Developing molecular classifiers to detect environmental stressors, smolt stages and morbidity in coho salmon, Oncorhynchus kisutch.

Aquatic species are increasingly confronted with environmental stressors because of climate change. Although molecular technologies have advanced our understanding of how organisms respond to stressors in laboratory settings, the ability to detect physiological responses to specific stressors under complex field conditions remains underdeveloped. This research applied multi-stressor challenge trials on coho salmon, employing the "Salmon Fit-Chips" genomic tool and a random forest-based classification model to develop classifiers predictive for chronic thermal and hypoxic stress, as well as salinity acclimation, smolt stage and morbidity status. The study also examined how smolts and de-smolts (smolts not having entered SW during the smolt window) responded transcriptionally to exposure to saltwater. Using RF classifiers optimized with 4 to 12 biomarkers, we identified transcriptional signatures that accurately predicted the presence of each stressor and physiological state, achieving prediction accuracy rates between 86.8 % and 100 %, regardless of other background stressors present. Stressor recovery time was established by placing fish back into non-stressor conditions after stress exposure, providing important context to stressor detections in field applications. Recovery from thermal and hypoxic stress requires about 3 and 2 days, respectively, with >3 days needed for re-acclimation to freshwater for seawater acclimated fish. The study also found non-additive (synergistic) effects of multiple stressors on mortality risk. Importantly, osmotic stress associated with de-smolts was the most important predictor of mortality. In saltwater, de-smolts exposed to salinity, high temperature, and hypoxia experienced a 9-fold increase in mortality compared to those only exposed to saltwater, suggesting a synergistic response to multiple stressors. These findings suggest that delays in hatchery releases to support release of larger fish need to be carefully scrutinized to ensure fish are not being released as de-smolts, which are highly susceptible to additional climate-induced stressors like rising temperatures and reduced dissolved oxygen levels in the marine environment.

NephroCAGE-German-Canadian Consortium on AI for Improved Kidney Transplantation Outcome: Protocol for an Algorithm Development and Validation Study.

BACKGROUND: Recent advances in hardware and software enabled the use of artificial intelligence (AI) algorithms for analysis of complex data in a wide range of daily-life use cases. We aim to explore the benefits of applying AI to a specific use case in transplant nephrology: risk prediction for severe posttransplant events. For the first time, we combine multinational real-world transplant data, which require specific legal and technical protection measures. OBJECTIVE: The German-Canadian NephroCAGE consortium aims to develop and evaluate specific processes, software tools, and methods to (1) combine transplant data of more than 8000 cases over the past decades from leading transplant centers in Germany and Canada, (2) implement specific measures to protect sensitive transplant data, and (3) use multinational data as a foundation for developing high-quality prognostic AI models. METHODS: To protect sensitive transplant data addressing the first and second objectives, we aim to implement a decentralized NephroCAGE federated learning infrastructure upon a private blockchain. Our NephroCAGE federated learning infrastructure enables a switch of paradigms: instead of pooling sensitive data into a central database for analysis, it enables the transfer of clinical prediction models (CPMs) to clinical sites for local data analyses. Thus, sensitive transplant data reside protected in their original sites while the comparable small algorithms are exchanged instead. For our third objective, we will compare the performance of selected AI algorithms, for example, random forest and extreme gradient boosting, as foundation for CPMs to predict severe short- and long-term posttransplant risks, for example, graft failure or mortality. The CPMs will be trained on donor and recipient data from retrospective cohorts of kidney transplant patients. RESULTS: We have received initial funding for NephroCAGE in February 2021. All clinical partners have applied for and received ethics approval as of 2022. The process of exploration of clinical transplant database for variable extraction has started at all the centers in 2022. In total, 8120 patient records have been retrieved as of August 2023. The development and validation of CPMs is ongoing as of 2023. CONCLUSIONS: For the first time, we will (1) combine kidney transplant data from nephrology centers in Germany and Canada, (2) implement federated learning as a foundation to use such real-world transplant data as a basis for the training of CPMs in a privacy-preserving way, and (3) develop a learning software system to investigate population specifics, for example, to understand population heterogeneity, treatment specificities, and individual impact on selected posttransplant outcomes. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/48892.

Comprehensive immune profiling of SARS-CoV-2 infected kidney transplant patients.

Introduction: The immune responses of kidney transplant recipients against SARS-CoV-2 remains under studied. Methods: In this prospective pilot study, we performed comprehensive immune profiling using cellular, proteomic, and serologic assays on a cohort of 9 kidney transplant recipients and 12 non-transplant individuals diagnosed with COVID-19. Results: Our data show that in addition to having reduced SARS-CoV-2 specific antibody levels, kidney transplant recipients exhibited significant cellular differences including a decrease in naïve-but increase in effector T cells, a high number of CD28+ CD4 effector memory T cells, and increased CD8 T memory stem cells compared with non-transplant patients. Furthermore, transplant patients had lower concentrations of serum cytokine MIP-1ß as well as a less diverse T cell receptor repertoire. Conclusion: Overall, our results show that compared to non-transplant patients, kidney transplant recipients with SARS-CoV-2 infection exhibit an immunophenotype that is reminiscent of the immune signature observed in patients with severe COVID-19.

High-throughput sequencing defines donor and recipient HLA B-cell epitope frequencies for prospective matching in transplantation.

Compatibility for human leukocyte antigen (HLA) genes between transplant donors and recipients improves graft survival but prospective matching is rarely performed due to the vast heterogeneity of this gene complex. To reduce complexity, we have combined next-generation sequencing and in silico mapping to determine transplant population frequencies and matching probabilities of 150 antibody-binding eplets across all 11 classical HLA genes in 2000 ethnically heterogeneous renal patients and donors. We show that eplets are more common and uniformly distributed between donors and recipients than the respective HLA isoforms. Simulations of targeted eplet matching shows that a high degree of overall compatibility, and perfect identity at the clinically important HLA class II loci, can be obtained within a patient waiting list of approximately 250 subjects. Internal epitope-based allocation is thus feasible for most major renal transplant programs, while regional or national sharing may be required for other solid organs.

Discovery and surveillance of viruses from salmon in British Columbia using viral immune-response biomarkers, metatranscriptomics, and high-throughput RT-PCR.

The emergence of infectious agents poses a continual economic and environmental challenge to aquaculture production, yet the diversity, abundance, and epidemiology of aquatic viruses are poorly characterised. In this study, we applied salmon host transcriptional biomarkers to identify and select fish in a viral disease state, but only those that were negative for known viruses based on RT-PCR screening. These fish were selected for metatranscriptomic sequencing to discover potential viral pathogens of dead and dying farmed Atlantic (Salmo salar) and Chinook (Oncorhynchus tshawytscha) salmon in British Columbia (BC). We found that the application of the biomarker panel increased the probability of discovering viruses in aquaculture populations. We discovered two viruses that have not previously been characterised in Atlantic salmon farms in BC (Atlantic salmon calicivirus and Cutthroat trout virus-2), as well as partially sequenced three putative novel viruses. To determine the epidemiology of the newly discovered or emerging viruses, we conducted high-throughput reverse transcription polymerase chain reaction (RT-PCR) and screened over 9,000 farmed and wild salmon sampled over one decade. Atlantic salmon calicivirus and Cutthroat trout virus-2 were in more than half of the farmed Atlantic salmon we tested. Importantly we detected some of the viruses we first discovered in farmed Atlantic salmon in Chinook salmon, suggesting a broad host range. Finally, we applied in situ hybridisation to determine infection and found differing cell tropism for each virus tested. Our study demonstrates that continual discovery and surveillance of emerging viruses in these ecologically important salmon will be vital for management of both aquaculture and wild resources in the future.

Testosterone therapy: Prescribing and monitoring patterns of practice in British Columbia.

INTRODUCTION: Guidelines recommend that testosterone therapy (TTh) be restricted to men with a biochemical diagnosis of hypogonadism, and that therapeutic responses be titrated within the normal range. METHODS: Using four provincial longitudinal databases in British Columbia, we identified men prescribed TTh from 1997-2013. We characterized the prescribing and monitoring practices of TTh in the context of serum testosterone levels drawn prior to and following initiation of TTh in a population-based setting. RESULTS: In our analysis of 37 741 men who received at least one TTh prescription, 48% received injectable testosterone and the vast majority were treated by general practitioners. The number of prescriptions for men increased annually, particularly after 2008; 40% discontinued their treatment after their first or second prescription, while 27% received more than 10 repeats. The absolute percentage of pre- and post-serum testosterone levels ordered increased by 16% and 31% during the study period, respectively. However, after initiating TTh, only 36% of all the men had a followup serum testosterone level drawn. Of those with low serum testosterone levels prior to TTh, 49% remained biochemically hypogonadal following TTh, suggesting non-compliance or inadequate dosing. CONCLUSIONS: Many men prescribed TTh did not continue beyond a short trial. While the practice of checking pre-and post-TTh testosterone levels improved over the study period, it is concerning that only one-third had a followup serum testosterone level and half remained biochemically low. Further education is required around TTh prescribing, dose titration, and monitoring to ensure both effective and safe prescribing practice.

Identification of Hypoxia-Specific Biomarkers in Salmonids Using RNA-Sequencing and Validation Using High-Throughput qPCR.

Identifying early gene expression responses to hypoxia (i.e., low dissolved oxygen) as a tool to assess the degree of exposure to this stressor is crucial for salmonids, because they are increasingly exposed to hypoxic stress due to anthropogenic habitat change, e.g., global warming, excessive nutrient loading, and persistent algal blooms. Our goal was to discover and validate gill gene expression biomarkers specific to the hypoxia response in salmonids across multi-stressor conditions. Gill tissue was collected from 24 freshwater juvenile Chinook salmon (Oncorhynchus tshawytscha), held in normoxia [dissolved oxygen (DO) > 8 mg L-1] and hypoxia (DO = 4‒5 mg L-1) in 10 and 18° temperatures for up to six days. RNA-sequencing (RNA-seq) was then used to discover 240 differentially expressed genes between hypoxic and normoxic conditions, but not affected by temperature. The most significantly differentially expressed genes had functional roles in the cell cycle and suppression of cell proliferation associated with hypoxic conditions. The most significant genes (n = 30) were selected for real-time qPCR assay development. These assays demonstrated a strong correlation (r = 0.88; P < 0.001) between the expression values from RNA-seq and the fold changes from qPCR. Further, qPCR of the 30 candidate hypoxia biomarkers was applied to an additional 322 Chinook salmon exposed to hypoxic and normoxic conditions to reveal the top biomarkers to define hypoxic stress. Multivariate analyses revealed that smolt stage, water salinity, and morbidity status were relevant factors to consider with the expression of these genes in relation to hypoxic stress. These hypoxia candidate genes will be put into application screening Chinook salmon to determine the identity of stressors impacting the fish.

Discovery and validation of candidate smoltification gene expression biomarkers across multiple species and ecotypes of Pacific salmonids.

Early marine survival of juvenile salmon is intimately associated with their physiological condition during smoltification and ocean entry. Smoltification (parr-smolt transformation) is a developmental process that allows salmon to acquire seawater tolerance in preparation for marine living. Traditionally, this developmental process has been monitored using gill Na+/K+-ATPase (NKA) activity or plasma hormones, but gill gene expression offers the possibility of another method. Here, we describe the discovery of candidate genes from gill tissue for staging smoltification using comparisons of microarray studies with particular focus on the commonalities between anadromous Rainbow trout and Sockeye salmon datasets, as well as a literature comparison encompassing more species. A subset of 37 candidate genes mainly from the microarray analyses was used for TaqMan quantitative PCR assay design and their expression patterns were validated using gill samples from four groups, representing three species and two ecotypes: Coho salmon, Sockeye salmon, stream-type Chinook salmon and ocean-type Chinook salmon. The best smoltification biomarkers, as measured by consistent changes across these four groups, were genes involved in ion regulation, oxygen transport and immunity. Smoltification gene expression patterns (using the top 10 biomarkers) were confirmed by significant correlations with NKA activity and were associated with changes in body brightness, caudal fin darkness and caudal peduncle length. We incorporate gene expression patterns of pre-smolt, smolt and de-smolt trials from acute seawater transfers from a companion study to develop a preliminary seawater tolerance classification model for ocean-type Chinook salmon. This work demonstrates the potential of gene expression biomarkers to stage smoltification and classify juveniles as pre-smolt, smolt or de-smolt.

Salmonid gene expression biomarkers indicative of physiological responses to changes in salinity and temperature, but not dissolved oxygen.

An organism's ability to respond effectively to environmental change is critical to its survival. Yet, life stage and overall condition can dictate tolerance thresholds to heightened environmental stressors, such that stress may not be equally felt across individuals and at all times. Also, the transcriptional responses induced by environmental changes can reflect both generalized responses as well as others that are highly specific to the type of change being experienced. Thus, if transcriptional biomarkers specific to a stressor, even under multi-stressor conditions, can be identified, the biomarkers could then be applied in natural environments to determine when and where an individual experiences such a stressor. Here, we experimentally challenged juvenile Chinook salmon (Oncorhynchus tshawytscha) to validate candidate gill gene expression biomarkers. A sophisticated experimental design manipulated salinity (freshwater, brackish water and seawater), temperature (10, 14 and 18°C) and dissolved oxygen (normoxia and hypoxia) in all 18 possible combinations for 6 days using separate trials for three smolt statuses (pre-smolt, smolt and de-smolt). In addition, changes in juvenile behaviour, plasma variables, gill Na+/K+-ATPase activity, body size, body morphology and skin pigmentation supplemented the gene expression responses. We identified biomarkers specific to salinity and temperature that transcended the multiple stressors, smolt status and mortality (live, dead and moribund). Similar biomarkers for dissolved oxygen were not identified. This work demonstrates the unique power of gene expression biomarkers to identify a specific stressor even under multi-stressor conditions, and we discuss our next steps for hypoxia biomarkers using an RNA-seq study.

Immunosignature Analysis of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS).

A random-sequence peptide microarray can interrogate serum antibodies in a broad, unbiased fashion to generate disease-specific immunosignatures. This approach has been applied to cancer detection, diagnosis of infections, and interrogation of vaccine response. We hypothesized that there is an immunosignature specific to ME/CFS and that this could aid in the diagnosis. We studied two subject groups meeting the Canadian Consensus Definition of ME/CFS. ME/CFS (n = 25) and matched control (n = 25) sera were obtained from a Canadian study. ME/CFS (n = 25) sera were obtained from phase 1/2 Norwegian trials (NCT01156909). Sera from six healthy controls from the USA were included in the analysis. Canadian cases and controls were tested for a disease immunosignature. By combining results from unsupervised and supervised analyses, a candidate immunosignature with 654 peptides was able to differentiate ME/CFS from controls. The immunosignature was tested and further refined using the Norwegian and USA samples. This resulted in a 256-peptide immunosignature with the ability to separate ME/CFS cases from controls in the international data sets. We were able to identify a 256-peptide signature that separates ME/CFS samples from healthy controls, suggesting that the hit-and-run hypothesis of immune dysfunction merits further investigation. By extending testing of both our signature and one previously reported in the literature to larger cohorts, and further interrogating the specific peptides we and others have identified, we may deepen our understanding of the origins of ME/CFS and work towards a clinically meaningful diagnostic biomarker.

Developing specific molecular biomarkers for thermal stress in salmonids.

BACKGROUND: Pacific salmon (Oncorhynchus spp.) serve as good biological indicators of the breadth of climate warming effects on fish because their anadromous life cycle exposes them to environmental challenges in both marine and freshwater environments. Our study sought to mine the extensive functional genomic studies in fishes to identify robust thermally-responsive biomarkers that could monitor molecular physiological signatures of chronic thermal stress in fish using non-lethal sampling of gill tissue. RESULTS: Candidate thermal stress biomarkers for gill tissue were identified using comparisons among microarray datasets produced in the Molecular Genetics Laboratory, Pacific Biological Station, Nanaimo, BC, six external, published microarray studies on chronic and acute temperature stress in salmon, and a comparison of significant genes across published studies in multiple fishes using deep literature mining. Eighty-two microarray features related to 39 unique gene IDs were selected as candidate chronic thermal stress biomarkers. Most of these genes were identified both in the meta-analysis of salmon microarray data and in the literature mining for thermal stress markers in salmonids and other fishes. Quantitative reverse transcription PCR (qRT-PCR) assays for 32 unique genes with good efficiencies across salmon species were developed, and their activity in response to thermally challenged sockeye salmon (O. nerka) and Chinook salmon (O. tshawytscha) (cool, 13-14 °C and warm temperatures 18-19 °C) over 5-7 days was assessed. Eight genes, including two transcripts of each SERPINH1 and HSP90AA1, FKBP10, MAP3K14, SFRS2, and EEF2 showed strong and robust chronic temperature stress response consistently in the discovery analysis and both sockeye and Chinook salmon validation studies. CONCLUSIONS: The results of both discovery analysis and gene expression showed that a panel of genes involved in chaperoning and protein rescue, oxidative stress, and protein biosynthesis were differentially activated in gill tissue of Pacific salmon in response to elevated temperatures. While individually, some of these biomarkers may also respond to other stressors or biological processes, when expressed in concert, we argue that a biomarker panel comprised of some or all of these genes could provide a reliable means to specifically detect thermal stress in field-caught salmon.

Molecular indices of viral disease development in wild migrating salmon†.

Infectious diseases can impact the physiological performance of individuals, including their mobility, visual acuity, behavior and tolerance and ability to effectively respond to additional stressors. These physiological effects can influence competitiveness, social hierarchy, habitat usage, migratory behavior and risk to predation, and in some circumstances, viability of populations. While there are multiple means of detecting infectious agents (microscopy, culture, molecular assays), the detection of infectious diseases in wild populations in circumstances where mortality is not observable can be difficult. Moreover, if infection-related physiological compromise leaves individuals vulnerable to predation, it may be rare to observe wildlife in a late stage of disease. Diagnostic technologies designed to diagnose cause of death are not always sensitive enough to detect early stages of disease development in live-sampled organisms. Sensitive technologies that can differentiate agent carrier states from active disease states are required to demonstrate impacts of infectious diseases in wild populations. We present the discovery and validation of salmon host transcriptional biomarkers capable of distinguishing fish in an active viral disease state [viral disease development (VDD)] from those carrying a latent viral infection, and viral versus bacterial disease states. Biomarker discovery was conducted through meta-analysis of published and in-house microarray data, and validation performed on independent datasets including disease challenge studies and farmed salmon diagnosed with various viral, bacterial and parasitic diseases. We demonstrate that the VDD biomarker panel is predictive of disease development across RNA-viral species, salmon species and salmon tissues, and can recognize a viral disease state in wild-migrating salmon. Moreover, we show that there is considerable overlap in the biomarkers resolved in our study in salmon with those based on similar human viral influenza research, suggesting a highly conserved suite of host genes associated with viral disease that may be applicable across a broad range of vertebrate taxa.

Controlled diesel exhaust and allergen coexposure modulates microRNA and gene expression in humans: Effects on inflammatory lung markers.

BACKGROUND: Air pollution's association with asthma may be due to its augmentation of allergenic effects, but the role of microRNA (miRNA) and gene expression in this synergy is unknown. OBJECTIVE: We sought to determine whether exposure to allergen, exposure to diesel exhaust (DE), or coexposures modulate miRNA, gene expression, or inflammatory pathways and whether these measurements are correlated. METHODS: Fifteen participants with atopy completed this controlled study of 2 hours of filtered air or DE (300 µg PM2.5/m3) exposure, followed by saline-controlled segmental bronchial allergen challenge. Gene and miRNA expression in bronchial brushings and lung inflammatory markers were measured 48 hours later, in study arms separated by approximately 4 weeks. Expression of miRNAs, messenger RNAs, and inflammatory markers and their interrelationships were determined using regression. RESULTS: Robust linear models indicated that DE plus saline and DE plus allergen significantly modulated the highest number of miRNAs and messenger RNAs, respectively, relative to control (filtered air plus saline). In mixed models, allergen exposure modulated (q ≤ 0.2) miRNAs including miR-183-5p, miR-324-5p, and miR-132-3p and genes including NFKBIZ and CDKN1A, but DE did not significantly modify this allergenic effect. Repression of CDKN1A by allergen-induced miR-132-3p may contribute to shedding of bronchial epithelial cells. CONCLUSIONS: Expression of specific miRNAs and genes associated with bronchial immune responses were significantly modulated by DE or allergen. However, DE did not augment the effect of allergen at 48 hours, suggesting that adjuvancy may be transient or require higher or prolonged exposure. In silico analysis suggested a possible mechanism contributing to epithelial wall damage following allergen exposure.

Novel multivariate methods for integration of genomics and proteomics data: applications in a kidney transplant rejection study.

Multi-omics research is a key ingredient of data-intensive life sciences research, permitting measurement of biological molecules at different functional levels in the same individual. For a complete picture at the biological systems level, appropriate statistical techniques must however be developed to integrate different 'omics' data sets (e.g., genomics and proteomics). We report here multivariate projection-based analyses approaches to genomics and proteomics data sets, using the case study of and applications to observations in kidney transplant patients who experienced an acute rejection event (n=20) versus non-rejecting controls (n=20). In this data sets, we show how these novel methodologies might serve as promising tools for dimension reduction and selection of relevant features for different analytical frameworks. Unsupervised analyses highlighted the importance of post transplant time-of-rejection, while supervised analyses identified gene and protein signatures that together predicted rejection status with little time effect. The selected genes are part of biological pathways that are representative of immune responses. Gene enrichment profiles revealed increases in innate immune responses and neutrophil activities and a depletion of T lymphocyte related processes in rejection samples as compared to controls. In all, this article offers candidate biomarkers for future detection and monitoring of acute kidney transplant rejection, as well as ways forward for methodological advances to better harness multi-omics data sets.

Alteration of human blood cell transcriptome in uremia.

BACKGROUND: End-stage renal failure is associated with profound changes in physiology and health, but the molecular causation of these pleomorphic effects termed "uremia" is poorly understood. The genomic changes of uremia were explored in a whole genome microarray case-control comparison of 95 subjects with end-stage renal failure (n = 75) or healthy controls (n = 20). METHODS: RNA was separated from blood drawn in PAXgene tubes and gene expression analyzed using Affymetrix Human Genome U133 Plus 2.0 arrays. Quality control and normalization was performed, and statistical significance determined with multiple test corrections (qFDR). Biological interpretation was aided by knowledge mining using NIH DAVID, MetaCore and PubGene RESULTS: Over 9,000 genes were differentially expressed in uremic subjects compared to normal controls (fold change: -5.3 to +6.8), and more than 65% were lower in uremia. Changes appeared to be regulated through key gene networks involving cMYC, SP1, P53, AP1, NFkB, HNF4 alpha, HIF1A, c-Jun, STAT1, STAT3 and CREB1. Gene set enrichment analysis showed that mRNA processing and transport, protein transport, chaperone functions, the unfolded protein response and genes involved in tumor genesis were prominently lower in uremia, while insulin-like growth factor activity, neuroactive receptor interaction, the complement system, lipoprotein metabolism and lipid transport were higher in uremia. Pathways involving cytoskeletal remodeling, the clathrin-coated endosomal pathway, T-cell receptor signaling and CD28 pathways, and many immune and biological mechanisms were significantly down-regulated, while the ubiquitin pathway and certain others were up-regulated. CONCLUSIONS: End-stage renal failure is associated with profound changes in human gene expression which appears to be mediated through key transcription factors. Dialysis and primary kidney disease had minor effects on gene regulation, but uremia was the dominant influence in the changes observed. This data provides important insight into the changes in cellular biology and function, opportunities for biomarkers of disease progression and therapy, and potential targets for intervention in uremia.

A computational pipeline for the development of multi-marker bio-signature panels and ensemble classifiers.

BACKGROUND: Biomarker panels derived separately from genomic and proteomic data and with a variety of computational methods have demonstrated promising classification performance in various diseases. An open question is how to create effective proteo-genomic panels. The framework of ensemble classifiers has been applied successfully in various analytical domains to combine classifiers so that the performance of the ensemble exceeds the performance of individual classifiers. Using blood-based diagnosis of acute renal allograft rejection as a case study, we address the following question in this paper: Can acute rejection classification performance be improved by combining individual genomic and proteomic classifiers in an ensemble? RESULTS: The first part of the paper presents a computational biomarker development pipeline for genomic and proteomic data. The pipeline begins with data acquisition (e.g., from bio-samples to microarray data), quality control, statistical analysis and mining of the data, and finally various forms of validation. The pipeline ensures that the various classifiers to be combined later in an ensemble are diverse and adequate for clinical use. Five mRNA genomic and five proteomic classifiers were developed independently using single time-point blood samples from 11 acute-rejection and 22 non-rejection renal transplant patients. The second part of the paper examines five ensembles ranging in size from two to 10 individual classifiers. Performance of ensembles is characterized by area under the curve (AUC), sensitivity, and specificity, as derived from the probability of acute rejection for individual classifiers in the ensemble in combination with one of two aggregation methods: (1) Average Probability or (2) Vote Threshold. One ensemble demonstrated superior performance and was able to improve sensitivity and AUC beyond the best values observed for any of the individual classifiers in the ensemble, while staying within the range of observed specificity. The Vote Threshold aggregation method achieved improved sensitivity for all 5 ensembles, but typically at the cost of decreased specificity. CONCLUSION: Proteo-genomic biomarker ensemble classifiers show promise in the diagnosis of acute renal allograft rejection and can improve classification performance beyond that of individual genomic or proteomic classifiers alone. Validation of our results in an international multicenter study is currently underway.

DNA methylation profiles of airway epithelial cells and PBMCs from healthy, atopic and asthmatic children.

BACKGROUND: Allergic inflammation is commonly observed in a number of conditions that are associated with atopy including asthma, eczema and rhinitis. However, the genetic, environmental or epigenetic factors involved in these conditions are likely to be different. Epigenetic modifications, such as DNA methylation, can be influenced by the environment and result in changes to gene expression. OBJECTIVES: To characterize the DNA methylation pattern of airway epithelial cells (AECs) compared to peripheral blood mononuclear cells (PBMCs) and to discern differences in methylation within each cell type amongst healthy, atopic and asthmatic subjects. METHODS: PBMCs and AECs from bronchial brushings were obtained from children undergoing elective surgery for non-respiratory conditions. The children were categorized as atopic, atopic asthmatic, non-atopic asthmatic or healthy controls. Extracted DNA was bisulfite treated and 1505 CpG loci across 807 genes were analyzed using the Illumina GoldenGate Methylation Cancer Panel I. Gene expression for a subset of genes was performed using RT-PCR. RESULTS: We demonstrate a signature set of CpG sites that are differentially methylated in AECs as compared to PBMCs regardless of disease phenotype. Of these, 13 CpG sites were specific to healthy controls, 8 sites were only found in atopics, and 6 CpGs were unique to asthmatics. We found no differences in the methylation status of PBMCs between disease phenotypes. In AECs derived from asthmatics compared to atopics, 8 differentially methylated sites were identified including CpGs in STAT5A and CRIP1. We demonstrate STAT5A gene expression is decreased whereas CRIP1 gene expression is elevated in the AECs from asthmatic compared to both healthy and atopic subjects. DISCUSSION: We characterized a cell specific DNA methylation signature for AECs compared to PBMCs regardless of asthmatic or atopic status. Our data highlight the importance of understanding DNA methylation in the epithelium when studying the epithelial contribution to asthma.

Effects of sample timing and treatment on gene expression in early acute renal allograft rejection.

BACKGROUND: We have shown that genomic biomarkers in peripheral blood provide evidence of early graft rejection and may offer an important option for posttransplant monitoring, and we are working to improve this signature to maximize assay performance. METHODS: This clinical refinement study (n=79) used gene expression profiling in a case-control design to compare whole blood samples between normal subjects (n=20) and patients with (n=20) or without (n=39) biopsy-confirmed acute rejection (BCAR). RESULTS: Gene expression in peripheral blood from subjects with BCAR before treatment differed significantly from that of normal subjects and transplant recipients without BCAR. Hierarchical clustering and principal component analysis showed that samples obtained 1 to 5 days after the start of treatment of BCAR were segregated across both groups before treatment or without BCAR and that this was closely related to the time lag between treatment and sampling. Genes differentially expressed during BCAR included FKSG49, LMAN2, NFYC, LIMK2, JUNB, NASP, MALAT1, ITGAX, HLA-J, FKBP1A, and RBMS1, and gene ontology analysis highlighted changes in networks related to cytoskeletal reorganization, apoptosis, and immune signaling, whereas after treatment change highlighted pathways of cellular metabolism, cell-cycle regulation, DNA damage, and apoptosis. CONCLUSION: Gene expression in the peripheral blood is associated with BCAR, and the pattern of expression changes rapidly after treatment. This may offer a potential tool for diagnosis of rejection and immunologic monitoring of response to treatment, which is now being evaluated in a large multicenter international study.

Proteomic signatures in plasma during early acute renal allograft rejection.

Acute graft rejection is an important clinical problem in renal transplantation and an adverse predictor for long term graft survival. Plasma biomarkers may offer an important option for post-transplant monitoring and permit timely and effective therapeutic intervention to minimize graft damage. This case-control discovery study (n = 32) used isobaric tagging for relative and absolute protein quantification (iTRAQ) technology to quantitate plasma protein relative concentrations in precise cohorts of patients with and without biopsy-confirmed acute rejection (BCAR). Plasma samples were depleted of the 14 most abundant plasma proteins to enhance detection sensitivity. A total of 18 plasma proteins that encompassed processes related to inflammation, complement activation, blood coagulation, and wound repair exhibited significantly different relative concentrations between patient cohorts with and without BCAR (p value <0.05). Twelve proteins with a fold-change >or=1.15 were selected for diagnostic purposes: seven were increased (titin, lipopolysaccharide-binding protein, peptidase inhibitor 16, complement factor D, mannose-binding lectin, protein Z-dependent protease and beta(2)-microglobulin) and five were decreased (kininogen-1, afamin, serine protease inhibitor, phosphatidylcholine-sterol acyltransferase, and sex hormone-binding globulin) in patients with BCAR. The first three principal components of these proteins showed clear separation of cohorts with and without BCAR. Performance improved with the inclusion of sequential proteins, reaching a primary asymptote after the first three (titin, kininogen-1, and lipopolysaccharide-binding protein). Longitudinal monitoring over the first 3 months post-transplant based on ratios of these three proteins showed clear discrimination between the two patient cohorts at time of rejection. The score then declined to baseline following treatment and resolution of the rejection episode and remained comparable between cases and controls throughout the period of quiescent follow-up. Results were validated using ELISA where possible, and initial cross-validation estimated a sensitivity of 80% and specificity of 90% for classification of BCAR based on a four-protein ELISA classifier. This study provides evidence that protein concentrations in plasma may provide a relevant measure for the occurrence of BCAR and offers a potential tool for immunologic monitoring.

Functional genomic analysis of peripheral blood during early acute renal allograft rejection.

BACKGROUND: Acute graft rejection is an important clinical problem in renal transplantation and an adverse predictor for long-term graft survival. Peripheral blood biomarkers that provide evidence of early graft rejection may offer an important option for posttransplant monitoring, optimize the utility of graft biopsy, and permit timely and effective therapeutic intervention to minimize the graft damage. METHODS: In this feasibility study (n=58), we have used gene expression profiling in a case-control design to compare whole blood samples between normal subjects (n=20) and patients with (n=11) or without (n=22) biopsy-confirmed acute rejection (BCAR) or borderline changes (n=5). RESULTS: A total of 183 probe sets representing 160 genes were differentially expressed (false discovery rate [FDR] <0.01) between subjects with or without BCAR, from which linear discriminant analysis and cross-validation identified an initial gene signature of 24 probe sets, and a more refined set of 11 probe sets found to classify subject samples correctly. Cross-validation suggested an out-of-sample sensitivity of 73% and specificity of 91% for identification of samples with or without BCAR. An increase in classifier gene expression correlated closely with acute rejection during the first 3 months posttransplant. Biological evaluation indicated that the differentially expressed genes encompassed processes related to immune response, signal transduction, and cytoskeletal reorganization. CONCLUSION: Preliminary evidence indicates that gene expression in the peripheral blood may yield a relevant measure for the occurrence of BCAR and offer a potential tool for immunologic monitoring. These results now require confirmation in a larger cohort.