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

Clinical Rheumatology volume 40, pages 1381–1391 (2021)Cite this article

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.

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Funding

This work was supported by the National Natural Science Foundation of China (81572199) and the Tianjin Application Foundation and Cutting Edge Technology Research Project (15JCYBYC50600).

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Author notes

  1. Jiange He and Jiqiang Tang contributed equally to this work.

Affiliations

  1. Logistics University of Chinese Armed Police Force, Tianjin, China

    Jiange He & Dong Jia

  2. Orthopedics Department, Characteristic Medical Center of People’s Armed Police Force, Tianjin, China

    Jiqiang Tang & Tong Li

  3. The Second Affiliated Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China

    Qijin Feng

  4. Orthopedics Department, Tianjin Third Central Hospital, Tianjin, China

    Kainan Wu

  5. PLA 960th Hospital, Jinan, China

    Kairui Yang

  6. Orthopedics Department, Tianjin First Central Hospital, 24 Fukang Road, Nankai District, Tianjin, 300000, China

    Qun Xia

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  1. Jiange He
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  2. Jiqiang Tang
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  3. Qijin Feng
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  4. Tong Li
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  5. Kainan Wu
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  6. Kairui Yang
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  7. Dong Jia
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  8. Qun Xia
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Corresponding author

Correspondence to Qun Xia.

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He, J., Tang, J., Feng, Q. et al. Weighted gene co-expression network analysis identifies RHOH and TRAF1 as key candidate genes for psoriatic arthritis. Clin Rheumatol 40, 1381–1391 (2021). https://doi.org/10.1007/s10067-020-05395-8

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  • DOI: https://doi.org/10.1007/s10067-020-05395-8

Keywords

  • Computational Biology
  • Gene expression
  • Psoriatic arthritis
  • WGCNA