impact factor
logo
 

Full Papers

 

Systematic analysis of the molecular mechanisms of methotrexate therapy for rheumatoid arthritis using text mining


1, 2, 3, 4, 5, 6

 

  1. Department of Clinical Epidemiology and Evidence-based Medicine, the First Affiliated Hospital, China Medical University, Shenyang, China.
  2. Department of Clinical Epidemiology and Evidence-based Medicine, the First Affiliated Hospital, China Medical University, Shenyang, China.
  3. Department of Clinical Epidemiology and Evidence-based Medicine, the First Affiliated Hospital, China Medical University, Shenyang, China.
  4. Department of Clinical Epidemiology and Evidence-based Medicine, and Department of Medical Record Management Center, the First Affiliated Hospital, China Medical University, Shenyang, China. fulingyucmu@sina.com
  5. Department of Clinical Epidemiology and Evidence-based Medicine, the First Affiliated Hospital, China Medical University, and Department of Medical Informatics, China Medical University, China.
  6. Department of Medical Record Management Center, the First Af liated Hospital, China Medical University, Shenyang, China.

CER13031
Full Papers

purchase article

PMID: 33124557 [PubMed]

Received: 20/12/2019
Accepted : 06/07/2020
In Press: 17/10/2020

Abstract

OBJECTIVES:
The purpose of this study was to determine the expression of related genes in patients with rheumatoid arthritis (RA) treated with methotrexate (MTX), to identify hub genes, and to systematically analyse the functions, pathways, and networks of these genes.
METHODS:
The PubMed identifiers (PMIDs) of relevant publications were obtained from the PubMed database, and gene data were extracted from these documents using the text mining software PubTator. The Database for Annotation, Visualization and Integrated Discovery (DAVID) was used to obtain enriched Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway information. In addition, the STRING database was used to construct a protein-protein interaction (PPI) network. Genes with which at least 10 other genes interacted were identified as hub genes.
RESULTS:
A total of 216 genes were identified as being associated with treatment efficacy for MTX, of which 14 pathways exhibited significant correlation (p<0.05, FDR<0.05). In addition, the constructed MTX treatment-related network consisted of 267 interactions. Fourteen genes were found to interact with at least 10 other genes (p<0.05, FDR<0.05) and identified as hub genes in the PPI network. These genes were JAK1, MAPK1, JUN, AKT1, MAPK14, MAPK8, FGB, FN1, ALB, B2M, IL2RB, GGH, IL2RA, and TP53.
CONCLUSIONS:
This study will assist in elucidating the molecular mechanisms associated with the treatment efficacy of MTX for RA and provide a scientific rationale for guiding patient medication. However, the relationship between particular genes and the efficacy of MTX treatment for RA patients requires additional investigation.

Rheumatology Article

Rheumatology Addendum