Potential biomarkers for the diagnosis and differential diagnosis of immune-mediated demyelinating diseases screened by tandem mass spectrometry technology
10.3760/cma.j.cn114452-20210831-00548
- VernacularTitle:基于串联质谱标签技术筛选免疫介导性脱髓鞘疾病诊断与鉴别诊断的生物标志物
- Author:
Yaowei DING
1
;
Yijun SHI
;
Guoge LI
;
Wencan JIANG
;
Guanghui ZHENG
;
Guojun ZHANG
Author Information
1. 首都医科大学附属北京天坛医院实验诊断中心 国家药监局体外诊断试剂质量控制重点实验室 北京市免疫试剂临床工程技术研究中心，北京100071
- Keywords:
Demyelinating diseases;
Tandem mass spectrometry;
Chromatography, liquid;
Proteomics;
Cerebrospinal fluid
- From:
Chinese Journal of Laboratory Medicine
2022;45(1):36-44
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To screen the potential biomarkers for the diagnosis and differential diagnosis of immune-mediated demyelinating diseases by tandem mass tags (TMT) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) technology.Methods:Twenty patients with demyelinating diseases (demyelinating group) and 10 patients with noninflammatory neurological diseases (NND group) from Beijing Tiantan Hospital affiliated to Capital Medical University from January 2020 to January 2021 were enrolled in this study. The demyelinating group included 10 patients with Guillain-Barre syndrome (GBS subgroup) and 10 patients with multiple sclerosis (MS subgroup). TMT proteomics was used to screen out the different protein expression patterns between the demyelinating group and the NND group and between the GBS subgroup and the MS subgroup (difference>2 or<0.5 and with statistical significance), and String database was used to perform gene ontology (GO) analysis and Kyoto encyclopedia of gene and genomes (KEGG) analysis on the pathways involved in the differently expressed proteins between the groups. In addition, 80 demyelinating patients (demyelinating diseases validation group) and 40 healthy subjects (healthy control group) were selected for retrospective analysis of general lipid indexes. The demyelinating diseases validation group included 40 GBS patients (GBS validation group) and 40 MS patients (MS validation group). Receiver operating characteristic (ROC) curve was obtained to evaluate the value of general lipid indexes for the diagnosis of demyelinating diseases and the differential diagnosis between GBS and MS groups.Results:A total of 362 proteins were detected by TMT proteomics. There were 101 differentially expressed proteins between the demyelinating group and the NND group, and 45 differentially expressed proteins between the GBS group and the MS group. Compared with the NND group, GO enrichment analysis showed that the top five enrichment pathways in the demyelinating group were macrophage colony stimulating factor and receptor complex, negative regulation of cholesterol input, negative regulation of very low density lipoprotein particle clearance, triglyceride-rich lipoprotein particle remodeling, and cholesterol reverse transport. Compared with MS group, the top five enriched pathways in GBS group were high-density lipoprotein particle receptor binding, negative regulation of very low density lipoprotein particle remodeling, negative regulation of cholesterol input, negative regulation of very low density lipoprotein particle clearance, and medium density lipoprotein particle. KEGG enrichment analysis results showed that differentially expressed proteins in the demyelinating group and the NND group were enriched in 8 pathways, including phosphatidylinositide 3-kinases-protein kinase B signaling pathway, complement and coagulation cascade reaction, extracellular matrix and its receptor interaction, Staphylococcus aureus infection, cholesterol metabolism, RAS signaling pathway, phagosome, and mitogen-activated protein kinase signaling pathway. Differentially expressed proteins in GBS group and MS group were enriched in 9 pathways: cholesterol metabolism, complement and coagulation cascade, platelet activation, peroxisome proliferators-activated receptors signaling pathway, vitamin digestion and absorption, novel coronavirus infection, fat digestion and absorption, axon guidance, and neutrophil extracellular trap formation pathway. The levels of triglyceride (TG), total cholesterol (TC), low density lipoprotein cholesterol (LDL-C) and apolipoprotein B (apoB) were significantly higher, while high density lipoprotein cholesterol (HDL-C) and apolipoprotein A1 (apoA1) levels were significantly lower in the demyelinating disease validation group than in the healthy control group (all P<0.05 or 0.01). Area under the curve (AUC) of TG, TC, HDL-C, LDL-C, apoA1 and apoB alone or in combination for the diagnosis of immune-mediated demyelinating diseases was 0.746, 0.643, 0.798, 0.703, 0.806, 0.708 and 0.868, respectively. The AUC of HDL-C, apoA1, LDL-C and apoB for differential diagnosis between GBS and MS was 0.692, 0.653, 0.632, 0.695 and 0.718, respectively. Conclusions:There are differences in cerebrospinal fluid proteomics between patients with immune-mediated demyelinating disease and patients with NND, GBS and MS, and the differentially expressed protein patterns mainly exist in the pathways related to lipid metabolism. Lipid related indicators may be used as biomarkers for the diagnosis and differential diagnosis of immune-mediated demyelinating disease.
