11 June 2019: Original Paper
Metabolomic Characterization of Human Model of Liver Rejection Identifies Aberrancies Linked to Cyclooxygenase (COX) and Nitric Oxide Synthase (NOS)
Nicholas J. Skill ABCDEFG 1*, Campbell M. Elliott CDEF 1, Brian Ceballos B 1, Romil Saxena BCD 2, Robert Pepin B 3, Lisa Bettcher B 3, Matthew Ellensberg B 3, Daniel Raftery CDE 3, Mary A. Malucio AEG 1, Burcin Ekser DF 1, Richard S. Mangus A 1, Chandrashekhar A. Kubal AE 1
DOI: 10.12659/AOT.913800
Ann Transplant 2019; 24:341-349
Abstract
BACKGROUND: Acute liver rejection (ALR), a significant complication of liver transplantation, burdens patients, healthcare payers, and the healthcare providers due to an increase in morbidity, cost, and resources. Despite clinical resolution, ALR is associated with an increased risk of graft loss. A unique protocol of delayed immunosuppression used in our institute provided a model to characterize metabolomic profiles in human ALR.
MATERIAL AND METHODS: Twenty liver allograft biopsies obtained 48 hours after liver transplantation in the absence of immunosuppression were studied. Hepatic metabolites were quantitated in these biopsies by liquid chromatography and mass spectroscopy (LC/MS). Metabolite profiles were compared among: 1) biopsies with reperfusion injury but no histological evidence of rejection (n=7), 2) biopsies with histological evidence of moderate or severe rejection (n=5), and 3) biopsies with histological evidence of mild rejection (n=8).
RESULTS: There were 133 metabolites consistently detected by LC/MS and these were prioritized using variable importance to projection (VIP) analysis, comparing moderate or severe rejection vs. no rejection or mild rejection using partial least squares discriminant statistical analysis (PLS-DA). Twenty metabolites were identified as progressively different. Further PLS-DA using these metabolites identified 3 metabolites (linoleic acid, γ-linolenic acid, and citrulline) which are associated with either cyclooxygenase or nitric oxide synthase functionality.
CONCLUSIONS: Hepatic metabolic aberrancies associated with cyclooxygenase and nitric oxide synthase function occur contemporaneous with ALR. Additional studies are required to better characterize the role of these metabolic pathways to enhance utility of the metabolomics approach in diagnosis and outcomes of ALR.
Keywords: Graft Rejection, Liver Transplantation, Metabolomics, Nitric Oxide Synthase, Prostaglandin-Endoperoxide Synthases, End stage liver disease, Liver
Background
Acute liver rejection (ALR) following liver transplantation occurs in approximately 4–20% of patients [1,2]. According to the United Network for Organ Sharing (UNOS), in 2017 the number of liver transplants performed in the USA was 8082, representing an increase of 24.5% since 2016. Currently, the number of patients waiting for liver transplant is approximately 13 914 and the average waiting time for liver transplant is 511 days. Therefore, although the incidence of acute liver rejection is low, the high volume of transplants coupled with increased frequency and limited donors encourages the maximization of graft survival by addressing ALR, a major cause of graft damage.
This study aimed to characterize metabolomic aberrancies in a human model of liver rejection to guide future studies aimed at addressing graft damage congruent with ALR. Between 2008 and 2012, the standard immunosuppression protocol for patients receiving liver transplants at Indiana University Hospital was begun 2 days following transplant and prior to collection of liver biopsy at the time of fascial closure. The hypothesis was that a delay in immunosuppression would induce tolerance [3]. This immunosuppression delay protocol coupled with the collection of a fascial closure biopsy provides an opportunity to characterize ALR consequences in a human model of early liver rejection, specifically to utilize a targeted liquid chromatography/mass spectrometry (LC/MS) platform for metabolomics to profile and quantify hepatic metabolites in order to identify metabolic signatures associated with ALR.
Metabolomics is the study of a large number of small molecule metabolites in biofluids and tissue to identify biomarkers associated with altered metabolic pathways. As metabolites are modulated by protein and enzymatic function, they reflect many of the alterations caused by disease or other biological stresses. Metabolites are exquisitely sensitive to different biological states and therefore represent a promising approach to identify biopathology contemporaneous with rejection [4–6]. Several analytical techniques such as nuclear magnetic resonance (NMR), LC-MS, and gas chromatography-mass spectrometry (GC-MS) have been used to detect metabolic changes [7]. Several studies have used a variety of analytical techniques to elucidate aberrant pathways associated with cancer [8]. While a few of these studies have used animal models [9–11], the majority have focused on humans [4,10,12–22] using NMR [4,16], LC-MS [12,13,15,17,21,22], and GC-MS [13–15,18,19], or HPLC methods [20]. These studies have reported alterations in numerous metabolic pathways, including glycolysis, amino acid, fatty acid, and bile acid metabolism. While there are few reports that have focused exclusively on altered metabolic pathways associated with liver rejection, there have been studies relating to rejection-associated events. Previous reports have documented metabolic pathways and individual metabolites that modulate immune cell function and immune responses [23]. For example, modulation of T cells has been well documented in conjunction with rejection, as has the role of metabolism and nutrient availability upon T cell activation and function [5,24]. Moreover, activation of T cells requires metabolic reprogramming in order to increase glycolytic flux, lactate, lipids, proteins, nucleic acid, and carbohydrates [25]. These changes in metabolic profiles also direct signaling. For example, increased intracellular leucine metabolism controls mammalian target of rapamycin (mTOR) signaling required to induce Th1, Th2, and Th17 CD4(+) T effector cell differentiation [26]. Therefore, there is a need to better understand changes in hepatic biochemical pathways associated with rejection, and metabolomics is an established analytical modality available to identify key compounds. Focusing on hepatic tissue prior to immunosuppression in patients provides a unique opportunity to improve our understanding of graft damage and loss.
Material and Methods
PATIENTS AND PROCEDURES:
In all liver transplants, the muscle layer was left open and skin was closed immediately after transplantation to prevent compartment syndrome. All patients were taken back to the operating room for delayed fascial closure on the 2nd post-transplant day [28]. During fascial closure, a second allograft biopsy was performed. A part of the second liver allograft biopsy was frozen for future use. Patients did not receive any immunosuppression prior to fascial closure [3]. For the purpose of this study, the day 2 biopsies were divided in to 3 groups (n=5–8 per group): Group 1 (control), patients with no evidence of rejection; Group 2, patients with histological evidence of mild rejection; and Group 3, patients with evidence of moderate or severe rejection. To evaluate the metabolic changes associated with liver rejection, we performed LC-MS analysis, targeting 216 metabolites in liver biopsies taken 2 days after liver transplantation.
IMMUNOSUPPRESSION PROTOCOL:
The induction immunosuppression consisted of 3 doses of 2 mg/kg rabbit anti-thymocyte globulin (rATG) every 48 hours starting on post-transplant day 2 along with a single dose of 1.5 mg/m2 BSA of rituximab on post-transplant day 3. Premedication for rATG was given immediately before its administration in the form of solumedrol [500 (first dose), 250 (second dose), and 120 mg (third dose)], acetaminophen (650 mg), and diphenhydramine (25 mg). Maintenance immunosuppression was also initiated on post-transplant day 2 in the form of tacrolimus monotherapy, although some recipients received additional mycophenolate mofetil. The goal trough levels for tacrolimus were 7 to 10 ng/mL in the first 3 months and 6 to 8 ng/mL thereafter [3].
LC/MS:
Day 2 liver allograft biopsies were frozen in liquid nitrogen and stored at −86°C. Tissue was transported on dry ice to the Northwest Metabolomics Research Center (NW-MRC) at the University of Washington for analysis. Briefly, targeted LC/MS/MS was performed according to methods developed at the University of Washington Metabolomic Research Center as per Zhu et al. [29] Targeted aqueous metabolite profiling analysis was performed using an Agilent 1260/AB-Sciex 5500 Qtrap Liquid Chromatography-Mass spectroscopy/mass spectroscopy (LC-MS/MS) instrument and standard operating procedures we developed previously [29]. The LC-MS/MS analysis is based on hydrophilic interaction chromatography (HILIC), and targets 216 metabolites located in more than 35 different metabolic pathways. This system provides detailed information on metabolites involved in glycolysis, tricarboxylic acid cycle (TCA), and pentose phosphate shunt, as well as amino acid, fatty acid, and nucleic acid metabolism, and other pathways. Twenty-six isotope-labeled internal standards were included to monitor sample preparation steps and system performance, as well as to provide absolute quantitation of a number of amino and organic acids.
DATA ANALYSIS FOR METABOLOMICS:
The intensity of tissue peaks in each data set were normalized to tissue weight. Statistical analysis was performed using XLSTAT software. Each data set was mean-centered before the analysis. Univariate analysis of the individual metabolites was performed using the
Results
HISTOLOGICAL EVIDENCE OF REJECTION:
Of the 60 patients recruited and transplanted, routine pathology reports described histological evidence of rejection in 14 patients (23%). Biopsies were stratified based on these reports into 3 groups: 1) no histological evidence of rejection, 2) evidence of mild rejection, and 3) patients with evidence of moderate or severe rejection. Seven samples from each group were selected for pathology review and metabolomic analysis. A pathologist (RS) reviewed all 21 fascial closure liver biopsies taken 2 days post-transplant. Her analysis found 5 biopsies had unequivocal evidence of moderate or severe rejection (endothelialitis, cell infiltration, or bile duct injury). Seven biopsies had no evidence of rejection but had reperfusion damage. One sample was indeterminable, did not reach criteria for rejection, and had no reperfusion injury. The remaining 8 biopsies had histological evidence of mild rejection. The 1 biopsy that was indeterminable was not included in either rejection or control groups and data were not included in the metabolomic analysis.
The biopsies in the rejection group were characterized by the presence of a mixed inflammatory infiltrate in portal tracts that comprised variable combinations of lymphocytes, eosinophils, and neutrophils. Endothelialitis and bile duct damage were present in varying degrees of severity. Control biopsies showed features of reperfusion damage that included variable combinations and severity of portal edema, peribiliary neutrophils, perivenular hepatocellular necrosis, and presence of lobular neutrophils. One biopsy showed mild macro-vesicular steatosis with necrosis and neutrophils. The biopsies were characterized into 3 groups for the purpose of metabolomic analysis: Group 1 was reperfusion injury only (N=7), Group 2 was categorical histological evidence of moderate or severe rejection (N=5), and Group 3 was histological evidence of mild rejection (N=8).
LC/MS-BASED METABOLOMICS:
The LC-MS/MS method was optimized to target a total of 216 metabolites in the liver biopsy samples. However, after deleting metabolites that were not detected, metabolites below the signal to noise cutoff, and metabolites inconsistently detected in the samples, 133 metabolites were quantified. We assessed and compared differences in metabolites between 1) biopsies with mild rejection or with moderate or severe rejection when compared to tissues with reperfusion injury and 2) biopsies with mild rejection when compared to biopsies with moderate or severe rejection. Each metabolite was ranked by its variable importance in the projection (VIP) score via partial least squares- discriminative analysis (PLS-DA) using XLSTAT Biomed software (Figure 1). Twenty-one metabolites with VIP scores above 1.5 were included in a secondary PLS-DA analysis comparing no rejection (reperfusion injury) to both moderate to severe rejection (Figure 2A) and mild rejection (Figure 2B). Of these metabolites, linoleic acid, γ-linolenic acid, and citrulline emerged as providing the strongest predictive model of rejection (Figure 2). The differences between these metabolites in rejection (mild, moderate, and severe) and control biopsies were examined individually (Figure 3). They were then used to construct a final sample model by PLS-DA. Cross-validation of this model was then used to estimate how closely the 3 metabolites, taken as a group, correlate with the biopsy histology report from the pathologist (RS) (Figure 4). The resulting aggregate indicates that, taken together, the 3 metabolites can accurately identify the rejection status of each patient in our sample group, and that this is likely to be the case for independent samples.
Discussion
This study represents a unique model of human liver rejection due to the unique immunosuppression and surgical protocol that was followed. There are no previously published data on human liver rejection in this setting. In the absence of immunosuppression, changes occurring in the liver biopsies in the setting of cellular rejection are novel and intriguing. Using 2-day protocol liver biopsies, targeted LC/MS-based metabolomics analysis, and PLS-DA, we identified 3 aberrant metabolites (linolenic acid, γ-linolenic acid, and citrulline) contemporaneous with liver rejection.
LC/MS/MS-based metabolomics provides broad-based coverage of the important small molecule metabolites in biofluids and tissue to allow the identification of altered metabolic pathways. As metabolites are modulated by protein function, they reflect many of the alterations caused by disease or other biological stresses [4–6]. Analysis using PLS-DA is appropriate when large numbers of potentially correlated variables must be analyzed. It is especially well suited to cases where the number of variables exceeds the number of samples, which would otherwise produce overfitting using conventional regression models. We used VIP scores, which represent the effect of a particular variable on the PLS-DA model, to eliminate non-predictive variables from our dataset, and to identify the variables with the highest degree of predictive power at the level of individual patients. This analysis revealed 3 metabolites: linoleic acid, γ linolenic acid, and citrulline. Linoleic acid and γ-linolenic acid are associated with cyclooxygenase (COX) pathways, while citrulline is associated with nitric oxide synthase (NOS) pathways.
Linoleic acid is an octadecadeinoic fatty acid and a precursor for arachidonic acid, which is a substrate for COX enzymes and subsequent biosynthesis of vasoactive molecules. Changes in arachidonic acid are linked to numerous pathologies of the liver, including portal hypertension and liver cirrhosis [30,31]. Linoleic acid regulates the COX-2/VEGF/MAP kinase pathway [32] and endothelial vasodilatory function [33]. Studies have shown that COX-2 was significantly increased in a rodent model of liver rejection [34]. However, whether increased COX is beneficial or not is controversial. Some studies have shown that increased COX-2 is protective [35], while others have found that inhibition of COX-2 increases graft survival in animal models [34,36]. Moreover, linoleic acid is also associated with pathologies independent of COX, as it is synthesized from phosphatidylcholine via phospholipase A2 or phospholipase A1. Aberrancies of phospholipase A2 are associated with Parkinson disease, peroxisomal beta-oxidation enzyme deficiency, neurodegeneration with brain iron accumulation, and peroxisomal acyl-CoA oxidase deficiency [37,39].
The second metabolite identified by PLS-DA was γ-linolenic acid, which is an all-cis-6,9,12-octadecatrienoic acid designated as 18: 3 and is synthesized from linoleic acid by introduction of a (third) double bond at the delta 6 position under the catalytic influence of delta-6-desaturase enzyme. This step is believed to be the rate-limiting stage in the metabolic pathway. Aging, obesity, diabetes, high alcohol intake, stress-related hormones, and viral infections are known to reduce conversion of linoleic acid to γ-linolenic acid [40–43]. γ-linolenic acid is known to inhibit angiogenesis, partly via the decrease in the expression of VE-cadherin and beta-catenin [44], potentially due to the elimination of the precursor, -linoleic acid. Hepatocyte expression of insulin growth factor-I, insulin growth factor-II, growth hormone receptor, insulin receptor, Insulin growth factor binding protein-3, and Insulin growth factor binding protein-4 mRNAs are all upregulated by linoleic acid [45]. Conversion of linoleic acid to γ-linolenic acid is known to be beneficial for human health [46]. Linolenic acid attenuates endothelial apoptosis
The third metabolite identified by PLS-DA was citrulline, a key intermediate in the urea cycle produced via the metabolism of ornithine and carbamoyl phosphate. Moreover, citrulline is a by-product of the enzymatic production of nitric oxide from the amino acid arginine. As citrulline is a part of the urea cycle and urea is a marker of liver failure, it is not unexpected that rejection is associated with increased citrulline. However, urea levels were not significantly higher in patients with rejection. Because citrulline is involved in many biological pathways, it is impossible to accurately hypothesize the pathobiology, physiological, and biochemical milieu associated with changes to hepatic linoleic acid, γ-linoleic acid and citrulline based on biopsies. However, the fact that they are connected to important hepatic perfusion regulators suggests that changes impart/reflect a response to tissue stress, damage, and/or acute graft rejection. Arginine is the predominate substrate for the production of nitric oxide (NO), a well-documented vasodilator associated with liver perfusion and portal hypertension [51,52]. The role of NO in liver perfusion is well documented and focuses on sinusoidal stellate cell control of sinusoidal dilation and thus an increase in resistance to portal venous blood flow. A reduction in citrulline might be indicative of a modulation of NO biosynthesis. Reduced citrulline could be reflective of a reduction of NOS activity, as citrulline is the biproduct of the conversion of arginine to NO. In contrast, as citrulline is also the substrate, a reduction could be indicative of an increase in NOS activity. What we do know is that a change in NO within the liver will modulate perfusion and affect ischemia and hypoxia and impart an additional stress to the liver. Moreover, endothelial NOS (eNOS) is also known to “uncouple” when co-factors are absent, leading to the formation of oxygen free radicals [53]. The conversion of arginine to NO and citrulline is a 2-step process involving N-hydroxy-l-arginine as an intermediate; therefore, uncoupling of endothelial NOS could result in a reduction in citrulline.
The data do not suggest that either linolenic acid or citrulline should replace current markers of acute liver rejection. LC-MS/MS is unlikely to be quicker or cheaper than histology and liver functional tests. Nevertheless, there is utility in investigating linolenic acid and citrulline, as both have been shown to be markers of interest in other pathologies. For example, the ratio of linolenic acid to deoxycholic acid species is a potential biomarker for metabolic abnormalities in obesity [54] and hepatic steatosis [55]. Moreover, the circulating citrulline concentration is a biomarker of intestinal functionality [56,57]. What the data may reveal is hepatic response to acute liver rejection by the modulation of vasodilators to maintain liver perfusion. However, we are cognizant that differences in metabolomics signatures between control livers and livers with rejection could be independent of rejection. It is possible that these differences are linked to other aspects of liver disease. For example, sarcopenia, which is associated with modulated metabolism, poorer outcomes, and changes in the levels of citrulline and linoleic acid, occurs in patients with liver disease [58–61]. A preliminary analysis of sarcopenia in the patients within this study, based on measurement of the psoas muscle at the C3, as previously described [62,63], was performed and identified 3 patients with sarcopenia. Two patients within the early rejection group had sarcopenia. One patient with no evidence of rejection was identified with sarcopenia. Because the frequency of overlapping sarcopenia within the 3 cohorts is sporadic, it is difficult to determine if sarcopenia is an independent variable in hepatic metabolites associated with hepatic response to rejection.
Additional research is required to further elucidate our findings and to better understand any connection among metabolic changes, acute liver rejection, and graft survival. Further research is likely to focus on metabolomic quantification post-transplant in rodent models of liver rejection [64]. This is because rejection rates observed in clinical programs are very low; therefore, to expand this project using patient samples only would be prohibitive. Moreover, the delayed immunosuppression protocol is controversial and delayed immunosuppression and 2-day protocol biopsies are not the standard of care at our institute at present.
Finally, the immunosuppression protocol deserves further explanation. The premise behind delayed introduction of immunosuppression was to allow immune activation of recipient lymphocytes in the allograft. It was thought that the potent rATG would then lead to apoptosis and death of recipient lymphocytes within the graft, allowing operational tolerance in the long term. Although this approach permits a degree of rejection in the allograft, this is a desired effect and has no adverse effects in the long term, which was demonstrated in our larger study involving 1000 patients [3]. Based on this large-sample experience, we do not believe that deaths that occurred in this study cohort were due to the delayed immunosuppression.
Conclusions
Contemporaneous with acute liver rejection, increases in linoleic acid and γ-linolenic acid are observed alongside a decrease in citrulline. These metabolites are connected to pathways that regulate liver perfusion.
References
1. Au KP, Chan SC, Chok KS, Clinical factors affecting rejection rates in liver transplantation: Hepatobiliary Pancreat Dis Int, 2015; 14(4); 367-73, pmid: 26256080
2. Neil DA, Hubscher SG, Current views on rejection pathology in liver transplantation: Transpl Int, 2010; 23(10); 971-83, pmid: 20723179
3. Mangus RS, Fridell JA, Vianna RM, Immunosuppression induction with rabbit anti-thymocyte globulin with or without rituximab in 1000 liver transplant patients with long-term follow-up: Liver Transpl, 2012; 18(7); 786-95, pmid: 22237953
4. Gao H, Lu Q, Liu X, Application of 1H NMR-based metabonomics in the study of metabolic profiling of human hepatocellular carcinoma and liver cirrhosis: Cancer Sci, 2009; 100(4); 782-85, pmid: 19469021
5. Mayr M, Metabolomics: Ready for the prime time?: Circ Cardiovasc Genet, 2008; 1(1); 58-65, pmid: 20031543
6. Zhang J, Liu L, Wei S, Metabolomics study of esophageal adenocarcinoma: J Thorac Cardiovasc Surg, 2011; 141(2); 469-75, pmid: 20880550
7. Gowda GA, Zhang S, Gu H, Metabolomics-based methods for early disease diagnostics: Expert Rev Mol Diagn, 2008; 8(5); 617-33, pmid: 18785810
8. Bowers J, Hughes E, Skill N, Detection of hepatocellular carcinoma in hepatitis C patients: biomarker discovery by LC-MS: J Chromatogr B Analyt Technol Biomed Life Sci, 2014; 966; 154-62
9. Li S, Liu H, Jin Y, Metabolomics study of alcohol-induced liver injury and hepatocellular carcinoma xenografts in mice: J Chromatogr B Analyt Technol Biomed Life Sci, 2011; 879(24); 2369-75
10. Tan Y, Yin P, Tang L, Metabolomics study of stepwise hepatocarcinogenesis from the model rats to patients: potential biomarkers effective for small hepatocellular carcinoma diagnosis: Mol Cell Proteomics, 2012; 11(2); M111.010694
11. Wang J, Zhang S, Li Z, (1)H-NMR-based metabolomics of tumor tissue for the metabolic characterization of rat hepatocellular carcinoma formation and metastasis: Tumour Biol, 2011; 32(1); 223-31, pmid: 20890798
12. Chen F, Xue J, Zhou L, Identification of serum biomarkers of hepatocarcinoma through liquid chromatography/mass spectrometry-based metabonomic method: Anal Bioanal Chem, 2011; 401(6); 1899-904, pmid: 21833635
13. Chen T, Xie G, Wang X, Serum and urine metabolite profiling reveals potential biomarkers of human hepatocellular carcinoma: Mol Cell Proteomics, 2011; 10(7); M110.004945
14. Lin X, Zhang Y, Ye G, Classification and differential metabolite discovery of liver diseases based on plasma metabolic profiling and support vector machines: J Sep Sci, 2011; 34(21); 3029-36, pmid: 21919198
15. Patterson AD, Maurhofer O, Beyoglu D, Aberrant lipid metabolism in hepatocellular carcinoma revealed by plasma metabolomics and lipid profiling: Cancer Res, 2011; 71(21); 6590-600, pmid: 21900402
16. Shariff MI, Gomaa AI, Cox IJ, Urinary metabolic biomarkers of hepatocellular carcinoma in an Egyptian population: A validation study: J Proteome Res, 2011; 10(4); 1828-36, pmid: 21275434
17. Wang B, Chen D, Chen Y, Metabonomic profiles discriminate hepatocellular carcinoma from liver cirrhosis by ultraperformance liquid chromatography-mass spectrometry: J Proteome Res, 2012; 11(2); 1217-27, pmid: 22200553
18. Wu H, Xue R, Dong L, Metabolomic profiling of human urine in hepatocellular carcinoma patients using gas chromatography/mass spectrometry: Anal Chim Acta, 2009; 648(1); 98-104, pmid: 19616694
19. Xue R, Lin Z, Deng C, A serum metabolomic investigation on hepatocellular carcinoma patients by chemical derivatization followed by gas chromatography/mass spectrometry: Rapid Commun Mass Spectrom, 2008; 22(19); 3061-68, pmid: 18767022
20. Yang J, Xu G, Zheng Y, Diagnosis of liver cancer using HPLC-based metabonomics avoiding false-positive result from hepatitis and hepatocirrhosis diseases: J Chromatogr B Analyt Technol Biomed Life Sci, 2004; 813(1–2); 59-65
21. Yin P, Wan D, Zhao C, A metabonomic study of hepatitis B-induced liver cirrhosis and hepatocellular carcinoma by using RP-LC and HILIC coupled with mass spectrometry: Mol Biosyst, 2009; 5(8); 868-76, pmid: 19603122
22. Zhou L, Wang Q, Yin P, Serum metabolomics reveals the deregulation of fatty acids metabolism in hepatocellular carcinoma and chronic liver diseases: Anal Bioanal Chem, 2012; 403(1); 203-13, pmid: 22349331
23. Everts B, Metabolomics in immunology research: Methods Mol Biol, 2018; 1730; 29-42, pmid: 29363063
24. Baumann AK, Schlue J, Noyan F, Preferential accumulation of T helper cells but not cytotoxic T cells characterizes benign subclinical rejection of human liver allografts: Liver Transpl, 2016; 22(7); 943-55, pmid: 26929119
25. Yang Z, Matteson EL, Goronzy JJ, Weyand CM, T-cell metabolism in autoimmune disease: Arthritis Res Ther, 2015; 17; 29, pmid: 25890351
26. Powell JD, Delgoffe GM, The mammalian target of rapamycin: Linking T cell differentiation, function, and metabolism: Immunity, 2010; 33(3); 301-11, pmid: 20870173
27. , Terminology for hepatic allograft rejection. International Working Party: Hepatology, 1995; 22(2); 648-54, pmid: 7635435
28. Jernigan TW, Fabian TC, Croce MA, Staged management of giant abdominal wall defects: acute and long-term results: Ann Surg, 2003; 238(3); 349-55, pmid: 14501501 discussion 355–57
29. Zhu J, Djukovic D, Deng L, Colorectal cancer detection using targeted serum metabolic profiling: J Proteome Res, 2014; 13(9); 4120-30, pmid: 25126899
30. Skill NJ, Theodorakis NG, Wang YN, Role of cyclooxygenase isoforms in prostacyclin biosynthesis and murine prehepatic portal hypertension: Am J Physiol Gastrointest Liver Physiol, 2008; 295(5); G953-64, pmid: 18772366
31. Jeong SW, Jang JY, Lee SH, Increased expression of cyclooxygenase-2 is associated with the progression to cirrhosis: Korean J Intern Med, 2010; 25(4); 364-71, pmid: 21179273
32. Deshpande R, Mansara P, Kaul-Ghanekar R, Alpha-linolenic acid regulates Cox2/VEGF/MAP kinase pathway and decreases the expression of HPV oncoproteins E6/E7 through restoration of p53 and Rb expression in human cervical cancer cell lines: Tumour Biol, 2016; 37(3); 3295-305, pmid: 26440049
33. Steer P, Vessby B, Lind L, Endothelial vasodilatory function is related to the proportions of saturated fatty acids and alpha-linolenic acid in young men, but not in women: Eur J Clin Invest, 2003; 33(5); 390-96, pmid: 12713452
34. Martelius TJ, Wolff H, Bruggeman CA, Induction of cyclo-oxygenase-2 by acute liver allograft rejection and cytomegalovirus infection in the rat: Transpl Int, 2002; 15(12); 610-14, pmid: 12478407
35. Motino O, Frances DE, Casanova N, Protective role of hepatocyte cyclooxygenase-2 expression against liver ischemia-reperfusion injury in mice: Hepatology, 2018 [Epub ahead of print]
36. Ma N, Szabolcs MJ, Sun J, The effect of selective inhibition of cyclooxygenase (COX)-2 on acute cardiac allograft rejection: Transplantation, 2002; 74(11); 1528-34, pmid: 12490785
37. Cicchetti F, Drouin-Ouellet J, Gross RE, Environmental toxins and Parkinson’s disease: What have we learned from pesticide-induced animal models?: Trends Pharmacol Sci, 2009; 30(9); 475-83, pmid: 19729209
38. Hague SM, Klaffke S, Bandmann O, Neurodegenerative disorders: Parkinson’s disease and Huntington’s disease: J Neurol Neurosurg Psychiatry, 2005; 76(8); 1058-63, pmid: 16024878
39. Pardo LM, van Duijn CM, In search of genes involved in neurodegenerative disorders: Mutat Res, 2005; 592(1–2); 89-101, pmid: 16009383
40. Horrobin DF, Loss of delta-6-desaturase activity as a key factor in aging: Med Hypotheses, 1981; 7(9); 1211-20, pmid: 6270521
41. Kroger J, Schulze MB, Recent insights into the relation of Delta5 desaturase and Delta6 desaturase activity to the development of type 2 diabetes: Curr Opin Lipidol, 2012; 23(1); 4-10, pmid: 22123669
42. Abel S, De Kock M, van Schalkwyk DJ, Altered lipid profile, oxidative status and hepatitis B virus interactions in human hepatocellular carcinoma: Prostaglandins Leukot Essent Fatty Acids, 2009; 81(5–6); 391-99, pmid: 19782547
43. Araya J, Rodrigo R, Pettinelli P, Decreased liver fatty acid delta-6 and delta-5 desaturase activity in obese patients: Obesity (Silver Spring), 2010; 18(7); 1460-63, pmid: 19875987
44. Cai J, Jiang WG, Mansel RE, Inhibition of the expression of VE-cadherin/catenin complex by gamma linolenic acid in human vascular endothelial cells, and its impact on angiogenesis: Biochem Biophys Res Commun, 1999; 258(1); 113-18, pmid: 10222244
45. Fang XL, Shu G, Zhang ZQ, Roles of alpha-linolenic acid on IGF-I secretion and GH/IGF system gene expression in porcine primary hepatocytes: Mol Biol Rep, 2012; 39(12); 10987-96, pmid: 23053988
46. Barcelo-Coblijn G, Murphy EJ, Alpha-linolenic acid and its conversion to longer chain n-3 fatty acids: Benefits for human health and a role in maintaining tissue n-3 fatty acid levels: Prog Lipid Res, 2009; 48(6); 355-74, pmid: 19619583
47. Zhang W, Wang R, Han SF, Alpha-linolenic acid attenuates high glucose-induced apoptosis in cultured human umbilical vein endothelial cells via PI3K/Akt/eNOS pathway: Nutrition, 2007; 23(10); 762-70, pmid: 17716867
48. Lewin M, Samuel S, Merkel J, Bickler P, Varespladib (LY315920) appears to be a potent, broad-spectrum, inhibitor of snake venom phospholipase A2 and a possible pre-referral treatment for envenomation: Toxins (Basel), 2016; 8(9) pii: E248
49. Thotala D, Craft JM, Ferraro DJ, Cytosolic phospholipaseA2 inhibition with PLA-695 radiosensitizes tumors in lung cancer animal models: PLoS One, 2013; 8(7); e69688, pmid: 23894523
50. Lee KL, Foley MA, Chen L, Discovery of Ecopladib, an indole inhibitor of cytosolic phospholipase A2alpha: J Med Chem, 2007; 50(6); 1380-400, pmid: 17305324
51. Theodorakis NG, Wang YN, Skill NJ, The role of nitric oxide synthase isoforms in extrahepatic portal hypertension: Studies in gene-knockout mice: Gastroenterology, 2003; 124(5); 1500-8, pmid: 12730888
52. Theodorakis NG, Wang YN, Wu JM, Role of endothelial nitric oxide synthase in the development of portal hypertension in the carbon tetrachloride-induced liver fibrosis model: Am J Physiol Gastrointest Liver Physiol, 2009; 297(4); G792-99, pmid: 19628654
53. Li H, Forstermann U, Pharmacological prevention of eNOS uncoupling: Curr Pharm Des, 2014; 20(22); 3595-606, pmid: 24180386
54. Lei S, Huang F, Zhao A, The ratio of dihomo-gamma-linolenic acid to deoxycholic acid species is a potential biomarker for the metabolic abnormalities in obesity: FASEB J, 2017; 31(9); 3904-12, pmid: 28490483
55. Matsuda M, Kawamoto T, Tamura R, Predictive value of serum dihomo-gamma-linolenic acid level and estimated Delta-5 desaturase activity in patients with hepatic steatosis: Obes Res Clin Pract, 2017; 11(1); 34-43, pmid: 26964726
56. Fragkos KC, Forbes A, Citrulline as a marker of intestinal function and absorption in clinical settings: A systematic review and meta-analysis: United European Gastroenterol J, 2018; 6(2); 181-91
57. Crenn P, Coudray-Lucas C, Thuillier F, Postabsorptive plasma citrulline concentration is a marker of absorptive enterocyte mass and intestinal failure in humans: Gastroenterology, 2000; 119(6); 1496-505, pmid: 11113071
58. Meeks AC, Madill J, Sarcopenia in liver transplantation: A review: Clin Nutr ESPEN, 2017; 22; 76-80, pmid: 29415839
59. Ogawa SBody weight and bone/calcium metabolism. Sarcopenia and its relationship with bone and calcium metabolism: Clin Calcium, 2018; 28(7); 907-12, pmid: 29950542 [in Japanese]
60. Barillaro C, Liperoti R, Martone AM, The new metabolic treatments for sarcopenia: Aging Clin Exp Res, 2013; 25(2); 119-27, pmid: 23739896
61. Ter Borg S, de Groot LC, Mijnarends DM, Differences in nutrient intake and biochemical nutrient status between sarcopenic and nonsarcopenic older adults-results from the Maastricht Sarcopenia Study: J Am Med Dir Assoc, 2016; 17(5); 393-401, pmid: 26825685
62. Gu DH, Kim MY, Seo YS, Clinical usefulness of psoas muscle thickness for the diagnosis of sarcopenia in patients with liver cirrhosis: Clin Mol Hepatol, 2018; 24(3); 319-30, pmid: 29706058
63. Mangus RS, Bush WJ, Miller C, Severe sarcopenia and increased fat stores in pediatric patients with liver, kidney, or intestine failure: J Pediatr Gastroenterol Nutr, 2017; 65(5); 579-83, pmid: 28604513
64. Kaizu T, Ikeda A, Nakao A, Donor graft adenoviral iNOS gene transfer ameliorates rat liver transplant preservation injury and improves survival: Hepatology, 2006; 43(3); 464-73, pmid: 16496305
11 June 2019: Original Paper
Metabolomic Characterization of Human Model of Liver Rejection Identifies Aberrancies Linked to Cyclooxygenase (COX) and Nitric Oxide Synthase (NOS)
Nicholas J. Skill ABCDEFG 1*, Campbell M. Elliott CDEF 1, Brian Ceballos B 1, Romil Saxena BCD 2, Robert Pepin B 3, Lisa Bettcher B 3, Matthew Ellensberg B 3, Daniel Raftery CDE 3, Mary A. Malucio AEG 1, Burcin Ekser DF 1, Richard S. Mangus A 1, Chandrashekhar A. Kubal AE 1
DOI: 10.12659/AOT.913800
Ann Transplant 2019; 24:341-349
Abstract
BACKGROUND: Acute liver rejection (ALR), a significant complication of liver transplantation, burdens patients, healthcare payers, and the healthcare providers due to an increase in morbidity, cost, and resources. Despite clinical resolution, ALR is associated with an increased risk of graft loss. A unique protocol of delayed immunosuppression used in our institute provided a model to characterize metabolomic profiles in human ALR.
MATERIAL AND METHODS: Twenty liver allograft biopsies obtained 48 hours after liver transplantation in the absence of immunosuppression were studied. Hepatic metabolites were quantitated in these biopsies by liquid chromatography and mass spectroscopy (LC/MS). Metabolite profiles were compared among: 1) biopsies with reperfusion injury but no histological evidence of rejection (n=7), 2) biopsies with histological evidence of moderate or severe rejection (n=5), and 3) biopsies with histological evidence of mild rejection (n=8).
RESULTS: There were 133 metabolites consistently detected by LC/MS and these were prioritized using variable importance to projection (VIP) analysis, comparing moderate or severe rejection vs. no rejection or mild rejection using partial least squares discriminant statistical analysis (PLS-DA). Twenty metabolites were identified as progressively different. Further PLS-DA using these metabolites identified 3 metabolites (linoleic acid, γ-linolenic acid, and citrulline) which are associated with either cyclooxygenase or nitric oxide synthase functionality.
CONCLUSIONS: Hepatic metabolic aberrancies associated with cyclooxygenase and nitric oxide synthase function occur contemporaneous with ALR. Additional studies are required to better characterize the role of these metabolic pathways to enhance utility of the metabolomics approach in diagnosis and outcomes of ALR.
Keywords: Graft Rejection, Liver Transplantation, Metabolomics, Nitric Oxide Synthase, Prostaglandin-Endoperoxide Synthases, End stage liver disease, Liver
Background
Acute liver rejection (ALR) following liver transplantation occurs in approximately 4–20% of patients [1,2]. According to the United Network for Organ Sharing (UNOS), in 2017 the number of liver transplants performed in the USA was 8082, representing an increase of 24.5% since 2016. Currently, the number of patients waiting for liver transplant is approximately 13 914 and the average waiting time for liver transplant is 511 days. Therefore, although the incidence of acute liver rejection is low, the high volume of transplants coupled with increased frequency and limited donors encourages the maximization of graft survival by addressing ALR, a major cause of graft damage.
This study aimed to characterize metabolomic aberrancies in a human model of liver rejection to guide future studies aimed at addressing graft damage congruent with ALR. Between 2008 and 2012, the standard immunosuppression protocol for patients receiving liver transplants at Indiana University Hospital was begun 2 days following transplant and prior to collection of liver biopsy at the time of fascial closure. The hypothesis was that a delay in immunosuppression would induce tolerance [3]. This immunosuppression delay protocol coupled with the collection of a fascial closure biopsy provides an opportunity to characterize ALR consequences in a human model of early liver rejection, specifically to utilize a targeted liquid chromatography/mass spectrometry (LC/MS) platform for metabolomics to profile and quantify hepatic metabolites in order to identify metabolic signatures associated with ALR.
Metabolomics is the study of a large number of small molecule metabolites in biofluids and tissue to identify biomarkers associated with altered metabolic pathways. As metabolites are modulated by protein and enzymatic function, they reflect many of the alterations caused by disease or other biological stresses. Metabolites are exquisitely sensitive to different biological states and therefore represent a promising approach to identify biopathology contemporaneous with rejection [4–6]. Several analytical techniques such as nuclear magnetic resonance (NMR), LC-MS, and gas chromatography-mass spectrometry (GC-MS) have been used to detect metabolic changes [7]. Several studies have used a variety of analytical techniques to elucidate aberrant pathways associated with cancer [8]. While a few of these studies have used animal models [9–11], the majority have focused on humans [4,10,12–22] using NMR [4,16], LC-MS [12,13,15,17,21,22], and GC-MS [13–15,18,19], or HPLC methods [20]. These studies have reported alterations in numerous metabolic pathways, including glycolysis, amino acid, fatty acid, and bile acid metabolism. While there are few reports that have focused exclusively on altered metabolic pathways associated with liver rejection, there have been studies relating to rejection-associated events. Previous reports have documented metabolic pathways and individual metabolites that modulate immune cell function and immune responses [23]. For example, modulation of T cells has been well documented in conjunction with rejection, as has the role of metabolism and nutrient availability upon T cell activation and function [5,24]. Moreover, activation of T cells requires metabolic reprogramming in order to increase glycolytic flux, lactate, lipids, proteins, nucleic acid, and carbohydrates [25]. These changes in metabolic profiles also direct signaling. For example, increased intracellular leucine metabolism controls mammalian target of rapamycin (mTOR) signaling required to induce Th1, Th2, and Th17 CD4(+) T effector cell differentiation [26]. Therefore, there is a need to better understand changes in hepatic biochemical pathways associated with rejection, and metabolomics is an established analytical modality available to identify key compounds. Focusing on hepatic tissue prior to immunosuppression in patients provides a unique opportunity to improve our understanding of graft damage and loss.
Material and Methods
PATIENTS AND PROCEDURES:
In all liver transplants, the muscle layer was left open and skin was closed immediately after transplantation to prevent compartment syndrome. All patients were taken back to the operating room for delayed fascial closure on the 2nd post-transplant day [28]. During fascial closure, a second allograft biopsy was performed. A part of the second liver allograft biopsy was frozen for future use. Patients did not receive any immunosuppression prior to fascial closure [3]. For the purpose of this study, the day 2 biopsies were divided in to 3 groups (n=5–8 per group): Group 1 (control), patients with no evidence of rejection; Group 2, patients with histological evidence of mild rejection; and Group 3, patients with evidence of moderate or severe rejection. To evaluate the metabolic changes associated with liver rejection, we performed LC-MS analysis, targeting 216 metabolites in liver biopsies taken 2 days after liver transplantation.
IMMUNOSUPPRESSION PROTOCOL:
The induction immunosuppression consisted of 3 doses of 2 mg/kg rabbit anti-thymocyte globulin (rATG) every 48 hours starting on post-transplant day 2 along with a single dose of 1.5 mg/m2 BSA of rituximab on post-transplant day 3. Premedication for rATG was given immediately before its administration in the form of solumedrol [500 (first dose), 250 (second dose), and 120 mg (third dose)], acetaminophen (650 mg), and diphenhydramine (25 mg). Maintenance immunosuppression was also initiated on post-transplant day 2 in the form of tacrolimus monotherapy, although some recipients received additional mycophenolate mofetil. The goal trough levels for tacrolimus were 7 to 10 ng/mL in the first 3 months and 6 to 8 ng/mL thereafter [3].
LC/MS:
Day 2 liver allograft biopsies were frozen in liquid nitrogen and stored at −86°C. Tissue was transported on dry ice to the Northwest Metabolomics Research Center (NW-MRC) at the University of Washington for analysis. Briefly, targeted LC/MS/MS was performed according to methods developed at the University of Washington Metabolomic Research Center as per Zhu et al. [29] Targeted aqueous metabolite profiling analysis was performed using an Agilent 1260/AB-Sciex 5500 Qtrap Liquid Chromatography-Mass spectroscopy/mass spectroscopy (LC-MS/MS) instrument and standard operating procedures we developed previously [29]. The LC-MS/MS analysis is based on hydrophilic interaction chromatography (HILIC), and targets 216 metabolites located in more than 35 different metabolic pathways. This system provides detailed information on metabolites involved in glycolysis, tricarboxylic acid cycle (TCA), and pentose phosphate shunt, as well as amino acid, fatty acid, and nucleic acid metabolism, and other pathways. Twenty-six isotope-labeled internal standards were included to monitor sample preparation steps and system performance, as well as to provide absolute quantitation of a number of amino and organic acids.
DATA ANALYSIS FOR METABOLOMICS:
The intensity of tissue peaks in each data set were normalized to tissue weight. Statistical analysis was performed using XLSTAT software. Each data set was mean-centered before the analysis. Univariate analysis of the individual metabolites was performed using the
Results
HISTOLOGICAL EVIDENCE OF REJECTION:
Of the 60 patients recruited and transplanted, routine pathology reports described histological evidence of rejection in 14 patients (23%). Biopsies were stratified based on these reports into 3 groups: 1) no histological evidence of rejection, 2) evidence of mild rejection, and 3) patients with evidence of moderate or severe rejection. Seven samples from each group were selected for pathology review and metabolomic analysis. A pathologist (RS) reviewed all 21 fascial closure liver biopsies taken 2 days post-transplant. Her analysis found 5 biopsies had unequivocal evidence of moderate or severe rejection (endothelialitis, cell infiltration, or bile duct injury). Seven biopsies had no evidence of rejection but had reperfusion damage. One sample was indeterminable, did not reach criteria for rejection, and had no reperfusion injury. The remaining 8 biopsies had histological evidence of mild rejection. The 1 biopsy that was indeterminable was not included in either rejection or control groups and data were not included in the metabolomic analysis.
The biopsies in the rejection group were characterized by the presence of a mixed inflammatory infiltrate in portal tracts that comprised variable combinations of lymphocytes, eosinophils, and neutrophils. Endothelialitis and bile duct damage were present in varying degrees of severity. Control biopsies showed features of reperfusion damage that included variable combinations and severity of portal edema, peribiliary neutrophils, perivenular hepatocellular necrosis, and presence of lobular neutrophils. One biopsy showed mild macro-vesicular steatosis with necrosis and neutrophils. The biopsies were characterized into 3 groups for the purpose of metabolomic analysis: Group 1 was reperfusion injury only (N=7), Group 2 was categorical histological evidence of moderate or severe rejection (N=5), and Group 3 was histological evidence of mild rejection (N=8).
LC/MS-BASED METABOLOMICS:
The LC-MS/MS method was optimized to target a total of 216 metabolites in the liver biopsy samples. However, after deleting metabolites that were not detected, metabolites below the signal to noise cutoff, and metabolites inconsistently detected in the samples, 133 metabolites were quantified. We assessed and compared differences in metabolites between 1) biopsies with mild rejection or with moderate or severe rejection when compared to tissues with reperfusion injury and 2) biopsies with mild rejection when compared to biopsies with moderate or severe rejection. Each metabolite was ranked by its variable importance in the projection (VIP) score via partial least squares- discriminative analysis (PLS-DA) using XLSTAT Biomed software (Figure 1). Twenty-one metabolites with VIP scores above 1.5 were included in a secondary PLS-DA analysis comparing no rejection (reperfusion injury) to both moderate to severe rejection (Figure 2A) and mild rejection (Figure 2B). Of these metabolites, linoleic acid, γ-linolenic acid, and citrulline emerged as providing the strongest predictive model of rejection (Figure 2). The differences between these metabolites in rejection (mild, moderate, and severe) and control biopsies were examined individually (Figure 3). They were then used to construct a final sample model by PLS-DA. Cross-validation of this model was then used to estimate how closely the 3 metabolites, taken as a group, correlate with the biopsy histology report from the pathologist (RS) (Figure 4). The resulting aggregate indicates that, taken together, the 3 metabolites can accurately identify the rejection status of each patient in our sample group, and that this is likely to be the case for independent samples.
Discussion
This study represents a unique model of human liver rejection due to the unique immunosuppression and surgical protocol that was followed. There are no previously published data on human liver rejection in this setting. In the absence of immunosuppression, changes occurring in the liver biopsies in the setting of cellular rejection are novel and intriguing. Using 2-day protocol liver biopsies, targeted LC/MS-based metabolomics analysis, and PLS-DA, we identified 3 aberrant metabolites (linolenic acid, γ-linolenic acid, and citrulline) contemporaneous with liver rejection.
LC/MS/MS-based metabolomics provides broad-based coverage of the important small molecule metabolites in biofluids and tissue to allow the identification of altered metabolic pathways. As metabolites are modulated by protein function, they reflect many of the alterations caused by disease or other biological stresses [4–6]. Analysis using PLS-DA is appropriate when large numbers of potentially correlated variables must be analyzed. It is especially well suited to cases where the number of variables exceeds the number of samples, which would otherwise produce overfitting using conventional regression models. We used VIP scores, which represent the effect of a particular variable on the PLS-DA model, to eliminate non-predictive variables from our dataset, and to identify the variables with the highest degree of predictive power at the level of individual patients. This analysis revealed 3 metabolites: linoleic acid, γ linolenic acid, and citrulline. Linoleic acid and γ-linolenic acid are associated with cyclooxygenase (COX) pathways, while citrulline is associated with nitric oxide synthase (NOS) pathways.
Linoleic acid is an octadecadeinoic fatty acid and a precursor for arachidonic acid, which is a substrate for COX enzymes and subsequent biosynthesis of vasoactive molecules. Changes in arachidonic acid are linked to numerous pathologies of the liver, including portal hypertension and liver cirrhosis [30,31]. Linoleic acid regulates the COX-2/VEGF/MAP kinase pathway [32] and endothelial vasodilatory function [33]. Studies have shown that COX-2 was significantly increased in a rodent model of liver rejection [34]. However, whether increased COX is beneficial or not is controversial. Some studies have shown that increased COX-2 is protective [35], while others have found that inhibition of COX-2 increases graft survival in animal models [34,36]. Moreover, linoleic acid is also associated with pathologies independent of COX, as it is synthesized from phosphatidylcholine via phospholipase A2 or phospholipase A1. Aberrancies of phospholipase A2 are associated with Parkinson disease, peroxisomal beta-oxidation enzyme deficiency, neurodegeneration with brain iron accumulation, and peroxisomal acyl-CoA oxidase deficiency [37,39].
The second metabolite identified by PLS-DA was γ-linolenic acid, which is an all-cis-6,9,12-octadecatrienoic acid designated as 18: 3 and is synthesized from linoleic acid by introduction of a (third) double bond at the delta 6 position under the catalytic influence of delta-6-desaturase enzyme. This step is believed to be the rate-limiting stage in the metabolic pathway. Aging, obesity, diabetes, high alcohol intake, stress-related hormones, and viral infections are known to reduce conversion of linoleic acid to γ-linolenic acid [40–43]. γ-linolenic acid is known to inhibit angiogenesis, partly via the decrease in the expression of VE-cadherin and beta-catenin [44], potentially due to the elimination of the precursor, -linoleic acid. Hepatocyte expression of insulin growth factor-I, insulin growth factor-II, growth hormone receptor, insulin receptor, Insulin growth factor binding protein-3, and Insulin growth factor binding protein-4 mRNAs are all upregulated by linoleic acid [45]. Conversion of linoleic acid to γ-linolenic acid is known to be beneficial for human health [46]. Linolenic acid attenuates endothelial apoptosis
The third metabolite identified by PLS-DA was citrulline, a key intermediate in the urea cycle produced via the metabolism of ornithine and carbamoyl phosphate. Moreover, citrulline is a by-product of the enzymatic production of nitric oxide from the amino acid arginine. As citrulline is a part of the urea cycle and urea is a marker of liver failure, it is not unexpected that rejection is associated with increased citrulline. However, urea levels were not significantly higher in patients with rejection. Because citrulline is involved in many biological pathways, it is impossible to accurately hypothesize the pathobiology, physiological, and biochemical milieu associated with changes to hepatic linoleic acid, γ-linoleic acid and citrulline based on biopsies. However, the fact that they are connected to important hepatic perfusion regulators suggests that changes impart/reflect a response to tissue stress, damage, and/or acute graft rejection. Arginine is the predominate substrate for the production of nitric oxide (NO), a well-documented vasodilator associated with liver perfusion and portal hypertension [51,52]. The role of NO in liver perfusion is well documented and focuses on sinusoidal stellate cell control of sinusoidal dilation and thus an increase in resistance to portal venous blood flow. A reduction in citrulline might be indicative of a modulation of NO biosynthesis. Reduced citrulline could be reflective of a reduction of NOS activity, as citrulline is the biproduct of the conversion of arginine to NO. In contrast, as citrulline is also the substrate, a reduction could be indicative of an increase in NOS activity. What we do know is that a change in NO within the liver will modulate perfusion and affect ischemia and hypoxia and impart an additional stress to the liver. Moreover, endothelial NOS (eNOS) is also known to “uncouple” when co-factors are absent, leading to the formation of oxygen free radicals [53]. The conversion of arginine to NO and citrulline is a 2-step process involving N-hydroxy-l-arginine as an intermediate; therefore, uncoupling of endothelial NOS could result in a reduction in citrulline.
The data do not suggest that either linolenic acid or citrulline should replace current markers of acute liver rejection. LC-MS/MS is unlikely to be quicker or cheaper than histology and liver functional tests. Nevertheless, there is utility in investigating linolenic acid and citrulline, as both have been shown to be markers of interest in other pathologies. For example, the ratio of linolenic acid to deoxycholic acid species is a potential biomarker for metabolic abnormalities in obesity [54] and hepatic steatosis [55]. Moreover, the circulating citrulline concentration is a biomarker of intestinal functionality [56,57]. What the data may reveal is hepatic response to acute liver rejection by the modulation of vasodilators to maintain liver perfusion. However, we are cognizant that differences in metabolomics signatures between control livers and livers with rejection could be independent of rejection. It is possible that these differences are linked to other aspects of liver disease. For example, sarcopenia, which is associated with modulated metabolism, poorer outcomes, and changes in the levels of citrulline and linoleic acid, occurs in patients with liver disease [58–61]. A preliminary analysis of sarcopenia in the patients within this study, based on measurement of the psoas muscle at the C3, as previously described [62,63], was performed and identified 3 patients with sarcopenia. Two patients within the early rejection group had sarcopenia. One patient with no evidence of rejection was identified with sarcopenia. Because the frequency of overlapping sarcopenia within the 3 cohorts is sporadic, it is difficult to determine if sarcopenia is an independent variable in hepatic metabolites associated with hepatic response to rejection.
Additional research is required to further elucidate our findings and to better understand any connection among metabolic changes, acute liver rejection, and graft survival. Further research is likely to focus on metabolomic quantification post-transplant in rodent models of liver rejection [64]. This is because rejection rates observed in clinical programs are very low; therefore, to expand this project using patient samples only would be prohibitive. Moreover, the delayed immunosuppression protocol is controversial and delayed immunosuppression and 2-day protocol biopsies are not the standard of care at our institute at present.
Finally, the immunosuppression protocol deserves further explanation. The premise behind delayed introduction of immunosuppression was to allow immune activation of recipient lymphocytes in the allograft. It was thought that the potent rATG would then lead to apoptosis and death of recipient lymphocytes within the graft, allowing operational tolerance in the long term. Although this approach permits a degree of rejection in the allograft, this is a desired effect and has no adverse effects in the long term, which was demonstrated in our larger study involving 1000 patients [3]. Based on this large-sample experience, we do not believe that deaths that occurred in this study cohort were due to the delayed immunosuppression.
Conclusions
Contemporaneous with acute liver rejection, increases in linoleic acid and γ-linolenic acid are observed alongside a decrease in citrulline. These metabolites are connected to pathways that regulate liver perfusion.
References
1. Au KP, Chan SC, Chok KS, Clinical factors affecting rejection rates in liver transplantation: Hepatobiliary Pancreat Dis Int, 2015; 14(4); 367-73, pmid: 26256080
2. Neil DA, Hubscher SG, Current views on rejection pathology in liver transplantation: Transpl Int, 2010; 23(10); 971-83, pmid: 20723179
3. Mangus RS, Fridell JA, Vianna RM, Immunosuppression induction with rabbit anti-thymocyte globulin with or without rituximab in 1000 liver transplant patients with long-term follow-up: Liver Transpl, 2012; 18(7); 786-95, pmid: 22237953
4. Gao H, Lu Q, Liu X, Application of 1H NMR-based metabonomics in the study of metabolic profiling of human hepatocellular carcinoma and liver cirrhosis: Cancer Sci, 2009; 100(4); 782-85, pmid: 19469021
5. Mayr M, Metabolomics: Ready for the prime time?: Circ Cardiovasc Genet, 2008; 1(1); 58-65, pmid: 20031543
6. Zhang J, Liu L, Wei S, Metabolomics study of esophageal adenocarcinoma: J Thorac Cardiovasc Surg, 2011; 141(2); 469-75, pmid: 20880550
7. Gowda GA, Zhang S, Gu H, Metabolomics-based methods for early disease diagnostics: Expert Rev Mol Diagn, 2008; 8(5); 617-33, pmid: 18785810
8. Bowers J, Hughes E, Skill N, Detection of hepatocellular carcinoma in hepatitis C patients: biomarker discovery by LC-MS: J Chromatogr B Analyt Technol Biomed Life Sci, 2014; 966; 154-62
9. Li S, Liu H, Jin Y, Metabolomics study of alcohol-induced liver injury and hepatocellular carcinoma xenografts in mice: J Chromatogr B Analyt Technol Biomed Life Sci, 2011; 879(24); 2369-75
10. Tan Y, Yin P, Tang L, Metabolomics study of stepwise hepatocarcinogenesis from the model rats to patients: potential biomarkers effective for small hepatocellular carcinoma diagnosis: Mol Cell Proteomics, 2012; 11(2); M111.010694
11. Wang J, Zhang S, Li Z, (1)H-NMR-based metabolomics of tumor tissue for the metabolic characterization of rat hepatocellular carcinoma formation and metastasis: Tumour Biol, 2011; 32(1); 223-31, pmid: 20890798
12. Chen F, Xue J, Zhou L, Identification of serum biomarkers of hepatocarcinoma through liquid chromatography/mass spectrometry-based metabonomic method: Anal Bioanal Chem, 2011; 401(6); 1899-904, pmid: 21833635
13. Chen T, Xie G, Wang X, Serum and urine metabolite profiling reveals potential biomarkers of human hepatocellular carcinoma: Mol Cell Proteomics, 2011; 10(7); M110.004945
14. Lin X, Zhang Y, Ye G, Classification and differential metabolite discovery of liver diseases based on plasma metabolic profiling and support vector machines: J Sep Sci, 2011; 34(21); 3029-36, pmid: 21919198
15. Patterson AD, Maurhofer O, Beyoglu D, Aberrant lipid metabolism in hepatocellular carcinoma revealed by plasma metabolomics and lipid profiling: Cancer Res, 2011; 71(21); 6590-600, pmid: 21900402
16. Shariff MI, Gomaa AI, Cox IJ, Urinary metabolic biomarkers of hepatocellular carcinoma in an Egyptian population: A validation study: J Proteome Res, 2011; 10(4); 1828-36, pmid: 21275434
17. Wang B, Chen D, Chen Y, Metabonomic profiles discriminate hepatocellular carcinoma from liver cirrhosis by ultraperformance liquid chromatography-mass spectrometry: J Proteome Res, 2012; 11(2); 1217-27, pmid: 22200553
18. Wu H, Xue R, Dong L, Metabolomic profiling of human urine in hepatocellular carcinoma patients using gas chromatography/mass spectrometry: Anal Chim Acta, 2009; 648(1); 98-104, pmid: 19616694
19. Xue R, Lin Z, Deng C, A serum metabolomic investigation on hepatocellular carcinoma patients by chemical derivatization followed by gas chromatography/mass spectrometry: Rapid Commun Mass Spectrom, 2008; 22(19); 3061-68, pmid: 18767022
20. Yang J, Xu G, Zheng Y, Diagnosis of liver cancer using HPLC-based metabonomics avoiding false-positive result from hepatitis and hepatocirrhosis diseases: J Chromatogr B Analyt Technol Biomed Life Sci, 2004; 813(1–2); 59-65
21. Yin P, Wan D, Zhao C, A metabonomic study of hepatitis B-induced liver cirrhosis and hepatocellular carcinoma by using RP-LC and HILIC coupled with mass spectrometry: Mol Biosyst, 2009; 5(8); 868-76, pmid: 19603122
22. Zhou L, Wang Q, Yin P, Serum metabolomics reveals the deregulation of fatty acids metabolism in hepatocellular carcinoma and chronic liver diseases: Anal Bioanal Chem, 2012; 403(1); 203-13, pmid: 22349331
23. Everts B, Metabolomics in immunology research: Methods Mol Biol, 2018; 1730; 29-42, pmid: 29363063
24. Baumann AK, Schlue J, Noyan F, Preferential accumulation of T helper cells but not cytotoxic T cells characterizes benign subclinical rejection of human liver allografts: Liver Transpl, 2016; 22(7); 943-55, pmid: 26929119
25. Yang Z, Matteson EL, Goronzy JJ, Weyand CM, T-cell metabolism in autoimmune disease: Arthritis Res Ther, 2015; 17; 29, pmid: 25890351
26. Powell JD, Delgoffe GM, The mammalian target of rapamycin: Linking T cell differentiation, function, and metabolism: Immunity, 2010; 33(3); 301-11, pmid: 20870173
27. , Terminology for hepatic allograft rejection. International Working Party: Hepatology, 1995; 22(2); 648-54, pmid: 7635435
28. Jernigan TW, Fabian TC, Croce MA, Staged management of giant abdominal wall defects: acute and long-term results: Ann Surg, 2003; 238(3); 349-55, pmid: 14501501 discussion 355–57
29. Zhu J, Djukovic D, Deng L, Colorectal cancer detection using targeted serum metabolic profiling: J Proteome Res, 2014; 13(9); 4120-30, pmid: 25126899
30. Skill NJ, Theodorakis NG, Wang YN, Role of cyclooxygenase isoforms in prostacyclin biosynthesis and murine prehepatic portal hypertension: Am J Physiol Gastrointest Liver Physiol, 2008; 295(5); G953-64, pmid: 18772366
31. Jeong SW, Jang JY, Lee SH, Increased expression of cyclooxygenase-2 is associated with the progression to cirrhosis: Korean J Intern Med, 2010; 25(4); 364-71, pmid: 21179273
32. Deshpande R, Mansara P, Kaul-Ghanekar R, Alpha-linolenic acid regulates Cox2/VEGF/MAP kinase pathway and decreases the expression of HPV oncoproteins E6/E7 through restoration of p53 and Rb expression in human cervical cancer cell lines: Tumour Biol, 2016; 37(3); 3295-305, pmid: 26440049
33. Steer P, Vessby B, Lind L, Endothelial vasodilatory function is related to the proportions of saturated fatty acids and alpha-linolenic acid in young men, but not in women: Eur J Clin Invest, 2003; 33(5); 390-96, pmid: 12713452
34. Martelius TJ, Wolff H, Bruggeman CA, Induction of cyclo-oxygenase-2 by acute liver allograft rejection and cytomegalovirus infection in the rat: Transpl Int, 2002; 15(12); 610-14, pmid: 12478407
35. Motino O, Frances DE, Casanova N, Protective role of hepatocyte cyclooxygenase-2 expression against liver ischemia-reperfusion injury in mice: Hepatology, 2018 [Epub ahead of print]
36. Ma N, Szabolcs MJ, Sun J, The effect of selective inhibition of cyclooxygenase (COX)-2 on acute cardiac allograft rejection: Transplantation, 2002; 74(11); 1528-34, pmid: 12490785
37. Cicchetti F, Drouin-Ouellet J, Gross RE, Environmental toxins and Parkinson’s disease: What have we learned from pesticide-induced animal models?: Trends Pharmacol Sci, 2009; 30(9); 475-83, pmid: 19729209
38. Hague SM, Klaffke S, Bandmann O, Neurodegenerative disorders: Parkinson’s disease and Huntington’s disease: J Neurol Neurosurg Psychiatry, 2005; 76(8); 1058-63, pmid: 16024878
39. Pardo LM, van Duijn CM, In search of genes involved in neurodegenerative disorders: Mutat Res, 2005; 592(1–2); 89-101, pmid: 16009383
40. Horrobin DF, Loss of delta-6-desaturase activity as a key factor in aging: Med Hypotheses, 1981; 7(9); 1211-20, pmid: 6270521
41. Kroger J, Schulze MB, Recent insights into the relation of Delta5 desaturase and Delta6 desaturase activity to the development of type 2 diabetes: Curr Opin Lipidol, 2012; 23(1); 4-10, pmid: 22123669
42. Abel S, De Kock M, van Schalkwyk DJ, Altered lipid profile, oxidative status and hepatitis B virus interactions in human hepatocellular carcinoma: Prostaglandins Leukot Essent Fatty Acids, 2009; 81(5–6); 391-99, pmid: 19782547
43. Araya J, Rodrigo R, Pettinelli P, Decreased liver fatty acid delta-6 and delta-5 desaturase activity in obese patients: Obesity (Silver Spring), 2010; 18(7); 1460-63, pmid: 19875987
44. Cai J, Jiang WG, Mansel RE, Inhibition of the expression of VE-cadherin/catenin complex by gamma linolenic acid in human vascular endothelial cells, and its impact on angiogenesis: Biochem Biophys Res Commun, 1999; 258(1); 113-18, pmid: 10222244
45. Fang XL, Shu G, Zhang ZQ, Roles of alpha-linolenic acid on IGF-I secretion and GH/IGF system gene expression in porcine primary hepatocytes: Mol Biol Rep, 2012; 39(12); 10987-96, pmid: 23053988
46. Barcelo-Coblijn G, Murphy EJ, Alpha-linolenic acid and its conversion to longer chain n-3 fatty acids: Benefits for human health and a role in maintaining tissue n-3 fatty acid levels: Prog Lipid Res, 2009; 48(6); 355-74, pmid: 19619583
47. Zhang W, Wang R, Han SF, Alpha-linolenic acid attenuates high glucose-induced apoptosis in cultured human umbilical vein endothelial cells via PI3K/Akt/eNOS pathway: Nutrition, 2007; 23(10); 762-70, pmid: 17716867
48. Lewin M, Samuel S, Merkel J, Bickler P, Varespladib (LY315920) appears to be a potent, broad-spectrum, inhibitor of snake venom phospholipase A2 and a possible pre-referral treatment for envenomation: Toxins (Basel), 2016; 8(9) pii: E248
49. Thotala D, Craft JM, Ferraro DJ, Cytosolic phospholipaseA2 inhibition with PLA-695 radiosensitizes tumors in lung cancer animal models: PLoS One, 2013; 8(7); e69688, pmid: 23894523
50. Lee KL, Foley MA, Chen L, Discovery of Ecopladib, an indole inhibitor of cytosolic phospholipase A2alpha: J Med Chem, 2007; 50(6); 1380-400, pmid: 17305324
51. Theodorakis NG, Wang YN, Skill NJ, The role of nitric oxide synthase isoforms in extrahepatic portal hypertension: Studies in gene-knockout mice: Gastroenterology, 2003; 124(5); 1500-8, pmid: 12730888
52. Theodorakis NG, Wang YN, Wu JM, Role of endothelial nitric oxide synthase in the development of portal hypertension in the carbon tetrachloride-induced liver fibrosis model: Am J Physiol Gastrointest Liver Physiol, 2009; 297(4); G792-99, pmid: 19628654
53. Li H, Forstermann U, Pharmacological prevention of eNOS uncoupling: Curr Pharm Des, 2014; 20(22); 3595-606, pmid: 24180386
54. Lei S, Huang F, Zhao A, The ratio of dihomo-gamma-linolenic acid to deoxycholic acid species is a potential biomarker for the metabolic abnormalities in obesity: FASEB J, 2017; 31(9); 3904-12, pmid: 28490483
55. Matsuda M, Kawamoto T, Tamura R, Predictive value of serum dihomo-gamma-linolenic acid level and estimated Delta-5 desaturase activity in patients with hepatic steatosis: Obes Res Clin Pract, 2017; 11(1); 34-43, pmid: 26964726
56. Fragkos KC, Forbes A, Citrulline as a marker of intestinal function and absorption in clinical settings: A systematic review and meta-analysis: United European Gastroenterol J, 2018; 6(2); 181-91
57. Crenn P, Coudray-Lucas C, Thuillier F, Postabsorptive plasma citrulline concentration is a marker of absorptive enterocyte mass and intestinal failure in humans: Gastroenterology, 2000; 119(6); 1496-505, pmid: 11113071
58. Meeks AC, Madill J, Sarcopenia in liver transplantation: A review: Clin Nutr ESPEN, 2017; 22; 76-80, pmid: 29415839
59. Ogawa SBody weight and bone/calcium metabolism. Sarcopenia and its relationship with bone and calcium metabolism: Clin Calcium, 2018; 28(7); 907-12, pmid: 29950542 [in Japanese]
60. Barillaro C, Liperoti R, Martone AM, The new metabolic treatments for sarcopenia: Aging Clin Exp Res, 2013; 25(2); 119-27, pmid: 23739896
61. Ter Borg S, de Groot LC, Mijnarends DM, Differences in nutrient intake and biochemical nutrient status between sarcopenic and nonsarcopenic older adults-results from the Maastricht Sarcopenia Study: J Am Med Dir Assoc, 2016; 17(5); 393-401, pmid: 26825685
62. Gu DH, Kim MY, Seo YS, Clinical usefulness of psoas muscle thickness for the diagnosis of sarcopenia in patients with liver cirrhosis: Clin Mol Hepatol, 2018; 24(3); 319-30, pmid: 29706058
63. Mangus RS, Bush WJ, Miller C, Severe sarcopenia and increased fat stores in pediatric patients with liver, kidney, or intestine failure: J Pediatr Gastroenterol Nutr, 2017; 65(5); 579-83, pmid: 28604513
64. Kaizu T, Ikeda A, Nakao A, Donor graft adenoviral iNOS gene transfer ameliorates rat liver transplant preservation injury and improves survival: Hepatology, 2006; 43(3); 464-73, pmid: 16496305
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About Ann Transplant

eISSN: 2329-0358
Annals of Transplantation is one of the fast-developing journals open to all scientists and fields of transplant medicine and related research. The journal is published quarterly and provides extensive coverage of the most important advances in transplantation. Using an electronic on-line submission and peer review tracking system, Annals of Transplantation is committed to rapid review and publication.
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About Ann Transplant

eISSN: 2329-0358
Annals of Transplantation is one of the fast-developing journals open to all scientists and fields of transplant medicine and related research. The journal is published quarterly and provides extensive coverage of the most important advances in transplantation. Using an electronic on-line submission and peer review tracking system, Annals of Transplantation is committed to rapid review and publication.
Categories
ISI Journals
Publisher
International Scientific Information, Inc.
150 Broadhollow Rd., Suite 114
Melville, NY, 11747 | USA
phone:
1.631.629.4327
e-mail:
[email protected]
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www.isi-science.com
Information
Copyright © 2025
International Scientific Infromation, Inc.
All rights reserved.
About Ann Transplant

eISSN: 2329-0358
Annals of Transplantation is one of the fast-developing journals open to all scientists and fields of transplant medicine and related research. The journal is published quarterly and provides extensive coverage of the most important advances in transplantation. Using an electronic on-line submission and peer review tracking system, Annals of Transplantation is committed to rapid review and publication.
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Information
Copyright © 2002 - 2025
International Scientific
Infromation, Inc.
All rights reserved.
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11 June 2019: Original Paper
Metabolomic Characterization of Human Model of Liver Rejection Identifies Aberrancies Linked to Cyclooxygenase (COX) and Nitric Oxide Synthase (NOS)
Nicholas J. Skill ABCDEFG 1*, Campbell M. Elliott CDEF 1, Brian Ceballos B 1, Romil Saxena BCD 2, Robert Pepin B 3, Lisa Bettcher B 3, Matthew Ellensberg B 3, Daniel Raftery CDE 3, Mary A. Malucio AEG 1, Burcin Ekser DF 1, Richard S. Mangus A 1, Chandrashekhar A. Kubal AE 1
DOI: 10.12659/AOT.913800
Ann Transplant 2019; 24:341-349
Abstract
BACKGROUND: Acute liver rejection (ALR), a significant complication of liver transplantation, burdens patients, healthcare payers, and the healthcare providers due to an increase in morbidity, cost, and resources. Despite clinical resolution, ALR is associated with an increased risk of graft loss. A unique protocol of delayed immunosuppression used in our institute provided a model to characterize metabolomic profiles in human ALR.
MATERIAL AND METHODS: Twenty liver allograft biopsies obtained 48 hours after liver transplantation in the absence of immunosuppression were studied. Hepatic metabolites were quantitated in these biopsies by liquid chromatography and mass spectroscopy (LC/MS). Metabolite profiles were compared among: 1) biopsies with reperfusion injury but no histological evidence of rejection (n=7), 2) biopsies with histological evidence of moderate or severe rejection (n=5), and 3) biopsies with histological evidence of mild rejection (n=8).
RESULTS: There were 133 metabolites consistently detected by LC/MS and these were prioritized using variable importance to projection (VIP) analysis, comparing moderate or severe rejection vs. no rejection or mild rejection using partial least squares discriminant statistical analysis (PLS-DA). Twenty metabolites were identified as progressively different. Further PLS-DA using these metabolites identified 3 metabolites (linoleic acid, γ-linolenic acid, and citrulline) which are associated with either cyclooxygenase or nitric oxide synthase functionality.
CONCLUSIONS: Hepatic metabolic aberrancies associated with cyclooxygenase and nitric oxide synthase function occur contemporaneous with ALR. Additional studies are required to better characterize the role of these metabolic pathways to enhance utility of the metabolomics approach in diagnosis and outcomes of ALR.
Keywords: Graft Rejection, Liver Transplantation, Metabolomics, Nitric Oxide Synthase, Prostaglandin-Endoperoxide Synthases, End stage liver disease, Liver
Background
Acute liver rejection (ALR) following liver transplantation occurs in approximately 4–20% of patients [1,2]. According to the United Network for Organ Sharing (UNOS), in 2017 the number of liver transplants performed in the USA was 8082, representing an increase of 24.5% since 2016. Currently, the number of patients waiting for liver transplant is approximately 13 914 and the average waiting time for liver transplant is 511 days. Therefore, although the incidence of acute liver rejection is low, the high volume of transplants coupled with increased frequency and limited donors encourages the maximization of graft survival by addressing ALR, a major cause of graft damage.
This study aimed to characterize metabolomic aberrancies in a human model of liver rejection to guide future studies aimed at addressing graft damage congruent with ALR. Between 2008 and 2012, the standard immunosuppression protocol for patients receiving liver transplants at Indiana University Hospital was begun 2 days following transplant and prior to collection of liver biopsy at the time of fascial closure. The hypothesis was that a delay in immunosuppression would induce tolerance [3]. This immunosuppression delay protocol coupled with the collection of a fascial closure biopsy provides an opportunity to characterize ALR consequences in a human model of early liver rejection, specifically to utilize a targeted liquid chromatography/mass spectrometry (LC/MS) platform for metabolomics to profile and quantify hepatic metabolites in order to identify metabolic signatures associated with ALR.
Metabolomics is the study of a large number of small molecule metabolites in biofluids and tissue to identify biomarkers associated with altered metabolic pathways. As metabolites are modulated by protein and enzymatic function, they reflect many of the alterations caused by disease or other biological stresses. Metabolites are exquisitely sensitive to different biological states and therefore represent a promising approach to identify biopathology contemporaneous with rejection [4–6]. Several analytical techniques such as nuclear magnetic resonance (NMR), LC-MS, and gas chromatography-mass spectrometry (GC-MS) have been used to detect metabolic changes [7]. Several studies have used a variety of analytical techniques to elucidate aberrant pathways associated with cancer [8]. While a few of these studies have used animal models [9–11], the majority have focused on humans [4,10,12–22] using NMR [4,16], LC-MS [12,13,15,17,21,22], and GC-MS [13–15,18,19], or HPLC methods [20]. These studies have reported alterations in numerous metabolic pathways, including glycolysis, amino acid, fatty acid, and bile acid metabolism. While there are few reports that have focused exclusively on altered metabolic pathways associated with liver rejection, there have been studies relating to rejection-associated events. Previous reports have documented metabolic pathways and individual metabolites that modulate immune cell function and immune responses [23]. For example, modulation of T cells has been well documented in conjunction with rejection, as has the role of metabolism and nutrient availability upon T cell activation and function [5,24]. Moreover, activation of T cells requires metabolic reprogramming in order to increase glycolytic flux, lactate, lipids, proteins, nucleic acid, and carbohydrates [25]. These changes in metabolic profiles also direct signaling. For example, increased intracellular leucine metabolism controls mammalian target of rapamycin (mTOR) signaling required to induce Th1, Th2, and Th17 CD4(+) T effector cell differentiation [26]. Therefore, there is a need to better understand changes in hepatic biochemical pathways associated with rejection, and metabolomics is an established analytical modality available to identify key compounds. Focusing on hepatic tissue prior to immunosuppression in patients provides a unique opportunity to improve our understanding of graft damage and loss.
Material and Methods
PATIENTS AND PROCEDURES:
In all liver transplants, the muscle layer was left open and skin was closed immediately after transplantation to prevent compartment syndrome. All patients were taken back to the operating room for delayed fascial closure on the 2nd post-transplant day [28]. During fascial closure, a second allograft biopsy was performed. A part of the second liver allograft biopsy was frozen for future use. Patients did not receive any immunosuppression prior to fascial closure [3]. For the purpose of this study, the day 2 biopsies were divided in to 3 groups (n=5–8 per group): Group 1 (control), patients with no evidence of rejection; Group 2, patients with histological evidence of mild rejection; and Group 3, patients with evidence of moderate or severe rejection. To evaluate the metabolic changes associated with liver rejection, we performed LC-MS analysis, targeting 216 metabolites in liver biopsies taken 2 days after liver transplantation.
IMMUNOSUPPRESSION PROTOCOL:
The induction immunosuppression consisted of 3 doses of 2 mg/kg rabbit anti-thymocyte globulin (rATG) every 48 hours starting on post-transplant day 2 along with a single dose of 1.5 mg/m2 BSA of rituximab on post-transplant day 3. Premedication for rATG was given immediately before its administration in the form of solumedrol [500 (first dose), 250 (second dose), and 120 mg (third dose)], acetaminophen (650 mg), and diphenhydramine (25 mg). Maintenance immunosuppression was also initiated on post-transplant day 2 in the form of tacrolimus monotherapy, although some recipients received additional mycophenolate mofetil. The goal trough levels for tacrolimus were 7 to 10 ng/mL in the first 3 months and 6 to 8 ng/mL thereafter [3].
LC/MS:
Day 2 liver allograft biopsies were frozen in liquid nitrogen and stored at −86°C. Tissue was transported on dry ice to the Northwest Metabolomics Research Center (NW-MRC) at the University of Washington for analysis. Briefly, targeted LC/MS/MS was performed according to methods developed at the University of Washington Metabolomic Research Center as per Zhu et al. [29] Targeted aqueous metabolite profiling analysis was performed using an Agilent 1260/AB-Sciex 5500 Qtrap Liquid Chromatography-Mass spectroscopy/mass spectroscopy (LC-MS/MS) instrument and standard operating procedures we developed previously [29]. The LC-MS/MS analysis is based on hydrophilic interaction chromatography (HILIC), and targets 216 metabolites located in more than 35 different metabolic pathways. This system provides detailed information on metabolites involved in glycolysis, tricarboxylic acid cycle (TCA), and pentose phosphate shunt, as well as amino acid, fatty acid, and nucleic acid metabolism, and other pathways. Twenty-six isotope-labeled internal standards were included to monitor sample preparation steps and system performance, as well as to provide absolute quantitation of a number of amino and organic acids.
DATA ANALYSIS FOR METABOLOMICS:
The intensity of tissue peaks in each data set were normalized to tissue weight. Statistical analysis was performed using XLSTAT software. Each data set was mean-centered before the analysis. Univariate analysis of the individual metabolites was performed using the
Results
HISTOLOGICAL EVIDENCE OF REJECTION:
Of the 60 patients recruited and transplanted, routine pathology reports described histological evidence of rejection in 14 patients (23%). Biopsies were stratified based on these reports into 3 groups: 1) no histological evidence of rejection, 2) evidence of mild rejection, and 3) patients with evidence of moderate or severe rejection. Seven samples from each group were selected for pathology review and metabolomic analysis. A pathologist (RS) reviewed all 21 fascial closure liver biopsies taken 2 days post-transplant. Her analysis found 5 biopsies had unequivocal evidence of moderate or severe rejection (endothelialitis, cell infiltration, or bile duct injury). Seven biopsies had no evidence of rejection but had reperfusion damage. One sample was indeterminable, did not reach criteria for rejection, and had no reperfusion injury. The remaining 8 biopsies had histological evidence of mild rejection. The 1 biopsy that was indeterminable was not included in either rejection or control groups and data were not included in the metabolomic analysis.
The biopsies in the rejection group were characterized by the presence of a mixed inflammatory infiltrate in portal tracts that comprised variable combinations of lymphocytes, eosinophils, and neutrophils. Endothelialitis and bile duct damage were present in varying degrees of severity. Control biopsies showed features of reperfusion damage that included variable combinations and severity of portal edema, peribiliary neutrophils, perivenular hepatocellular necrosis, and presence of lobular neutrophils. One biopsy showed mild macro-vesicular steatosis with necrosis and neutrophils. The biopsies were characterized into 3 groups for the purpose of metabolomic analysis: Group 1 was reperfusion injury only (N=7), Group 2 was categorical histological evidence of moderate or severe rejection (N=5), and Group 3 was histological evidence of mild rejection (N=8).
LC/MS-BASED METABOLOMICS:
The LC-MS/MS method was optimized to target a total of 216 metabolites in the liver biopsy samples. However, after deleting metabolites that were not detected, metabolites below the signal to noise cutoff, and metabolites inconsistently detected in the samples, 133 metabolites were quantified. We assessed and compared differences in metabolites between 1) biopsies with mild rejection or with moderate or severe rejection when compared to tissues with reperfusion injury and 2) biopsies with mild rejection when compared to biopsies with moderate or severe rejection. Each metabolite was ranked by its variable importance in the projection (VIP) score via partial least squares- discriminative analysis (PLS-DA) using XLSTAT Biomed software (Figure 1). Twenty-one metabolites with VIP scores above 1.5 were included in a secondary PLS-DA analysis comparing no rejection (reperfusion injury) to both moderate to severe rejection (Figure 2A) and mild rejection (Figure 2B). Of these metabolites, linoleic acid, γ-linolenic acid, and citrulline emerged as providing the strongest predictive model of rejection (Figure 2). The differences between these metabolites in rejection (mild, moderate, and severe) and control biopsies were examined individually (Figure 3). They were then used to construct a final sample model by PLS-DA. Cross-validation of this model was then used to estimate how closely the 3 metabolites, taken as a group, correlate with the biopsy histology report from the pathologist (RS) (Figure 4). The resulting aggregate indicates that, taken together, the 3 metabolites can accurately identify the rejection status of each patient in our sample group, and that this is likely to be the case for independent samples.
Discussion
This study represents a unique model of human liver rejection due to the unique immunosuppression and surgical protocol that was followed. There are no previously published data on human liver rejection in this setting. In the absence of immunosuppression, changes occurring in the liver biopsies in the setting of cellular rejection are novel and intriguing. Using 2-day protocol liver biopsies, targeted LC/MS-based metabolomics analysis, and PLS-DA, we identified 3 aberrant metabolites (linolenic acid, γ-linolenic acid, and citrulline) contemporaneous with liver rejection.
LC/MS/MS-based metabolomics provides broad-based coverage of the important small molecule metabolites in biofluids and tissue to allow the identification of altered metabolic pathways. As metabolites are modulated by protein function, they reflect many of the alterations caused by disease or other biological stresses [4–6]. Analysis using PLS-DA is appropriate when large numbers of potentially correlated variables must be analyzed. It is especially well suited to cases where the number of variables exceeds the number of samples, which would otherwise produce overfitting using conventional regression models. We used VIP scores, which represent the effect of a particular variable on the PLS-DA model, to eliminate non-predictive variables from our dataset, and to identify the variables with the highest degree of predictive power at the level of individual patients. This analysis revealed 3 metabolites: linoleic acid, γ linolenic acid, and citrulline. Linoleic acid and γ-linolenic acid are associated with cyclooxygenase (COX) pathways, while citrulline is associated with nitric oxide synthase (NOS) pathways.
Linoleic acid is an octadecadeinoic fatty acid and a precursor for arachidonic acid, which is a substrate for COX enzymes and subsequent biosynthesis of vasoactive molecules. Changes in arachidonic acid are linked to numerous pathologies of the liver, including portal hypertension and liver cirrhosis [30,31]. Linoleic acid regulates the COX-2/VEGF/MAP kinase pathway [32] and endothelial vasodilatory function [33]. Studies have shown that COX-2 was significantly increased in a rodent model of liver rejection [34]. However, whether increased COX is beneficial or not is controversial. Some studies have shown that increased COX-2 is protective [35], while others have found that inhibition of COX-2 increases graft survival in animal models [34,36]. Moreover, linoleic acid is also associated with pathologies independent of COX, as it is synthesized from phosphatidylcholine via phospholipase A2 or phospholipase A1. Aberrancies of phospholipase A2 are associated with Parkinson disease, peroxisomal beta-oxidation enzyme deficiency, neurodegeneration with brain iron accumulation, and peroxisomal acyl-CoA oxidase deficiency [37,39].
The second metabolite identified by PLS-DA was γ-linolenic acid, which is an all-cis-6,9,12-octadecatrienoic acid designated as 18: 3 and is synthesized from linoleic acid by introduction of a (third) double bond at the delta 6 position under the catalytic influence of delta-6-desaturase enzyme. This step is believed to be the rate-limiting stage in the metabolic pathway. Aging, obesity, diabetes, high alcohol intake, stress-related hormones, and viral infections are known to reduce conversion of linoleic acid to γ-linolenic acid [40–43]. γ-linolenic acid is known to inhibit angiogenesis, partly via the decrease in the expression of VE-cadherin and beta-catenin [44], potentially due to the elimination of the precursor, -linoleic acid. Hepatocyte expression of insulin growth factor-I, insulin growth factor-II, growth hormone receptor, insulin receptor, Insulin growth factor binding protein-3, and Insulin growth factor binding protein-4 mRNAs are all upregulated by linoleic acid [45]. Conversion of linoleic acid to γ-linolenic acid is known to be beneficial for human health [46]. Linolenic acid attenuates endothelial apoptosis
The third metabolite identified by PLS-DA was citrulline, a key intermediate in the urea cycle produced via the metabolism of ornithine and carbamoyl phosphate. Moreover, citrulline is a by-product of the enzymatic production of nitric oxide from the amino acid arginine. As citrulline is a part of the urea cycle and urea is a marker of liver failure, it is not unexpected that rejection is associated with increased citrulline. However, urea levels were not significantly higher in patients with rejection. Because citrulline is involved in many biological pathways, it is impossible to accurately hypothesize the pathobiology, physiological, and biochemical milieu associated with changes to hepatic linoleic acid, γ-linoleic acid and citrulline based on biopsies. However, the fact that they are connected to important hepatic perfusion regulators suggests that changes impart/reflect a response to tissue stress, damage, and/or acute graft rejection. Arginine is the predominate substrate for the production of nitric oxide (NO), a well-documented vasodilator associated with liver perfusion and portal hypertension [51,52]. The role of NO in liver perfusion is well documented and focuses on sinusoidal stellate cell control of sinusoidal dilation and thus an increase in resistance to portal venous blood flow. A reduction in citrulline might be indicative of a modulation of NO biosynthesis. Reduced citrulline could be reflective of a reduction of NOS activity, as citrulline is the biproduct of the conversion of arginine to NO. In contrast, as citrulline is also the substrate, a reduction could be indicative of an increase in NOS activity. What we do know is that a change in NO within the liver will modulate perfusion and affect ischemia and hypoxia and impart an additional stress to the liver. Moreover, endothelial NOS (eNOS) is also known to “uncouple” when co-factors are absent, leading to the formation of oxygen free radicals [53]. The conversion of arginine to NO and citrulline is a 2-step process involving N-hydroxy-l-arginine as an intermediate; therefore, uncoupling of endothelial NOS could result in a reduction in citrulline.
The data do not suggest that either linolenic acid or citrulline should replace current markers of acute liver rejection. LC-MS/MS is unlikely to be quicker or cheaper than histology and liver functional tests. Nevertheless, there is utility in investigating linolenic acid and citrulline, as both have been shown to be markers of interest in other pathologies. For example, the ratio of linolenic acid to deoxycholic acid species is a potential biomarker for metabolic abnormalities in obesity [54] and hepatic steatosis [55]. Moreover, the circulating citrulline concentration is a biomarker of intestinal functionality [56,57]. What the data may reveal is hepatic response to acute liver rejection by the modulation of vasodilators to maintain liver perfusion. However, we are cognizant that differences in metabolomics signatures between control livers and livers with rejection could be independent of rejection. It is possible that these differences are linked to other aspects of liver disease. For example, sarcopenia, which is associated with modulated metabolism, poorer outcomes, and changes in the levels of citrulline and linoleic acid, occurs in patients with liver disease [58–61]. A preliminary analysis of sarcopenia in the patients within this study, based on measurement of the psoas muscle at the C3, as previously described [62,63], was performed and identified 3 patients with sarcopenia. Two patients within the early rejection group had sarcopenia. One patient with no evidence of rejection was identified with sarcopenia. Because the frequency of overlapping sarcopenia within the 3 cohorts is sporadic, it is difficult to determine if sarcopenia is an independent variable in hepatic metabolites associated with hepatic response to rejection.
Additional research is required to further elucidate our findings and to better understand any connection among metabolic changes, acute liver rejection, and graft survival. Further research is likely to focus on metabolomic quantification post-transplant in rodent models of liver rejection [64]. This is because rejection rates observed in clinical programs are very low; therefore, to expand this project using patient samples only would be prohibitive. Moreover, the delayed immunosuppression protocol is controversial and delayed immunosuppression and 2-day protocol biopsies are not the standard of care at our institute at present.
Finally, the immunosuppression protocol deserves further explanation. The premise behind delayed introduction of immunosuppression was to allow immune activation of recipient lymphocytes in the allograft. It was thought that the potent rATG would then lead to apoptosis and death of recipient lymphocytes within the graft, allowing operational tolerance in the long term. Although this approach permits a degree of rejection in the allograft, this is a desired effect and has no adverse effects in the long term, which was demonstrated in our larger study involving 1000 patients [3]. Based on this large-sample experience, we do not believe that deaths that occurred in this study cohort were due to the delayed immunosuppression.
Conclusions
Contemporaneous with acute liver rejection, increases in linoleic acid and γ-linolenic acid are observed alongside a decrease in citrulline. These metabolites are connected to pathways that regulate liver perfusion.
References
1. Au KP, Chan SC, Chok KS, Clinical factors affecting rejection rates in liver transplantation: Hepatobiliary Pancreat Dis Int, 2015; 14(4); 367-73, pmid: 26256080
2. Neil DA, Hubscher SG, Current views on rejection pathology in liver transplantation: Transpl Int, 2010; 23(10); 971-83, pmid: 20723179
3. Mangus RS, Fridell JA, Vianna RM, Immunosuppression induction with rabbit anti-thymocyte globulin with or without rituximab in 1000 liver transplant patients with long-term follow-up: Liver Transpl, 2012; 18(7); 786-95, pmid: 22237953
4. Gao H, Lu Q, Liu X, Application of 1H NMR-based metabonomics in the study of metabolic profiling of human hepatocellular carcinoma and liver cirrhosis: Cancer Sci, 2009; 100(4); 782-85, pmid: 19469021
5. Mayr M, Metabolomics: Ready for the prime time?: Circ Cardiovasc Genet, 2008; 1(1); 58-65, pmid: 20031543
6. Zhang J, Liu L, Wei S, Metabolomics study of esophageal adenocarcinoma: J Thorac Cardiovasc Surg, 2011; 141(2); 469-75, pmid: 20880550
7. Gowda GA, Zhang S, Gu H, Metabolomics-based methods for early disease diagnostics: Expert Rev Mol Diagn, 2008; 8(5); 617-33, pmid: 18785810
8. Bowers J, Hughes E, Skill N, Detection of hepatocellular carcinoma in hepatitis C patients: biomarker discovery by LC-MS: J Chromatogr B Analyt Technol Biomed Life Sci, 2014; 966; 154-62
9. Li S, Liu H, Jin Y, Metabolomics study of alcohol-induced liver injury and hepatocellular carcinoma xenografts in mice: J Chromatogr B Analyt Technol Biomed Life Sci, 2011; 879(24); 2369-75
10. Tan Y, Yin P, Tang L, Metabolomics study of stepwise hepatocarcinogenesis from the model rats to patients: potential biomarkers effective for small hepatocellular carcinoma diagnosis: Mol Cell Proteomics, 2012; 11(2); M111.010694
11. Wang J, Zhang S, Li Z, (1)H-NMR-based metabolomics of tumor tissue for the metabolic characterization of rat hepatocellular carcinoma formation and metastasis: Tumour Biol, 2011; 32(1); 223-31, pmid: 20890798
12. Chen F, Xue J, Zhou L, Identification of serum biomarkers of hepatocarcinoma through liquid chromatography/mass spectrometry-based metabonomic method: Anal Bioanal Chem, 2011; 401(6); 1899-904, pmid: 21833635
13. Chen T, Xie G, Wang X, Serum and urine metabolite profiling reveals potential biomarkers of human hepatocellular carcinoma: Mol Cell Proteomics, 2011; 10(7); M110.004945
14. Lin X, Zhang Y, Ye G, Classification and differential metabolite discovery of liver diseases based on plasma metabolic profiling and support vector machines: J Sep Sci, 2011; 34(21); 3029-36, pmid: 21919198
15. Patterson AD, Maurhofer O, Beyoglu D, Aberrant lipid metabolism in hepatocellular carcinoma revealed by plasma metabolomics and lipid profiling: Cancer Res, 2011; 71(21); 6590-600, pmid: 21900402
16. Shariff MI, Gomaa AI, Cox IJ, Urinary metabolic biomarkers of hepatocellular carcinoma in an Egyptian population: A validation study: J Proteome Res, 2011; 10(4); 1828-36, pmid: 21275434
17. Wang B, Chen D, Chen Y, Metabonomic profiles discriminate hepatocellular carcinoma from liver cirrhosis by ultraperformance liquid chromatography-mass spectrometry: J Proteome Res, 2012; 11(2); 1217-27, pmid: 22200553
18. Wu H, Xue R, Dong L, Metabolomic profiling of human urine in hepatocellular carcinoma patients using gas chromatography/mass spectrometry: Anal Chim Acta, 2009; 648(1); 98-104, pmid: 19616694
19. Xue R, Lin Z, Deng C, A serum metabolomic investigation on hepatocellular carcinoma patients by chemical derivatization followed by gas chromatography/mass spectrometry: Rapid Commun Mass Spectrom, 2008; 22(19); 3061-68, pmid: 18767022
20. Yang J, Xu G, Zheng Y, Diagnosis of liver cancer using HPLC-based metabonomics avoiding false-positive result from hepatitis and hepatocirrhosis diseases: J Chromatogr B Analyt Technol Biomed Life Sci, 2004; 813(1–2); 59-65
21. Yin P, Wan D, Zhao C, A metabonomic study of hepatitis B-induced liver cirrhosis and hepatocellular carcinoma by using RP-LC and HILIC coupled with mass spectrometry: Mol Biosyst, 2009; 5(8); 868-76, pmid: 19603122
22. Zhou L, Wang Q, Yin P, Serum metabolomics reveals the deregulation of fatty acids metabolism in hepatocellular carcinoma and chronic liver diseases: Anal Bioanal Chem, 2012; 403(1); 203-13, pmid: 22349331
23. Everts B, Metabolomics in immunology research: Methods Mol Biol, 2018; 1730; 29-42, pmid: 29363063
24. Baumann AK, Schlue J, Noyan F, Preferential accumulation of T helper cells but not cytotoxic T cells characterizes benign subclinical rejection of human liver allografts: Liver Transpl, 2016; 22(7); 943-55, pmid: 26929119
25. Yang Z, Matteson EL, Goronzy JJ, Weyand CM, T-cell metabolism in autoimmune disease: Arthritis Res Ther, 2015; 17; 29, pmid: 25890351
26. Powell JD, Delgoffe GM, The mammalian target of rapamycin: Linking T cell differentiation, function, and metabolism: Immunity, 2010; 33(3); 301-11, pmid: 20870173
27. , Terminology for hepatic allograft rejection. International Working Party: Hepatology, 1995; 22(2); 648-54, pmid: 7635435
28. Jernigan TW, Fabian TC, Croce MA, Staged management of giant abdominal wall defects: acute and long-term results: Ann Surg, 2003; 238(3); 349-55, pmid: 14501501 discussion 355–57
29. Zhu J, Djukovic D, Deng L, Colorectal cancer detection using targeted serum metabolic profiling: J Proteome Res, 2014; 13(9); 4120-30, pmid: 25126899
30. Skill NJ, Theodorakis NG, Wang YN, Role of cyclooxygenase isoforms in prostacyclin biosynthesis and murine prehepatic portal hypertension: Am J Physiol Gastrointest Liver Physiol, 2008; 295(5); G953-64, pmid: 18772366
31. Jeong SW, Jang JY, Lee SH, Increased expression of cyclooxygenase-2 is associated with the progression to cirrhosis: Korean J Intern Med, 2010; 25(4); 364-71, pmid: 21179273
32. Deshpande R, Mansara P, Kaul-Ghanekar R, Alpha-linolenic acid regulates Cox2/VEGF/MAP kinase pathway and decreases the expression of HPV oncoproteins E6/E7 through restoration of p53 and Rb expression in human cervical cancer cell lines: Tumour Biol, 2016; 37(3); 3295-305, pmid: 26440049
33. Steer P, Vessby B, Lind L, Endothelial vasodilatory function is related to the proportions of saturated fatty acids and alpha-linolenic acid in young men, but not in women: Eur J Clin Invest, 2003; 33(5); 390-96, pmid: 12713452
34. Martelius TJ, Wolff H, Bruggeman CA, Induction of cyclo-oxygenase-2 by acute liver allograft rejection and cytomegalovirus infection in the rat: Transpl Int, 2002; 15(12); 610-14, pmid: 12478407
35. Motino O, Frances DE, Casanova N, Protective role of hepatocyte cyclooxygenase-2 expression against liver ischemia-reperfusion injury in mice: Hepatology, 2018 [Epub ahead of print]
36. Ma N, Szabolcs MJ, Sun J, The effect of selective inhibition of cyclooxygenase (COX)-2 on acute cardiac allograft rejection: Transplantation, 2002; 74(11); 1528-34, pmid: 12490785
37. Cicchetti F, Drouin-Ouellet J, Gross RE, Environmental toxins and Parkinson’s disease: What have we learned from pesticide-induced animal models?: Trends Pharmacol Sci, 2009; 30(9); 475-83, pmid: 19729209
38. Hague SM, Klaffke S, Bandmann O, Neurodegenerative disorders: Parkinson’s disease and Huntington’s disease: J Neurol Neurosurg Psychiatry, 2005; 76(8); 1058-63, pmid: 16024878
39. Pardo LM, van Duijn CM, In search of genes involved in neurodegenerative disorders: Mutat Res, 2005; 592(1–2); 89-101, pmid: 16009383
40. Horrobin DF, Loss of delta-6-desaturase activity as a key factor in aging: Med Hypotheses, 1981; 7(9); 1211-20, pmid: 6270521
41. Kroger J, Schulze MB, Recent insights into the relation of Delta5 desaturase and Delta6 desaturase activity to the development of type 2 diabetes: Curr Opin Lipidol, 2012; 23(1); 4-10, pmid: 22123669
42. Abel S, De Kock M, van Schalkwyk DJ, Altered lipid profile, oxidative status and hepatitis B virus interactions in human hepatocellular carcinoma: Prostaglandins Leukot Essent Fatty Acids, 2009; 81(5–6); 391-99, pmid: 19782547
43. Araya J, Rodrigo R, Pettinelli P, Decreased liver fatty acid delta-6 and delta-5 desaturase activity in obese patients: Obesity (Silver Spring), 2010; 18(7); 1460-63, pmid: 19875987
44. Cai J, Jiang WG, Mansel RE, Inhibition of the expression of VE-cadherin/catenin complex by gamma linolenic acid in human vascular endothelial cells, and its impact on angiogenesis: Biochem Biophys Res Commun, 1999; 258(1); 113-18, pmid: 10222244
45. Fang XL, Shu G, Zhang ZQ, Roles of alpha-linolenic acid on IGF-I secretion and GH/IGF system gene expression in porcine primary hepatocytes: Mol Biol Rep, 2012; 39(12); 10987-96, pmid: 23053988
46. Barcelo-Coblijn G, Murphy EJ, Alpha-linolenic acid and its conversion to longer chain n-3 fatty acids: Benefits for human health and a role in maintaining tissue n-3 fatty acid levels: Prog Lipid Res, 2009; 48(6); 355-74, pmid: 19619583
47. Zhang W, Wang R, Han SF, Alpha-linolenic acid attenuates high glucose-induced apoptosis in cultured human umbilical vein endothelial cells via PI3K/Akt/eNOS pathway: Nutrition, 2007; 23(10); 762-70, pmid: 17716867
48. Lewin M, Samuel S, Merkel J, Bickler P, Varespladib (LY315920) appears to be a potent, broad-spectrum, inhibitor of snake venom phospholipase A2 and a possible pre-referral treatment for envenomation: Toxins (Basel), 2016; 8(9) pii: E248
49. Thotala D, Craft JM, Ferraro DJ, Cytosolic phospholipaseA2 inhibition with PLA-695 radiosensitizes tumors in lung cancer animal models: PLoS One, 2013; 8(7); e69688, pmid: 23894523
50. Lee KL, Foley MA, Chen L, Discovery of Ecopladib, an indole inhibitor of cytosolic phospholipase A2alpha: J Med Chem, 2007; 50(6); 1380-400, pmid: 17305324
51. Theodorakis NG, Wang YN, Skill NJ, The role of nitric oxide synthase isoforms in extrahepatic portal hypertension: Studies in gene-knockout mice: Gastroenterology, 2003; 124(5); 1500-8, pmid: 12730888
52. Theodorakis NG, Wang YN, Wu JM, Role of endothelial nitric oxide synthase in the development of portal hypertension in the carbon tetrachloride-induced liver fibrosis model: Am J Physiol Gastrointest Liver Physiol, 2009; 297(4); G792-99, pmid: 19628654
53. Li H, Forstermann U, Pharmacological prevention of eNOS uncoupling: Curr Pharm Des, 2014; 20(22); 3595-606, pmid: 24180386
54. Lei S, Huang F, Zhao A, The ratio of dihomo-gamma-linolenic acid to deoxycholic acid species is a potential biomarker for the metabolic abnormalities in obesity: FASEB J, 2017; 31(9); 3904-12, pmid: 28490483
55. Matsuda M, Kawamoto T, Tamura R, Predictive value of serum dihomo-gamma-linolenic acid level and estimated Delta-5 desaturase activity in patients with hepatic steatosis: Obes Res Clin Pract, 2017; 11(1); 34-43, pmid: 26964726
56. Fragkos KC, Forbes A, Citrulline as a marker of intestinal function and absorption in clinical settings: A systematic review and meta-analysis: United European Gastroenterol J, 2018; 6(2); 181-91
57. Crenn P, Coudray-Lucas C, Thuillier F, Postabsorptive plasma citrulline concentration is a marker of absorptive enterocyte mass and intestinal failure in humans: Gastroenterology, 2000; 119(6); 1496-505, pmid: 11113071
58. Meeks AC, Madill J, Sarcopenia in liver transplantation: A review: Clin Nutr ESPEN, 2017; 22; 76-80, pmid: 29415839
59. Ogawa SBody weight and bone/calcium metabolism. Sarcopenia and its relationship with bone and calcium metabolism: Clin Calcium, 2018; 28(7); 907-12, pmid: 29950542 [in Japanese]
60. Barillaro C, Liperoti R, Martone AM, The new metabolic treatments for sarcopenia: Aging Clin Exp Res, 2013; 25(2); 119-27, pmid: 23739896
61. Ter Borg S, de Groot LC, Mijnarends DM, Differences in nutrient intake and biochemical nutrient status between sarcopenic and nonsarcopenic older adults-results from the Maastricht Sarcopenia Study: J Am Med Dir Assoc, 2016; 17(5); 393-401, pmid: 26825685
62. Gu DH, Kim MY, Seo YS, Clinical usefulness of psoas muscle thickness for the diagnosis of sarcopenia in patients with liver cirrhosis: Clin Mol Hepatol, 2018; 24(3); 319-30, pmid: 29706058
63. Mangus RS, Bush WJ, Miller C, Severe sarcopenia and increased fat stores in pediatric patients with liver, kidney, or intestine failure: J Pediatr Gastroenterol Nutr, 2017; 65(5); 579-83, pmid: 28604513
64. Kaizu T, Ikeda A, Nakao A, Donor graft adenoviral iNOS gene transfer ameliorates rat liver transplant preservation injury and improves survival: Hepatology, 2006; 43(3); 464-73, pmid: 16496305
In Press
Original article
Steroid Use in ABO-Incompatible Kidney Transplants: Withdrawal vs MaintenanceAnn Transplant In Press; DOI: 10.12659/AOT.947747
Original article
Intra-Arterial Contrast-Enhanced Ultrasound for Transcatheter Thrombolysis in Post-Transplant Hepatic Arter...Ann Transplant In Press; DOI: 10.12659/AOT.947500
Original article
Early Atropine Protocol Enhances Dobutamine Stress Echocardiography in End-Stage Liver Disease: A Practical...Ann Transplant In Press; DOI: 10.12659/AOT.950166
Most Viewed Current Articles
15 Aug 2023 : Review article 7,362
Free-Circulating Nucleic Acids as Biomarkers in Patients After Solid Organ TransplantationDOI :10.12659/AOT.939750
Ann Transplant 2023; 28:e939750
03 Jan 2023 : Original article 7,247
Impact of Autologous Stem Cell Transplantation on Primary Central Nervous System Lymphoma in First-Line and...DOI :10.12659/AOT.938467
Ann Transplant 2023; 28:e938467
16 May 2023 : Original article 7,067
Breaking Antimicrobial Resistance: High-Dose Amoxicillin with Clavulanic Acid for Urinary Tract Infections ...DOI :10.12659/AOT.939258
Ann Transplant 2023; 28:e939258
28 May 2024 : Original article 6,667
Effect of Dexmedetomidine Combined with Remifentanil on Emergence Agitation During Awakening from Sevoflura...DOI :10.12659/AOT.943281
Ann Transplant 2024; 29:e943281
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About Ann Transplant

eISSN: 2329-0358
Annals of Transplantation is one of the fast-developing journals open to all scientists and fields of transplant medicine and related research. The journal is published quarterly and provides extensive coverage of the most important advances in transplantation. Using an electronic on-line submission and peer review tracking system, Annals of Transplantation is committed to rapid review and publication.
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About Ann Transplant

eISSN: 2329-0358
Annals of Transplantation is one of the fast-developing journals open to all scientists and fields of transplant medicine and related research. The journal is published quarterly and provides extensive coverage of the most important advances in transplantation. Using an electronic on-line submission and peer review tracking system, Annals of Transplantation is committed to rapid review and publication.
Categories
ISI Journals
Publisher
International Scientific Information, Inc.
150 Broadhollow Rd., Suite 114
Melville, NY, 11747 | USA
phone:
1.631.629.4327
e-mail:
[email protected]
www:
www.isi-science.com
Information
Copyright © 2025
International Scientific Infromation, Inc.
All rights reserved.
About Ann Transplant

eISSN: 2329-0358
Annals of Transplantation is one of the fast-developing journals open to all scientists and fields of transplant medicine and related research. The journal is published quarterly and provides extensive coverage of the most important advances in transplantation. Using an electronic on-line submission and peer review tracking system, Annals of Transplantation is committed to rapid review and publication.
Categories
Information
Copyright © 2002 - 2025
International Scientific
Infromation, Inc.
All rights reserved.
Links
Publisher
International Scientific Information, Inc.
150 Broadhollow Rd., Suite 114
Melville, NY, 11747 | USA
phone:
1.631.629.4327
e-mail:
[email protected]
www:
www.isi-science.com
In Press
Original article
Steroid Use in ABO-Incompatible Kidney Transplants: Withdrawal vs MaintenanceAnn Transplant In Press; DOI: 10.12659/AOT.947747
Original article
Intra-Arterial Contrast-Enhanced Ultrasound for Transcatheter Thrombolysis in Post-Transplant Hepatic Arter...Ann Transplant In Press; DOI: 10.12659/AOT.947500
Original article
Early Atropine Protocol Enhances Dobutamine Stress Echocardiography in End-Stage Liver Disease: A Practical...Ann Transplant In Press; DOI: 10.12659/AOT.950166
Most Viewed Current Articles
15 Aug 2023 : Review article 7,362
Free-Circulating Nucleic Acids as Biomarkers in Patients After Solid Organ TransplantationDOI :10.12659/AOT.939750
Ann Transplant 2023; 28:e939750
03 Jan 2023 : Original article 7,247
Impact of Autologous Stem Cell Transplantation on Primary Central Nervous System Lymphoma in First-Line and...DOI :10.12659/AOT.938467
Ann Transplant 2023; 28:e938467
16 May 2023 : Original article 7,067
Breaking Antimicrobial Resistance: High-Dose Amoxicillin with Clavulanic Acid for Urinary Tract Infections ...DOI :10.12659/AOT.939258
Ann Transplant 2023; 28:e939258
28 May 2024 : Original article 6,667
Effect of Dexmedetomidine Combined with Remifentanil on Emergence Agitation During Awakening from Sevoflura...DOI :10.12659/AOT.943281
Ann Transplant 2024; 29:e943281
Your Privacy
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About Ann Transplant

eISSN: 2329-0358
Annals of Transplantation is one of the fast-developing journals open to all scientists and fields of transplant medicine and related research. The journal is published quarterly and provides extensive coverage of the most important advances in transplantation. Using an electronic on-line submission and peer review tracking system, Annals of Transplantation is committed to rapid review and publication.
Categories
ISI Journals
Publisher
International Scientific Information, Inc.
150 Broadhollow Rd., Suite 114
Melville, NY, 11747 | USA
phone:
1.631.629.4327
e-mail:
[email protected]
www:
www.isi-science.com
Information
Copyright © 2025
International Scientific Infromation, Inc.
All rights reserved.
About Ann Transplant

eISSN: 2329-0358
Annals of Transplantation is one of the fast-developing journals open to all scientists and fields of transplant medicine and related research. The journal is published quarterly and provides extensive coverage of the most important advances in transplantation. Using an electronic on-line submission and peer review tracking system, Annals of Transplantation is committed to rapid review and publication.
Categories
ISI Journals
Publisher
International Scientific Information, Inc.
150 Broadhollow Rd., Suite 114
Melville, NY, 11747 | USA
phone:
1.631.629.4327
e-mail:
[email protected]
www:
www.isi-science.com
Information
Copyright © 2025
International Scientific Infromation, Inc.
All rights reserved.
About Ann Transplant

eISSN: 2329-0358
Annals of Transplantation is one of the fast-developing journals open to all scientists and fields of transplant medicine and related research. The journal is published quarterly and provides extensive coverage of the most important advances in transplantation. Using an electronic on-line submission and peer review tracking system, Annals of Transplantation is committed to rapid review and publication.
Categories
Information
Copyright © 2002 - 2025
International Scientific
Infromation, Inc.
All rights reserved.
Links
Publisher
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Melville, NY, 11747 | USA
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Abstract
BACKGROUND: Acute liver rejection (ALR), a significant complication of liver transplantation, burdens patients, healthcare payers, and the healthcare providers due to an increase in morbidity, cost, and resources. Despite clinical resolution, ALR is associated with an increased risk of graft loss. A unique protocol of delayed immunosuppression used in our institute provided a model to characterize metabolomic profiles in human ALR.
MATERIAL AND METHODS: Twenty liver allograft biopsies obtained 48 hours after liver transplantation in the absence of immunosuppression were studied. Hepatic metabolites were quantitated in these biopsies by liquid chromatography and mass spectroscopy (LC/MS). Metabolite profiles were compared among: 1) biopsies with reperfusion injury but no histological evidence of rejection (n=7), 2) biopsies with histological evidence of moderate or severe rejection (n=5), and 3) biopsies with histological evidence of mild rejection (n=8).
RESULTS: There were 133 metabolites consistently detected by LC/MS and these were prioritized using variable importance to projection (VIP) analysis, comparing moderate or severe rejection vs. no rejection or mild rejection using partial least squares discriminant statistical analysis (PLS-DA). Twenty metabolites were identified as progressively different. Further PLS-DA using these metabolites identified 3 metabolites (linoleic acid, γ-linolenic acid, and citrulline) which are associated with either cyclooxygenase or nitric oxide synthase functionality.
CONCLUSIONS: Hepatic metabolic aberrancies associated with cyclooxygenase and nitric oxide synthase function occur contemporaneous with ALR. Additional studies are required to better characterize the role of these metabolic pathways to enhance utility of the metabolomics approach in diagnosis and outcomes of ALR.
Keywords: Graft Rejection, Liver Transplantation, Metabolomics, Nitric Oxide Synthase, Prostaglandin-Endoperoxide Synthases, End stage liver disease, Liver
Background
Acute liver rejection (ALR) following liver transplantation occurs in approximately 4–20% of patients [1,2]. According to the United Network for Organ Sharing (UNOS), in 2017 the number of liver transplants performed in the USA was 8082, representing an increase of 24.5% since 2016. Currently, the number of patients waiting for liver transplant is approximately 13 914 and the average waiting time for liver transplant is 511 days. Therefore, although the incidence of acute liver rejection is low, the high volume of transplants coupled with increased frequency and limited donors encourages the maximization of graft survival by addressing ALR, a major cause of graft damage.
This study aimed to characterize metabolomic aberrancies in a human model of liver rejection to guide future studies aimed at addressing graft damage congruent with ALR. Between 2008 and 2012, the standard immunosuppression protocol for patients receiving liver transplants at Indiana University Hospital was begun 2 days following transplant and prior to collection of liver biopsy at the time of fascial closure. The hypothesis was that a delay in immunosuppression would induce tolerance [3]. This immunosuppression delay protocol coupled with the collection of a fascial closure biopsy provides an opportunity to characterize ALR consequences in a human model of early liver rejection, specifically to utilize a targeted liquid chromatography/mass spectrometry (LC/MS) platform for metabolomics to profile and quantify hepatic metabolites in order to identify metabolic signatures associated with ALR.
Metabolomics is the study of a large number of small molecule metabolites in biofluids and tissue to identify biomarkers associated with altered metabolic pathways. As metabolites are modulated by protein and enzymatic function, they reflect many of the alterations caused by disease or other biological stresses. Metabolites are exquisitely sensitive to different biological states and therefore represent a promising approach to identify biopathology contemporaneous with rejection [4–6]. Several analytical techniques such as nuclear magnetic resonance (NMR), LC-MS, and gas chromatography-mass spectrometry (GC-MS) have been used to detect metabolic changes [7]. Several studies have used a variety of analytical techniques to elucidate aberrant pathways associated with cancer [8]. While a few of these studies have used animal models [9–11], the majority have focused on humans [4,10,12–22] using NMR [4,16], LC-MS [12,13,15,17,21,22], and GC-MS [13–15,18,19], or HPLC methods [20]. These studies have reported alterations in numerous metabolic pathways, including glycolysis, amino acid, fatty acid, and bile acid metabolism. While there are few reports that have focused exclusively on altered metabolic pathways associated with liver rejection, there have been studies relating to rejection-associated events. Previous reports have documented metabolic pathways and individual metabolites that modulate immune cell function and immune responses [23]. For example, modulation of T cells has been well documented in conjunction with rejection, as has the role of metabolism and nutrient availability upon T cell activation and function [5,24]. Moreover, activation of T cells requires metabolic reprogramming in order to increase glycolytic flux, lactate, lipids, proteins, nucleic acid, and carbohydrates [25]. These changes in metabolic profiles also direct signaling. For example, increased intracellular leucine metabolism controls mammalian target of rapamycin (mTOR) signaling required to induce Th1, Th2, and Th17 CD4(+) T effector cell differentiation [26]. Therefore, there is a need to better understand changes in hepatic biochemical pathways associated with rejection, and metabolomics is an established analytical modality available to identify key compounds. Focusing on hepatic tissue prior to immunosuppression in patients provides a unique opportunity to improve our understanding of graft damage and loss.
Material and Methods
PATIENTS AND PROCEDURES:
In all liver transplants, the muscle layer was left open and skin was closed immediately after transplantation to prevent compartment syndrome. All patients were taken back to the operating room for delayed fascial closure on the 2nd post-transplant day [28]. During fascial closure, a second allograft biopsy was performed. A part of the second liver allograft biopsy was frozen for future use. Patients did not receive any immunosuppression prior to fascial closure [3]. For the purpose of this study, the day 2 biopsies were divided in to 3 groups (n=5–8 per group): Group 1 (control), patients with no evidence of rejection; Group 2, patients with histological evidence of mild rejection; and Group 3, patients with evidence of moderate or severe rejection. To evaluate the metabolic changes associated with liver rejection, we performed LC-MS analysis, targeting 216 metabolites in liver biopsies taken 2 days after liver transplantation.
IMMUNOSUPPRESSION PROTOCOL:
The induction immunosuppression consisted of 3 doses of 2 mg/kg rabbit anti-thymocyte globulin (rATG) every 48 hours starting on post-transplant day 2 along with a single dose of 1.5 mg/m2 BSA of rituximab on post-transplant day 3. Premedication for rATG was given immediately before its administration in the form of solumedrol [500 (first dose), 250 (second dose), and 120 mg (third dose)], acetaminophen (650 mg), and diphenhydramine (25 mg). Maintenance immunosuppression was also initiated on post-transplant day 2 in the form of tacrolimus monotherapy, although some recipients received additional mycophenolate mofetil. The goal trough levels for tacrolimus were 7 to 10 ng/mL in the first 3 months and 6 to 8 ng/mL thereafter [3].
LC/MS:
Day 2 liver allograft biopsies were frozen in liquid nitrogen and stored at −86°C. Tissue was transported on dry ice to the Northwest Metabolomics Research Center (NW-MRC) at the University of Washington for analysis. Briefly, targeted LC/MS/MS was performed according to methods developed at the University of Washington Metabolomic Research Center as per Zhu et al. [29] Targeted aqueous metabolite profiling analysis was performed using an Agilent 1260/AB-Sciex 5500 Qtrap Liquid Chromatography-Mass spectroscopy/mass spectroscopy (LC-MS/MS) instrument and standard operating procedures we developed previously [29]. The LC-MS/MS analysis is based on hydrophilic interaction chromatography (HILIC), and targets 216 metabolites located in more than 35 different metabolic pathways. This system provides detailed information on metabolites involved in glycolysis, tricarboxylic acid cycle (TCA), and pentose phosphate shunt, as well as amino acid, fatty acid, and nucleic acid metabolism, and other pathways. Twenty-six isotope-labeled internal standards were included to monitor sample preparation steps and system performance, as well as to provide absolute quantitation of a number of amino and organic acids.
DATA ANALYSIS FOR METABOLOMICS:
The intensity of tissue peaks in each data set were normalized to tissue weight. Statistical analysis was performed using XLSTAT software. Each data set was mean-centered before the analysis. Univariate analysis of the individual metabolites was performed using the
Results
HISTOLOGICAL EVIDENCE OF REJECTION:
Of the 60 patients recruited and transplanted, routine pathology reports described histological evidence of rejection in 14 patients (23%). Biopsies were stratified based on these reports into 3 groups: 1) no histological evidence of rejection, 2) evidence of mild rejection, and 3) patients with evidence of moderate or severe rejection. Seven samples from each group were selected for pathology review and metabolomic analysis. A pathologist (RS) reviewed all 21 fascial closure liver biopsies taken 2 days post-transplant. Her analysis found 5 biopsies had unequivocal evidence of moderate or severe rejection (endothelialitis, cell infiltration, or bile duct injury). Seven biopsies had no evidence of rejection but had reperfusion damage. One sample was indeterminable, did not reach criteria for rejection, and had no reperfusion injury. The remaining 8 biopsies had histological evidence of mild rejection. The 1 biopsy that was indeterminable was not included in either rejection or control groups and data were not included in the metabolomic analysis.
The biopsies in the rejection group were characterized by the presence of a mixed inflammatory infiltrate in portal tracts that comprised variable combinations of lymphocytes, eosinophils, and neutrophils. Endothelialitis and bile duct damage were present in varying degrees of severity. Control biopsies showed features of reperfusion damage that included variable combinations and severity of portal edema, peribiliary neutrophils, perivenular hepatocellular necrosis, and presence of lobular neutrophils. One biopsy showed mild macro-vesicular steatosis with necrosis and neutrophils. The biopsies were characterized into 3 groups for the purpose of metabolomic analysis: Group 1 was reperfusion injury only (N=7), Group 2 was categorical histological evidence of moderate or severe rejection (N=5), and Group 3 was histological evidence of mild rejection (N=8).
LC/MS-BASED METABOLOMICS:
The LC-MS/MS method was optimized to target a total of 216 metabolites in the liver biopsy samples. However, after deleting metabolites that were not detected, metabolites below the signal to noise cutoff, and metabolites inconsistently detected in the samples, 133 metabolites were quantified. We assessed and compared differences in metabolites between 1) biopsies with mild rejection or with moderate or severe rejection when compared to tissues with reperfusion injury and 2) biopsies with mild rejection when compared to biopsies with moderate or severe rejection. Each metabolite was ranked by its variable importance in the projection (VIP) score via partial least squares- discriminative analysis (PLS-DA) using XLSTAT Biomed software (Figure 1). Twenty-one metabolites with VIP scores above 1.5 were included in a secondary PLS-DA analysis comparing no rejection (reperfusion injury) to both moderate to severe rejection (Figure 2A) and mild rejection (Figure 2B). Of these metabolites, linoleic acid, γ-linolenic acid, and citrulline emerged as providing the strongest predictive model of rejection (Figure 2). The differences between these metabolites in rejection (mild, moderate, and severe) and control biopsies were examined individually (Figure 3). They were then used to construct a final sample model by PLS-DA. Cross-validation of this model was then used to estimate how closely the 3 metabolites, taken as a group, correlate with the biopsy histology report from the pathologist (RS) (Figure 4). The resulting aggregate indicates that, taken together, the 3 metabolites can accurately identify the rejection status of each patient in our sample group, and that this is likely to be the case for independent samples.
Discussion
This study represents a unique model of human liver rejection due to the unique immunosuppression and surgical protocol that was followed. There are no previously published data on human liver rejection in this setting. In the absence of immunosuppression, changes occurring in the liver biopsies in the setting of cellular rejection are novel and intriguing. Using 2-day protocol liver biopsies, targeted LC/MS-based metabolomics analysis, and PLS-DA, we identified 3 aberrant metabolites (linolenic acid, γ-linolenic acid, and citrulline) contemporaneous with liver rejection.
LC/MS/MS-based metabolomics provides broad-based coverage of the important small molecule metabolites in biofluids and tissue to allow the identification of altered metabolic pathways. As metabolites are modulated by protein function, they reflect many of the alterations caused by disease or other biological stresses [4–6]. Analysis using PLS-DA is appropriate when large numbers of potentially correlated variables must be analyzed. It is especially well suited to cases where the number of variables exceeds the number of samples, which would otherwise produce overfitting using conventional regression models. We used VIP scores, which represent the effect of a particular variable on the PLS-DA model, to eliminate non-predictive variables from our dataset, and to identify the variables with the highest degree of predictive power at the level of individual patients. This analysis revealed 3 metabolites: linoleic acid, γ linolenic acid, and citrulline. Linoleic acid and γ-linolenic acid are associated with cyclooxygenase (COX) pathways, while citrulline is associated with nitric oxide synthase (NOS) pathways.
Linoleic acid is an octadecadeinoic fatty acid and a precursor for arachidonic acid, which is a substrate for COX enzymes and subsequent biosynthesis of vasoactive molecules. Changes in arachidonic acid are linked to numerous pathologies of the liver, including portal hypertension and liver cirrhosis [30,31]. Linoleic acid regulates the COX-2/VEGF/MAP kinase pathway [32] and endothelial vasodilatory function [33]. Studies have shown that COX-2 was significantly increased in a rodent model of liver rejection [34]. However, whether increased COX is beneficial or not is controversial. Some studies have shown that increased COX-2 is protective [35], while others have found that inhibition of COX-2 increases graft survival in animal models [34,36]. Moreover, linoleic acid is also associated with pathologies independent of COX, as it is synthesized from phosphatidylcholine via phospholipase A2 or phospholipase A1. Aberrancies of phospholipase A2 are associated with Parkinson disease, peroxisomal beta-oxidation enzyme deficiency, neurodegeneration with brain iron accumulation, and peroxisomal acyl-CoA oxidase deficiency [37,39].
The second metabolite identified by PLS-DA was γ-linolenic acid, which is an all-cis-6,9,12-octadecatrienoic acid designated as 18: 3 and is synthesized from linoleic acid by introduction of a (third) double bond at the delta 6 position under the catalytic influence of delta-6-desaturase enzyme. This step is believed to be the rate-limiting stage in the metabolic pathway. Aging, obesity, diabetes, high alcohol intake, stress-related hormones, and viral infections are known to reduce conversion of linoleic acid to γ-linolenic acid [40–43]. γ-linolenic acid is known to inhibit angiogenesis, partly via the decrease in the expression of VE-cadherin and beta-catenin [44], potentially due to the elimination of the precursor, -linoleic acid. Hepatocyte expression of insulin growth factor-I, insulin growth factor-II, growth hormone receptor, insulin receptor, Insulin growth factor binding protein-3, and Insulin growth factor binding protein-4 mRNAs are all upregulated by linoleic acid [45]. Conversion of linoleic acid to γ-linolenic acid is known to be beneficial for human health [46]. Linolenic acid attenuates endothelial apoptosis
The third metabolite identified by PLS-DA was citrulline, a key intermediate in the urea cycle produced via the metabolism of ornithine and carbamoyl phosphate. Moreover, citrulline is a by-product of the enzymatic production of nitric oxide from the amino acid arginine. As citrulline is a part of the urea cycle and urea is a marker of liver failure, it is not unexpected that rejection is associated with increased citrulline. However, urea levels were not significantly higher in patients with rejection. Because citrulline is involved in many biological pathways, it is impossible to accurately hypothesize the pathobiology, physiological, and biochemical milieu associated with changes to hepatic linoleic acid, γ-linoleic acid and citrulline based on biopsies. However, the fact that they are connected to important hepatic perfusion regulators suggests that changes impart/reflect a response to tissue stress, damage, and/or acute graft rejection. Arginine is the predominate substrate for the production of nitric oxide (NO), a well-documented vasodilator associated with liver perfusion and portal hypertension [51,52]. The role of NO in liver perfusion is well documented and focuses on sinusoidal stellate cell control of sinusoidal dilation and thus an increase in resistance to portal venous blood flow. A reduction in citrulline might be indicative of a modulation of NO biosynthesis. Reduced citrulline could be reflective of a reduction of NOS activity, as citrulline is the biproduct of the conversion of arginine to NO. In contrast, as citrulline is also the substrate, a reduction could be indicative of an increase in NOS activity. What we do know is that a change in NO within the liver will modulate perfusion and affect ischemia and hypoxia and impart an additional stress to the liver. Moreover, endothelial NOS (eNOS) is also known to “uncouple” when co-factors are absent, leading to the formation of oxygen free radicals [53]. The conversion of arginine to NO and citrulline is a 2-step process involving N-hydroxy-l-arginine as an intermediate; therefore, uncoupling of endothelial NOS could result in a reduction in citrulline.
The data do not suggest that either linolenic acid or citrulline should replace current markers of acute liver rejection. LC-MS/MS is unlikely to be quicker or cheaper than histology and liver functional tests. Nevertheless, there is utility in investigating linolenic acid and citrulline, as both have been shown to be markers of interest in other pathologies. For example, the ratio of linolenic acid to deoxycholic acid species is a potential biomarker for metabolic abnormalities in obesity [54] and hepatic steatosis [55]. Moreover, the circulating citrulline concentration is a biomarker of intestinal functionality [56,57]. What the data may reveal is hepatic response to acute liver rejection by the modulation of vasodilators to maintain liver perfusion. However, we are cognizant that differences in metabolomics signatures between control livers and livers with rejection could be independent of rejection. It is possible that these differences are linked to other aspects of liver disease. For example, sarcopenia, which is associated with modulated metabolism, poorer outcomes, and changes in the levels of citrulline and linoleic acid, occurs in patients with liver disease [58–61]. A preliminary analysis of sarcopenia in the patients within this study, based on measurement of the psoas muscle at the C3, as previously described [62,63], was performed and identified 3 patients with sarcopenia. Two patients within the early rejection group had sarcopenia. One patient with no evidence of rejection was identified with sarcopenia. Because the frequency of overlapping sarcopenia within the 3 cohorts is sporadic, it is difficult to determine if sarcopenia is an independent variable in hepatic metabolites associated with hepatic response to rejection.
Additional research is required to further elucidate our findings and to better understand any connection among metabolic changes, acute liver rejection, and graft survival. Further research is likely to focus on metabolomic quantification post-transplant in rodent models of liver rejection [64]. This is because rejection rates observed in clinical programs are very low; therefore, to expand this project using patient samples only would be prohibitive. Moreover, the delayed immunosuppression protocol is controversial and delayed immunosuppression and 2-day protocol biopsies are not the standard of care at our institute at present.
Finally, the immunosuppression protocol deserves further explanation. The premise behind delayed introduction of immunosuppression was to allow immune activation of recipient lymphocytes in the allograft. It was thought that the potent rATG would then lead to apoptosis and death of recipient lymphocytes within the graft, allowing operational tolerance in the long term. Although this approach permits a degree of rejection in the allograft, this is a desired effect and has no adverse effects in the long term, which was demonstrated in our larger study involving 1000 patients [3]. Based on this large-sample experience, we do not believe that deaths that occurred in this study cohort were due to the delayed immunosuppression.
Conclusions
Contemporaneous with acute liver rejection, increases in linoleic acid and γ-linolenic acid are observed alongside a decrease in citrulline. These metabolites are connected to pathways that regulate liver perfusion.
References
1. Au KP, Chan SC, Chok KS, Clinical factors affecting rejection rates in liver transplantation: Hepatobiliary Pancreat Dis Int, 2015; 14(4); 367-73, pmid: 26256080
2. Neil DA, Hubscher SG, Current views on rejection pathology in liver transplantation: Transpl Int, 2010; 23(10); 971-83, pmid: 20723179
3. Mangus RS, Fridell JA, Vianna RM, Immunosuppression induction with rabbit anti-thymocyte globulin with or without rituximab in 1000 liver transplant patients with long-term follow-up: Liver Transpl, 2012; 18(7); 786-95, pmid: 22237953
4. Gao H, Lu Q, Liu X, Application of 1H NMR-based metabonomics in the study of metabolic profiling of human hepatocellular carcinoma and liver cirrhosis: Cancer Sci, 2009; 100(4); 782-85, pmid: 19469021
5. Mayr M, Metabolomics: Ready for the prime time?: Circ Cardiovasc Genet, 2008; 1(1); 58-65, pmid: 20031543
6. Zhang J, Liu L, Wei S, Metabolomics study of esophageal adenocarcinoma: J Thorac Cardiovasc Surg, 2011; 141(2); 469-75, pmid: 20880550
7. Gowda GA, Zhang S, Gu H, Metabolomics-based methods for early disease diagnostics: Expert Rev Mol Diagn, 2008; 8(5); 617-33, pmid: 18785810
8. Bowers J, Hughes E, Skill N, Detection of hepatocellular carcinoma in hepatitis C patients: biomarker discovery by LC-MS: J Chromatogr B Analyt Technol Biomed Life Sci, 2014; 966; 154-62
9. Li S, Liu H, Jin Y, Metabolomics study of alcohol-induced liver injury and hepatocellular carcinoma xenografts in mice: J Chromatogr B Analyt Technol Biomed Life Sci, 2011; 879(24); 2369-75
10. Tan Y, Yin P, Tang L, Metabolomics study of stepwise hepatocarcinogenesis from the model rats to patients: potential biomarkers effective for small hepatocellular carcinoma diagnosis: Mol Cell Proteomics, 2012; 11(2); M111.010694
11. Wang J, Zhang S, Li Z, (1)H-NMR-based metabolomics of tumor tissue for the metabolic characterization of rat hepatocellular carcinoma formation and metastasis: Tumour Biol, 2011; 32(1); 223-31, pmid: 20890798
12. Chen F, Xue J, Zhou L, Identification of serum biomarkers of hepatocarcinoma through liquid chromatography/mass spectrometry-based metabonomic method: Anal Bioanal Chem, 2011; 401(6); 1899-904, pmid: 21833635
13. Chen T, Xie G, Wang X, Serum and urine metabolite profiling reveals potential biomarkers of human hepatocellular carcinoma: Mol Cell Proteomics, 2011; 10(7); M110.004945
14. Lin X, Zhang Y, Ye G, Classification and differential metabolite discovery of liver diseases based on plasma metabolic profiling and support vector machines: J Sep Sci, 2011; 34(21); 3029-36, pmid: 21919198
15. Patterson AD, Maurhofer O, Beyoglu D, Aberrant lipid metabolism in hepatocellular carcinoma revealed by plasma metabolomics and lipid profiling: Cancer Res, 2011; 71(21); 6590-600, pmid: 21900402
16. Shariff MI, Gomaa AI, Cox IJ, Urinary metabolic biomarkers of hepatocellular carcinoma in an Egyptian population: A validation study: J Proteome Res, 2011; 10(4); 1828-36, pmid: 21275434
17. Wang B, Chen D, Chen Y, Metabonomic profiles discriminate hepatocellular carcinoma from liver cirrhosis by ultraperformance liquid chromatography-mass spectrometry: J Proteome Res, 2012; 11(2); 1217-27, pmid: 22200553
18. Wu H, Xue R, Dong L, Metabolomic profiling of human urine in hepatocellular carcinoma patients using gas chromatography/mass spectrometry: Anal Chim Acta, 2009; 648(1); 98-104, pmid: 19616694
19. Xue R, Lin Z, Deng C, A serum metabolomic investigation on hepatocellular carcinoma patients by chemical derivatization followed by gas chromatography/mass spectrometry: Rapid Commun Mass Spectrom, 2008; 22(19); 3061-68, pmid: 18767022
20. Yang J, Xu G, Zheng Y, Diagnosis of liver cancer using HPLC-based metabonomics avoiding false-positive result from hepatitis and hepatocirrhosis diseases: J Chromatogr B Analyt Technol Biomed Life Sci, 2004; 813(1–2); 59-65
21. Yin P, Wan D, Zhao C, A metabonomic study of hepatitis B-induced liver cirrhosis and hepatocellular carcinoma by using RP-LC and HILIC coupled with mass spectrometry: Mol Biosyst, 2009; 5(8); 868-76, pmid: 19603122
22. Zhou L, Wang Q, Yin P, Serum metabolomics reveals the deregulation of fatty acids metabolism in hepatocellular carcinoma and chronic liver diseases: Anal Bioanal Chem, 2012; 403(1); 203-13, pmid: 22349331
23. Everts B, Metabolomics in immunology research: Methods Mol Biol, 2018; 1730; 29-42, pmid: 29363063
24. Baumann AK, Schlue J, Noyan F, Preferential accumulation of T helper cells but not cytotoxic T cells characterizes benign subclinical rejection of human liver allografts: Liver Transpl, 2016; 22(7); 943-55, pmid: 26929119
25. Yang Z, Matteson EL, Goronzy JJ, Weyand CM, T-cell metabolism in autoimmune disease: Arthritis Res Ther, 2015; 17; 29, pmid: 25890351
26. Powell JD, Delgoffe GM, The mammalian target of rapamycin: Linking T cell differentiation, function, and metabolism: Immunity, 2010; 33(3); 301-11, pmid: 20870173
27. , Terminology for hepatic allograft rejection. International Working Party: Hepatology, 1995; 22(2); 648-54, pmid: 7635435
28. Jernigan TW, Fabian TC, Croce MA, Staged management of giant abdominal wall defects: acute and long-term results: Ann Surg, 2003; 238(3); 349-55, pmid: 14501501 discussion 355–57
29. Zhu J, Djukovic D, Deng L, Colorectal cancer detection using targeted serum metabolic profiling: J Proteome Res, 2014; 13(9); 4120-30, pmid: 25126899
30. Skill NJ, Theodorakis NG, Wang YN, Role of cyclooxygenase isoforms in prostacyclin biosynthesis and murine prehepatic portal hypertension: Am J Physiol Gastrointest Liver Physiol, 2008; 295(5); G953-64, pmid: 18772366
31. Jeong SW, Jang JY, Lee SH, Increased expression of cyclooxygenase-2 is associated with the progression to cirrhosis: Korean J Intern Med, 2010; 25(4); 364-71, pmid: 21179273
32. Deshpande R, Mansara P, Kaul-Ghanekar R, Alpha-linolenic acid regulates Cox2/VEGF/MAP kinase pathway and decreases the expression of HPV oncoproteins E6/E7 through restoration of p53 and Rb expression in human cervical cancer cell lines: Tumour Biol, 2016; 37(3); 3295-305, pmid: 26440049
33. Steer P, Vessby B, Lind L, Endothelial vasodilatory function is related to the proportions of saturated fatty acids and alpha-linolenic acid in young men, but not in women: Eur J Clin Invest, 2003; 33(5); 390-96, pmid: 12713452
34. Martelius TJ, Wolff H, Bruggeman CA, Induction of cyclo-oxygenase-2 by acute liver allograft rejection and cytomegalovirus infection in the rat: Transpl Int, 2002; 15(12); 610-14, pmid: 12478407
35. Motino O, Frances DE, Casanova N, Protective role of hepatocyte cyclooxygenase-2 expression against liver ischemia-reperfusion injury in mice: Hepatology, 2018 [Epub ahead of print]
36. Ma N, Szabolcs MJ, Sun J, The effect of selective inhibition of cyclooxygenase (COX)-2 on acute cardiac allograft rejection: Transplantation, 2002; 74(11); 1528-34, pmid: 12490785
37. Cicchetti F, Drouin-Ouellet J, Gross RE, Environmental toxins and Parkinson’s disease: What have we learned from pesticide-induced animal models?: Trends Pharmacol Sci, 2009; 30(9); 475-83, pmid: 19729209
38. Hague SM, Klaffke S, Bandmann O, Neurodegenerative disorders: Parkinson’s disease and Huntington’s disease: J Neurol Neurosurg Psychiatry, 2005; 76(8); 1058-63, pmid: 16024878
39. Pardo LM, van Duijn CM, In search of genes involved in neurodegenerative disorders: Mutat Res, 2005; 592(1–2); 89-101, pmid: 16009383
40. Horrobin DF, Loss of delta-6-desaturase activity as a key factor in aging: Med Hypotheses, 1981; 7(9); 1211-20, pmid: 6270521
41. Kroger J, Schulze MB, Recent insights into the relation of Delta5 desaturase and Delta6 desaturase activity to the development of type 2 diabetes: Curr Opin Lipidol, 2012; 23(1); 4-10, pmid: 22123669
42. Abel S, De Kock M, van Schalkwyk DJ, Altered lipid profile, oxidative status and hepatitis B virus interactions in human hepatocellular carcinoma: Prostaglandins Leukot Essent Fatty Acids, 2009; 81(5–6); 391-99, pmid: 19782547
43. Araya J, Rodrigo R, Pettinelli P, Decreased liver fatty acid delta-6 and delta-5 desaturase activity in obese patients: Obesity (Silver Spring), 2010; 18(7); 1460-63, pmid: 19875987
44. Cai J, Jiang WG, Mansel RE, Inhibition of the expression of VE-cadherin/catenin complex by gamma linolenic acid in human vascular endothelial cells, and its impact on angiogenesis: Biochem Biophys Res Commun, 1999; 258(1); 113-18, pmid: 10222244
45. Fang XL, Shu G, Zhang ZQ, Roles of alpha-linolenic acid on IGF-I secretion and GH/IGF system gene expression in porcine primary hepatocytes: Mol Biol Rep, 2012; 39(12); 10987-96, pmid: 23053988
46. Barcelo-Coblijn G, Murphy EJ, Alpha-linolenic acid and its conversion to longer chain n-3 fatty acids: Benefits for human health and a role in maintaining tissue n-3 fatty acid levels: Prog Lipid Res, 2009; 48(6); 355-74, pmid: 19619583
47. Zhang W, Wang R, Han SF, Alpha-linolenic acid attenuates high glucose-induced apoptosis in cultured human umbilical vein endothelial cells via PI3K/Akt/eNOS pathway: Nutrition, 2007; 23(10); 762-70, pmid: 17716867
48. Lewin M, Samuel S, Merkel J, Bickler P, Varespladib (LY315920) appears to be a potent, broad-spectrum, inhibitor of snake venom phospholipase A2 and a possible pre-referral treatment for envenomation: Toxins (Basel), 2016; 8(9) pii: E248
49. Thotala D, Craft JM, Ferraro DJ, Cytosolic phospholipaseA2 inhibition with PLA-695 radiosensitizes tumors in lung cancer animal models: PLoS One, 2013; 8(7); e69688, pmid: 23894523
50. Lee KL, Foley MA, Chen L, Discovery of Ecopladib, an indole inhibitor of cytosolic phospholipase A2alpha: J Med Chem, 2007; 50(6); 1380-400, pmid: 17305324
51. Theodorakis NG, Wang YN, Skill NJ, The role of nitric oxide synthase isoforms in extrahepatic portal hypertension: Studies in gene-knockout mice: Gastroenterology, 2003; 124(5); 1500-8, pmid: 12730888
52. Theodorakis NG, Wang YN, Wu JM, Role of endothelial nitric oxide synthase in the development of portal hypertension in the carbon tetrachloride-induced liver fibrosis model: Am J Physiol Gastrointest Liver Physiol, 2009; 297(4); G792-99, pmid: 19628654
53. Li H, Forstermann U, Pharmacological prevention of eNOS uncoupling: Curr Pharm Des, 2014; 20(22); 3595-606, pmid: 24180386
54. Lei S, Huang F, Zhao A, The ratio of dihomo-gamma-linolenic acid to deoxycholic acid species is a potential biomarker for the metabolic abnormalities in obesity: FASEB J, 2017; 31(9); 3904-12, pmid: 28490483
55. Matsuda M, Kawamoto T, Tamura R, Predictive value of serum dihomo-gamma-linolenic acid level and estimated Delta-5 desaturase activity in patients with hepatic steatosis: Obes Res Clin Pract, 2017; 11(1); 34-43, pmid: 26964726
56. Fragkos KC, Forbes A, Citrulline as a marker of intestinal function and absorption in clinical settings: A systematic review and meta-analysis: United European Gastroenterol J, 2018; 6(2); 181-91
57. Crenn P, Coudray-Lucas C, Thuillier F, Postabsorptive plasma citrulline concentration is a marker of absorptive enterocyte mass and intestinal failure in humans: Gastroenterology, 2000; 119(6); 1496-505, pmid: 11113071
58. Meeks AC, Madill J, Sarcopenia in liver transplantation: A review: Clin Nutr ESPEN, 2017; 22; 76-80, pmid: 29415839
59. Ogawa SBody weight and bone/calcium metabolism. Sarcopenia and its relationship with bone and calcium metabolism: Clin Calcium, 2018; 28(7); 907-12, pmid: 29950542 [in Japanese]
60. Barillaro C, Liperoti R, Martone AM, The new metabolic treatments for sarcopenia: Aging Clin Exp Res, 2013; 25(2); 119-27, pmid: 23739896
61. Ter Borg S, de Groot LC, Mijnarends DM, Differences in nutrient intake and biochemical nutrient status between sarcopenic and nonsarcopenic older adults-results from the Maastricht Sarcopenia Study: J Am Med Dir Assoc, 2016; 17(5); 393-401, pmid: 26825685
62. Gu DH, Kim MY, Seo YS, Clinical usefulness of psoas muscle thickness for the diagnosis of sarcopenia in patients with liver cirrhosis: Clin Mol Hepatol, 2018; 24(3); 319-30, pmid: 29706058
63. Mangus RS, Bush WJ, Miller C, Severe sarcopenia and increased fat stores in pediatric patients with liver, kidney, or intestine failure: J Pediatr Gastroenterol Nutr, 2017; 65(5); 579-83, pmid: 28604513
64. Kaizu T, Ikeda A, Nakao A, Donor graft adenoviral iNOS gene transfer ameliorates rat liver transplant preservation injury and improves survival: Hepatology, 2006; 43(3); 464-73, pmid: 16496305
11 June 2019: Original Paper
Metabolomic Characterization of Human Model of Liver Rejection Identifies Aberrancies Linked to Cyclooxygenase (COX) and Nitric Oxide Synthase (NOS)
Nicholas J. Skill ABCDEFG 1*, Campbell M. Elliott CDEF 1, Brian Ceballos B 1, Romil Saxena BCD 2, Robert Pepin B 3, Lisa Bettcher B 3, Matthew Ellensberg B 3, Daniel Raftery CDE 3, Mary A. Malucio AEG 1, Burcin Ekser DF 1, Richard S. Mangus A 1, Chandrashekhar A. Kubal AE 1
DOI: 10.12659/AOT.913800
Ann Transplant 2019; 24:341-349
Abstract
BACKGROUND: Acute liver rejection (ALR), a significant complication of liver transplantation, burdens patients, healthcare payers, and the healthcare providers due to an increase in morbidity, cost, and resources. Despite clinical resolution, ALR is associated with an increased risk of graft loss. A unique protocol of delayed immunosuppression used in our institute provided a model to characterize metabolomic profiles in human ALR.
MATERIAL AND METHODS: Twenty liver allograft biopsies obtained 48 hours after liver transplantation in the absence of immunosuppression were studied. Hepatic metabolites were quantitated in these biopsies by liquid chromatography and mass spectroscopy (LC/MS). Metabolite profiles were compared among: 1) biopsies with reperfusion injury but no histological evidence of rejection (n=7), 2) biopsies with histological evidence of moderate or severe rejection (n=5), and 3) biopsies with histological evidence of mild rejection (n=8).
RESULTS: There were 133 metabolites consistently detected by LC/MS and these were prioritized using variable importance to projection (VIP) analysis, comparing moderate or severe rejection vs. no rejection or mild rejection using partial least squares discriminant statistical analysis (PLS-DA). Twenty metabolites were identified as progressively different. Further PLS-DA using these metabolites identified 3 metabolites (linoleic acid, γ-linolenic acid, and citrulline) which are associated with either cyclooxygenase or nitric oxide synthase functionality.
CONCLUSIONS: Hepatic metabolic aberrancies associated with cyclooxygenase and nitric oxide synthase function occur contemporaneous with ALR. Additional studies are required to better characterize the role of these metabolic pathways to enhance utility of the metabolomics approach in diagnosis and outcomes of ALR.
Keywords: Graft Rejection, Liver Transplantation, Metabolomics, Nitric Oxide Synthase, Prostaglandin-Endoperoxide Synthases, End stage liver disease, Liver
Background
Acute liver rejection (ALR) following liver transplantation occurs in approximately 4–20% of patients [1,2]. According to the United Network for Organ Sharing (UNOS), in 2017 the number of liver transplants performed in the USA was 8082, representing an increase of 24.5% since 2016. Currently, the number of patients waiting for liver transplant is approximately 13 914 and the average waiting time for liver transplant is 511 days. Therefore, although the incidence of acute liver rejection is low, the high volume of transplants coupled with increased frequency and limited donors encourages the maximization of graft survival by addressing ALR, a major cause of graft damage.
This study aimed to characterize metabolomic aberrancies in a human model of liver rejection to guide future studies aimed at addressing graft damage congruent with ALR. Between 2008 and 2012, the standard immunosuppression protocol for patients receiving liver transplants at Indiana University Hospital was begun 2 days following transplant and prior to collection of liver biopsy at the time of fascial closure. The hypothesis was that a delay in immunosuppression would induce tolerance [3]. This immunosuppression delay protocol coupled with the collection of a fascial closure biopsy provides an opportunity to characterize ALR consequences in a human model of early liver rejection, specifically to utilize a targeted liquid chromatography/mass spectrometry (LC/MS) platform for metabolomics to profile and quantify hepatic metabolites in order to identify metabolic signatures associated with ALR.
Metabolomics is the study of a large number of small molecule metabolites in biofluids and tissue to identify biomarkers associated with altered metabolic pathways. As metabolites are modulated by protein and enzymatic function, they reflect many of the alterations caused by disease or other biological stresses. Metabolites are exquisitely sensitive to different biological states and therefore represent a promising approach to identify biopathology contemporaneous with rejection [4–6]. Several analytical techniques such as nuclear magnetic resonance (NMR), LC-MS, and gas chromatography-mass spectrometry (GC-MS) have been used to detect metabolic changes [7]. Several studies have used a variety of analytical techniques to elucidate aberrant pathways associated with cancer [8]. While a few of these studies have used animal models [9–11], the majority have focused on humans [4,10,12–22] using NMR [4,16], LC-MS [12,13,15,17,21,22], and GC-MS [13–15,18,19], or HPLC methods [20]. These studies have reported alterations in numerous metabolic pathways, including glycolysis, amino acid, fatty acid, and bile acid metabolism. While there are few reports that have focused exclusively on altered metabolic pathways associated with liver rejection, there have been studies relating to rejection-associated events. Previous reports have documented metabolic pathways and individual metabolites that modulate immune cell function and immune responses [23]. For example, modulation of T cells has been well documented in conjunction with rejection, as has the role of metabolism and nutrient availability upon T cell activation and function [5,24]. Moreover, activation of T cells requires metabolic reprogramming in order to increase glycolytic flux, lactate, lipids, proteins, nucleic acid, and carbohydrates [25]. These changes in metabolic profiles also direct signaling. For example, increased intracellular leucine metabolism controls mammalian target of rapamycin (mTOR) signaling required to induce Th1, Th2, and Th17 CD4(+) T effector cell differentiation [26]. Therefore, there is a need to better understand changes in hepatic biochemical pathways associated with rejection, and metabolomics is an established analytical modality available to identify key compounds. Focusing on hepatic tissue prior to immunosuppression in patients provides a unique opportunity to improve our understanding of graft damage and loss.
Material and Methods
PATIENTS AND PROCEDURES:
In all liver transplants, the muscle layer was left open and skin was closed immediately after transplantation to prevent compartment syndrome. All patients were taken back to the operating room for delayed fascial closure on the 2nd post-transplant day [28]. During fascial closure, a second allograft biopsy was performed. A part of the second liver allograft biopsy was frozen for future use. Patients did not receive any immunosuppression prior to fascial closure [3]. For the purpose of this study, the day 2 biopsies were divided in to 3 groups (n=5–8 per group): Group 1 (control), patients with no evidence of rejection; Group 2, patients with histological evidence of mild rejection; and Group 3, patients with evidence of moderate or severe rejection. To evaluate the metabolic changes associated with liver rejection, we performed LC-MS analysis, targeting 216 metabolites in liver biopsies taken 2 days after liver transplantation.
IMMUNOSUPPRESSION PROTOCOL:
The induction immunosuppression consisted of 3 doses of 2 mg/kg rabbit anti-thymocyte globulin (rATG) every 48 hours starting on post-transplant day 2 along with a single dose of 1.5 mg/m2 BSA of rituximab on post-transplant day 3. Premedication for rATG was given immediately before its administration in the form of solumedrol [500 (first dose), 250 (second dose), and 120 mg (third dose)], acetaminophen (650 mg), and diphenhydramine (25 mg). Maintenance immunosuppression was also initiated on post-transplant day 2 in the form of tacrolimus monotherapy, although some recipients received additional mycophenolate mofetil. The goal trough levels for tacrolimus were 7 to 10 ng/mL in the first 3 months and 6 to 8 ng/mL thereafter [3].
LC/MS:
Day 2 liver allograft biopsies were frozen in liquid nitrogen and stored at −86°C. Tissue was transported on dry ice to the Northwest Metabolomics Research Center (NW-MRC) at the University of Washington for analysis. Briefly, targeted LC/MS/MS was performed according to methods developed at the University of Washington Metabolomic Research Center as per Zhu et al. [29] Targeted aqueous metabolite profiling analysis was performed using an Agilent 1260/AB-Sciex 5500 Qtrap Liquid Chromatography-Mass spectroscopy/mass spectroscopy (LC-MS/MS) instrument and standard operating procedures we developed previously [29]. The LC-MS/MS analysis is based on hydrophilic interaction chromatography (HILIC), and targets 216 metabolites located in more than 35 different metabolic pathways. This system provides detailed information on metabolites involved in glycolysis, tricarboxylic acid cycle (TCA), and pentose phosphate shunt, as well as amino acid, fatty acid, and nucleic acid metabolism, and other pathways. Twenty-six isotope-labeled internal standards were included to monitor sample preparation steps and system performance, as well as to provide absolute quantitation of a number of amino and organic acids.
DATA ANALYSIS FOR METABOLOMICS:
The intensity of tissue peaks in each data set were normalized to tissue weight. Statistical analysis was performed using XLSTAT software. Each data set was mean-centered before the analysis. Univariate analysis of the individual metabolites was performed using the
Results
HISTOLOGICAL EVIDENCE OF REJECTION:
Of the 60 patients recruited and transplanted, routine pathology reports described histological evidence of rejection in 14 patients (23%). Biopsies were stratified based on these reports into 3 groups: 1) no histological evidence of rejection, 2) evidence of mild rejection, and 3) patients with evidence of moderate or severe rejection. Seven samples from each group were selected for pathology review and metabolomic analysis. A pathologist (RS) reviewed all 21 fascial closure liver biopsies taken 2 days post-transplant. Her analysis found 5 biopsies had unequivocal evidence of moderate or severe rejection (endothelialitis, cell infiltration, or bile duct injury). Seven biopsies had no evidence of rejection but had reperfusion damage. One sample was indeterminable, did not reach criteria for rejection, and had no reperfusion injury. The remaining 8 biopsies had histological evidence of mild rejection. The 1 biopsy that was indeterminable was not included in either rejection or control groups and data were not included in the metabolomic analysis.
The biopsies in the rejection group were characterized by the presence of a mixed inflammatory infiltrate in portal tracts that comprised variable combinations of lymphocytes, eosinophils, and neutrophils. Endothelialitis and bile duct damage were present in varying degrees of severity. Control biopsies showed features of reperfusion damage that included variable combinations and severity of portal edema, peribiliary neutrophils, perivenular hepatocellular necrosis, and presence of lobular neutrophils. One biopsy showed mild macro-vesicular steatosis with necrosis and neutrophils. The biopsies were characterized into 3 groups for the purpose of metabolomic analysis: Group 1 was reperfusion injury only (N=7), Group 2 was categorical histological evidence of moderate or severe rejection (N=5), and Group 3 was histological evidence of mild rejection (N=8).
LC/MS-BASED METABOLOMICS:
The LC-MS/MS method was optimized to target a total of 216 metabolites in the liver biopsy samples. However, after deleting metabolites that were not detected, metabolites below the signal to noise cutoff, and metabolites inconsistently detected in the samples, 133 metabolites were quantified. We assessed and compared differences in metabolites between 1) biopsies with mild rejection or with moderate or severe rejection when compared to tissues with reperfusion injury and 2) biopsies with mild rejection when compared to biopsies with moderate or severe rejection. Each metabolite was ranked by its variable importance in the projection (VIP) score via partial least squares- discriminative analysis (PLS-DA) using XLSTAT Biomed software (Figure 1). Twenty-one metabolites with VIP scores above 1.5 were included in a secondary PLS-DA analysis comparing no rejection (reperfusion injury) to both moderate to severe rejection (Figure 2A) and mild rejection (Figure 2B). Of these metabolites, linoleic acid, γ-linolenic acid, and citrulline emerged as providing the strongest predictive model of rejection (Figure 2). The differences between these metabolites in rejection (mild, moderate, and severe) and control biopsies were examined individually (Figure 3). They were then used to construct a final sample model by PLS-DA. Cross-validation of this model was then used to estimate how closely the 3 metabolites, taken as a group, correlate with the biopsy histology report from the pathologist (RS) (Figure 4). The resulting aggregate indicates that, taken together, the 3 metabolites can accurately identify the rejection status of each patient in our sample group, and that this is likely to be the case for independent samples.
Discussion
This study represents a unique model of human liver rejection due to the unique immunosuppression and surgical protocol that was followed. There are no previously published data on human liver rejection in this setting. In the absence of immunosuppression, changes occurring in the liver biopsies in the setting of cellular rejection are novel and intriguing. Using 2-day protocol liver biopsies, targeted LC/MS-based metabolomics analysis, and PLS-DA, we identified 3 aberrant metabolites (linolenic acid, γ-linolenic acid, and citrulline) contemporaneous with liver rejection.
LC/MS/MS-based metabolomics provides broad-based coverage of the important small molecule metabolites in biofluids and tissue to allow the identification of altered metabolic pathways. As metabolites are modulated by protein function, they reflect many of the alterations caused by disease or other biological stresses [4–6]. Analysis using PLS-DA is appropriate when large numbers of potentially correlated variables must be analyzed. It is especially well suited to cases where the number of variables exceeds the number of samples, which would otherwise produce overfitting using conventional regression models. We used VIP scores, which represent the effect of a particular variable on the PLS-DA model, to eliminate non-predictive variables from our dataset, and to identify the variables with the highest degree of predictive power at the level of individual patients. This analysis revealed 3 metabolites: linoleic acid, γ linolenic acid, and citrulline. Linoleic acid and γ-linolenic acid are associated with cyclooxygenase (COX) pathways, while citrulline is associated with nitric oxide synthase (NOS) pathways.
Linoleic acid is an octadecadeinoic fatty acid and a precursor for arachidonic acid, which is a substrate for COX enzymes and subsequent biosynthesis of vasoactive molecules. Changes in arachidonic acid are linked to numerous pathologies of the liver, including portal hypertension and liver cirrhosis [30,31]. Linoleic acid regulates the COX-2/VEGF/MAP kinase pathway [32] and endothelial vasodilatory function [33]. Studies have shown that COX-2 was significantly increased in a rodent model of liver rejection [34]. However, whether increased COX is beneficial or not is controversial. Some studies have shown that increased COX-2 is protective [35], while others have found that inhibition of COX-2 increases graft survival in animal models [34,36]. Moreover, linoleic acid is also associated with pathologies independent of COX, as it is synthesized from phosphatidylcholine via phospholipase A2 or phospholipase A1. Aberrancies of phospholipase A2 are associated with Parkinson disease, peroxisomal beta-oxidation enzyme deficiency, neurodegeneration with brain iron accumulation, and peroxisomal acyl-CoA oxidase deficiency [37,39].
The second metabolite identified by PLS-DA was γ-linolenic acid, which is an all-cis-6,9,12-octadecatrienoic acid designated as 18: 3 and is synthesized from linoleic acid by introduction of a (third) double bond at the delta 6 position under the catalytic influence of delta-6-desaturase enzyme. This step is believed to be the rate-limiting stage in the metabolic pathway. Aging, obesity, diabetes, high alcohol intake, stress-related hormones, and viral infections are known to reduce conversion of linoleic acid to γ-linolenic acid [40–43]. γ-linolenic acid is known to inhibit angiogenesis, partly via the decrease in the expression of VE-cadherin and beta-catenin [44], potentially due to the elimination of the precursor, -linoleic acid. Hepatocyte expression of insulin growth factor-I, insulin growth factor-II, growth hormone receptor, insulin receptor, Insulin growth factor binding protein-3, and Insulin growth factor binding protein-4 mRNAs are all upregulated by linoleic acid [45]. Conversion of linoleic acid to γ-linolenic acid is known to be beneficial for human health [46]. Linolenic acid attenuates endothelial apoptosis
The third metabolite identified by PLS-DA was citrulline, a key intermediate in the urea cycle produced via the metabolism of ornithine and carbamoyl phosphate. Moreover, citrulline is a by-product of the enzymatic production of nitric oxide from the amino acid arginine. As citrulline is a part of the urea cycle and urea is a marker of liver failure, it is not unexpected that rejection is associated with increased citrulline. However, urea levels were not significantly higher in patients with rejection. Because citrulline is involved in many biological pathways, it is impossible to accurately hypothesize the pathobiology, physiological, and biochemical milieu associated with changes to hepatic linoleic acid, γ-linoleic acid and citrulline based on biopsies. However, the fact that they are connected to important hepatic perfusion regulators suggests that changes impart/reflect a response to tissue stress, damage, and/or acute graft rejection. Arginine is the predominate substrate for the production of nitric oxide (NO), a well-documented vasodilator associated with liver perfusion and portal hypertension [51,52]. The role of NO in liver perfusion is well documented and focuses on sinusoidal stellate cell control of sinusoidal dilation and thus an increase in resistance to portal venous blood flow. A reduction in citrulline might be indicative of a modulation of NO biosynthesis. Reduced citrulline could be reflective of a reduction of NOS activity, as citrulline is the biproduct of the conversion of arginine to NO. In contrast, as citrulline is also the substrate, a reduction could be indicative of an increase in NOS activity. What we do know is that a change in NO within the liver will modulate perfusion and affect ischemia and hypoxia and impart an additional stress to the liver. Moreover, endothelial NOS (eNOS) is also known to “uncouple” when co-factors are absent, leading to the formation of oxygen free radicals [53]. The conversion of arginine to NO and citrulline is a 2-step process involving N-hydroxy-l-arginine as an intermediate; therefore, uncoupling of endothelial NOS could result in a reduction in citrulline.
The data do not suggest that either linolenic acid or citrulline should replace current markers of acute liver rejection. LC-MS/MS is unlikely to be quicker or cheaper than histology and liver functional tests. Nevertheless, there is utility in investigating linolenic acid and citrulline, as both have been shown to be markers of interest in other pathologies. For example, the ratio of linolenic acid to deoxycholic acid species is a potential biomarker for metabolic abnormalities in obesity [54] and hepatic steatosis [55]. Moreover, the circulating citrulline concentration is a biomarker of intestinal functionality [56,57]. What the data may reveal is hepatic response to acute liver rejection by the modulation of vasodilators to maintain liver perfusion. However, we are cognizant that differences in metabolomics signatures between control livers and livers with rejection could be independent of rejection. It is possible that these differences are linked to other aspects of liver disease. For example, sarcopenia, which is associated with modulated metabolism, poorer outcomes, and changes in the levels of citrulline and linoleic acid, occurs in patients with liver disease [58–61]. A preliminary analysis of sarcopenia in the patients within this study, based on measurement of the psoas muscle at the C3, as previously described [62,63], was performed and identified 3 patients with sarcopenia. Two patients within the early rejection group had sarcopenia. One patient with no evidence of rejection was identified with sarcopenia. Because the frequency of overlapping sarcopenia within the 3 cohorts is sporadic, it is difficult to determine if sarcopenia is an independent variable in hepatic metabolites associated with hepatic response to rejection.
Additional research is required to further elucidate our findings and to better understand any connection among metabolic changes, acute liver rejection, and graft survival. Further research is likely to focus on metabolomic quantification post-transplant in rodent models of liver rejection [64]. This is because rejection rates observed in clinical programs are very low; therefore, to expand this project using patient samples only would be prohibitive. Moreover, the delayed immunosuppression protocol is controversial and delayed immunosuppression and 2-day protocol biopsies are not the standard of care at our institute at present.
Finally, the immunosuppression protocol deserves further explanation. The premise behind delayed introduction of immunosuppression was to allow immune activation of recipient lymphocytes in the allograft. It was thought that the potent rATG would then lead to apoptosis and death of recipient lymphocytes within the graft, allowing operational tolerance in the long term. Although this approach permits a degree of rejection in the allograft, this is a desired effect and has no adverse effects in the long term, which was demonstrated in our larger study involving 1000 patients [3]. Based on this large-sample experience, we do not believe that deaths that occurred in this study cohort were due to the delayed immunosuppression.
Conclusions
Contemporaneous with acute liver rejection, increases in linoleic acid and γ-linolenic acid are observed alongside a decrease in citrulline. These metabolites are connected to pathways that regulate liver perfusion.
References
1. Au KP, Chan SC, Chok KS, Clinical factors affecting rejection rates in liver transplantation: Hepatobiliary Pancreat Dis Int, 2015; 14(4); 367-73, pmid: 26256080
2. Neil DA, Hubscher SG, Current views on rejection pathology in liver transplantation: Transpl Int, 2010; 23(10); 971-83, pmid: 20723179
3. Mangus RS, Fridell JA, Vianna RM, Immunosuppression induction with rabbit anti-thymocyte globulin with or without rituximab in 1000 liver transplant patients with long-term follow-up: Liver Transpl, 2012; 18(7); 786-95, pmid: 22237953
4. Gao H, Lu Q, Liu X, Application of 1H NMR-based metabonomics in the study of metabolic profiling of human hepatocellular carcinoma and liver cirrhosis: Cancer Sci, 2009; 100(4); 782-85, pmid: 19469021
5. Mayr M, Metabolomics: Ready for the prime time?: Circ Cardiovasc Genet, 2008; 1(1); 58-65, pmid: 20031543
6. Zhang J, Liu L, Wei S, Metabolomics study of esophageal adenocarcinoma: J Thorac Cardiovasc Surg, 2011; 141(2); 469-75, pmid: 20880550
7. Gowda GA, Zhang S, Gu H, Metabolomics-based methods for early disease diagnostics: Expert Rev Mol Diagn, 2008; 8(5); 617-33, pmid: 18785810
8. Bowers J, Hughes E, Skill N, Detection of hepatocellular carcinoma in hepatitis C patients: biomarker discovery by LC-MS: J Chromatogr B Analyt Technol Biomed Life Sci, 2014; 966; 154-62
9. Li S, Liu H, Jin Y, Metabolomics study of alcohol-induced liver injury and hepatocellular carcinoma xenografts in mice: J Chromatogr B Analyt Technol Biomed Life Sci, 2011; 879(24); 2369-75
10. Tan Y, Yin P, Tang L, Metabolomics study of stepwise hepatocarcinogenesis from the model rats to patients: potential biomarkers effective for small hepatocellular carcinoma diagnosis: Mol Cell Proteomics, 2012; 11(2); M111.010694
11. Wang J, Zhang S, Li Z, (1)H-NMR-based metabolomics of tumor tissue for the metabolic characterization of rat hepatocellular carcinoma formation and metastasis: Tumour Biol, 2011; 32(1); 223-31, pmid: 20890798
12. Chen F, Xue J, Zhou L, Identification of serum biomarkers of hepatocarcinoma through liquid chromatography/mass spectrometry-based metabonomic method: Anal Bioanal Chem, 2011; 401(6); 1899-904, pmid: 21833635
13. Chen T, Xie G, Wang X, Serum and urine metabolite profiling reveals potential biomarkers of human hepatocellular carcinoma: Mol Cell Proteomics, 2011; 10(7); M110.004945
14. Lin X, Zhang Y, Ye G, Classification and differential metabolite discovery of liver diseases based on plasma metabolic profiling and support vector machines: J Sep Sci, 2011; 34(21); 3029-36, pmid: 21919198
15. Patterson AD, Maurhofer O, Beyoglu D, Aberrant lipid metabolism in hepatocellular carcinoma revealed by plasma metabolomics and lipid profiling: Cancer Res, 2011; 71(21); 6590-600, pmid: 21900402
16. Shariff MI, Gomaa AI, Cox IJ, Urinary metabolic biomarkers of hepatocellular carcinoma in an Egyptian population: A validation study: J Proteome Res, 2011; 10(4); 1828-36, pmid: 21275434
17. Wang B, Chen D, Chen Y, Metabonomic profiles discriminate hepatocellular carcinoma from liver cirrhosis by ultraperformance liquid chromatography-mass spectrometry: J Proteome Res, 2012; 11(2); 1217-27, pmid: 22200553
18. Wu H, Xue R, Dong L, Metabolomic profiling of human urine in hepatocellular carcinoma patients using gas chromatography/mass spectrometry: Anal Chim Acta, 2009; 648(1); 98-104, pmid: 19616694
19. Xue R, Lin Z, Deng C, A serum metabolomic investigation on hepatocellular carcinoma patients by chemical derivatization followed by gas chromatography/mass spectrometry: Rapid Commun Mass Spectrom, 2008; 22(19); 3061-68, pmid: 18767022
20. Yang J, Xu G, Zheng Y, Diagnosis of liver cancer using HPLC-based metabonomics avoiding false-positive result from hepatitis and hepatocirrhosis diseases: J Chromatogr B Analyt Technol Biomed Life Sci, 2004; 813(1–2); 59-65
21. Yin P, Wan D, Zhao C, A metabonomic study of hepatitis B-induced liver cirrhosis and hepatocellular carcinoma by using RP-LC and HILIC coupled with mass spectrometry: Mol Biosyst, 2009; 5(8); 868-76, pmid: 19603122
22. Zhou L, Wang Q, Yin P, Serum metabolomics reveals the deregulation of fatty acids metabolism in hepatocellular carcinoma and chronic liver diseases: Anal Bioanal Chem, 2012; 403(1); 203-13, pmid: 22349331
23. Everts B, Metabolomics in immunology research: Methods Mol Biol, 2018; 1730; 29-42, pmid: 29363063
24. Baumann AK, Schlue J, Noyan F, Preferential accumulation of T helper cells but not cytotoxic T cells characterizes benign subclinical rejection of human liver allografts: Liver Transpl, 2016; 22(7); 943-55, pmid: 26929119
25. Yang Z, Matteson EL, Goronzy JJ, Weyand CM, T-cell metabolism in autoimmune disease: Arthritis Res Ther, 2015; 17; 29, pmid: 25890351
26. Powell JD, Delgoffe GM, The mammalian target of rapamycin: Linking T cell differentiation, function, and metabolism: Immunity, 2010; 33(3); 301-11, pmid: 20870173
27. , Terminology for hepatic allograft rejection. International Working Party: Hepatology, 1995; 22(2); 648-54, pmid: 7635435
28. Jernigan TW, Fabian TC, Croce MA, Staged management of giant abdominal wall defects: acute and long-term results: Ann Surg, 2003; 238(3); 349-55, pmid: 14501501 discussion 355–57
29. Zhu J, Djukovic D, Deng L, Colorectal cancer detection using targeted serum metabolic profiling: J Proteome Res, 2014; 13(9); 4120-30, pmid: 25126899
30. Skill NJ, Theodorakis NG, Wang YN, Role of cyclooxygenase isoforms in prostacyclin biosynthesis and murine prehepatic portal hypertension: Am J Physiol Gastrointest Liver Physiol, 2008; 295(5); G953-64, pmid: 18772366
31. Jeong SW, Jang JY, Lee SH, Increased expression of cyclooxygenase-2 is associated with the progression to cirrhosis: Korean J Intern Med, 2010; 25(4); 364-71, pmid: 21179273
32. Deshpande R, Mansara P, Kaul-Ghanekar R, Alpha-linolenic acid regulates Cox2/VEGF/MAP kinase pathway and decreases the expression of HPV oncoproteins E6/E7 through restoration of p53 and Rb expression in human cervical cancer cell lines: Tumour Biol, 2016; 37(3); 3295-305, pmid: 26440049
33. Steer P, Vessby B, Lind L, Endothelial vasodilatory function is related to the proportions of saturated fatty acids and alpha-linolenic acid in young men, but not in women: Eur J Clin Invest, 2003; 33(5); 390-96, pmid: 12713452
34. Martelius TJ, Wolff H, Bruggeman CA, Induction of cyclo-oxygenase-2 by acute liver allograft rejection and cytomegalovirus infection in the rat: Transpl Int, 2002; 15(12); 610-14, pmid: 12478407
35. Motino O, Frances DE, Casanova N, Protective role of hepatocyte cyclooxygenase-2 expression against liver ischemia-reperfusion injury in mice: Hepatology, 2018 [Epub ahead of print]
36. Ma N, Szabolcs MJ, Sun J, The effect of selective inhibition of cyclooxygenase (COX)-2 on acute cardiac allograft rejection: Transplantation, 2002; 74(11); 1528-34, pmid: 12490785
37. Cicchetti F, Drouin-Ouellet J, Gross RE, Environmental toxins and Parkinson’s disease: What have we learned from pesticide-induced animal models?: Trends Pharmacol Sci, 2009; 30(9); 475-83, pmid: 19729209
38. Hague SM, Klaffke S, Bandmann O, Neurodegenerative disorders: Parkinson’s disease and Huntington’s disease: J Neurol Neurosurg Psychiatry, 2005; 76(8); 1058-63, pmid: 16024878
39. Pardo LM, van Duijn CM, In search of genes involved in neurodegenerative disorders: Mutat Res, 2005; 592(1–2); 89-101, pmid: 16009383
40. Horrobin DF, Loss of delta-6-desaturase activity as a key factor in aging: Med Hypotheses, 1981; 7(9); 1211-20, pmid: 6270521
41. Kroger J, Schulze MB, Recent insights into the relation of Delta5 desaturase and Delta6 desaturase activity to the development of type 2 diabetes: Curr Opin Lipidol, 2012; 23(1); 4-10, pmid: 22123669
42. Abel S, De Kock M, van Schalkwyk DJ, Altered lipid profile, oxidative status and hepatitis B virus interactions in human hepatocellular carcinoma: Prostaglandins Leukot Essent Fatty Acids, 2009; 81(5–6); 391-99, pmid: 19782547
43. Araya J, Rodrigo R, Pettinelli P, Decreased liver fatty acid delta-6 and delta-5 desaturase activity in obese patients: Obesity (Silver Spring), 2010; 18(7); 1460-63, pmid: 19875987
44. Cai J, Jiang WG, Mansel RE, Inhibition of the expression of VE-cadherin/catenin complex by gamma linolenic acid in human vascular endothelial cells, and its impact on angiogenesis: Biochem Biophys Res Commun, 1999; 258(1); 113-18, pmid: 10222244
45. Fang XL, Shu G, Zhang ZQ, Roles of alpha-linolenic acid on IGF-I secretion and GH/IGF system gene expression in porcine primary hepatocytes: Mol Biol Rep, 2012; 39(12); 10987-96, pmid: 23053988
46. Barcelo-Coblijn G, Murphy EJ, Alpha-linolenic acid and its conversion to longer chain n-3 fatty acids: Benefits for human health and a role in maintaining tissue n-3 fatty acid levels: Prog Lipid Res, 2009; 48(6); 355-74, pmid: 19619583
47. Zhang W, Wang R, Han SF, Alpha-linolenic acid attenuates high glucose-induced apoptosis in cultured human umbilical vein endothelial cells via PI3K/Akt/eNOS pathway: Nutrition, 2007; 23(10); 762-70, pmid: 17716867
48. Lewin M, Samuel S, Merkel J, Bickler P, Varespladib (LY315920) appears to be a potent, broad-spectrum, inhibitor of snake venom phospholipase A2 and a possible pre-referral treatment for envenomation: Toxins (Basel), 2016; 8(9) pii: E248
49. Thotala D, Craft JM, Ferraro DJ, Cytosolic phospholipaseA2 inhibition with PLA-695 radiosensitizes tumors in lung cancer animal models: PLoS One, 2013; 8(7); e69688, pmid: 23894523
50. Lee KL, Foley MA, Chen L, Discovery of Ecopladib, an indole inhibitor of cytosolic phospholipase A2alpha: J Med Chem, 2007; 50(6); 1380-400, pmid: 17305324
51. Theodorakis NG, Wang YN, Skill NJ, The role of nitric oxide synthase isoforms in extrahepatic portal hypertension: Studies in gene-knockout mice: Gastroenterology, 2003; 124(5); 1500-8, pmid: 12730888
52. Theodorakis NG, Wang YN, Wu JM, Role of endothelial nitric oxide synthase in the development of portal hypertension in the carbon tetrachloride-induced liver fibrosis model: Am J Physiol Gastrointest Liver Physiol, 2009; 297(4); G792-99, pmid: 19628654
53. Li H, Forstermann U, Pharmacological prevention of eNOS uncoupling: Curr Pharm Des, 2014; 20(22); 3595-606, pmid: 24180386
54. Lei S, Huang F, Zhao A, The ratio of dihomo-gamma-linolenic acid to deoxycholic acid species is a potential biomarker for the metabolic abnormalities in obesity: FASEB J, 2017; 31(9); 3904-12, pmid: 28490483
55. Matsuda M, Kawamoto T, Tamura R, Predictive value of serum dihomo-gamma-linolenic acid level and estimated Delta-5 desaturase activity in patients with hepatic steatosis: Obes Res Clin Pract, 2017; 11(1); 34-43, pmid: 26964726
56. Fragkos KC, Forbes A, Citrulline as a marker of intestinal function and absorption in clinical settings: A systematic review and meta-analysis: United European Gastroenterol J, 2018; 6(2); 181-91
57. Crenn P, Coudray-Lucas C, Thuillier F, Postabsorptive plasma citrulline concentration is a marker of absorptive enterocyte mass and intestinal failure in humans: Gastroenterology, 2000; 119(6); 1496-505, pmid: 11113071
58. Meeks AC, Madill J, Sarcopenia in liver transplantation: A review: Clin Nutr ESPEN, 2017; 22; 76-80, pmid: 29415839
59. Ogawa SBody weight and bone/calcium metabolism. Sarcopenia and its relationship with bone and calcium metabolism: Clin Calcium, 2018; 28(7); 907-12, pmid: 29950542 [in Japanese]
60. Barillaro C, Liperoti R, Martone AM, The new metabolic treatments for sarcopenia: Aging Clin Exp Res, 2013; 25(2); 119-27, pmid: 23739896
61. Ter Borg S, de Groot LC, Mijnarends DM, Differences in nutrient intake and biochemical nutrient status between sarcopenic and nonsarcopenic older adults-results from the Maastricht Sarcopenia Study: J Am Med Dir Assoc, 2016; 17(5); 393-401, pmid: 26825685
62. Gu DH, Kim MY, Seo YS, Clinical usefulness of psoas muscle thickness for the diagnosis of sarcopenia in patients with liver cirrhosis: Clin Mol Hepatol, 2018; 24(3); 319-30, pmid: 29706058
63. Mangus RS, Bush WJ, Miller C, Severe sarcopenia and increased fat stores in pediatric patients with liver, kidney, or intestine failure: J Pediatr Gastroenterol Nutr, 2017; 65(5); 579-83, pmid: 28604513
64. Kaizu T, Ikeda A, Nakao A, Donor graft adenoviral iNOS gene transfer ameliorates rat liver transplant preservation injury and improves survival: Hepatology, 2006; 43(3); 464-73, pmid: 16496305
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eISSN: 2329-0358
Annals of Transplantation is one of the fast-developing journals open to all scientists and fields of transplant medicine and related research. The journal is published quarterly and provides extensive coverage of the most important advances in transplantation. Using an electronic on-line submission and peer review tracking system, Annals of Transplantation is committed to rapid review and publication.
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About Ann Transplant

eISSN: 2329-0358
Annals of Transplantation is one of the fast-developing journals open to all scientists and fields of transplant medicine and related research. The journal is published quarterly and provides extensive coverage of the most important advances in transplantation. Using an electronic on-line submission and peer review tracking system, Annals of Transplantation is committed to rapid review and publication.
Categories
ISI Journals
Publisher
International Scientific Information, Inc.
150 Broadhollow Rd., Suite 114
Melville, NY, 11747 | USA
phone:
1.631.629.4327
e-mail:
[email protected]
www:
www.isi-science.com
Information
Copyright © 2025
International Scientific Infromation, Inc.
All rights reserved.
About Ann Transplant

eISSN: 2329-0358
Annals of Transplantation is one of the fast-developing journals open to all scientists and fields of transplant medicine and related research. The journal is published quarterly and provides extensive coverage of the most important advances in transplantation. Using an electronic on-line submission and peer review tracking system, Annals of Transplantation is committed to rapid review and publication.
Categories
Information
Copyright © 2002 - 2025
International Scientific
Infromation, Inc.
All rights reserved.
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Publisher
International Scientific Information, Inc.
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Melville, NY, 11747 | USA
phone:
1.631.629.4327
e-mail:
[email protected]
www:
www.isi-science.com
In Press
Original article
Steroid Use in ABO-Incompatible Kidney Transplants: Withdrawal vs MaintenanceAnn Transplant In Press; DOI: 10.12659/AOT.947747
Original article
Intra-Arterial Contrast-Enhanced Ultrasound for Transcatheter Thrombolysis in Post-Transplant Hepatic Arter...Ann Transplant In Press; DOI: 10.12659/AOT.947500
Original article
Early Atropine Protocol Enhances Dobutamine Stress Echocardiography in End-Stage Liver Disease: A Practical...Ann Transplant In Press; DOI: 10.12659/AOT.950166
Most Viewed Current Articles
15 Aug 2023 : Review article 7,362
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03 Jan 2023 : Original article 7,247
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Ann Transplant 2023; 28:e938467
16 May 2023 : Original article 7,067
Breaking Antimicrobial Resistance: High-Dose Amoxicillin with Clavulanic Acid for Urinary Tract Infections ...DOI :10.12659/AOT.939258
Ann Transplant 2023; 28:e939258
28 May 2024 : Original article 6,667
Effect of Dexmedetomidine Combined with Remifentanil on Emergence Agitation During Awakening from Sevoflura...DOI :10.12659/AOT.943281
Ann Transplant 2024; 29:e943281
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About Ann Transplant

eISSN: 2329-0358
Annals of Transplantation is one of the fast-developing journals open to all scientists and fields of transplant medicine and related research. The journal is published quarterly and provides extensive coverage of the most important advances in transplantation. Using an electronic on-line submission and peer review tracking system, Annals of Transplantation is committed to rapid review and publication.
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About Ann Transplant

eISSN: 2329-0358
Annals of Transplantation is one of the fast-developing journals open to all scientists and fields of transplant medicine and related research. The journal is published quarterly and provides extensive coverage of the most important advances in transplantation. Using an electronic on-line submission and peer review tracking system, Annals of Transplantation is committed to rapid review and publication.
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ISI Journals
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Melville, NY, 11747 | USA
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About Ann Transplant

eISSN: 2329-0358
Annals of Transplantation is one of the fast-developing journals open to all scientists and fields of transplant medicine and related research. The journal is published quarterly and provides extensive coverage of the most important advances in transplantation. Using an electronic on-line submission and peer review tracking system, Annals of Transplantation is committed to rapid review and publication.
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Copyright © 2002 - 2025
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11 June 2019: Original Paper
Metabolomic Characterization of Human Model of Liver Rejection Identifies Aberrancies Linked to Cyclooxygenase (COX) and Nitric Oxide Synthase (NOS)
Nicholas J. Skill ABCDEFG 1*, Campbell M. Elliott CDEF 1, Brian Ceballos B 1, Romil Saxena BCD 2, Robert Pepin B 3, Lisa Bettcher B 3, Matthew Ellensberg B 3, Daniel Raftery CDE 3, Mary A. Malucio AEG 1, Burcin Ekser DF 1, Richard S. Mangus A 1, Chandrashekhar A. Kubal AE 1
DOI: 10.12659/AOT.913800
Ann Transplant 2019; 24:341-349
Abstract
BACKGROUND: Acute liver rejection (ALR), a significant complication of liver transplantation, burdens patients, healthcare payers, and the healthcare providers due to an increase in morbidity, cost, and resources. Despite clinical resolution, ALR is associated with an increased risk of graft loss. A unique protocol of delayed immunosuppression used in our institute provided a model to characterize metabolomic profiles in human ALR.
MATERIAL AND METHODS: Twenty liver allograft biopsies obtained 48 hours after liver transplantation in the absence of immunosuppression were studied. Hepatic metabolites were quantitated in these biopsies by liquid chromatography and mass spectroscopy (LC/MS). Metabolite profiles were compared among: 1) biopsies with reperfusion injury but no histological evidence of rejection (n=7), 2) biopsies with histological evidence of moderate or severe rejection (n=5), and 3) biopsies with histological evidence of mild rejection (n=8).
RESULTS: There were 133 metabolites consistently detected by LC/MS and these were prioritized using variable importance to projection (VIP) analysis, comparing moderate or severe rejection vs. no rejection or mild rejection using partial least squares discriminant statistical analysis (PLS-DA). Twenty metabolites were identified as progressively different. Further PLS-DA using these metabolites identified 3 metabolites (linoleic acid, γ-linolenic acid, and citrulline) which are associated with either cyclooxygenase or nitric oxide synthase functionality.
CONCLUSIONS: Hepatic metabolic aberrancies associated with cyclooxygenase and nitric oxide synthase function occur contemporaneous with ALR. Additional studies are required to better characterize the role of these metabolic pathways to enhance utility of the metabolomics approach in diagnosis and outcomes of ALR.
Keywords: Graft Rejection, Liver Transplantation, Metabolomics, Nitric Oxide Synthase, Prostaglandin-Endoperoxide Synthases, End stage liver disease, Liver
Background
Acute liver rejection (ALR) following liver transplantation occurs in approximately 4–20% of patients [1,2]. According to the United Network for Organ Sharing (UNOS), in 2017 the number of liver transplants performed in the USA was 8082, representing an increase of 24.5% since 2016. Currently, the number of patients waiting for liver transplant is approximately 13 914 and the average waiting time for liver transplant is 511 days. Therefore, although the incidence of acute liver rejection is low, the high volume of transplants coupled with increased frequency and limited donors encourages the maximization of graft survival by addressing ALR, a major cause of graft damage.
This study aimed to characterize metabolomic aberrancies in a human model of liver rejection to guide future studies aimed at addressing graft damage congruent with ALR. Between 2008 and 2012, the standard immunosuppression protocol for patients receiving liver transplants at Indiana University Hospital was begun 2 days following transplant and prior to collection of liver biopsy at the time of fascial closure. The hypothesis was that a delay in immunosuppression would induce tolerance [3]. This immunosuppression delay protocol coupled with the collection of a fascial closure biopsy provides an opportunity to characterize ALR consequences in a human model of early liver rejection, specifically to utilize a targeted liquid chromatography/mass spectrometry (LC/MS) platform for metabolomics to profile and quantify hepatic metabolites in order to identify metabolic signatures associated with ALR.
Metabolomics is the study of a large number of small molecule metabolites in biofluids and tissue to identify biomarkers associated with altered metabolic pathways. As metabolites are modulated by protein and enzymatic function, they reflect many of the alterations caused by disease or other biological stresses. Metabolites are exquisitely sensitive to different biological states and therefore represent a promising approach to identify biopathology contemporaneous with rejection [4–6]. Several analytical techniques such as nuclear magnetic resonance (NMR), LC-MS, and gas chromatography-mass spectrometry (GC-MS) have been used to detect metabolic changes [7]. Several studies have used a variety of analytical techniques to elucidate aberrant pathways associated with cancer [8]. While a few of these studies have used animal models [9–11], the majority have focused on humans [4,10,12–22] using NMR [4,16], LC-MS [12,13,15,17,21,22], and GC-MS [13–15,18,19], or HPLC methods [20]. These studies have reported alterations in numerous metabolic pathways, including glycolysis, amino acid, fatty acid, and bile acid metabolism. While there are few reports that have focused exclusively on altered metabolic pathways associated with liver rejection, there have been studies relating to rejection-associated events. Previous reports have documented metabolic pathways and individual metabolites that modulate immune cell function and immune responses [23]. For example, modulation of T cells has been well documented in conjunction with rejection, as has the role of metabolism and nutrient availability upon T cell activation and function [5,24]. Moreover, activation of T cells requires metabolic reprogramming in order to increase glycolytic flux, lactate, lipids, proteins, nucleic acid, and carbohydrates [25]. These changes in metabolic profiles also direct signaling. For example, increased intracellular leucine metabolism controls mammalian target of rapamycin (mTOR) signaling required to induce Th1, Th2, and Th17 CD4(+) T effector cell differentiation [26]. Therefore, there is a need to better understand changes in hepatic biochemical pathways associated with rejection, and metabolomics is an established analytical modality available to identify key compounds. Focusing on hepatic tissue prior to immunosuppression in patients provides a unique opportunity to improve our understanding of graft damage and loss.
Material and Methods
PATIENTS AND PROCEDURES:
In all liver transplants, the muscle layer was left open and skin was closed immediately after transplantation to prevent compartment syndrome. All patients were taken back to the operating room for delayed fascial closure on the 2nd post-transplant day [28]. During fascial closure, a second allograft biopsy was performed. A part of the second liver allograft biopsy was frozen for future use. Patients did not receive any immunosuppression prior to fascial closure [3]. For the purpose of this study, the day 2 biopsies were divided in to 3 groups (n=5–8 per group): Group 1 (control), patients with no evidence of rejection; Group 2, patients with histological evidence of mild rejection; and Group 3, patients with evidence of moderate or severe rejection. To evaluate the metabolic changes associated with liver rejection, we performed LC-MS analysis, targeting 216 metabolites in liver biopsies taken 2 days after liver transplantation.
IMMUNOSUPPRESSION PROTOCOL:
The induction immunosuppression consisted of 3 doses of 2 mg/kg rabbit anti-thymocyte globulin (rATG) every 48 hours starting on post-transplant day 2 along with a single dose of 1.5 mg/m2 BSA of rituximab on post-transplant day 3. Premedication for rATG was given immediately before its administration in the form of solumedrol [500 (first dose), 250 (second dose), and 120 mg (third dose)], acetaminophen (650 mg), and diphenhydramine (25 mg). Maintenance immunosuppression was also initiated on post-transplant day 2 in the form of tacrolimus monotherapy, although some recipients received additional mycophenolate mofetil. The goal trough levels for tacrolimus were 7 to 10 ng/mL in the first 3 months and 6 to 8 ng/mL thereafter [3].
LC/MS:
Day 2 liver allograft biopsies were frozen in liquid nitrogen and stored at −86°C. Tissue was transported on dry ice to the Northwest Metabolomics Research Center (NW-MRC) at the University of Washington for analysis. Briefly, targeted LC/MS/MS was performed according to methods developed at the University of Washington Metabolomic Research Center as per Zhu et al. [29] Targeted aqueous metabolite profiling analysis was performed using an Agilent 1260/AB-Sciex 5500 Qtrap Liquid Chromatography-Mass spectroscopy/mass spectroscopy (LC-MS/MS) instrument and standard operating procedures we developed previously [29]. The LC-MS/MS analysis is based on hydrophilic interaction chromatography (HILIC), and targets 216 metabolites located in more than 35 different metabolic pathways. This system provides detailed information on metabolites involved in glycolysis, tricarboxylic acid cycle (TCA), and pentose phosphate shunt, as well as amino acid, fatty acid, and nucleic acid metabolism, and other pathways. Twenty-six isotope-labeled internal standards were included to monitor sample preparation steps and system performance, as well as to provide absolute quantitation of a number of amino and organic acids.
DATA ANALYSIS FOR METABOLOMICS:
The intensity of tissue peaks in each data set were normalized to tissue weight. Statistical analysis was performed using XLSTAT software. Each data set was mean-centered before the analysis. Univariate analysis of the individual metabolites was performed using the
Results
HISTOLOGICAL EVIDENCE OF REJECTION:
Of the 60 patients recruited and transplanted, routine pathology reports described histological evidence of rejection in 14 patients (23%). Biopsies were stratified based on these reports into 3 groups: 1) no histological evidence of rejection, 2) evidence of mild rejection, and 3) patients with evidence of moderate or severe rejection. Seven samples from each group were selected for pathology review and metabolomic analysis. A pathologist (RS) reviewed all 21 fascial closure liver biopsies taken 2 days post-transplant. Her analysis found 5 biopsies had unequivocal evidence of moderate or severe rejection (endothelialitis, cell infiltration, or bile duct injury). Seven biopsies had no evidence of rejection but had reperfusion damage. One sample was indeterminable, did not reach criteria for rejection, and had no reperfusion injury. The remaining 8 biopsies had histological evidence of mild rejection. The 1 biopsy that was indeterminable was not included in either rejection or control groups and data were not included in the metabolomic analysis.
The biopsies in the rejection group were characterized by the presence of a mixed inflammatory infiltrate in portal tracts that comprised variable combinations of lymphocytes, eosinophils, and neutrophils. Endothelialitis and bile duct damage were present in varying degrees of severity. Control biopsies showed features of reperfusion damage that included variable combinations and severity of portal edema, peribiliary neutrophils, perivenular hepatocellular necrosis, and presence of lobular neutrophils. One biopsy showed mild macro-vesicular steatosis with necrosis and neutrophils. The biopsies were characterized into 3 groups for the purpose of metabolomic analysis: Group 1 was reperfusion injury only (N=7), Group 2 was categorical histological evidence of moderate or severe rejection (N=5), and Group 3 was histological evidence of mild rejection (N=8).
LC/MS-BASED METABOLOMICS:
The LC-MS/MS method was optimized to target a total of 216 metabolites in the liver biopsy samples. However, after deleting metabolites that were not detected, metabolites below the signal to noise cutoff, and metabolites inconsistently detected in the samples, 133 metabolites were quantified. We assessed and compared differences in metabolites between 1) biopsies with mild rejection or with moderate or severe rejection when compared to tissues with reperfusion injury and 2) biopsies with mild rejection when compared to biopsies with moderate or severe rejection. Each metabolite was ranked by its variable importance in the projection (VIP) score via partial least squares- discriminative analysis (PLS-DA) using XLSTAT Biomed software (Figure 1). Twenty-one metabolites with VIP scores above 1.5 were included in a secondary PLS-DA analysis comparing no rejection (reperfusion injury) to both moderate to severe rejection (Figure 2A) and mild rejection (Figure 2B). Of these metabolites, linoleic acid, γ-linolenic acid, and citrulline emerged as providing the strongest predictive model of rejection (Figure 2). The differences between these metabolites in rejection (mild, moderate, and severe) and control biopsies were examined individually (Figure 3). They were then used to construct a final sample model by PLS-DA. Cross-validation of this model was then used to estimate how closely the 3 metabolites, taken as a group, correlate with the biopsy histology report from the pathologist (RS) (Figure 4). The resulting aggregate indicates that, taken together, the 3 metabolites can accurately identify the rejection status of each patient in our sample group, and that this is likely to be the case for independent samples.
Discussion
This study represents a unique model of human liver rejection due to the unique immunosuppression and surgical protocol that was followed. There are no previously published data on human liver rejection in this setting. In the absence of immunosuppression, changes occurring in the liver biopsies in the setting of cellular rejection are novel and intriguing. Using 2-day protocol liver biopsies, targeted LC/MS-based metabolomics analysis, and PLS-DA, we identified 3 aberrant metabolites (linolenic acid, γ-linolenic acid, and citrulline) contemporaneous with liver rejection.
LC/MS/MS-based metabolomics provides broad-based coverage of the important small molecule metabolites in biofluids and tissue to allow the identification of altered metabolic pathways. As metabolites are modulated by protein function, they reflect many of the alterations caused by disease or other biological stresses [4–6]. Analysis using PLS-DA is appropriate when large numbers of potentially correlated variables must be analyzed. It is especially well suited to cases where the number of variables exceeds the number of samples, which would otherwise produce overfitting using conventional regression models. We used VIP scores, which represent the effect of a particular variable on the PLS-DA model, to eliminate non-predictive variables from our dataset, and to identify the variables with the highest degree of predictive power at the level of individual patients. This analysis revealed 3 metabolites: linoleic acid, γ linolenic acid, and citrulline. Linoleic acid and γ-linolenic acid are associated with cyclooxygenase (COX) pathways, while citrulline is associated with nitric oxide synthase (NOS) pathways.
Linoleic acid is an octadecadeinoic fatty acid and a precursor for arachidonic acid, which is a substrate for COX enzymes and subsequent biosynthesis of vasoactive molecules. Changes in arachidonic acid are linked to numerous pathologies of the liver, including portal hypertension and liver cirrhosis [30,31]. Linoleic acid regulates the COX-2/VEGF/MAP kinase pathway [32] and endothelial vasodilatory function [33]. Studies have shown that COX-2 was significantly increased in a rodent model of liver rejection [34]. However, whether increased COX is beneficial or not is controversial. Some studies have shown that increased COX-2 is protective [35], while others have found that inhibition of COX-2 increases graft survival in animal models [34,36]. Moreover, linoleic acid is also associated with pathologies independent of COX, as it is synthesized from phosphatidylcholine via phospholipase A2 or phospholipase A1. Aberrancies of phospholipase A2 are associated with Parkinson disease, peroxisomal beta-oxidation enzyme deficiency, neurodegeneration with brain iron accumulation, and peroxisomal acyl-CoA oxidase deficiency [37,39].
The second metabolite identified by PLS-DA was γ-linolenic acid, which is an all-cis-6,9,12-octadecatrienoic acid designated as 18: 3 and is synthesized from linoleic acid by introduction of a (third) double bond at the delta 6 position under the catalytic influence of delta-6-desaturase enzyme. This step is believed to be the rate-limiting stage in the metabolic pathway. Aging, obesity, diabetes, high alcohol intake, stress-related hormones, and viral infections are known to reduce conversion of linoleic acid to γ-linolenic acid [40–43]. γ-linolenic acid is known to inhibit angiogenesis, partly via the decrease in the expression of VE-cadherin and beta-catenin [44], potentially due to the elimination of the precursor, -linoleic acid. Hepatocyte expression of insulin growth factor-I, insulin growth factor-II, growth hormone receptor, insulin receptor, Insulin growth factor binding protein-3, and Insulin growth factor binding protein-4 mRNAs are all upregulated by linoleic acid [45]. Conversion of linoleic acid to γ-linolenic acid is known to be beneficial for human health [46]. Linolenic acid attenuates endothelial apoptosis
The third metabolite identified by PLS-DA was citrulline, a key intermediate in the urea cycle produced via the metabolism of ornithine and carbamoyl phosphate. Moreover, citrulline is a by-product of the enzymatic production of nitric oxide from the amino acid arginine. As citrulline is a part of the urea cycle and urea is a marker of liver failure, it is not unexpected that rejection is associated with increased citrulline. However, urea levels were not significantly higher in patients with rejection. Because citrulline is involved in many biological pathways, it is impossible to accurately hypothesize the pathobiology, physiological, and biochemical milieu associated with changes to hepatic linoleic acid, γ-linoleic acid and citrulline based on biopsies. However, the fact that they are connected to important hepatic perfusion regulators suggests that changes impart/reflect a response to tissue stress, damage, and/or acute graft rejection. Arginine is the predominate substrate for the production of nitric oxide (NO), a well-documented vasodilator associated with liver perfusion and portal hypertension [51,52]. The role of NO in liver perfusion is well documented and focuses on sinusoidal stellate cell control of sinusoidal dilation and thus an increase in resistance to portal venous blood flow. A reduction in citrulline might be indicative of a modulation of NO biosynthesis. Reduced citrulline could be reflective of a reduction of NOS activity, as citrulline is the biproduct of the conversion of arginine to NO. In contrast, as citrulline is also the substrate, a reduction could be indicative of an increase in NOS activity. What we do know is that a change in NO within the liver will modulate perfusion and affect ischemia and hypoxia and impart an additional stress to the liver. Moreover, endothelial NOS (eNOS) is also known to “uncouple” when co-factors are absent, leading to the formation of oxygen free radicals [53]. The conversion of arginine to NO and citrulline is a 2-step process involving N-hydroxy-l-arginine as an intermediate; therefore, uncoupling of endothelial NOS could result in a reduction in citrulline.
The data do not suggest that either linolenic acid or citrulline should replace current markers of acute liver rejection. LC-MS/MS is unlikely to be quicker or cheaper than histology and liver functional tests. Nevertheless, there is utility in investigating linolenic acid and citrulline, as both have been shown to be markers of interest in other pathologies. For example, the ratio of linolenic acid to deoxycholic acid species is a potential biomarker for metabolic abnormalities in obesity [54] and hepatic steatosis [55]. Moreover, the circulating citrulline concentration is a biomarker of intestinal functionality [56,57]. What the data may reveal is hepatic response to acute liver rejection by the modulation of vasodilators to maintain liver perfusion. However, we are cognizant that differences in metabolomics signatures between control livers and livers with rejection could be independent of rejection. It is possible that these differences are linked to other aspects of liver disease. For example, sarcopenia, which is associated with modulated metabolism, poorer outcomes, and changes in the levels of citrulline and linoleic acid, occurs in patients with liver disease [58–61]. A preliminary analysis of sarcopenia in the patients within this study, based on measurement of the psoas muscle at the C3, as previously described [62,63], was performed and identified 3 patients with sarcopenia. Two patients within the early rejection group had sarcopenia. One patient with no evidence of rejection was identified with sarcopenia. Because the frequency of overlapping sarcopenia within the 3 cohorts is sporadic, it is difficult to determine if sarcopenia is an independent variable in hepatic metabolites associated with hepatic response to rejection.
Additional research is required to further elucidate our findings and to better understand any connection among metabolic changes, acute liver rejection, and graft survival. Further research is likely to focus on metabolomic quantification post-transplant in rodent models of liver rejection [64]. This is because rejection rates observed in clinical programs are very low; therefore, to expand this project using patient samples only would be prohibitive. Moreover, the delayed immunosuppression protocol is controversial and delayed immunosuppression and 2-day protocol biopsies are not the standard of care at our institute at present.
Finally, the immunosuppression protocol deserves further explanation. The premise behind delayed introduction of immunosuppression was to allow immune activation of recipient lymphocytes in the allograft. It was thought that the potent rATG would then lead to apoptosis and death of recipient lymphocytes within the graft, allowing operational tolerance in the long term. Although this approach permits a degree of rejection in the allograft, this is a desired effect and has no adverse effects in the long term, which was demonstrated in our larger study involving 1000 patients [3]. Based on this large-sample experience, we do not believe that deaths that occurred in this study cohort were due to the delayed immunosuppression.
Conclusions
Contemporaneous with acute liver rejection, increases in linoleic acid and γ-linolenic acid are observed alongside a decrease in citrulline. These metabolites are connected to pathways that regulate liver perfusion.
References
1. Au KP, Chan SC, Chok KS, Clinical factors affecting rejection rates in liver transplantation: Hepatobiliary Pancreat Dis Int, 2015; 14(4); 367-73, pmid: 26256080
2. Neil DA, Hubscher SG, Current views on rejection pathology in liver transplantation: Transpl Int, 2010; 23(10); 971-83, pmid: 20723179
3. Mangus RS, Fridell JA, Vianna RM, Immunosuppression induction with rabbit anti-thymocyte globulin with or without rituximab in 1000 liver transplant patients with long-term follow-up: Liver Transpl, 2012; 18(7); 786-95, pmid: 22237953
4. Gao H, Lu Q, Liu X, Application of 1H NMR-based metabonomics in the study of metabolic profiling of human hepatocellular carcinoma and liver cirrhosis: Cancer Sci, 2009; 100(4); 782-85, pmid: 19469021
5. Mayr M, Metabolomics: Ready for the prime time?: Circ Cardiovasc Genet, 2008; 1(1); 58-65, pmid: 20031543
6. Zhang J, Liu L, Wei S, Metabolomics study of esophageal adenocarcinoma: J Thorac Cardiovasc Surg, 2011; 141(2); 469-75, pmid: 20880550
7. Gowda GA, Zhang S, Gu H, Metabolomics-based methods for early disease diagnostics: Expert Rev Mol Diagn, 2008; 8(5); 617-33, pmid: 18785810
8. Bowers J, Hughes E, Skill N, Detection of hepatocellular carcinoma in hepatitis C patients: biomarker discovery by LC-MS: J Chromatogr B Analyt Technol Biomed Life Sci, 2014; 966; 154-62
9. Li S, Liu H, Jin Y, Metabolomics study of alcohol-induced liver injury and hepatocellular carcinoma xenografts in mice: J Chromatogr B Analyt Technol Biomed Life Sci, 2011; 879(24); 2369-75
10. Tan Y, Yin P, Tang L, Metabolomics study of stepwise hepatocarcinogenesis from the model rats to patients: potential biomarkers effective for small hepatocellular carcinoma diagnosis: Mol Cell Proteomics, 2012; 11(2); M111.010694
11. Wang J, Zhang S, Li Z, (1)H-NMR-based metabolomics of tumor tissue for the metabolic characterization of rat hepatocellular carcinoma formation and metastasis: Tumour Biol, 2011; 32(1); 223-31, pmid: 20890798
12. Chen F, Xue J, Zhou L, Identification of serum biomarkers of hepatocarcinoma through liquid chromatography/mass spectrometry-based metabonomic method: Anal Bioanal Chem, 2011; 401(6); 1899-904, pmid: 21833635
13. Chen T, Xie G, Wang X, Serum and urine metabolite profiling reveals potential biomarkers of human hepatocellular carcinoma: Mol Cell Proteomics, 2011; 10(7); M110.004945
14. Lin X, Zhang Y, Ye G, Classification and differential metabolite discovery of liver diseases based on plasma metabolic profiling and support vector machines: J Sep Sci, 2011; 34(21); 3029-36, pmid: 21919198
15. Patterson AD, Maurhofer O, Beyoglu D, Aberrant lipid metabolism in hepatocellular carcinoma revealed by plasma metabolomics and lipid profiling: Cancer Res, 2011; 71(21); 6590-600, pmid: 21900402
16. Shariff MI, Gomaa AI, Cox IJ, Urinary metabolic biomarkers of hepatocellular carcinoma in an Egyptian population: A validation study: J Proteome Res, 2011; 10(4); 1828-36, pmid: 21275434
17. Wang B, Chen D, Chen Y, Metabonomic profiles discriminate hepatocellular carcinoma from liver cirrhosis by ultraperformance liquid chromatography-mass spectrometry: J Proteome Res, 2012; 11(2); 1217-27, pmid: 22200553
18. Wu H, Xue R, Dong L, Metabolomic profiling of human urine in hepatocellular carcinoma patients using gas chromatography/mass spectrometry: Anal Chim Acta, 2009; 648(1); 98-104, pmid: 19616694
19. Xue R, Lin Z, Deng C, A serum metabolomic investigation on hepatocellular carcinoma patients by chemical derivatization followed by gas chromatography/mass spectrometry: Rapid Commun Mass Spectrom, 2008; 22(19); 3061-68, pmid: 18767022
20. Yang J, Xu G, Zheng Y, Diagnosis of liver cancer using HPLC-based metabonomics avoiding false-positive result from hepatitis and hepatocirrhosis diseases: J Chromatogr B Analyt Technol Biomed Life Sci, 2004; 813(1–2); 59-65
21. Yin P, Wan D, Zhao C, A metabonomic study of hepatitis B-induced liver cirrhosis and hepatocellular carcinoma by using RP-LC and HILIC coupled with mass spectrometry: Mol Biosyst, 2009; 5(8); 868-76, pmid: 19603122
22. Zhou L, Wang Q, Yin P, Serum metabolomics reveals the deregulation of fatty acids metabolism in hepatocellular carcinoma and chronic liver diseases: Anal Bioanal Chem, 2012; 403(1); 203-13, pmid: 22349331
23. Everts B, Metabolomics in immunology research: Methods Mol Biol, 2018; 1730; 29-42, pmid: 29363063
24. Baumann AK, Schlue J, Noyan F, Preferential accumulation of T helper cells but not cytotoxic T cells characterizes benign subclinical rejection of human liver allografts: Liver Transpl, 2016; 22(7); 943-55, pmid: 26929119
25. Yang Z, Matteson EL, Goronzy JJ, Weyand CM, T-cell metabolism in autoimmune disease: Arthritis Res Ther, 2015; 17; 29, pmid: 25890351
26. Powell JD, Delgoffe GM, The mammalian target of rapamycin: Linking T cell differentiation, function, and metabolism: Immunity, 2010; 33(3); 301-11, pmid: 20870173
27. , Terminology for hepatic allograft rejection. International Working Party: Hepatology, 1995; 22(2); 648-54, pmid: 7635435
28. Jernigan TW, Fabian TC, Croce MA, Staged management of giant abdominal wall defects: acute and long-term results: Ann Surg, 2003; 238(3); 349-55, pmid: 14501501 discussion 355–57
29. Zhu J, Djukovic D, Deng L, Colorectal cancer detection using targeted serum metabolic profiling: J Proteome Res, 2014; 13(9); 4120-30, pmid: 25126899
30. Skill NJ, Theodorakis NG, Wang YN, Role of cyclooxygenase isoforms in prostacyclin biosynthesis and murine prehepatic portal hypertension: Am J Physiol Gastrointest Liver Physiol, 2008; 295(5); G953-64, pmid: 18772366
31. Jeong SW, Jang JY, Lee SH, Increased expression of cyclooxygenase-2 is associated with the progression to cirrhosis: Korean J Intern Med, 2010; 25(4); 364-71, pmid: 21179273
32. Deshpande R, Mansara P, Kaul-Ghanekar R, Alpha-linolenic acid regulates Cox2/VEGF/MAP kinase pathway and decreases the expression of HPV oncoproteins E6/E7 through restoration of p53 and Rb expression in human cervical cancer cell lines: Tumour Biol, 2016; 37(3); 3295-305, pmid: 26440049
33. Steer P, Vessby B, Lind L, Endothelial vasodilatory function is related to the proportions of saturated fatty acids and alpha-linolenic acid in young men, but not in women: Eur J Clin Invest, 2003; 33(5); 390-96, pmid: 12713452
34. Martelius TJ, Wolff H, Bruggeman CA, Induction of cyclo-oxygenase-2 by acute liver allograft rejection and cytomegalovirus infection in the rat: Transpl Int, 2002; 15(12); 610-14, pmid: 12478407
35. Motino O, Frances DE, Casanova N, Protective role of hepatocyte cyclooxygenase-2 expression against liver ischemia-reperfusion injury in mice: Hepatology, 2018 [Epub ahead of print]
36. Ma N, Szabolcs MJ, Sun J, The effect of selective inhibition of cyclooxygenase (COX)-2 on acute cardiac allograft rejection: Transplantation, 2002; 74(11); 1528-34, pmid: 12490785
37. Cicchetti F, Drouin-Ouellet J, Gross RE, Environmental toxins and Parkinson’s disease: What have we learned from pesticide-induced animal models?: Trends Pharmacol Sci, 2009; 30(9); 475-83, pmid: 19729209
38. Hague SM, Klaffke S, Bandmann O, Neurodegenerative disorders: Parkinson’s disease and Huntington’s disease: J Neurol Neurosurg Psychiatry, 2005; 76(8); 1058-63, pmid: 16024878
39. Pardo LM, van Duijn CM, In search of genes involved in neurodegenerative disorders: Mutat Res, 2005; 592(1–2); 89-101, pmid: 16009383
40. Horrobin DF, Loss of delta-6-desaturase activity as a key factor in aging: Med Hypotheses, 1981; 7(9); 1211-20, pmid: 6270521
41. Kroger J, Schulze MB, Recent insights into the relation of Delta5 desaturase and Delta6 desaturase activity to the development of type 2 diabetes: Curr Opin Lipidol, 2012; 23(1); 4-10, pmid: 22123669
42. Abel S, De Kock M, van Schalkwyk DJ, Altered lipid profile, oxidative status and hepatitis B virus interactions in human hepatocellular carcinoma: Prostaglandins Leukot Essent Fatty Acids, 2009; 81(5–6); 391-99, pmid: 19782547
43. Araya J, Rodrigo R, Pettinelli P, Decreased liver fatty acid delta-6 and delta-5 desaturase activity in obese patients: Obesity (Silver Spring), 2010; 18(7); 1460-63, pmid: 19875987
44. Cai J, Jiang WG, Mansel RE, Inhibition of the expression of VE-cadherin/catenin complex by gamma linolenic acid in human vascular endothelial cells, and its impact on angiogenesis: Biochem Biophys Res Commun, 1999; 258(1); 113-18, pmid: 10222244
45. Fang XL, Shu G, Zhang ZQ, Roles of alpha-linolenic acid on IGF-I secretion and GH/IGF system gene expression in porcine primary hepatocytes: Mol Biol Rep, 2012; 39(12); 10987-96, pmid: 23053988
46. Barcelo-Coblijn G, Murphy EJ, Alpha-linolenic acid and its conversion to longer chain n-3 fatty acids: Benefits for human health and a role in maintaining tissue n-3 fatty acid levels: Prog Lipid Res, 2009; 48(6); 355-74, pmid: 19619583
47. Zhang W, Wang R, Han SF, Alpha-linolenic acid attenuates high glucose-induced apoptosis in cultured human umbilical vein endothelial cells via PI3K/Akt/eNOS pathway: Nutrition, 2007; 23(10); 762-70, pmid: 17716867
48. Lewin M, Samuel S, Merkel J, Bickler P, Varespladib (LY315920) appears to be a potent, broad-spectrum, inhibitor of snake venom phospholipase A2 and a possible pre-referral treatment for envenomation: Toxins (Basel), 2016; 8(9) pii: E248
49. Thotala D, Craft JM, Ferraro DJ, Cytosolic phospholipaseA2 inhibition with PLA-695 radiosensitizes tumors in lung cancer animal models: PLoS One, 2013; 8(7); e69688, pmid: 23894523
50. Lee KL, Foley MA, Chen L, Discovery of Ecopladib, an indole inhibitor of cytosolic phospholipase A2alpha: J Med Chem, 2007; 50(6); 1380-400, pmid: 17305324
51. Theodorakis NG, Wang YN, Skill NJ, The role of nitric oxide synthase isoforms in extrahepatic portal hypertension: Studies in gene-knockout mice: Gastroenterology, 2003; 124(5); 1500-8, pmid: 12730888
52. Theodorakis NG, Wang YN, Wu JM, Role of endothelial nitric oxide synthase in the development of portal hypertension in the carbon tetrachloride-induced liver fibrosis model: Am J Physiol Gastrointest Liver Physiol, 2009; 297(4); G792-99, pmid: 19628654
53. Li H, Forstermann U, Pharmacological prevention of eNOS uncoupling: Curr Pharm Des, 2014; 20(22); 3595-606, pmid: 24180386
54. Lei S, Huang F, Zhao A, The ratio of dihomo-gamma-linolenic acid to deoxycholic acid species is a potential biomarker for the metabolic abnormalities in obesity: FASEB J, 2017; 31(9); 3904-12, pmid: 28490483
55. Matsuda M, Kawamoto T, Tamura R, Predictive value of serum dihomo-gamma-linolenic acid level and estimated Delta-5 desaturase activity in patients with hepatic steatosis: Obes Res Clin Pract, 2017; 11(1); 34-43, pmid: 26964726
56. Fragkos KC, Forbes A, Citrulline as a marker of intestinal function and absorption in clinical settings: A systematic review and meta-analysis: United European Gastroenterol J, 2018; 6(2); 181-91
57. Crenn P, Coudray-Lucas C, Thuillier F, Postabsorptive plasma citrulline concentration is a marker of absorptive enterocyte mass and intestinal failure in humans: Gastroenterology, 2000; 119(6); 1496-505, pmid: 11113071
58. Meeks AC, Madill J, Sarcopenia in liver transplantation: A review: Clin Nutr ESPEN, 2017; 22; 76-80, pmid: 29415839
59. Ogawa SBody weight and bone/calcium metabolism. Sarcopenia and its relationship with bone and calcium metabolism: Clin Calcium, 2018; 28(7); 907-12, pmid: 29950542 [in Japanese]
60. Barillaro C, Liperoti R, Martone AM, The new metabolic treatments for sarcopenia: Aging Clin Exp Res, 2013; 25(2); 119-27, pmid: 23739896
61. Ter Borg S, de Groot LC, Mijnarends DM, Differences in nutrient intake and biochemical nutrient status between sarcopenic and nonsarcopenic older adults-results from the Maastricht Sarcopenia Study: J Am Med Dir Assoc, 2016; 17(5); 393-401, pmid: 26825685
62. Gu DH, Kim MY, Seo YS, Clinical usefulness of psoas muscle thickness for the diagnosis of sarcopenia in patients with liver cirrhosis: Clin Mol Hepatol, 2018; 24(3); 319-30, pmid: 29706058
63. Mangus RS, Bush WJ, Miller C, Severe sarcopenia and increased fat stores in pediatric patients with liver, kidney, or intestine failure: J Pediatr Gastroenterol Nutr, 2017; 65(5); 579-83, pmid: 28604513
64. Kaizu T, Ikeda A, Nakao A, Donor graft adenoviral iNOS gene transfer ameliorates rat liver transplant preservation injury and improves survival: Hepatology, 2006; 43(3); 464-73, pmid: 16496305
In Press
Original article
Steroid Use in ABO-Incompatible Kidney Transplants: Withdrawal vs MaintenanceAnn Transplant In Press; DOI: 10.12659/AOT.947747
Original article
Intra-Arterial Contrast-Enhanced Ultrasound for Transcatheter Thrombolysis in Post-Transplant Hepatic Arter...Ann Transplant In Press; DOI: 10.12659/AOT.947500
Original article
Early Atropine Protocol Enhances Dobutamine Stress Echocardiography in End-Stage Liver Disease: A Practical...Ann Transplant In Press; DOI: 10.12659/AOT.950166
Most Viewed Current Articles
15 Aug 2023 : Review article 7,362
Free-Circulating Nucleic Acids as Biomarkers in Patients After Solid Organ TransplantationDOI :10.12659/AOT.939750
Ann Transplant 2023; 28:e939750
03 Jan 2023 : Original article 7,247
Impact of Autologous Stem Cell Transplantation on Primary Central Nervous System Lymphoma in First-Line and...DOI :10.12659/AOT.938467
Ann Transplant 2023; 28:e938467
16 May 2023 : Original article 7,067
Breaking Antimicrobial Resistance: High-Dose Amoxicillin with Clavulanic Acid for Urinary Tract Infections ...DOI :10.12659/AOT.939258
Ann Transplant 2023; 28:e939258
28 May 2024 : Original article 6,667
Effect of Dexmedetomidine Combined with Remifentanil on Emergence Agitation During Awakening from Sevoflura...DOI :10.12659/AOT.943281
Ann Transplant 2024; 29:e943281
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About Ann Transplant

eISSN: 2329-0358
Annals of Transplantation is one of the fast-developing journals open to all scientists and fields of transplant medicine and related research. The journal is published quarterly and provides extensive coverage of the most important advances in transplantation. Using an electronic on-line submission and peer review tracking system, Annals of Transplantation is committed to rapid review and publication.
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Melville, NY, 11747 | USA
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Copyright © 2025
International Scientific Infromation, Inc.
All rights reserved.
About Ann Transplant

eISSN: 2329-0358
Annals of Transplantation is one of the fast-developing journals open to all scientists and fields of transplant medicine and related research. The journal is published quarterly and provides extensive coverage of the most important advances in transplantation. Using an electronic on-line submission and peer review tracking system, Annals of Transplantation is committed to rapid review and publication.
Categories
ISI Journals
Publisher
International Scientific Information, Inc.
150 Broadhollow Rd., Suite 114
Melville, NY, 11747 | USA
phone:
1.631.629.4327
e-mail:
[email protected]
www:
www.isi-science.com
Information
Copyright © 2025
International Scientific Infromation, Inc.
All rights reserved.
About Ann Transplant

eISSN: 2329-0358
Annals of Transplantation is one of the fast-developing journals open to all scientists and fields of transplant medicine and related research. The journal is published quarterly and provides extensive coverage of the most important advances in transplantation. Using an electronic on-line submission and peer review tracking system, Annals of Transplantation is committed to rapid review and publication.
Categories
Information
Copyright © 2002 - 2025
International Scientific
Infromation, Inc.
All rights reserved.
Links
Publisher
International Scientific Information, Inc.
150 Broadhollow Rd., Suite 114
Melville, NY, 11747 | USA
phone:
1.631.629.4327
e-mail:
[email protected]
www:
www.isi-science.com
In Press
Original article
Diagnostic Utility of FAR1 Methylation Levels in Hepatocellular Carcinoma Patients Undergoing Liver Transpl...Ann Transplant In Press; DOI: 10.12659/AOT.951568
Original article
Inferior Long-Term Outcome of Fatty Liver Allografts After Orthotopic Liver TransplantationAnn Transplant In Press; DOI: 10.12659/AOT.950589
Database Analysis
Identification and Validation of Liver Transplantation-Induced Acute Lung Injury Biomarkers Using a Bioinfo...Ann Transplant In Press; DOI: 10.12659/AOT.950289
Original article
Survival and Recurrence in Liver Transplant Patients With Intrahepatic Cholangiocarcinoma and Hepatocellula...Ann Transplant In Press; DOI: 10.12659/AOT.950997
Most Viewed Current Articles
24 Aug 2021 : Review article 18,372
Normothermic Machine Perfusion (NMP) of the Liver – Current Status and Future PerspectivesDOI :10.12659/AOT.931664
Ann Transplant 2021; 26:e931664
05 Apr 2022 : Original article 14,731
Impact of Statins on Hepatocellular Carcinoma Recurrence After Living-Donor Liver TransplantationDOI :10.12659/AOT.935604
Ann Transplant 2022; 27:e935604
22 Nov 2022 : Original article 14,244
Long-Term Effects of Everolimus-Facilitated Tacrolimus Reduction in Living-Donor Liver Transplant Recipient...DOI :10.12659/AOT.937988
Ann Transplant 2022; 27:e937988
29 Dec 2021 : Original article 13,752
Efficacy and Safety of Tacrolimus-Based Maintenance Regimens in De Novo Kidney Transplant Recipients: A Sys...DOI :10.12659/AOT.933588
Ann Transplant 2021; 26:e933588
Your Privacy
We use cookies to ensure the functionality of our website, to personalize content and advertising, to provide social media features, and to analyze our traffic. If you allow us to do so, we also inform our social media, advertising and analysis partners about your use of our website, You can decise for yourself which categories you you want to deny or allow. Please note that based on your settings not all functionalities of the site are available. View our privacy policy.
About Ann Transplant

eISSN: 2329-0358
Annals of Transplantation is one of the fast-developing journals open to all scientists and fields of transplant medicine and related research. The journal is published quarterly and provides extensive coverage of the most important advances in transplantation. Using an electronic on-line submission and peer review tracking system, Annals of Transplantation is committed to rapid review and publication.
Categories
ISI Journals
Publisher
International Scientific Information, Inc.
150 Broadhollow Rd., Suite 114
Melville, NY, 11747 | USA
phone:
1.631.629.4327
e-mail:
[email protected]
www:
www.isi-science.com
Information
Copyright © 2026
International Scientific Information, Inc.
All rights reserved.
About Ann Transplant

eISSN: 2329-0358
Annals of Transplantation is one of the fast-developing journals open to all scientists and fields of transplant medicine and related research. The journal is published quarterly and provides extensive coverage of the most important advances in transplantation. Using an electronic on-line submission and peer review tracking system, Annals of Transplantation is committed to rapid review and publication.
Categories
ISI Journals
Publisher
International Scientific Information, Inc.
150 Broadhollow Rd., Suite 114
Melville, NY, 11747 | USA
phone:
1.631.629.4327
e-mail:
[email protected]
www:
www.isi-science.com
Information
Copyright © 2026
International Scientific Information, Inc.
All rights reserved.
About Ann Transplant

eISSN: 2329-0358
Annals of Transplantation is one of the fast-developing journals open to all scientists and fields of transplant medicine and related research. The journal is published quarterly and provides extensive coverage of the most important advances in transplantation. Using an electronic on-line submission and peer review tracking system, Annals of Transplantation is committed to rapid review and publication.
Categories
Information
Copyright © 2002 - 2026
International Scientific
Information, Inc.
All rights reserved.
Links
Publisher
International Scientific Information, Inc.
150 Broadhollow Rd., Suite 114
Melville, NY, 11747 | USA
phone:
1.631.629.4327
e-mail:
[email protected]
www:
www.isi-science.com






