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Published in: Arthritis Research & Therapy 1/2019

Open Access 01-12-2019 | Systemic Lupus Erythematosus | Research article

Performance of cytokine models in predicting SLE activity

Authors: Nopparat Ruchakorn, Pintip Ngamjanyaporn, Thanitta Suangtamai, Thanuchporn Kafaksom, Charin Polpanumas, Veerachat Petpisit, Trairak Pisitkun, Prapaporn Pisitkun

Published in: Arthritis Research & Therapy | Issue 1/2019

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Abstract

Background

Identification of universal biomarkers to predict systemic lupus erythematosus (SLE) flares is challenging due to the heterogeneity of the disease. Several biomarkers have been reported. However, the data of validated biomarkers to use as a predictor for lupus flares show variation. This study aimed to identify the biomarkers that are sensitive and specific to predict lupus flares.

Methods

One hundred and twenty-four SLE patients enrolled in this study and were prospectively followed up. The evaluation of disease activity achieved by the SLE disease activity index (SLEDAI-2K) and clinical SLEDAI (modified SLEDAI). Patients with active SLE were categorized into renal or non-renal flares. Serum cytokines were measured by multiplex bead-based flow cytometry. The correlation and logistic regression analysis were performed.

Results

Levels of IFN-α, MCP-1, IL-6, IL-8, and IL-18 significantly increased in active SLE and correlated with clinical SLEDAI. Complement C3 showed a weakly negative relationship with IFN-α and IL-18. IL-18 showed the highest positive likelihood ratios for active SLE. Multiple logistic regression analysis showed that IL-6, IL-8, and IL-18 significantly increased odds ratio (OR) for active SLE at baseline while complement C3 and IL-18 increased OR for active SLE at 12 weeks. IL-18 and IL-6 yielded higher sensitivity and specificity than anti-dsDNA and C3 to predict active renal and active non-renal, respectively.

Conclusion

The heterogeneity of SLE pathogenesis leads to different signaling mechanisms and mediates through several cytokines. The monitoring of cytokines increases the sensitivity and specificity to determine SLE disease activity. IL-18 predicts the risk of active renal SLE while IL-6 and IL-8 predict the risk of active non-renal. The sensitivity and specificity of these cytokines are higher than the anti-dsDNA or C3. We propose to use the serum level of IL-18, IL-6, and IL-8 to monitor SLE disease activity in clinical practice.
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Metadata
Title
Performance of cytokine models in predicting SLE activity
Authors
Nopparat Ruchakorn
Pintip Ngamjanyaporn
Thanitta Suangtamai
Thanuchporn Kafaksom
Charin Polpanumas
Veerachat Petpisit
Trairak Pisitkun
Prapaporn Pisitkun
Publication date
01-12-2019
Publisher
BioMed Central
Published in
Arthritis Research & Therapy / Issue 1/2019
Electronic ISSN: 1478-6362
DOI
https://doi.org/10.1186/s13075-019-2029-1

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