Early markers of reperfusion injury after liver transplantation: association with primary dysfunction

Heidelberg, Germany

Early markers of reperfusion injury after liver transplantation: association with primary dysfunction

Helge Bruns, Jan Heil, Daniel Schultze, Mohammed Al Saeedi and Peter Schemmer

Heidelberg, Germany

BACKGROUND: In patients with end-stage liver disease, liver

transplantation is the only available curative treatment. Although the outcome and quality of life in the patients have improved over the past decades, primary dys- or nonfunction (PDF/PNF) can occur. Early detection of PDF and PNF is crucial and could lead to individual therapies. This study was designed to identify early markers of reperfusion injury and PDF in liver biopsies taken during the frst hour after reperfusion.

METHODS: Biopsies from donor livers were prospectively taken as a routine during the frst hour after reperfusion. Recipient data, transaminases and outcome were routinely monitored. In total, 10 biopsy specimens taken from patients with 90-day mortality and PDF, and patients with long-term survival but without PDF were used for DNA microarrays. Markers that were signifcantly up- or down-regulated in the microarray were verifed using quantitative real-time PCR.

RESULTS: Age, indications and labMELD score were similar in both groups. Peak-transaminases during the frst week after transplantation were signifcantly different in the two groups. In total, 20 differentially regulated markers that correlated to PDF were identifed using microarray analysis and verifed with quantitative real-time PCR.

CONCLUSIONS: The markers identifed in this study could predict PDF at a very early time point and might point to interventions that ameliorate reperfusion injury and thus prevent PDF. Identifcation of patients and organs at risk might lead to individualized therapies and could ultimately improve outcome.

(Hepatobiliary Pancreat Dis Int 2015;14:246-252)

primary dysfunction; liver transplantation; predictive markers; reperfusion injury; microarray

Introduction

In patients with end-stage liver disease, there is no curative therapeutic alternative to liver transplantation.[1-3]Immunosuppressive regimens, surgical technique, and perioperative management have improved over the past few decades and liver transplantation is nowadays considered to be a safe procedure.[4]Consequently, the quality of life and long-term survival have greatly improved.[4-6]Since the 1980s, liver transplantation has been recognized as a standard therapy.[7,8]Nonetheless, the fve-year survival of the patients is still around 70%.[9]The early phase of the frst 6 months after liver transplantation is considered to be the most vulnerable time. Primary dysfunction (PDF) or primary nonfunction (PNF) occurs in 10%-20% of cases.[10,11]Some of the factors that lead to PDF and PNF are wellknown.[10,12]Because of the higher demand for organs and a large number of patients on the waiting list, organs which are prone to PDF and PNF have to be used. Ultimately, this has led to the appearance of concept of extended criteria donors, which describes organs that might have a higher risk of failure and thus will not be suitable for all recipients. Although the outcome after transplantation of these organs is comparable to standard organs, this practice is considered to generate a higher risk of PDF and PNF.[13,14]Steatosis, prolonged cold or warm ischemic time, and (even invisible) organ damage during explantation and backtable preparation are well-known to increase the risk for PDF and PNF.[15-20]In a process as complex as transplantation, multiple factors contribute to success or failure： organ-specifc, recipient-specifc,surgery-related, and immunosuppressive regimen related.[21]Moreover, preservation and perfusion solutions and techniques (e.g. machine perfusion) might have an effect on organ quality and outcome after transplantation.[22,23]Thus, no single factor or marker is likely to predict the outcome of an individual patient. It might be possible to fnd a panel of markers that help to identify patients and organs at risk after liver transplantation and it is likely that this panel needs to include factors from all aspects involved in transplantation. As far as clinical data are concerned, one promising approach is large-scale data mining.[9]Regression models have found that criteria might help to identify high-risk organs using clinical donor parameters such as age, cardiac death, split/partial grafts, race, less height, cerebrovascular accident and other causes of brain death.[24]These parameters can be used to calculate the donor risk index (DRI).[24]As far as recipients are concerned, increased labMELD scores not only predict survival of patients on the waiting list, but also correlate with increased morbidity after liver transplantation.[25]At the time of organ harvest or during backtable operation and transplantation, damage can be done to the liver, that is not apparent in the frst place and contributes to reperfusion injury and impairment of postoperative liver function.[16-20]

Most of the factors described above cumulate in a highly complex and only the partly understood process is known as reperfusion injury, the very moment, when the liver is responding to the unavoidable organ damage.[15,23,26-28]Insights in what happens during reperfusion might be the key to individualized therapies and understanding why patient outcome after transplantation can be so different. This problem has been approached from different angles; several authors and groups have already tried to identify biological markers.[11]The organ damage during reperfusion injury seems to be lasting. And patients with PDF are known to have a decreased organ survival.[29]Thus, identifcation of early markers would allow individualized therapies and preserve organ function after transplantation.

The objective of the present study was to identify candidate markers that correlate with PDF and thus may be helpful as a panel of predictive markers in the future and in better understanding of the underlying process.

Methods

Patients and sample selection

This study was approved by the local ethics committee, and informed consent was obtained. All national and institutional guidelines and regulations concerning data acquisition were followed at all times. To avoid the variation of different underlying diseases, only patients who were transplanted because of ethyltoxic liver cirrhosis were included in this study. Samples were collected prospectively and data on aspartate aminotransferase (AST), alanine aminotransferase (ALT), pre-transplant labMELD score, age, underlying diseases, and survival were collected from a database. DRI was calculated as described elsewhere.[24]Peak levels of AST during the frst postoperative week were used as surrogate parameter for liver injury and PDF. A cutoff value of AST >1500 IU/L was used as a defnition of PDF as described elsewhere.[11]Five specimens taken from patients who survived <90 days (short-term survivors) with peak AST level >1500 IU/L were randomly selected. As a control group, 5 specimens taken from patients who survived >1000 days (long-term survivors) with peak AST levels <1000 IU/L were matched for age and labMELD score.

Sample collection

Within the frst hour after reperfusion, biopsy specimens were taken from the grafts and stored in RNAlater (Qiagen, Hilden, Germany). RNA was extracted from 20 mg of specimens using RNEasy Kit (Qiagen, Hilden, Germany) according to the manufacturer's instructions, and the RNA was stored until needed.

Gene expression analysis

Expression profling was kindly performed by the microarray unit of the DKFZ Genomics and Proteomics Core Facility using the HumanHT-12 v3 whole-genome gene expression direct hybridization assay (Illumina, San Diego, CA, USA). Briefy, 250 ng mRNA was converted to cDNA and labeled using the Ambion Illumina Total Prep RNA Amplifcation Kit (Ambion, Austin, TX, USA). After mixing with hybridization reagents and incubation to the HumanHT-12 v3 BeadChips, BeadChips were washed and stained, and the Illumina BeadArray Reader was used to measure fuorescence. Using this microarray, we simultaneously tested 48804 50-mer probes biased towards the 3' end of mRNA transcripts.

Quantitative real-time PCR

The expression level of 20 genes was determined as described elsewhere.[30]Briefy, triplicates of each gene and each specimen were used with GAPDH as endogenous control. Assays were performed with a StepOne™Real-Time PCR System (Applied Biosystems, Foster City, CA, USA) using Power SYBR Green PCR Master Mix (Applied Biosystems, Warrington, UK), and relative gene quantifcation was analyzed using StepOne™ Software 2.1 (Applied Biosystems, Foster City, CA, USA).

Statistical analysis

Data analysis and description was performed using R-software.[31]For the analysis of patient-related parametric data, Student'sttest and the Mann-WhitneyUtest were performed where appropriate and a value ofP<0.05 was considered statistically signifcant. All data were expressed as median and range or mean±SEM as appropriate. For data obtained from microarray analysis, the Illumina's GenomeStudio gene expression module was used and the Bioconductor package ofRwas employed.[32,33]The list of genes with a differential expression andP<0.01 were obtained after comparison of the patient groups.

Results

Donor characteristics are shown in Table 1. No signifcant difference in patient age and labMELD score was seen between the groups. The median age of recipients was 49.5 (30-66) years and the median labMELD score was 28.5 (11-40). There was a signifcant difference in transaminases and survival. Serum AST levels were 3227 ±1414 vs 525±228 IU/L in short- and long-term survivors (P=0.04), and ALT levels were 1214±499 vs 231 ± 40 IU/L (P=0.04). Survival was signifcantly different with a median survival of 34 days (range 11-81) in theshort-term survivors and 1297 days (range 1255-1423) in the long-term survivors. At the time of this study, the long-term survivors were still alive.

Table 1.Donor and recipient characteristics

Table 2.Signifcantly differentially regulated markers in long- vs short-term survivors

Microarray analysis identifed 20 genes that were differently regulated between the two groups (Table 2). A total of 8 markers (GSTA2-1, HULC, LOC647169, HLADRB1, GSTA2-2, CYP4F2, THRSP and SLC22A18AS) were upregulated in the long-term survivors compared with the short-term survivors, and 12 markers (HLADRB6, UBD, APOA4, LOC400578, EEF1A2, TNFRSF12A, SPSB1, GDF15, MGC102966, IL1RN, DBH and RNY5) were upregulated in the short-term survivors compared with the long-term survivors. The ratios between the short- and long-term survivors were verifed using quantitative real-time PCR. The coeffcient of determination between the microarray data and the fndings from quantitative real-time PCR wasr2=0.70.

Discussion

Multiple approaches exist for the identifcation of patients at risk after liver transplantation, mostly focusing on clinical parameters and laboratory fndings. The MELD score has been validated for waiting list mortality and it seems to be correlated with post-transplant survival as well. A recent multivariate analysis[25]identifed a high MELD score as one of the most important parameters related to post-transplant mortality. Other established parameters include DRI, ischemic times and underlying liver disease.[24,34-36]For identifcation of patients at risk after liver transplantation, early allograft dysfunction can be defned as bilirubin of 10 mg/dL or INR of 1.6 at day 7 or ALT or AST of >2000 IU/L within the frst 7 days after liver transplantation and used for identifcation of patients at risk.[37]In contrast to these scores, our study focuses on the molecular correlations with PDF and reperfusion injury, attempting to identify patients at risk and fnd possible interventions. We identifed a panel of 20 markers that were differentially regulated between the short- and long-term survivors after reperfusion. These markers can be detected at a very early time-point and run ahead of classical markers of organ damage such as elevated levels of transaminases. Thus, the identifed markers could be meaningful in identifcation of patients at risk for PDF or PNF after liver transplantation. They might also serve as hints to possible interventions to avoid, suppress, or turn back organ damage. The interpretation of microarray data is a non-trivial problem. Microarrays can be used to test thousands of markers, resulting in alpha-infation due to multiple testing. Appropriate statistical methods should be used to avoid false-positive results. The stricter the statistical noise is suppressed, the higher the probability of false-negative results; thus, the true number of differentially regulated markers can be underestimated.

In differentially regulated expression, it is not clear whether markers are up-regulated in one group or downregulated in the other, unless suitable controls are introduced, i.e. samples taken before reperfusion. Nonetheless, it is worth noting the potentially protective markers upregulated in the long-term survivors. Interestingly, three genes from the glutathione S-transferase (GST)-family were identifed in our study. They might be key players or even conductors in the concert of reperfusion injury since glutathione is the main radical scavenger of the liver.[38-42]Radical oxygen species play a major role in reperfusion injury after cold or warm ischemia. Preclinical studies and clinical trials of glutathione or N-acetylcystein have already been performed.[42]The data from the preclinical studies are encouraging, but no signifcant effect could be detected in clinical trials. This might be partly due to patient selection, i.e. a subgroup of patients might be beneftted from this kind of approaches in our study.[43-48]As another important marker, THRSP-mRNA has been up-regulated in long-term survivors. THRSP is known to be expressed in the liver and adipocytes and it is related to lipid metabolism of lipogenic breast cancers.[49-51]Lipid metabolism has many roles in liver injury. There is a marked relationship between macro-steatotic liver and increased risk for reperfusion injury, and lipid droplets are related to regenerative processes.[15,23,52-54]The markers identifed in this study could serve as targets to identify patients at risk for PDF and extended liver damage caused by reperfusion injury. The recipients might beneft from pharmacological approaches to decrease reperfusion injury through radical scavengers (e.g. melatonin, NAC or sulforaphane), Kupffer cell inhibitors (e.g glycine or taurine) or from multi-drug administration to the perfusion solution or given to the donor or recipient.[15,21,23,55-61]If these markers are not donor but injuryspecifc, individualized therapies directly suppressing up- or down-regulation of these markers might lead to a better outcome after liver transplantation. Investigation of the identifed markers and their respective role in reperfusion injury might lead to individualized therapies.

According to one of the multiple defnitions of PDF, all of the short-term survivors in our study had PDF.[11]Unfortunately, it is not clear when the damage to the transplanted livers of the survivors comes to a point of no return when cell death cannot be prevented anymore. Thus, even a very early intervention, which could be introduced before classical markers of PDF and tissue necrosis such as excessively elevated transaminases can be detected, may be too late to prevent PDF. Because ofthe design of this study, whether differential regulation of the genes identifed is a response to reperfusion injury or part of this complex process remains unclear. The markers could be donor-specifc and not related to other factors associated with reperfusion injury. This could be easily detected when pre- and post-perfusion samples taken from the same organ are compared, since differential regulation of the detected markers could even be a reaction of the transplanted organ to a recipient-specifc stimulus introduced to the liver when the organ is reperfused. When the data from this study are interpreted, it has to be kept in mind that this is a retrospective analysis. Thus, we have identifed a correlation. Claiming this to be a causality that would be, as in every other retrospective analysis, a logical fallacy of thecum hoc,ergo propter hoc-type.

However, this study's focus was not to further elucidate the mechanisms of reperfusion injury, but to identify markers that correlate to injury, despite their possible contribution or involvement. Still, the panel of markers identifed in this analysis remains incomplete： organ harvest, surgery, ischemic time, recipient, and pharmacological interventions including perfusion and storage solutions and immunosuppressants have a well-known strong infuence on reperfusion injury and thus organ and patient survival.[27,28]In the authors' opinion, understanding this complex to predict meaningful interventions needs a complex approach. This can be understood as good news： fnding markers related to reperfusion injury does not imply PDF or PNF is going to happen or that this cannot be avoided with specifc interventions. Identifcation of elevated or decreased levels of the markers identifed in this study can point to high-risk patients who might beneft from organ protective approaches after transplantation. It is only partly understood why organs that recover from PDF in terms of recovered function still show decreased survival but could be the key to identifcation of interventions needed.[29]Still, it is not even clear what kind of possible pharmacological or other interventions might be benefcial to these patients. Since organ damage related to reperfusion triggers a cascade of immunological processes that are known to amplify injury itself and generate a vicious circle, these patients might have a huge beneft from individualized immunosuppressive regimens. But there are also other pharmacological interventions with promising preclinical results that target very early (donor preconditioning：before organ harvest), early (perfusion, storage, and rinse solutions, perfusion techniques; recipient preconditioning, immunoinduction), or late (immunosuppressive strategies) time-points of reperfusion injury.[15-23,55,56,58,61,62]

In conclusion, we were able to identify 20 markers that were differentially regulated in short- and longterm survivors. These markers clearly correlate to PDF and indicate reperfusion injury at a very early timepoint, although it remains unclear whether regulation of these markers is related to the donor or to the injury. Moreover, it is not clear which of these genes are involved in the injury (or have protective function) or which of these genes are only a sign of injury (or resistance to injury). Taken together, this study might help to identify organs that are at high risk and do not tolerate prolonged ischemia, and these organs or patients might beneft from improved and individualized immunosuppressive regimens.

Acknowledgements:The authors would like to thank the microarray unit of the DKFZ Genomics and Proteomics Core Facility for providing the Illumina whole-genome expression BeadChips and related services.

Contributors:BH, SD, ASM and SP participated in the research design. BH, HJ, SD, ASM and SP analyzed the data. BH and SP wrote the manuscript. All authors reviewed and contributed to the fnal manuscript. SP is the guarantor.

Funding:This study was supported by an unrestricted grant from Novartis Pharma GmbH, Nürnberg, Germany.

Ethical approval:This study was approved by the Ethics Committee of the Ruprecht-Karls-University Heidelberg Medical School (S-301/2001).

Competing interest:The author or one or more of the authors have received or will receive benefts for personal or professional use from a commercial party related directly or indirectly to the subject of this article.

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Received September 4, 2014

Accepted after revision February 23, 2015

AuthorAffliations:Department of General and Transplant Surgery, University Hospital Heidelberg, Im Neuenheimer Feld 110, Heidelberg 69120, Germany (Bruns H, Heil J, Schultze D, Al Saeedi M and Schemmer P)

Peter Schemmer, MD, Department of General and Transplant Surgery, University Hospital Heidelberg, Im Neuenheimer Feld 110, Heidelberg 69120, Germany (Tel： +49-6221/56-6110; Fax： +49-6221/56-4215; Email： Peter.Schemmer@med.uni-heidelberg.de)

© 2015, Hepatobiliary Pancreat Dis Int. All rights reserved.

10.1016/S1499-3872(15)60384-8

Published online May 22, 2015.