蛋白质组学分析在肥厚型心肌病生物标志物发现中的应用。
Application of Proteomics Profiling for Biomarker Discovery in Hypertrophic Cardiomyopathy.
机构信息
Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Division of Cardiology, Department of Medicine, Columbia University Medical Center, 622 West 168th Street, PH 3-342, New York, NY, 10032, USA.
出版信息
J Cardiovasc Transl Res. 2019 Dec;12(6):569-579. doi: 10.1007/s12265-019-09896-z. Epub 2019 Jul 5.
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.
高通量蛋白质组学分析从未应用于发现肥厚型心肌病（HCM）患者的生物标志物。本研究旨在确定可区分 HCM 与对照的血浆蛋白生物标志物。我们进行了一项 HCM 患者（n=15）和对照组（n=22）的病例对照研究。我们使用 SOMAscan 测定法对 1129 种蛋白质进行了血浆蛋白质组学分析。我们使用稀疏偏最小二乘判别分析来识别 50 种最具判别力的蛋白质。我们还使用带有平衡子采样的蒙特卡罗交叉验证来确定接受者操作特征曲线的曲线下面积（AUC）。平均 AUC 为 0.94（95%置信区间，0.82-1.00），判别准确率为 89%。在 HCM 中，50 种蛋白质中有 13 种与肌钙蛋白 I 相关，12 种与纽约心脏协会（NYHA）分级相关。蛋白质组学分析可用于阐明可区分 HCM 与对照的蛋白质生物标志物。
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