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Investigation of serum biomarkers in primary gout patients using iTRAQ-based screening


1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14

 

  1. Department of Rheumatology, Ningbo no. 2 Hospital, Zhejiang, China.
  2. Department of Rheumatology, Ningbo no. 2 Hospital, Zhejiang, China. nbdeyycy@163.com
  3. Stem Cell and Regenerative Medicine Laboratory, Ningbo no. 2 Hospital, Zhejiang, China.
  4. Medical School, Ningbo University, Zhejiang, China.
  5. Medical School, Ningbo University, Zhejiang, China.
  6. Medical School, Ningbo University, Zhejiang, China.
  7. Medical School, Ningbo University, Zhejiang, China.
  8. Department of Rheumatology, Ningbo no. 2 Hospital, Zhejiang, China.
  9. Department of Rheumatology, Ningbo no. 2 Hospital, Zhejiang, China.
  10. Department of Rheumatology, Ningbo no. 2 Hospital, Zhejiang, China.
  11. Department of Rheumatology, Ningbo no. 2 Hospital, Zhejiang, China.
  12. Department of Rheumatology, Ningbo no. 2 Hospital, Zhejiang, China.
  13. Department of Rheumatology, Ningbo no. 2 Hospital, Zhejiang, China.
  14. Stem Cell and Regenerative Medicine Laboratory, Ningbo no. 2 Hospital, Zhejiang, China.

CER10908
2018 Vol.36, N°5
PI 0791, PF 0797
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PMID: 29600944 [PubMed]

Received: 22/10/2017
Accepted : 09/01/2018
In Press: 21/03/2018
Published: 26/09/2018

Abstract

OBJECTIVES:
Primary gout is a major disease that affects human health; however, its pathogenesis is not well known. The purpose of this study was to identify biomarkers to explore the underlying mechanisms of primary gout.
METHODS:
We used the isobaric tags for relative and absolute quantitation (iTRAQ) technique combined with liquid chromatography-tandem mass spectrometry to screen differentially expressed proteins between gout patients and controls. We also identified proteins potentially involved in gout pathogenesis by analysing biological processes, cellular components, molecular functions, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and protein-protein interactions. We further verified some samples using enzyme-linked immunosorbent assay (ELISA). Statistical analyses were carried out using SPSS v. 20.0 and ROC (receiver operating characterstic) curve analyses were carried out using Medcalc software. Two-sided p-values <0.05 were deemed to be statistically significant for all analyses.
RESULTS:
We identified 95 differentially expressed proteins (50 up-regulated and 45 down-regulated), and selected nine proteins (α-enolase (ENOA), glyceraldehyde-3-phosphate dehydrogenase (G3P), complement component C9 (CO9), profilin-1 (PROF1), lipopolysaccharide-binding protein (LBP), tubulin beta-4A chain (TBB4A), phosphoglycerate kinase (PGK1), glucose-6-phosphate isomerase (G6PI), and transketolase (TKT)) for verification. This showed that the level of TBB4A was significantly higher in primary gout than in controls (p=0.023).
CONCLUSIONS:
iTRAQ technology was useful in the selection of differentially expressed proteins from proteomes, and provides a strong theoretical basis for the study of biomarkers and mechanisms in primary gout. In addition, TBB4A protein may be associated with primary gout.

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