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Updated: Sep 5, 2025

A Strategy for Sensitive, Large Scale Quantitative Metabolomics
Published on: May 27, 2014
Integrated proteomics and metabolomics analysis reveals hubs protein and network alterations in myasthenia gravis
Tong Tong1, Jing Zhang1, Li Jia1
1Department of Anesthesiology, The Fourth Affiliated Hospital of Hebei Medical University, Shijiazhuang 050011, China.
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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