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Hierarchical cluster analysis of cytokine profiles reveals a cutaneous vasculitis-associated subgroup in dermatomyositis

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Abstract

Objectives

Dermatomyositis (DM) is a chronic inflammatory autoimmune disease with notable heterogeneity. The intent of this study was to explore the difference in cytokine profiles of different subsets in DM based on the disease activity and myositis-specific antibodies, and to identify the clinical phenotypes associated with different cytokine profiles.

Methods

Serum levels of 34 cytokines were prospectively measured in 47 consecutive DM patients and healthy controls. Concentrations of the cytokines were compared between the active and stable groups. Univariate and multivariate logistic regression models were used to identify the cytokines associated with DM disease activity. The cytokine profiles of anti-MDA5 and anti-TIF1γ subsets were compared, and the correlation analysis was performed between the elevated cytokines and clinical parameters in the two subsets. Hierarchical cluster analysis was used to establish clinical-cytokine subgroups in DM.

Results

Serum levels of MIP-1α, IP-10, IL-8, IL-1RA, MCP-1, GRO-α, and IL-22 were significantly higher in DM patients compared with healthy controls. IP-10, IL-6, IL-1RA, IFN-α, and MCP-1 were significantly elevated in the DM-active subset than the DM-stable subset. The combination of three cytokines (IP-10, IL-1RA, and MCP-1) had a better performance in differentiating between the active subset and the stable subset than the conventional inflammatory markers. SDF-1α, IP-10, IL-7, IL-17A, RANTES, IFN-γ, TNF-α, MIP-1β, IFN-α, MCP-1, GRO-α, and IL-1α were significantly higher in the anti-MDA5 subset than in the TIF1γ subset. Cluster analysis revealed a hypercytokinemic-vasculitis subgroup in patients with DM.

Conclusions

Multiple cytokine signatures were depicted in different subsets of DM. A vasculitis-associated subgroup was firstly identified in DM with regards of cytokinome and deserves further mechanistic study.

Key Points

• The multivariate regression model of three cytokines (IP-10, IL-1RA, and MCP-1) could be a promising tool for distinguishing between the active and stable subset in DM.

• Cytokine profiles of anti-MDA5-DM and anti-TIF1γ-DM were compared to identify the immunopathological differences between the two subsets.

• Cluster analysis revealed a hypercytokinemic-vasculitis subgroup in patients with DM.

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Availability of data and material

The datasets used and/or analyzed during the current study are available from the corresponding authors on reasonable request.

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Acknowledgments

We would like to thank Dr. Huiyi Zhu (Peking Union Medical College Hospital, China) for sample collection.

Funding

This work was supported by the 13th Five-Year National Science and Technology Major Project for New Drugs of the Ministry of Science and Technology of China (2019ZX09734001-002-004), National Natural Science Foundation of China (81471615, 81601430), Medical and Health Science and Technology Innovation Project of Chinese Academy of Medical Sciences (2019-I2M-2-008).

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Contributions

All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Jingjing Bai, Chanyuan Wu, Danli Zhong, and Dong Xu. The first draft of the manuscript was written by Jingjing Bai, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Qian Wang and Xiaofeng Zeng were responsible for project administration and funding acquisition. Qian Wang and Xiaofeng Zeng contributed equally.

Corresponding authors

Correspondence to Qian Wang or Xiaofeng Zeng.

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This study was approved by the Peking Union Medical College Hospital Ethics Committee according to the principles of the Declaration of Helsinki, and informed consent was obtained from each patient.

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Bai, J., Wu, C., Zhong, D. et al. Hierarchical cluster analysis of cytokine profiles reveals a cutaneous vasculitis-associated subgroup in dermatomyositis. Clin Rheumatol 40, 999–1008 (2021). https://doi.org/10.1007/s10067-020-05339-2

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