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Integrating serum proteomics and metabolomics to compare the common and distinct features between acute aggressive ischemic stroke (APIS) and acute non-aggressive ischemic stroke (ANPIS)

缺血性中风 代谢组学 蛋白质组学 冲程(发动机) 医学 急性中风 生物信息学 内科学 心脏病学 生物 缺血 工程类 生物化学 机械工程 基因 组织纤溶酶原激活剂
作者
Minchao Lai,Xiaojun Zhang,Danya Zhou,Xiaojuan Zhang,Mengting Zhu,Qingxian Liu,Ye Zhang,Dian Wang
出处
期刊:Journal of Proteomics [Elsevier]
卷期号:261: 104581-104581 被引量:13
标识
DOI:10.1016/j.jprot.2022.104581
摘要

Understanding common and distinct pathophysiological features between acute progressive ischemic stroke (APIS) and acute non-progressive ischemic stroke (ANPIS) is a prerequisite to making clear the mechanism to determine the prognosis of acute ischemic stroke (AIS). Here, we recruited three independent sets of subjects, all of which included the APIS, ANPIS, and control groups. They were used for serum proteomic and metabolomic analyses, and validation of the critical pathophysiological processes and potential biomarkers of APIS, respectively. Results showed that there were both common and distinct metabolome and proteome between APIS and ANPIS. APIS and ANPIS shared basic processes of AIS in inflammation and oxidative stress response. Coagulation and lipid metabolism disorder, activation of the complement system, and inflammation may enhance with each other in the symptom worsening of APIS. The contents of serum amyloid A1 (SAA1) and S100 calcium-binding protein A9 (S100-A9) in the validation set confirmed the key pathophysiological processes indicated by omics data; they also jointly conferred a moderate value to distinguish APIS from ANPIS. Collectively, disturbance in coagulation and lipid metabolism, complement activation, and inflammation may be synergistically involved in symptom deterioration in APIS. SAA1 and S100-A9 serve as a potential biomarker panel to distinguish APIS from ANPIS. THE SIGNIFICANCE: In this study, we integrated serum proteomics and metabolomics to explore the similarities and differences in pathophysiological processes between APIS and ANPIS. The global metabolic networks have been constructed, and the crucial common pathophysiological processes and the key distinct pathophysiological features between APIS and ANPIS were investigated based on the differentially expressed proteins and metabolites (DEPs/DEMs). Furthermore, pivotal serum proteins (SAA1 and S100A9) were detected in a dependent set to validate the key pathophysiological characteristics, as well as to assess the possibility of them being used as a biomarker panel. Taken together, the multi-omics integration strategy used in this clinical study shows potential to comprehensively interpret and compare the pathophysiological processes of AIS in various conditions, as well as to screen a reliable new biomarker panel.
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