The macrophage activation marker sCD163 is associated with morphological disease stages in patients with non-alcoholic fatty liver disease
Konstantin Kazankov1, Francisco Barrera2,3, Holger Jon Møller4, Chiara Rosso5, Elisabetta Bugianesi5, Ezio David6, Ramy Ibrahim Kamal Jouness5, Saeed Esmaili2, Mohammed Eslam2, Duncan McLeod7, Bo Martin Bibby8, Hendrik Vilstrup1, Jacob George2, Henning Grønbæk1 1) Department of Hepatology and Gastroenterology, Aarhus University Hospital, Aarhus, Denmark
2) The Storr Liver Centre, Westmead Millennium Institute, University of Sydney and Westmead Hospital, Westmead, Australia
3) Department of Gastroenterology, Pontificia Universidad Católica, Santiago, Chile 4) Department of Clinical Biochemistry, Aarhus University Hospital, Aarhus, Denmark
5) Division of Gastroenterology and Hepatology, Department of Medical Sciences, University of Torino, Torino, Italy
6) Division of Pathology, Department of Medical Sciences, University of Torino, Torino, Italy 7) Department of Anatomical Pathology, Institute of Clinical Pathology and Medical Research (ICPMR), Westmead Hospital, Westmead, Australia
8) Department of Biostatistics, Aarhus University, Aarhus, Denmark
Corresponding author:
Konstantin Kazankov, MD, PhD
Department of Hepatology and Gastroenterology Aarhus University Hospital
Norrebrogade 44 DK-8000 Aarhus C Denmark Phone: 0045 25 21 09 33 E-mail: [email protected] Word count Abstract: 215 words
Total manuscript: xx words Number of tables: 3
Abbreviations
NAFLD, non-alcoholic fatty liver disease; NASH, non-alcoholic steatohepatitis; sCD163, soluble CD163; CK-18, cytokeratin-18; BMI, body mass index; HOMA-IR, homeostatic model assessment of insulin resistance; NAFLD-FS, NAFLD fibrosis score; ELISA, enzyme-linked immunosorbent assay; FLIP algorithm, Fatty Liver Inhibition of Progression algorithm; ROC, Receiver Operating Characteristics; IQR, interquartile range; AUROC, area under Receiver Operating Characteristics curve; TACE/ADAM17, tumor necrosis factor alpha-converting enzyme; ALT, alanine
transaminase; AST, aspartate transaminase; CI, confidence interval; OR, odds ratio
Conflict of interests
Aarhus University and HJM have received royalties from IQ-products, who sell ELISA kits for sCD163 measurement. A different kit was used in the present study, and the study was not supported by IQ-products in any way.
IQ-products: Rozenburglaan 13a, 9727 DL Groningen, Netherlands. Tel: +31 (0) 50 5757 000. http://www.iqproducts.nl
Financial support
The NOVO Nordisk Foundation, The Danish Strategic Research Council (10-092797) and
“Savværksejer Jeppe Juhl og hustru Ovita Juhls mindelegat”. JG is supported by a National Health and Medical Research Council of Australia (NHMRC) Program Grant (1053206), project grants (632630, 1049857), and the Robert W. Storr Bequest to the Sydney Medical Foundation, University of Sydney. EB is supported by FP7/2007-2013 under grant agreement no HEALTH-F2-2009-241762 for the project FLIP and by PRIN 2009ARYX4T.
Background and aims: Macrophage activation plays a key pathogenic role in experimental non-alcoholic fatty liver disease (NAFLD) and contributes to the progression of steatohepatitis (NASH) and fibrosis. We studied macrophage activation in human NAFLD by measuring soluble (s)CD163, a specific macrophage activation marker, hypothesizing that sCD163 would be associated with the patients’ morphological disease grade. Further, we investigated an association between sCD163 and the apoptosis marker cytokeratin-18 (CK-18) to explore a link between macrophage activation and apoptosis.
Methods: sCD163 associations with biochemical and histological measures of NAFLD were investigated in two independent cohorts of 157 Australian and 174 Italian NAFLD patients with liver biopsies graded for NAFLD severity, steatosis, and fibrosis. sCD163 and CK-18 were measured by ELISA.
Results: In both cohorts sCD163 increased in parallel with the patients’ morphological disease grading, being independently associated with the Kleiner fibrosis score (p<0.001). A high sCD163 predicted advanced fibrosis (F≥3; Australian cohort: AUROC 0.77 (95% CI: 0.76–0.87), Italian cohort: 0.80 (95% CI: 0.72–0.88)). In both groups, sCD163 was independently associated with CK-18 (p<0.001).
Conclusion: Soluble CD163 reflecting macrophage activation is associated with morphological features of NAFLD suggesting their involvement in the pathogenesis of NAFLD, NASH and particularly fibrosis. An independent association between sCD163 and cytokeratin-18 suggests that apoptosis may contribute to macrophage activation in NAFLD/NASH.
Key words: Non-alcoholic steatohepatitis, liver fibrosis, macrophages, biomarker, cirrhosis KEY POINTS
- sCD163, a specific macrophage activation marker, increases in parallel with the histological severity of non-alcoholic fatty liver disease in two independent cohorts
- sCD163 is independently associated with fibrosis stage after adjustment for known NAFLD risk factors
- sCD163 shows promising capability as a marker of advanced fibrosis in NAFLD patients - sCD163 is independently associated with the apoptosis marker cytokeratin-18, which suggest apoptosis may contribute to macrophage activation in NAFLD.
Macrophages in the liver play a critical role in inflammation and fibrosis[1], including in non-alcoholic fatty liver disease (NAFLD) and non-non-alcoholic steatohepatitis (NASH). The mechanisms for macrophage activation and action have been reviewed recently[2], however, the vast majority of studies reporting an essential role for macrophages in NAFLD/NASH stem from experimental models[3, 4]; human data remain scarce. This gap may to some extent be filled by assessing the circulating levels of soluble (s)CD163 in patients with NAFLD/NASH.
CD163 is a lineage-specific hemoglobin-haptoglobin scavenger receptor expressed exclusively on the surface of monocytes and macrophages and is up regulated in conditions with macrophage activation[5, 6]. Following activation, CD163 is shed from the cell surface and detected in the blood as sCD163[7]. We have previously demonstrated a role for macrophage activation in inflammatory liver diseases through close associations between sCD163 and the severity of cirrhosis, chronic viral hepatitis and alcoholic hepatitis, as well as the degree of portal hypertension and its
complications[8-14].
In children with NAFLD, the number of CD163-positive macrophages increases in association with histological disease severity[15], and we have shown cross-sectional and dynamic associations between sCD163 and liver enzymes in obese children undergoing lifestyle intervention[16].
Recently, we and others demonstrated associations of sCD163 with histological NAFLD severity in morbidly obese adults and a reduction in their levels after bariatric surgery[17, 18]. These findings were recently confirmed with a reduction in sCD163 levels after bariatric surgery in association with diminished intrahepatic fat content[19]. However, sCD163 has not been investigated specifically in patients with histologically confirmed NAFLD/NASH.
We hypothesized an association between the macrophage activation marker sCD163 and NAFLD severity; we therefore measured sCD163 levels in two cohorts of patients with biopsy-proven NAFLD and related our findings to biochemical and histological measures of disease severity. Apoptosis, which can be assessed by cytokeratin-18 (CK-18), may be involved in the pathogenesis of NASH[20], however, the association between macrophage activation and apoptosis by CK-18 apoptosis has not been explored yet. Thus, we investigated the association between sCD163 and CK-18.
PATIENTS AND METHODS Study population
We undertook this cross-sectional study in two cohorts from liver centers in Australia and Italy. The Australian cohort consisted of patients consecutively recruited at the Storr Liver Centre, Westmead Hospital, Westmead, Australia. The Italian cohort comprised patients from the Division of
Gastroenterology and Hepatology, Department of Medical Sciences, University of Torino, Italy. All patients were referred for the investigation of abnormal liver tests or steatosis detected by
ultrasound. All patients had an alcohol intake of <20 g/day (males) or <10 g/day (females) assessed by two separate interviews with the patient and close family members. The diagnosis of NAFLD was established by liver biopsy in all cases. We carefully excluded patients with liver disease of other etiology using standard assays and methods. The final number of patients eligible was 157 in
the Australian cohort and 174 in the Italian cohort. At the time of liver biopsy, demographic and clinical data were obtained, including age, gender, ethnicity, height, weight, and waist
circumference. Body Mass Index (BMI) was calculated. Arterial hypertension was defined as blood pressure ≥130/≥85 mmHg or treatment with antihypertensive drugs. Diabetes was defined as fasting blood glucose ≥7.0 mmol/L, previous diagnosis of diabetes or use of anti-diabetic drugs.
Hyperlipidemia was defined as fasting total cholesterol >5.5 mmol/L, triglycerides >1.7 mmol/L or treatment with lipid-lowering drugs.
At the time of biopsy, a fasting blood sample was obtained and routine biochemical tests were performed as described below. Additional blood samples were drawn and frozen at -80°C for future research. All patients signed an informed consent form in accordance with the Helsinki Declaration. The acquisition, storage, and use of blood samples were approved by the Sydney West Area Health Service Ethics Committee and by the Ethics Committee of the University Hospital San Giovanni Battista of Torino.
Biochemical analyses
Haematological and liver parameters, fasting glucose and insulin, triglycerides and cholesterol and its components were determined using standard assays and methods. The Homeostatic model assessment of insulin resistance (HOMA-IR) was calculated[21]. The NAFLD Fibrosis Score (NAFLD-FS) was calculated according to the established formula[22].
All sCD163 measurements were performed at the Department of Clinical Biochemistry, Aarhus University Hospital. The plasma concentration of sCD163 was determined in duplicate by an in-house sandwich ELISA using a BEP-2000 ELISA-analyser (Dade Behring) essentially as
previously described[23]. Soluble CD163 is resistant to repeated freezing and thawing[23]. Control samples and serum standards with concentrations that ranged from 6.25 to 200 µg/l were included in each run to avoid bias. The inter-assay coefficient of variation in the current project (n=8) was 5.9-8.1 % at a level of 1.40 mg/l and 4.1-4.3% at a level of 3.77 mg/l. The limit of detection was 6.25 μg/L. We have previously established a reference interval (0.69–3.86 mg/L) for sCD163 in a large cohort (n=240) of healthy individuals using the same assay[24].
The determination of CK-18-Asp396 was performed by the commercial M30-Apoptosense enzyme-linked immunosorbent assay (ELISA) Kit (PEVIVA, Sweden) according to the manufacturer’s instructions in samples collected at the time of liver biopsy and stored at -80°C. CK-18 was measured in all samples from both cohorts at the Department of Medical Sciences, University of Torino, Italy, to eliminate inter-lab variability. Inter and intra-assay coefficients of variation were below 10%.
Histological analysis
Stained liver biopsies were examined by experienced pathologists blinded to clinical information (Duncan McLeod and Ezio David) and assessed as described by Kleiner et al.[25] for steatosis (graded 0–3), hepatocyte ballooning (0–2) and lobular inflammation (0–3). The Kleiner Fibrosis
Score, ranging 0–4, was determined. The diagnosis of NASH was based on the Fatty Liver
Inhibition of Progression (FLIP) algorithm[26]. All biopsies had a minimum of 11 portal tracts, and inadequate biopsies were excluded. In the Australian cohort, this led to missing histological data in six cases. Moreover, in another 33 patients of the Australian cohort, the differentiation between grades of steatosis 0 and 1 was lacking, and the diagnosis of NASH could not be made. In the Italian cohort, all 174 biopsies were of adequate quality as screening for inadequate liver biopsies was made before the inclusion of cases in the database.
We assessed the interobserver variation in histological assessment between the two liver
pathologists in a subset of 40 randomly selected patients from the Australian cohort. We found an interobserver agreement with kappa values of 0.85 (95% CI: 0.71–0.99) for steatosis, 0.66 (95% CI: 0.46–0.87) for hepatocyte ballooning, 0.66 (95% CI: 0.48–0.85) for lobular inflammation, and 0.78 (95% CI: 0.66–0.88) for fibrosis, comparable to previously published results[25].
Immunohistochemistry
Immunohistochemical staining was done in representative biopsies from seven randomly selected patients with NASH and another seven without NASH. The primary antibodies were mouse monoclonal anti-human CD163 (Cell Marque, USA, MRQ-26) diluted 1:50. Cell clustering in the liver biopsies was quantified as the observed number of CD163-stained clusters divided by the total length of the stained cell cores.
Statistical methods
Student’s t-test was used for the comparison of normally distributed variables between the groups. For non-normally distributed data, the Mann-Whitney test was used. The relationship between sCD163 and other continuous variables was analysed by simple linear regression or Spearman's rank correlation. Spearman’s rank test was used to study the relationships between sCD163 and histological scores. For differences in proportions, we used the χ2-test or Fisher’s exact test. To investigate the relationship between sCD163 and the histological scores adjusted for the NAFLD risk factors ethnicity, BMI, waist-hip ratio, age, gender, and the presence of diabetes,
hyperlipidaemia and hypertension, we used multiple ordered logistic regression analysis. In addition, the acute phase protein C-reactive protein was included in this analysis. In the Italian cohort, we included age, gender, BMI, waist and the presence of diabetes, hyperlipidaemia and hypertension, while ethnicity was the same (Caucasian) for all subjects.
Non-parametric Receiver Operating Characteristics (ROC) analysis was used to assess the
performance of sCD163 in the prediction of advanced fibrosis and NASH. All data are expressed as means ± SD and medians with interquartile ranges (IQR) or proportions. A p-value ≤0.05 was considered statistically significant. STATA version 13.0 ®StataCorp LP was used for data analysis; kappa statistics for interobserver variation of histological examinations were performed using MedCalc version 12.7 software.
RESULTS
Patient characteristics
Demographic, clinical, biochemical and histological data for the patients in both cohorts are presented in Table 1. Patients in the Australian cohort were slightly older and had a higher proportion of females. They also had higher BMI and were more insulin resistant with higher HOMA-IR and prevalence of diabetes. The patients in the Italian cohort had more severe
histological disease with higher fibrosis score and percentage with NASH (Table 1), as well as more pronounced lobular inflammation and hepatocyte ballooning (Supplementary Table 1).
sCD163 and liver histology
Focusing on liver fibrosis first, we observed higher sCD163 in patients with advanced fibrosis (F≥3) than in those with lower fibrosis stages (Australian cohort: 3.9 (3.0–4.3) vs. 2.5 (1.9–3.1) mg/L, p<0.001; Italian cohort: 2.5 (1.9–3.5) vs. 1.4 (1.1–1.9) mg/L, p<0.001) and correlated with the Kleiner fibrosis score (Australian cohort: rho=0.42, p<0.001; Italian: rho=0.45, p<0.001) (Figure 1A). Further, sCD163 showed a highly significant independent association with the fibrosis score in both the Australian (p<0.005) and the Italian (p=0.003) cohorts after adjustment for the known NAFLD risk factors in multiple ordered logistic regression analysis.
We also investigated the association of sCD163 with the more dynamic aspects of liver pathology in the cohorts. In both cohorts, sCD163 correlated with steatosis (rho=0.22, p=0.02 and rho=0.33, p<0.001) and hepatocyte ballooning (rho=0.38, p<0.001 and rho=0.13, p=0.09) (Figure 1B, C). In the Italian cohort, sCD163 was independently associated with the steatosis score after adjustment for the NAFLD risk factors in multiple ordered logistic regression analysis (p=0.001). After the same adjustment, sCD163 was associated with hepatocyte ballooning (p<0.001) only in the Australian cohort.
In the Australian cohort we observed higher sCD163 levels in patients with NASH s defined by the FLIP algorithm than in those without NASH (3.1 (2.6–4.3) vs. 2.4 (1.9–3.0) mg/L, p<0.001), but not in the Italian cohort (1.6 (1.2–2.3) vs. 1.5 (1.1–2.2) mg/L, p=0.52). Further, sCD163 was significantly associated with lobular inflammation in the Australian cohort only (rho=0.26, p=0.001) (Figure 1D).
Immunohistochemistry
In order to link evidence of macrophage activation in plasma to liver disease we examined liver biopsies by immunohistochemistry for CD163 expression in a subset of patients. CD163-stained cells were observed in the hepatic sinusoids of patients both with and without NASH. However, in patients with NASH we observed clustering of CD163-positive macrophages, which was nearly absent in patients without NASH (Figure 2), quantitatively expressed by the marked difference in the number of clusters/mm total stained cell core length (1.94 ± 1.48 vs. 0.36 ± 0.49, p=0.02). Moreover, the number of CD163-positive clusters/mm was closely associated with sCD163 levels (r=0.77, p=0.016).
sCD163 as a predictive marker of advanced fibrosis and NASH
We examined whether sCD163 would serve as a non-invasive marker for the presence of advanced fibrosis. In non-parametric ROC analysis, sCD163 was a good predictor for advanced fibrosis, and the AUROCs of sCD163 were comparable with the AUROCs of the well-established model
NAFLD-FS (Table 2). Furthermore, sCD163 was significantly associated with advanced fibrosis in both cohorts in multivariate logistic regression analysis with the NAFLD-FS as a covariate (Table 3), and adding sCD163 to the NAFLD-FS resulted in higher AUROCs for the prediction of advanced fibrosis (Table 2). The values of sensitivity and specificity for sCD163 and the NAFLD-FS were comparable. Of note, there were considerable variations in the two cohorts for both sCD163 and the NAFLD-FS (Supplementary Table 2 and 3).
sCD163 did not show good accuracy for the presence of NASH in any of the cohorts (best area under the ROC-curve (AUROC) 0.70); notably, CK-18 performed similarly (best AUROC 0.68) (Supplementary Table 4).
sCD163 and the apoptosis marker CK-18
There was a significant association between sCD163 and CK-18 in both the Australian (r=0.45, p<0.001, Figure 3A) and the Italian cohort (r=0.36 p<0.001, Figure 3B), which remained significant after adjustment for the histological NAFLD Activity Score and the fibrosis score (p=0.001 and p=0.02, respectively). CK-18 was associated with all of the histological measures of liver injury and fibrosis in the Australian cohort and with steatosis and fibrosis in the Italian cohort (Supplementary Table 5).
DISCUSSION
In the present study, we investigated the macrophage activation marker sCD163 in two independent NAFLD cohorts. The main findings of our study were the progressive increase in sCD163 levels in parallel with morphological NAFLD severity and the independent associations of sCD163 with liver fibrosis. In addition, we demonstrate an association between sCD163 and CK-18 levels, suggesting a link between apoptosis and macrophage activation.
Both macrophages in the liver and adipose tissue may contribute to the circulating sCD163 levels, and recent studies confirm associations of sCD163 with obesity, insulin resistance and the presence of diabetes[27-29]. However, the association between sCD163 and liver histology in the present study was independent of anthropometric, metabolic, and inflammatory measures, suggesting a direct relationship between macrophage activation, liver injury, and sCD163 levels. In the same line the association between changes in sCD163 and liver enzymes following lifestyle intervention and bariatric surgery was independent of BMI and metabolic measures[16, 17]. In addition, we showed higher systemic than portal sCD163 levels in NAFLD[17], suggesting hepatic secretion of sCD163 into the systemic circulation as also shown in patients with cirrhosis and portal hypertension[10]. Together, these human data support a key role for hepatic macrophages in NAFLD/NASH pathogenesis as proposed by experimental studies[3, 4, 30].
An important observation was that sCD163 in the Italian cohort was systematically lower than in the Australian cohort. The Italian patients were younger, less obese and had a lower percentage of diabetes, however presenting a similar degree of liver damage. The characteristics of these patients may suggest that at least some of them represent a previously described subgroup of NAFLD patients who are less obese and have a lower frequency of the metabolic syndrome but are not free from NASH and advanced fibrosis[31, 32]. It is at present unknown whether the pathogenesis of NAFLD in these patients differs from that of “traditional” NAFLD/NASH that is closely associated with obesity or whether it may include lower degree of macrophage activation. To our knowledge, no study has investigated macrophage involvement specifically in this subgroup of NAFLD patients. However, sCD163 showed comparable associations with liver histology and especially fibrosis in the two cohorts, suggesting a similar role of macrophages independent of the presence of obesity.
Overall , sCD163 levels in NAFLD patients were considerably lower than the levels observed in liver diseases with severe inflammation such as alcoholic hepatitis[8], acute liver failure[33] and acute-on-chronic liver failure[14], as well as the levels in decompensated liver cirrhosis[10, 11, 13]. Furthermore, in the present study sCD163 levels were within the reference interval in many cases, mainly in patients with low grades and stages of disease, whereas sCD163 increased in parallel with disease severity. In this regard, our present observations resemble the pattern of sCD163 in chronic viral hepatitis[9]. Of note, the median sCD163 levels in NAFLD patients with severe fibrosis in both the Italian and the Australian cohort were close to the levels in patients with chronic hepatitis B and C and severe fibrosis. Based on these clinical data, it may be proposed that the degree of macrophage activation is generally low in slowly progressing conditions such as NAFLD and chronic viral hepatitis, but is more pronounced in the setting of severe inflammation and fibrosis. The exact mechanism for the shedding of sCD163 in NAFLD/NASH and increased sCD163 levels is at present unknown. It is established that it can be mediated by tumor necrosis factor alpha-converting enzyme (TACE/ADAM17) as part of the inflammatory macrophage response[34], and this enzyme shows increased activity in mouse models of NAFLD[35]. Further, in NAFLD,
macrophages may be activated by different stimuli and events, including damaged hepatocytes and apoptotic bodies[36, 37]. Consistent with this we demonstrated an association of sCD163 with CK-18. Further, we observed a greater number of CD163-positive macrophages clustering into
microgranulomas in the stained biopsies from the NASH patients similar to earlier studies[38, 39], and also by the association of sCD163 with the degree of hepatocyte ballooning and macrophage clustering.
Recent data indicate that fibrosis stage is the histological feature best associated with the long-term outcome of NAFLD[40, 41]. We found that sCD163 performed well in predicting advanced
fibrosis, and sCD163 remained significantly associated with advanced fibrosis even with the established model NAFLD-FS as a covariate. Further, addition of sCD163 to the NAFLD-FS resulted in better AUROCs, which may support the potential of sCD163 as a biomarker of fibrosis in NAFLD. However, in a number of cases, sCD163 levels were within the reference interval, and there was a noteworthy difference in sCD163 levels as well as sensitivities and specificities between the two cohorts, which may limit this potential. However, it is important to note that sCD163 reflects a specific pathogenic process in NAFLD/NASH, i.e. macrophage activation, and combining sCD163 with other markers of liver fibrosis reflecting different pathophysiological aspects in a
panel may prove beneficial. This will need to be investigated in future preferably prospective studies. Despite its independent associations with NASH features such as steatosis and hepatocyte ballooning, sCD163 was not a predictor of steatohepatitis. A possible explanation may be that features of steatosis and necroinflammatory activity are dynamic over time, whereas liver fibrosis is a more stable histological phenomenon and a more robust measure of liver injury. Furthermore, the histological evaluation of necroinflammation measures shows higher variability than that of liver fibrosis[25], which was confirmed in a subset of the present study.
Our study has strengths and limitations. The main strength was the large number of well-classified patients referred specifically for evaluation of suspected NAFLD in two independent cohorts with completely different provenience and case mix. The most important limitation remains the cross-sectional design of the study, which could challenge the interpretation of associations as to cause and effect in terms of macrophage activation and the mechanisms involved.
In conclusion, we provide evidence for macrophage activation in human NAFLD/NASH, with independent associations between sCD163 and the morphological disease stages. The positive association between sCD163 and CK-18 suggests that apoptosis may contribute to macrophage activation in NAFLD. sCD163 was a good marker of advanced fibrosis, and may have potential as a biomarker for the non-invasive assessment of disease stage in NAFLD.
Acknowledgements.
Thanks to Kirsten Bank Petersen, Department of Clinical Biochemistry, Aarhus University Hospital, for excellent technical assistance, and to Dr. Ezio David, Department of Pathology, San Giovanni Battista Hospital, Torino, Italy for help with liver biopsy assessment.
References
[1] Tacke F, Zimmermann HW. Macrophage heterogeneity in liver injury and fibrosis. J Hepatol 2014;60:1090-1096.
[2] Baffy G. Kupffer cells in non-alcoholic fatty liver disease: the emerging view. J Hepatol 2009;51:212-223.
[3] Tomita K, Tamiya G, Ando S, Ohsumi K, Chiyo T, Mizutani A et al. Tumour necrosis factor alpha signalling through activation of Kupffer cells plays an essential role in liver fibrosis of non-alcoholic steatohepatitis in mice. Gut 2006;55:415-424.
[4] Tosello-Trampont AC, Landes SG, Nguyen V, Novobrantseva TI, Hahn YS. Kuppfer cells trigger nonalcoholic steatohepatitis development in diet-induced mouse model through tumor necrosis factor-alpha production. J Biol Chem 2012;287:40161-40172.
[5] Moller HJ, de FM, Aerts H, Hollak C, Moestrup SK. Plasma level of the
macrophage-derived soluble CD163 is increased and positively correlates with severity in Gaucher's disease. Eur J Haematol 2004;72:135-139.
[6] Moestrup SK, Moller HJ. CD163: a regulated hemoglobin scavenger receptor with a role in the anti-inflammatory response. Ann Med 2004;36:347-354.
[7] Weaver LK, Hintz-Goldstein KA, Pioli PA, Wardwell K, Qureshi N, Vogel SN et al. Pivotal advance: activation of cell surface Toll-like receptors causes shedding of the hemoglobin scavenger receptor CD163. J Leukoc Biol 2006;80:26-35.
[8] Sandahl TD, Gronbaek H, Moller HJ, Stoy S, Thomsen KL, Dige AK et al. Hepatic macrophage activation and the LPS pathway in patients with alcoholic hepatitis: a prospective cohort study. Am J Gastroenterol 2014;109:1749-1756.
[9] Kazankov K, Barrera F, Moller HJ, Bibby BM, Vilstrup H, George J et al. Soluble CD163, a macrophage activation marker, is independently associated with fibrosis in patients with chronic viral hepatitis B and C. Hepatology 2014;60:521-530.
[10] Holland-Fischer P, Gronbaek H, Sandahl TD, Moestrup SK, Riggio O, Ridola L et al. Kupffer cells are activated in cirrhotic portal hypertension and not normalised by TIPS. Gut 2011;60:1389-1393.
[11] Gronbaek H, Sandahl TD, Mortensen C, Vilstrup H, Moller HJ, Moller S. Soluble CD163, a marker of Kupffer cell activation, is related to portal hypertension in patients with liver cirrhosis. Aliment Pharmacol Ther 2012;36:173-180.
[12] Waidmann O, Brunner F, Herrmann E, Zeuzem S, Piiper A, Kronenberger B. Macrophage activation is a prognostic parameter for variceal bleeding and overall survival in patients with liver cirrhosis. J Hepatol 2013;58:956-961.
[13] Rode A, Nicoll A, Moller HJ, Lim L, Angus PW, Kronborg I et al. Hepatic
macrophage activation predicts clinical decompensation in chronic liver disease. Gut 2013;62:1231-1232.
[14] Gronbaek H, Rodgaard-Hansen S, Aagaard NK, Arroyo V, Moestrup SK, Garcia E et al. The soluble macrophage activation markers sCD163 and Mannose Receptor (sMR) predict mortality in patients with liver cirrhosis without or with acute-on-chronic liver failure (ACLF). J Hepatol 2015.
[15] De VR, Alisi A, Masotti A, Ceccarelli S, Panera N, Citti A et al. Markers of activated inflammatory cells correlate with severity of liver damage in children with nonalcoholic fatty liver disease. Int J Mol Med 2012;30:49-56.
[16] Kazankov K, Moller HJ, Lange A, Birkebaek NH, Holland-Fischer P, Solvig J et al. The macrophage activation marker sCD163 is associated with changes in NAFLD and metabolic profile during lifestyle intervention in obese children. Pediatr Obes 2015;10:226-233.
[17] Kazankov K, Tordjman J, Moller HJ, Vilstrup H, Poitou C, Bedossa P et al. The macrophage activation marker sCD163 is independently associated with NAFLD severity in morbid obesity and reduced by bariatric surgery. J Gastroenterol Hepatol 2015.
[18] Mueller JL, Feeney ER, Zheng H, Misdraji J, Kruger AJ, Alatrakchi N et al. Circulating Soluble CD163 is Associated with Steatohepatitis and Advanced Fibrosis in Nonalcoholic Fatty Liver Disease. Clin Transl Gastroenterol 2015;6:e114.
[19] Fjeldborg K, Pedersen SB, Moller HJ, Rask P, Danielsen AV, Stodkilde-Jorgensen H et al. Intrahepatic fat content correlates with soluble CD163 in relation to weight loss induced by Roux-en-Y gastric bypass. Obesity (Silver Spring) 2015;23:154-161.
[20] Kwok R, Tse YK, Wong GL, Ha Y, Lee AU, Ngu MC et al. Systematic review with meta-analysis: non-invasive assessment of non-alcoholic fatty liver disease - the role of transient elastography and plasma cytokeratin-18 fragments. Aliment Pharmacol Ther 2013.
[21] Turner RC, Holman RR, Matthews D, Hockaday TD, Peto J. Insulin deficiency and insulin resistance interaction in diabetes: estimation of their relative contribution by feedback analysis from basal plasma insulin and glucose concentrations. Metabolism 1979;28:1086-1096.
[22] Angulo P, Hui JM, Marchesini G, Bugianesi E, George J, Farrell GC et al. The NAFLD fibrosis score: a noninvasive system that identifies liver fibrosis in patients with NAFLD. Hepatology 2007;45:846-854.
[23] Moller HJ, Hald K, Moestrup SK. Characterization of an enzyme-linked immunosorbent assay for soluble CD163. Scand J Clin Lab Invest 2002;62:293-299.
[24] Moller HJ. Soluble CD163. Scand J Clin Lab Invest 2012;72:1-13.
[25] Kleiner DE, Brunt EM, Van NM, Behling C, Contos MJ, Cummings OW et al. Design and validation of a histological scoring system for nonalcoholic fatty liver disease. Hepatology 2005;41:1313-1321.
[26] Bedossa P. Utility and appropriateness of the fatty liver inhibition of progression (FLIP) algorithm and steatosis, activity, and fibrosis (SAF) score in the evaluation of biopsies of nonalcoholic fatty liver disease. Hepatology 2014;60:565-575.
[27] Moller HJ, Frikke-Schmidt R, Moestrup SK, Nordestgaard BG, Tybjaerg-Hansen A. Serum soluble CD163 predicts risk of type 2 diabetes in the general population. Clin Chem
2011;57:291-297.
[28] Parkner T, Sorensen LP, Nielsen AR, Fischer CP, Bibby BM, Nielsen S et al. Soluble CD163: a biomarker linking macrophages and insulin resistance. Diabetologia 2012;55:1856-1862.
[29] Fjeldborg K, Christiansen T, Bennetzen M, Moller J, Pedersen SB, Richelsen B. The macrophage-specific serum marker, soluble CD163, is increased in obesity and reduced after dietary-induced weight loss. Obesity (Silver Spring) 2013;21:2437-2443.
[30] Stienstra R, Saudale F, Duval C, Keshtkar S, Groener JE, van RN et al. Kupffer cells promote hepatic steatosis via interleukin-1beta-dependent suppression of peroxisome proliferator-activated receptor alpha activity. Hepatology 2010;51:511-522.
[31] Bugianesi E, Gastaldelli A, Vanni E, Gambino R, Cassader M, Baldi S et al. Insulin resistance in non-diabetic patients with non-alcoholic fatty liver disease: sites and mechanisms. Diabetologia 2005;48:634-642.
[32] Younossi ZM, Stepanova M, Negro F, Hallaji S, Younossi Y, Lam B et al. Nonalcoholic fatty liver disease in lean individuals in the United States. Medicine (Baltimore) 2012;91:319-327.
[33] Moller HJ, Gronbaek H, Schiodt FV, Holland-Fischer P, Schilsky M, Munoz S et al. Soluble CD163 from activated macrophages predicts mortality in acute liver failure. J Hepatol 2007;47:671-676.
[34] Etzerodt A, Rasmussen MR, Svendsen P, Chalaris A, Schwarz J, Galea I et al. Structural Basis for inflammation-Driven Shedding of CD163 and Tumor Necrosis Factor-alpha in Macrophages. J Biol Chem 2013.
[35] Fiorentino L, Vivanti A, Cavalera M, Marzano V, Ronci M, Fabrizi M et al. Increased tumor necrosis factor alpha-converting enzyme activity induces insulin resistance and hepatosteatosis in mice. Hepatology 2010;51:103-110.
[36] Canbay A, Feldstein AE, Higuchi H, Werneburg N, Grambihler A, Bronk SF et al. Kupffer cell engulfment of apoptotic bodies stimulates death ligand and cytokine expression. Hepatology 2003;38:1188-1198.
[37] Hirsova P, Gores GJ. Death Receptor-Mediated Cell Death and Proinflammatory Signaling in Nonalcoholic Steatohepatitis. Cell Mol Gastroenterol Hepatol 2015;1:17-27.
[38] Itoh M, Kato H, Suganami T, Konuma K, Marumoto Y, Terai S et al. Hepatic crown-like structure: a unique histological feature in non-alcoholic steatohepatitis in mice and humans. PLoS One 2013;8:e82163.
[39] Caballero T, Gila A, Sanchez-Salgado G, Munoz de RP, Leon J, Delgado S et al. Histological and immunohistochemical assessment of liver biopsies in morbidly obese patients. Histol Histopathol 2012;27:459-466.
[40] Ekstedt M, Hagstrom H, Nasr P, Fredrikson M, Stal P, Kechagias S et al. Fibrosis stage is the strongest predictor for disease-specific mortality in NAFLD after up to 33 years of follow-up. Hepatology 2015;61:1547-1554.
[41] Angulo P, Kleiner DE, Dam-Larsen S, Adams LA, Bjornsson ES,
Charatcharoenwitthaya P et al. Liver Fibrosis, but No Other Histologic Features, Is Associated With Long-term Outcomes of Patients With Nonalcoholic Fatty Liver Disease. Gastroenterology
2015;149:389-397.
Table 1. Patient characteristics. Australian cohort (n = 157) Italian cohort (n = 174) P Age (years) 48 ± 13 43 ± 11 <0.001 Sex (m : f) 89 (57%) : 68 (43%) 130 (75%) : 44 (25%) 0.001 BMI (kg/m2) 30.7 ± 5.1 27.9 ± 3.9 <0.001
NASH according to FLIP algorithm (n(%))
Missing score 46 (39%)39 86 (49%)0 0.08 Fibrosis stage (n(%)) 0 1 2 3 4
Missing Kleiner Fibrosis Score
51 (34%) 55 (36%) 20 (13%) 13 (9%) 12 (8%) 6 63 (36%) 38 (22%) 32 (19%) 30 (17%) 11 (6%) 0 0.015 sCD163 (mg/L) 2.6 (2.0–3.6) 1.6 (1.1–2.3) <0.001 CK-18 (U/L) 186 (85–387) 208 (123–331) 0.14 Diabetes (n(%)) 40 (25%) 26 (15%) 0.02 HOMA-IR 3.9 (2.7–6.2) 3.0 (2.0–5.1) 0.002 ALT (IU/L) 65 (47–96) 70 (43–95) 0.86 AST (IU/L) 46 (33–62) 36 (28–48) <0.001 Albumin (g/L) 45 ± 3 46 ± 4 0.03 Platelets (109/L) 258 ± 73 230 ± 70 <0.001 Triglycerides (mmol/L) 1.8 (1.2–2.6) 1.4 (1.0–2.1) <0.001 Hypertension (n(%)) 53 (34%) 59 (34%) 0.98 Hyperlipidaemia (n(%)) 130 (83%) 94 (54%) 0.014 Waist-hip ratio 0.97 ± 0.08
-Parameters are presented as means ± SD for normally distributed and medians (interquartile range) for non-normally distributed variables, and as total number (%) for categorical variables.
BMI, Body Mass Index; NASH, non-alcoholic steatohepatitis; FLIP, Fatty Liver Inhibition of Progression; sCD163, soluble CD163; CK-18, cytokeratin-18; HOMA-IR, homeostatic model assessment of insulin resistance; ALT, alanine transaminase; AST, aspartate transaminase
Table 2. Prediction of advanced fibrosis (F≥3) by sCD163 and the NAFLD Fibrosis Score.
Australian cohort Italian cohort sCD163 (mg/L) 0.77 (95% CI: 0.76–0.87) 0.80 (95% CI: 0.72–0.88) NAFLD-FS 0.80 (95% CI: 0.70–0.91) 0.73 (95% CI: 0.63–0.83) NAFLD-FS + sCD163 0.83 (95% CI: 0.73–0.93) 0.83 (95% CI: 0.75–0.91)
Data shown as areas under the Receiver Operating Characteristics curve with 95% Confidence Intervals. sCD163, soluble CD163; NAFLD-FS, NAFLD fibrosis score
Table 3. Multiple logistic regression analysis in the Australian and the Italian cohorts with advanced fibrosis (F≥3) as the dependent variable.
OR (95% Confidence Interval) P Australian cohort sCD163 (mg/L) 1.36 (1.04–1.79) 0.026 NAFLD-FS 2.0 (1.40–2.86) <0.001 Italian cohort sCD163 (mg/L) 2.02 (1.31–3.13) 0.002 NAFLD-FS 1.42 (1.02–1.96) 0.037
OR, odds ratio; sCD163, soluble CD163; NAFLD-FS, NAFLD fibrosis score
Figure 1. Soluble CD163 according to the histological scores in the Australian and the Italian cohorts.
(A) sCD163 and the Kleiner Fibrosis score. (B) sCD163 and Steatosis score.
(C) sCD163 and Hepatocyte ballooning score. (D) sCD163 and Lobular inflammation score.
Boxes represent interquartile ranges (IQR) with medians; whiskers show adjacent values. Punctured lines represent the reference interval (0.69–3.86 mg/L).
Figure 2. Representative images of liver biopsies with immunohistochemical staining for CD163. (A) A patient without non-alcoholic steatohepatitis (NASH).
(B) A patient with NASH.
The stained macrophages are seen in the liver sinusoids; arrows mark CD163-positive macrophage clusters.
Magnitude x4, scale bar 500 µm; magnitude x20, scale bar 100 µm.
Figure 3. Relationship between soluble CD163 and cytokeratin-18 in the Australian and the Italian cohort.
(A) Australian cohort (B) Italian cohort
