Weighted gene co-expression network analysis identifies RHOH and TRAF1 as key candidate genes for psoriatic arthritis

Clin Rheumatol. 2021 Apr;40(4):1381-1391. doi: 10.1007/s10067-020-05395-8. Epub 2020 Sep 21.

Abstract

Background: Psoriatic arthritis (PsA) is inflammatory arthritis associated with psoriasis, which involves the axial joint and the distal interphalangeal joints. Its clinical features are varied, often resulting in delayed diagnosis and treatment. Improved knowledge about disease mechanisms will catalyze the rapid development of effective targeted therapies for this disease. The perturbations in the gene co-expression network may not be detected by the differential expression analysis of the microarray. This study aims to identify key modules and hub genes in psoriatic arthritis-applied WGCNA (weighted gene co-expression network analysis) on a microarray.

Methods: This study downloaded the array data of GSE61281 from the gene expression overview (GEO) database, which includes 20 psoriatic arthritis samples and 12 healthy controls. The analysis was performed with the WGCNA package. Gene ontology (GO) annotation and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on these key modules. Candidate hub genes were identified using GS and MM measures, Cytoscape, and the online database STRING.

Results: A total of 10 co-expression modules were constructed. The lightcyan module was identified as the key module. GO and KEGG pathway analyses were mainly enriched in dephosphorylation, regulation of small GTPase-mediated signal transduction, Ras signaling pathway, MAPK signaling pathway, and vascular smooth muscle contraction. Two hub genes, RHOH/TRAF1, were selected.

Conclusions: This finding may indicate that RHOH/TRAF1 play a critical role in the pathogenesis of PsA. This is one of the first studies in PsA using WGCNA, which may provide a new research direction for further understanding of the molecular mechanism and clinical application of PsA. Key points • The WGCNA method was applied to the expression profile microarray of psoriatic arthritis and the co-expression module was constructed. • Identify the key modules by combining the onset time of psoriasis in patients with psoriatic arthritis. • Three screening methods are used to identify and verify hub genes of key modules.

Keywords: Computational Biology; Gene expression; Psoriatic arthritis; WGCNA.

MeSH terms

  • Arthritis, Psoriatic* / genetics
  • Gene Expression Profiling
  • Gene Ontology
  • Gene Regulatory Networks
  • Humans
  • TNF Receptor-Associated Factor 1
  • Transcription Factors
  • rho GTP-Binding Proteins

Substances

  • RhoH protein, human
  • TNF Receptor-Associated Factor 1
  • Transcription Factors
  • rho GTP-Binding Proteins