, and 20, tail vein plasma samples were collected after a 6-h fast.Two mice within the HFD group died before the end of the experiment forreasons unrelated to the dietary intervention. After 21 weeks, ad libitum–fedmice were anesthetized using isofluorane. Blood was collected by orbitalpuncture, followed by sacrifice via cervical dislocation. Liver and epididymalwhite adipose tissues were removed, weighed, and immediately frozen inliquid nitrogen. For histology, liver was frozen with OCT compound, andadipose tissue samples were fixed in 10% formalin and processed for paraffinembedding. Animal experiments were approved by the local animal ethicscommittee at Wageningen University.Hepatic triglyceride content determination, RNA extraction, real-time

PCR, and Affymetrix Microarrays. Liver triglycerides were determinedenzymatically as previously described (10). Other techniques were employedas previously described (11). Microarray data were analyzed as previouslydescribed (12). Genes with a P value �0.05 were considered significantlyregulated. Array data have been submitted to the Gene Expression Omnibus(accession no. GSE24031). Gene set enrichment analysis was used to identifysignificantly regulated pathways (13). Gene sets with a false discovery rate�0.25 were considered significant.Plasma measurements. Plasma concentrations of multiple chemokines weremeasured with multiplex technologies (Rodent Map 2.0; Rules Based Medi-cine, Austin, TX). Plasma free fatty acids and alanine aminotransferase weremeasured with commercially available kits from Instruchemie (Delfzijl, theNetherlands). Plasma leptin and insulin levels were measured using kits fromLinco (St. Louis, MO).Liver immunohistochemistry. For oil red O staining, 5 �m frozen liversections were air-dried for 30 min, followed by fixation in formal calcium (4%formaldehyde and 1% CaCl2). Oil red O staining was performed using standardprotocols. Hematoxylin-eosin (H-E) staining of frozen liver sections wascarried out as described at http://www.ihcworld.com/histology.htm. Collagenwas stained using fast green FCF/sirius red F3B.

For immunohistochemistry, 5 �m frozen liver sections were cut, driedovernight, fixed in acetone for 10 min, and washed in PBS prior to use. Forvisualization of hepatic stellate cell activation, rabbit anti–glial fibrillary acidicprotein (GFAP) polyclonal antibody was used (Dako, Glostrup, Denmark).For detection of macrophages/monocytes, a rat polyclonal anti-Cd68 antibody(Serotec, Oxford, U.K.) was used. Sections were incubated for 30 min atroom temperature with GFAP (1:1,000 dilution) or Cd68 (1:100 dilution)primary antibodies, followed by incubation for 30 min at room temperaturewith anti-rabbit peroxidase-conjugated En Vision (GFAP; Dako) or 1:20diluted anti-rat IgG peroxidase-conjugated secondary antibodies (Cd68; Sero-tec). Visualization of the complex was done using 3-amino-9-ethylcarbazolechromogen for 15 min, followed by staining with H-E. Negative controls wereperformed by omitting the primary antibody.Immunohistochemistry of adipose tissue. 5-�m-thick paraffin-embeddedsections were cut, dried for 30 min at 37°C, and washed in PBS prior to use.Staining of adipose tissue macrophages was carried out using an antibodyagainst Cd68 as described above. H-E staining of sections was done usingstandard protocols. Collagen was stained using fast green FCF/sirius red F3B.Multivariate Rules-Based Medicine data analysis. The data obtained fromthe commercial Rules-Based Medicine multiplex analysis (70 proteins mea-sured in 126 plasma samples) contained a number of technically unreliableentries for specific samples and proteins that were: 1) lower than the leastdetectable dose (LDD): replaced by 0.5 � LDD, 2) not detectable (i.e., notmeasured on the standard curve): replaced by 0.1 � LDD, or 3) notmeasurable (i.e., not sufficient sample material available): replaced by 0.1 �LDD. Proteins were removed if they did not contain more than 50% reliable

entries for two or more groups of the totally available 14 groups (7 timepoints � 2 diets). This approach assures that potentially relevant groupdifferences are retained in the data. Of the 70 proteins screened, 19 wereexcluded, 18 contained more than 50% reliable entries for at least two groups,and 33 proteins contained 100% reliable entries for all groups. One mouse wasremoved from the dataset for multivariate analysis on the basis that someplasma proteins display atypical outlying values.

Multiway partial least squares (PLS) (MPLS) is a multivariate statisticaltechnique that is an extension of standard PLS analysis able to analyze dataacross different time points (14–16). Both methods are able to analyze largenumbers of variables in small sample sizes by reducing the dimensionality ofthe data. In contrast to standard two-dimensional data (matrix), multiway datacan be represented as a collection of matrices (a cube) where each matrixcontains data from one specific time point. For MPLS, the data were centeredacross the samples (i.e., zero mean) to remove offsets followed by autoscalingfor the variables (i.e., a mean � SD of 0 � 1 to remove arbitrary differencesin measurement scales [16]).

Validation of the MPLS models using a double cross-validation strategy andthe selection of most important proteins from the models have been per-formed as previously described (17). Because (double) cross-validation relieson a random subdivision of data, the complete validation procedure wasrepeated five times on the basis of different random subdivisions of the dataduring cross-validation. A model was considered to be reliable if at least four(out of five) models could be calculated with an R2 0.7.Statistical analyses. Statistically significant differences were calculatedusing Student’s T test. The cutoff for statistical significance was set at P �0.05. MPLS was performed using the N-way toolbox (http://www.models.life.ku.dk/nwaytoolbox) in combination with Matlab, version 7.1.0, release 14(The Mathworks, Natick, MA) and homemade software.

RESULTS

Development of NASH in a subpopulation of C57Bl/6

mice fed a HFD. To study the effect of chronic high-fatfeeding on liver metabolic functions, C57Bl/6 mice werefed an LFD or HFD for 21 weeks. Mice fed the HFD gainedmore weight compared with mice fed the LFD (Fig. 1A),which was already evident after 2 weeks. Enhancedweight gain in mice fed a HFD may be related to increasedenergy intake (Fig. 1B). After 21 weeks, weight of theepididymal fat pad, which was assumed to reflect overalladiposity of the animals, was markedly higher in mice fedan HFD (Fig. 1C).

To characterize the effect of an HFD on hepatic steato-sis, liver sections were stained with H-E (Fig. 1D) and oilred O (Fig. 1E). Remarkably, a marked heterogeneity in fataccumulation and histology was observed within eachgroup. Scoring of the sections by a pathologist (T.R.)indicated different stages of NAFLD and led to classifica-tion of mice into four subgroups, which surprisingly butnot deliberately ended up being of approximately equalsize. These subgroups were low-fat low (LFL) responders(n 4), which display normal liver morphology; low-fathigh (LFH) responders (n 6), which develop benignhepatic steatosis; high-fat low (HFL) responders (n 4),which show a pre-NASH phenotype of macrovesicularlipid droplets; and high-fat high (HFH) responders (n 4),which develop overt NASH characterized by ballooning ofhepatocytes, presence of Mallory bodies, and activatedinflammatory cells (Fig. 1D).

Quantitation of hepatic triglycerides confirmed the het-erogeneity between the subgroups, with HFH mice accu-mulating the highest amount of triglycerides (Fig. 1F).Consequently, liver–to–body weight ratio was increasedspecifically in HFH mice, indicating hepatomegaly (Fig.1G). Finally, plasma alanine aminotransferase activity washighest in the HFH subgroup, reflecting increased liverdamage (Fig. 1H).

ADIPOSE TISSUE DYSFUNCTION AND NASH

3182 DIABETES, VOL. 59, DECEMBER 2010 diabetes.diabetesjournals.org

NASH-related metabolic pathways are exclusivelyimpaired in HFH Responders. To correlate changes inliver functions with gene expression, expression profil-ing was performed on individual mouse livers. Microar-ray data were processed according to subgroups, withLFL mice serving as the reference group for calculationof fold change and P values. The most dramatic effectswere observed in HFH responders as shown by changesin expression of 3,000 genes (Fig. 2A). To identifygenes regulated exclusively in HFH responders, weselected genes that were statistically significantly regu-

lated in HFH versus all subgroups but unchanged inother comparisons. This HFH responder gene expres-sion signature comprised 388 upregulated and 319downregulated genes. One dominant pathway within theHFH expression signature was lipid metabolism, illus-trated by the marked induction of Cidec and Mogat1(Fig. 2B). Other lipid metabolism genes such as Cd36and Ppar� increased gradually from LFL to HFH, corre-lating with hepatic triglycerides (Fig. 1F and Fig. 2B).Another pathway well represented within the HFHexpression signature was inflammation, as shown by

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FIG. 1. A subpopulation of mice fed an HFD develops NASH. A: Changes in body weight in C57Bl/6 mice fed an LFD (�; n � 10) or HFD (f; n �8). B: Mean energy intake of mice fed an LFD or HFD during 21 weeks of dietary intervention. C: Weight of epididymal fat pad after 21 weeksof dietary intervention. Error bars reflect SD. *Significantly different from mice fed an LFD according to Student’s t test (P < 0.05). H-E staining(D) and oil red O staining (E) of representative liver sections of the four subgroups (LFL, LFH, HFL, and HFH). F: liver triglycerideconcentration. G: Liver weight (expressed as percentage of total body weight [BW]). H: Activity of alanine aminotransferase (ALT) (glutamatepyruvate transaminase) in plasma. Error bars reflect SD. Bars with different letters are statistically different (P < 0.05 according to Student’st test). n � 4 mice per group for LFL, HFL, and HFH, and n � 6 mice per group for LFH. (A high-quality digital representation of this figure isavailable in the online issue.)

C. DUVAL AND ASSOCIATES


marked and specific induction of acute phase genesencoding orosomucoid, serum amyloid-A, and lipoca-lin-2 in the HFH subgroup (Fig. 2B), and confirmed byquantitative PCR (Fig. 2C). Finally, many genes in theHFH expression signature were related to fibrosis, in-cluding Ctgf, collagens, metalloproteases, and Timp1(Fig. 2B and C). Expression analysis of individual micewithin the HFH group showed uniform induction ofgenes involved in the above-mentioned pathways (Fig.2B). Gene set enrichment analysis indicated that whilepathways related to lipid metabolism were upregulated inall subgroups when compared with LFL mice, with most

prominent effects observed in HFH mice, numerous path-ways of inflammation, cell cycle, and oxidative stress werespecifically induced in HFH mice (supplemental Table 1,available in an online appendix [available at http://diabetes.diabetesjournals.org/cgi/content/full/db10-0224/DC1]). Thecomplete microarray dataset is available at http://humannutrition2.wur.nl/duval2010.

The elevated inflammatory status in HFH livers wascorroborated by immunostaining for macrophagemarker Cd68 (Fig. 3A). Early fibrosis was detected inone HFH mouse (Fig. 3B). Finally, hepatic stellateactivation was demonstrated in HFH mice by GFAP

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FIG. 2. Upregulation of inflammatory and fibrotic gene expression in HFH responder mice. A: Number of genes up- or downregulated in the varioussubgroups in comparison with the LFL mice as determined by Affymetrix GeneChip analysis. Genes with a P value <0.05 were consideredsignificantly regulated. B: Heat map showing changes in expression of selected genes involved in lipid metabolism, inflammation, and fibrosis inliver. 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%. Errorbars reflect SD. Bars with different letters are statistically different (P < 0.05 according to Student’s t test). Number of mice per group: n � 4for the LFL, HFL, and HFH groups and n � 6 for the LFH group.



immunostaining (Fig. 3C). Overall, these analyses sup-port induction of inflammation and fibrosis in HFHresponders, indicating NASH.HFH responder mice exhibit adipose tissue dysfunc-tion. Mice classified as high responders also gained themost body weight (Fig. 4A), likely related to increasedfood intake (Fig. 4B). Indeed, a positive correlation wasfound between final body weight and hepatic triglycerides(Fig. 4C). Remarkably, despite increased weight gain,weight of the epididymal fat pad at sacrifice was markedlylower in HFH compared with that in HFL mice (Fig. 4D).As expected, leptin expression in adipose tissue mirrored

adiposity (Fig. 4E), which was also true for the plasma freefatty acids (Fig. 4F). Evaluation of the morphology of theepididymal fat pad in HFH mice after H-E staining revealedatrophied adipocytes surrounded by inflammatory cells,which were hardly observed in HFL responders (Fig. 4G).Cd68 immunostaining indicated increased presence ofmacrophages in HFH mice (Fig. 4H), which was supportedby gene expression of F4/80 and Cd68 (Fig. 5). In contrast,expression of the anti-inflammatory adipokine adiponectinwas markedly reduced in HFH mice, as was resistin (Fig.5). Interestingly, expression of adipogenic (Ppar� andFabp4) and lipogenic (Dgat2, Srebp-1, and fatty acid

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FIG. 3. (Immuno)histochemical staining confirms enhanced inflammation and early fibrosis in HFH mice. A: Immunohistochemical staining ofmacrophage activation in representative liver sections of HFL (left panel) and HFH (right panel) mice using antibody against the specificmacrophage marker Cd68. B: Collagen staining using fast green FCF/sirius red F3B. C: Staining of stellate cell activation using antibody againstGFAP. (A high-quality digital representation of this figure is available in the online issue.)



synthase, Fasn) marker genes was significantly downregu-lated in HFH mice compared with HFL mice, suggestingadipose tissue dysfunction. Finally, collagen staining re-vealed fibrotic adipose tissue in HFH mice (Fig. 4I), whichwas supported by increased expression of tissue inhibitorof matrix metalloproteinases (Timp-1) (Fig. 5). These datasuggest that HFH responders, classification of which is

entirely determined by liver histology, exhibit adiposetissue dysfunction characterized by decreased fat mass,enhanced macrophage infiltration, inflammation, and adi-pose tissue remodelling.Plasma biomarkers are significantly associated withliver triglycerides. To find early biomarkers that maypredict NASH in C57Bl/6 mice and that may serve as

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FIG. 4. Adipose dysfunction in HFH mice. A: Body weight changes in the four subgroups during the 21-week dietary intervention. White squares,LFL; light-gray squares, LFH; dark-gray squares, HFL; black squares, HFH. B: Mean daily energy intake. C: Positive correlation between final bodyweight and liver triglyceride concentration (P < 0.05). D: Weight of epididymal fat depot. E: Adipose tissue leptin mRNA expression asdetermined by quantitative PCR. Mean expression in LFL mice was set at 100%. F: Plasma free fatty acid levels. Error bars reflect SD.*Significantly different from HFL mice according to Student’s t test (P < 0.05). Number of mice per group: n � 4 for LFL, HFL, and HFH and n �6 for LFH. G: H-E staining of representative adipose tissue sections. H: Immunohistochemical staining of macrophages using antibody againstCd68. I: Collagen staining using fast green FCF/sirius red F3B. (A high-quality digital representation of this figure is available in the online issue.)



potential mediators between adipose tissue dysfunctionand NASH, plasma was collected at different time points ofdiet intervention and assayed for 70 plasma proteins usingmultiplex analysis. Levels of most plasma proteins werenot consistently different between the subgroups. Oneexception was the acute phase protein haptoglobin, whichwas elevated in HFH mice after 12 weeks of diet interven-tion (Fig. 6A). Similarly, plasma levels of the fibrosismarker TIMP-1 started to deviate at week 12 and furtherincreased until the end. Remarkably, interleukin (IL)-1�and leptin levels were already elevated in HFH after 2weeks and this pattern was maintained throughout theintervention. Finally, plasma insulin levels indicated thatHFH mice became hyperinsulinemic from week 12, sug-gesting development of insulin resistance.

To systematically screen for plasma biomarkers thatpredict liver triglycerides, multivariate analysis was per-formed using MPLS. The results of multivariate analysisbetween plasma proteins at different time points and livertriglycerides are depicted in Fig. 6B and supplementalTable 2. In addition to leptin, plasma levels of C-reactiveprotein (CRP), eotaxin, haptoglobin, and macrophage in-flammatory protein (MIP)-1� early in the interventionwere positively associated with liver triglycerides at 20weeks. Intermediate prognostic markers of liver triglycer-ides included IL-18, IL-1�, MIP-1�, and MIP-2, whereasinsulin, TIMP-1, GCP-2, and MPO emerged as late markers.Throughout the diet intervention, highest regression coef-ficients were obtained for CRP, haptoglobin, leptin, andIL-1� (supplemental Table 2). Adiponectin was not signif-icantly associated with liver triglycerides. The completemultivariate dataset is available at http://humannutrition2.wur.nl/duval2010. Besides potentially serving as predictivebiomarkers of liver triglycerides, these proteins may pro-vide a functional link between adipose tissue dysfunctionand NAFLD.

DISCUSSION

C57Bl/6 mice fed a HFD represent a popular animal modelfor human obesity and insulin resistance. Despite devel-opment of hepatic steatosis and other features of patientswith NAFLD (18), except for a recent report the model hasnot been extensively used to study NAFLD (19). Asexpected, high-fat feeding increased adipose tissue massand hepatic fat storage. Consistent with previous datashowing considerable variability in the obese and diabeticphenotype (20,21), we observed marked heterogeneity inbody weight gain. Additionally, the magnitude of fat stor-age and NAFLD scoring differed markedly between themice, giving rise to four well-distinguishable groups. De-tailed histological and gene expression analysis indicatedthat HFH mice exhibit NASH. Accordingly, detailed studyof these HFH responders may give novel insight into thedevelopment and progression of NAFLD.

Although humans have no epididymal fat pads, westudied epididymal adipose tissue because it representsthe most commonly used fat depot in mouse studies, iseasily accessible, can be accurately weighed, and is rela-tively homogenous. Unfortunately, we did not have accessto dual-energy X-ray absorptiometry or magnetic reso-nance imaging to be able to measure fat percentage, leanbody mass, or fat distribution. Remarkably, HFH mice,despite showing the highest weight gain, had significantlyless epididymal fat after 21 weeks compared with HFLmice, which likely reflects differences in overall adiposity.An important question is why there is an apparent limit tothe expansion of adipose tissue in HFH mice and, espe-cially, what is the link with NASH. Obesity-related adipo-cyte hypertrophy is known to be associated with adiposeinflammation characterized by infiltration of macrophagesand other leukocytes, appearance of so-called crown-likestructures, and increased expression of several inflamma-

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FIG. 5. Changes in adipose gene expression indicates adipose tissuedysfunction. Adipose tissue mRNA expression of a selected group ofgenes was determined by quantitative real-time PCR after 21 weeks ofdietary intervention. Mean expression in LFL mice was set at 100%.Error bars reflect SD. *Significantly different from HFL mice accord-ing to Student’s t test (P < 0.05). Number of mice per group: n � 4 forLFL, HFL, and HFH and n � 6 for LFH.



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FIG. 6. Plasma proteins as early predictive biomarker for NASH in C57Bl/6 mice. A: Plasma concentration of haptoglobin, TIMP-1, IL-1�, leptin,and insulin were determined by multiplex assay at specific time points during the 21 weeks of dietary intervention after a 6-h fast. White squares,LFL; light-gray squares, LFH; dark-gray squares, HFL; black squares, HFH. Error bars reflect SD. *Significantly different from HFL mice accordingto Student’s t test (P < 0.05). Number of mice per group: n � 4 for LFL, HFL, and HFH and n � 6 for LFH. B: Graphs illustrating the result ofmultivariate analysis showing the association of protein plasma concentrations at various time points with final liver triglyceride content. TheabsRSD is the absolute relative standard deviation: the standard deviation of the regression coefficients divided by the absolute mean value ofthe regression coefficients. Significant proteins display an inverse absRSD value higher than two (bold line indicates the inverse absRSDthreshold value of 2). w, weeks.



tory markers (2,3,22,23). How adipose tissue inflammationdevelops during obesity is not clear, but a role of hyper-trophy, hypoxia, and adipocyte cell death has been sug-gested (23,24). Compared with HFL mice, adipose tissue ofHFH mice showed more pronounced inflammation asshown by increased macrophage staining and expressionof inflammatory marker genes and increased collagenstaining, suggesting fibrosis. Furthermore, decreased adi-pocyte size and increased cell death were observed in HFHmice. Since HFH mice are classified entirely based on liverhistology, these data indicate a strong link between inflam-matory and morphological changes in adipose tissue andprogression of steatosis to NASH. Consequently, adiposetissue failure or dysfunction may signal progression ofhepatic steatosis toward NASH. These data support theprevious suggestion that poor expansion of adipose tissuemass due to remodeling contributes to hepatic steatosisinduced by high-fat feeding (23) and thereby strengthen anemerging view that obesity starts to cause metabolicproblems when adipose tissue cannot fully meet demandsfor additional storage, leading to fat accumulation in otherorgans such as muscle, liver, and �-cells and causinglipotoxicity (25–27). The limited expandability of adiposetissue may be related to adipose tissue fibrosis and asso-ciated disproportionate accumulation of extracellular ma-trix components (22).

Multivariate longitudinal analysis of plasma proteinsyielded a number of candidates that may serve as prog-nostic markers for NAFLD and NASH. In addition, theseproteins may provide insight into the functional linkbetween adipose tissue dysfunction and NAFLD. Besidesleptin, the best predictive markers were the acute phaseproteins CRP and haptoglobin and MIP-1� (Ccl3). PlasmaCRP was previously proposed as a diagnostic marker forNASH (28). In one study, high-sensitivity CRP was signif-icantly elevated in patients with NASH compared with thatin patients with only steatosis (29). Furthermore, high-sensitivity CRP correlated with the severity of fibrosis inNASH. In another study, plasma CRP was not helpful indiagnosis of NASH in severely obese patients, possiblybecause adipose tissue contributes to plasma CRP inobesity.

Hardly any data exist on the relation between plasmahaptoglobin and NASH. Haptoglobin was included in acomposite biomarker combining 13 parameters to predictNASH (30). Interestingly, in a recent study plasma hapto-globin showed a negative correlation with fibrosis stage(31). There are no reports on the association betweenplasma MIP-1� and hepatic steatosis or NASH. However, itwas reported that MIP-1� mRNA in human liver is posi-tively associated with liver fat (32).

Another good predictive marker for liver triglycerideswas IL-1�. Plasma IL-1� levels were significantly elevatedin HFH mice already after 2 weeks of HFD, probablybecause of elevated production in adipose tissue. Re-cently, we showed that IL-1� may promote steatosis inmice by inhibiting PPAR� activity (33). Whether adiposetissue–derived IL-1� links adipose tissue dysfunction andNASH requires further study.

Recent studies indicate that IL-18 promotes hepaticsteatosis in mice (34,35). Interestingly, patients withNAFLD were found to have significantly elevated plasmaIL-18 levels (36). According to our multivariate analysis,plasma IL-18 from week eight onward was significantlyassociated with liver triglycerides. Overall, further re-search into the potential use of plasma CRP, haptoglobin,

MIP-1�, and possibly IL-1�, eotaxin, and IL-18 as prognos-tic biomarkers for NAFLD in humans is warranted.

One of the late biomarkers to emerge from our studywas TIMP-1. Specifically, plasma TIMP-1 levels started todeviate in the HFH mice after 12 weeks of HFD. SinceTIMP-1 expression was increased in HFH mice in bothliver and adipose tissue, it is unclear which tissue primar-ily contributes to increased plasma levels. TIMP-1 is usedextensively as a marker of fibrosis related to viral hepatitis(37). However, its use in the context of NAFLD is verylimited. According to our data, plasma TIMP-1 levels mayhave potential as a biomarker for NASH. Consistent withthis notion, plasma TIMP-1 was recently shown to be avaluable component of a composite predictive marker ofNASH in human (38).

An adipokine that has been extensively linked to NAFLDis adiponectin (37,39). Besides its antisteatotic role(38,40), adiponectin has potent anti-inflammatory effectsin liver (39). In humans, plasma adiponectin, either aloneor as ratio to plasma leptin (41), has shown promise as adiagnostic marker for NASH, although it should be vali-dated in larger cohorts of patients (9). In the present study,plasma adiponectin was not significantly associated withliver triglycerides.

Overall, the best predictive marker for liver triglycer-ides, which was also clearly elevated in HFH mice, wasleptin. Portal infusion with leptin was shown to increasehepatic triglycerides in rats (42). Furthermore, leptinappears to be one of the key regulators of inflammationand progression to fibrosis in NASH (43–46). Althoughsome studies have found elevated plasma leptin levels inpatients with NASH (47,48), other studies have not, thussomewhat questioning the potential of plasma leptin as anoninvasive marker for diagnosis of NASH in humans (49).

Hyperleptinemia in HFH mice is expected to decreasefood intake. However, energy intake was higher in HFHcompared with that in other subgroups, suggesting exis-tence of leptin resistance, at least centrally in the hypo-thalamus. In contrast, leptin resistance is expected to beabsent from liver, in which chronically elevated leptinlevels may promote NASH by stimulating hepatic triglyc-eride storage, inflammation, and fibrosis (37). Leptin resis-tance may thus be the basis for hyperleptinemia andhyperphagia in HFH mice, leading to accelerated weightand fat gain and consequent adipose tissue dysfunction.

The significant heterogeneity in the response to HFD inC57Bl/6 mice has been previously reported (20,21). Theunderlying reason for the large heterogeneity is uncertainbut may be related to copy no. variations in the mousegenome (50) and perhaps specifically by differences in thecopy no. of the Ide gene encoding the insulin-degradingenzyme (51). Alternatively, the variation in phenotypeafter HFD may be mediated by epigenetic mechanisms(21), giving rise to variable adipose expression of specificgenes. However, the importance of epigenetic mechanismsin controlling expression of one of these genes was laterdiscounted (52). Overall, the relative importance of ge-netic, epigenetic, and environmental factors in the re-sponse to high-fat feeding in C57Bl/6 mice is still unclear.

In conclusion, we show that a subset of C57Bl/6 micefed a HFD composed of palm oil developed NASH. Ourdata support the existence of a tight relationship betweenadipose tissue dysfunction and NASH pathogenesis andpoint to several novel potential predictive biomarkers forNASH.



ACKNOWLEDGMENTS

No potential conflicts of interest relevant to this articlewere reported.

C.D. designed the research, collected data, analyzed thedata, wrote the manuscript, and reviewed and edited themanuscript. U.T. analyzed the data and reviewed andedited the manuscript. S.K. collected and analyzed thedata. B.A. collected data and reviewed and edited themanuscript. R.S. collected data and reviewed and editedthe manuscript. M.V.B. analyzed the data and reviewedand edited the manuscript. T.R. analyzed the data andreviewed and edited the manuscript. S.K. designed theresearch, collected data, analyzed the data, wrote themanuscript, and reviewed and edited the manuscript. M.M.designed the research and reviewed and edited themanuscript.

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