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Identification of key genes in rheumatoid arthritis and osteoarthritis based on bioinformatics analysis.

Abstract Rheumatoid arthritis (RA) and osteoarthritis (OA) comprise the most common forms of arthritis. The aim of this study was to identify differentially expressed genes (DEGs) and associated biological processes between RA and OA using a bioinformatics approach to elucidate their potential pathogenesis.The gene expression profiles of the GSE55457 datasets, originally produced through use of the high-throughput Affymetrix Human Genome U133A Array, were downloaded from the Gene Expression Omnibus (GEO) database. The GSE55457 dataset contains information from 33 samples, including 10 normal control (NC) samples, 13 RA samples, and 10 OA samples. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed to identify functional categories and associated molecular and biochemical pathways, respectively, for the identified DEGs, and a protein-protein interaction (PPI) network of the DEGs was constructed using Cytoscape software.GO and KEGG results suggested that several biological pathways (ie, "immune response," "inflammation," and "osteoclast differentiation") are commonly involved in the development of both RA and OA, whereas several other pathways (eg, "MAPK signaling pathway," and "ECM-receptor interaction") presented significant differences between these disorders.This study provides further insights into the underlying pathogenesis of RA and OA, which may facilitate the diagnosis and treatment of these diseases.
PMID
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Authors

Mayor MeshTerms
Keywords
Journal Title medicine
Publication Year Start




PMID- 29851858
OWN - NLM
STAT- MEDLINE
DCOM- 20180612
LR  - 20180612
IS  - 1536-5964 (Electronic)
IS  - 0025-7974 (Linking)
VI  - 97
IP  - 22
DP  - 2018 Jun
TI  - Identification of key genes in rheumatoid arthritis and osteoarthritis based on
      bioinformatics analysis.
PG  - e10997
LID - 10.1097/MD.0000000000010997 [doi]
AB  - Rheumatoid arthritis (RA) and osteoarthritis (OA) comprise the most common forms 
      of arthritis. The aim of this study was to identify differentially expressed
      genes (DEGs) and associated biological processes between RA and OA using a
      bioinformatics approach to elucidate their potential pathogenesis.The gene
      expression profiles of the GSE55457 datasets, originally produced through use of 
      the high-throughput Affymetrix Human Genome U133A Array, were downloaded from the
      Gene Expression Omnibus (GEO) database. The GSE55457 dataset contains information
      from 33 samples, including 10 normal control (NC) samples, 13 RA samples, and 10 
      OA samples. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes
      pathway (KEGG) enrichment analyses were performed to identify functional
      categories and associated molecular and biochemical pathways, respectively, for
      the identified DEGs, and a protein-protein interaction (PPI) network of the DEGs 
      was constructed using Cytoscape software.GO and KEGG results suggested that
      several biological pathways (ie, "immune response," "inflammation," and
      "osteoclast differentiation") are commonly involved in the development of both RA
      and OA, whereas several other pathways (eg, "MAPK signaling pathway," and
      "ECM-receptor interaction") presented significant differences between these
      disorders.This study provides further insights into the underlying pathogenesis
      of RA and OA, which may facilitate the diagnosis and treatment of these diseases.
FAU - Zhu, Naiqiang
AU  - Zhu N
AD  - Second Department of Spinal Surgery, the Affiliated Hospital of Chengde Medical
      College.
FAU - Hou, Jingyi
AU  - Hou J
AD  - Hebei Key Laboratory of Study and Exploitation of Chinese Medicine, Chengde
      Medical College.
FAU - Wu, Yuanhao
AU  - Wu Y
AD  - Department of Rheumatology and Immunology, First Teaching Hospital of Tianjin
      University of Traditional Chinese Medicine, Tianjin.
FAU - Li, Geng
AU  - Li G
AD  - China-Japan Friendship Hospital, Beijing, China.
FAU - Liu, Jinxin
AU  - Liu J
AD  - Hebei Key Laboratory of Study and Exploitation of Chinese Medicine, Chengde
      Medical College.
AD  - Key Lab of Chinese Medicine Resources Conservation, State Administration of
      Traditional Chinese Medicine of the People's Republic of China, Institute of
      Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union
      Medical College, Beijing.
FAU - Ma, GuiYun
AU  - Ma G
AD  - Second Department of Spinal Surgery, the Affiliated Hospital of Chengde Medical
      College.
FAU - Chen, Bin
AU  - Chen B
AD  - Second Department of Spinal Surgery, the Affiliated Hospital of Chengde Medical
      College.
FAU - Song, Youxin
AU  - Song Y
AD  - Second Department of Spinal Surgery, the Affiliated Hospital of Chengde Medical
      College.
LA  - eng
PT  - Journal Article
PT  - Observational Study
PL  - United States
TA  - Medicine (Baltimore)
JT  - Medicine
JID - 2985248R
SB  - AIM
SB  - IM
MH  - Arthritis, Rheumatoid/*genetics
MH  - Computational Biology/*methods
MH  - Databases, Genetic
MH  - Gene Expression Profiling/*methods
MH  - Gene Ontology
MH  - Genetic Predisposition to Disease
MH  - Humans
MH  - Osteoarthritis/*genetics
MH  - Signal Transduction
EDAT- 2018/06/01 06:00
MHDA- 2018/06/13 06:00
CRDT- 2018/06/01 06:00
PHST- 2018/06/01 06:00 [entrez]
PHST- 2018/06/01 06:00 [pubmed]
PHST- 2018/06/13 06:00 [medline]
AID - 10.1097/MD.0000000000010997 [doi]
AID - 00005792-201806010-00086 [pii]
PST - ppublish
SO  - Medicine (Baltimore). 2018 Jun;97(22):e10997. doi: 10.1097/MD.0000000000010997.