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Introduction Cardiac arrhythmia is strongly linked with heart failure (HF) and a primary cause of stroke. The condition affects around 37,000 people in Northern Ireland although it is estimated that many thousands more remain undiagnosed. It is important to be able to diagnose cardiac arrhythmia early, so that appropriate interventions can be made to reduce risk of subsequent stroke or HF. Currently, diagnosis and management of cardiac arrhythmia is reliant on assessment of clinical risk factors, however, routine monitoring of circulating biomarkers would significantly improve accuracy for prediction of arrhythmia and associated adverse events. The aim of this study was to (i) identify protein biomarkers, which can predict cardiac arrhythmia and (ii) identify protein biomarkers that are predictive of HF in patients with arrhythmia. Methods Multiple Reaction Monitoring mass spectrometry-based assays were developed for measurement of a selection of candidate protein biomarkers of cardiovascular injury. Assays were developed using nanoflow reverse phase C18 chromatographic ChipCube based separation, coupled to an Agilent 6460 triple quadrupole mass spectrometer. Optimised MRM assays were applied, in a sample blinded manner, for analysis of a cohort of 410 serum samples. This included 112 patients with cardiac arrhythmia as well as matched controls without cardiac arrhythmia. Results MRM assays were established for measurement of 25 proteins. Individually, a number of the biomarker proteins show significant differential expression between patients with and without cardiac arrhythmia. An 11-protein biomarker model was identified, which was comparable to BNP in prediction of HF within the cardiac arrhythmia subset of patients (Protein panel AUC = 0.856 vs BNP AUC = 0.838). Combination of the 11 proteins with BNP notably enhanced the predictive capacity of BNP (AUC = 0.898). Conclusions/Implications Through this study, assays have been developed for robust, multiplexed measurement of 25 cardiovascular disease-associated proteins in patient serum samples. A number of proteins were identified, which show significant expression changes in association with cardiac arrhythmia and will be further explored. Importantly, a statistical model revealed a panel of 11 proteins, which can predict HF in patients with cardiac arrhythmia, with comparable accuracy to BNP. This panel will need to be further validated in independent patient cohorts.

Background Advances in cancer therapy have significantly improved long term survival rates of those with breast cancer. Concurrently, chemotherapy-induced cardiac dysfunction is receiving increased attention in breast cancer survivors. Reduced left ventricular systolic function related to cancer therapies has recently been designated cancer therapeutics-related cardiac dysfunction (CTRCD). The addition of Trastuzumab to Epirubicin treatment has been shown to slow progression of disease, reduce mortality and extend duration of survival in patients with HER2+ Breast Cancer. However, both drugs have off target cardiotoxic effects. Currently echocardiography is the standard diagnostic test for detecting left ventricular systolic dysfunction in patients receiving these agents, but often becomes abnormal only when significant irreversible cardiac damage has occurred. There is an emerging need for blood-based biomarkers to aid in diagnosing subclinical cardiac dysfunction and to stratify those at risk prior to therapy. Methods AC16 cardiomyocytes were treated with Epirubicin (26ug/ml) and Trastuzumab (150ug/ml), both together and in monotherapy, over 10hr and 26hr studies. Cell viability was assessed via MTT cell viability assay. Protein and gene expression of Troponin I and BNP were assessed via western blot analysis and RT-PCR. Western blot analysis and fluorescent microscopy staining of oxidative stress markers was also carried out to investigate potential mechanisms of cardiac damage. Results Morphological changes occurred in all cells treated over 26hrs, particularly with combined treatment. Cell viability decreased significantly compared to control in the combined treatment group over 26hrs (p 0.0126*). Troponin I expression also increased significantly in the combined treatment group compared to monotreatment with Epirubicin for the same timepoint (p 0.015). BNP levels significantly increased in cells treated with a combination of Epirubicin and Trastuzumab compared to Trastuzumab alone (p=0.023). Conclusion Combined treatment with Epirubicin and Trastuzumab produces significantly more cell damage than monotreatment with either therapy. Troponin I and BNP are biomarkers that should be explored as a diagnostic tool for prediction of subclinical CTRCD.

Brief introduction Almost half of all deaths in Europe are attributable to by Cardiovascular Disease (CVD). There is a critical unmet need for better biomarkers so that CVD can be diagnosed at an earlier stage and with greater accuracy. Mass spectrometry-based multiple reaction monitoring (MRM) allows for rapid, targeted measurement of multiple protein biomarkers via detection of ‘proteotypic’ peptide fragments. Such assays can be developed in blood samples, which is desirable for minimally-invasive, routine monitoring of cardiovascular health. The purpose of this study was to design a robust MRM-based assay for the simultaneous detection and measurement of a panel of 36 proteins, including 19 known and 17 novel protein biomarkers of CVD, in blood. The overall aim was to evaluate the potential clinical utility of this biomarker panel for prediction of heart failure in a cohort of 500 patients. Explanation of basic methods Proteotypic peptides for each of the 36 candidate biomarker proteins were identified using Skyline and Spectrum Mill PeptideSelector software. MRM assays were developed using nanoflow reverse phase C18 chromatographic ChipCube based separation, coupled to a 6460 triple quadrupole mass spectrometer. Patient samples and synthetic peptides were used to obtain reference MS/MS spectra for building high quality MRM assays. For initial verification of the candidate protein biomarker panel, the MRM assay was applied, in a sample blinded manner, to a cohort of 500 serum samples from patients with heart failure and age-matched non-heart failure controls with CVD risk-factors. Results MRM assays were established for 35 peptides, corresponding to 9 of the known candidate biomarker proteins and all 16 of the novel biomarkers (Table 1). Individually, a number of the biomarker proteins show differential expression between heart failure with preserved and reduced ejection fraction (Table 2). Combined measurement of all biomarker proteins was found to have greater predictive capacity for heart failure than the current gold standard of B-type natriuretic peptide (BNP) alone. A statistical mode found that the biomarker panel, combined with BNP was capable of correctly predicting heart failure in blinded patient samples with accuracy of 82.19% AUC of 0.89 (Figure 1). Conclusions/Implications Through this study, assays have been developed for robust, multiplexed measurement of 26 CVD biomarker proteins in patient serum samples. Here it was observed that measurement of the full panel of CVD protein biomarkers offers more accurate prediction of heart failure than measurement of BNP alone. This panel will need to be further validated in independent patient cohorts. Conflict of interest None

Introduction The need for biomarkers to identify cardiac dysfunction in patients with diabetes (DM) is becoming increasingly pressing due to the global rise in disease prevalence and reducing healthcare resources to detect and manage these complications. With the risk of heart failure being 2–5 fold greater in those with diabetes, early identification of cardiac dysfunction may facilitate more timely management and reduce or delay future heart failure development. The aim of this ongoing study is to identify serum protein and micro RNA (miRNA) biomarker signatures that can be used to diagnose asymptomatic left ventricular diastolic dysfunction (LVDD) in diabetic patients. Methods The biomarker discovery cohort consisted of a selected subset of 200 patients from within the STOP-HF population. Four pooled age- and gender-matched groups of 50 patients were analysed, with and without DM and with and without asymptomatic LVDD. LVDD was defined on echocardiography as left atrial volume index ≥34 ml/m2 and E’ Results The proteomics and miRNA discovery analysis identified over 70 potential biomarkers that were differentially expressed in patients with both diabetes and LVDD compared with the other three discovery groups. GO-Term enrichment analysis revealed a significant involvement of processes relating to inflammation, including Humoral immune response, Complement activation, and Acute inflammatory responses (q-values: 1.00 E-30, 1.00 E-30, 1.00 E-30 respectively). Conclusion Verification and validation of the diagnostic potential of these novel protein and miRNA biomarkers candidates may support future strategies for the early identification and monitoring of LVDD in diabetic populations. Furthermore, functional analysis and identification of disease relevance of these biomarkers could highlight new therapeutic targets, including novel anti-inflammatory approaches.