Gene Co-expression Network Analysis Associated with Acupuncture Treatment of Rheumatoid Arthritis: An Animal Model

Dea Ravn, Afsaneh Mohammadnejad, Kemal Sabaredzovic, Weilong Li, Jesper Lund, Shuxia Li, Anders Jørgen Svendsen, Veit Schwämmle, Qihua Tan*

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Abstract

Background: Classical acupuncture is being used in the treatment of rheumatoid arthritis (RA). To explore the biological response to acupuncture, a network-based analysis was performed on gene expression data collected from an animal model of RA treated with acupuncture. Methods: Gene expression data were obtained from published microarray studies on blood samples from rats with collagen induced arthritis (CIA) and non-CIA rats, both treated with manual acupuncture. The weighted gene co-expression network analysis was performed to identify gene clusters expressed in association withacupuncture treatment time and RA status. Gene ontology and pathway analyses were applied for functional annotation and network visualization. Results: A cluster of 347 genes were identified that differentially downregulated expression in association with acupuncture treatment over time; specifically in rats with CIA with module-RA correlation at 1 hour after acupuncture (-0.27; p < 0.001) and at 34 days after acupuncture (-0.33; p < 0.001). Functional annotationshowed highly significant enrichment of porphyrin-containing compound biosynthetic processes (p < 0.001). The network-based analysis also identified a module of 140 genes differentially expressed between CIA and non-CIA in rats (p < 0.001). This cluster of genes was enriched for antigen processing and presentation of exogenous peptide antigen (p < 0.001). Other functional gene clusters previously reported in earlier studies were also observed. Conclusion: The identified gene expression networks and their hub-genes could help with the understanding of mechanisms involved in the pathogenesis of RA, as well understanding the effects of acupuncture treatment of RA.
OriginalsprogEngelsk
TidsskriftJournal of Acupuncture Research
Vol/bind37
Udgave nummer2
Sider (fra-til)128-135
Antal sider8
ISSN1414-431X
DOI
StatusUdgivet - 2020

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