Discovery of plasma biomarkers for predicting the severity of coronary artery atherosclerosis by quantitative proteomics. Issue 1 (22nd April 2020)

• Record Type: Journal Article
• Authors: 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
• Is Part Of: BMJ open diabetes research and care. Volume 8:Issue 1(2020)
• Publication Date: 2020-04-22
• Subjects: biomarkers -- coronary artery disease -- type 2 diabetes -- proteomic analysis; Diabetes -- Periodicals; 616.462005
• DOI: 10.1136/bmjdrc-2019-001152
• Languages: English
• ISSNs: 2052-4897

Abstract

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.