Serum proteomic profiling of obese patients:correlation with liver pathology and evolution afterbariatric surgery

V Trak-Smayra,1,2 D Dargere,1 R Noun,3 M Albuquerque,1 C Yaghi,4

M-H Gannage-Yared,5 P Bedossa,1,6 V Paradis1,6

1 Centre de rechercheBiomedical Bichat Beaujon,INSERM U773, Paris, France;2 Departement d’Anatomiepathologique, Universite Saint-Joseph, Beirut, Lebanon;3 Service de Chirurgie hepato-biliaire, Hotel-Dieu de France,Beirut, Lebanon; 4 Serviced’Hepatologie Hotel-Dieu deFrance, Beirut, Lebanon;5 Service de Biochimie, Hotel-Dieu de France, Beirut, Lebanon;6 Service d’Anatomiepathologique Hopital Beaujon,Clichy, and Centre de RechercheBiomedicale Bichat Beaujon,INSERM U 772, Paris, France

Correspondence to:Dr V Paradis, PathologyDepartment, Beaujon Hospital,100 bd du general Leclerc,92110 Clichy, France;vparadis@teaser.fr

Revised 6 March 2008Accepted 11 March 2008Published Online First10 April 2008

ABSTRACTObjective: Chronic liver diseases, including cirrhosis, maydevelop in obese patients. Steatosis and non-alcoholicsteatohepatitis (NASH) are risk factors for progression tofibrosis. To date, diagnosis of steatosis and NASH relieson liver biopsy. The aim of the study was to identify serummarkers of steatosis and NASH in obese patients usingSELDI–TOF ProteinChip.Patients: Eighty obese non-alcoholic patient candidatesfor bariatric surgery and devoid of hepatitis B and Cinfection were selected. Serum samples were collectedbefore surgery and at 6 months after surgery for 33 ofthese patients. Wedge liver biopsy was performed at thetime of bariatric surgery. Twenty-four serum samples fromhealthy blood donors served as controls. The proteinprofiles of each serum were assessed using SELDI–TOFProteinChip technology and were compared according toliver histological lesions.Results: Twenty-four obese patients (30%) had non-significant liver lesions, 32 (40%) had significant steatosisand 24 (30%) had NASH. Comparison of serum proteinprofiles according to liver lesions identified three peaks(CM10-7558.4, CM10-7924.2 and Q10-7926.9) theintensity of which significantly increased according to theseverity of the liver lesions (steatosis and NASH) andreturned to normal after bariatric surgery. None wascorrelated with either liver function tests or metabolicparameters. Identification using immunoSELDI assaycharacterised these peaks as the double charged ions ofa- and b-haemoglobin subunits.Conclusion: The differential proteomic method demon-strated changes in serum protein profiles in obesepatients according to severity of liver lesions. Freehaemoglobin subunits may serve as a serum biomarker ofthe severity of liver damages.

Non-alcoholic fatty liver disease (NAFLD) covers aspectrum of liver damage mimicking alcoholic liverdisease and potentially leading to cirrhosis.1–3 Itoccurs in patients with metabolic syndrome,suffering from central obesity in association withother cardiovascular risk factors, without excessivealcohol consumption.4 5 NAFLD is becoming morefrequent with the increasing worldwide prevalenceof obesity.6 In this setting, a major challenge will beto identify patients at risk for deleterious evolutionin order to prevent cirrhosis and its complications.

Obesity-associated insulin resistance results inthe accumulation of free fatty acids and triglycer-ides in hepatocytes.7 Additional factors, such asexcessive production of reactive oxygen species,might induce inflammation and extracellular

matrix deposits.7 8 Morphologically, patterns ofliver damage vary from steatosis to steatohepatitis(NASH), fibrosis, cirrhosis, and even to thedevelopment of hepatocellular carcinoma (HCC).The disease prognosis differs according to theseverity of lesions, and the presence of NASHmight be a critical factor.9 Although biochemicaland radiological investigations are suggestive ofsteatosis, they cannot detect lesions consistentwith NASH, a diagnosis that still requires liverbiopsy. However, there is increasing reluctance onthe part of both patients and physicians to performliver biopsy due to its potential risk of complica-tions.6 10 Therefore, several retrospective studieshave sought to correlate clinical and biologicalvariables with histopathological patterns in anattempt to search for sensitive and specific non-invasive markers of NASH and advanced fibro-sis.9 11–14 Most of those studies pointed to high bodymass index (BMI), diabetes mellitus and older ageas relevant predictors of deleterious evolu-tion.9 11 12 14

Clinical proteomics is a validated approach thathas enabled the determination of new serumbiomarkers in several carcinomas, includingHCC.15–19 Using this approach, serum proteinprofiles are compared according to patientphenotype in order to isolate peaks or peakclusters expressed differentially. Among the differ-ent technologies available, surface-enhanced laserdesorption/ionisation–time of flight mass spectro-metry (SELDI–TOF MS) is attractive because itprovides protein profiles in an easy and rapidmanner from small amounts of proteins, obtainedfrom various biological complex samples.20 Usingthis approach, we searched for serum markers ofsteatosis and NASH in a cohort of morbidly obesepatients and we sought to determine potentialmodifications in their serum protein profiles afterbariatric surgery.

MATERIALS AND METHODSPatientsOur series included 80 consecutive candidates forbariatric surgery who were included prospectively.Patients were selected on the basis of high BMI(.32 kg/m2), absence of significant alcohol con-sumption (,200 g per week for men and 100 g forwomen) and negative autoimmune and viralhepatitis work-ups. Written informed consentwas obtained for all patients. A blood sample,collected before bariatric surgery, was analysed todetermine serum levels of alanine aminotransferase

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(ALT), aspartate aminotransferase (AST), c-glutamyltransferase(GGT), alkaline phosphatase, glucose, total cholesterol, trigly-cerides, serum levels of adiponectin, insulin, and determinationof homeostasis model assessment (HOM) index. An aliquot ofthe serum was also immediately frozen for proteomic analysisand stored at 280uC until use.

Bariatric surgery consisted of either gastric bypass orgastroplasty. Wedge liver biopsy was systematically performedduring surgery. Thirty-three of 80 patients were reviewed6 months after surgery. They were weighed and a blood samplewas collected for liver function tests, metabolic parameters andproteomic analysis.

A control group of 24 non-obese individuals was designatedamong blood donors fulfilling the inclusion criteria concerningalcohol consumption and viral hepatitis tests. For each ofthem, blood samples were collected and tested for proteomicanalysis.

Pathological analysisWedge liver biopsy was routinely processed for histologicalanalysis. Slides were stained with haematoxylin–eosin,Picrosirius red and Masson’s trichrome for evaluation of fibrosis.Scoring systems were adapted from Brunt and Kleiner’s criteria.21

Steatosis was scored as absent (,10%), mild (10–30%), moderate(30–60%) or severe (.60% of hepatocytes), respectively. Portaland lobular inflammatory infiltrates were graded as absent (0),mild (1) or significant (2). Fibrosis was staged according to Kleineret al: no fibrosis (0), zone 3 perisinusoidal or portal fibrosis (1),perisinusoidal and portal fibrosis without bridging (2), bridgingfibrosis (3) and cirrhosis (4). The presence of apoptotic bodies,ballooning degeneration and Mallory’s hyaline was noted(0 = absence, 1 = presence). The diagnosis of NASH was basedon a combination of steatosis and either lobular inflammationwith ballooning degeneration or extensive fibrosis (stage .2). Ascore of NASH was obtained by adding semi-quantitativeevaluation of inflammation, liver cell ballooning, and fibrosis.

Among the 33 patients who were reviewed 6 months aftersurgery, initial liver biopsy showed normal liver, steatosis andNASH at baseline in 11, 11 and 11 patients, respectively.

Proteomic analysisA total of 137 serum samples, comprising 80 samples belongingto obese patients before bariatric surgery (S1, serum collectedbefore patient’s transfer to the operating room), 33 samplescollected 6 months after surgery (S2) and 24 samples belongingto the control group were analysed. Each serum aliquot wasthawed and diluted (1:10) in denaturing buffer (urea 7 mol/l,thiourea 2 mol/l, CHAPS 4% (3-[(3-cholamidopropyl) dimethyl-ammonio]-1-propanesulfate), dithioerythritol 0.1%).

Serum samples were processed using three types of chip arrays(cationic exchange/CM10, anionic exchange/Q10 and immobi-lised metal ion affinity capture/IMAC30 ProteinChip array loadedwith zinc) according to the manufacturer’s protocols (CiphergenProteinChip Reader; Ciphergen Biosystems, Freemont, California,USA).

The arrays were analysed with the Ciphergen ProteinChipReader (series 4000, Ciphergen Biosystems). Intra-ProteinChiparray reproducibility was checked by spotting eight different

Table 1 Clinical and biological data of the different subgroups of patients

Non-obese controls Obese patients before bariatric surgery

p*

Obese patients afterbariatric surgery

p{n = 24 All patients (n = 80)Patients evaluated after6 months (n = 33) n = 33

Age (years) 30 (10) 35 (12) 35 (12) NS 35 (12)

Female/male ratio 11/19 60/20 25/8 NS 25/8

BMI (kg/m2) 24 (2.5) 42 (5.5) 41 (4.6) NS 30 (4) ,0.001

Diabetes (%) 0 (0%) 21 (26%) 6 (18%) NS 6 NS

Fasting glucose (mmol/l) NA 6.4 (3) 7 (4.3) NS 5.2 (0.7) ,0.05

Cholesterol (mmol/l) NA 5.5 (1) 5.4 (1) NS 5.0 (1.3) ,0.05

Triglycerides (mmol/l) NA 1.9 (0.9) 1.8 (0.8) NS 1.3 (0.6) ,0.05

AST (IU/l) NA 33.7 (18.3) 36.6 (23.1) NS 20.6 (5.6) ,0.01

ALT (IU/l) NA 44.7 (33.2) 44.2 (27.5) NS 26.8 (11.2) ,0.001

Alkaline phosphatase (IU/l) NA 72.2 (13.8) 72.3 (14.1) NS 68.7 (15.9) NS

HOMA index NA 2.8 (2.5) 2.6 (2.2) NS 2 (1.2) ,0.001

Adiponectin (mg/l) NA 7.8 (5.4) 8.2 (5.1) NS 11.4 (5.0) ,0.01

Insulin NA 10.1 (8.9) 9.3 (7.4) NS 8.9 (4.9) NS

Results are given as the mean (SD), except where indicated otherwise.*p, comparison between all obese patients and the group of 33 obese patients with follow-up after bariatric surgery.{p, comparison between and after surgery in the group of 33 patients with follow-up.ALT, alanine aminotransferase; AST, aspartate transaminase; BMI, body mass index; HOMA, homeostasis model assessment; NA, not applicable; NS, not significant.

Table 2 Main histological findings in obese patients before bariatricsurgery

Histological feature CategoryNo of biopsy specimens(%)

Steatosis No (,10%) 24 (30%)

Mild (,30%) 11 (14%)

Moderate (30–60%) 18 (22%)

Severe (.60%) 23 (29%)

Fibrosis stage 0 = None 33 (41%)

1 = Sinusoidal or portal fibrosis 24 (30%)

Sinusoidal (1A/1B) 5/0

Portal (1C) 19

2 = Portal and sinusoidal 17 (21%)

3 = Bridging fibrosis 6 (8%)

4 = Cirrhosis 0 (0%)

Diagnosis Non-significant 24 (30%)

Steatosis without NASH 32 (40%)

NASH 24 (30%)

NASH, non-alcoholic steatohepatitis.

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aliquots of one sample on the same array, and inter-ProteinChiparray reproducibility was checked by including one sample oneach array. The mean of the three inter-ProteinChip arrayscoefficient of variations ranged from 29.2% to 37.7%, and 29.3%to 33% for low and intermediate molecular weight proteins,respectively.

Statistical analysisSpectra were analysed with ProteinChip software version 3.0.2(Ciphergen Biosystems). For each comparison, raw intensitydata were normalised using the total ion current of all profilesand logarithm transformed. To characterise protein peaks ofpotential interest differentially expressed in various phenotypegroups of patients, the logarithm-transformed intensity of eachprotein peak was compared according to groups using non-parametric tests. Peaks were considered as significantly differentfor a p value less than 0.05.

To validate the results, we predicted the class of futuresamples according to their protein profiles using several models:compound covariate predictor, diagonal linear discriminantanalysis, nearest-neighbour classification, and support vectormachines with linear kernel. We estimated the prediction errorof each model using the leave-one-out cross-validation(LOOCV) procedure.22 23 For each LOOCV training set, theentire model-building process was repeated, including the peakselection process. We also evaluated whether the cross-validatederror rate estimate for a model was significantly less than wouldbe expected from random prediction. The class labels wererandomly permuted and the entire LOOCV process was repeated.

Identification of biomarkersTo confirm the identity of potential biomarkers, epoxy-activated protein chips (PS20, Ciphergen) were precoupled withantiserum H80 (rabbit polyclonal IgG against the a1-haemoglo-bin subunit), or antiserum H76 (rabbit polyclonal IgG againstthe b-haemoglobin subunit) or non-immune rabbit IgG (SantaCruz Biotechnology, Santa Cruz, California, USA). Antibody(4 ml, 0.2 mg/ml) was applied to the protein chip and mixedwith 2 ml 50 mmol/l NaHCO3 buffer (pH 9.2). After shaking for2 h at room temperature in a humid chamber, spots werewashed (0.5 mol/l ethanolamine (pH 8) for 1 h, and thenphosphate-buffered saline (PBS) containing 0.5% Triton X-100).

Serum samples, diluted 2-fold in PBS containing 0.1% Triton X-100, were applied to the spot. The chips were incubated for 2 h,and wells were washed twice with PBS containing 0.1% TritonX-100, then with 50 mmol/l Tris-HCl, 1 mol/l urea, 0.1%CHAPS and 0.5 mol/l NaCl (pH 7.2), and then with HEPES5 mmol/l (pH 7.2) before air drying. Sinapinic acid (20 mg/ml in50% acetonitrile and 0.5% trifluoroacetic acid (TFA), 260.5 ml)was added to each spot and dried. Protein mass spectra weregenerated.

RESULTS

Clinical and biological dataThe group of obese patients comprised 60 women and 20 menwith a mean age of 35 years (19–67 years). The mean BMI uponadmission was 42 kg/m2 (range, 37–47). The mean BMImeasured 6 months after bariatric surgery was 30 kg/m2 (range,26–34). The mean BMI of the control group was 24 kg/m

2

(range, 21.5–26.5). Detailed biological data are presented intable 1. Baseline clinical and biological data of obese patientswith follow-up available 6 months after bariatric surgery didnot differ from the whole group of obese patients.

Figure 1 Mean peak intensity of selected peaks according to liver lesions before and after bariatric surgery. NASH, non-alcholic steatohepatitis.

Figure 2 Mean peak intensity of selected peaks according to theamount of steatosis. Error bars indicate standard error.

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Liver biopsy analysisEighty biopsy specimens belonging to obese patients werecollected at the time of bariatric surgery. Steatosis was present(.10%) in 56 patients (70%), and 23 (29%) had severe steatosis(.60%). When steatosis was mild or moderate, it waspredominantly located in the centrolobular area. Portal andlobular inflammation was present to a mild degree in 44 (55%)and 39 cases (49%), respectively. Ballooning degeneration wasfound in six cases (7.5%) and apoptotic bodies were detected in25 cases (31%). Fibrosis was staged 0 in 33 cases (41%), 1 in 24cases (30%), 2 in 17 cases (21%) and 3 in six cases (8%). Therewere no cases of cirrhosis. Finally, 24 patients (30%) wereconsidered as having no significant liver lesions, 32 (40%) assignificant steatosis alone (without NASH) and 24 (30%) asNASH. The main histopathological data are shown in table 2.

Proteomic analysis

Comparison of protein profiles of obese patients and controlsFor each serum, a mean of 666 protein peaks were generatedwith the three Chip-arrays (IMAC 30, Q10 and CM10).Comparison of the protein profiles obtained in the obese groupbefore surgery (n = 80) with those of the control group (n = 24)showed a total of 112 differentially expressed protein peaks(p,0.01). Seventy-one were upregulated in the obese groupwhereas 41 were downregulated. Comparing the proteomeprofiles of the control group and those of the obese patientswithout significant liver lesions (n = 24), 97 peaks differedsignificantly (p,0.05).

Comparison of protein profiles in obese patients according tohistopathological lesionsIn the group of obese patients, comparison of those having nosignificant liver lesions (n = 24) with those with steatosis alone(n = 32) identified 17 differentially expressed protein peaks(CM10: 8, Q10: 4 and IMAC30: 5, p,0.05). Eight proteins wereupregulated and nine were downregulated in the presence ofsignificant steatosis. In a similar manner, comparison of serumprotein profiles of obese patients with NASH (n = 24) to thosewithout significant liver lesions (n = 24) showed 50 differen-tially expressed protein peaks (Q10: 12, CM10: 26 and IMAC30:12). Forty-six proteins were upregulated and four were

downregulated in NASH. Some of the peaks had very high pvalues in different statistical tests (eg, p,1025) indicating strongstatistical significance of differential expression. Comparison ofprotein profile of the group of patients with steatosis withoutNASH to those with NASH identified 67 peaks differentiallyexpressed (CM10, 22; IMAC, 24; and Q10, 21). Fifty wereupregulated and 17 downregulated when serum proteomeprofiles of patients with NASH were compared to those withsteatosis.

To validate the results, we assessed the classification of futuresamples with different models and the LOOCV procedure. Forprediction of NASH according to the serum protein profile, 75%of patients were correctly classified for the presence of NASH.Sensitivity, specificity, positive predictive value and negativepredictive value were 0.83, 0.67, 0.71 and 0.8, respectively. Forprediction of steatosis, the percentage of correct classificationswas also 75%. Sensitivity was 0.78 and specificity was 0.71.

Modifications in protein profiles after weight loss in obese patientsComparison of serum protein profiles before and after bariatricsurgery showed 94 significantly modified peaks. Sixty-twopeaks were downregulated in the serum and 32 peaks wereupregulated after weight loss. Six out of the 17 protein peakswhich had been previously correlated with the presence ofsignificant steatosis, as well as 17 of the 50 peaks associatedwith the diagnosis of NASH, returned to near normal valuesafter bariatric surgery.

Serum biomarkers of liver lesions in obese patientsFinally, three protein peaks (CM10-7558.4, CM10-7924.2 andQ10-7926.9) were found to be common when comparing peaksdifferentially expressed between obese patients without lesionsto those with pure steatosis and those with NASH.Interestingly, mean peak intensity progressively and signifi-cantly increased from no lesion to steatosis and then to NASH(p,0.001). Six months after bariatric surgery, all three peaks

Figure 3 Mean peak intensity of selected peaks according to non-alcoholic steatohepatitis (NASH) score. Error bars indicate standarderror.

Figure 4 Mean peak intensity of selected peaks according to liverhistology before and after surgery in the group of 33 obese patients whowere re-evaluated 6 months after surgery. Cross = mean peak valuebefore bariatric surgery, circle = mean peak value after surgery. In red,patients with normal liver at baseline; in green, patients with steatosis;and in blue, patients with non-alcoholic steatosis (NASH). *p,0.05,**p,0.001 for comparison before and after surgery. Error bars indicatestandard error.

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returned to values close to those of patients without liverlesions (fig 1).

Mean intensity of each of these three peaks was notsignificantly different when comparing the control group toobese patients without liver lesions. Furthermore, in the wholegroup of obese patients, no significant correlation was observedbetween any of the three peaks and laboratory parameters,either liver function tests or metabolic parameters. Peakintensities of CM10-7558.4, CM10-7924.2 and Q10-7926.9 werethen compared in the group of 80 obese patients according tosteatosis intensity (,10%, n = 24; 10–30%, n = 11; and .30%,n = 41). A clear significant increase of all three peaks wasobserved according to the amount of steatosis (p,0.001 for eachpeak) (fig 2). Similarly, CM10-7558.4, CM10-7924.2 and Q10-7926.9 peak intensity also increased according to a NASHscoring system (p,0.01 for CM10-7558.4 and CM10-7924.2,and p,0.05 for Q10-7926.9) (fig 3). Comparing peak intensitybefore and after surgery in the 33 patients who were re-evaluated 6 months after surgery, no change was observed forpatients having normal liver at baseline, whereas a significantdecrease in all peaks was found in patients with steatosis orNASH (fig 4). Taken together, all these results suggest thatCM10-7558.4, CM10-7924.2 and Q10-7926.9 are serum biomar-kers mirroring liver lesions rather than severity of serummetabolic disturbances or liver test abnormalities.

Finally, we assessed performance of the two main diagnosticpeaks (CM10-7558.4 and CM10-7924.2) and metabolic para-meters (serum level of adiponectin, insulin and homeostasismodel assessment (HOMA) index) for the diagnosis of steatosisand NASH using areas under the receiver operating character-istic curves (AUROCs). The AUROCs of the two protein peakswere superior to those of metabolic parameters both fordiagnosis of steatosis and NASH (table 3).

Identification of biomarkersThe very close m/z values between CM10-7924 and Q10-7926suggested that they were both related to the same protein thatbinds to CM10 and Q10 Protein arrays. Furthermore, weobserved a significant and strong correlation between peakintensity of CM10-7924.2 and CM10-7558.4 (r = 0.84, p,0.001)

(fig 5). This also suggested that these two peaks were differentforms related to the same protein species. According to the m/zratio, we assumed that CM10-7558.4 and CM10-7924.2 werethe double-charged ions of haemoglobin-a (calculated mass,15 126 kDa) and haemoglobin-b (calculated mass, 15 857 kDa)subunits, respectively. These two peaks were also representedby two prominent peaks in the SELDI spectra (fig 6). Tovalidate this assumption, we performed an immuno-SELDIassay. As shown in fig 7, protein-Chip precoupled withantiserum against haemoglobin-a selectively retained a protein,which, after desorption and ionisation–TOF, produced aspectrum with two peaks at 7558 and 15 126 Da. Similarly,proteinChip coupled with a specific antibody against haemo-globin-b also produced a spectrum with two peaks at 7924 and15 857 Da. A chip coated with non-immune rabbit IgG in thepresence of the same serum or coated with either antibodyagainst haemoglobin-a or haemoglobin-b in the presence of PBSdid not capture any of these peaks (fig 7). These results stronglysuggest that CM10-7924.2 and CM10-7558.4 correspond to thedouble-charged ions of a- and b-haemoglobin subunits.

Figure 5 Correlation between CM-7558.4 and CM-7924-2 peak intensity inobese patients.

Table 3 Areas under the receiver operating characteristic curves(AUROCs) for the diagnosis of steatosis and non-alcoholic steato-hepatitis (NASH)

Metabolic parameter, or peak AUROC 95% CI

Steatosis

Adiponectin 0.55 0.5 to 0.66

Insulin 0.63 0.5 to 0.78

HOMA 0.65 0.5 to 0.8

CM10-7558.4 0.73 0.58 to 0.88

CM10-7924.2 0.71 0.56 to 0.87

NASH

Adiponectin 0.64 0.5 to 0.79

Insulin 0.56 0.56 to 0.86

HOMA 0.73 0.58 to 0.88

CM10-7558.4 0.81 0.7 to 0.92

CM10-7924.2 0.81 0.71 to 0.91

CI, confidence interval; HOMA, homeostasis model assessment.

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DISCUSSIONThis study focused on serum proteomics in a cohort of obesepatients who underwent bariatric surgery in order to identifynon-invasive markers of liver disease. We showed that threeprotein peaks (CM10-7558.4, CM10-7924.2 and Q10-7926.9),which were related to different haemoglobin subunits, progres-sively increased in intensity from patients who were obese butwithout liver lesions to those with steatosis and NASH, butreturned to near normal values after patients had lost weight.

Morbid obesity is a known risk factor for chronic liver disease,and an increased risk of progression to cirrhosis has beenassociated with the diagnosis of NASH.1–3 6 The prevalence ofNASH had been previously estimated at 2.7% in the generalpopulation, but this percentage tends to increase to 10% or even30% in obese individuals.24 In our series, 70% of the patientspresented with steatosis and 30% of them were diagnosed ashaving NASH on biopsy. These results are similar to previousseries, although slight variations exist according to histopatho-logical criteria for defining NASH.24 While the prevalence ofextensive fibrosis has been reported in 20–40% of cases, only 8%of our patients displayed septal fibrosis.11–14 This difference couldbe explained by the predominance, in the present series, ofyoung individuals, bearing in mind that fibrosis advances withage.11 12 Indeed, when the fibrosis stage is mild, periportalfibrosis is more prevalent than pericentrolobular fibrosis,suggesting that this feature is a characteristic in obese patients.25

Up to now, no screening test has proven its efficacy atdetecting liver damage in obese patients. The diagnosis relies onliver biopsy, since liver blood tests may be normal in thiscontext. Ultrasound and computed tomography are efficient atidentifying significant steatosis but are not suitable forvisualising liver inflammation and the early stages of fibrosis.Therefore, while liver biopsy remains the ‘‘gold standard’’, it isfar from acceptable because of its adverse effects in a diseaseoften considered as benign. In our study, we attempted tosearch for non-invasive markers of steatosis and NASH using aproteomics approach. In contrast to other studies targetingspecific proteins, this approach provides a complete proteinprofile of major proteins present in a serum sample.26–28 In ourseries, comparison of the protein profiles obtained in the

different patient categories led to the determination of severaldifferentially expressed protein peaks. This proteomics approachhas already been tested in a series of obese patients, and it wasfound that, among several differentially expressed protein peaksbetween the four groups in the study (controls, steatosis,steatosis and NASH), the intensity of one (H50-6833 Da) had amolecular weight very close to a protein peak characteristic ofNASH in our series (CM10-6831 Da).29 Interestingly, our studypointed out three peaks (CM10-7558.4, CM10-7924.2 and Q10-7926.9), the expression levels of which increased starting fromobese patients with no lesions, to steatosis, then to NASH, andreturning to control values after weight loss. It can be suggestedthat they could reflect blood markers of either metabolicsyndrome or liver function tests. However, when comparingthese three markers between control patients and obese patientswithout liver lesions, they were at similar levels, suggesting thatthese biomarkers are not related to the metabolic syndrome butrather to liver lesions. In fact, we cannot exclude the possibilitythat some overweight controls potentially have unrecognisednon-alcoholic fatty liver disease (NAFLD) in the absence of anyimaging in that group. Furthermore, none of the liver functiontests showed significant correlation with peak intensity at theindividual level. Finally, although liver function tests did notsignificantly change within the group of patients with steatosisalone, according to the amount of steatosis, the peak intensitiesof CM10-7558.4, CM10-7924.2 and Q10-7926.9 did. The samewas also true for patients with NASH. In addition, in the groupof patients with serum available before and after bariatricsurgery, whether the peak intensities decreased after surgery inthose with steatosis or NASH at baseline, no change wasobserved in patients with normal liver at baseline. All these datatogether strongly support the hypothesis that the three proteinpeaks are relevant markers of liver lesions.

Using an immunocapture test, we identified these peaks as a-and b-haemoglobin subunits. Haemoglobin consists of a- and b-polypeptide chains. Haemoglobin is normally sequestrated inerythrocytes. Why free haemoglobin subunits are detected inthe serum of patients is unclear. It might be argued that pre-analytical serum processing might induce lysis of red blood cellsand release of haemoglobin. However, the close correlation

Figure 6 Serum protein profiles ofobese patients with non-significantlesions (A) and obese patients with non-alcoholic steatosis (NASH) (B) in CM10ProteinChip. In the sera of obese patientswith NASH (B), the haemoglobin-asubunit appears as a double-charged ionat m/z = 7558 Da (double green arrow)and 15 126 Da (single green arrow). Thehaemoglobin-b subunit double-chargedion is detected as a peak at 7924 Da(double red–green arrow) and 15 857 Da(single red arrow). These peaks are notdetected in sera of obese patients withoutliver lesions (A).

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between the amounts of haemoglobin subunits, as assessed bytheir peak intensities, and the severity of liver lesions does notsupport the hypothesis of pre-analytical serum degradation atrandom. Interestingly, an increase in erythrocyte susceptibilityto haemolysis in response to free-radical injury in an experi-mental model of NASH and in obese individuals has beenreported.30 31 Because of excessive phagocytosis of damagederythrocytes by Kupffer cells in NASH, iron accumulates in thesinusoids with subsequent promotion of inflammation andfibrosis in the liver. The role of iron in the pathogenesis of thisdisease was further confirmed by the improvement of biologicaltests and pathological liver lesions after iron depletion.32

Although critical to oxygenation, free haemoglobin is directlytoxic to cells through lipid peroxidation.33–34 Moreover, reactiveoxygen species, major contributors to the pathogenesis ofNASH and key factors in stimulating haemolysis, may be thecommon pathway resulting in the increase in a- and b-haemoglobin observed in patients displaying NASH. Finally,the possibility that free haemoglobin may serve not only as amarker but also as a weapon for liver cell injury in this contextmight be considered.33

In the present study, we demonstrated that a proteomics-based method allows changes in serum protein profiles in obesepatients to be outlined according to the severity of the liverlesions and that these profiles were significantly modified afterweight loss, suggesting an improvement in liver lesions.

Identification of free haemoglobin subunits as markers of theseverity of liver damage may serve as serum biomarker of liverlesions. Further studies are required to confirm these observa-tions and their physiological implications, especially in apopulation of non-morbidly obese patients.

Funding: Financial support was provided by research grant ‘‘Conseil de la recherche,Universite Saint-Joseph’’ Beirut, Lebanon.

Competing interests: None.

Ethics approval: Ethics approval was obtained from Universite Saint-Joseph, Beirut,in November 2005.

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Figure 7 Characterisation of proteinpeaks using immuno-SELDI in sera ofobese patients with NASH. (A) Protein-Chip precoupled with antiserum againsthaemoglobin-a selectively retained aprotein, which, after desorption andionisation–TOF produced a spectrum withtwo peaks at m/z = 7558 Da (greenarrow) and 15 126 Da (red arrow). Thesepeaks were not observed in the presenceof PBS. A chip coated with non-immuneIgG in the presence of the same serumdid not capture any of these peaks.(B) The same experiments with theproteinChip coupled with a specificantibody against haemoglobin-b. Twopeaks at 7924 Da (green arrow) and15 857 Da (red arrow). NASH, non-alcoholic steatosis; PBS, phosphate-buffered saline; SELDI, surface-enhancedlaser desorption/ionisation; TOF, time offlight.

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ANSWERFrom the question on page 742

Epitheloid granulomata were detected in the gastric antrum andcorpus as a manifestation of upper gastrointestinal tractCrohn’s disease and an abundance of giardia lambliasis couldbe ascertained on the mucosal surface of the duodenum (fig 1,below). The patient was subsequently treated with metronida-zole (400 mg, three times daily, for 7 days) and recoveredimmediately. He did not have any further symptoms for thefollowing 18 months whilst remaining on azathioprine andfollow-up stool examination did not reveal giardia cysts.

The flagellated protozoan Giardia lamblia is spread viacontaminated food or water. It causes an epithelial barrierdysfunction1 resulting in symptoms that may mimic activeCrohn’s disease. Worldwide, about 200 million new infectionsare reported every year and incidence may be significantlyincreased in some populations, such as patients with Crohn’sdisease.2 Diagnosis is established by microscopic examination ofstool and through detection of the parasites in duodenal biopsies,but only direct fluorescent-antibody and enzyme immune assaysattain a sensitivity of over 90%. Mesenterial lymphadenopathy isfrequently found in active giardiasis.3 Therapeutic options includemetronidazole, tinidazole and albendazole.

Gut 2009;58:832. doi:10.1136/gut.2008.167874a

REFERENCES1. Troeger H, Epple H, Schneider T, et al. Effect of chronic Giardia lamblia infection on

epithelial transport and barrier function in human duodenum. Gut 2007;56:328–35.2. Scheurlen C, Kruis W, Spengler U, et al. Crohn’s disease is frequently complicated by

giardiasis. Scand J Gastroenterol 1988;23:833–9.3. Orchard JL, Petorak V. Abnormal abdominal CT findings in a patient with giardiasis.

Resolution after treatment. Dig Dis Sci 1995;40:346–8.

Figure 1 Histopathological findings in the duodenum with an abundanceof giardia on the mucosal surface of the duodenal villi (white arrows).

Editor’s quiz: GI snapshot

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832 Gut June 2009 Vol 58 No 6

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 V Trak-Smayra, D Dargere, R Noun, et al. and evolution after bariatric surgerypatients: correlation with liver pathology Serum proteomic profiling of obese

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