PDF(Pubmed)
Abstract：
UNASSIGNED: Hypertrophic cardiomyopathy (HCM) is defined clinically by pathological left ventricular hypertrophy. We have previously developed a plasma proteomics biomarker panel that correlates with clinical markers of disease severity and sudden cardiac death risk in adult patients with HCM. The aim of this study was to investigate the utility of adult biomarkers and perform new discoveries in proteomics for childhood-onset HCM.
UNASSIGNED: Fifty-nine protein biomarkers were identified from an exploratory plasma proteomics screen in children with HCM and augmented into our existing multiplexed targeted liquid chromatography-tandem/mass spectrometry-based assay. The association of these biomarkers with clinical phenotypes and outcomes was prospectively tested in plasma collected from 148 children with HCM and 50 healthy controls. Machine learning techniques were used to develop novel pediatric plasma proteomic biomarker panels.
UNASSIGNED: Four previously identified adult HCM markers (aldolase fructose-bisphosphate A, complement C3a, talin-1, and thrombospondin 1) and 3 new markers (glycogen phosphorylase B, lipoprotein a and profilin 1) were elevated in pediatric HCM. Using supervised machine learning applied to training (n=137) and validation cohorts (n=61), this 7-biomarker panel differentiated HCM from healthy controls with an area under the curve of 1.0 in the training data set (sensitivity 100% [95% CI, 95-100]; specificity 100% [95% CI, 96-100]) and 0.82 in the validation data set (sensitivity 75% [95% CI, 59-86]; specificity 88% [95% CI, 75-94]). Reduced circulating levels of 4 other peptides (apolipoprotein L1, complement 5b, immunoglobulin heavy constant epsilon, and serum amyloid A4) found in children with high sudden cardiac death risk provided complete separation from the low and intermediate risk groups and predicted mortality and adverse arrhythmic outcomes (hazard ratio, 2.04 [95% CI, 1.0-4.2]; P=0.044).
UNASSIGNED: In children, a 7-biomarker proteomics panel can distinguish HCM from controls with high sensitivity and specificity, and another 4-biomarker panel identifies those at high risk of adverse arrhythmic outcomes, including sudden cardiac death.
UNASSIGNED: Fifty-nine protein biomarkers were identified from an exploratory plasma proteomics screen in children with HCM and augmented into our existing multiplexed targeted liquid chromatography-tandem/mass spectrometry-based assay. The association of these biomarkers with clinical phenotypes and outcomes was prospectively tested in plasma collected from 148 children with HCM and 50 healthy controls. Machine learning techniques were used to develop novel pediatric plasma proteomic biomarker panels.
UNASSIGNED: Four previously identified adult HCM markers (aldolase fructose-bisphosphate A, complement C3a, talin-1, and thrombospondin 1) and 3 new markers (glycogen phosphorylase B, lipoprotein a and profilin 1) were elevated in pediatric HCM. Using supervised machine learning applied to training (n=137) and validation cohorts (n=61), this 7-biomarker panel differentiated HCM from healthy controls with an area under the curve of 1.0 in the training data set (sensitivity 100% [95% CI, 95-100]; specificity 100% [95% CI, 96-100]) and 0.82 in the validation data set (sensitivity 75% [95% CI, 59-86]; specificity 88% [95% CI, 75-94]). Reduced circulating levels of 4 other peptides (apolipoprotein L1, complement 5b, immunoglobulin heavy constant epsilon, and serum amyloid A4) found in children with high sudden cardiac death risk provided complete separation from the low and intermediate risk groups and predicted mortality and adverse arrhythmic outcomes (hazard ratio, 2.04 [95% CI, 1.0-4.2]; P=0.044).
UNASSIGNED: In children, a 7-biomarker proteomics panel can distinguish HCM from controls with high sensitivity and specificity, and another 4-biomarker panel identifies those at high risk of adverse arrhythmic outcomes, including sudden cardiac death.
摘要：
■肥厚型心肌病（HCM）在临床上由病理性左心室肥大定义。我们先前已经开发了血浆蛋白质组学生物标志物组,其与患有HCM的成年患者的疾病严重程度和心源性猝死风险的临床标志物相关。这项研究的目的是研究成人生物标志物的实用性，并在儿童期发病的HCM中进行蛋白质组学的新发现。
■在患有HCM的儿童中，从探索性血浆蛋白质组学筛选中鉴定出了59种蛋白质生物标志物，并扩展到我们现有的基于多重靶向液相色谱-串联/质谱的测定中。在148名HCM儿童和50名健康对照者的血浆中前瞻性地测试了这些生物标志物与临床表型和结果的关联。机器学习技术用于开发新的儿科血浆蛋白质组生物标志物组。
■四个先前鉴定的成年HCM标记（醛缩酶果糖-二磷酸A，补体C3a,talin-1和血小板反应蛋白1)和3种新标志物(糖原磷酸化酶B，脂蛋白a,和profilin1）在小儿HCM中升高。使用监督机器学习应用于训练(n=137)和验证队列(n=61)，该7个生物标志物组将HCM与健康对照区分开来,训练数据集的曲线下面积为1.0(灵敏度100%[95%CI,95-100];特异性100%[95%CI,96-100]),验证数据集的曲线下面积为0.82(灵敏度75%[95%CI,59-86];特异性88%[95%CI,75-94]).4种其他肽的循环水平降低（载脂蛋白L1，补体5b，免疫球蛋白重恒定ε，和血清淀粉样蛋白A4肽）在心脏性猝死风险高的儿童中发现，与低风险和中风险组完全分离，并预测死亡率和不良心律失常结果（风险比，2.04[95%CI，1.0-4.2]；P=0.044）。
■在儿童中，一个7个生物标志物蛋白质组学小组可以区分HCM与对照，具有高灵敏度和特异性，第二个4个生物标志物小组确定了那些处于不良心律失常结果高风险的人，包括心脏性猝死.
■在患有HCM的儿童中，从探索性血浆蛋白质组学筛选中鉴定出了59种蛋白质生物标志物，并扩展到我们现有的基于多重靶向液相色谱-串联/质谱的测定中。在148名HCM儿童和50名健康对照者的血浆中前瞻性地测试了这些生物标志物与临床表型和结果的关联。机器学习技术用于开发新的儿科血浆蛋白质组生物标志物组。
■四个先前鉴定的成年HCM标记（醛缩酶果糖-二磷酸A，补体C3a,talin-1和血小板反应蛋白1)和3种新标志物(糖原磷酸化酶B，脂蛋白a,和profilin1）在小儿HCM中升高。使用监督机器学习应用于训练(n=137)和验证队列(n=61)，该7个生物标志物组将HCM与健康对照区分开来,训练数据集的曲线下面积为1.0(灵敏度100%[95%CI,95-100];特异性100%[95%CI,96-100]),验证数据集的曲线下面积为0.82(灵敏度75%[95%CI,59-86];特异性88%[95%CI,75-94]).4种其他肽的循环水平降低（载脂蛋白L1，补体5b，免疫球蛋白重恒定ε，和血清淀粉样蛋白A4肽）在心脏性猝死风险高的儿童中发现，与低风险和中风险组完全分离，并预测死亡率和不良心律失常结果（风险比，2.04[95%CI，1.0-4.2]；P=0.044）。
■在儿童中，一个7个生物标志物蛋白质组学小组可以区分HCM与对照，具有高灵敏度和特异性，第二个4个生物标志物小组确定了那些处于不良心律失常结果高风险的人，包括心脏性猝死.
