Metabolomics: Perspectives on potential biomarkers in organ transplantation and immunosuppressant toxicity

Integration of FTIR Spectroscopy and Machine Learning for Kidney Allograft Rejection: A Complementary Diagnostic Tool

Background: Kidney transplantation is a life-saving treatment for end-stage kidney disease, but allograft rejection remains a critical challenge, requiring accurate and timely diagnosis. The study aims to evaluate the integration of Fourier Transform Infrared (FTIR) spectroscopy and machine learning algorithms as a minimally invasive method to detect kidney allograft rejection and differentiate between T Cell-Mediated Rejection (TCMR) and Antibody-Mediated Rejection (AMR). Additionally, the goal is to discriminate these rejection types aiming to develop a reliable decision-making support tool. Methods: This retrospective study included 41 kidney transplant recipients and analyzed 81 serum samples matched to corresponding allograft biopsies. FTIR spectroscopy was applied to pre-biopsy serum samples, and Naïve Bayes classification models were developed to distinguish rejection from non-rejection and classify rejection types. Data preprocessing involved, e.g., atmospheric compensation, second derivative, and feature selection using Fast Correlation-Based Filter for spectral regions 600-1900 cm-1 and 2800-3400 cm-1. Model performance was assessed via area under the receiver operating characteristic curve (AUC-ROC), sensitivity, specificity, and accuracy. Results: The Naïve Bayes model achieved an AUC-ROC of 0.945 in classifying rejection versus non-rejection and AUC-ROC of 0.989 in distinguishing TCMR from AMR. Feature selection significantly improved model performance, identifying key spectral wavenumbers associated with rejection mechanisms. This approach demonstrated high sensitivity and specificity for both classification tasks. Conclusions: The integration of FTIR spectroscopy with machine learning may provide a promising, minimally invasive method for early detection and precise classification of kidney allograft rejection. Further validation in larger, more diverse populations is needed to confirm these findings' reliability.

Metabolomic Profiling of Plasma, Urine, and Saliva of Kidney Transplantation Recipients

Kidney biopsy is commonly used to diagnose kidney transplant dysfunction after transplantation. Therefore, the development of minimally invasive and quantitative methods to evaluate kidney function in transplant recipients is necessary. Here, we used capillary electrophoresis-mass spectrometry to analyze the biofluids collected from transplant recipients with impaired (Group I, n = 31) and stable (Group S, n = 19) kidney function and from donors (Group D, n = 9). Metabolomics analyses identified and quantified 97 metabolites in plasma, 133 metabolites in urine, and 108 metabolites in saliva. Multivariate analyses revealed apparent differences in the metabolomic profiles of the three groups. In plasma samples, arginine biosynthesis and purine metabolism between the I and S Groups differed. In addition, considerable differences in metabolomic profiles were observed between samples collected from participants with T cell-mediated rejection (TCR), antibody-mediated rejection, and other kidney disorders (KD). The metabolomic profiles in the three types of biofluids showed different patterns between TCR and KD, wherein 3-indoxyl sulfate showed a significant increase in TCR consistently in both plasma and urine samples. These results suggest that each biofluid has different metabolite features to evaluate kidney function after transplantation and that 3-indoxyl sulfate could predict acute rejection.

Improving data quality in liquid chromatography-mass spectrometry metabolomics of human urine

Signal variation is a common drawback in untargeted metabolomics using liquid chromatography-mass spectrometry (LC-MS), mainly due to the complexity of biological matrices and reduced sample preparation, which results in the accumulation of sample components in the column and the ion source. Here we propose a simple, easy to implement approach to improve data quality in untargeted metabolomics by LC-MS. This approach involves the use of a divert valve to direct the column effluent to waste at the beginning of the chromatographic run and during column cleanup and equilibration, in combination with longer column cleanups in between injections. Our approach was tested using urine samples collected from patients after renal transplantation. Analytical responses were contrasted before and after introducing these modifications by analyzing a batch of untargeted metabolomics data. A significant improvement in peak area repeatability was observed for the quality controls, with relative standard deviations (RSDs) for several metabolites decreasing from ∼60% to ∼10% when our approach was introduced. Similarly, RSDs of peak areas for internal standards improved from ∼40% to ∼10%. Furthermore, calibrant solutions were more consistent after introducing these modifications when comparing peak areas of solutions injected at the beginning and the end of each analytical sequence. Therefore, we recommend the use of a divert valve and extended column cleanup as a powerful strategy to improve data quality in untargeted metabolomics, especially for very complex types of samples where minimum sample preparation is required, such as in this untargeted metabolomics study with urine from renal transplanted patients.

Combination of mesenchymal stem cells and FK506 prolongs heart allograft survival by inhibiting TBK1/IRF3-regulated-IFN-γ production

Lifelong immunosuppression use presents many serious side effects to transplant recipients. Previous studies have shown that mesenchymal stem cells (MSC) regulate the progress of inflammation and protect allograft function. However, the benefits of MSC combined with low-dose tacrolimus (FK506) has not been investigated in heart transplant recipients, and its mechanism deserves further investigation. SD Rat bone marrow-derived MSC were infused into recipient mouse (C57BL/6, B6) through the tail vein, followed by a BALB/c donor cervical ectopic heart transplantation on the next day of infusion. T-lymphocyte subsets and their functions were determined using flow cytometry, ELISA, and qPCR. Thereafter, in vitro and in vivo experiments were conducted to identify the mechanisms regarding MSC and FK506 combination (MF group) use in regulating IFN-γ signaling. MF group in the allogeneic heart transplantation mouse model inhibited acute rejection and prolonged mean survival time (MST) of grafts from 7 days (d) to 22d. Pathological examination of heart grafts suggested that inflammatory cell infiltration decreased, and tissue damage was significantly reduced in the MF group. IFN-γ mRNA expression levels in the grafts and recipients decreased, while IL-4 and TGF-β mRNA expression increased in the MF group. Phosphorylation of TBK1/IRF3 in recipient immune cells decreased under donor antigen stimulation. Combination use of MSC and FK506 can prolong graft survival, possibly by down-regulating TBK1/IRF3 phosphorylation, thus reducing IFN-γ production to prevent infiltration of inflammatory cells in the graft and extend graft survival. The findings provide a potential new approach to immunosuppression selection.

Fecal Metabolomics Reveals Distinct Profiles of Kidney Transplant Recipients and Healthy Controls

Monitoring graft recipients remains dependent on traditional biomarkers and old technologies lacking specificity, sensitivity, or accuracy. Recently, metabolomics is becoming a promising approach that may offer to kidney transplants a more effective and specific monitoring. Furthermore, emerging evidence suggested a fundamental role of gut microbiota as an important determinant of patients’ metabolomes. In the current study, we enrolled forty stable renal allografts recipients compared to twenty healthy individuals. Samples were taken at different time points from patient to patient following transplantation surgery, which varied from 3 months to 22 years post-graft. All patients started the immunosuppression therapy immediately following kidney graft (Day 0). Gas chromatography–mass spectrometry (GC–MS) was employed to perform untargeted analysis of fecal metabolites. Globally, the fecal metabolic signature was significantly different between kidney transplants and the control group. Fecal metabolome was dominated by lipids (sterols and fatty acids) in the stable transplant group compared to the controls (p < 0.05). Overall, 18 metabolites were significantly altered within kidney transplant recipients. Furthermore, the most notable altered metabolic pathways in kidney transplants include ubiquinone and other terpenoid-quinone biosynthesis, tyrosine metabolism, tryptophan biosynthesis, and primary bile acid biosynthesis. Fecal metabolites could effectively distinguish stable transplant recipients from controls, supporting the potential utility of metabolomics in rapid and non-invasive diagnosis to produce relevant biomarkers and to help clinicians in monitoring kidney transplants. Further investigations are needed to clarify the physiological relevance of fecal metabolome and to assess the impact of microbiota modulation.

Graft assessment for acute rejection after intestinal transplantation: current status and future perspective

Intestinal transplantation has since its inception evolved as a lifesaving treatment option for patients with irreversible intestinal failure who can no longer be sustained on parenteral nutrition. Improvement in short-term survival after transplantation has also justified the expansion of treatment indications. Unfortunately, success is somewhat limited by a plateau observed in long-term survival. The reason for this sub-optimal long-term result experienced in this cohort may in part be attributed to the intestinal graft with the lymphoid content it carries inflicting the host with multiple complications where acute cellular rejection is one of the most common causes for graft loss. Graft monitoring is for this reason of paramount importance and detection of rejection at an early stage essential to enable early instigation of treatment and successful reversal of the pathology. Due to the challenges in diagnosing acute rejection with a noninvasive marker we are still limited to a surveillance protocol using endoscopy and biopsies for the diagnosis of rejection. The purpose of our paper is to review the adequacy of different methods in monitoring the graft for acute rejection using biomarkers, endoscopy and imaging. In conclusion, the evidence base continues to support the use of histology for the diagnosis of acute rejection. The role of biomarkers are still debatable, although markers such as calprotectin might be beneficial in excluding an ongoing process.

Comparison of sample preparation methods, validation of an UPLC-MS/MS procedure for the quantification of cyclosporine A in whole blood sample

Current main methods for therapeutic drug monitoring (TDM) of cyclosporine A (CsA) are immunoassays and liquid chromatography tandem mass spectrometry. The sample pretreatment of these methods is mainly based on extraction of drug which is bound to erythrocytes by divalent heavy metal ions (such as zinc and copper). Although these methods are effective for whole blood drug extraction and measurement, the pollution of heavy metals in sample pretreatment process will have potential negative impact on environment and human health. To overcome the pollution problem, in this study we have developed and validated an UPLC-MS/MS method for CsA determination in whole blood samples using physical pretreatment method. According to the characteristics of erythrocytes, a series of physical pretreatment methods, including sonication, freeze-thaw and osmotic burst, have been developed and evaluated. The results showed that the osmotic burst method was an effective way for drug extraction from erythrocytes. The lower limit of quantitation for CsA was 25 ng/mL, the within-run and between-run coefficient of variations were both less than 11.6 %. The agreement of the UPLC-MS/MS methods using these two sample pretreatment was evaluated by Bland-Altman plot and the two-tailed Student's T-test. Comparison studies show that the effect of erythrocyte fragmentation by osmotic burst is similar to that of zinc sulfate method. The CsA measurement of 103 whole blood samples obtained by these two UPLC-MS/MS assays were no significant difference. These results demonstrate that the sample pretreatment by osmotic burst method is an eco-friendly and precise method for detecting the whole blood CsA concentration and therapeutic drug monitoring of CsA.

Prognostic value of endogenous and exogenous metabolites in liver transplantation

Liver transplantation has been widely accepted as an effective intervention for end-stage liver diseases and early hepatocellular carcinomas. However, a variety of postoperative complications and adverse reactions have baffled medical staff and patients. Currently, transplantation monitoring relies primarily on nonspecific biochemical tests, whereas diagnosis of multiple complications depends on invasive pathological examination. Therefore, a noninvasive monitoring method with high selectivity and specificity is desperately needed. This review summarized the potential of endogenous small-molecule metabolites as biomarkers for assessing graft function, ischemia-reperfusion injury and liver rejection. Exogenous metabolites, mainly those immunosuppressive agents with high intra- and inter-individual variability, were also discussed for transplantation monitoring.

The Role of Metabolomics in Current Concepts of Organ Preservation

In solid organ transplantation (Tx), both survival rates and quality of life have improved dramatically over the last few decades. Each year, the number of people on the wait list continues to increase, widening the gap between organ supply and demand. Therefore, the use of extended criteria donor grafts is growing, despite higher susceptibility to ischemia-reperfusion injury (IRI) and consecutive inferior Tx outcomes. Thus, tools to characterize organ quality prior to Tx are crucial components for Tx success. Innovative techniques of metabolic profiling revealed key pathways and mechanisms involved in IRI occurring during organ preservation. Although large-scale trials are needed, metabolomics appears to be a promising tool to characterize potential biomarkers, for the assessment of graft quality before Tx and evaluate graft-related outcomes. In this comprehensive review, we summarize the currently available literature on the use of metabolomics in solid organ Tx, with a special focus on metabolic profiling during graft preservation to assess organ quality prior to Tx.

Metabonomic Profile of Macrosteatotic Allografts for Orthotopic Liver Transplantation in Patients With Initial Poor Function: Mechanistic Investigation and Prognostic Prediction

BACKGROUND

Our previous study revealled amplified hazardous effects of macrosteatosis (MaS) on graft failure (GF) in recipients with severe liver damage in short post-operative days, with vague mechanism inside.

AIM

We aimed to uncover the molecular mechanism of donor MaS on GF, and construct the predictive model to monitor post-transplant prognosis based on "omics" perspective.

METHODS

Ultra-performance liquid chromatography coupled to mass spectrometry metabolomic analysis was performed in allograft tissues from 82 patients with initial poor function (IPF) from multi-liver transplant (LT) centers. Pathway analysis was performed by on-line toolkit Metaboanalyst (v 3.0). Predictive model was constructed based on combinative metabonomic and clinical data extracted by stepwised cox proportional analysis.

RESULTS

Principle component analysis (PCA) analysis revealled stratification on metabolic feature in organs classified by MaS status. Differential metabolits both associated with MaS and GF were significantly enriched on pathway of glycerophospholipid metabolism (P < 0.05). Phosphatidylcholine (PC) and phosphatidylethanolamine (PE) involved in glycerophospholipid metabolism was significantly decreased in cases with MaS donors and GF (P < 0.05). Better prediction was observed on graft survival by combinative model (area under the curve = 0.91) and confirmed by internal validation.

CONCLUSION

Metabonomic features of allografts can be clearly distinguished by MaS status in patients with IPF. Dysfunction on glycerophospholipid metabolism was culprit to link donor MaS and final GF. Decrement on PC and PE exerted the fatal effects of MaS on organ failure. Metabonomic data might help for monitoring long-term graft survival after LT.

Advances in Detection of Kidney Transplant Injury

Early detection of graft injury after kidney transplantation is key to maintaining long-term good graft function. Graft injury could be due to a multitude of factors including ischaemia reperfusion injury, cell or antibody-mediated rejection, progressive interstitial fibrosis and tubular atrophy, infections and toxicity from the immunosuppressive drugs themselves. The current gold standard for assessing renal graft dysfunction is renal biopsy. However, biopsy is usually late when triggered by a change in serum creatinine and of limited utility in diagnosis of early injury when histological changes are equivocal. Therefore, there is a need for timely, objective and non-invasive diagnostic techniques with good early predictive value to determine graft injury and provide precision in titrating immunosuppression. We review potential novel plasma and urine biomarkers that offer sensitive new strategies for early detection and provide major insights into mechanisms of graft injury. This is a rapidly expanding field, but it is likely that a combination of biomarkers will be required to provide adequate sensitivity and specificity for detecting graft injury.

Combining the advantages of multilevel and orthogonal partial least squares data analysis for longitudinal metabolomics: Application to kidney transplantation

Kidney transplantation is one of the renal replacement options in patients suffering from end-stage renal disease (ESRD). After a transplant, patient follow-up is essential and is mostly based on immunosuppressive drug levels control, creatinine measurement and kidney biopsy in case of a rejection suspicion. The extensive analysis of metabolite levels offered by metabolomics might improve patient monitoring, help in the surveillance of the restoration of a "normal" renal function and possibly also predict rejection. The longitudinal follow-up of those patients with repeated measurements is useful to understand changes and decide whether an intervention is necessary. The time modality, therefore, constitutes a specific dimension in the data structure, requiring dedicated consideration for proper statistical analysis. The handling of specific data structures in metabolomics has received strong interest in recent years. In this work, we demonstrated the recently developed ANOVA multiblock OPLS (AMOPLS) to efficiently analyse longitudinal metabolomic data by considering the intrinsic experimental design. Indeed, AMOPLS combines the advantages of multilevel approaches and OPLS by separating between and within individual variations using dedicated predictive components, while removing most uncorrelated variations in the orthogonal component(s), thus facilitating interpretation. This modelling approach was applied to a clinical cohort study aiming to evaluate the impact of kidney transplantation over time on the plasma metabolic profile of graft patients and donor volunteers. A dataset of 266 plasma metabolites was identified using an LC-MS multiplatform analytical setup. Two separate AMOPLS models were computed: one for the recipient group and one for the donor group. The results highlighted the benefits of transplantation for recipients and the relatively low impacts on blood metabolites of donor volunteers.

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.

The Key Role of Warm and Cold Ischemia in Uterus Transplantation: A Review

Introduction: Uterus transplantation (UTx) is a promising treatment for uterine infertility that has resulted in several births since 2014. Ischemia is a key step in organ transplantation because it may lead to changes jeopardizing graft viability. Method: We performed a systematic review of animal and human studies relating to uterine ischemia. Results: We retained 64 studies published since 2000. There were 35 studies in animals, 24 in humans, and five literature reviews. Modest preliminary results in large animals and humans are limited but encouraging. In small animals, pregnancies have been reported to occur after 24 h of cold ischemia (CI). In ewes, uterine contractions have been detected after 24 h of CI. Furthermore, it has been shown in animals that uterine tolerance to CI and to warm ischemia (WI) can be increased by pharmacological products. In women, mean CI time in studies of births from uteri obtained from live donors was between 2 h 47 min and 6 h 20 min from a deceased donor; with only one birth in this case. Muscle contractions have also been demonstrated in myometrial samples from women, after six or more hours of CI. Conclusion: The uterus seems to be able to tolerate a prolonged period of CI, of at least six hours. Studies of the ischemia tolerance of the uterus and ways to improve it are essential for the development of UTx, particularly for procedures using grafts from deceased donors.

Changes in the metabolic composition of storage solution with prolonged cold ischemia of the uterus

INTRODUCTION

The development of uterine transplantation (UTx) from deceased donors requires knowledge of the tolerance of the uterus to prolonged cold ischemia (CI). This can be evaluated through the use of biological parameters to assess degradation of the organ between its procurement and transplantation. The objective of this study was to analyze changes in the metabolic composition of the storage solution in cases of prolonged CI in uteri from ewes.

METHODS

Eighteen uterine auto-transplantations were performed in ewes. CI time was 1 h (T1) or 24 h (T24). Samples of Celsior® were taken when the explanted uterus was flushed (T0) and at the end of CI. A dual approach to metabolic analyses was followed: targeted biochemical analyses targeting several predefined metabolites and non-targeted metabolomics analyses based on nuclear magnetic resonance (NMR).

RESULTS

Metabolic analyses were performed on 16 explanted uteri. Metabolomic profiles differed significantly between T1 and T24 (p = 0.003). Hypoxia-associated degradation of the organ was demonstrated by the significantly higher lactate levels at T24 than at T1 (p < 0.05), accompanied by cell lysis, and significantly higher levels of creatine kinase activity in T24 than in T1 uteri (p < 0.05). Oxidative stress increased over time, with a significantly higher oxidized glutathione/glutathione ratio for T24 than for T1 uteri (p < 0.05).

CONCLUSION

The metabolic results indicate a significant degradation of the uterus during 24 h of CI. Metabolic analysis of the storage solution could be used as a non-invasive tool for evaluating uterine degradation during CI before transplantation.

Urinary metabolomic profiling for noninvasive diagnosis of acute T cell-mediated rejection after kidney transplantation

To improve early renal allograft function, it is important to develop a noninvasive diagnostic method for acute T cell-mediated rejection (TCMR). This study aims to explore potential noninvasive urinary biomarkers to screen for acute TCMR in kidney transplant recipients (KTRs) using untargeted metabolomic profiling. Urinary metabolites, collected from KTRs with stable graft function (STA) or acute TCMR episodes, were analyzed using liquid chromatography-mass spectrometry (LC-MS). Multivariate statistical analyses were performed to discriminate differences in urinary metabolites between the two groups. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance of potential urinary biomarkers. Statistical analysis revealed the differences in urinary metabolites between the two groups and indicated several statistically significant metabolic features suitable for potential biomarkers. By comparing the retention times and mass fragmentation patterns of the chemicals in metabolite databases, samples, and standards, six of these features were clearly identified. ROC curve analysis showed the best performance of the training set (area under the curve value, 0.926; sensitivity, 90.0%; specificity, 84.6%) using a panel of five potential biomarkers: guanidoacetic acid, methylimidazoleacetic acid, dopamine, 4-guanidinobutyric acid, and L-tryptophan. The diagnostic accuracy of this model was 62.5% for an independent test dataset. LC-MS-based untargeted metabolomic profiling is a promising method to discriminate between acute TCMR and STA groups. Our model, based on a panel of five potential biomarkers, needs to be further validated in larger scale studies.

Gas chromatography-mass spectrometry based metabolomics profile of hippocampus and cerebellum in mice after chronic arsenic exposure

Intake of arsenic (As) via drinking water has been a serious threat to global public health. Though there are numerous reports of As neurotoxicity, its pathogenesis mechanisms remain vague especially its chronic effects on metabolic network. Hippocampus is a renowned area in relation to learning and memory, whilst recently, cerebellum is argued to be involved with process of cognition. Therefore, the study aimed to explore metabolomics alternations in these two areas after chronic As exposure, with the purpose of further illustrating details of As neurotoxicity. Twelve 3-week-old male C57BL/6J mice were divided into two groups, receiving deionized drinking water (control group) or 50 mg/L of sodium arsenite (via drinking water) for 24 weeks. Learning and memory abilities were tested by Morris water maze (MWM) test. Pathological and morphological changes of hippocampus and cerebellum were captured via transmission electron microscopy (TEM). Metabolic alterations were analyzed by gas chromatography-mass spectrometry (GC-MS). MWM test confirmed impairments of learning and memory abilities of mice after chronic As exposure. Metabolomics identifications indicated that tyrosine increased and aspartic acid (Asp) decreased simultaneously in both hippocampus and cerebellum. Intermediates (succinic acid) and indirect involved components of tricarboxylic acid cycle (proline, cysteine, and alanine) were found declined in cerebellum, indicating disordered energy metabolism. Our findings suggest that these metabolite alterations are related to As-induced disorders of amino acids and energy metabolism, which might therefore, play an important part in mechanisms of As neurotoxicity.

Navigating T-Cell Immunometabolism in Transplantation

Recently, a new discipline termed "immunometabolism" has transformed the field of immunology. It encompasses the study of the intrinsic metabolic pathways of different immune subsets and their impact on cellular fate and function. For instance, broadly speaking, proinflammatory cells depend on glycolysis and glutamine oxidation, whereas cells involved in anti-inflammatory response, such as Foxp3+ regulatory T (Treg) cells, use predominantly fatty acid oxidation. However, although a useful paradigm, this actually is a reductionist view, and the engagement of these metabolic pathways is not mutually exclusive between these subsets. Over the past several years, new insights and new methods to better dissect, define, and harness the metabolic properties of immune cells for immunotherapeutic purposes have come to the forefront. In this review, we will discuss the metabolic heterogeneity of different T-cell subsets as well as basic principles of integrative technologies, such as metabolomics, which can be used to better understand the metabolic signatures of immune responses. Given the interest of exploiting this information in the context of transplantation, we will highlight the scope of immunometabolism in unraveling novel mechanisms of immune regulation that can be manipulated to promote Treg cell stability and function while inhibiting T effectors to establish long-term transplantation tolerance.

Metabolomics Study for Identification of Potential Biomarkers of Long-term Survival in Kidney Transplantation Recipients

BACKGROUND

The recent progress and appropriate use of immunosuppressive drugs have considerably improved the short-term survival in kidney transplantation recipients (KTRs). The development of new strategies to improve long-term survival outcome after kidney transplantation is also becoming important. Although current diagnosis of allograft dysfunction relies on serum creatinine concentration and biopsy, they are nonspecific indicators of allograft function. Therefore, noninvasive, sensitive, and specific biomarkers for the prediction of long-term survival are needed. The aim of this study was to discover potential biomarkers for long-term survival in KTRs through the use of liquid chromatography-tandem mass spectrometry.

METHODS

We used the metabolic approach to explore the change of metabolites in the serum of KTRs. Twenty-four KTRs with long-term good survival (LGS) and 10 KTRs with chronic antibody-mediated rejection (CAMR) were included in this study. After quantile normalization with chromatographic data, multivariate statistical analysis was performed. We attempted to analyze metabolic profiling with LGS and CAMR groups.

RESULTS

The orthogonal partial least-squares discriminant analysis score plot showed a separation between 2 groups in the principal component. In the corresponding loading plot, 344 metabolites responsible for the separation observed in the score plot were identified (variable influence on projection ≥1.0). We then selected 54 metabolites to compare mass with charge by searching a web database, and 11 compounds were identified.

CONCLUSIONS

We found metabolites in serum that differ in LGS and CAMR groups. Further studies are needed to figure out potential metabolomic biomarkers to predict long-term survival in KTRs.

Ischemia/reperfusion-associated tubular cells injury in renal transplantation: Can metabolomics inform about mechanisms and help identify new therapeutic targets?

Tubular cells are central targets of ischemia-reperfusion (I/R) injury in kidney transplantation. Inflammation and metabolic disturbances occurring within these cells are deleterious by themselves but also favor secondary events, such as activation of immune response. It is critical to have an in depth understanding of the mechanisms governing tubular cells response to I/R if one wants to define pertinent biomarkers or to elaborate targeted therapeutic interventions. As oxidative damage was shown to be central in the patho-physiological mechanisms, the impact of I/R on proximal tubular cells metabolism has been widely studied, contrary to its effects on expression and activity of membrane transporters of the proximal tubular cells. Yet, temporal modulation of transporters over ischemia and reperfusion periods appears to play a central role, not only in the induction of cells injury but also in graft function recovery. Metabolomics in cell models or diverse biofluids has the potential to provide large pictures of biochemical consequences of I/R. Metabolomic studies conducted in experimental models of I/R or in transplanted patients indeed retrieved metabolites belonging to the pathways known to be particularly affected. Interestingly, they also revealed that metabolic disturbances and transporters activities are in very close mutual interplay. As well as helping to select diagnostic biomarkers, such analyses could also contribute to identify new pharmacological targets and to set up innovative nephroprotective strategies for the future. Even if various therapeutic approaches have been evaluated for a long time to prevent or treat I/R injuries, metabolomics has helped identifying new ones, those related to membrane transporters seeming to be of particular interest. However, considering the very complex and multifactorial effects of I/R in the context of kidney transplantation, all tracks must be followed if one wants to prevent or limit its deleterious consequences.

Urinary Metabolomics for Noninvasive Detection of Antibody-Mediated Rejection in Children After Kidney Transplantation

BACKGROUND

Biomarkers are needed that identify patients with antibody-mediated rejection (AMR). The goal of this study was to evaluate the utility of urinary metabolomics for early noninvasive detection of AMR in pediatric kidney transplant recipients.

METHODS

Urine samples (n = 396) from a prospective, observational cohort of 59 renal transplant patients with surveillance or indication biopsies were assayed for 133 unique metabolites by quantitative mass spectrometry. Samples were classified according to Banff criteria for AMR and partial least squares discriminant analysis was used to identify associated changes in metabolite patterns by creating a composite index based on all 133 metabolites.

RESULTS

Urine samples of patients with (n = 40) and without AMR (n = 278) were analyzed and a classifier for AMR was identified (area under receiver operating characteristic curve = 0.84; 95% confidence interval, 0.77-0.91; P = 0.006). Application of the classifier to "indeterminate" samples (samples that partially fulfilled Banff criteria for AMR; n = 65) yielded an AMR score of 0.19 ± 0.15, intermediate between scores for AMR and No AMR (0.28 ± 0.14 and 0.10 ± 0.13 respectively, P ≤ 0.001). The AMR score was associated with the presence of donor-specific antibodies, biopsy indication, Banff ct, t, ah and cg scores, and retained accuracy when applied to subclinical cases (creatinine, <25% increase from baseline) or had minimal or no transplant glomerulopathy (Banff cg0-1). Exploratory classifiers that segregated samples based on concurrent T cell-mediated rejection (TCMR) identified overlapping metabolite signatures between AMR and TCMR, suggesting similar pathophysiology of tissue injury.

CONCLUSIONS

These preliminary findings identify a urine metabolic classifier for AMR. Independent validation is needed to verify its utility for accurate, noninvasive AMR detection.

1H NMR To Evaluate the Metabolome of Bronchoalveolar Lavage Fluid (BALf) in Bronchiolitis Obliterans Syndrome (BOS): Toward the Development of a New Approach for Biomarker Identification

This report describes the application of NMR spectroscopy to the profiling of metabolites in bronchoalveolar lavage fluid (BALf) of lung transplant recipients without bronchiolitis obliterans syndrome (BOS) (stable, S, n = 10), and with BOS at different degrees of severity (BOS 0p, n = 10; BOS I, n = 10). Through the fine-tuning of a number of parameters concerning both sample preparation/processing and variations of spectra acquisition modes, an efficient and reproducible protocol was designed for the screening of metabolites in a pulmonary fluid that should reflect the status of airway inflammation/injury. Exploiting the combination of mono- and bidimensional NMR experiments, 38 polar metabolites, including amino acids, Krebs cycle intermediates, mono- and disaccharides, nucleotides, and phospholipid precursors, were unequivocally identified. To determine which signature could be correlated with the onset of BOS, the metabolites' content of the above recipients was analyzed by multivariate (PCA and OPLS-DA) statistical methods. PCA analysis (almost) totally differentiated S from BOS I, and this discrimination was significantly improved by the application of OPLS-DA, whose model was characterized by excellent fit and prediction values (R² = 0.99 and Q² = 0.88). The analysis of S vs BOS 0p and of BOS 0p vs BOS I samples showed a clear discrimination of considered cohorts, although with a poorer efficiency compared to those measured for S vs BOS I patients. The data shown in this work assess the suitability of the NMR approach in monitoring different pathological lung conditions.

β-Thalassemia Patients Revealed a Significant Change of Untargeted Metabolites in Comparison to Healthy Individuals

β-Thalassemia is one of the most prevalent forms of congenital blood disorders characterized by reduced hemoglobin levels with severe complications, affecting all dimensions of life. The mechanisms underlying the phenotypic heterogeneity of β-thalassemia are still poorly understood. We aimed to work over metabolite biomarkers to improve mechanistic understanding of phenotypic heterogeneity and hence better management of disorder at different levels. Untargeted serum metabolites were analyzed after protein precipitation and SPE (solid phase extraction) from 100 β-thalassemia patients and 61 healthy controls using GC-MS. 40 metabolites were identified having a significance difference between these two groups at probability of 0.05 and fold change >1.5. Out of these 40 metabolites, 17 were up-regulated while 23 were down-regulated. PCA and PLS-DA model was also created that revealed a fine separation with a sensitivity of 70% and specificity of 100% on external validation of samples. Metabolic pathway analysis revealed alteration in multiple pathways including glycolysis, pyruvate, propanoate, glycerophospholipid, galactose, fatty acid, starch and sucrose metabolism along with fatty acid elongation in mitochondria, glycerolipid, glyoxylate and dicarboxylate metabolism pointing towards the shift of metabolism in β-thalassemia patients in comparison to healthy individuals.

Systems Biology in Kidney Transplantation: The Application of Multi-Omics to a Complex Model

In spite of reduction of rejection rates and improvement in short-term survival post-kidney transplantation, modest progress has occurred in long-term graft attrition over the years. Timely identification of molecular events that precede clinical and histopathological changes might help in early intervention and thereby increase the graft half-life. Evolution of "omics" tools has enabled systemic investigation of the influence of the whole genome, epigenome, transcriptome, proteome and microbiome on transplant function and survival. In this omics era, systemic approaches, in-depth clinical phenotyping and use of strict validation methods are the key for further understanding the complex mechanisms associated with graft function. Systems biology is an interdisciplinary holistic approach that focuses on complex and dynamic interactions within biological systems. The complexity of the human kidney transplant is unlikely to be captured by a reductionist approach. It appears essential to integrate multi-omics data that can elucidate the multidimensional and multilayered regulation of the underlying heterogeneous and complex kidney transplant model. Herein, we discuss studies that focus on genetic biomarkers, emerging technologies and systems biology approaches, which should increase the ability to discover biomarkers, understand mechanisms and stratify patients and responses post-kidney transplantation.