Proteomics and metabolomics analyses reveal the full spectrum of inflammatory and lipid metabolic abnormalities in dyslipidemia. (15th June 2021)

• Record Type: Journal Article
• Authors: Du, Hui; Rao, Yifei; Liu, Ronghua; Deng, Kesui; Guan, Yongmei; Luo, Dewei; Mao, Qiping; Yu, Jianwei; Bo, Tao; Fan, Ziquan; Ouyang, Hui; Feng, Yulin; Zhu, Weifeng
• Is Part Of: Biomedical chromatography. Volume 35:Number 10(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-06-15
• Subjects: biomarkers -- dyslipidemia -- metabolic pathways -- metabolomics -- proteomics; Chromatographic analysis -- Periodicals; Biology -- Periodicals; Medicine -- Periodicals; Biology -- Periodicals; Chromatography -- methods -- Periodicals; Medicine -- Periodicals; 543.089
• DOI: 10.1002/bmc.5183
• Languages: English
• ISSNs: 0269-3879

Abstract

Abstract: Dyslipidemia is a common, chronic metabolic disease associated with cardiovascular complications. Due to the multiplicity of etiological factors, the pathogenesis of dyslipidemia is still unclear. In this study, we combined proteomics and metabolomics methods to analyze the plasma of patients with dyslipidemia and healthy subjects. isobaric tags for relative and absolute quantification (iTRAQ) markers, combined with LC–MS/MS proteomics technology and the UHPLC/Orbitfast‐X Tribrid system, were used to establish the metabolite profile in clinical dyslipidemia. A total of 137 differentially expressed proteins, mainly related to biological processes such as protein activation cascades, adaptive immune responses, complement activation, acute inflammatory responses, and regulation of acute inflammatory responses, were identified. These proteins are involved in the regulation of important metabolic pathways, such as immunity and inflammation, coagulation and hemostasis, lipid metabolism, and oxidation and antioxidant defenses. The analysis of clinical metabolites showed there were 69 different metabolites in plasma, mainly related to glycerolipid, sphingolipid, porphyrin, α‐linolenic acid, linoleic acid, and arachidonic acid metabolism, suggesting that the regulation of inflammation and lipid metabolism may be disturbed in patients with dyslipidemia. Among these, significant changes were observed in indole‐3‐propionic acid (IPA), which is considered as a potential biomarker of dyslipidemia. The combined analysis of proteins and metabolites showed that arachidonic acid, linoleic acid, and lipid metabolic pathways were closely related to dyslipidemia. IPA may be a potential biomarker. The information provided in this study may provide new insights into the pathogenesis of animal models of dyslipidemia and related disease models, as well as potential intervention targets.