TMT-Based Proteomic Analysis of Plasma from Children with Rolandic Epilepsy

Rolandic epilepsy is one of the most common epileptic syndromes in childhood. We used TMT-based proteomics and bioinformatics analysis to identify the differentially expressed proteins in plasma of children with Rolandic epilepsy. Our aim was to provide a molecular basis for exploring possible mecha...

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Published inDisease markers Vol. 2020; no. 2020; pp. 1 - 10
Main Authors Ma, Dihui, Gu, Feng, Jiang, Tiechao, Sun, Ji, Liang, Jianmin
Format Journal Article
LanguageEnglish
Published Cairo, Egypt Hindawi Publishing Corporation 07.10.2020
Hindawi
John Wiley & Sons, Inc
Subjects
Age
Antioxidants
Bioinformatics
Biomarkers
Children
Chromatography
Complement activation
Electroencephalography
Epilepsy
Fibrinogen
Genes
Glycolysis
Headache
Immune response
Innate immunity
Lipid metabolism
Liquid chromatography
Magnetic resonance imaging
Mass spectrometry
Mass spectroscopy
Migraine
Pathogenesis
Peptides
Physiological aspects
Plasma
Proteins
Proteomics
Software
China
United States > US
Online AccessGet full text
ISSN0278-0240
1875-8630
1875-8630
DOI10.1155/2020/8840482

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Abstract Rolandic epilepsy is one of the most common epileptic syndromes in childhood. We used TMT-based proteomics and bioinformatics analysis to identify the differentially expressed proteins in plasma of children with Rolandic epilepsy. Our aim was to provide a molecular basis for exploring possible mechanisms underlying the pathogenesis of epilepsy. Subjects were divided into two groups (five in each): patients with Rolandic epilepsy as cases and patients with migraine as controls. Total proteins were extracted and quantitatively labeled with TMT, then analyzed using liquid chromatography mass spectrometry. Bioinformatics analysis was used to identify the hub genes. A total of 752 proteins were identified, of which 670 contained quantitative proteins. 217 differentially expressed proteins were identified, 46 of which were only upregulated in more than two groups and 111 of which were only downregulated in more than two groups. Bioinformatics analysis revealed top 10 hub genes in the up- and downregulated groups, respectively. Our study demonstrates that some differentially expressed proteins are associated with epilepsy. Activation of acute-phase or innate immune response and complement and fibrinogen systems and repression of glycolysis, lipoprotein metabolism, and antioxidant activity may play a role in the development of epilepsy.
AbstractList Rolandic epilepsy is one of the most common epileptic syndromes in childhood. We used TMT-based proteomics and bioinformatics analysis to identify the differentially expressed proteins in plasma of children with Rolandic epilepsy. Our aim was to provide a molecular basis for exploring possible mechanisms underlying the pathogenesis of epilepsy. Subjects were divided into two groups (five in each): patients with Rolandic epilepsy as cases and patients with migraine as controls. Total proteins were extracted and quantitatively labeled with TMT, then analyzed using liquid chromatography mass spectrometry. Bioinformatics analysis was used to identify the hub genes. A total of 752 proteins were identified, of which 670 contained quantitative proteins. 217 differentially expressed proteins were identified, 46 of which were only upregulated in more than two groups and 111 of which were only downregulated in more than two groups. Bioinformatics analysis revealed top 10 hub genes in the up- and downregulated groups, respectively. Our study demonstrates that some differentially expressed proteins are associated with epilepsy. Activation of acute-phase or innate immune response and complement and fibrinogen systems and repression of glycolysis, lipoprotein metabolism, and antioxidant activity may play a role in the development of epilepsy.
Rolandic epilepsy is one of the most common epileptic syndromes in childhood. We used TMT-based proteomics and bioinformatics analysis to identify the differentially expressed proteins in plasma of children with Rolandic epilepsy. Our aim was to provide a molecular basis for exploring possible mechanisms underlying the pathogenesis of epilepsy. Subjects were divided into two groups (five in each): patients with Rolandic epilepsy as cases and patients with migraine as controls. Total proteins were extracted and quantitatively labeled with TMT, then analyzed using liquid chromatography mass spectrometry. Bioinformatics analysis was used to identify the hub genes. A total of 752 proteins were identified, of which 670 contained quantitative proteins. 217 differentially expressed proteins were identified, 46 of which were only upregulated in more than two groups and 111 of which were only downregulated in more than two groups. Bioinformatics analysis revealed top 10 hub genes in the up- and downregulated groups, respectively. Our study demonstrates that some differentially expressed proteins are associated with epilepsy. Activation of acute-phase or innate immune response and complement and fibrinogen systems and repression of glycolysis, lipoprotein metabolism, and antioxidant activity may play a role in the development of epilepsy.Rolandic epilepsy is one of the most common epileptic syndromes in childhood. We used TMT-based proteomics and bioinformatics analysis to identify the differentially expressed proteins in plasma of children with Rolandic epilepsy. Our aim was to provide a molecular basis for exploring possible mechanisms underlying the pathogenesis of epilepsy. Subjects were divided into two groups (five in each): patients with Rolandic epilepsy as cases and patients with migraine as controls. Total proteins were extracted and quantitatively labeled with TMT, then analyzed using liquid chromatography mass spectrometry. Bioinformatics analysis was used to identify the hub genes. A total of 752 proteins were identified, of which 670 contained quantitative proteins. 217 differentially expressed proteins were identified, 46 of which were only upregulated in more than two groups and 111 of which were only downregulated in more than two groups. Bioinformatics analysis revealed top 10 hub genes in the up- and downregulated groups, respectively. Our study demonstrates that some differentially expressed proteins are associated with epilepsy. Activation of acute-phase or innate immune response and complement and fibrinogen systems and repression of glycolysis, lipoprotein metabolism, and antioxidant activity may play a role in the development of epilepsy.
Audience Academic
Author Sun, Ji
Ma, Dihui
Gu, Feng
Jiang, Tiechao
Liang, Jianmin
AuthorAffiliation 3 Department of Infectious Diseases, The People's Hospital of Jilin Province, Changchun, Jilin 130021, China
4 Department of Neurology, The First Hospital of Jilin University, Changchun, Jilin 130021, China
1 Department of Pediatric Neurology, The First Hospital of Jilin University, Changchun, Jilin 130021, China
2 Department of Cardiology, The China-Japan Union Hospital of Jilin University, Changchun, Jilin 130031, China
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Copyright Copyright © 2020 Ji Sun et al.
COPYRIGHT 2020 John Wiley & Sons, Inc.
Copyright © 2020 Ji Sun et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0
Copyright © 2020 Ji Sun et al. 2020
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– notice: Copyright © 2020 Ji Sun et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0
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Snippet Rolandic epilepsy is one of the most common epileptic syndromes in childhood. We used TMT-based proteomics and bioinformatics analysis to identify the...
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SubjectTerms Age
Antioxidants
Bioinformatics
Biomarkers
Children
Chromatography
Complement activation
Electroencephalography
Epilepsy
Fibrinogen
Genes
Glycolysis
Headache
Immune response
Innate immunity
Lipid metabolism
Liquid chromatography
Magnetic resonance imaging
Mass spectrometry
Mass spectroscopy
Migraine
Pathogenesis
Peptides
Physiological aspects
Plasma
Proteins
Proteomics
Software
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Title TMT-Based Proteomic Analysis of Plasma from Children with Rolandic Epilepsy
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