Application of metabolomics to investigate the process of human orthotopic liver transplantation: a proof-of-principle study

Recent Progress and Future Direction for the Application of Multiomics Data in Clinical Liver Transplantation

Omics data address key issues in liver transplantation (LT) as the most effective therapeutic means for end-stage liver disease. The purpose of this study was to review the current application and future direction for omics in LT. We reviewed the use of multiomics to elucidate the pathogenesis leading to LT and prognostication. Future directions with respect to the use of omics in LT are also described based on perspectives of surgeons with experience in omics. Significant molecules were identified and summarized based on omics, with a focus on post-transplant liver fibrosis, early allograft dysfunction, tumor recurrence, and graft failure. We emphasized the importance omics for clinicians who perform LTs and prioritized the directions that should be established. We also outlined the ideal workflow for omics in LT. In step with advances in technology, the quality of omics data can be guaranteed using an improved algorithm at a lower price. Concerns should be addressed on the translational value of omics for better therapeutic effects in patients undergoing LT.

Quantitative Metabolomics of Tissue, Perfusate, and Bile from Rat Livers Subjected to Normothermic Machine Perfusion

Machine perfusion (MP) allows the maintenance of liver cells in a metabolically active state ex vivo and can potentially revert metabolic perturbations caused by donor warm ischemia, procurement, and static cold storage (SCS). The present preclinical research investigated the metabolic outcome of the MP procedure by analyzing rat liver tissue, bile, and perfusate samples by means of high-field (600 MHz) nuclear magnetic resonance (NMR) spectroscopy. An established rat model of normothermic MP (NMP) was used. Experiments were carried out with the addition of an oxygen carrier (OxC) to the perfusion fluid (OxC-NMP, n = 5) or without (h-NMP, n = 5). Bile and perfusate samples were collected throughout the procedure, while biopsies were only taken at the end of NMP. Two additional groups were: (1) Native, in which tissue or bile specimens were collected from rats in resting conditions; and (2) SCS, in which biopsies were taken from cold-stored livers. Generally, NMP groups showed a distinctive metabolomic signature in all the analyzed biological matrices. In particular, many of the differentially expressed metabolites were involved in mitochondrial biochemical pathways. Succinate, acetate, 3-hydroxybutyrate, creatine, and O-phosphocholine were deeply modulated in ex vivo perfused livers compared to both the Native and SCS groups. These novel results demonstrate a broad modulation of mitochondrial metabolism during NMP that exceeds energy production and redox balance maintenance.

Targeted metabolomics analysis of postoperative delirium

Postoperative delirium is the most common complication among older adults undergoing major surgery. The pathophysiology of delirium is poorly understood, and no blood-based, predictive markers are available. We characterized the plasma metabolome of 52 delirium cases and 52 matched controls from the Successful Aging after Elective Surgery (SAGES) cohort (N = 560) of patients ≥ 70 years old without dementia undergoing scheduled major non-cardiac surgery. We applied targeted mass spectrometry with internal standards and pooled controls using a nested matched case-control study preoperatively (PREOP) and on postoperative day 2 (POD2) to identify potential delirium risk and disease markers. Univariate analyses identified 37 PREOP and 53 POD2 metabolites associated with delirium and multivariate analyses achieved significant separation between the two groups with an 11-metabolite prediction model at PREOP (AUC = 83.80%). Systems biology analysis using the metabolites with differential concentrations rendered "valine, leucine, and isoleucine biosynthesis" at PREOP and "citrate cycle" at POD2 as the most significantly enriched pathways (false discovery rate < 0.05). Perturbations in energy metabolism and amino acid synthesis pathways may be associated with postoperative delirium and suggest potential mechanisms for delirium pathogenesis. Our results could lead to the development of a metabolomic delirium predictor.

Deregulation of the Purine Pathway in Pre-Transplant Liver Biopsies Is Associated with Graft Function and Survival after Transplantation

The current shortage of livers for transplantation has increased the use of marginal organs sourced from donation after circulatory death (DCD). However, these organs have a higher incidence of graft failure, and pre-transplant biomarkers which predict graft function and survival remain limited. Here, we aimed to find biomarkers of liver function before transplantation to allow better clinical evaluation. Matched pre- and post-transplant liver biopsies from DCD (n = 24) and donation after brain death (DBD, n = 70) were collected. Liver biopsies were analysed using mass spectroscopy molecular phenotyping. Discrimination analysis was used to parse metabolites differentiated between the two groups. Five metabolites in the purine pathway were investigated. Of these, the ratios of the levels of four metabolites to those of urate differed between DBD and DCD biopsies at the pre-transplantation stage (q < 0.05). The ratios of Adenosine monophosphate (AMP) and adenine levels to those of urate also differed in biopsies from recipients experiencing early graft function (EGF) (q < 0.05) compared to those of recipients experiencing early allograft dysfunction (EAD). Using random forest, a panel consisting of alanine aminotransferase (ALT) and the ratios of AMP, adenine, and hypoxanthine levels to urate levels predicted EGF with area under the curve (AUC) of 0.84 (95% CI (0.71, 0.97)). Survival analysis revealed that the metabolite classifier could stratify six-year survival outcomes (p = 0.0073). At the pre-transplantation stage, a panel composed of purine metabolites and ALT could improve the prediction of EGF and survival.

Systematic Review: Clinical Metabolomics to Forecast Outcomes in Liver Transplantation Surgery

Liver transplantation is an effective intervention for end-stage liver disease, fulminant hepatic failure, and early hepatocellular carcinoma. Yet, there is marked patient-to-patient variation in liver transplantation outcomes. This calls for novel diagnostics to enable rational deployment of donor livers. Metabolomics is a postgenomic high-throughput systems biology approach to diagnostic innovation in clinical medicine. We report here an original systematic review of the metabolomic studies that have identified putative biomarkers in the context of liver transplantation. Eighteen studies met the inclusion criteria that involved sampling of blood (n = 4), dialysate fluid (n = 4), bile (n = 5), and liver tissue (n = 5). Metabolites of amino acid and nitrogen metabolism, anaerobic glycolysis, lipid breakdown products, and bile acid metabolism were significantly different in transplanted livers with and without graft dysfunction. However, criteria for defining the graft dysfunction varied across studies. This systematic review demonstrates that metabolomics can be deployed in identification of metabolic indicators of graft dysfunction with a view to implicated molecular mechanisms. We conclude the article with a horizon scanning of metabolomics technology in liver transplantation and its future prospects and challenges in research and clinical practice.

Microdialysis Workflow for Metabotyping Superficial Pathologies: Application to Burn Injury

Burn injury can be a devastating traumatic injury, with long-term personal and social implications for the patient. The many complex local and disseminating pathological processes underlying burn injury's clinical challenges are orchestrated from the site of injury and develop over time, yet few studies of the molecular basis of these mechanisms specifically explore the local signaling environment. Those that do are typically destructive in nature and preclude the collection of longitudinal temporal data. Burn injury therefore exemplifies a superficial temporally dynamic pathology for which experimental sampling typically prioritizes either specificity to the local burn site or continuous collection from circulation. Here, we present an exploratory approach to the targeted elucidation of complex, local, acutely temporally dynamic interstitia through its application to burn injury. Subcutaneous microdialysis is coupled with ultraperformance liquid chromatography-mass spectrometry (UPLC-MS) analysis, permitting the application of high-throughput metabolomic profiling to samples collected both continuously and specifically from the burn site. We demonstrate this workflow's high yield of burn-altered metabolites including the complete structural elucidation of niacinamide and uric acid, two compounds potentially involved in the pathology of burn injury. Further understanding the metabolic changes induced by burn injury will help to guide therapeutic intervention in the future. This approach is equally applicable to the analysis of other tissues and pathological conditions, so it may further improve our understanding of the metabolic changes underlying a wide variety of pathological processes.

Computational Modeling in Liver Surgery

The need for extended liver resection is increasing due to the growing incidence of liver tumors in aging societies. Individualized surgical planning is the key for identifying the optimal resection strategy and to minimize the risk of postoperative liver failure and tumor recurrence. Current computational tools provide virtual planning of liver resection by taking into account the spatial relationship between the tumor and the hepatic vascular trees, as well as the size of the future liver remnant. However, size and function of the liver are not necessarily equivalent. Hence, determining the future liver volume might misestimate the future liver function, especially in cases of hepatic comorbidities such as hepatic steatosis. A systems medicine approach could be applied, including biological, medical, and surgical aspects, by integrating all available anatomical and functional information of the individual patient. Such an approach holds promise for better prediction of postoperative liver function and hence improved risk assessment. This review provides an overview of mathematical models related to the liver and its function and explores their potential relevance for computational liver surgery. We first summarize key facts of hepatic anatomy, physiology, and pathology relevant for hepatic surgery, followed by a description of the computational tools currently used in liver surgical planning. Then we present selected state-of-the-art computational liver models potentially useful to support liver surgery. Finally, we discuss the main challenges that will need to be addressed when developing advanced computational planning tools in the context of liver surgery.

A Metabolomics Signature Linked To Liver Fibrosis In The Serum Of Transplanted Hepatitis C Patients

Liver fibrosis must be evaluated in patients with hepatitis C virus (HCV) after liver transplantation because its severity affects their prognosis and the recurrence of HCV. Since invasive biopsy is still the gold standard to identify patients at risk of graft loss from rapid fibrosis progression, it becomes crucial the development of new accurate, non-invasive methods that allow repetitive examination of the patients. Therefore, we have developed a non-invasive, accurate model to distinguish those patients with different liver fibrosis stages. Two hundred and three patients with HCV were histologically classified (METAVIR) into five categories of fibrosis one year after liver transplantation. In this cross-sectional study, patients at fibrosis stages F0-F1 (n = 134) were categorised as “slow fibrosers” and F2-F4 (n = 69) as “rapid fibrosers”. Chloroform/methanol serum extracts were analysed by reverse ultra-high performance liquid chromatography coupled to mass spectrometry. A diagnostic model was built through linear discriminant analyses. An algorithm consisting of two sphingomyelins and two phosphatidylcholines accurately classifies rapid and slow fibrosers after transplantation. The proposed model yielded an AUROC of 0.92, 71% sensitivity, 85% specificity, and 84% accuracy. Moreover, specific bile acids and sphingomyelins increased notably along with liver fibrosis severity, differentiating between rapid and slow fibrosers.

Mass Spectrometry Based Metabolomics Comparison of Liver Grafts from Donors after Circulatory Death (DCD) and Donors after Brain Death (DBD) Used in Human Orthotopic Liver Transplantation

Use of marginal liver grafts, especially those from donors after circulatory death (DCD), has been considered as a solution to organ shortage. Inferior outcomes have been attributed to donor warm ischaemic damage in these DCD organs. Here we sought to profile the metabolic mechanisms underpinning donor warm ischaemia. Non-targeted Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometry metabolomics was applied to biopsies of liver grafts from donors after brain death (DBD; n = 27) and DCD (n = 10), both during static cold storage (T₁) as well as post-reperfusion (T₂). Furthermore 6 biopsies from DBD donors prior to the organ donation (T₀) were also profiled. Considering DBD and DCD together, significant metabolic differences were discovered between T₁ and T₂ (688 peaks) that were primarily related to amino acid metabolism, meanwhile T₀ biopsies grouped together with T₂, denoting the distinctively different metabolic activity of the perfused state. Major metabolic differences were discovered between DCD and DBD during cold-phase (T₁) primarily related to glucose, tryptophan and kynurenine metabolism, and in the post-reperfusion phase (T₂) related to amino acid and glutathione metabolism. We propose tryptophan/kynurenine and S-adenosylmethionine as possible biomarkers for the previously established higher graft failure of DCD livers, and conclude that the associated pathways should be targeted in more exhaustive and quantitative investigations.

Metabolic profiling during ex vivo machine perfusion of the human liver

As donor organ shortages persist, functional machine perfusion is under investigation to improve preservation of the donor liver. The transplantation of donation after circulatory death (DCD) livers is limited by poor outcomes, but its application may be expanded by ex vivo repair and assessment of the organ before transplantation. Here we employed subnormothermic (21 °C) machine perfusion of discarded human livers combined with metabolomics to gain insight into metabolic recovery during machine perfusion. Improvements in energetic cofactors and redox shifts were observed, as well as reversal of ischemia-induced alterations in selected pathways, including lactate metabolism and increased TCA cycle intermediates. We next evaluated whether DCD livers with steatotic and severe ischemic injury could be discriminated from ‘transplantable’ DCD livers. Metabolomic profiling was able to cluster livers with similar metabolic patterns based on the degree of injury. Moreover, perfusion parameters combined with differences in metabolic factors suggest variable mechanisms that result in poor energy recovery in injured livers. We conclude that machine perfusion combined with metabolomics has significant potential as a clinical instrument for the assessment of preserved livers.

Management of immunosuppressant agents following liver transplantation: Less is more

Immunosuppression in organ transplantation was revolutionary for its time, but technological and population changes cast new light on its use. First, metabolic syndrome (MS) is increasing as a public health issue, concomitantly increasing as an issue for post-orthotopic liver transplantation patients; yet the medications regularly used for immunosuppression contribute to dysfunctional metabolism. Current mainstay immunosuppression involves the use of calcineurin inhibitors; these are potent, but nonspecifically disrupt intracellular signaling in such a way as to exacerbate the impact of MS on the liver. Second, the impacts of acute cellular rejection and malignancy are reviewed in terms of their severity and possible interactions with immunosuppressive medications. Finally, immunosuppressive agents must be considered in terms of new developments in hepatitis C virus treatment, which undercut what used to be inevitable viral recurrence. Overall, while traditional immunosuppressive agents remain the most used, the specific side-effect profiles of all immunosuppressants must be weighed in light of the individual patient.

Lipidomics comparing DCD and DBD liver allografts uncovers lysophospholipids elevated in recipients undergoing early allograft dysfunction

Finding specific biomarkers of liver damage in clinical evaluations could increase the pool of available organs for transplantation. Lipids are key regulators in cell necrosis and hence this study hypothesised that lipid levels could be altered in organs suffering severe ischemia. Matched pre- and post-transplant biopsies from donation after circulatory death (DCD, n = 36, mean warm ischemia time = 2 min) and donation after brain death (DBD, n = 76, warm ischemia time = none) were collected. Lipidomic discovery and multivariate analysis (MVA) were applied. Afterwards, univariate analysis and clinical associations were conducted for selected lipids differentiating between these two groups. MVA grouped DCD vs. DBD (p = 6.20 × 10(-12)) and 12 phospholipids were selected for intact lipid measurements. Two lysophosphatidylcholines, LysoPC (16:0) and LysoPC (18:0), showed higher levels in DCD at pre-transplantation (q < 0.01). Lysophosphatidylcholines were associated with aspartate aminotransferase (AST) 14-day post-transplantation (q < 0.05) and were more abundant in recipients undergoing early allograft dysfunction (EAD) (p < 0.05). A receiver-operating characteristics (ROC) curve combining both lipid levels predicted EAD with 82% accuracy. These findings suggest that LysoPC (16:0) and LysoPC (18:0) might have a role in signalling liver tissue damage due to warm ischemia before transplantation.

Biomarker differences between cadaveric grafts used in human orthotopic liver transplantation as identified by coulometric electrochemical array detection (CEAD) metabolomics

Metabolomics in systems biology research unravels intracellular metabolic changes by high throughput methods, but such studies focusing on liver transplantation (LT) are limited. Microdialysate samples of liver grafts from donors after circulatory death (DCD; n=13) and brain death (DBD; n=27) during cold storage and post-reperfusion phase were analyzed through coulometric electrochemical array detection (CEAD) for identification of key metabolomics changes. Metabolite peak differences between the graft types at cold phase, post-reperfusion trends, and in failed allografts, were identified against reference chromatograms. In the cold phase, xanthine, uric acid, and kynurenine were overexpressed in DCD by 3-fold, and 3-nitrotyrosine (3-NT) and 4-hydroxy-3-methoxymandelic acid (HMMA) in DBD by 2-fold (p<0.05). In both grafts, homovanillic acid and methionine increased by 20%-30% with each 100 min increase in cold ischemia time (p<0.05). Uric acid expression was significantly different in DCD post-reperfusion. Failed allografts had overexpression of reduced glutathione and kynurenine (cold phase) and xanthine (post-reperfusion) (p<0.05). This differential expression of metabolites between graft types is a novel finding, meanwhile identification of overexpression of kynurenine in DCD grafts and in failed allografts is unique. Further studies should examine kynurenine as a potential biomarker predicting graft function, its causation, and actions on subsequent clinical outcomes.

Analytical protocols based on LC-MS, GC-MS and CE-MS for nontargeted metabolomics of biological tissues

Invasive, site-specific metabolite information could be better obtained from tissues. Hence, highly sensitive mass spectrometry-based metabolomics coupled with separation techniques are increasingly in demand in clinical research for tissue metabolomics application. Applying these techniques to nontargeted tissue metabolomics provides identification of distinct metabolites. These findings could help us to understand alterations at the molecular level, which can also be applied in clinical practice as screening markers for early disease diagnosis. However, tissues as solid and heterogeneous samples pose an additional analytical challenge that should be considered in obtaining broad, reproducible and representative analytical profiles. This manuscript summarizes the state of the art in tissue (human and animal) treatment (quenching, homogenization and extraction) for nontargeted metabolomics with mass spectrometry.

Metabolomics discloses donor liver biomarkers associated with early allograft dysfunction

BACKGROUND & AIMS

Early allograft dysfunction (EAD) dramatically influences graft and patient outcome after orthotopic liver transplantation and its incidence is strongly determined by donor liver quality. Nevertheless, objective biomarkers, which can assess graft quality and anticipate organ function, are still lacking. This study aims to investigate whether there is a preoperative donor liver metabolomic biosignature associated with EAD.

METHODS

A comprehensive metabolomic profiling of 124 donor liver biopsies collected before transplantation was performed by mass spectrometry coupled to liquid chromatography. Donor liver grafts were classified into two groups: showing EAD and immediate graft function (IGF). Multivariate data analysis was used to search for the relationship between the metabolomic profiles present in donor livers before transplantation and their function in recipients.

RESULTS

A set of liver graft dysfunction-associated biomarkers was identified. Key changes include significantly increased levels of bile acids, lysophospholipids, phospholipids, sphingomyelins and histidine metabolism products, all suggestive of disrupted lipid homeostasis and altered histidine pathway. Based on these biomarkers, a predictive EAD model was built and further evaluated by assessing 24 independent donor livers, yielding 91% sensitivity and 82% specificity. The model was also successfully challenged by evaluating donor livers showing primary non-function (n=4).

CONCLUSIONS

A metabolomic biosignature that accurately differentiates donor livers, which later showed EAD or IGF, has been deciphered. The remarkable metabolomic differences between donor livers before transplant can relate to their different quality. The proposed metabolomic approach may become a clinical tool for donor liver quality assessment and for anticipating graft function before transplant.

Direct infusion mass spectrometry metabolomics dataset: a benchmark for data processing and quality control

Direct-infusion mass spectrometry (DIMS) metabolomics is an important approach for characterising molecular responses of organisms to disease, drugs and the environment. Increasingly large-scale metabolomics studies are being conducted, necessitating improvements in both bioanalytical and computational workflows to maintain data quality. This dataset represents a systematic evaluation of the reproducibility of a multi-batch DIMS metabolomics study of cardiac tissue extracts. It comprises of twenty biological samples (cow vs. sheep) that were analysed repeatedly, in 8 batches across 7 days, together with a concurrent set of quality control (QC) samples. Data are presented from each step of the workflow and are available in MetaboLights. The strength of the dataset is that intra- and inter-batch variation can be corrected using QC spectra and the quality of this correction assessed independently using the repeatedly-measured biological samples. Originally designed to test the efficacy of a batch-correction algorithm, it will enable others to evaluate novel data processing algorithms. Furthermore, this dataset serves as a benchmark for DIMS metabolomics, derived using best-practice workflows and rigorous quality assessment.

Future perspectives of Chinese medical formulae: chinmedomics as an effector

Traditional Chinese medicine (TCM) has been used for thousands of years to treat or prevent disease. The health care paradigm has shifted from a focus on disease to TCM therapy with a holistic approach. However, the actual value of TCM has not been fully recognized worldwide due to a lack of scientific approaches to its study. Today omics has become practically available, and resembles TCM in many aspects, and can serve as a key driving force for the translation of the traditional Chinese medical formulae (chinmediformulae) into practice, and will develop and advance the concept of the metabolomics of chinmediformulae (chinmedomics). Chinmedomics seeks to elucidate the therapeutic and synergistic properties and metabolism of chinmediformulae and the involved metabolic pathways using modern analytical techniques. It is an integral part of top-down systems biology, which aims to improve understanding of chinmediformulae. This approach of combining chinmedomics with chinmediformulae with modern health care systems may lead to a revolution in TCM therapy. Although the scientific study of chinmedomics is at an early stage and requires further scrutiny and validation, the approach has major implications to improve the efficacy of chinmediformulae. This article introduces and reviews the concept of chinmedomics, and highlights recent examples of the approach, which are presented for description and discussion.

Current trends and challenges in sample preparation for global metabolomics using liquid chromatography-mass spectrometry

The choice of sample-preparation method is extremely important in metabolomic studies because it affects both the observed metabolite content and biological interpretation of the data. An ideal sample-preparation method for global metabolomics should (i) be as non-selective as possible to ensure adequate depth of metabolite coverage; (ii) be simple and fast to prevent metabolite loss and/or degradation during the preparation procedure and enable high-throughput; (iii) be reproducible; and (iv) incorporate a metabolism-quenching step to represent true metabolome composition at the time of sampling. Despite its importance, sample preparation is often an overlooked aspect of metabolomics, so the focus of this review is to explore the role, challenges, and trends in sample preparation specifically within the context of global metabolomics by liquid chromatography-mass spectrometry (LC-MS). This review will cover the most common methods including solvent precipitation and extraction, solid-phase extraction and ultrafiltration, and discuss how to improve analytical quality and metabolite coverage in metabolomic studies of biofluids, tissues, and mammalian cells. Recent developments in this field will also be critically examined, including in vivo methods, turbulent-flow chromatography, and dried blood spot sampling.

Metabolomics of oxidative stress in recent studies of endogenous and exogenously administered intermediate metabolites

Aerobic metabolism occurs in a background of oxygen radicals and reactive oxygen species (ROS) that originate from the incomplete reduction of molecular oxygen in electron transfer reactions. The essential role of aerobic metabolism, the generation and consumption of ATP and other high energy phosphates, sustains a balance of approximately 3000 essential human metabolites that serve not only as nutrients, but also as antioxidants, neurotransmitters, osmolytes, and participants in ligand-based and other cellular signaling. In hypoxia, ischemia, and oxidative stress, where pathological circumstances cause oxygen radicals to form at a rate greater than is possible for their consumption, changes in the composition of metabolite ensembles, or metabolomes, can be associated with physiological changes. Metabolomics and metabonomics are a scientific disciplines that focuse on quantifying dynamic metabolome responses, using multivariate analytical approaches derived from methods within genomics, a discipline that consolidated innovative analysis techniques for situations where the number of biomarkers (metabolites in our case) greatly exceeds the number of subjects. This review focuses on the behavior of cytosolic, mitochondrial, and redox metabolites in ameliorating or exacerbating oxidative stress. After reviewing work regarding a small number of metabolites—pyruvate, ethyl pyruvate, and fructose-1,6-bisphosphate—whose exogenous administration was found to ameliorate oxidative stress, a subsequent section reviews basic multivariate statistical methods common in metabolomics research, and their application in human and preclinical studies emphasizing oxidative stress. Particular attention is paid to new NMR spectroscopy methods in metabolomics and metabonomics. Because complex relationships connect oxidative stress to so many physiological processes, studies from different disciplines were reviewed. All, however, shared the common goal of ultimately developing “omics”-based, diagnostic tests to help influence therapies.