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Identification of a Multiplex Biomarker Panel for Hypertrophic Cardiomyopathy using Quantitative Proteomics and Machine Learning

Captur, G; Heywood, WE; Coats, C; Rosmini, S; Patel, V; Lopes, LR; Collis, R; ... Mills, K; + view all (2020) Identification of a Multiplex Biomarker Panel for Hypertrophic Cardiomyopathy using Quantitative Proteomics and Machine Learning. Molecular & Cellular Proteomics , 19 (1) pp. 114-127. 10.1074/mcp.RA119.001586. Green open access

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Abstract

Hypertrophic cardiomyopathy (HCM) is defined by pathological left ventricular hypertrophy (LVH). It is the commonest inherited cardiac condition and a significant number of high risk cases still go undetected until a sudden cardiac death (SCD) event. Plasma biomarkers do not currently feature in the assessment of HCM disease progression, which is tracked by serial imaging, or in SCD risk stratification which is based on imaging parameters and patient/family history. There is a need for new HCM plasma biomarkers to refine disease monitoring and improve patient risk stratification. To identify new plasma biomarkers for patients with HCM, we performed exploratory myocardial and plasma proteomics screens and subsequently developed a multiplexed targeted liquid chromatography-tandem/mass spectrometry-based assay to validate the 26 peptide biomarkers that were identified. The association of discovered biomarkers with clinical phenotypes was prospectively tested in plasma from 110 HCM patients with LVH (LVH+ HCM), 97 controls and 16 HCM sarcomere gene mutation carriers before the development of LVH (subclinical HCM). Six peptides (Aldolase Fructose-Bisphosphate A, Complement C3, Glutathione S-Transferase Omega 1, Ras Suppressor Protein 1, Talin 1, and Thrombospondin 1) were increased significantly in the plasma of LVH+ HCM compared to controls and correlated with imaging markers of phenotype severity: LV wall thickness, mass and % myocardial scar on cardiovascular magnetic resonance imaging. Using supervised machine learning, this six-biomarker panel differentiated between LVH+ HCM and controls, with an area under the curve of ≥0.87. Five of these peptides were also significantly increased in subclinical HCM compared to controls. In LVH+ HCM, the 6-marker panel correlated with the presence of non-sustained ventricular tachycardia and the estimated 5-year risk of sudden cardiac death. Using quantitative proteomic approaches, we have discovered six potentially useful circulating plasma biomarkers related to myocardial substrate changes in HCM, which correlate with the estimated sudden cardiac death risk.

Type: Article
Title: Identification of a Multiplex Biomarker Panel for Hypertrophic Cardiomyopathy using Quantitative Proteomics and Machine Learning
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1074/mcp.RA119.001586
Publisher version: https://doi.org/10.1074/mcp.RA119.001586
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Cardiovascular disease, Cardiovascular function or biology, Diagnostic, Mass Spectrometry, Multiple reaction monitoring
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science > Clinical Science
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science > Population Science and Experimental Medicine
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science > Population Science and Experimental Medicine > MRC Unit for Lifelong Hlth and Ageing
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health > Genetics and Genomic Medicine Dept
URI: https://discovery.ucl.ac.uk/id/eprint/10077188
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