Gabriela V. Cohen Freue

MRM‐based multiplexed quantitation of 67 putative cardiovascular disease biomarkers in human plasma

A highly‐multiplexed MRM‐based assay for determination of cardiovascular disease (CVD) status and disease classification has been developed for clinical research. A high‐flow system using ultra‐high performance LC and an Agilent 6490 triple quadrupole mass spectrometer, equipped with an ion funnel, provided ease of use and increased the robustness of the assay. The assay uses 135 stable isotope‐labeled peptide standards for the quantitation of 67 putative biomarkers of CVD in tryptic digests of whole plasma in a 30‐min assay. Eighty‐five analyses of the same sample showed no loss of sensitivity (<20% CV for 134/135 peptides) and no loss of retention time accuracy (<0.5% CV for all peptides). The maximum linear dynamic range of the MRM assays ranged from 103–105 for 106 of the assays. Excellent linear responses (r >0.98) were obtained for 117 of the 135 peptide targets with attomole level limits of quantitation (<20% CV and accuracy 80–120%) for 81 of the 135 peptides. The assay presented in this study is easy to use, robust, sensitive, and has high‐throughput capabilities through short analysis time and complete automated sample preparation. It is therefore well suited for CVD biomarker validation and discovery in plasma.

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 ≥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 β2-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.

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.

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.

Multiple Reaction Monitoring (MRM): Principles and Application to Coronary Artery Disease

We previously reported on a method for the quantitative analysis of the 45 most abundant plasma proteins, based on liquid chromatography MRM/mass spectrometry, with quantitation accuracy provided by the use of stable isotopically labeled standard peptides. In this paper, we describe the use of this MRM method for the discovery of biomarkers characteristic of the presence or absence of coronary artery disease. Quantitative analysis of peptides specific for 44 of these abundant proteins was performed on plasma from a group of 38 patients classified as coronary artery disease-positive or coronary artery disease-negative. Statistical analysis of the results resulted in the discovery of a panel of 5 proteins with discriminative concentrations between patients with and without coronary artery disease, with a P value of <0.05. An initial evaluation of the analytic pipeline by cross-validation resulted in an estimated sensitivity and specificity of 74% for the test samples. This demonstrates that MRM-mass spectrometry-based quantitation offers a potential methodology for both biomarker discovery and biomarker validation. Similar to other discovery methodologies (eg, isobaric tags for relative and absolute quantitation), MRM-mass spectrometry provides the sensitivity and accuracy needed in the discovery phase, but, unlike the others, MRM-mass spectrometry offers the high throughput needed for clinical validation. Thus, this advantage eliminates the need for the development and validation of different discovery and clinical validation methods. ### Mass Spectrometry Mass spectrometry (MS) is an analytical chemistry technique based on the determination of the mass (actually, the mass-to-charge ratio) of an analyte ion. This analyte can be fragmented inside the mass spectrometer, which is under vacuum, to give charged product ions. This process is known as collision-induced dissociation . The masses of the fragment ions can then be determined in a second stage of MS, giving rise to the terms MS/MS or tandem mass spectrometry (see Figure 1a). Because …

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.

Diagnostic Performance of High-Definition Coronary Computed Tomography Angiography Performed With Multiple Radiation Dose Reduction Strategies

BACKGROUND Numerous radiation dose reduction measures have been proposed for coronary computed tomographic angiography (CCTA). Although these techniques allow for imaging with reduced radiation, it is unknown whether diagnostic performance is maintained. A new high-definition CCTA (HD-CCTA) allows higher spatial resolution, reduced image noise, and lower radiation doses. OBJECTIVES The aim of this study was to determine the diagnostic performance of HD-CCTA, in combination with multiple radiation dose reduction strategies, for the detection of obstructive coronary artery disease. METHODS Consecutive patients (N = 43, aged 60 ± 10 years, 83% male) with chest pain and referred for quantitative coronary angiography (QCA) underwent HD-CCTA with radiation dose reduction measures, including prospective electrocardiographic triggering, reduction of additional tube on-time, and minimization of tube voltage and current. Intraluminal diameter stenosis ≥ 50% was considered significant. QCA served as the reference standard. The area under the receiver-operating-characteristic curve (AUC) was used to evaluate diagnostic accuracy. RESULTS All scans demonstrated diagnostic image quality, with 99% (543/548) of included coronary segments interpretable by HD-CCTA. Median effective radiation dose was 2.8 mSv (interquartile range, 1.3-3.9). The AUC for the per-patient assessment for stenosis ≥ 50% was 0.90 (95% confidence interval [CI], 0.77-0.96), with sensitivity of 95% (95% CI, 85%-100%), specificity of 79% (95% CI, 63%-95%), positive predictive value of 78% (95% CI, 61%-95%), and negative predictive value of 95% (95% CI, 85%-100%). CONCLUSIONS Compared with QCA, HD-CCTA with multiple dose reduction measures resulted in low radiation doses and high diagnostic accuracy to detect and exclude obstructive coronary artery disease.

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.

Plasma proteomics can discriminate isolated early from dual responses in asthmatic individuals undergoing an allergen inhalation challenge.

This proteomics study was designed to determine the utility of iTRAQ MALDI‐TOF/TOF technology to compare plasma samples from carefully phenotyped mild, atopic asthma subjects undergoing allergen inhalation challenge.