PMID- 28713977
OWN - NLM
STAT- MEDLINE
DCOM- 20180416
LR  - 20180416
IS  - 1791-3004 (Electronic)
IS  - 1791-2997 (Linking)
VI  - 16
IP  - 3
DP  - 2017 Sep
TI  - Analysis of gene expression profile microarray data in complex regional pain 
      syndrome.
PG  - 3371-3378
LID - 10.3892/mmr.2017.6950 [doi]
AB  - The aim of the present study was to predict key genes and proteins associated 
      with complex regional pain syndrome (CRPS) using bioinformatics analysis. The 
      gene expression profiling microarray data, GSE47603, which included peripheral 
      blood samples from 4 patients with CRPS and 5 healthy controls, was obtained from 
      the Gene Expression Omnibus (GEO) database. The differentially expressed genes 
      (DEGs) in CRPS patients compared with healthy controls were identified using the 
      GEO2R online tool. Functional enrichment analysis was then performed using The 
      Database for Annotation Visualization and Integrated Discovery online tool. 
      Protein‑protein interaction (PPI) network analysis was subsequently performed 
      using Search Tool for the Retrieval of Interaction Genes database and analyzed 
      with Cytoscape software. A total of 257 DEGs were identified, including 243 
      upregulated genes and 14 downregulated ones. Genes in the human leukocyte antigen 
      (HLA) family were most significantly differentially expressed. Enrichment 
      analysis demonstrated that signaling pathways, including immune response, cell 
      motion, adhesion and angiogenesis were associated with CRPS. PPI network analysis 
      revealed that key genes, including early region 1A binding protein p300 (EP300), 
      CREB‑binding protein (CREBBP), signal transducer and activator of transcription 
      (STAT)3, STAT5A and integrin alpha M were associated with CRPS. The results suggest 
      that the immune response may therefore serve an important role in CRPS 
      development. In addition, genes in the HLA family, such as HLA‑DQB1 and HLA‑DRB1, 
      may present potential biomarkers for the diagnosis of CRPS. Furthermore, EP300, 
      its paralog CREBBP, and the STAT family genes, STAT3 and STAT5 may be important 
      in the development of CRPS.
FAU - Tan, Wulin
AU  - Tan W
AD  - Department of Anesthesiology, The First Affiliated Hospital of Sun Yat‑sen 
      University, Guangzhou, Guangdong 510080, P.R. China.
FAU - Song, Yiyan
AU  - Song Y
AD  - Zhongshan School of Medicine, Sun Yat‑sen University, Guangzhou, Guangdong 
      510080, P.R. China.
FAU - Mo, Chengqiang
AU  - Mo C
AD  - Department of Urology, The First Affiliated Hospital of Sun Yat‑sen University, 
      Guangzhou, Guangdong 510080, P.R. China.
FAU - Jiang, Shuangjian
AU  - Jiang S
AD  - Department of Urology, The First Affiliated Hospital of Sun Yat‑sen University, 
      Guangzhou, Guangdong 510080, P.R. China.
FAU - Wang, Zhongxing
AU  - Wang Z
AD  - Department of Anesthesiology, The First Affiliated Hospital of Sun Yat‑sen 
      University, Guangzhou, Guangdong 510080, P.R. China.
LA  - eng
PT  - Journal Article
DEP - 20170712
PL  - Greece
TA  - Mol Med Rep
JT  - Molecular medicine reports
JID - 101475259
SB  - IM
MH  - Complex Regional Pain Syndromes/*genetics
MH  - Down-Regulation/genetics
MH  - *Gene Expression Profiling
MH  - Gene Ontology
MH  - Gene Regulatory Networks
MH  - Humans
MH  - *Oligonucleotide Array Sequence Analysis
MH  - Protein Interaction Maps/genetics
MH  - Up-Regulation/genetics
EDAT- 2017/07/18 06:00
MHDA- 2018/04/17 06:00
CRDT- 2017/07/18 06:00
PHST- 2016/04/06 00:00 [received]
PHST- 2017/03/16 00:00 [accepted]
PHST- 2017/07/18 06:00 [pubmed]
PHST- 2018/04/17 06:00 [medline]
PHST- 2017/07/18 06:00 [entrez]
AID - 10.3892/mmr.2017.6950 [doi]
PST - ppublish
SO  - Mol Med Rep. 2017 Sep;16(3):3371-3378. doi: 10.3892/mmr.2017.6950. Epub 2017 Jul 
      12.