Imperial College London
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Professor Reiko J. Tanaka

Faculty of Engineering, Department of Bioengineering

Professor of Computational Systems Biology & Medicine
 
 
 
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Contact

 

+44 (0)20 7594 6374r.tanaka Website

 
 
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Location

 

RSM 3.10Royal School of MinesSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Holm:2021:10.1159/000514503,
author = {Holm, JG and Hurault, G and Agner, T and Clausen, ML and Kezic, S and Tanaka, RJ and Thomsen, SF},
doi = {10.1159/000514503},
journal = {Dermatology: international journal for clinical and investigative dermatology},
pages = {513--520},
title = {Immunoinflammatory biomarkers in serum are associated with disease severity in atopic dermatitis},
url = {http://dx.doi.org/10.1159/000514503},
volume = {237},
year = {2021}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Background: A growing body of evidence links various biomarkers to atopic dermatitis (AD). Still, little is known about the association of specific biomarkers to disease characteristics and severity in AD. Objective: To explore the relationship between various immunological markers in the serum and disease severity in a hospital cohort of AD patients. Methods: Outpatients with AD referred to the Department of Dermatology, Bispebjerg Hospital, Copenhagen, Denmark, were divided into groups based on disease severity (SCORAD). Serum levels of a preselected panel of immunoinflammatory biomarkers were tested for association with disease characteristics. Two machine learning models were developed to predict SCORAD from the measured biomarkers. Results: A total of 160 patients with AD were included; 53 (33.1%) with mild, 73 (45.6%) with moderate, and 34 (21.3%) with severe disease. Mean age was 29.2 years (range 6–70 years) and 84 (52.5%) were females. Numerous biomarkers showed a statistically significant correlation with SCORAD, with the strongest correlations seen for CCL17/thymus and activation-regulated chemokine (chemokine ligand-17/TARC) and CCL27/cutaneous T cell-attracting-chemokine (CTACK; Spearman R of 0.50 and 0.43, respectively, p < 0.001). Extrinsic AD patients were more likely to have higher mean SCORAD (p < 0.001), CCL17 (p < 0.001), CCL26/eotaxin-3 (p < 0.001), and eosinophil count (p < 0.001) than intrinsic AD patients. Predictive models for SCORAD identified CCL17, CCL27, serum total IgE, IL-33, and IL-5 as the most important predictors for SCORAD, but with weaker associations than single cytokines. Conclusions: Specific immunoinflammatory biomarkers in the serum, mainly of the Th2 pathway, are correlated with disease severity in patients with AD. Predictive models identified biomarkers associated with disease severity but this finding warrants further investigation.
AU  - Holm,JG
AU  - Hurault,G
AU  - Agner,T
AU  - Clausen,ML
AU  - Kezic,S
AU  - Tanaka,RJ
AU  - Thomsen,SF
DO  - 10.1159/000514503
EP  - 520
PY  - 2021///
SN  - 1018-8665
SP  - 513
TI  - Immunoinflammatory biomarkers in serum are associated with disease severity in atopic dermatitis
T2  - Dermatology: international journal for clinical and investigative dermatology
UR  - http://dx.doi.org/10.1159/000514503
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000630113900001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - http://hdl.handle.net/10044/1/87479
VL  - 237
ER  -
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