Discovery of New Risk Markers for Ischemic Stroke Using a Novel Targeted Proteomics Chip

医学 内科学 冲程(发动机) 嗜酸性阳离子蛋白 利钠肽 蛋白质组学 免疫学 生物信息学 肿瘤科 嗜酸性粒细胞 心力衰竭 生物 机械工程 生物化学 哮喘 工程类 基因
作者
Lars Lind,Agneta Siegbahn,Bertil Lindahl,Markus Stenemo,Johan Sundström,Johan Ärnlöv
出处
期刊:Stroke [Lippincott Williams & Wilkins]
卷期号:46 (12): 3340-3347 被引量:73
标识
DOI:10.1161/strokeaha.115.010829
摘要

Emerging technologies have made it possible to simultaneously evaluate a large number of circulating proteins as potential new stroke risk markers.We explored associations between 85 cardiovascular proteins, assessed by a proteomics chip, and incident ischemic stroke in 2 independent cohorts of elderly (Prospective Investigation of the Vasculature in Uppsala Seniors [PIVUS]: n=977; 50% women, mean age=70.1 years, 71 fatal/nonfatal ischemic stroke events during 10.0 years; and Uppsala Longitudinal Study in Adult Men [ULSAM]: n=720, mean age=77.5 years, 75 ischemic stroke events during 9.5 years). The proteomics chip uses 2 antibodies for each protein and a polymerase chain reaction step to achieve a high-specific binding and the possibility to measure multiple proteins in parallel, but gives no absolute concentrations.In PIVUS, 16 proteins were related to incident ischemic stroke using a false discovery rate of 5%. Of these, N-terminal pro-B-type natriuretic peptide (P=0.0032), adrenomedullin (P=0.018), and eosinophil cationic protein (P=0.0071) were replicated in ULSAM after adjustment for established stroke risk factors. In predefined secondary meta-analyses of individual data, interleukin-27 subunit α, growth/differentiation factor 15, urokinase plasminogen activator surface receptor, tumor necrosis factor receptor superfamily member 6, macrophage colony-stimulating factor 1, and matrix metalloproteinase-7 were also potential risk markers for ischemic stroke after adjustment for multiple comparisons (P<0.0006). The addition of N-terminal pro-B-type natriuretic peptide, adrenomedullin, and eosinophil cationic protein to a model with established risk factors increased the C-statistic from 0.629 to 0.689 (P=0.001).Our data suggest that large-scale proteomics analysis is a promising way of discovering novel biomarkers that could substantially improve the prediction of ischemic stroke.

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