Macrophage activation markers predict mortality in patients with liver cirrhosis without or with acute-on-chronic liver failure (ACLF)

Accepted Manuscript The soluble macrophage activation markers sCD163 and Mannose Receptor (sMR) predict mortality in patients with liver cirrhosis without or with acuteon-chronic liver failure (ACLF) Henning Grønbæk, Sidsel Rødgaard-Hansen, Niels Kristian Aagaard, Vicente Arroyo, Søren K. Moestrup, Elisabet Garcia, Elsa Solà, Marco Domenicali, Salvatore Piano, Hendrik Vilstrup, Holger Jon Møller, On behalf of the CANONIC study investigators of the EASL-CLIF Consortium., PII: DOI: Reference:

S0168-8278(15)00779-5 http://dx.doi.org/10.1016/j.jhep.2015.11.021 JHEPAT 5904

To appear in:

Journal of Hepatology

Received Date: Revised Date: Accepted Date:

22 June 2015 21 October 2015 17 November 2015

Please cite this article as: Grønbæk, H., Rødgaard-Hansen, S., Aagaard, N.K., Arroyo, V., Moestrup, S.K., Garcia, E., Solà, E., Domenicali, M., Piano, S., Vilstrup, H., Møller, H.J., On behalf of the CANONIC study investigators of the EASL-CLIF Consortium., 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), Journal of Hepatology (2015), doi: http://dx.doi.org/10.1016/j.jhep.2015.11.021

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The soluble macrophage activation markers sCD163 and Mannose Receptor (sMR) predict mortality in patients with liver cirrhosis without or with acuteon-chronic liver failure (ACLF) Henning Grønbæk1, Sidsel Rødgaard-Hansen2, Niels Kristian Aagaard 1, Vicente Arroyo3, Søren K. Moestrup4, Elisabet Garcia3, Elsa Solà5, Marco Domenicali6, Salvatore Piano 7, Hendrik Vilstrup1, Holger Jon Møller2, on behalf of the CANONIC study investigators of the EASL-CLIF Consortium. 1) Department of Hepatology & Gastroenterology, Aarhus University Hospital, Aarhus, Denmark 2) Department of Clinical Biochemistry, Aarhus University Hospital, Aarhus, Denmark 3) The EASL-CLIF Consortium, Barcelona, Spain 4) Department of Biomedicine, Aarhus University, Aarhus & Institute of Molecular Medicine, University of Southern Denmark, Odense, Denmark 5) Liver Unit, Hospital Clinic de Barcelona, Unviersity of Barcelona, IDIBAPS, CIBEReHD, Barcelona, Spain. 6) Department of Medical and Surgical Sciences, University of Bologna, Italy. 7) Unit of Hepatic Emergencies and Liver Transplantation, Department of Medicine-DIMED, University of Padova, Padova, Italy. Email: [email protected] Correspondance to: Professor Henning Grønbæk, MD, PhD Department of Hepatology & Gastroenterology Aarhus University hospital, Nørrebrogade 44 DK-8000 Aarhus C Denmark Phone: +4521679281 E-mail: [email protected] Running title: Macrophage biomarkers sCD163 and sMR in ACLF patients Authors’ Contribution HG, HV, VA, HJM: study design, data evaluation, manuscript writing and final manuscript review; EG: statistical analysis, manuscript writing and final manuscript review; SRH, HJM, SKM: Biochemical measurements, manuscript writing, and final manuscript review; HG, NKA, MD, SP: Patient recruitment, data collection and final manuscript review.

Disclosures/conflicts of interest: The authors have nothing to disclose 6,385 words, including the abstract, references, tables, and figure legends.

Abstract: Introduction: Activation of liver macrophages plays a key role in liver and systemic inflammation and may be involved in development and prognosis of acute-on-chronic liver failure (ACLF). We therefore measured the circulating macrophage activation markers soluble sCD163 and mannosereceptor (sMR) and related them to the short-(1-3 months) and long-term (6 months) mortality in the cirrhosis patients of the CANONIC study. Methods: Eighty-six cirrhosis patients had no ascites and no ACLF, 580 had ascites but no ACLF; 100, 66, and 19 had ACLF-grade-I (ACLF-I), ACLF-II, and ACLF-III, respectively. The patients’ clinical course was registered and their MELD, CLIF-C Acute Decompensation (AD), and CLIF-C ACLF-scores computed at inclusion. Results: We found a stepwise increase (p<0.001) in median sCD163 (5.68(IQR:3.86-9.60); 8.26(5.02-12.34); 9.50(5.37-17.91); 15.68(10.12-19.42); 20.18(15.26-32.20) mg/L) and sMR (0.60(0.40-0.84); 0.81(0.57-1.12); 0.81(0.61-1.26); 1.17(0.89-1.62); 1.41(1.14-1.79) mg/L) with increasing grades of ACLF. Both sCD163 and sMR were independently associated with short and long-term mortality and showed equal or higher predictive accuracy than MELD, CLIF-C ACLF and CLIF-C AD-scores. Addition of the macrophage markers to the clinical scores improved the prognostic efficacy: In ACLF patients sCD163 improved prediction of short-term mortality (Cindex:0.74(0.67-0.80)) and in patients without ACLF sMR improved prediction of long-term mortality [C-index:0.80(0.76-0.85]. Conclusions: The severity related increase in sCD163 and sMR and close association with mortality suggest a primary importance of inflammatory activation of liver macrophages in the emergence and course of ACLF. Accordingly, supplementation of the macrophage biomarkers to the platform of the clinical scores improved the prognostic performance beyond that of the original scores. Key words: Acute-on-chronic liver failure, cirrhosis, macrophages, CD163, mannose receptor, cirrhosis complications, biomarker, prognosis.

Introduction: Acute-on-chronic liver failure (ACLF) is a newly identified syndrome in patients with liver cirrhosis, characterized by acute hepatic decompensation, an association to extrahepatic organ failure, and high short- (20-30% at 28 days) and long-term mortality rates (50-70%) at 6 months. Data from the CANONIC Study conducted by the EASL Chronic Liver Failure Consortium (CLIFC) provided the basis for the development of the CLIF-C Organ Failure (CLIF-C OF) score [1] with validation and further refinement by inclusion of two other independent predictors of mortality (age and white blood cell count) to develop a specific prognostic score for patients with ACLF, the CLIF-C ACLF score [2]. Just recently Jalan et al. described the CLIF-C Acute Decompensation (CLIF-C AD) score that showed predictability for acute decompensation and mortality in patients without ACLF from the CANONIC study [3]. These prognostic scores are pragmatically based on generally available standard clinical and biochemical data; however, biomarkers for suspected ACLF mechanisms may throw light on the pathogenesis of the condition, improve the predictive ability of the pragmatic scores, and suggest strategies for future rational treatments of ACLF. The resident liver macrophages (viz. the Kupffer cells) that constitute >80% of the body macrophage population are shown to play a pivotal role in liver inflammation and fibrosis in e.g. viral hepatitis and non-alcoholic steatohepatitis [4, 5] and are also important in the development and maintenance of portal hypertension [6]. The liver macrophages may thus be involved in the emergence and progression of the clinical complications to cirrhosis including ACLF [7-9]. Macrophages can be activated by various stimuli; however, in cirrhosis the most important pathway seems to be the pathogen-associated molecular patterns (PAMPs), e.g. endotoxins (LPS) from the intestines. Portal hypertension and a disrupted gut-blood barrier promote gut-to-blood translocation of gut bacteria and PAMPs that reach the liver and activate the toll-like receptors of the resident macrophages [10-12]. This pathway has been identified in e.g. alcoholic hepatitis [13, 14]. Furthermore “sterile” macrophage activation can be locally initiated by damage-associated

molecular patterns (DAMPs) from adjacent injured hepatocytes. Both signalling events likely lead to hepatic as well as systemic inflammation through the secretion of a number of cytokines [1, 15]. We have in several studies shown sCD163 to be a clinically relevant biomarker of Kupffer cell activation in liver disease and recently also introduced the soluble mannose receptor, sMR, as a novel biomarker of macrophage activation. We identified CD163 as the haemoglobin-haptoglobin scavenger receptor exclusively located on macrophages and to some extent monocytes [16] and after shedding released to the circulation as soluble (s)CD163 [17]. sCD163 shows clear associations to liver disease severity (fibrosis, cirrhosis, Child-Pugh and MELD scores) and to portal hypertension [18-21]. Furthermore, sCD163 levels are associated with prognosis in patients with cirrhosis of various aetiologies [20, 22, 23] and in severe alcoholic hepatitis [24]. We recently identified and characterized sMR in human serum (25). The soluble form seems to be a shedding product of the mannose-receptor primarily found on macrophages and dendritic cells. So far sMR has only been studied sparsely, but we have found significantly elevated levels in patients with liver disease and in patients with infections [25-27]. Thus the available knowledge suggests an important role of macrophages in liver diseases that may include also a role in the development and course of ACLF; however, this has not previously been studied. The CANONIC study, comprising a biobank of more than 850 cirrhosis patients, provides clinical, biochemical, and prognostic data that make it possible to derive solid data on the role of macrophages in ACLF by measurements of sCD163 and sMR We hypothesized that 1) sCD163 and sMR would be associated with liver disease severity (MELD and Child-Pugh scores as well as with the CANONIC study derived grading of ACLF); 2) the biomarkers would be associated with increased mortality; and 3) that addition of sCD163 and sMR to the CANONIC study derived prognostic scores would improve the prognostic prediction. Our results being in accordance with these expectations support the importance of liver resident macrophages for the prognosis of cirrhosis, and for the development and course of ACLF.

Patients and Methods Study Design Patients were included from February to September 2011 in 12 European countries after the appropriate approvals were obtained as previously described [1]. In brief, patients were screened at liver units in 29 university hospitals with a diagnosis of cirrhosis based on previous liver biopsy findings or a composite of clinical signs and findings provided by laboratory test results, endoscopy, and radiologic imaging. Written informed consent was obtained from patients or their legal surrogates before enrollment. The members of the writing committee assume responsibility for the accuracy and completeness of the data and for the fidelity of the study to the protocol. All authors had access to the study data and reviewed and approved the final manuscript. Grifols or Gambro did not play a role in the study design as well as analyses of the data.

Patients: Hospitalized patients were screened for at least 1 day in the presence of AD of cirrhosis as defined by the acute development of large ascites, hepatic encephalopathy, gastrointestinal hemorrhage, bacterial infection, or any combination of these. We enrolled patients who developed AD for the first time as well as those with a prior history of AD (one or more episodes) who recovered after specific treatment. We collected data from all enrolled patients on history (including previous episodes of AD), physical examination, laboratory measurements, and events that may be potential precipitating factors of both AD and ACLF: active alcoholism (more than 14 drinks per week in women and more than 21 drinks per week in men within the previous 3 months), bacterial infection, gastrointestinal hemorrhage, therapeutic paracenteses without use of intravenous albumin, transjugular intrahepatic portosystemic shunting, major surgery, hepatitis, and alcoholic hepatitis (liver biopsy required). As pre-specified in the study protocol, enrolled patients at each study site were divided into 3 groups: patients with organ failure (group I), patients without organ failure, who

were chronologically enrolled after each patient with organ failure (group II), and other enrolled patients without organ failure (group III). For logistical reasons, patients in groups I and II but not those in group III were subjected to an “intensive surveillance,” which consisted of collection of an extensive set of data at day1, day 2, days 3-7, days 8-14, days 15-21, days 22-28 after enrollment that was similar to the data obtained at enrollment. Patients in group III had regular follow-up to allow detection of organ failure. When patients in group III developed organ failure, the intensive surveillance program was applied during the 28 days after detection of organ failure. Blood, serum, plasma, and urine samples were obtained from all patients at enrollment. Samples were also obtained during the 28-day follow-up from patients in groups I and II and from those in group III who developed organ failure. Finally, as pre-specified in the study protocol, information on liver transplantation and mortality at 28, 90 and 180 days following enrollment was recorded. From the established biobank we used baseline blood samples taken from the patients median 1 day (IQR: 0-2) after admission. Of the original 1343 patients included in the CANONIC study we had access to data from 863 patients, from which 853 samples were available for sCD163 and sMR measurements. Of these, 295 patients (137 ACLF patients and 158 patients without ACLF) had follow-up blood samples drawn by day 3-7 and available for investigation of dynamic changes of sCD163 and sMR.

sCD163 and sMR assays We have previously established a reference interval (0.69–3.86 mg/L) for sCD163 in a large cohort of healthy individuals with the same assay [28]. The plasma concentration of sCD163 was determined in duplicate in samples that had been frozen at -80 °C by an in-house sandwich enzymelinked immunosorbent assay using a BEP-2000 ELISA-analyser (Dade Behring) as previously described [29]. Duplicate samples with CV>15% were rerun (n=18). Control samples and serum standards with concentrations that ranged from 6.25 to 200 µg/l were included in each run. The inter-assay coefficient of variation was 6.3% at a level of 1.91 mg/l and 5.4% at a level of 3.68

mg/l. The limit of detection (lowest standard) was 6.25 µg/L. Soluble CD163 is resistant to repeated freezing and thawing [29]. We measured sMR by a newly developed in-house ELISA assay as previously described [25]. In brief we used a polyclonal anti-human MR antibody (R&D Systems, catalogue number AF2534) as catching antibody and an in-house biotinylated monoclonal anti-MR antibody (Acris Antibodies, Clone 7-450, catalogue number AM05589PU-S) as detection antibody. Total variation was determined by two control samples included twice in each run and was 10.6% and 11.2%, respectively. The 95% reference interval was 0.10–0.43 mg/L based on measurements of serum samples from healthy individuals (n = 217). sMR is stable for more than 2 days at room temperature, for 2 weeks at 4 o C, and for at least 3 years at -20o C and -800C. The concentration of sMR was resistant to repeated rounds of freezing and thawing [25].

Statistical analyses Data for sCD163 and sMR markers were directly transcribed to a data sheet. The rest of the data were collected using an electronic case report form. Both parts were merged using the statistical analysis software. Quantitative variables are reported as mean and SD if normally distributed, or median and interquartile range if not. Categorical variables are reported as count and percentage in each category and total. Correlations of the markers with other variables are evaluated by means of the Spearman coefficient. Comparisons of markers between groups of clinical characteristics are assessed with the U-Mann Whitney test. We used ANOVA test for normally distributed data and the Kruskal-Wallis test if not normally distributed to compare quantitative variables across the groups of the study. Categorical variables were compared across the groups by the Chi-square test. If the number of available data for one of the groups was very small, no statistical comparisons were carried out.

The association of White Blood Cell Count, sCD163 and sMR in the whole subset of patients, ACLF patients or No-ACLF patients respectively with short and long term mortalities was identified by applying U-Mann Whitney test due to their non-normal distributions. Same associations were sought for MELD, CLIF-C ACLF and CLIF-C AD scores with T-test’s since they were normally distributed. Cox survival models for predicting short and long term mortalities with White Blood Cell Count, sCD163 and sMR, with the factors separately added to each of the scores and with each of the scores were fitted. Model estimations were performed in the presence of a competing risk event since transplantation can be considered an event 'competing' with death [30]. In all models, nonnormal distributed variables were log-transformed. The accuracy of each model was assessed by means of the C-index and its 95% confidence interval. Predictive accuracy was compared between models by means of a normal approximation with the Z-test. The significance level for all tests was set at 5%. Boxplots with the whiskers drawn from the quartiles to the extreme values for selected variables are shown.

Results: Basic clinical and biochemical data From the original CANONIC trial [1] with 1343 hospitalized patients with cirrhosis of whom 303 had ACLF at inclusion and 112 developed ACLF, we had access to data and blood samples for measurement of sCD163 and sMR in 853 patients. There were no stored blood samples available from the remaining group. Further, two of the patients could not be stratified due to missing data regarding ascites and ACLF status. Thus we stratified 851 patients into different groups according to their disease severity based on their ACLF classes [2] as shown in Table 1. Further, patients without ACLF were stratified by either the absence of ascites (at inclusion or previously) or the presence of ascites or subrogates (treatment with diuretics and/or an episode of SBP within 3

months prior to enrolment or within hospital admission after enrollments). The group without ascites had normal renin levels while the group with ascites/subrogates had significantly elevated renin levels (data not shown) suggesting clinically different patient groups. Thus 68 patients had no ascites and no ACLF, 580 had ascites/subrogates but no ACLF and 100, 66 and 19 had ACLF-grade I (ACLF-1), ACLF-II, and ACLF-III, respectively [2]. There was similar gender distribution between groups with generally more males than female patients, and almost similar age distribution although the patients in the ACLF-III group were the youngest (Table 1). The cirrhosis aetiology was similar among the groups with approximately 50% having alcohol cirrhosis, followed by HCV (21%), alcohol and HCV (11%) and 18% other. Previous decompensation episodes were more frequent in the groups presenting with ACLF-I-III compared to the patients without ACLF. At time of inclusion ACLF patients more frequently presented with ascites, hepatic encephalopathy, and bacterial infections while GI bleeding was more frequent in the group without ACLF and without ascites (Table I). We observed the expected differences regarding standard biochemical liver, kidney, and haematology related data.

Liver disease severity scores and mortality As expected or defined we observed an increasing frequency of organ failures in the groups with increasing disease severity assessed by the MELD, MELD-Na, Child-Pugh, CLIF-SOFA, and CLIF-C-OF scores (Table 2). Likewise, the 28-, 90-, and 180-days mortality rates rose with disease severity, ranging from 1-7% in the group without ACLF and without ascites while mortality rates in ACLF-I, ACLF-II and ACLF-III at day 28-day were 17%, 27%, 74% ; by day 90 31%, 45%, 74%; and by day 180 46%, 55%, 79%, respectively.

Blood leukocytes, sCD163 and sMR in the clinical study groups Median white blood cell counts (Fig 1A) were within the normal range in the groups of cirrhotic

patients without and with ascites, and in the ACLF-I group, and increased in the ACLF-II and -III groups. The median sCD163 (Fig 1B) and sMR (Fig 1C) levels in the whole study population were substantially higher than the reference level in healthy individuals (sCD163: 0.69–3.86 mg/L and sMR: 0.10–0.43 mg/L). We found a stepwise increase (p<0.001) in median (interquartile range, IQR) for sCD163 (5.68(IQR:3.86-9.60);

8.26(5.02-12.34); 9.50(5.37-17.91), 15.68(10.12-

19.42); 20.18(15.26-32.20) mg/L) and sMR (0.60(0.40-0.84); 0.81(0.57-1.12); 0.81(0.611.26); 1.17(0.89-1.62); 1.41(1.14-1.79) mg/L) with increasing disease severity. As expected, we observed an association between sCD163 and sMR for all patients (rho=0.68, P<0.0001) and in the patients with or without ACLF (rho=0.75, P<0.0001, rho=0.64, P<0.0001, respectively). Further, both sCD163 and sMR correlated with various strengths with all of the clinical scores (Table 3) and with a weak association with the white cell count.

Inflammatory markers sCD163, sMR, white blood cells, MELD score, and the CLIF-C-AD and CLIF-C ACLF score as predictors for 28, 90 and 180 days mortality. As previously shown the white blood cell count and the MELD, CLIF-C AD and CLIF-C ACLF scores were associated with early (28 and 90 days) and long-term (180 days) mortality in both cirrhotic patients with and without ACLF (Table 4). In patients with ACLF both sCD163 and sMR were associated with 28 and 90 days mortality with as good prognosis prediction as that of the MELD and CLIF-C ACLF scores. The supplementation of sCD163 to the CLIF-C ACLF score improved the prediction of 90 days mortality compared to the original score. In the patients without ACLF both sCD163 and sMR predicted the 90 and 180 days mortality as well as did the scores derived from the original complete dataset. sMR was a better predictor than the MELD score for 90 and 180 days mortality. Furthermore, the supplementation with sMR to the CLIF-C AD score significantly improved the prediction of both the 90 and 180 days mortality better

than the original score. The Youden index was used to maximize the potential effectiveness of the biomarkers. We used a cutoff for sCD163 of 13.32 mg/L with a sensitivity of 66.3% and a specificity of 78.4% to predict 28-day mortality and for sMR we used a cutoff of 1.05 with a sensitivity of 68.8 and specificity 72.3%.

Levels of sCD163 and sMR in patients with and without ACLF in relation to organ failure. In table 5 the sCD163 and sMR levels are shown for type of organ failure in patients with or without ACLF. In the patients with ACLF both the sCD163 and sMR levels were higher in the patients with liver, coagulation system, or cardiovascular failure than in those without any of these while the opposite was observed for renal failure. Further, sMR was higher in the patients with cerebral involvement while sCD163 was not so. In the patients without ACLF the sCD163 and sMR levels were higher among those with one organ failure (not renal) compared to no failure.

Changes of sCD163 and sMR during admission and relation to mortality The sCD163 and sMR levels at baseline and day 3-7 were significantly higher in patients that died compared to patients being alive by day 28, 90 and 180, respectively, for both patients with and without ACLF (Table 6). ACLF patients that died by day 28, 90 and 180 increased their sCD163 levels from baseline to day 3-7, while survivors had unchanged or slightly decreased sCD163 levels and the change in sCD163 from baseline to day 3-7 was significant between ACLF patients that died compared to survivors. We observed similar changes for sMR. In patients without ACLF both sCD163 and sMR levels were in general stable from baseline to day 3-7.

sCD163 and sMR at inclusion related to precipitating events. In supplemental Table 1 we present data on sCD163 and sMR levels in relation to the registered

precipitating events for the ACLF. There was no difference in sCD163 and sMR levels regarding previous decompensation or hospitalizations, however, sMR (but not sCD163) was higher in patients with any precipitating event in the inclusion period. Both sCD163 and sMR were higher in the patients with bacterial infection including sepsis as precipitating event. Conversely, the patients with gastrointestinal bleeding, surgery or TIPS as precipitating events had lower sCD163 and sMR levels, however, the numbers are small for the latter two. There was no difference in sCD163 or sMR regarding the cirrhosis aetiology. The few patients with acute viral hepatitis or biopsy verified alcoholic hepatitis had very high sCD163 and sMR; in contrast, other aetiologies had lower levels of both markers.

sCD163 and sMR levels in relation to bacterial infections and sepsis The patients with bacterial infections (n=197) in the peri-inclusion period i.e. from admission to inclusion had slightly higher sCD163 levels (9.89 mg/L (IQR: 6.71-16.49)) compared to patients without bacterial infections (n=656) (sCD163 8.41 (IQR: 4.89-12.68), P<0.0001). Similarly, we observed slightly higher sMR levels in these patients (0.95 mg/L (IQR: 0.69-1.42 mg/L) vs. 0.79 (0.55-1.12), P<0.0001). Further, we retrieved the data for bacterial infections emerging from inclusion to day 22. Again, the patients with bacterial infections in this period (n=324) had higher baseline sCD163 levels (10.89 mg/L (IQR: 6.75-17.17) compared to patients without infections (n= 529, 7.46 mg/L (IQR: 4.52-11.38), P<0.001); and with similar findings for sMR in patients with bacterial infections (0.98 mg/L (IQR: 0.73-1.44)) compared to no bacterial infections (0.73 mg/L (IQR: 0.53-1.02)), P<0.0001. Patients with sepsis had higher sCD163 (12.39 (7.93-19.72) vs. 9.20 (6.27-15.32) mg/L, P=0.01) and sMR levels (1.28 (0.85-1.67) vs. 0.87 (0.66-1.24) mg/L, P=0.0047) than patients without sepsis. Further, the levels increased with sepsis severity with the highest levels in septic shock patients

compared to sepsis only for sCD163 (32.20 (14.12-34.38) vs. 10.13 (6.70-14.23) mg/L, P= 0.0048) and for sMR 1.79 (1.29-2.21) vs. 0.92 (0.72-1.49) mg/L, P=0.0036).

Discussion: In the present study we investigated the soluble macrophage activation markers sCD163 and sMR in large groups of patients with liver cirrhosis and with ACLF. Novel and important findings were the graded increase in sCD163 and sMR levels with ACLF disease severity and that both markers predicted short- and long-term mortality. This indicates the importance of liver resident macrophages in the development and course of cirrhosis and ACLF. Accordingly, the inclusion of the macrophage biomarkers to the CLIF-C ACLF and CLIF-C AD scores improves the prognosis predictive performance beyond that of the original scores. The major strength of the present study is the large number of well-characterized patients from the CANONIC study recruited among specialised liver centres throughout Europe and with the originated scores [1-3]. The CANONIC study included a total of 1343 patients, however only 853 of these patients had blood samples stored in a biobank and available for the analysis of sCD163 and sMR. The CLIF-C-ACLF and CLIF-C-AD scores in the present study cohort had similar prediction as the originally derived scores; e.g. for CLIF-C ACLF 28 and 90 days mortality, respectively, C-index were 0.75(0.68-0.83) and 0.71(0.64-0.77) in the present study compared to 0.75(0.70-0.80) and 0.71 (0.67-0.76) in the original publication [2]. Similar for 90 and 180 days mortality the original CLIF-C AD score C-index were 0.74(0.70-0.78) and 0.71(0.68-0.75, respectively [3], compared to 0.74 (0.68-0.79) and 0.72 (0.68-0.77) in the present study. This indicates that no major selection bias exists between the original CANONIC cohort and the present cohort. The understanding of the pathogenic development and progression of liver cirrhosis and especially ACLF has advanced during recent years with an increased focus on inflammation as a pathogenic key player. In cirrhosis patients there is evidence for systemic inflammation by elevated circulating

levels of general inflammatory markers like WBC and CRP, but also elevated levels of TNF, Il-6, Il-18 [7, 31, 32]. These cytokines may derive from areas of local inflammation e.g. pneumonia, urinary tract infections etc. The liver, however, seems to be central and especially the liver macrophages may be an important major source of these cytokines and thus involved in both local liver and systemic inflammation. The liver macrophages play an important part of the innate immune system localized in the sinusoids as resident macrophages Kupffer cells, where they are subjected to the portal blood containing bacteria, endotoxins, and other substances from the gut. For the first time we have a unique circulating marker for activated macrophages that seem to be highly relevant in liver diseases [18-24, 33-35]. When macrophages are activated, the sCD163 is released, at least partly, by tumor necrosis factor alpha-converting enzyme (TACE/ADAM17) mediated shedding as shown after LPS injection in healthy volunteers [36]. However, macrophages may also be activated by other causes than infections in e.g. sterile inflammation clearing up apoptotic cells, or stimulated directly by other pathogens in e.g. viral hepatitis or NASH as reviewed [4, 5]. We have previously shown that a substantial part of circulating sCD163 may derive from the liver as we have demonstrated a gradient across the liver in TIPS treated patients [19] and indications also in NASH patients [34]. In patients with cirrhosis macrophages seem to be constitutively activated as sCD163 levels were above the upper normal range for all patient groups and with increasing levels with increasing CP-, MELD-, and ACLF-scores. The constitutive upregulation was also demonstrated by persistently elevated sCD163 levels after TIPS insertion despite reduction in portal pressure and endotoxin load to the liver [19]. In opposition to this the general inflammatory markers, e.g. the white blood cell count and CRP levels, were within the normal range in cirrhotic patients without ACLF, and thus reflects general stimulation most likely by infection per se. In this regard, the median sCD163 levels in liver healthy patients with pneumococcal bacteremia are 4.6 mg/L (IQR:2.8-8.9) [37] and in sepsis patients 3.70 (2.19- 11,18) at admission to an intensive care unit [38]. Interestingly, median sCD163 levels were approximately three times higher in pneumococcal infection in patients with alcohol related diseases compared to

liver healthy patients [37]. It may thus be proposed that the constitutively up-regulated or preactivated macrophages when stimulated by e.g. bacteria and other pro-inflammatory cytokines elicits an exaggerated inflammatory response that favors development of ACLF. Our data supports this with higher sCD163 levels in patients with bacterial infections and sepsis compared to patients without. Importantly, the levels increased markedly with sepsis severity and it may be suggested that this exaggerated response may be caused by proinflammatory cytokines. In experimental NASH LPS injections resulted in a blunted acute phase protein response despite an increased cytokine (TNF-a and IL-6) release [39]. This may suggest a reduced ability of the liver to respond in the normal way to inflammatory cytokines. We may speculate that this dysfunctional innate immune response may be involved in sepsis development and progression. A disrupted gut barrier leads to bacterial translocation in cirrhosis which seems to initiate and sustain inflammation that may take place both in mesenteric lymph nodes, the liver, and systemically [10]. The bacteria entering the mesenteric lymph nodes, the liver, and the systemic circulation stimulate the innate immune system to produce cytokines especially TNF as demonstrated in rats [40, 41]. The inflammatory cytokine response may be involved in the hemodynamic changes seen in cirrhosis as a prerequisite for ascites formation but also for ACLF development. The strong association between sCD163 levels, liver disease severity and ACLF classes may provide evidence for macrophages to play a pivotal role in this inflammatory cascade. This may be especially relevant in ACLF where sCD163 levels were a very strong predictor for short-term mortality; and addition of sCD163 to the original CLIF-C ACLF score significantly improved the prognostic prediction. In addition, we observed temporal differences among ACLF survivors and patients that died; the latter group remained with highly elevated or further increased sCD163 levels (and sMR) while survivors showed diminished levels. These data parallels our data from patients with acute liver failure [33]. The mannose receptor is expressed primarily by subsets of macrophages, dendritic and endothelial cells, and the MR binds a broad range of ligands e.g. mannose, sulphated carbohydrates and

collagen as recently reviewed [42]. However, MR expression has also been shown in hepatic and lymphatic endothelia, mesangial cells in kidneys, tracheal smooth muscle cells, and retinal pigment epithelium [43]. A soluble form, sMR, can be produced by proteolytic cleavage in vitro [44, 45], and we have recently demonstrated elevated sMR levels in patients with liver diseases in general and very high levels in patients with severe alcoholic hepatitis [25, 26]. This support the notion that the mannose receptor is involved in macrophage or dendritic cell activation in liver diseases, and especially in conditions characterized by severe inflammation. Further, our data demonstrates that sMR is associated with long-term prognosis in cirrhotic patients without ALCF, which suggest a role independent of severe inflammation and infections, which are more often seen in ACLF patients. The addition of sMR to the newly developed CLIF-C AD score significantly improved the original prognostic score. We are unable to determine whether sMR is primarily shed from macrophages or dendritic cells (or other cell types), and more than one cell type may very well be activated in cirrhosis with or without ACLF. However, due to the fact that sCD163 is exclusively of monocyte/macrophage origin, and the parallel changes observed for sMR, may suggest that macrophages are the primary source for both sCD163 and sMR. The close association between sCD163 and sMR for all patients (Spearman’s rho=0.68) supports this, and was also observed in cirrhosis patients with or without ACLF (Spearman’s rho=0.75 and =0.64 respectively). In conclusion we observed a stepwise increase in sCD163 and sMR levels with liver disease and ACLF severity, and a close association with mortality, which suggest the importance of liver resident macrophages in the development and course of ACLF. Accordingly, the inclusion of macrophage biomarkers to the CLIF-C ACLF and AD scores improves the prognosis predictive performance beyond that of the original scores.

Acknowledgement and financial support: Thanks to Kirsten Bank Petersen, Department of Clinical Biochemistry, Aarhus University Hospital, for excellent technical assistance.

The study obtained funding from The Danish Strategic Research Council (10-092797); HG received funding from the NOVO Nordisk Foundation and “Savværksejer Jeppe Juhl og hustru Ovita Juhls mindelegat”; The CLIF Consortium is supported by an unrestricted grant from Grifols. We thank the coordinators of the biobank at Hospital Clinic Barcelona – IDIBAPS for storage and handling of the samples.

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Legend to figures and graphical abstract: Figure 1: White blood cell count (WCC), sCD163, and sMR levels in patients in the different groups: Group 1: Liver cirrhosis, no ascites and no ACLF; Group 2: Liver cirrhosis with ascites/subrogates but no ACLF; Group 3: ACLF-I, Group 4: ACLF-II; group 5: ACLF-III.

Graphical abstract: White blood cell count (WCC), sCD163, and sMR levels in patients in the different study groups: Group 1: Liver cirrhosis, no ascites and no ACLF; Group 2: Liver cirrhosis with ascites/subrogates but no ACLF; Group 3: ACLF-I, Group 4: ACLF-II; group 5: ACLF-III. We observed a stepwise increase in WCC, sCD163 and sMR with increasing disease severity, and both sCD163 and sMR were independently associated with short and long-term mortality. Addition of sCD163 and sMR to the original CLIF-C ACLF and CLIF-C AD scores improved the prognostic efficacy: In ACLF patients sCD163 improved prediction of short-term mortality (Cindex:0.74(0.67-0.80)) and in patients without ACLF sMR improved prediction of long-term mortality [C-index:0.80(0.76-0.85].

Figure 1

60

A

WBC (x109/L)

50 40 30 20 10 0

1

2

3

4

5

sCD163 (mg/L)

80

Group B

60 40 20 0

1

2

3

4

5

5

Group C

sMR (mg/L)

4 3 2 1 0

1

2

3

4

5

Group

Table 1. Background characteristics of all patients and in the different groups with increasing liver disease severity.

Age (years) Male (N, %) Causes of cirrhosis (N, %) Alcohol HCV Alcohol+HCV Other Previous decompensation (N, %) Encephalopathy (N, %) Ascites (N, %) Bacterial infection (N, %) GI bleeding (N, %) Alcohol consumption (previous 3 months) Organ Failures (N, %) Liver failure Renal failure Brain failure Coagulation failure Cardiovascular failure Respiratory failure Physical exam MAP Laboratory data Hematocrit (%) Hemoglobin Platelet (x10^3/µL)** Bilirubin* Albumin INR* GGT* C-reactive protein* Creatinine* BUN* Serum sodium Serum Potasium

All Patients

No ACLF, No Ascites, No Subrogates

No ACLF, Ascites or Subrogates

ACLF – I

ACLF – II

ACLF – III

N=853 58±12 552(64.9)

N=86 56±12 63(73.3)

N=580 58±12 369(63.6)

N=100 59±11 67(67.0)

N=66 55±11 44(66.7)

N=19 53±10 9(47.4)

0.033 0.207

400(50.3) 170(21.4) 85(10.7) 141(17.7)

41(52.6) 15(19.2) 5(6.4) 17(21.8)

257(47.2) 127(23.4) 60(11.0) 100(18.4)

54(58.7) 14(15.2) 10(10.9) 14(15.2)

39(60.9) 12(18.8) 7(10.9) 6(9.4)

9(50.0) 2(11.1) 3(16.7) 4(22.2)

0.104 0.294 0.691 0.313

606(74.2)

36(42.9)

429(76.6)

83(88.3)

45(72.6)

13(76.5)

<0.001

285(33.5)

10(11.6)

167(28.8)

54(54.0)

38(57.6)

16(84.2)

<0.001

540(63.7)

0(0.0)

406(70.2)

68(68.0)

51(78.5)

15(79.0)

-

197(23.1)

14(16.3)

122(21.0)

27(27.0)

22(33.3)

12(63.2)

<0.001

138(16.2)

31(36.1)

86(14.8)

8(8.0)

10(15.2)

3(15.8)

<0.001

111(13.9)

11(14.1)

68(12.5)

11(11.6)

16(26.7)

5(26.3)

0.017

117(13.8) 109(12.8) 51(6.0) 60(7.1)

9(10.5) 0(0.0) 0(0.0) 0(0.0)

36(6.2) 0(0.0) 16(2.8) 16(2.8)

21(21.0) 66(66.0) 3(3.0) 6(6.0)

37(56.1) 28(42.4) 21(31.8) 26(39.4)

14(73.7) 15(79.0) 11(57.9) 12(63.2)

<0.001 <0.001 <0.001 <0.001

34(4.0)

3(3.5)

2(0.3)

1(1.0)

14(21.2)

14(73.7)

<0.001

17(2.0)

0(0.0)

3(0.5)

3(3.0)

6(9.1)

5(26.3)

<0.001

83±12

86±12

84±11

81±13

79±14

72±10

<0.001

31±6 10±2

33±6 11±2

30±6 10±2

29±5 10±2

27±9 9±3

<0.001 0.001

88(55 - 136)

111(61 - 169)

82 (55 - 143)

72 (55 - 113)

52 (25 - 104)

0.0073

3.0(1.6-6.8) 2.9±0.6 1.5(1.3-1.8) 81(40-179)

1.9(1.1-5.2) 3.1±0.6 1.3(1.2-1.5) 123(60-370)

31±6 10±2 89(56 132) 2.9(1.6-5.5) 2.9±0.6 1.5(1.3-1.7) 79(38-153)

2.6(1.2-8.3) 3.1±0.6 1.4(1.3-1.9) 109(44-192)

13(5-22) 2.7±0.7 2.2(1.7-2.7) 63(32-144)

25(6-35) 2.5±0.6 2.6(2.2-3.8) 57(21-213)

<0.001 <0.001 <0.001 0.001

18(7-40)

14(6-37)

16(6-36)

22(9-47)

25(12-48)

48(33-77)

<0.001

1.0(0.7-1.4) 31(17-60) 135±6 4.2±0.7

0.8(0.7-0.9) 23(15-38) 138±5 4.0±0.6

0.9(0.7-1.2) 28(16-52) 135±6 4.1±0.6

2.4(1.6-3.2) 73(39-101) 134±7 4.5±0.9

1.5(0.8-2.6) 43(15-90) 134±6 4.2±0.9

2.5(1.0-4.2) 61(50-107) 134±9 4.3±0.8

<0.001 <0.001 <0.001 <0.001

Data are mean ± SD or median (Q1-Q3)

Pvalue

Table 2: Clinical scores for liver disease severity (MELD, MELD-Na, Child-Pugh) and organ failures (CLIF-SOFA and CLIF-C- OF) and related mortality in the different study groups.

Scores MELD MELD-Na Child-Pugh CLIF-SOFA CLIF-C OF Mortality At 28 days At 90 days At 180 days

All Patients

No ACLF, No Ascites, No subrogates

No ACLF, +Ascites or subrogates

ACLF – I

ACLF – II

ACLF – III

N=853

N=86

N=580

N=100

N=66

N=19

18±7 21±7 9.5±2.1 6.8±3.0 7.7±1.9

14±5 15±6 7.5±1.5 4.6±1.9 6.7±0.9

17±5 19±6 9.4±1.9 6.0±2.1 7.0±1.1

24±5 26±5 9.6±2.0 8.0±2.3 8.7±1.2

29±7 30±6 11.8±1.7 11.2±2.0 10.8±1.1

36±6 36±5 12.8±1.7 14.8±3.3 14.1±2.0

<0.001 <0.001 <0.001 <0.001 <0.001

80 (9.4) 157 (18.8) 217 (26.6)

1(1.2) 3(3.6) 6(7.5)

30(5.2) 80(14.1) 116(20.9)

17(17.0) 30(30.9) 44(45.8)

18(27.3) 30(45.5) 36(55.4)

14(73.7) 14(73.7) 15(79.0)

<0.001 <0.001 <0.001

Pvalue

Table 3: Correlations between sCD163 and sMR and white blood cell count (WCC) and scores for liver disease severity (MELD, Child-Pugh, CLIF-C AD, CLIF-C ACLF scores). Correlations

sCD163 (mg/L)

sMR (mg/L)

All Patients (n=853) Spearman rho (p-value) 0.25 (<.0001)

No ACLF Patients (n=668) Spearman rho (p-value) 0.19 (<.0001)

ACLF Patients (n=185) Spearman rho (pvalue) 0.20 (0.0061)

MELD CHILD CLIF-C AD score CLIF-C ACLF score WBC (x109cells/L)

0.62 (<.0001) 0.56 (<.0001) NA NA

0.57 (<.0001) 0.48 (<.0001) 0.30 (<.0001) NA

0.65 (<.0001) 0.56 (<.0001) NA 0.34 (<.0001)

0.35 (<.0001)

0.31 (<.0001)

0.35 (<.0001)

MELD CHILD CLIF-C AD score CLIF-C ACLF score

0.46 (<.0001) 0.53 (<.0001) NA NA

0.56 (<.0001) 0.48 (<.0001) 0.39 (<.0001) NA

0.41 (<.0001) 0.53 (<.0001) NA 0.44 (<.0001)

WBC (x109cells/L)

NA: not applicable

Table 4. Mortality prediction by sCD163 and sMR alone and in combination with CLIF-C-ACLF and CLIF-C AD Scores No ACLF Patients (n=543)(1)

#Events

ACLF Patients (n=153) (1)

90-day Mortality

180-day Mortality

28-day Mortality

90-day Mortality

C-index (95 % CI) (2)

C-index (95 % CI) (2)

C-index (95 % CI) (2)

C-index (95 % CI) (2)

75

103

39

62

WBC (x10^9cells/L)

0.68 (0.63, 0.73)

0.66 (0.61, 0.70)

0.61 (0.51, 0.70)

0.60 (0.53, 0.68)

sCD163 (mg/L)

0.69 (0.63, 0.76)

0.68 (0.63, 0.73)

0.71 (0.63, 0.79)

0.66 (0.59, 0.73)

sMR (mg/L)

0.76 (0.71, 0.81)*

0.74 (0.69, 0.78)**

0.67 (0.59, 0.75) ***

0.66 (0.59, 0.72)

MELD

0.70 (0.64, 0.76)

0.66 (0.61, 0.72)

0.71 (0.63, 0.78)

0.69 (0.63, 0.76)

CLIF-C-ADs

0.74 (0.68, 0.79)

0.72 (0.68, 0.77)

CLIF-C-ACLFs

-

-

-

-

0.75 (0.68, 0.83)

0.71 (0.64, 0.77)

MELD+sCD163

0.72 (0.67, 0.78)

0.70 (0.65, 0.75)

0.73 (0.65, 0.80)

0.70 (0.64, 0.76)

MELD+sMR

0.78 (0.73, 0.83)

0.75 (0.71, 0.79)

0.72 (0.65, 0.80)

0.71 (0.64, 0.77)

CLIF-C-ADs + sCD163

0.78 (0.73, 0.83)

0.76 (0.72, 0.80)

CLIF-C-ADs + sMR

0.80 (0.76, 0.85)

0.78 (0.74, 0.82)

CLIF-C-ACLFs + sCD163

Not Applicable

CLIF-C-ACLFs + sMR Comparison C-index MELD vs. P=0.4736 MELD+CD163 Comparison C-index MELD vs. P=0.0076 MELD+sMR Not Applicable Comparison C-index CLIFCACLFs vs. CLIFC-ACLFs +sCD163 Comparison C-index CLIFCACLFs vs. CLIFC-ACLFs +sMR

Not Applicable 0.79 (0.72, 0.86)

0.74 (0.67, 0.80)

0.76 (0.69, 0.83)

0.72 (0.65, 0.78)

P=0.1818

P=0.5793

NS

P=0.0013

NS

NS

P=0.3267

P=0.0328

--

P=0.8026

(1) Patients involved in this analysis are those who have available data for all variables and scores showed. (2) C-index has been estimated under Competing Risk approach in Survival Analysis (3) WBC, sCD163 and sMR are log-tranformed *p=0,0477 with respect to MELD ** p=0.0054 with respect to MELD ***p=0.051 with respect to CLIF-C ACLF score

Table 5. Levels of sCD163 and sMR in patients with and without ACLF and organ failures at inclusion. sCD163 (mg/L) ACLF Patients (n=185)

13.77 (7.87 - 18.95)

           

11.37 (5.95 - 18.41) 16.08 (10.37 - 19.77) 14.12 (9.47 - 19.88) 12.47 (6.94 - 18.89) 17.18 (13.88 - 20.34) 9.22 (5.39 - 17.73) 17.85 (12.98 - 23.29) 11.69 (6.66 - 18.41) 17.01 (11.54 - 29.25) 12.26 (7.32 - 18.54) 13.03 (8.38 - 18.41) 13.77 (7.66 - 19.08)

Renal Failure (n=109) No Renal Failure (n=76) Cerebral Failure (n=35) No Cerebral Failure (n=150) Liver Failure (n=72) No Liver Failure (n=113) Coagulation Failure (n=44) No Coagulation Failure (n=141) Cardiovascular Failure (n=29) No Cardiovascular Failure (n=156) Respiratory Failure (n=14) No Respiratory Failure (n=171)

No ACLF (n=668)  No Failure (n=583)  1 Failure (No Renal) (n=85) Data are Median (Q1 – Q3)

7.92 (4.79 - 11.87) 7.26 (4.56 - 11.17) 10.90 (8.63 - 14.51)

p-value

sMR (mg/L)

p-value

1.03 (0.72 - 1.50) 0.0013 0.1553 <.0001 <.0001 0.0096 0.8887

<.0001

0.92 (0.66 - 1.45) 1.08 (0.81 - 1.51) 1.32 (0.91 - 1.74) 0.98 (0.67 - 1.44) 1.25 (0.96 - 1.63) 0.86 (0.62 - 1.32) 1.22 (0.95 - 1.60) 0.92 (0.67 - 1.45) 1.30 (1.04 - 1.62) 0.94 (0.68 - 1.47) 1.00 (0.76 - 1.82) 1.03 (0.71 - 1.50) 0.78 (0.55 - 1.10) 0.77 (0.54 - 1.06) 0.90 (0.67 - 1.27)

0.0484 0.0015 <.0001 0.0100 0.0047 --

0.0008

Table 6: Changes in sCD163 and sMR levels in 137 ACLF patients from baseline to day 3-7 and related to survival by day 28, 90 and 180 days. Similar data are presented for 158 patients without ACLF. ACLF Patients (n=137) 90-day

28-day Alive (104)

180-day

Dead (33)

pvalue

Alive (82)

Dead (52)

pvalue

Alive (69)

Dead (64)

p-value

18.58 (14.12-20.56) 22.26 (16.44-35.43) 3.29 (-0.65-6.95)

0.0005

11.81 (7.89- 18.26) 11.98 (6.99- 18.16) -0.55 (-1.80-1.21)

17.01 (11.95-0.17) 18.18 (12.88-8.14) 1.85 (-0.53-6.60)

0.0060

11.86 (8.13- 18.09) 12.03 (7.11- 17.98) -0.55 (-1.59- 1.11)

16.43 (10.37-0.35) 17.83 (11.2928.14) 1.55 (-1.17-6.42)

0.0102

0.98 (0.66 - 1.37) 0.95 (0.65 - 1.56) 0.04 (-0.08 - 0.23)

1.27 (0.87 - 1.60) 1.38 (0.99 - 1.95) 0.17 (-0.10 - 0.52)

0.0063

0.95 (0.66 - 1.32) 0.96 (0.65 - 1.42) 0.01 (-0.09-0.19)

1.24 (0.85 - 1.66) 1.38 (0.91 - 2.00) 0.17 (-0.09- 0.46)

0.0037

sCD163 (mg/L) Basal D3-7  (D3-7 - Basal)

12.14 (7.77 -18.28) 12.47 (7.05- 18.24) 0.08 (-1.48- 1.66)

<.0001 0.0085

0.0003 0.0029

0.0010 0.0056

sMR (mg/L) Basal D3-7

0.98 (0.68 - 1.46) 0.99 (0.68 - 1.58) 0.04 (-0.09 - .23)

1.41 (0.97 - 1.66) 1.63 (1.10 - 2.15) 0.30 (-0.05 - 0.53)

0.0083 0.0005

0.0149  (D3-7 - Basal) Missing data: 0 in 28-day; 3 in 90-day; 4 in 180-day

28-day Alive (154)

sCD163 (mg/L) 8.94 Basal (5.42-12.68) D3-7  (D3-7 - Basal)

8.80 (5.82-12.85) 0.11 (-0.91-1.17)

sMR (mg/L) 0.85 Basal (0.63 - 1.12) D3-7  (D3-7 - Basal)

0.87 (0.63 - 1.15) 0.00 (-0.16-0.10)

0.0013 0.1251

No ACLF Patients (n=158) 90-day

0.0006 0.0489

180-day

Dead (4)

pvalue

Alive (132)

Dead (25)

pvalue

Alive (120)

Dead (34)

pvalue

14.40 (12.94-16.99) 15.34 (11.55-25.07) -0.18 (-1.68-8.38)

NA

8.43 (5.15 - 12.35) 8.58 (5.65 - 12.20) 0.04 (-0.94 - 1.09)

12.52 (9.13 - 15.18) 11.94 (8.80 - 16.29) 0.46 (-0.29 - 1.24)

0.0065

8.59 (5.15- 12.35) 8.73 (5.65- 12.20) 0.03 (-1.01-1.05)

11.10 (7.56 - 14.92) 11.54 (8.12 - 18.05) 0.67 (-0.48-1.50)

0.0120

1.24 (1.02-1.65) 1.20 (1.06-1.64) 0.06 (-0.09-0.11)

NA

0.80 (0.61 - 1.11) 0.82 (0.62 - 1.07) 0.00 (-0.16 - 0.09)

1.11 (0.96 - 1.68) 1.13 (0.96 - 1.38) 0.01 (-0.14 - 0.12)

0.0003

0.80 (0.59 - 1.10) 0.82 (0.62 - 1.09) 0.00 (-0.15-0.10)

1.11 (0.89-1.34) 1.06 (0.91-1.38) 0.00 (-0.16-0.12)

0.0003

NA NA

NA NA

0.0021 0.1441

0.0001 0.8200

0.0031 0.0272

0.0004 0.8910

Graphical abstract

60

A

WBC (x109/L)

50 40 30 20 10 0

1

2

3

4

5

sCD163 (mg/L)

80

Group B

60 40 20 0

1

2

3

4

5

5

Group C

sMR (mg/L)

4 3 2 1 0

1

2

3

4

5

Group