Received: 16 August 2018 | Revised: 21 December 2018 | Accepted: 24 December 2018 DOI: 10.1111/liv.14037 CIRRH OS I S AND LIVE R FAILU RE Characterization of inflammatory response in hepatorenal syndrome: Relationship with kidney outcome and survival Cristina Solé1,2,3 | Elsa Solà1,2,3 | Patricia Huelin1,2,3 | Marta Carol2,5 | Rebeca Moreira1,2,3 | Unai Cereijo6 | José‐Manuel Mas6 | Isabel Graupera1,2,3 | Elisa Pose1,2,3 | Laura Napoleone1,2,3 | Gloria dePrada1,2,3 | Adrià Juanola1,2,3 | Núria Fabrellas2,5 | Ferran Torres7 | Manuel Morales‐Ruiz2,3,4 | Judith Farrés6 | Wladimiro Jiménez2,3,4 | Pere Ginès1,2,3 1 Liver Unit, Hospital Clínic de Barcelona, University of Barcelona, Barcelona, Spain 2 Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain 3 Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEReHD) 4 Biochemistry and Molecular Genetics Department, Hospital Clínic de Barcelona, Barcelona, Spain 5 Faculty of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain 6 Anaxomics Biotech, Barcelona, Spain 7 Medical Statistics Core Facility, IDIBAPS, Hospital Clinic Barcelona & Biostatistics Unit, Faculty of Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain Correspondence Dr Pere Ginès, Liver Unit, Hospital Clinic de Abstract Barcelona, Barcelona, Spain. Background: Several lines of evidence indicate that decompensated cirrhosis is charac‐ Email: pgines@clinic.cat terized by the presence of systemic inflammation. Hepatorenal syndrome (HRS‐AKI) is a Funding information Some of the work mentioned has been unique type of renal failure that occurs at late stages of cirrhosis. However, confirmation sponsored by the Instituto de Salud Carlos of the presence and significance of such inflammatory response in HRS‐AKI is lacking. III through the Plan Estatal de Investigación Ciéntifica y Técnica y de Innovación Aim and Methods: To characterize the systemic inflammatory response, as estimated 2013‐2016, PI 12/00330 and PI 16/00043. by measuring a large number of cytokines, in 161 patients hospitalized for an acute This grant was cofunded by the European Regional Development Fund (FEDER). decompensation of cirrhosis: 44 patients without acute kidney injury (AKI), 63 pa‐ This study has been supported in part by tients with hypovolaemia‐induced AKI and 58 patients with HRS‐AKI. an EU Horizon 20/20 Programme, Grant/ Award Number: H2020‐SC1‐2016‐RTD; Results: HRS‐AKI was characterized by an altered cytokine profile compared to the LIVERHOPE, Grant/Award Number: 731875. other two groups, particularly IL‐6, IL‐8, TNF‐α, VCAM‐1, fractalkine and MIP‐1α. Some of the investigators involved have been supported by the AGAUR SGR‐01281 The inflammatory response was not related to presence of bacterial infection, con‐ Grant. PG is a recipient of an ICREA comitant acute‐on‐chronic liver failure or severity of renal dysfunction. Patients who Academia Award. responded to terlipressin and albumin had only a decrease in TNF‐α and RANTES Handing Editor: Frank Tacke after treatment without changes in other cytokines. Interestingly, patients with per‐ sistent HRS‐AKI had higher levels of IP‐10 and VCAM‐1 compared to those with See Editorial on Page 1199 Abbreviations: CCL11, Eotaxin; CX3CL1, fractalkine; G‐CSF, granulocyte colony‐stimulating factor; ICAM‐1, intercellular adhesion molecule‐1; IFN‐γ, interferon gamma; IL‐10, interleu‐ kin‐10; IL‐1RA, interleukin‐1 receptor antagonist; IL‐1β, interleukin‐1 beta; IL‐6, interleukin‐6; IL‐8, interleukin‐8; IP‐10, interferon‐inducible protein‐10; MCP‐1, monocyte chemoattrac‐ tant protein‐1; MELD, model of end‐stage liver disease; MIP‐1α, macrophage inflammatory protein 1‐alpha; MIP‐1β, macrophage inflammatory protein 1‐beta; RANTES, regulated on acti‐ vation normal T cell expressed and secreted; TNF‐α, tumour necrosis factor‐alpha; VCAM‐1, vascular cell adhesion molecule‐1; VEGF, vascular endothelial growth factor. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. © 2018 The Authors. Liver International Published by John Wiley & Sons Ltd 1246 | © 2018 John Wiley & Sons A/S. wileyonlinelibrary.com/journal/liv Liver International. 2019;39:1246–1255. Published by John Wiley & Sons Ltd SOLÉ et al. | 1247 resolution of HRS‐AKI. VCAM‐1 was also an independent predictor of 3‐month mor‐ tality. A systems biology analysis approach showed that the inflammatory status of HRS‐AKI was similar to that of chronic nonhepatic inflammatory conditions, such as lupus erythematosus or inflammatory bowel disease. Conclusion: Hepatorenal syndrome is characterized by a marked systemic inflamma‐ tory state, reminiscent of that of nonhepatic inflammatory diseases, that correlates with patient outcomes. KEYWORDS AKI, cirrhosis, hepatorenal syndrome, inflammation 1 | I NTRO D U C TI O N LAY SUMMARY Hepatorenal syndrome (HRS) is a unique type of acute kidney injury (AKI), currently known as (HRS‐AKI), which develops in patients with • Hepatorenal syndrome, a type of renal dysfunction that decompensated cirrhosis and is considered a very severe complica‐ occurs at the end stage of cirrhosis, is characterized by a tion of the disease at the end of the spectrum of complications of marked systemic inflammatory state. cirrhosis.1,2 • Lack of resolution of renal impairment and short‐term A large body of evidence demonstrating that circulatory dys‐ mortality are associated with increased levels of some function plays a key role in the pathophysiology of HRS‐AKI. 2-4 It inflammatory markers; IL‐6, IL‐8, TNF‐α, ICAM‐1 and has been shown that HRS‐AKI occurs as a consequence of an in‐ particularly, VCAM‐1. tense renal vasoconstriction with marked reduction in renal blood • A systems biology analysis approach showed that the flow and glomerular filtration rate (GFR), which is pathogenically inflammatory status of hepatorenal syndrome was simi‐ related to a striking splanchnic arterial vasodilatation with activa‐ lar to that found in chronic nonhepatic inflammatory tion of major vasoconstrictor systems, as a consequence of portal diseases, such as lupus erythematosus or inflammatory hypertension. 4,5 Administration of vasoconstrictors, particularly bowel disease. terlipressin, in association with albumin, improves circulatory func‐ tion and is able to return renal function to baseline values in many patients, which confirms the major role of circulatory dysfunction extent and significance of inflammation in patients with HRS‐AKI. with arterial vasodilation in the pathogenesis of kidney impairment Given that HRS‐AKI is considered the hallmark of the disease, this in HRS‐AKI.6,7 information may be relevant not only with respect to pathogenesis In recent years, it has become increasingly evident that cirrhosis is but also for identification of potential targets of therapy to prevent a condition with marked systemic inflammatory state, which appears disease progression. to increase with disease progression, from compensated to decom‐ On this background, the aim of our study was to assess the ex‐ pensated cirrhosis, and is related to patient outcome.8,9 Some clinical istence of systemic inflammation, as estimated by plasma levels of a studies have assessed inflammation by measuring leucocyte count large number of inflammatory cytokines, in patients with HRS‐AKI 10 or C‐reactive protein (CRP) levels, while others have assessed the and investigate the relationship between inflammation and kidney prevalence of systemic inflammatory response syndrome (SIRS)11; and patient outcomes. Because systemic inflammation is common in however, these methods are not very accurate in the evaluation of ACLF and patients with HRS‐AKI frequently meet diagnostic criteria inflammation. Besides, studies in experimental animals have also of ACLF, the role of this latter condition as potential cause of inflam‐ demonstrated the existence of systemic inflammation that is more mation in HRS‐AKI was also assessed. conspicuous in animals with ascites compared to those without.12 Finally, few studies have evaluated a large number of inflammatory 2 | PATI E NT S A N D M E TH O DS cytokines and confirmed the presence of systemic inflammation, as estimated by increased plasma levels of relevant cytokines involved 2.1 | Patient population and study design in inflammation, which increase with disease progression.8,13,14 The hypothesis, therefore, has been raised that cirrhosis is a disease One‐hundred and sixty‐five episodes of AKI occurring in 161 pa‐ characterized by marked and progressive systemic inflammation that tients with decompensated cirrhosis admitted to the Liver Unit of 15 may play a role in the development of complications of the disease. Hospital Clinic were investigated in the current study. These patients However, so far there is lack of information regarding the presence, were selected from a prospective database with Biobank collection 1248 | SOLÉ et al. that includes consecutive patients with cirrhosis admitted to hospi‐ criterion of the median value. Multivariate Cox regression was per‐ tal for treatment of an acute decompensation of the disease. Three formed to identify the independent factors associated with mortal‐ groups of subjects were identified randomly from the database: (1) ity. There was no specific calculation of the sample size. However, patients with decompensated cirrhosis without AKI (N = 44), (2) pa‐ based on previous experience studies in patients with cirrhosis,14,18 tients with hypovolaemia‐induced AKI (N = 63) and (3) patients with it was considered that more than 100 patients had to be included in HRS‐AKI (N = 58). Forty‐one of the 58 patients (71%) with HRS‐AKI this study to achieve a significant number of outcomes in terms of met the classical criteria of type‐1 HRS.16 Exclusion criteria were lack of AKI resolution and 3‐month mortality. All statistical analyses previous kidney/liver transplantation, chronic haemodialysis before were performed using SPSS statistical package, version 23.0. The admission, hepatocellular carcinoma outside the Milan criteria or any significance level for all tests was set at 0.05 two‐tailed. other advanced malignancy, and lack of inform consent. Demographical, clinical and analytical data were collected pro‐ 2.5 | Systems biology analysis spectively at admission and at regular intervals during hospitalization, and patients were followed up for at least 3 months after discharge. We used a systems biology approach based on artificial neural Blood and urine samples were collected at the time of inclusion in this networks supervised algorithm (ANN algorithm) that measures study. Moreover, in 27 patients with type 1‐HRS, samples were also the strength of relationships between groups of human proteins.19 collected after treatment with terlipressin and albumin (median time Measures are based on the topology of the network, and the training between the two sample collections was of 7 days). Blood was centri‐ set is derived mostly from drug effects. The conditions used were fuged at 2000 g, at 4°C, for 10 min, and plasma was stored at −80°C those defined in BED (Biological Effectors Database, Anaxomics until analysis. All samples were stored at the Biobank as required Biotech, Barcelona, Spain) a hand‐curated collection of scientific by Spanish legislation. This study was approved by the Institutional knowledge relating biological processes to their molecular effectors. Review Board of our centre, the research Ethic Committee of the The ANN algorithm provides a predictive score (from 0% to 100%) Hospital Clínic of Barcelona (HCB/2017/0285), and all patients signed that quantifies the amount and strength of relationships between a written informed consent for participation in this study. the evaluated proteins. Each score is associated with a P value that describes the probability of the results being a true positive re‐ sult19,20 (see Supplementary materials). 2.2 | Multiplex cytokine assay The following 18 cytokines and vascular adhesion molecules 3 | R E S U LT S were determined in plasma with the Luminex® Immunoassay Kit (Panomics®, Affymetrix Inc, Santa Clara, CA, USA): eotaxin, G‐ 3.1 | Baseline characteristics of patients CSF, fractalkine, IFN‐γ, IL‐10, IL‐1RA, IL‐1β, IL‐6, IL‐8, IP‐10, MCP‐1, MIP‐1α, MIP‐1β, TNF‐α, VEGF, ICAM‐1, VCAM‐1 and RANTES (see The baseline characteristics of patients with decompensated cirrho‐ Supplementary materials). Urine MCP‐1 was also analysed (R&D® sis included in this study categorized into 3 groups (no AKI, hypovol‐ Systems, Minneapolis, MN, USA). Cytokines IL‐10, IL‐1RA and IL‐1β aemia‐induced AKI and HRS‐AKI) are shown in Table 1. Of interest, were excluded from statistical analyses because their levels were bacterial infections were more common in patients with HRS‐AKI out of the detection limit in more than 30% of the samples. compared to the other two groups, a finding consistent with the known role of bacterial infections as triggering factors of HRS‐AKI. As expected, the frequency and severity of ACLF were higher in pa‐ 2.3 | Definitions tients with HRS‐AKI compared to that of patients with hypovolae‐ AKI and ACLF were defined according to ICA1 and CANONIC17 defi‐ mia‐induced AKI. nitions respectively (see Supplementary materials). 3.2 | Systemic inflammatory response and 2.4 | Statistical analysis cytokine levels Comparisons of normally distributed continuous variables were The prevalence of SIRS, leucocyte count and serum CRP levels were made with Student's t test or ANOVA. Comparisons of non‐normally higher in patients with HRS‐AKI compared to the other two groups distributed continuous variables were made with Mann‐Whitney (Table 2). With respect to cytokine levels, patients with HRS‐AKI had U or Kruskal‐Wallis tests. Results for continuous variables are ex‐ a cytokine profile different from that in the other two groups, with pressed as median and interquartile range (IQR). Categorical vari‐ statistically significant differences in the levels of several cytokines, ables were expressed as number and percentage and compared with including higher urinary levels of MCP‐1 and plasma IL‐6, TNF‐α, the chi‐square test or Fisher exact test. Survival curves were calcu‐ VCAM‐1, and IL‐8, and lower levels of MIP1‐α and fractalkine. lated with Kaplan and Meier method and compared with log‐rank To further explore the cytokine profile of HRS‐AKI, we assessed test. Due to the lack of prior knowledge on the relevance of cut‐off whether the increased cytokine levels found in these patients could levels for quantitative variables, we decided to use the unsupervised be related to concomitant bacterial infections that were more SOLÉ et al. | 1249 TA B L E 1 Baseline demographical, clinical and laboratory characteristics of patients included in this study Hypovolaemia‐induced AKI No AKI (N = 44) (N = 63) HRS‐AKI (N = 58) P value Age, years 62 (56‐70) 62 (54‐67) 59 (53‐66) 0.556 Diabetes mellitus 14 (32) 21 (33) 16 (28) 0.783 Male gender 30 (68) 43 (68) 45 (78) 0.445 Aetiology of cirrhosis: Alcohol/ 24 (55)/10 (23) 26 (41)/15 (24) 28 (48)/12 (21) 0.558 hepatitis C Ascites 23 (52) 44 (67) 58 (100) <0.001 Hepatic encephalopathy 3 (7) 12 (19) 28 (48) <0.001 Bacterial infection 22 (50) 20 (32) 42 (72) <0.001 Serum creatinine (mg/dL) 0.8 (0.6‐1.0) 1.6 (1.3‐1.9) 2.6 (1.9‐3.1) <0.001 Serum bilirubin (mg/dL) 2.5 (1.4‐3.9) 2.6 (1.6‐5) 4.2 (2.4‐11.2) 0.004 INR 1.5 (1.3‐1.6) 1.5 (1.3‐1.9) 1.9 (1.5‐2.2) <0.001 Serum sodium (mEq/L) 137 (134‐140) 135 (132‐139) 131 (127‐135) <0.001 9 Platelet count (×10 /L) 85 (56‐140) 77 (49‐110) 76 (50‐103) 0.441 Mean arterial pressure (mm Hg) 82 (76‐92) 77 (69‐87) 74 (68‐84) 0.010 MELD score 14 (12‐18) 19 (15‐24) 28 (23‐34) <0.001 Child‐Pugh score 8 (6‐9) 8 (7‐10) 11 (9‐12) <0.001 ACLF Frequency 0 27 (43) 49 (84) <0.001 Grade 1 vs 2/3 – 21/6 26/23 <0.001 INR, International normalized ratio; MELD, model for end‐stage liver disease. Values are number and percentages (in brackets) or median and interquartile range (in brackets). common in this group of subjects. With this objective, we compared P < 0.001). Out of all cytokines evaluated, only plasma TNF‐α and cytokine levels in patients with HRS‐AKI categorized according to RANTES decreased significantly and MIP‐1α increased with reversal presence or absence of infection (42 and 16 patients, respectively) of kidney dysfunction (Table 3). (Supplementary Table 1). Out of the 5 cytokines that were differen‐ Since many patients with HRS‐AKI meet the criteria of ACLF, we tially increased in patients with HRS‐AKI, only plasma IL‐6 was sig‐ investigated whether the increased levels of inflammatory cytokines nificantly higher in patients with HRS‐AKI associated with infections found in HRS‐AKI were potentially related to the presence of con‐ compared to those without infections (59 (21‐180) vs 23 (12‐55) pg/ comitant ACLF. To this aim, we categorized patients with HRS‐AKI mL, respectively, P = 0.02). However, it is possible that a further ag‐ according to the presence or absence of ACLF. As shown in Table 4, gravation of the increased systemic inflammation during HRS‐AKI patients with HRS‐AKI with associated ACLF had levels of cytokines associated with bacterial infections could not be detected due to the that were similar to those of patients with HRS‐AKI without ACLF. low number of patients with HRS‐AKI without infections. Moreover, the levels of cytokines did not correlate with ACLF sever‐ Next, we analysed whether severity of kidney impairment in HRS‐ ity, except for higher levels of IL‐8 and ICAM‐1 in patients with ACLF AKI correlated with the intensity of systemic inflammatory response. grades 2‐3 vs those of patients with grade 1 (Table 5). To further ex‐ As shown in Supplementary Table 2, categorization of patients with plore the relationship between AKI and ACLF, we compared inflam‐ HRS‐AKI in those who met the diagnostic criteria of type‐1 HRS, the matory cytokine levels in patients with ACLF categorized according most severe form of HRS‐AKI, and those who did not meet these cri‐ to AKI type, either HRS‐AKI or hypovolaemia‐induced AKI. Patients teria, showed no significant differences with respect to frequency of with ACLF associated with HRS‐AKI had higher levels of IL‐6, TNF‐α SIRS, leucocyte count and CRP, as well as cytokine levels. In the HRS‐ and urinary MCP‐1 and lower levels of fractalkine and MIP1‐α com‐ AKI group, serum creatinine levels did not correlated with inflammatory pared to the hypovolaemia‐induce AKI counterparts (data not shown). biomarkers, except for urinary levels of MCP‐1 (r = 0.420, P = 0.002). We also investigated whether reversal of kidney impairment in 3.3 | Relationship of systemic inflammatory patients with HRS‐AKI was associated with changes in cytokine pro‐ response and cytokine levels with kidney file. To this purpose, we compared cytokine levels before and after outcome and patient survival kidney function improvement in 24 patients with type‐1 HRS treated with vasoconstrictors and albumin. As expected, serum creatinine Out of the 121 patients with AKI, resolution of kidney function im‐ decreased significantly after treatment (from 2.9 to 1.3 mg/dL; pairment was observed in 86 (71%), whereas the remaining 35 (29%) 1250 | SOLÉ et al. TA B L E 2 Comparison of systemic inflammatory markers and plasma and urine cytokine levels between the 3 groups of patients Hypovolaemia‐induced AKI No AKI (N = 44) (N = 63) HRS‐AKI (N = 58) P value C‐reactive protein (mg/dL) 1.6 (0.5‐3.9) 1.0 (0.4‐2.2) 3 (1.7‐6.1) <0.001 Leucocyte count (×109/L) 5 (4‐7) 5 (4‐8) 7 (4‐11) 0.046 SIRS 7 (16) 10 (16) 17 (33) 0.053 Plasma cytokines IL‐6 (pg/mL) 14 (3‐46) 14 (3‐46) 45 (19‐104) <0.001 TNF‐α (pg/mL) 22 (17‐39) 30 (19‐50) 47 (35‐61) <0.001 Fractalkine (pg/m) 111 (19‐559) 363 (88‐21924) 111 (29‐377) 0.004 MIP1‐α (pg/mL) 2048 (12‐3970) 41 (13‐3970) 14 (6‐52) 0.005 VCAM‐1 (ng/mL) 1816(1249‐2662) 2184(1659‐2866) 2410(1850‐3731) 0.006 IL‐8 (pg/mL) 25 (12‐75) 45 (18‐90) 56 (37‐92) 0.009 VEGF (pg/mL) 453 (75‐19,715) 179 (104‐1681) 166 (71‐539) 0.088 G‐CSF (pg/mL) 30 (3‐82) 14 (3‐41) 30 (6‐58) 0.132 MCP‐1 (pg/mL) 269 (175‐376) 284 (214‐444) 340 (212‐472) 0.370 RANTES (pg/mL) 7458 (1937‐23,962) 4515 (2040‐17,985) 4399 (1293‐20,774) 0.449 INF‐γ (pg/mL) 29 (5‐88) 37 (14‐129) 35 (13‐122) 0.454 IP‐10 (pg/mL) 961 (592‐1671) 1000 (594‐2067) 1206 (690‐2014) 0.556 ICAM‐1 (ng/mL) 269 (215‐500) 279 (215‐377) 306 (234‐443) 0.596 Eotaxin (pg/mL) 115 (78‐157) 101 (68‐161) 109 (84‐143) 0.772 MIP1‐β (pg/mL) 40 (15‐91) 30 (21‐72) 36 (23‐80) 0.779 Urinary cytokines uMCP‐1 (pg/mL) 408 (207‐1257) 443 (193‐1340) 1292 (689‐3356) <0.001 SIRS; Systemic inflammatory response. Values are number and percentages (in brackets) or median and interquartile range (in brackets). patients had persistent AKI. Patients with persistent AKI had signifi‐ 3.4 | Comparison of cytokine profile in HRS‐AKI cantly higher baseline leucocyte count and CRP levels and plasma with other chronic conditions using with systems IL‐6 and VCAM‐1 compared to those of patients with AKI resolu‐ biology approach tion. In the group of patients with HRS‐AKI, those with persistent AKI (27 patients, 47%) showed significantly higher leucocyte count We used a systems biology approach based on artificial neural and plasma levels of IP‐10 and VCAM‐1 compared to those who had networks that measures the strength of relationships between resolution of HRS‐AKI (31 patients, 53%), yet differences of these groups of human proteins in order to compare the extent of sys‐ latter two cytokines were barely significant (Table 6). temic inflammation in HRS‐AKI with that of other conditions char‐ At the end of the 3‐month follow‐up period, 110 patients acterized by well‐defined and marked systemic inflammatory status. (69%) were alive, 34 (21%) had died, and 15 (9%) had been trans‐ Interestingly, the cytokine pattern of HRS‐AKI was related to that of planted and 2 were lost to follow‐up. Interestingly, a number of a number of inflammatory conditions, including cystic fibrosis, rheu‐ inflammatory parameters and cytokines correlated with 3‐month matoid arthritis, systemic lupus erythematosus, Crohn's disease and mortality: leucocyte count, CRP levels and plasma IL‐6, IL‐8, ulcerative colitis (predictive value > 70) (Figure 2). TNF‐α, ICAM‐1 and VCAM‐1. In multivariate analysis, including those inflammatory variables that were associated with mortality in the univariate analysis, only plasma VCAM‐1 was an indepen‐ 4 | D I S CU S S I O N dent predictive factor of 3‐month mortality. Plasma VCAM‐1 was also the only inflammatory marker independently predictive of The results of the current study show that patients with HRS‐AKI 3‐month mortality in the group of patients with HRS‐AKI (3156 have marked systemic inflammation with altered cytokine pro‐ (2029‐4349) vs 1944 (1535‐2829) ng/mL, for patients who died file compared to that of patients with decompensated cirrhosis and survived at 3 months, respectively; P < 0.01), even when ad‐ without AKI and, most interestingly, to patients with AKI due to justed for the presence and severity of ACLF. Survival probability hypovolaemia. The systemic inflammatory response in HRS‐AKI in patients with HRS‐AKI according to VCAM‐1 levels is shown does not seem to be related to presence of bacterial infections, in Figure 1. concomitant ACLF or intensity of kidney dysfunction and is not SOLÉ et al. | 1251 TA B L E 3 Systemic inflammatory markers and plasma and urine TA B L E 4 Comparison of systemic inflammatory markers and cytokine levels in patients with type 1 HRS‐AKI before and after plasma and urine cytokine levels in patients with HRS‐AKI effective treatment with terlipressin and albumin categorized according to the presence of ACLF Terlipressin and HRS‐AKI without HRS‐AKI with P Baseline (N = 24) Albumin (N = 24) P value ACLF (N = 9) ACLF (N = 49) value Serum 2.9 (2.6‐3.6) 1.3 (1.2‐1.5) <0.001 C‐reactive 3 (2‐4) 3 (2‐6) 0.552 creatinine protein (mg/ (mg/dL) dL) C‐reactive 4.9 (2.5‐6.7) 1.3 (1.2‐1.5) 0.008 Leucocyte 7 (5‐9) 7 (4‐11) 0.991 protein (mg/ count (×109/L) dL) SIRS 3 (33) 14 (33) 1.000 Leucocyte 7 (2.9‐11) 5 (3‐9) 0.246 Plasma count (×109/L) cytokines Plasma Eotaxin (pg/mL) 114 (85‐269) 108 (82‐134) 0.439 cytokines G‐CSF (pg/mL) 30 (4‐102) 30 (8‐56) 0.880 Eotaxin (pg/mL) 104 (78‐130) 115 (85‐144) 0.909 Fractalkine 133 (44‐662) 106 (24‐307) 0.805 G‐CSF (pg/mL) 31 (9‐68) 18 (3‐41) 0.259 (pg/L) Fractalkine (pg/ 140 (13‐679) 79 (13‐835) 0.475 INF‐γ (pg/mL) 97 (22‐302) 31 (12‐94) 0.179 mL) IL‐6 (pg/mL) 21 (19‐76) 47 (18‐137) 0.629 INF‐γ (pg/mL) 73 (25‐165) 39 (18‐111) 0.230 IL‐8 (pg/mL) 46 (35‐83) 60 (37‐99) 0.599 IL‐6 (pg/mL) 73 (16‐95) 32 (7‐58) 0.128 IP‐10 (pg/mL) 1096 (816‐2933) 1232 (671‐1957) 0.660 IL‐8 (pg/mL) 62 (38‐78) 54 (38‐94) 0.648 MCP‐1 (pg/mL) 265 (148‐656) 344 (216‐463) 0.755 IP‐10 (pg/mL) 1457 (563‐2067) 884 (519‐1258) 0.116 MIP1‐α (pg/mL) 41 (12‐2011) 13 (5‐52) 0.218 MCP‐1 (pg/mL) 337 (189‐401) 283 (222‐384) 0.753 MIP1‐β (pg/mL) 30 (20‐87) 39 (24‐75) 0.540 MIP1‐α (pg/mL) 10 (6‐47) 46 (9‐3970) 0.030 TNF‐α (pg/mL) 51 (38‐53) 46 (33‐62) 0.755 MIP1‐β (pg/mL) 50 (18‐93) 31 (14‐52) 0.073 VEGF (pg/mL) 146 (79‐10,184) 168 (64‐394) 0.547 TNF‐α (pg/mL) 48 (33‐67) 30 (22‐52) 0.007 ICAM‐1 (ng/mL) 285 (217‐449) 314 (239‐439) 0.739 VEGF (pg/mL) 181 (87‐485) 163 (58‐961) 0.223 VCAM‐1 (ng/ 2242 (1559‐3132) 2459 0.512 ICAM‐1 (ng/mL) 296 (227‐403) 326 (219‐370) 0.775 mL) (1825‐3895) VCAM‐1 (ng/ 2054 2162 0.278 RANTES(pg/ 5706 3369 0.084 mL) (1748‐3009) (1604‐2598) mL) (2949‐69,961) (1241‐17,941) RANTES (pg/ 3897 2158 (974‐5004) 0.013 Urinary mL) (1321‐13453) cytokines Urinary uMCP‐1 (pg/ 736 (647‐1364) 1382 (810‐3543) 0.213 cytokines mL) uMCP‐1 (pg/ 3293 2193 0.193 SIRS; systemic inflammatory response. mL) (1113‐5204) (1218‐4657) Values are number and percentages (in brackets) or median and inter‐ Values are number and percentages (in brackets) or median and inter‐ quartile range (in brackets). quartile range (in brackets). normalized by improvement of kidney function with pharmaco‐ was also studied. This type of AKI was selected as comparator for logical therapy. Interestingly, the intensity of the inflammatory HRS‐AKI because in both conditions AKI is of prerenal origin, yet response is correlated with kidney and patient outcomes in such a the underlying pathogenic cause is very different. While a con‐ way that increased levels of some inflammatory markers, particu‐ tracted blood volume is the cause of renal hypoperfusion in the larly VCAM‐1, are associated with lack of resolution of AKI and former, the impairment of kidney function in the latter is related mortality. to opposite circulatory features, namely markedly dilated vascular In the current study, a large number of consecutive patients bed, particularly in the splanchnic circulation. 2-4 The results of the with cirrhosis and HRS‐AKI were investigated for the presence of current study clearly show that as decompensated cirrhosis pro‐ systemic inflammatory response as assessed by a large number gresses towards HRS‐AKI, there is progressive increase in inflam‐ of inflammatory and anti‐inflammatory cytokines using multiplex matory status with significantly increased levels of some powerful technology. A control group of patients with decompensated cir‐ inflammatory cytokines. Previous studies have shown that plasma rhosis without AKI was included for comparison. A group of pa‐ levels of inflammatory cytokines are significantly increased in tients with decompensated cirrhosis with AKI due to hypovolaemia decompensated compared to compensated cirrhosis, suggesting 1252 | SOLÉ et al. TA B L E 5 Comparison of systemic inflammatory markers and TA B L E 6 Comparison of systemic inflammatory markers and plasma and urine cytokine levels in patients with HRS‐AKI plasma and urine cytokine levels in patients with HRS‐AKI associated with ACLF classified according to ACLF severity calculated according to outcome of AKI ACLF 2 and 3 P AKI resolution AKI persistent P ACLF 1 (N = 26) (N = 23) value (N = 31) (N = 27) value C‐reactive 3 (1‐6) 3 (2‐6) 0.855 3.9 (2.6‐5.8) 2.2 (1.7‐6.4) 0.358 protein (mg/ Leucocyte 5.6 (3.0‐9.2) 7.8 (6.4‐11.6) 0.016 dL) count Leucocyte 6 (3‐11) 7 (4‐12) 0.400 (×109/L) count SIRS 11 (41) 6 (24) 0.199 (×109/L) Plasma SIRS 7 (32) 7 (33) 0.993 cytokines Plasma Eotaxin (pg/ 103 (79‐138) 110 (96‐156) 0.761 cytokines mL) Eotaxin (pg/ 101 (79‐127) 118 (100‐161) 0.123 G‐CSF (pg/mL) 27 (4‐57) 39 (6‐60) 0.742 mL) Fractalkine 117 (28‐4022) 97 (29‐223) 0.382 G‐CSF (pg/ 39 (12‐75) 21 (6‐43) 0.212 (pg/mL) mL) INF‐γ (pg/mL) 38 (13‐122) 32 (11‐124) 0.483 Fractalkine 90 (3‐428) 155 (29‐280) 0.595 (pg/L) IL‐6 (pg/mL) 41 (17‐96) 57 (21‐145) 0.459 INF‐γ (pg/mL) 35 (14‐94) 19 (11‐124) 0.582 IL‐8 (pg/mL) 60 (41‐80) 53 (36‐152) 0.714 IL‐6 (pg/mL) 45 (12‐80) 56 (21‐255) 0.207 IP‐10 (pg/mL) 915 (538‐1875) 1267 (807‐2564) 0.045 IL‐8 (pg/mL) 44 (27‐69) 91 (43‐202) 0.006 MCP‐1 (pg/mL) 330 (160‐402) 396 (215‐550) 0.293 IP‐10 (pg/mL) 898 (634‐1941) 1267 (778‐2162) 0.417 MIP1‐α (pg/ 14 (8‐49) 18 (5‐3970) 0.784 mL) MCP‐1 (pg/ 337 (198‐397) 411 (234‐712) 0.089 mL) MIP1‐β (pg/ 33 (20‐71) 43 (25‐84) 0.370 mL) MIP1‐α (pg/ 10 (6‐29) 25 (3‐3970) 0.701 mL) TNF‐α (pg/mL) 47 (32‐62) 46 (35‐59) 0.726 MIP1‐β (pg/ 37 (23‐65) 42 (28‐84) 0.548 VEGF (pg/mL) 172 (67‐1311) 157 (75‐291) 0.606 mL) ICAM‐1 (ng/ 278 (228‐367) 345 (236‐508) 0.129 TNF‐α (pg/mL) 46 (31‐61) 49 (34‐63) 0.749 mL) VEGF (pg/mL) 169 (69‐323) 144 (44‐1675) 0.936 VCAM‐1 (ng/ 2132 (1747‐2871) 3139 0.044 mL) (2005‐4266) ICAM‐1 (ng/ 273 (221‐344) 411 (251‐536) 0.019 mL) RANTES (pg/ 4668 3369 0.533 mL) (2071‐16,146) (1101‐26,588) VCAM‐1 (ng/ 2050 (1750‐3279) 3040 0.200 mL) (2120‐4044) Urinary cytokines RANTES (pg/ 3835 3369 0.417 mL) (1256‐26,358) (890‐16,162) uMCP‐1 (pg/ 1148 (716‐5069) 1164 (661‐2007) 0.123 mL) Urinary cytokines SIRS; systemic inflammatory response. Values are number and percentages (in brackets) or median and inter‐ uMCP‐1 (pg/ 1624 (824‐4849) 1250 (752‐2879) 0.274 quartile range (in brackets). mL) SIRS; systemic inflammatory response. Values are number and percentages (in brackets) or median and inter‐ systemic inflammation driving the complications of cirrhosis.15 quartile range (in brackets). Further support to this theory comes from our systems biology analyses showing that systemic inflammation in cirrhosis is similar the existence of an inflammatory driving force that occurs with to that found in some key chronic inflammatory conditions, such the progression of the disease. 8,9 Whether this inflammatory as inflammatory bowel diseases, rheumatoid arthritis or systemic driving force is cause or consequence of progression of liver dis‐ lupus erythematosus. ease is not known. Our data confirm that this inflammatory status One relevant issue of the current study is whether the increased across decompensated cirrhosis increases even more as the dis‐ inflammatory state observed in patients with HRS‐AKI was due to ease progresses towards HRS‐AKI which is considered one of the ‘hepatorenal syndrome’ itself or the presence of concomitant ACLF, latest stages of cirrhosis, given its high mortality rate. Our data since it has been shown that the latter condition is characterized by therefore are in agreement with the recently proposed theory of a marked systemic inflammation.13,14 Two lines of evidence suggest SOLÉ et al. | 1253 that the increased inflammatory state is not related to ACLF. Firstly, which prevented performing a propensity score matching analysis. patients with HRS‐AKI but without ALCF had plasma cytokine lev‐ Further studies are needed to try to dissect out whether systemic els that were not significantly different from those found in patients inflammation is due to hepatorenal syndrome ‘per se’ or to ACLF, with HRS‐AKI with ACLF. Moreover, cytokine levels were largely or both. unrelated to ACLF grade. On the other hand, cytokine profile of pa‐ A final issue that deserves discussion is that patients in whom tients with HRS‐AKI was noticeably different from that of patients HRS‐AKI persisted showed higher levels of some inflammatory mark‐ with ACLF associated with hypovolaemia‐induced AKI, suggesting ers, the most important of which appears to be VCAM‐1. Moreover, that cytokine profile was mostly related to ‘hepatorenal syndrome’ VCAM‐1 was also an independent predictive factor of survival in the and not to ACLF. Nevertheless, these findings should be taken with whole series of patients. VCAM‐1 is an inflammatory mediator that caution because of the relatively low number of patients included plays a central role in triggering the process of systemic inflamma‐ tion in response to several stimuli by helping recruit inflammatory cells outside of the systemic circulation. 21 Few previous studies have VCAM-1< 2372 ng/ml shown the potential relevance of VCAM‐1 as prognostic indicator VCAM-1 ≥ 2372 ng/ml ------ of patients with cirrhosis. 22 Our results extend these observations by showing that among a large number of inflammatory markers, VCAM‐1 plasma levels are associated with lack of resolution of HRS‐AKI and poor survival. These results together with findings of a similar inflammatory profile compared to that of some inflammatory Survival diseases shed light on the potential role of VCAM‐1 and TNF‐α as therapeutic targets in patients with advanced cirrhosis. 23 The current study has some limitations that should be acknowl‐ edged. Firstly, some cytokines, such as IL‐10 and IL‐1RA, were out‐ side of the range detection limit established for the multiplex assay p = 0.023 and could not be evaluated. The multiplex methodology allows the measurement of cytokines in little volume and in the same sample well. To achieve this multiplexing, the quantification of analytes is performed with serial dilutions of a common calibrator. Therefore, the individual adjustment of the detection limit for each analyte is not possible with the consequent lost of quantification in the case of Days some cytokines included in the multiplexing. This problem could be F I G U R E 1 Probability of 3‐month survival in patients with HRS‐ solved by performing high sensitivity immunoanalytical methods for AKI categorized according to median levels of VCAM‐1 single analytes, but due to limitations in the available sample volume, F I G U R E 2 Relationship between systemic inflammatory pattern in patients included in this study and different pathological conditions based on a network analysis. Link width and distance to the central point is proportional to the predictive score of the network analysis that quantifies the network relationships between the evaluated proteins. Only medically relevant conditions with a predictive score corresponding to P ≤ 0.1 are displayed. Conditions as defined in BED (Biological Effectors Database, Anaxomics Biotech) 1254 | SOLÉ et al. this alternative strategy was not possible. Secondly, given the rela‐ ORCID tive small sizes of our study populations and the exploratory nature Cristina Solé https://orcid.org/0000-0002-6104-8345 of this study, we decided not to implement multiplicity adjustment strategies. This study will require future replication and the findings Unai Cereijo https://orcid.org/0000-0003-1557-8836 in general and the P values in particular should be interpreted with Pere Ginès https://orcid.org/0000-0003-4657-4504 caution. Thirdly, although the number of patients studied may ap‐ pear relatively low, it is a quite large sample of patients considering REFERENCES the difficulty to perform clinical studies in decompensated cirrhosis and the sample size of previous pathogenic and therapeutic stud‐ 1. Angeli P, Ginès P, Wong F, et al. Diagnosis and management of ies in patients with HRS‐AKI. Finally, levels of cytokines in plasma acute kidney injury in patients with cirrhosis: revised consensus recommendations of the International Club of Ascites. J Hepatol. may not reflect the actual concentrations of the same cytokines in 2015;62(4):968‐974. https://doi.org/10.1016/j.jhep.2014.12.029. tissues. However, this is a limitation that can barely be addressed in 2. Ginès P, Schrier RW. Renal failure in cirrhosis. N Engl J human studies. Med. 2009;361(13):1279‐1290. https://doi.org/10.1056/ In conclusion, patients with HRS‐AKI have marked increase in NEJMra0809139. 3. Angeli P, Bernardi M, Villanueva C, et al. EASL Clinical Practice systemic inflammatory profile compared to that of patients without Guidelines for the management of patients with decompensated AKI and hypovolaemia‐induced AKI, which appears to be indepen‐ cirrhosis. J Hepatol. 2018;69(2):406‐460. https://doi.org/10.1016/j. dent of associated ACLF, and similar to inflammation observed in key jhep.2018.03.024. systemic inflammatory diseases, such as lupus erythematosus or in‐ 4. Ginès P, Solà E, Angeli P, Wong F, Nadim MK, Kamath PS. Hepatorenal syndrome. Nat Rev Dis Prim. 2018;4(1):23. https://doi. flammatory bowel disease. Interestingly, in patients with HRS‐AKI, org/10.1038/s41572-018-0022-7. lack of AKI resolution and survival is linked to some specific cyto‐ 5. Martin PY, Ginès P, Schrier RW. Nitric oxide as a mediator of hemo‐ kines, particularly, VCAM‐1. dynamic abnormalities and sodium and water retention in cirrho‐ sis. N Engl J Med. 1998;339(8):533‐541. https://doi.org/10.1056/ NEJM199808203390807. AC K N OW L E D G E M E N T S 6. Martín‐Llahí M, Pépin M‐N, Guevara M, et al. Terlipressin and albu‐ min vs albumin in patients with cirrhosis and hepatorenal syndrome: We thank Nicki Van Berckel for the administrative support. We a randomized study. Gastroenterology. 2008;134(5):1352‐1359. also thank the faculty and nurses of the Liver Unit, and the pa‐ https://doi.org/10.1053/j.gastro.2008.02.024. tients who participated in this study and their families. We are 7. Sanyal AJ, Boyer T, Garcia‐Tsao G, et al. A randomized, prospec‐ tive, double‐blind, placebo‐controlled trial of terlipressin for type 1 indebted to the Biobank core facility of the IDIBAPS for the tech‐ hepatorenal syndrome. Gastroenterology. 2008;134(5):1360‐1368. nical help provided. https://doi.org/10.1053/j.gastro.2008.02.014. 8. Giron‐Gonzalez JA, Martinez‐Sierra C, Rodriguez‐Ramos C, et al. Implication of inflammation‐related cytokines in the natural his‐ C O N FL I C T O F I N T E R E S T tory of liver cirrhosis. Liver Int. 2004;24(5):437‐445. https://doi. org/10.1111/j.1478-3231.2004.0951.x. PG reports Investigator Research grant and Advisory Board work 9. Albillos A, Lario M, Álvarez‐Mon M. Cirrhosis‐associated im‐ from Grifols, Investigator Research grant and Advisory Board from mune dysfunction: distinctive features and clinical relevance. Gilead, Investigator Research grant from Mallinckrodt, Advisory J Hepatol. 2014;61(6):1385‐1396. https://doi.org/10.1016/j. Board for Promethera, Advisory Board for Martin‐Pharmaceuticals, jhep.2014.08.010. 10. Cervoni J‐P, Thévenot T, Weil D, et al. C‐Reactive protein grants from Ferring‐Pharmaceuticals, grants and Advisory Board predicts short‐term mortality in patients with cirrhosis. J Work from Sequana, outside the submitted work. No other authors Hepatol. 2012;56(6):1299‐1304. https://doi.org/10.1016/j. have any declared interests. jhep.2011.12.030. 11. Thabut D, Massard J, Gangloff A, et al. Model for end‐stage liver disease score and systemic inflammatory response are major AU T H O R C O N T R I B U T I O N S prognostic factors in patients with cirrhosis and acute functional renal failure. Hepatology. 2007;46(6):1872‐1882. https://doi. The authors have all contributed to this manuscript and approve the org/10.1002/hep.21920. version of this submission. CS contributed to the conception and de‐ 12. Muñoz L, Albillos A, Nieto M, et al. Mesenteric Th1 polarization and sign of this study, acquisition of data, the analysis and interpretation monocyte TNF‐α production: first steps to systemic inflammation in rats with cirrhosis. Hepatology. 2005;42(2):411‐419. https://doi. of the data and drafting the manuscript; PH, MC, RM, UC, JMM, org/10.1002/hep.20799. IG, EP, LN, GDP, AJ, NF, MMR, JF, WJ, participated in the analyses 13. Clària J, Stauber RE, Coenraad MJ, et al. Systemic inflammation in of the results, interpretation of data, and/or critical revision of the decompensated cirrhosis: characterization and role in acute‐on‐ manuscript. FT contributed to statistical analysis and interpretation chronic liver failure. Hepatology. 2016;64(4):1249‐1264. https://doi. org/10.1002/hep.28740. of data. PG and ES participated in this study concept, interpretation 14. Solé C, Solà E, Morales‐Ruiz M, et al. Characterization of inflam‐ of the data, drafting the manuscript, critical revision of the manu‐ matory response in acute‐on‐chronic liver failure and relationship script for important intellectual content, obtained funding and study with prognosis. Sci Rep. 2016;6(1):32341. https://doi.org/10.1038/ supervision. srep32341. SOLÉ et al. | 1255 15. Bernardi M, Moreau R, Angeli P, Schnabl B, Arroyo V. Mechanisms 21. Vestweber D. How leukocytes cross the vascular endothelium. of decompensation and organ failure in cirrhosis: from periph‐ Nat Rev Immunol. 2015;15(11):692‐704. https://doi.org/10.1038/ eral arterial vasodilation to systemic inflammation hypothesis. nri3908. J Hepatol. 2015;63(5):1272‐1284. https://doi.org/10.1016/j. 22. Lo Iacono O, Rincón D, Hernando A, et al. Serum levels of soluble jhep.2015.07.004. vascular cell adhesion molecule are related to hyperdynamic circula‐ 16. Arroyo V, Ginès P, Gerbes AL, et al. Definition and diagnostic cri‐ tion in patients with liver cirrhosis. Liver Int. 2008;28(8):1129‐1135. teria of refractory ascites and hepatorenal syndrome in cirrho‐ https://doi.org/10.1111/j.1478-3231.2008.01763.x. sis. Hepatology. 1996;23(1):164‐176. https://doi.org/10.1002/ 23. Vaglio A, Grayson PC, Fenaroli P, et al. Drug‐induced lupus: tra‐ hep.510230122. ditional and new concepts. Autoimmun Rev. 2018;17(9):912‐918. 17. Moreau R, Jalan R, Gines P, et al. Acute‐on‐chronic liver failure is https://doi.org/10.1016/j.autrev.2018.03.016. a distinct syndrome that develops in patients with acute decom‐ pensation of cirrhosis. Gastroenterology. 2013;144(7):1426‐1437. https://doi.org/10.1053/j.gastro.2013.02.042. 18. Fagundes C, Pépin M‐N, Guevara M, et al. Urinary neutro‐ S U P P O R T I N G I N FO R M AT I O N phil gelatinase‐associated lipocalin as biomarker in the differential diagnosis of impairment of kidney function in cir‐ Additional supporting information may be found online in the rhosis. J Hepatol. 2012;57(2):267‐273. https://doi.org/10.1016/j. Supporting Information section at the end of the article.   jhep.2012.03.015. 19. Guillén‐Gómez E, Bardají‐de‐Quixano B, Ferrer S, et al. Urinary pro‐ teome analysis identified neprilysin and VCAM as proteins involved How to cite this article: Solé C, Solà E, Huelin P, et al. in diabetic nephropathy. J Diabetes Res. 2018;2018:1‐12. https:// doi.org/10.1155/2018/6165303. Characterization of inflammatory response in hepatorenal 20. Iborra‐Egea O, Gálvez‐Montón C, Roura S, et al. Mechanisms of ac‐ syndrome: Relationship with kidney outcome and survival. tion of sacubitril/valsartan on cardiac remodeling: a systems biology Liver Int. 2019;39:1246–1255. https://doi.org/10.1111/ approach. NPJ Syst Biol Appl. 2017;3:12. https://doi.org/10.1038/ liv.14037 s41540-017-0013-4.