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.

Circulating graft-derived cell-free DNA (dd-cfDNA) is a new marker of cardiac allograft damage that is used for noninvasive rejection diagnostics. We performed dd-cfDNA (%) in heart transplant recipients during the first posttransplant year.

In 87 patients, serial dd-cfDNA determination at predefined time-points was performed in 770 single samples. dd-cfDNA fraction (%) was measured using an established universal droplet digital polymerase chain reaction method, providing same-day turn-around. Rejection was diagnosed according to clinical parameters and biopsies.

Median dd-cfDNA (%) was high (5.36%) immediately after reperfusion and decreased to a median (interquartile range) of 0.10% (0.05%-0.24%) in clinically stable patients by postoperative day 10. Compared to dd-cfDNA (%) samples in clinically stable patients, values were higher (P < 0.001) in biopsy-proven rejection ISHLT 1R (0.42% [0.15%-0.53%]) and 2R rejection (0.84% [0.39%-0.97%]). Moreover, dd-cfDNA (%) was already significantly increased 9-30 days before biopsy-proven rejection (0.36% [0.20%-0.61%]). An as yet unknown finding was a slightly, but significantly (P < 0.0001) higher dd-cfDNA (%) value in samples of stable patients with pericardial effusions (PEs) (n = 94; 0.18% [0.07%-0.30%]) compared to samples of non-PE patients (n = 132; 0.07% [0.04%-0.17%]). Using a cutoff of 0.35%, sensitivity and specificity of dd-cfDNA for cardiac rejection were 0.76 and 0.83 (area under the curve [AUC] ROC-curve: 0.81 [95% confidence interval, 0.73-0.89]). Omitting PE samples from the control group yielded an AUC of 0.86 [95% confidence interval, 0.76-0.95]. Samples drawn <12 hours after endomyocardial biopsy showed high (0.40% [0.15%-1.21%]) dd-cfDNA values, also in ISHLT0R (0.36% [0.10%-0.60%]).

dd-cfDNA plasma values were significantly associated with cardiac rejection. However, PE or improper sampling (eg, shortly after biopsy) should be considered as confounders for rejection diagnoses using dd-cfDNA.

Rejection is one of the key factors that determine the long-term allograft function and survival in renal transplant patients. Reliable and timely diagnosis is important to treat rejection as early as possible. Allograft biopsies are not suitable for continuous monitoring of rejection. Thus, there is an unmet need for non-invasive methods to diagnose acute and chronic rejection. Proteomics in urine and blood samples has been explored for this purpose in 29 studies conducted since 2003. This review describes the different proteomic approaches and summarizes the results from the studies that examined proteomics for the rejection diagnoses. The potential limitations and open questions in establishing proteomic markers for rejection are discussed, including ongoing trials and future challenges to this topic.

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.

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.

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.

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).

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.

In this study, we explored a time course of peripheral whole blood transcriptomes from kidney transplantation patients who either experienced an acute rejection episode or did not in order to better delineate the immunological and biological processes measureable in blood leukocytes that are associated with acute renal allograft rejection. Using microarrays, we generated gene expression data from 24 acute rejectors and 24 nonrejectors. We filtered the data to obtain the most unambiguous and robustly expressing probe sets and selected a subset of patients with the clearest phenotype. We then performed a data-driven exploratory analysis using data reduction and differential gene expression analysis tools in order to reveal gene expression signatures associated with acute allograft rejection. Using a template-matching algorithm, we then expanded our analysis to include time course data, identifying genes whose expression is modulated leading up to acute rejection. We have identified molecular phenotypes associated with acute renal allograft rejection, including a significantly upregulated signature of neutrophil activation and accumulation following transplant surgery that is common to both acute rejectors and nonrejectors. Our analysis shows that this expression signature appears to stabilize over time in nonrejectors but persists in patients who go on to reject the transplanted organ. In addition, we describe an expression signature characteristic of lymphocyte activity and proliferation. This lymphocyte signature is significantly downregulated in both acute rejectors and nonrejectors following surgery; however, patients who go on to reject the organ show a persistent downregulation of this signature relative to the neutrophil signature.

The improvement of long-term transplant organ and patient survival remains a critical challenge following kidney transplantation. Proteomics and biochemical profiling (metabolomics) may allow for the detection of early changes in cell signal transduction regulation and biochemistry with high sensitivity and specificity. Hence, these analytical strategies hold the promise to detect and monitor disease processes and drug effects before histopathological and pathophysiological changes occur. In addition, they will identify enriched populations and enable individualized drug therapy. However, proteomics and metabolomics have not yet lived up to such high expectations. Renal transplant patients are highly complex, making it difficult to establish cause-effect relationships between surrogate markers and disease processes. Appropriate study design, adequate sample handling, storage and processing, quality and reproducibility of bioanalytical multi-analyte assays, data analysis and interpretation, mechanistic verification, and clinical qualification (=establishment of sensitivity and specificity in adequately powered prospective clinical trials) are important factors for the success of molecular marker discovery and development in renal transplantation. However, a newly developed and appropriately qualified molecular marker can only be successful if it is realistic that it can be implemented in a clinical setting. The development of combinatorial markers with supporting software tools is an attractive goal.

Surveillance endoscopy with biopsy is the standard method to monitor intestinal transplant recipients but it is invasive, costly and prone to sampling error. Early noninvasive biomarkers of intestinal rejection are needed. In this pilot study we applied metabolomics to characterize the metabolomic profile of intestinal allograft rejection. Fifty-six samples of ileostomy fluid or stool from 11 rejection and 45 nonrejection episodes were analyzed by ultraperformance liquid chromatography in conjunction with Quadrupole time-of-flight mass spectrometry (UPLC-QTOFMS). The data were acquired in duplicate for each sample in positive ionization mode and preprocessed using XCMS (Scripps) followed by multivariate data analysis. We detected a total of 2541 metabolites in the positive ionization mode (mass 50-850 Daltons). A significant interclass separation was found between rejection and nonrejection. The proinflammatory mediator leukotriene E4 was the metabolite with the highest fold change in the rejection group compared to nonrejection. Water-soluble vitamins B2, B5, B6, and taurocholate were also detected with high fold change in rejection. The metabolomic profile of rejection was more heterogeneous than nonrejection. Although larger studies are needed, metabolomics appears to be a promising tool to characterize the pathophysiologic mechanisms involved in intestinal allograft rejection and potentially to identify noninvasive biomarkers.

Many patients with intestinal failure require intestinal transplantation (ITx) to survive. Acute cellular rejection poses a challenge in ITx because its biologic components are incompletely understood. New methodologies for its integrative and longitudinal analysis are needed.

In this study, we characterized episodes of acute cellular rejection in ITx recipients using a noninvasive proteomic analysis. Ostomy effluent was obtained from all patients undergoing ITx at University of California, Los Angeles from July 2008 to September 2009 during surveillance endoscopies in the first 8 weeks post-ITx. Effluent was analyzed using 17-plex Luminex technology and matrix-assisted laser desorption/ionization proteomics.

Of 56 ostomy effluent samples from 17 ITx recipients, 14% developed biopsy-proven rejection at a median of 25 days post-ITx. Six had mild rejection, two were indeterminate for rejection, and no graft loss was seen in the first 3 months posttransplantation. Effluent levels of five innate immune cytokines were elevated in the posttransplantation phase: granulocyte colony-stimulating factor, interleukin-8, tissue necrosis factor-α, interleukin-1β, and interferon-γ. Proteomic analysis revealed 17 protein features differentially seen in rejection, two identified as human neutrophil peptide 1 and 2. This was confirmed by the presence of human neutrophil peptide-positive lamina propria neutrophils in biopsy tissue samples.

Proteomic and cytokine analysis of ostomy effluents suggests an early and unappreciated role of innate immune activation during rejection.

There is a critical need for biomarkers for early diagnosis, treatment response, and surrogate end point and outcome prediction in organ transplantation, leading to a tailored and individualized treatment. Genomic and proteomic platforms have provided multiple promising new biomarkers during the last few years. However, there is still no routine application of any of these markers in clinical transplantation. This article will discuss the existing gap between biomarker discovery and clinical application in the kidney transplant setting. Approaches to implementing biomarker monitoring into clinical practice will also be discussed.

The critical importance of donor organ quality, i.e., number of surviving nephrons, ability to withstand injury, and capacity for repair in determining short- and long-term outcomes is becoming increasingly clear. This review provides an overview of studies to assess donor kidney quality and subsequent transplant outcomes based on clinical pathology and transcriptome-based variables available at time of transplantation. Prediction scores using clinical variables function when applied to large data sets but perform poorly for the individual patient. Histopathology findings in pre-implantation or post-reperfusion biopsies help to assess structural integrity of the donor kidney, provide information on pre-existing donor disease, and can serve as a baseline for tracking changes over time. However, more validated approaches of analysis and prospective studies are needed to reduce the number of discarded organs, improve allocation, and allow prediction of outcomes. Molecular profiling detects changes not seen by morphology or captured by clinical markers. In particular, molecular profiles provide a quantitative measurement of inflammatory burden or immune activation and reflect coordinated changes in pathways associated with injury and repair. However, description of transcriptome patterns is not an end in itself. The identification of predictive gene sets and the application to an individualized patient management needs the integration of clinical and pathology-based variables, as well as more objective reference markers of transplant function, post-transplant events, and long-term outcomes.

This review covers the contribution of genomics to the field of renal transplantation over the last two years. The tangible advances in genomics have mainly been in the use of expression arrays to inform our understanding of processes involved in the complex immune responses that are a feature of transplantation. There is qualitative and quantitative data on transcription elements indicative of acute and chronic rejection, short and medium term outcome and tolerance. The promise is that translation of this information will allow the development of clinical biomarkers applicable to improvements in patient care.

Biomarkers that reflect immune response recovery and predict clinical events during withdrawal or minimization of immunosuppressive therapy have not been evaluated. This study aimed to evaluate whether immune response recovers after withdrawal of long-term immunosuppressive treatment in stable liver transplant patients and to determine whether specific biomarkers reflect immune response reactivity and predict rejection. Pharmacokinetic-pharmacodynamic profiles were determined in 24 patients and 80 healthy donors before immunosuppressive treatment reduction began, at 50%, and at complete withdrawal. In patients who rejected, effector-T-cell response mediated by soluble IFN-γ, %CD4(+)IFN-γ and %CD8(+)IL-2/IFN-γ were significantly increased, while TGF-β1 production and the TGF-β1/IFN-γ ratio were significantly decreased. In patients with rejection, soluble IFN-γ and %CD8(+)IL-2 were significantly higher before immunosuppressive treatment was reduced. Further studies are required, but this battery of biomarkers performed in whole blood could be a useful tool to monitor immunosuppressive treatment minimization or withdrawal protocols and identify patients at increased risk of rejection.

To improve the outcome of orthotopic liver transplantation (OLT), knowledge of early molecular events occurring upon ischemia/reperfusion is essential. Powerful approaches for profiling metabolic changes in tissues and biofluids are now available. Our objective was to investigate the applicability of two technologies to a small but well-defined cohort of patients undergoing OLT: consecutive liver biopsies by Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) and microdialysates of extracellular fluid by coulometric electrochemical array detection (CEAD). FT-ICR MS detected reproducibly more than 4,000 peaks, revealing hundreds of significant metabolic differences between pre- and postreperfusion grafts. These included increased urea production, bile acid synthesis and clearance of preservation solution upon reperfusion, indicating a rapid resumption of biochemical function within the graft. FT-ICR MS also identified successfully the only graft obtained by donation-after-cardiac-death as a "metabolic outlier." CEAD time-profile analysis showed that there was considerable change in redox-active metabolites (up to 18 h postreperfusion), followed by their stabilization. Collectively these results verify the applicability of FT-ICR MS and CEAD for characterizing multiple metabolic pathways during OLT. The success of this proof-of-principle application of these technologies to a clinical setting, considering the potential metabolic heterogeneity across only eight donor livers, is encouraging.

Understanding heterogeneity in adaptive immune responses is essential to dissect pathways of memory B and T cell differentiation and to define correlates of protective immunity. Traditionally, immunologists have deconvoluted this heterogeneity with flow cytometry--with combinations of markers to define signatures that represent specific lineages, differentiation states, and functions. Genome-scale technologies have become widely available and provide the ability to define expression signatures--sets of genes--that represent discrete biological properties of cell populations. Because genomic signatures can serve as surrogates of a phenotype, function, or cell state, they can integrate phenotypic information between experiments, cell types, and species. Here, we discuss how integration of well-defined expression signatures across experimental conditions together with functional analysis of their component genes could provide new opportunities to dissect the complexity of the adaptive immune response and map the immune response to vaccines and pathogens.