Zsuzsanna Hollander

The Human Serum Metabolome

Continuing improvements in analytical technology along with an increased interest in performing comprehensive, quantitative metabolic profiling, is leading to increased interest pressures within the metabolomics community to develop centralized metabolite reference resources for certain clinically important biofluids, such as cerebrospinal fluid, urine and blood. As part of an ongoing effort to systematically characterize the human metabolome through the Human Metabolome Project, we have undertaken the task of characterizing the human serum metabolome. In doing so, we have combined targeted and non-targeted NMR, GC-MS and LC-MS methods with computer-aided literature mining to identify and quantify a comprehensive, if not absolutely complete, set of metabolites commonly detected and quantified (with todays technology) in the human serum metabolome. Our use of multiple metabolomics platforms and technologies allowed us to substantially enhance the level of metabolome coverage while critically assessing the relative strengths and weaknesses of these platforms or technologies. Tables containing the complete set of 4229 confirmed and highly probable human serum compounds, their concentrations, related literature references and links to their known disease associations are freely available at http://www.serummetabolome.ca.

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.

Ten-Year Trends in Direct Costs of COPD: A Population-Based Study

BACKGROUND Up-to-date estimates of burden of diseases are required for evidence-based decision-making. The objectives of this study were to determine the excess costs of COPD and its trend from 2001 to 2010 in British Columbia, Canada. METHODS We used British Columbias administrative health data to construct a cohort of patients with COPD and a matched comparison cohort of subjects without COPD. We followed each patient from the time of first COPD-related health-care event (or equivalent time for the comparison cohort). Direct medical costs (in 2010 Canadian dollars [

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

]) were calculated based on billing records pertaining to hospital admissions, outpatient services use, medication dispensations, and community care services. We determined the excess medical costs of COPD by calculating the difference in overall medical costs between the COPD and the comparison cohorts. RESULTS The COPD and comparison cohorts comprised 153,570 and 246,801 people, respectively (for both cohorts, mean age at entry was 66.9 years; 47.2% female patients). The excess costs of COPD during the study period were

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

5,452 per patient-year. Inpatient, outpatient, medication, and community care costs were responsible for 57%, 16%, 22%, and 5% of the excess costs, respectively. Excess costs increased by

Biomarker Development for Chronic Obstructive Pulmonary Disease. From Discovery to Clinical Implementation

296/person-y (P < .01), with hospital costs demonstrating the largest increase over time (

Gender‐specific plasma proteomic biomarkers in patients with Anderson–Fabry disease

258/person-y; P < .01). CONCLUSIONS The direct economic burden of COPD is high and has increased significantly between 2001 and 2010 over and above the increase in the health-care costs of the general population. Further investigation is required to elucidate the underlying reasons for the temporal increase in COPD direct costs.

The Projected Epidemic of COPD Hospitalizations Over the Next 15 Years: A Population Based Perspective

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.