Discovery of Novel Biomarkers for Diagnosing and Predicting the Progression of Multiple Sclerosis Using TMT-Based Quantitative Proteomics

ObjectiveHere, we aimed to identify protein biomarkers that could rapidly and accurately diagnose multiple sclerosis (MS) using a highly sensitive proteomic immunoassay.MethodsTandem mass tag (TMT) quantitative proteomic analysis was performed to determine the differentially expressed proteins (DEPs...

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Main Authors: Yijun Shi, Yaowei Ding, Guoge Li, Lijuan Wang, Rasha Alsamani Osman, Jialu Sun, Lingye Qian, Guanghui Zheng, Guojun Zhang
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-08-01
Series:Frontiers in Immunology
Subjects:
SST
Online Access:https://www.frontiersin.org/articles/10.3389/fimmu.2021.700031/full
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spelling doaj-202f4d480f7541b8b86ae5b18e33a6782021-08-20T11:13:06ZengFrontiers Media S.A.Frontiers in Immunology1664-32242021-08-011210.3389/fimmu.2021.700031700031Discovery of Novel Biomarkers for Diagnosing and Predicting the Progression of Multiple Sclerosis Using TMT-Based Quantitative ProteomicsYijun Shi0Yaowei Ding1Guoge Li2Lijuan Wang3Lijuan Wang4Lijuan Wang5Rasha Alsamani Osman6Jialu Sun7Lingye Qian8Guanghui Zheng9Guanghui Zheng10Guanghui Zheng11Guojun Zhang12Guojun Zhang13Guojun Zhang14Laboratory of Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaLaboratory of Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaLaboratory of Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaLaboratory of Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaNMPA Key Laboratory for Quality Control of In Vitro Diagnostics , Beijing, ChinaBeijing Engineering Research Center of Immunological Reagents Clinical Research, Beijing, ChinaLaboratory of Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaLaboratory of Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaLaboratory of Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaLaboratory of Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaNMPA Key Laboratory for Quality Control of In Vitro Diagnostics , Beijing, ChinaBeijing Engineering Research Center of Immunological Reagents Clinical Research, Beijing, ChinaLaboratory of Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaNMPA Key Laboratory for Quality Control of In Vitro Diagnostics , Beijing, ChinaBeijing Engineering Research Center of Immunological Reagents Clinical Research, Beijing, ChinaObjectiveHere, we aimed to identify protein biomarkers that could rapidly and accurately diagnose multiple sclerosis (MS) using a highly sensitive proteomic immunoassay.MethodsTandem 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.ResultsCompared 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.ConclusionOur 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.https://www.frontiersin.org/articles/10.3389/fimmu.2021.700031/fullmultiple sclerosisbiomarkerproteomicsdifferentially expressed proteinsIGFBP7SST
collection DOAJ
language English
format Article
sources DOAJ
author Yijun Shi
Yaowei Ding
Guoge Li
Lijuan Wang
Lijuan Wang
Lijuan Wang
Rasha Alsamani Osman
Jialu Sun
Lingye Qian
Guanghui Zheng
Guanghui Zheng
Guanghui Zheng
Guojun Zhang
Guojun Zhang
Guojun Zhang
spellingShingle Yijun Shi
Yaowei Ding
Guoge Li
Lijuan Wang
Lijuan Wang
Lijuan Wang
Rasha Alsamani Osman
Jialu Sun
Lingye Qian
Guanghui Zheng
Guanghui Zheng
Guanghui Zheng
Guojun Zhang
Guojun Zhang
Guojun Zhang
Discovery of Novel Biomarkers for Diagnosing and Predicting the Progression of Multiple Sclerosis Using TMT-Based Quantitative Proteomics
Frontiers in Immunology
multiple sclerosis
biomarker
proteomics
differentially expressed proteins
IGFBP7
SST
author_facet Yijun Shi
Yaowei Ding
Guoge Li
Lijuan Wang
Lijuan Wang
Lijuan Wang
Rasha Alsamani Osman
Jialu Sun
Lingye Qian
Guanghui Zheng
Guanghui Zheng
Guanghui Zheng
Guojun Zhang
Guojun Zhang
Guojun Zhang
author_sort Yijun Shi
title Discovery of Novel Biomarkers for Diagnosing and Predicting the Progression of Multiple Sclerosis Using TMT-Based Quantitative Proteomics
title_short Discovery of Novel Biomarkers for Diagnosing and Predicting the Progression of Multiple Sclerosis Using TMT-Based Quantitative Proteomics
title_full Discovery of Novel Biomarkers for Diagnosing and Predicting the Progression of Multiple Sclerosis Using TMT-Based Quantitative Proteomics
title_fullStr Discovery of Novel Biomarkers for Diagnosing and Predicting the Progression of Multiple Sclerosis Using TMT-Based Quantitative Proteomics
title_full_unstemmed Discovery of Novel Biomarkers for Diagnosing and Predicting the Progression of Multiple Sclerosis Using TMT-Based Quantitative Proteomics
title_sort discovery of novel biomarkers for diagnosing and predicting the progression of multiple sclerosis using tmt-based quantitative proteomics
publisher Frontiers Media S.A.
series Frontiers in Immunology
issn 1664-3224
publishDate 2021-08-01
description ObjectiveHere, we aimed to identify protein biomarkers that could rapidly and accurately diagnose multiple sclerosis (MS) using a highly sensitive proteomic immunoassay.MethodsTandem 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.ResultsCompared 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.ConclusionOur 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.
topic multiple sclerosis
biomarker
proteomics
differentially expressed proteins
IGFBP7
SST
url https://www.frontiersin.org/articles/10.3389/fimmu.2021.700031/full
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