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Dermatomyositis: immunological landscape, biomarkers, and potential candidate drugs

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Abstract

Introduction

Dermatomyositis (DM) is a rare inflammatory disease characterized by the invasion of the skin and muscles. Environmental, genetic, and immunological factors contribute to disease pathology. To date, no bioinformatics studies have been conducted on the potential pathogenic genes and immune cell infiltration in DM. Therefore, we aimed to identify differentially expressed genes (DEGs) and immune cells, as well as potential pathogenic genes and immune characteristics, which may be useful for the diagnosis and treatment of DM.

Method

GSE1551, GSE5370, GSE39454, and GSE48280 from Gene Expression Omnibus were included in our study. Limma, ClusterProfiler, and Kyoto Encyclopedia of Genes and Genomes were used to identify DEGs, Gene Ontology (GO), and perform pathway analyses, respectively. Cytoscape was used to construct the protein-protein interaction (PPI) network. Small-molecule drugs were identified using a connectivity map (CMap), and the TIMER database was used to identify infiltrating cells.

Results

DEG analysis identified 12 downregulated and 163 upregulated genes. GO analysis showed that DEGs were enriched in immune-related pathways. Ten hub genes were identified from the PPI network. Additionally, CMap analysis showed that caffeic acid, sulfaphenazole, molindone, tiabendazole, and bacitracin were potential small-molecule drugs with therapeutic significance. We identified eight immune cells with differential infiltration in patients with DM and controls. Finally, we constructed a powerful diagnostic model based on memory B cells, M1, and M2 macrophages.

Conclusions

This study explored the potential molecular mechanism and immunological landscape of DM and may guide future research and treatment of DM.

Key Points

• We explored the molecular mechanism and immunological landscape of dermatomyositis.

• GO analysis showed that DEGs were enriched in immune-related pathways.

• We predicted small-molecular drugs with potential therapeutic significance based on bioanalytical techniques.

• We identified six immune cells with differential infiltration in patients with DM and controls.

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Data availability

All data generated or analyzed during this study are included in this published article.

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  1. Ruxue Yin and Gangjian Wang contributed equally to this work.

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  1. Department of Rheumatology, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe East Road, Zhengzhou, 450052, Henan, China

    Ruxue Yin, Lei Zhang, Tianfang Li & Shengyun Liu

  2. Department of Oncology, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe East Road, Zhengzhou, 450052, China

    Gangjian Wang

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Conceptualization: Ruxue Yin, Gangjian Wang, and Shengyun Liu; data curation: Ruxue Yin and Lei Zhang; formal analysis: Ruxue Yin, Gangjian Wang, and Shengyun Liu; methodology: Ruxue Yin, Gangjian Wang, and Tianfang Li; resources: Gangjian Wang, Lei Zhang, and Tianfang Li; supervision: Ruxue Yin, Tianfang Li, and Shengyun Liu; writing—original draft: Ruxue Yin and Shengyun Liu; writing—review and editing: Ruxue Yin, Gangjian Wang, and Shengyun Liu.

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Yin, R., Wang, G., Zhang, L. et al. Dermatomyositis: immunological landscape, biomarkers, and potential candidate drugs. Clin Rheumatol 40, 2301–2310 (2021). https://doi.org/10.1007/s10067-020-05568-5

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