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通过定量蛋白质组学发现预测冠状动脉粥样硬化严重程度的血浆生物标志物。

Discovery of plasma biomarkers for predicting the severity of coronary artery atherosclerosis by quantitative proteomics.

作者信息

Ku Eu Jeong, Cho Kyung-Cho, Lim Cheong, Kang Jeong Won, Oh Jae Won, Choi Yu Ri, Park Jong-Moon, Han Na-Young, Oh Jong Jin, Oh Tae Jung, Jang Hak Chul, Lee Hookeun, Kim Kwang Pyo, Choi Sung Hee

机构信息

Internal Medicine, Chungbuk National University Hospital, Cheongju, South Korea.

Internal Medicine, Chungbuk National University College of Medicine, Cheongju, South Korea.

出版信息

BMJ Open Diabetes Res Care. 2020 Apr;8(1). doi: 10.1136/bmjdrc-2019-001152.

Abstract

INTRODUCTION

Cardiovascular disease (CVD) in patients with diabetes is the leading cause of death. Finding early biomarkers for detecting asymptomatic patients with CVD can improve survival. Recently, plasma proteomics-targeted selected reaction monitoring/multiple reaction monitoring analyses (MRM)-has emerged as highly specific and sensitive tools compared with classic ELISA methods. The objective was to identify differentially regulated proteins according to the severity of the coronary artery atherosclerosis.

RESEARCH DESIGN AND METHODS

A discovery cohort, a verification cohort and a validation cohort consisted of 18, 53, and 228 subjects, respectively. The grade of coronary artery stenosis was defined as a percentage of luminal stenosis of the major coronary arteries. Participants were divided into six groups, depending on the presence of diabetes and the grade of coronary artery stenosis. Two mass spectrometric approaches were employed: (1) conventional shotgun liquid chromatography tandem mass spectrometry for a discovery and (2) quantitative MRM for verification and validation. An analysis of the covariance was used to examine the biomarkers' predictivity beyond conventional cardiovascular risks.

RESULTS

A total of 1349 different proteins were identified from a discovery cohort. We selected 52 proteins based on the tandem mass tag quantitative analysis then summarized as follows: chemokine (C-X-C motif) ligand 7 (CXCL7), apolipoprotein C-II (APOC2), human lipopolysaccharide-binding protein (LBP) and dedicator of cytokinesis 2 (DOCK2) in diabetes; CXCL7, APOC2, LBP, complement 4A (C4A), vitamin D-binding protein (VTDB) and laminin β1 subunit in non-diabetes. Analysis of covariance showed that APOC2, DOCK2, CXCL7 and VTDB were upregulated and C4A was downregulated in patients with diabetes showing severe coronary artery stenosis. LBP and VTDB were downregulated in patients without diabetes, showing severe coronary artery stenosis.

CONCLUSION

We identified significant associations between circulating APOC2, C4A, CXCL7, DOCK2, LBP and VTDB levels and the degree of coronary artery stenosis using the MRM technique.

摘要

引言

糖尿病患者的心血管疾病(CVD)是主要死因。寻找用于检测无症状CVD患者的早期生物标志物可提高生存率。最近,与经典酶联免疫吸附测定(ELISA)方法相比,血浆蛋白质组学靶向选择反应监测/多反应监测分析(MRM)已成为高度特异性和灵敏的工具。目的是根据冠状动脉粥样硬化的严重程度鉴定差异调节的蛋白质。

研究设计与方法

一个发现队列、一个验证队列和一个确认队列分别由18、53和228名受试者组成。冠状动脉狭窄程度定义为主要冠状动脉管腔狭窄的百分比。参与者根据糖尿病的存在情况和冠状动脉狭窄程度分为六组。采用了两种质谱方法:(1)用于发现的传统鸟枪法液相色谱串联质谱法,以及(2)用于验证和确认的定量MRM。使用协方差分析来检验生物标志物超出传统心血管风险的预测能力。

结果

从发现队列中总共鉴定出1349种不同的蛋白质。我们基于串联质量标签定量分析选择了52种蛋白质,总结如下:糖尿病患者中的趋化因子(C-X-C基序)配体7(CXCL7)、载脂蛋白C-II(APOC2)、人脂多糖结合蛋白(LBP)和胞质分裂 dedicator 2(DOCK2);非糖尿病患者中的CXCL7、APOC2、LBP、补体4A(C4A)、维生素D结合蛋白(VTDB)和层粘连蛋白β1亚基。协方差分析表明,在患有严重冠状动脉狭窄的糖尿病患者中,APOC2、DOCK2、CXCL7和VTDB上调,C4A下调。在没有糖尿病且患有严重冠状动脉狭窄的患者中,LBP和VTDB下调。

结论

我们使用MRM技术确定了循环中APOC2、C4A、CXCL7、DOCK2、LBP和VTDB水平与冠状动脉狭窄程度之间的显著关联。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5ce5/7202779/e33930c17511/bmjdrc-2019-001152f01.jpg

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