Literature DB >> 32454159

Comparative proteomics analysis of patients with quick development and slow development Chronic Obstructive Pulmonary Disease (COPD).

Fengsen Li1, Dan Xu2, Jing Wang3, Jing Jing2, Zheng Li2, Xiang Jin4.   

Abstract

BACKGROUND: The development of Chronic Obstructive Pulmonary Disease (COPD) has been assessed and divided into slow development (SD), normal development (ND) and quick development (QD). Little is known about the plasma proteome characters among these three phenotypes.
METHODS: We performed a comparative proteomic analysis in the plasma of normal control (NC), SD, ND and QD phenotype COPD patients using isobaric tags for relative and absolute quantitation (iTRAQ) technique.
RESULTS: A total of 683 proteins were successfully identified in the plasma samples, of which 394 were considered as high-quality proteins (95% confidential peptides ≥ 2). Further, a total of 25, 19 and 27 different abundant proteins (DAPs) were identified in SD, ND and QD groups, respectively. Gene ontology (GO) classification analysis of all DAPs showed that immune system process (GO:0002376) were the most significant. The pathway enrichment analysis showed that innate immune response (GO:0045087), receptor-mediated endocytosis (GO:0006898) and proteolysis (GO:0006508) were the branch-end terms. Notably, the 15 QD special DAPs were considered as potential markers for identify patient might have quick development COPD, and thus provided more aggressive treatment strategy for these patients.
CONCLUSION: This work provides an insight into global plasma proteome profiles among the SD, ND and QD phenotypes of COPD patients. The most significant GO terms that the DAPs enriched in were immune system related terms. In addition, the 15 QD specific DPAs provided candidates of potential markers to predict the development types of COPD patients.
Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  COPD; Comparative proteomics; Development phenotype; Potential biomarker candidates; iTRAQ

Year:  2020        PMID: 32454159     DOI: 10.1016/j.lfs.2020.117829

Source DB:  PubMed          Journal:  Life Sci        ISSN: 0024-3205            Impact factor:   5.037


  2 in total

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2.  Dynamic Urinary Proteome Changes in Ovalbumin-Induced Asthma Mouse Model Using Data-Independent Acquisition Proteomics.

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  2 in total

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