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

Captur, Gabriella; Heywood, Wendy; Coats, Caroline; Rosmini, Stefania; Patel, Vimal; Lopes, Luís Rocha; Collis, Richard; Patel, Nina; Syrris, Petros; Bassett, Paul; O’Brien, Ben; Moon, James; Elliott, Perry; Mills, Kevin

doi:10.1074/mcp.ra119.001586

Cited by 41 publications

(36 citation statements)

References 64 publications

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“…Inflammation is involved in cardiac remodeling and activation of complement cascade accompanies cardiovascular disturbances both in humans and rodents ( 96 , 97 ). C3 level has been shown to be elevated in serum of patients with left ventricular hypertrophy ( 98 ), in hypertensive patients ( 99 ) and more recently was recognized as a marker of hypertrophic cardiomyopathy ( 100 ). However we could not point at the immune proteins as biomarkers for monitoring the cardiac recovery because we observed upregulation of complement cascade proteins in cardiac muscle but not in the plasma.…”

Section: Discussionmentioning

confidence: 99%

Proteomic and Structural Manifestations of Cardiomyopathy in Rat Models of Obesity and Weight Loss

et al. 2021

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Obesity cardiomyopathy increases the risk of heart failure and death. Obesity is curable, leading to the restoration of the heart phenotype, but it is not clear if there are any after-effects of obesity present after weight loss. We characterize the proteomic landscape of obesity cardiomyopathy with an evaluation of whether the cardiac phenotype is still shaped after weight loss. Cardiomyopathy was validated by cardiac hypertrophy, fibrosis, oversized myocytes, and mTOR upregulation in a rat model of cafeteria diet-induced developmental obesity. By global proteomic techniques (LC-MS/MS) a plethora of molecular changes was observed in the heart and circulation of obese animals, suggesting abnormal utilization of metabolic substrates. This was confirmed by increased levels of cardiac ACSL-1, a key enzyme for fatty acid degradation and decreased GLUT-1, a glucose transporter in obese rats. Calorie restriction and weight loss led to the normalization of the heart’s size, but fibrosis was still excessive. The proteomic compositions of cardiac tissue and plasma were different after weight loss as compared to control. In addition to morphological consequences, obesity cardiomyopathy involves many proteomic changes. Weight loss provides for a partial repair of the heart’s architecture, but the trace of fibrotic deposition and proteomic alterations may occur.

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Section: Discussionmentioning

confidence: 99%

Proteomic and Structural Manifestations of Cardiomyopathy in Rat Models of Obesity and Weight Loss

et al. 2021

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“…Hypertrophic cardiomyopathy (HCM), an inheritable condition characterized by myocardial hypertrophy without systemic etiology, increases the risk of heart failure, stroke, and SCD (Captur et al, 2020 ). HCM is reported in pathologic registries as one of the most common causes of SCD in youth athletes (Rasmusen and Schmied, 2020 ), and HCM has been shown to be the most common cardiomyopathy in elite soccer players (Malhotra et al, 2018 ).…”

Section: Five Parameters Measured By Wearable Sensors To Minimize Injmentioning

confidence: 99%

Wearable Technology and Analytics as a Complementary Toolkit to Optimize Workload and to Reduce Injury Burden

Seshadri¹,

Thom²,

Harlow³

et al. 2021

Front. Sports Act. Living

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Wearable sensors enable the real-time and non-invasive monitoring of biomechanical, physiological, or biochemical parameters pertinent to the performance of athletes. Sports medicine researchers compile datasets involving a multitude of parameters that can often be time consuming to analyze in order to create value in an expeditious and accurate manner. Machine learning and artificial intelligence models may aid in the clinical decision-making process for sports scientists, team physicians, and athletic trainers in translating the data acquired from wearable sensors to accurately and efficiently make decisions regarding the health, safety, and performance of athletes. This narrative review discusses the application of commercial sensors utilized by sports teams today and the emergence of descriptive analytics to monitor the internal and external workload, hydration status, sleep, cardiovascular health, and return-to-sport status of athletes. This review is written for those who are interested in the application of wearable sensor data and data science to enhance performance and reduce injury burden in athletes of all ages.

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“…Identifying the specific mutation in a patient and the family can greatly facilitate determining the prognosis and most appropriate management because hypertrophic cardiomyopathy is a heterogeneous group of diseases, not a single disease. Genetic testing for this purpose is rapidly improving with advances in whole genome sequencing, proteomics and machine learning 1 , 10 , 11. The improving diagnostic techniques and treatment modalities have implications for screening families.…”

Section: Discussionmentioning

confidence: 99%

Hypertrophic cardiomyopathy masked by pericarditis

Nichols¹,

Koelmeyer²

2019

Autops. Case Rep.

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Hypertrophic cardiomyopathy used to be regarded as a rare untreatable cause of sudden death in young male athletes. This report is the case of a middle-aged female patient with hereditary hypertrophic cardiomyopathy masked by superimposed pericarditis and revealed by autopsy. This case report illustrates how co-morbidity can hide a crucial diagnosis. This case report also illustrates the value of autopsy disclosing a familial disease that is increasingly recognized and dramatically more treatable than a few decades ago. Sudden death due to hypertrophic cardiomyopathy has become preventable, if the diagnosis is made soon enough. The lessons for patient care from this case include the importance of not missing the diagnosis of hypertrophic cardiomyopathy in female patients.

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

Cited by 41 publications

References 64 publications

Proteomic and Structural Manifestations of Cardiomyopathy in Rat Models of Obesity and Weight Loss

Proteomic and Structural Manifestations of Cardiomyopathy in Rat Models of Obesity and Weight Loss

Wearable Technology and Analytics as a Complementary Toolkit to Optimize Workload and to Reduce Injury Burden

Hypertrophic cardiomyopathy masked by pericarditis

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