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Identification and Clinical Validation of Key Extracellular Proteins as the Potential Biomarkers in Relapsing-Remitting Multiple Sclerosis

BACKGROUND: Multiple sclerosis (MS) is a demyelinating disease of the central nervous system (CNS) mediated by autoimmunity. No objective clinical indicators are available for the diagnosis and prognosis of MS. Extracellular proteins are most glycosylated and likely to enter into the body fluid to s...

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Autores principales: Li, Meng, Chen, Hongping, Yin, Pengqi, Song, Jihe, Jiang, Fangchao, Tang, Zhanbin, Fan, Xuehui, Xu, Chen, Wang, Yingju, Xue, Yang, Han, Baichao, Wang, Haining, Li, Guozhong, Zhong, Di
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8688859/
https://www.ncbi.nlm.nih.gov/pubmed/34950135
http://dx.doi.org/10.3389/fimmu.2021.753929
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author Li, Meng
Chen, Hongping
Yin, Pengqi
Song, Jihe
Jiang, Fangchao
Tang, Zhanbin
Fan, Xuehui
Xu, Chen
Wang, Yingju
Xue, Yang
Han, Baichao
Wang, Haining
Li, Guozhong
Zhong, Di
author_facet Li, Meng
Chen, Hongping
Yin, Pengqi
Song, Jihe
Jiang, Fangchao
Tang, Zhanbin
Fan, Xuehui
Xu, Chen
Wang, Yingju
Xue, Yang
Han, Baichao
Wang, Haining
Li, Guozhong
Zhong, Di
author_sort Li, Meng
collection PubMed
description BACKGROUND: Multiple sclerosis (MS) is a demyelinating disease of the central nervous system (CNS) mediated by autoimmunity. No objective clinical indicators are available for the diagnosis and prognosis of MS. Extracellular proteins are most glycosylated and likely to enter into the body fluid to serve as potential biomarkers. Our work will contribute to the in-depth study of the functions of extracellular proteins and the discovery of disease biomarkers. METHODS: MS expression profiling data of the human brain was downloaded from the Gene Expression Omnibus (GEO). Extracellular protein-differentially expressed genes (EP-DEGs) were screened by protein annotation databases. GO and KEGG were used to analyze the function and pathway of EP-DEGs. STRING, Cytoscape, MCODE and Cytohubba were used to construct a protein-protein interaction (PPI) network and screen key EP-DEGs. Key EP-DEGs levels were detected in the CSF of MS patients. ROC curve and survival analysis were used to evaluate the diagnostic and prognostic ability of key EP-DEGs. RESULTS: We screened 133 EP-DEGs from DEGs. EP-DEGs were enriched in the collagen-containing extracellular matrix, signaling receptor activator activity, immune-related pathways, and PI3K-Akt signaling pathway. The PPI network of EP-DEGs had 85 nodes and 185 edges. We identified 4 key extracellular proteins IL17A, IL2, CD44, IGF1, and 16 extracellular proteins that interacted with IL17A. We clinically verified that IL17A levels decreased, but Del-1 and resolvinD1 levels increased. The diagnostic accuracy of Del-1 (AUC: 0.947) was superior to that of IgG (AUC: 0.740) with a sensitivity of 82.4% and a specificity of 100%. High Del-1 levels were significantly associated with better relapse-free and progression-free survival. CONCLUSION: IL17A, IL2, CD44, and IGF1 may be key extracellular proteins in the pathogenesis of MS. IL17A, Del-1, and resolvinD1 may co-regulate the development of MS and Del-1 is a potential biomarker of MS. We used bioinformatics methods to explore the biomarkers of MS and validated the results in clinical samples. The study provides a theoretical and experimental basis for revealing the pathogenesis of MS and improving the diagnosis and prognosis of MS.
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spelling pubmed-86888592021-12-22 Identification and Clinical Validation of Key Extracellular Proteins as the Potential Biomarkers in Relapsing-Remitting Multiple Sclerosis Li, Meng Chen, Hongping Yin, Pengqi Song, Jihe Jiang, Fangchao Tang, Zhanbin Fan, Xuehui Xu, Chen Wang, Yingju Xue, Yang Han, Baichao Wang, Haining Li, Guozhong Zhong, Di Front Immunol Immunology BACKGROUND: Multiple sclerosis (MS) is a demyelinating disease of the central nervous system (CNS) mediated by autoimmunity. No objective clinical indicators are available for the diagnosis and prognosis of MS. Extracellular proteins are most glycosylated and likely to enter into the body fluid to serve as potential biomarkers. Our work will contribute to the in-depth study of the functions of extracellular proteins and the discovery of disease biomarkers. METHODS: MS expression profiling data of the human brain was downloaded from the Gene Expression Omnibus (GEO). Extracellular protein-differentially expressed genes (EP-DEGs) were screened by protein annotation databases. GO and KEGG were used to analyze the function and pathway of EP-DEGs. STRING, Cytoscape, MCODE and Cytohubba were used to construct a protein-protein interaction (PPI) network and screen key EP-DEGs. Key EP-DEGs levels were detected in the CSF of MS patients. ROC curve and survival analysis were used to evaluate the diagnostic and prognostic ability of key EP-DEGs. RESULTS: We screened 133 EP-DEGs from DEGs. EP-DEGs were enriched in the collagen-containing extracellular matrix, signaling receptor activator activity, immune-related pathways, and PI3K-Akt signaling pathway. The PPI network of EP-DEGs had 85 nodes and 185 edges. We identified 4 key extracellular proteins IL17A, IL2, CD44, IGF1, and 16 extracellular proteins that interacted with IL17A. We clinically verified that IL17A levels decreased, but Del-1 and resolvinD1 levels increased. The diagnostic accuracy of Del-1 (AUC: 0.947) was superior to that of IgG (AUC: 0.740) with a sensitivity of 82.4% and a specificity of 100%. High Del-1 levels were significantly associated with better relapse-free and progression-free survival. CONCLUSION: IL17A, IL2, CD44, and IGF1 may be key extracellular proteins in the pathogenesis of MS. IL17A, Del-1, and resolvinD1 may co-regulate the development of MS and Del-1 is a potential biomarker of MS. We used bioinformatics methods to explore the biomarkers of MS and validated the results in clinical samples. The study provides a theoretical and experimental basis for revealing the pathogenesis of MS and improving the diagnosis and prognosis of MS. Frontiers Media S.A. 2021-12-07 /pmc/articles/PMC8688859/ /pubmed/34950135 http://dx.doi.org/10.3389/fimmu.2021.753929 Text en Copyright © 2021 Li, Chen, Yin, Song, Jiang, Tang, Fan, Xu, Wang, Xue, Han, Wang, Li and Zhong https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Immunology
Li, Meng
Chen, Hongping
Yin, Pengqi
Song, Jihe
Jiang, Fangchao
Tang, Zhanbin
Fan, Xuehui
Xu, Chen
Wang, Yingju
Xue, Yang
Han, Baichao
Wang, Haining
Li, Guozhong
Zhong, Di
Identification and Clinical Validation of Key Extracellular Proteins as the Potential Biomarkers in Relapsing-Remitting Multiple Sclerosis
title Identification and Clinical Validation of Key Extracellular Proteins as the Potential Biomarkers in Relapsing-Remitting Multiple Sclerosis
title_full Identification and Clinical Validation of Key Extracellular Proteins as the Potential Biomarkers in Relapsing-Remitting Multiple Sclerosis
title_fullStr Identification and Clinical Validation of Key Extracellular Proteins as the Potential Biomarkers in Relapsing-Remitting Multiple Sclerosis
title_full_unstemmed Identification and Clinical Validation of Key Extracellular Proteins as the Potential Biomarkers in Relapsing-Remitting Multiple Sclerosis
title_short Identification and Clinical Validation of Key Extracellular Proteins as the Potential Biomarkers in Relapsing-Remitting Multiple Sclerosis
title_sort identification and clinical validation of key extracellular proteins as the potential biomarkers in relapsing-remitting multiple sclerosis
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8688859/
https://www.ncbi.nlm.nih.gov/pubmed/34950135
http://dx.doi.org/10.3389/fimmu.2021.753929
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