David Lin

Inflammation in myocardial diseases.

Inflammatory processes underlie a broad spectrum of conditions that injure the heart muscle and cause both structural and functional deficits. In this article, we address current knowledge regarding 4 common forms of myocardial inflammation: myocardial ischemia and reperfusion, sepsis, viral myocarditis, and immune rejection. Each of these pathological states has its own unique features in pathogenesis and disease evolution, but all reflect inflammatory mechanisms that are partially shared. From the point of injury to the mobilization of innate and adaptive immune responses and inflammatory amplification, the cellular and soluble mediators and mechanisms examined in this review will be discussed with a view that both beneficial and adverse consequences arise in these human conditions.

The Biological Role of Inflammation in Atherosclerosis

The concept of the involvement of inflammation in the pathogenesis of atherosclerosis has existed since the 1800s, stemming from sentinel pathologic observations made by Rudolf Virchow, Karl Rokitansky, and others. Our understanding of the complex role played by immune and inflammatory mediators in the initiation and progression of atherosclerosis has evolved considerably in the intervening years, and today, a dramatically evolved understanding of these processes has led to advances in both diagnostic and prognostic approaches, as well as novel treatment modalities targeting inflammatory and immune mediators. Therapeutic interventions working through multiple mechanisms involved in atheroma pathogenesis, such as statins, which both lower lipids and alter the inflammatory milieu in the vessel wall, hold promise for the future. In this brief review, we explore the biological role of inflammation in atherosclerosis, with a focus on cellular involvement in both acute and chronic inflammation, and outline novel biomarkers of inflammation and atherosclerosis with a particular focus on the potential application of these novel approaches in improving strategies for disease diagnosis and management.

Whole Blood Genomic Biomarkers of Acute Cardiac Allograft Rejection

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.

Computational Biomarker Pipeline from Discovery to Clinical Implementation: Plasma Proteomic Biomarkers for Cardiac Transplantation

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.

Whole blood biomarkers of acute cardiac allograft rejection: double-crossing the biopsy.

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.

An automated assay for the clinical measurement of plasma renin activity by immuno-MALDI (iMALDI) ☆

Plasma renin activity (PRA) is essential for the screening and diagnosis of primary aldosteronism (PA), a form of secondary hypertension, which affects approximately 100 million people worldwide. It is commonly determined by radioimmunoassay (RIA) and, more recently, by relatively low-throughput LC-MS/MS methods. In order to circumvent the negative aspects of RIAs (radioisotopes, cross-reactivity) and the low throughput of LC-MS based methods, we have developed a high-throughput immuno-MALDI (iMALDI)-based assay for PRA determination using an Agilent Bravo for automated liquid handling and a Bruker Microflex LRF instrument for MALDI analysis, with the goal of implementing the assay in clinical laboratories. The current assay allows PRA determination of 29 patient samples (192 immuno-captures), within ~6 to 7h, using a 3-hour Ang I generation period, at a 7.5-fold faster analysis time than LC-MS/MS. The assay is performed on 350μL of plasma, and has a linear range from 0.08 to 5.3ng/L/s in the reflector mode, and 0.04 to 5.3ng/L/s in the linear mode. The analytical precision is 2.0 to 9.7% CV in the reflector mode, and 1.5 to 14.3% CV in the linear mode. A method comparison to a clinically employed LC-MS/MS assay for PRA determination showed excellent correlation within the linear range, with an R(2) value of ≥0.98. This automated high throughput iMALDI platform has clinically suitable sensitivity, precision, linear range, and correlation with the standard method for PRA determination. Furthermore, the developed workflow based on the iMALDI technology can be used for the determination of other proteomic biomarkers. This article is part of a Special Issue entitled: Medical Proteomics.

Plasma Protein Biosignatures for Detection of Cardiac Allograft Vasculopathy

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.

Predicting acute cardiac rejection from donor heart and pre-transplant recipient blood gene expression

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.

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.

CLASSIFICATION OF ACUTE RENAL REJECTION WITH PROTEOGENOMIC ENSEMBLE CLASSIFIERS: 1477

O.P. Gunther1, R. Ng2, R. Balshaw3, D. Lin4, A. Scherer5, V. Chen2, G. Cohen-Freue2, M. Takhar2, Z. Hollander2, R. McMaster3, B. McManus6, P. Keown3 1Proof Centre Of Excellence, University of British Columbia, Vancouver/CANADA, 2, PROOF Centre of Excellence, Vancouver/ CANADA, 3, University of British Columbia, Vancouver/CANADA, 4Pathology And Laboratory Medicine, University Of British Columbia, 1PROOF Center of Excellence, Vancouver/BC/CANADA, 5, Spheromics, Kontiolahti/FINLAND, 6, Providence Heart + Lung Institute at St. Paul’s Hospital, the University of British Columbia, Vancouver/BC/CANADA