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Comparative proteomic analysis of neutrophils from patients with microscopic polyangiitis and granulomatosis with polyangiitis.

Authors :
Uchida T
Nagai K
Sato T
Iizuka N
Arito M
Takakuwa Y
Nakano H
Ooka S
Kurokawa MS
Suematsu N
Okamoto K
Ozaki S
Kato T
Source :
Journal of proteomics [J Proteomics] 2013 Oct 08; Vol. 91, pp. 259-69. Date of Electronic Publication: 2013 Aug 02.
Publication Year :
2013

Abstract

Both microscopic polyangiitis (MPA) and granulomatosis with polyangiitis (GPA) belong to ANCA-associated vasculitis (AAV), in which neutrophils play a key role in their pathology. In this study, in order to discriminate between MPA and GPA, protein profiles of peripheral blood polymorphonuclear cells (PMNs) of 11 MPA patients and 9 GPA patients and 10 healthy controls (HC) were analyzed by 2D-DIGE. In all the 864 spots detected, intensity of 55 spots was significantly different (p<0.05) among the three groups by ANOVA. 31 out of the 55 spots were identified by mass spectrometry. Orthogonal partial-least-squares-discriminate analysis revealed that the abundance profile of the protein spots discriminated the AAV group from the HC group, and the MPA group from the GPA group completely. 13 protein spots were considered as biomarker candidates to distinguish between MPA and GPA. In those, spots whose intensity was higher in MPA than in GPA included actin with various pI values, while a considerable part of spots whose intensity was higher in GPA were proteins related with the activity of neutrophils. Among the candidate proteins, ROC analysis showed that a combination of neutrophil gelatinase-associated lipocalin and a-kinase anchor protein 7 isoforms beta had a high diagnostic potential.<br />Biological Significance: In this study, protein profiles of polymorphonuclear cells (PMNs) of microscopic polyangiitis (MPA) and granulomatosis with polyangiitis (GPA) patients and healthy controls (HC) were investigated by 2D-DIGE, and MS analysis. As a result, we found that the protein profiles of PMNs were useful for distinguishing between patients (MPA and GPA) and HC, and between patients with MPA and patients with GPA. Especially, we found that the 13 protein spots that consisted of 10 proteins considerably contributed to the discrimination between MPA and GPA. This is the first to demonstrate that protein profiles of PMNs are different among MPA, GPA and healthy control. The 10 proteins we identified in this study would be new biomarkers for the diagnosis of the diseases, and may be reflect the pathology difference between MPA and GPA.<br /> (© 2013.)

Details

Language :
English
ISSN :
1876-7737
Volume :
91
Database :
MEDLINE
Journal :
Journal of proteomics
Publication Type :
Academic Journal
Accession number :
23911962
Full Text :
https://doi.org/10.1016/j.jprot.2013.07.021