Laboratory of Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
NMPA Key Laboratory for Quality Control of In Vitro Diagnostics , Beijing, China.
Front Immunol. 2021 Aug 20;12:700031. doi: 10.3389/fimmu.2021.700031. eCollection 2021.
Here, we aimed to identify protein biomarkers that could rapidly and accurately diagnose multiple sclerosis (MS) using a highly sensitive proteomic immunoassay.
Tandem mass tag (TMT) quantitative proteomic analysis was performed to determine the differentially expressed proteins (DEPs) in cerebrospinal fluid (CSF) samples collected from 10 patients with MS and 10 non-inflammatory neurological controls (NINCs). The DEPs were analyzed using bioinformatics tools, and the candidate proteins were validated using the ELISA method in another cohort comprising 160 samples (paired CSF and plasma of 40 patients with MS, CSF of 40 NINCs, and plasma of 40 healthy individuals). Receiver operating characteristic (ROC) curves were used to determine the diagnostic potential of this method.
Compared to NINCs, we identified 83 CSF-specific DEPs out of a total of 343 proteins in MS patients. Gene ontology (GO) enrichment analysis revealed that these DEPs are mainly involved in platelet degranulation, negative regulation of proteolysis, and post-translational protein modification. Pathway enrichment analysis revealed that the complement and coagulation cascades, Ras signaling pathway, and PI3K-Akt signaling pathway are the main components. Insulin-like growth factor-binding protein 7 (IGFBP7), insulin-like growth factor 2 (IGF2), and somatostatin (SST) were identified as the potential proteins with high scores, degree, and centrality in the protein-protein interaction (PPI) network. We validated the expression of these three proteins using ELISA. Compared to NINCs, the level of CSF IGFBP7 was significantly upregulated, and the level of CSF SST was significantly downregulated in the MS group.
Our results suggest that SST and IGFBP7 might be associated with the pathogenesis of MS and would be helpful in diagnosing MS. Since IGFBP7 was used to classify relapsing remitting MS (RRMS) and secondary progressive MS (SPMS) patients, therefore, it may act as a potential key marker and therapeutic target in MS.
本研究旨在通过高灵敏度的蛋白质组免疫分析,寻找能够快速、准确诊断多发性硬化症(MS)的蛋白质生物标志物。
采用串联质量标签(TMT)定量蛋白质组学分析方法,检测 10 例 MS 患者和 10 例非炎症性神经对照组(NINCs)脑脊液(CSF)样本中的差异表达蛋白(DEPs)。使用生物信息学工具分析 DEPs,并采用 ELISA 法在另一包含 160 例样本的队列中验证候选蛋白(40 例 MS 患者的 CSF 和血浆配对、40 例 NINCs 的 CSF 和 40 例健康个体的血浆)。使用受试者工作特征(ROC)曲线确定该方法的诊断潜力。
与 NINCs 相比,我们在 MS 患者中总共 343 种蛋白中鉴定出 83 种 CSF 特异性 DEPs。GO 富集分析显示,这些 DEPs 主要参与血小板脱颗粒、蛋白酶体负调控和翻译后蛋白修饰。通路富集分析显示,补体和凝血级联、Ras 信号通路和 PI3K-Akt 信号通路是主要组成部分。胰岛素样生长因子结合蛋白 7(IGFBP7)、胰岛素样生长因子 2(IGF2)和生长抑素(SST)被鉴定为蛋白质-蛋白质相互作用(PPI)网络中具有高评分、高度数和中心性的潜在蛋白。我们使用 ELISA 验证了这三种蛋白的表达。与 NINCs 相比,MS 组 CSF IGFBP7 水平显著上调,CSF SST 水平显著下调。
我们的研究结果表明,SST 和 IGFBP7 可能与 MS 的发病机制有关,并有助于 MS 的诊断。由于 IGFBP7 用于分类复发缓解型 MS(RRMS)和继发性进展型 MS(SPMS)患者,因此,它可能是 MS 中的潜在关键标志物和治疗靶点。