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Application of Proteomics Profiling for Biomarker Discovery in Hypertrophic Cardiomyopathy.


ABSTRACT: High-throughput proteomics profiling has never been applied to discover biomarkers in patients with hypertrophic cardiomyopathy (HCM). The objective was to identify plasma protein biomarkers that can distinguish HCM from controls. We performed a case-control study of patients with HCM (n?=?15) and controls (n?=?22). We carried out plasma proteomics profiling of 1129 proteins using the SOMAscan assay. We used the sparse partial least squares discriminant analysis to identify 50 most discriminant proteins. We also determined the area under the curve (AUC) of the receiver operating characteristic curve using the Monte Carlo cross validation with balanced subsampling. The average AUC was 0.94 (95% confidence interval, 0.82-1.00) and the discriminative accuracy was 89%. In HCM, 13 out of the 50 proteins correlated with troponin I and 12 with New York Heart Association class. Proteomics profiling can be used to elucidate protein biomarkers that distinguish HCM from controls.

SUBMITTER: Shimada YJ 

PROVIDER: S-EPMC7102897 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Application of Proteomics Profiling for Biomarker Discovery in Hypertrophic Cardiomyopathy.

Shimada Yuichi J YJ   Hasegawa Kohei K   Kochav Stephanie M SM   Mohajer Pouya P   Jung Jeeyoun J   Maurer Mathew S MS   Reilly Muredach P MP   Fifer Michael A MA  

Journal of cardiovascular translational research 20190705 6


High-throughput proteomics profiling has never been applied to discover biomarkers in patients with hypertrophic cardiomyopathy (HCM). The objective was to identify plasma protein biomarkers that can distinguish HCM from controls. We performed a case-control study of patients with HCM (n = 15) and controls (n = 22). We carried out plasma proteomics profiling of 1129 proteins using the SOMAscan assay. We used the sparse partial least squares discriminant analysis to identify 50 most discriminant  ...[more]

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