Early prediction of renal graft function: Analysis of a multi-center, multi-level data set.

PURPOSE OF THE STUDY: Long-term graft survival rates after renal transplantation are still poor. We aimed to build an early predictor of an established long-term outcomes marker, the estimated glomerular filtration rate (eGFR) one year post-transplant (eGFR-1y). MATERIALS AND METHODS: A large cohort of 376 patients was characterized for a multi-level bio-marker panel including gene expression, cytokines, metabolomics and antibody reactivity profiles. Almost one thousand samples from the pre-transplant and early post-transplant period were analysed and employed for machine learning-assisted prediction. RESULTS: Pre-transplant data led to a prediction achieving a Pearson's correlation coefficient of r=0.38 between measured and predicted eGFR-1y. Two weeks post-transplant, the correlation was improved to r=0.63, and at the third month, to r=0.76. eGFR values were stable throughout the first post-transplant year. Several characteristics were predictive for eGFR, including age of donor and recipient, body mass index, HLA mismatch, cytomegalovirus mismatch and valganciclovir prophylaxis. Additionally, a subset of 19 nuclear magnetic resonance bins of the urine metabolome data was shown to have potential applications in non-invasive eGFR monitoring. Importantly, we identified the expression of the genes TMEM176B and HMMR as potential prognostic markers for changes in the eGFR after the second post-transplantation week. CONCLUSIONS: Our multi-center, multi-level data set represents a milestone in the efforts to predict transplant outcome. While an acceptable predictive capacity was achieved, we are still far from predicting changes in the eGFR precisely. Additional studies employing further marker panels are needed to establish predictors of eGFR-1y for clinical application; herein, gene expression markers seem to hold the most promise.

Risk factors for Epstein-Barr virus reactivation after renal transplantation: Results of a large, multi-centre study.

Epstein-Barr virus (EBV) reactivation is a very common and potentially lethal complication of renal transplantation. However, its risk factors and effects on transplant outcome are not well known. Here, we have analysed a large, multi-centre cohort (N = 512) in which 18.4% of the patients experienced EBV reactivation during the first post-transplant year. The patients were characterized pre-transplant and two weeks post-transplant by a multi-level biomarker panel. EBV reactivation was episodic for most patients, only 12 patients showed prolonged viraemia for over four months. Pre-transplant EBV shedding and male sex were associated with significantly increased incidence of post-transplant EBV reactivation. Importantly, we also identified a significant association of post-transplant EBV with acute rejection and with decreased haemoglobin levels. No further severe complications associated with EBV, either episodic or chronic, could be detected. Our data suggest that despite relatively frequent EBV reactivation, it had no association with serious complications during the first post-transplantation year. EBV shedding prior to transplantation could be employed as biomarkers for personalized immunosuppressive therapy. In summary, our results support the employed immunosuppressive regimes as relatively safe with regard to EBV. However, long-term studies are paramount to support these conclusions.

Sex-Associated Differences in Cytomegalovirus Prevention: Prophylactic Strategy is Potentially Associated With a Strong Kidney Function Impairment in Female Renal Transplant Patients.

Post-transplantation cytomegalovirus (CMV) syndrome can be prevented using the antiviral drug (val)ganciclovir. (Val)ganciclovir is typically administered following a prophylactic or a pre-emptive strategy. The prophylactic strategy entails early universal administration, the pre-emptive strategy, early treatment in case of infection. However, it is not clear which strategy is superior with respect to transplantation outcome; sex-specific effects of these prevention strategies are not known. We have retrospectively analyzed 540 patients from the multi-centre Harmony study along eight pre-defined visits: 308 were treated according to a prophylactic, 232 according to a pre-emptive strategy. As expected, we observed an association of prophylactic strategy with lower incidence of CMV syndrome, delayed onset and lower viral loads compared to the pre-emptive strategy. However, in female patients, the prophylactic strategy was associated with a strong impairment of glomerular filtration rate one year post-transplant (difference: -11.8 ± 4.3 ml min-1·1.73 m-2, p = 0.006). Additionally, we observed a tendency of higher incidence of acute rejection and severe BK virus reactivation in the prophylactic strategy group. While the prophylactic strategy was more effective for preventing CMV syndrome, our results suggest for the first time that the prophylactic strategy might lead to inferior transplantation outcomes in female patients, providing evidence for a strong association with sex. Further randomized controlled studies are necessary to confirm this potential negative effect.

A novel approach reveals that HLA class 1 single antigen bead-signatures provide a means of high-accuracy pre-transplant risk assessment of acute cellular rejection in renal transplantation.

BACKGROUND: Acute cellular rejection (ACR) is associated with complications after kidney transplantation, such as graft dysfunction and graft loss. Early risk assessment is therefore critical for the improvement of transplantation outcomes. In this work, we retrospectively analyzed a pre-transplant HLA antigen bead assay data set that was acquired by the e:KID consortium as part of a systems medicine approach. RESULTS: The data set included single antigen bead (SAB) reactivity profiles of 52 low-risk graft recipients (negative complement dependent cytotoxicity crossmatch, PRA < 30%) who showed detectable pre-transplant anti-HLA 1 antibodies. To assess whether the reactivity profiles provide a means for ACR risk assessment, we established a novel approach which differs from standard approaches in two aspects: the use of quantitative continuous data and the use of a multiparameter classification method. Remarkably, it achieved significant prediction of the 38 graft recipients who experienced ACR with a balanced accuracy of 82.7% (sensitivity = 76.5%, specificity = 88.9%). CONCLUSIONS: The resultant classifier achieved one of the highest prediction accuracies in the literature for pre-transplant risk assessment of ACR. Importantly, it can facilitate risk assessment in non-sensitized patients who lack donor-specific antibodies. As the classifier is based on continuous data and includes weak signals, our results emphasize that not only strong but also weak binding interactions of antibodies and HLA 1 antigens contain predictive information. TRIAL REGISTRATION: ClinicalTrials.gov NCT00724022 . Retrospectively registered July 2008.

BKV, CMV, and EBV Interactions and their Effect on Graft Function One Year Post-Renal Transplantation: Results from a Large Multi-Centre Study.

BACKGROUND: BK virus (BKV), Cytomegalovirus (CMV) and Epstein-Barr virus (EBV) reactivations are common after kidney transplantation and associated with increased morbidity and mortality. Although CMV might be a risk factor for BKV and EBV, the effects of combined reactivations remain unknown. The purpose of this study is to ascertain the interaction and effects on graft function of these reactivations. METHODS: 3715 serum samples from 540 kidney transplant recipients were analysed for viral load by qPCR. Measurements were performed throughout eight visits during the first post-transplantation year. Clinical characteristics, including graft function (GFR), were collected in parallel. FINDINGS: BKV had the highest prevalence and viral loads. BKV or CMV viral loads over 10,000 copies·mL-1 led to significant GFR impairment. 57 patients had BKV-CMV combined reactivation, both reactivations were significantly associated (p = 0.005). Combined reactivation was associated with a significant GFR reduction one year post-transplantation of 11.7 mL·min-1·1.73 m-2 (p = 0.02) at relatively low thresholds (BKV > 1000 and CMV > 4000 copies·mL-1). For EBV, a significant association was found with CMV reactivation (p = 0.02), but no GFR reduction was found. Long cold ischaemia times were a further risk factor for high CMV load. INTERPRETATION: BKV-CMV combined reactivation has a deep impact on renal function one year post-transplantation and therefore most likely on long-term allograft function, even at low viral loads. Frequent viral monitoring and subsequent interventions for low BKV and/or CMV viraemia levels and/or long cold ischaemia time are recommended. FUND: Investigator Initiated Trial; financial support by German Federal Ministry of Education and Research (BMBF).

Differential T cell response against BK virus regulatory and structural antigens: A viral dynamics modelling approach.

BK virus (BKV) associated nephropathy affects 1-10% of kidney transplant recipients, leading to graft failure in about 50% of cases. Immune responses against different BKV antigens have been shown to have a prognostic value for disease development. Data currently suggest that the structural antigens and regulatory antigens of BKV might each trigger a different mode of action of the immune response. To study the influence of different modes of action of the cellular immune response on BKV clearance dynamics, we have analysed the kinetics of BKV plasma load and anti-BKV T cell response (Elispot) in six patients with BKV associated nephropathy using ODE modelling. The results show that only a small number of hypotheses on the mode of action are compatible with the empirical data. The hypothesis with the highest empirical support is that structural antigens trigger blocking of virus production from infected cells, whereas regulatory antigens trigger an acceleration of death of infected cells. These differential modes of action could be important for our understanding of BKV resolution, as according to the hypothesis, only regulatory antigens would trigger a fast and continuous clearance of the viral load. Other hypotheses showed a lower degree of empirical support, but could potentially explain the clearing mechanisms of individual patients. Our results highlight the heterogeneity of the dynamics, including the delay between immune response against structural versus regulatory antigens, and its relevance for BKV clearance. Our modelling approach is the first that studies the process of BKV clearance by bringing together viral and immune kinetics and can provide a framework for personalised hypotheses generation on the interrelations between cellular immunity and viral dynamics.

BioMiner: Paving the Way for Personalized Medicine.

Personalized medicine is promising a revolution for medicine and human biology in the 21st century. The scientific foundation for this revolution is accomplished by analyzing biological high-throughput data sets from genomics, transcriptomics, proteomics, and metabolomics. Currently, access to these data has been limited to either rather simple Web-based tools, which do not grant much insight or analysis by trained specialists, without firsthand involvement of the physician. Here, we present the novel Web-based tool "BioMiner," which was developed within the scope of an international and interdisciplinary project (SYSTHER) and gives access to a variety of high-throughput data sets. It provides the user with convenient tools to analyze complex cross-omics data sets and grants enhanced visualization abilities. BioMiner incorporates transcriptomic and cross-omics high-throughput data sets, with a focus on cancer. A public instance of BioMiner along with the database is available at http://systherDB.microdiscovery.de/, login and password: "systher"; a tutorial detailing the usage of BioMiner can be found in the Supplementary File.

Quantifying the length and variance of the eukaryotic cell cycle phases by a stochastic model and dual nucleoside pulse labelling.

A fundamental property of cell populations is their growth rate as well as the time needed for cell division and its variance. The eukaryotic cell cycle progresses in an ordered sequence through the phases G1, S, G2, and M, and is regulated by environmental cues and by intracellular checkpoints. Reflecting this regulatory complexity, the length of each phase varies considerably in different kinds of cells but also among genetically and morphologically indistinguishable cells. This article addresses the question of how to describe and quantify the mean and variance of the cell cycle phase lengths. A phase-resolved cell cycle model is introduced assuming that phase completion times are distributed as delayed exponential functions, capturing the observations that each realization of a cycle phase is variable in length and requires a minimal time. In this model, the total cell cycle length is distributed as a delayed hypoexponential function that closely reproduces empirical distributions. Analytic solutions are derived for the proportions of cells in each cycle phase in a population growing under balanced growth and under specific non-stationary conditions. These solutions are then adapted to describe conventional cell cycle kinetic assays based on pulse labelling with nucleoside analogs. The model fits well to data obtained with two distinct proliferating cell lines labelled with a single bromodeoxiuridine pulse. However, whereas mean lengths are precisely estimated for all phases, the respective variances remain uncertain. To overcome this limitation, a redesigned experimental protocol is derived and validated in silico. The novelty is the timing of two consecutive pulses with distinct nucleosides that enables accurate and precise estimation of both the mean and the variance of the length of all phases. The proposed methodology to quantify the phase length distributions gives results potentially equivalent to those obtained with modern phase-specific biosensor-based fluorescent imaging.

How oligoclonal are germinal centers? A new method for estimating clonal diversity from immunohistological sections.

BACKGROUND: The germinal center (GC) reaction leads to antibody affinity maturation and generation of memory B cells, but its underlying mechanisms are poorly understood. To assemble this puzzle, several key pieces of information are needed, one in particular being the number of participating B cell clones. Since this clonal diversity cannot be observed directly, earlier studies resorted to interpreting two types of available experimental data: Immunohistology of GCs containing two phenotypically distinct B-cell populations, and antibody gene sequences of small B-cell samples from GCs. Based on a simple model, investigators concluded that a typical GC was seeded by 2-8 B cells, endorsing the current notion that GCs are oligoclonal from the onset. RESULTS: A re-evaluation of these data showed that the used simple model is not statistically consistent with the original data. From an analysis of the experimental system, we propose a new model for estimating GC clonal diversity, including the initially neglected sampling and measurement errors, and making more general assumptions. Consistency analysis with the new model yielded an estimation of sampling and measurement errors in the experimental data of 10-11% for one B-cell population and 62-64% for the other population, and an average number of 19-23 seeder B cells. An independent analysis of antibody gene sequences of small B-cell samples from GCs, using an adapted Yule estimator of diversity, yielded a minimum estimation of 20-30 GC founder B cells, confirming the previous results. CONCLUSIONS: Our new experimental-based model provides a highly improved method to estimate the clonal diversity of GCs from immunohistochemistry data of chimeric animals. Calculations based on this model, and validated by an independent approach, indicate that GCs most likely contain broadly varying numbers of different B cell clones, averaging 5- to 10-fold more clones than previously estimated. These findings, in line with recent results showing that GC sizes and life times are also subject to high variability, dramatically change the picture of GC dynamics.

A minimal model of peptide binding predicts ensemble properties of serum antibodies.

BACKGROUND: The importance of peptide microarrays as a tool for serological diagnostics has strongly increased over the last decade. However, interpretation of the binding signals is still hampered by our limited understanding of the technology. This is in particular true for arrays probed with antibody mixtures of unknown complexity, such as sera. To gain insight into how signals depend on peptide amino acid sequences, we probed random-sequence peptide microarrays with sera of healthy and infected mice. We analyzed the resulting antibody binding profiles with regression methods and formulated a minimal model to explain our findings. RESULTS: Multivariate regression analysis relating peptide sequence to measured signals led to the definition of amino acid-associated weights. Although these weights do not contain information on amino acid position, they predict up to 40-50% of the binding profiles' variation. Mathematical modeling shows that this position-independent ansatz is only adequate for highly diverse random antibody mixtures which are not dominated by a few antibodies. Experimental results suggest that sera from healthy individuals correspond to that case, in contrast to sera of infected ones. CONCLUSIONS: Our results indicate that position-independent amino acid-associated weights predict linear epitope binding of antibody mixtures only if the mixture is random, highly diverse, and contains no dominant antibodies. The discovered ensemble property is an important step towards an understanding of peptide-array serum-antibody binding profiles. It has implications for both serological diagnostics and B cell epitope mapping.

A "crossomics" study analysing variability of different components in peripheral blood of healthy caucasoid individuals.

BACKGROUND: Different immunotherapy approaches for the treatment of cancer and autoimmune diseases are being developed and tested in clinical studies worldwide. Their resulting complex experimental data should be properly evaluated, therefore reliable normal healthy control baseline values are indispensable. METHODOLOGY/PRINCIPAL FINDINGS: To assess intra- and inter-individual variability of various biomarkers, peripheral blood of 16 age and gender equilibrated healthy volunteers was sampled on 3 different days within a period of one month. Complex "crossomics" analyses of plasma metabolite profiles, antibody concentrations and lymphocyte subset counts as well as whole genome expression profiling in CD4+T and NK cells were performed. Some of the observed age, gender and BMI dependences are in agreement with the existing knowledge, like negative correlation between sex hormone levels and age or BMI related increase in lipids and soluble sugars. Thus we can assume that the distribution of all 39.743 analysed markers is well representing the normal Caucasoid population. All lymphocyte subsets, 20% of metabolites and less than 10% of genes, were identified as highly variable in our dataset. CONCLUSIONS/SIGNIFICANCE: Our study shows that the intra-individual variability was at least two-fold lower compared to the inter-individual one at all investigated levels, showing the importance of personalised medicine approach from yet another perspective.

Is there a typical germinal center? A large-scale immunohistological study on the cellular composition of germinal centers during the hapten-carrier-driven primary immune response in mice.

Germinal centers (GCs) are complex, multicell-type, transient structures that form in secondary lymphatic tissues in response to T cell-dependent stimulation. This process is crucial to the adaptive immune response because it is the source of affinity maturation and long-lived B cell memory. Our previous studies showed that the growth of murine splenic GCs is nonsynchronized, involving broad-volume distributions of individual GCs at any time. This raises the question whether such a thing as a typical GC exists. To address this matter, we acquired large-scale confocal data on GCs throughout the course of the 2-phenyl-5-oxazolone chicken serum albumin-driven primary immune response in BALB/c mice. Semiautomated image analysis of 3457 GC sections revealed that, although there is no typical GC in terms of size, GCs have a typical cellular composition in that the cell ratios of resident T cells, macrophages, proliferating cells, and apoptotic nuclei are maintained during the established phase of the response. Moreover, our data provide evidence that the dark zone (DZ) and light zone (LZ) compartments of GCs are about the same size and led us to estimate that the minimal cell loss rate in GCs is 3% per hour. Furthermore, we found that the population of GC macrophages is larger and more heterogeneous than previously thought, and that despite enrichment of T cells in the LZ, the DZ of murine splenic GCs is not poor in T cells. DZ and LZ differ in the T cell-to-macrophage ratio rather than in the density of T cells.

Affinity maturation of B cells involves not only a few but a whole spectrum of relevant mutations.

Affinity maturation of B lymphocytes within germinal centers involves both diversification of their B-cell receptors (BCRs) by somatic hypermutation (SHM) and a crucial receptor-mediated selection step. However, in contrast to recent advances in revealing the molecular mechanism of SHM, the fundamentals of the selection process are still poorly understood, i.e. it is often not clear how and how many mutations contribute to improving a BCR during the response against a given antigen. A general drawback in assessing the mutations relevant to the selection process is the difficult task of rating the relative contributions of selection and intrinsic biases to the experimentally observed mutation patterns of BCRs. The approach proposed here is premised on statistical comparison of the frequency distributions of nucleotide substitutions as observed in datasets of hypermutated BCRs against their frequency distribution expected under the null hypothesis of no selection. Thereby, we show that the spectrum of mutations relevant to maturation of canonical anti-(4-hydroxy-3-nitrophenyl)acetyl BCRs is much broader than previously acknowledged, going beyond the scope of single key mutations. Moreover, our results suggest that maturation not only involves selection by means of affinity but likewise expression and stabilization of BCRs.

Broad volume distributions indicate nonsynchronized growth and suggest sudden collapses of germinal center B cell populations.

Immunization with a T cell-dependent Ag leads to the formation of several hundred germinal centers (GCs) within secondary lymphoid organs, a key process in the maturation of the immune response. Although prevailing perceptions about affinity maturation intuitively assume simultaneous seeding, growth, and decay of GCs, our previous mathematical simulations led us to hypothesize that their growth might be nonsynchronized. To investigate this, we performed computer-aided three-dimensional reconstructions of splenic GCs to measure size distributions at consecutive time points following immunization of BALB/c mice with a conjugate of 2-phenyl-oxazolone and chicken serum albumin. Our analysis reveals a broad volume distribution of GCs, indicating that individual GCs certainly do not obey the average time course of the GC volumes and that their growth is nonsynchronized. To address the cause and implications of this behavior, we compared our empirical data with simulations of a stochastic mathematical model that allows for frequent and sudden collapses of GCs. Strikingly, this model succeeds in reproducing the empirical average kinetics of GC volumes as well as the underlying broad size distributions. Possible causes of GC B cell population collapses are discussed in the context of the affinity-maturation process.

Epitope mapping using randomly generated peptide libraries.

Characterizing the immune response towards a pathogen is of high interest for vaccine development and diagnosis. However, the characterization of disease-related antigen-antibody interactions is of enormous complexity. Here, we present a method comprising binding studies of serum antibody pools to synthetic random peptide libraries, and data analysis of the resulting binding patterns. The analysis can be applied to classify and predict different groups of individuals and to detect the peptides which best discriminate the investigated groups. As an example, the analysis of antibody repertoire binding patterns of different mice strains and of mice infected with helminth parasites is shown. Due to the design of the library and the sophisticated analysis, the method is able to classify and predict the different mice strains and the infection with very high accuracy and with a very small number of peptides, illustrating the potential of random library screenings in determining molecular markers for diagnosis.

Recirculation of germinal center B cells: a multilevel selection strategy for antibody maturation.

Optimization of antibody affinity is a hallmark of the humoral immune response. It takes place in hundreds of transient microstructures called germinal centers (GCs). Their function and time-dependent behavior are subjects of active investigation. According to a generally accepted notion, their individual kinetics follows the average kinetics of all GCs present in the observed lymphatic tissue. In this review, we challenge this view and point out, with the help of mathematical simulations, that inferring the kinetics of individual GCs from cross-sectional evaluation of GC kinetics is virtually impossible. Thus, the time course of individual GCs is open to conjecture. For instance, one possible interpretation is that GCs exist for a time span considerably shorter than that of the observed average kinetics. We explore the implications of different temporal organizations of GCs in the light of the hypothesis that GC B-cell emigrants recolonize GC niches. This assumption leads to a view where GCs work in parallel but are linked by recirculation of B-cell emigrants. In this view, interleaved global and local competition provide for an implementation of multiple levels of B-cell selection in affinity maturation. The concepts of iteration, all-or-none behavior, and phasic mutation schedule are discussed in the light of this hypothesis.

Affinity profiling using the peptide microarray technology: a case study.

Little about the reliability of measurements obtained using synthetic peptide microarrays is known. We report results from a study on the quantitative reliability of microarrays manufactured by robot-supported immobilization of presynthesized peptides for different microarray platforms. Technological precision is assessed for inter- and intra-device readout comparisons. Correlations between measured signals and known dissociation constants using a phenomenological model derived from the mass action law are discussed. Special emphasis is on discussing the pitfalls of high-throughput affinity measurements. We show that the quantitative determination of binding affinities is prone to be biased toward a mean affinity of around 10(-7)M, while the classification of peptides into either "binders" or "nonbinders" provides very high prediction accuracy. The experimental requirements needed to obtain reliable binding affinity predictions are discussed.