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Background: Nine mRNA transcripts associated with acute cellular rejection (ACR) in previous microarray studies were ported to the clinically amenable NanoString nCounter platform. Here we report the diagnostic performance of the resulting blood test to exclude ACR in heart allograft recipients: HEARTBiT., Methods: Blood samples for transcriptomic profiling were collected during routine post-transplantation monitoring in 8 Canadian transplant centres participating in the Biomarkers in Transplantation initiative, a large (n = 1622) prospective observational study conducted between 2009 and 2014. All adult cardiac transplant patients were invited to participate (median age = 56 [17 to 71]). The reference standard for rejection status was histopathology grading of tissue from endomyocardial biopsy (EMB). All locally graded ISHLT ≥ 2R rejection samples were selected for analysis (n = 36). ISHLT 1R (n = 38) and 0R (n = 86) samples were randomly selected to create a cohort approximately matched for site, age, sex, and days post-transplantation, with a focus on early time points (median days post-transplant = 42 [7 to 506])., Results: ISHLT ≥ 2R rejection was confirmed by EMB in 18 and excluded in 92 samples in the test set. HEARTBiT achieved 47% specificity (95% confidence interval [CI], 36%-57%) given ≥ 90% sensitivity, with a corresponding area under the receiver operating characteristic curve of 0.69 (95% CI, 0.56-0.81)., Conclusions: HEARTBiT's diagnostic performance compares favourably to the only currently approved minimally invasive diagnostic test to rule out ACR, AlloMap (CareDx, Brisbane, CA) and may be used to inform care decisions in the first 2 months post-transplantation, when AlloMap is not approved, and most ACR episodes occur., (Copyright © 2019 Canadian Cardiovascular Society. Published by Elsevier Inc. All rights reserved.)

Aims: Chronic heart failure is a costly epidemic that affects up to 2% of people in developed countries. The purpose of this study was to discover novel blood proteomic biomarker signatures of recovered heart function that could lead to more effective heart failure patient management by both primary care and specialty physicians., Methods and Results: The discovery cohort included 41 heart transplant patients and 20 healthy individuals. Plasma levels of 138 proteins were detected in at least 75% of these subjects by iTRAQ mass spectrometry. Eighteen proteins were identified that had (i) differential levels between pre-transplant patients with end-stage heart failure and healthy individuals; and (ii) levels that returned to normal by 1 month post-transplant in patients with stable heart function after transplantation. Seventeen of the 18 markers were validated by multiple reaction monitoring mass spectrometry in a cohort of 39 heart failure patients treated with drug therapy, of which 30 had recovered heart function and 9 had not. This 17-protein biomarker panel had 93% sensitivity and 89% specificity, while the RAMP® NT-proBNP assay had the same specificity but 80% sensitivity. Performance further improved when the panel was combined with NT-proBNP, yielding a net reclassification index relative to NT-proBNP of 0.28., Conclusions: We have identified potential blood biomarkers of recovered heart function by harnessing data from transplant patients. These biomarkers can lead to the development of an inexpensive protein-based blood test that could be used by physicians to monitor response to therapy in heart failure, resulting in more personalized, front-line heart failure patient management., (© 2014 The Authors. European Journal of Heart Failure © 2014 European Society of Cardiology.)

Background: Coronary angiography remains the most widely used tool for routine screening and diagnosis of cardiac allograft vasculopathy (CAV), a major pathologic process that develops in 50% of cardiac transplant recipients beyond the first year after transplant. Given the invasiveness, expense, discomfort, and risk of complications associated with angiography, a minimally invasive alternative that is sensitive and specific would be highly desirable for monitoring CAV in patients., Methods: Plasma proteomic analysis using isobaric tags for relative and absolute quantitation-matrix-assisted laser desorption ionization double time-of-flight mass spectrometry was carried out on samples from 40 cardiac transplant patients (10 CAV, 9 non-significant CAV, 21 possible CAV). Presence of CAV was defined as left anterior descending artery diameter stenosis ≥ 40% by digital angiography and quantitatively measured by blinded expert appraisal. Moderated t-test robust-linear models for microarray data were used to identify biomarkers that are significantly differentially expressed between patient samples with CAV and with non-significant CAV. A proteomic panel for diagnosis of CAV was generated using the Elastic Net classification method., Results: We identified an 18-plasma protein biomarker classifier panel that was able to classify and differentiate patients with angiographically significant CAV from those without significant CAV, with an 80% sensitivity and 89% specificity, while providing insight into the possible underlying immune and non-alloimmune contributory mechanisms of CAV., Conclusion: Our results support of the potential utility of proteomic biomarker panels as a minimally invasive means to identify patients with significant, angiographically detectable coronary artery stenosis in the cardiac allograft, in the context of post-cardiac transplantation monitoring and screening for CAV. The potential biologic significance of the biomarkers identified may also help improve our understanding of CAV pathophysiology., (Copyright © 2013 International Society for Heart and Lung Transplantation. Published by Elsevier Inc. All rights reserved.)

Recent technical advances in the field of quantitative proteomics have stimulated a large number of biomarker discovery studies of various diseases, providing avenues for new treatments and diagnostics. However, inherent challenges have limited the successful translation of candidate biomarkers into clinical use, thus highlighting the need for a robust analytical methodology to transition from biomarker discovery to clinical implementation. We have developed an end-to-end computational proteomic pipeline for biomarkers studies. At the discovery stage, the pipeline emphasizes different aspects of experimental design, appropriate statistical methodologies, and quality assessment of results. At the validation stage, the pipeline focuses on the migration of the results to a platform appropriate for external validation, and the development of a classifier score based on corroborated protein biomarkers. At the last stage towards clinical implementation, the main aims are to develop and validate an assay suitable for clinical deployment, and to calibrate the biomarker classifier using the developed assay. The proposed pipeline was applied to a biomarker study in cardiac transplantation aimed at developing a minimally invasive clinical test to monitor acute rejection. Starting with an untargeted screening of the human plasma proteome, five candidate biomarker proteins were identified. Rejection-regulated proteins reflect cellular and humoral immune responses, acute phase inflammatory pathways, and lipid metabolism biological processes. A multiplex multiple reaction monitoring mass-spectrometry (MRM-MS) assay was developed for the five candidate biomarkers and validated by enzyme-linked immune-sorbent (ELISA) and immunonephelometric assays (INA). A classifier score based on corroborated proteins demonstrated that the developed MRM-MS assay provides an appropriate methodology for an external validation, which is still in progress. Plasma proteomic biomarkers of acute cardiac rejection may offer a relevant post-transplant monitoring tool to effectively guide clinical care. The proposed computational pipeline is highly applicable to a wide range of biomarker proteomic studies.

Background: Acute rejection in cardiac transplant patients remains a contributory factor to limited survival of implanted hearts. Currently, there are no biomarkers in clinical use that can predict, at the time of transplantation, the likelihood of post-transplant acute cellular rejection. Such a development would be of great value in personalizing immunosuppressive treatment., Methods: Recipient age, donor age, cold ischemic time, warm ischemic time, panel-reactive antibody, gender mismatch, blood type mismatch and human leukocyte antigens (HLA-A, -B and -DR) mismatch between recipients and donors were tested in 53 heart transplant patients for their power to predict post-transplant acute cellular rejection. Donor transplant biopsy and recipient pre-transplant blood were also examined for the presence of genomic biomarkers in 7 rejection and 11 non-rejection patients, using non-targeted data mining techniques., Results: The biomarker based on the 8 clinical variables had an area under the receiver operating characteristic curve (AUC) of 0.53. The pre-transplant recipient blood gene-based panel did not yield better performance, but the donor heart tissue gene-based panel had an AUC = 0.78. A combination of 25 probe sets from the transplant donor biopsy and 18 probe sets from the pre-transplant recipient whole blood had an AUC = 0.90. Biologic pathways implicated include VEGF- and EGFR-signaling, and MAPK., Conclusions: Based on this study, the best predictive biomarker panel contains genes from recipient whole blood and donor myocardial tissue. This panel provides clinically relevant prediction power and, if validated, may personalize immunosuppressive treatment and rejection monitoring., (Copyright © 2013 International Society for Heart and Lung Transplantation. Published by Elsevier Inc. All rights reserved.)

Background: Acute rejection is still a significant barrier to long-term survival of the allograft. Current acute rejection diagnostic methods are not specific enough or are invasive. There have been a number of studies that have explored the blood or the biopsy to discover genomic biomarkers of acute rejection; however, none of the studies to date have used both., Methods: We analyzed endomyocardial biopsy tissue and whole blood-derived messenger RNA from 11 acute rejection and 20 nonrejection patients using Affymetrix Human Genome U133 Plus 2.0 chips. We used a novel approach and gained insight into the biology of rejection based on gene expression in the biopsy, and applied this knowledge to the blood analysis to identify novel blood biomarkers., Results: We identified probesets that are differentially expressed between acute rejection and nonrejection patients in the biopsy and blood, and developed three biomarker panels: (1) based on biopsy-only (area under the curve=0.85), (2) based on biopsy-targeted whole blood (area under the curve=0.83), and (3) based on whole blood-only (area under the curve=0.60) analyses., Conclusions: Most of the probesets replicated between biopsy and blood are regulated in opposite direction between the two sources of information. We also observed that the biopsy-targeted blood biomarker discovery approach can improve performance of the biomarker panel. The biomarker panel developed using this targeted approach is able to diagnose acute cardiac allograft rejection almost as well as the biopsy-only based biomarker panel.

Background: Significant progress has been made in cardiac transplantation over the past 30 years; however, the means for detection of acute cardiac allograft rejection remains in need of improvement. At present, the endomyocardial biopsy, an invasive and inconvenient procedure for patients, is required for the surveillance and diagnosis of acute cardiac allograft rejection. In the Biomarkers in Transplantation initiative, we investigated gene expression profiles in peripheral blood of cardiac transplant subjects as potential biomarkers for diagnosis of allograft rejection., Methods: Whole blood samples were obtained from 28 cardiac transplant subjects who consented to the study. Serial samples were collected from pre-transplant through 3 years post-transplant according to the standard protocol. Temporally correspondent biopsies were also collected, reviewed in a blinded manner, and graded according to current ISHLT guidelines. Blood samples were analyzed using Affymetrix microarrays. Genomic profiles were compared in subjects with acute rejection (AR; ISHLT Grade > or =2R) and no rejection (NR; Grade 0R). Biomarker panel genes were identified using linear discriminant analysis., Results: We found 1,295 differentially expressed probe-sets between AR and NR samples and developed a 12-gene biomarker panel that classifies our internal validation samples with 83% sensitivity and 100% specificity., Conclusions: Based on our current results, we believe whole blood genomic biomarkers hold great potential in the diagnosis of acute cardiac allograft rejection. A prospective, Canada-wide trial will be conducted shortly to further evaluate the classifier panel in diverse patients and a range of clinical programs.