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Metabolomics‐proteomics profiles delineate metabolic changes in kidney fibrosis disease
Author(s) -
Cao Hongxin,
Zhang Aihua,
Sun Hui,
Zhou Xiaohang,
Guan Yu,
Liu Qi,
Kong Ling,
Wang Xijun
Publication year - 2015
Publication title -
proteomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.26
H-Index - 167
eISSN - 1615-9861
pISSN - 1615-9853
DOI - 10.1002/pmic.201500062
Subject(s) - proteomics , metabolomics , biology , computational biology , actin cytoskeleton , metabolic pathway , quantitative proteomics , signal transduction , biological pathway , systems biology , bioinformatics , microbiology and biotechnology , cytoskeleton , metabolism , biochemistry , cell , gene expression , gene
Kidney fibrosis (KF) is a common process that leads to the progression of various types of kidney disease including kidney‐yang deficiency syndrome, however, little is known regarding the underlying biology of this disorder. Fortunately, integrated omics approaches provide the molecule fingerprints related to the disease. In an attempt to address this issue, we integrated metabolomics–proteomics profiles analyzed pathogenic mechanisms of KF based on rat model. A total 37 serum differential metabolites were contributed to KF progress, involved several important metabolic pathways. Using iTRAQ‐based quantitative proteomics analysis, 126 differential serum proteins were identified and provide valuable insight into the underlying mechanisms of KF. These proteins appear to be involved in complement and coagulation cascades, regulation of actin cytoskeleton, MAPK signaling pathway, RNA transport, etc. Interestingly, pathway/network analysis of integrated proteomics and metabolomics data firstly reveals that these signaling pathways were closely related with KF. It further indicated that most of these proteins play a pivotal role in the regulation of metabolism pathways.