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Integrated proteomics and metabolomics analysis reveals hubs protein and network alterations in myasthenia gravis

Background: Thymoma-associated myasthenia gravis (TAMG) is a well-described subtype of Myasthenia gravis (MG). Nevertheless, the detailed proteins and bioprocess differentiating TAMG from TAMG (−) thymoma have remained unclear. Methods: The proteomics and metabolomics were carried out on serum sampl...

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Autores principales: Tong, Tong, Zhang, Jing, Jia, Li, Liang, Ping, Wang, Na
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9320536/
https://www.ncbi.nlm.nih.gov/pubmed/35802752
http://dx.doi.org/10.18632/aging.204156
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author Tong, Tong
Zhang, Jing
Jia, Li
Liang, Ping
Wang, Na
author_facet Tong, Tong
Zhang, Jing
Jia, Li
Liang, Ping
Wang, Na
author_sort Tong, Tong
collection PubMed
description Background: Thymoma-associated myasthenia gravis (TAMG) is a well-described subtype of Myasthenia gravis (MG). Nevertheless, the detailed proteins and bioprocess differentiating TAMG from TAMG (−) thymoma have remained unclear. Methods: The proteomics and metabolomics were carried out on serum samples from thymoma group (n = 60, TNMG), TAMG (+) thymoma group (n = 70, TAMG (+)), and TAMG (−) thymomas group (n = 62, TAMG (−)), and controls (n = 159). groups. Proteomics and metabolomics analyses, including weighted gene co-expression network analysis (WGCNA), was conducted to detect the hub proteins and metabolomics processes that could differentiate TAMG (+) from TAMG (−) thymomas. MetaboAnalyst was used to examine the integration of proteomic and metabolomic analysis to differentiate TAMG (+) from TAMG (−) thymomas. Results: The of module–trait correlation of WGCNA analysis identified KRT1, GSN, COL6A1, KRT10, FOLR2, KRT9, KRT2, TPI1, ARF3, LYZ, ADIPOQ, SEMA4B, IGKV1-27, MASP2, IGF2R was associated with TAMG (+) thymomas. In addition, organismal systems-immune system and metabolism-biosynthesis of other secondary metabolites were closely related to the mechanism of TAMG (+) pathogenesis. Conclusion: Our integrated proteomics and metabolomics analysis supply a systems-level view of proteome changes in TAMG (+), TAMG (−) thymomas and exposes disease-associated protein network alterations involved in.
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spelling pubmed-93205362022-07-27 Integrated proteomics and metabolomics analysis reveals hubs protein and network alterations in myasthenia gravis Tong, Tong Zhang, Jing Jia, Li Liang, Ping Wang, Na Aging (Albany NY) Research Paper Background: Thymoma-associated myasthenia gravis (TAMG) is a well-described subtype of Myasthenia gravis (MG). Nevertheless, the detailed proteins and bioprocess differentiating TAMG from TAMG (−) thymoma have remained unclear. Methods: The proteomics and metabolomics were carried out on serum samples from thymoma group (n = 60, TNMG), TAMG (+) thymoma group (n = 70, TAMG (+)), and TAMG (−) thymomas group (n = 62, TAMG (−)), and controls (n = 159). groups. Proteomics and metabolomics analyses, including weighted gene co-expression network analysis (WGCNA), was conducted to detect the hub proteins and metabolomics processes that could differentiate TAMG (+) from TAMG (−) thymomas. MetaboAnalyst was used to examine the integration of proteomic and metabolomic analysis to differentiate TAMG (+) from TAMG (−) thymomas. Results: The of module–trait correlation of WGCNA analysis identified KRT1, GSN, COL6A1, KRT10, FOLR2, KRT9, KRT2, TPI1, ARF3, LYZ, ADIPOQ, SEMA4B, IGKV1-27, MASP2, IGF2R was associated with TAMG (+) thymomas. In addition, organismal systems-immune system and metabolism-biosynthesis of other secondary metabolites were closely related to the mechanism of TAMG (+) pathogenesis. Conclusion: Our integrated proteomics and metabolomics analysis supply a systems-level view of proteome changes in TAMG (+), TAMG (−) thymomas and exposes disease-associated protein network alterations involved in. Impact Journals 2022-07-08 /pmc/articles/PMC9320536/ /pubmed/35802752 http://dx.doi.org/10.18632/aging.204156 Text en Copyright: © 2022 Tong et al. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Tong, Tong
Zhang, Jing
Jia, Li
Liang, Ping
Wang, Na
Integrated proteomics and metabolomics analysis reveals hubs protein and network alterations in myasthenia gravis
title Integrated proteomics and metabolomics analysis reveals hubs protein and network alterations in myasthenia gravis
title_full Integrated proteomics and metabolomics analysis reveals hubs protein and network alterations in myasthenia gravis
title_fullStr Integrated proteomics and metabolomics analysis reveals hubs protein and network alterations in myasthenia gravis
title_full_unstemmed Integrated proteomics and metabolomics analysis reveals hubs protein and network alterations in myasthenia gravis
title_short Integrated proteomics and metabolomics analysis reveals hubs protein and network alterations in myasthenia gravis
title_sort integrated proteomics and metabolomics analysis reveals hubs protein and network alterations in myasthenia gravis
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9320536/
https://www.ncbi.nlm.nih.gov/pubmed/35802752
http://dx.doi.org/10.18632/aging.204156
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