Confirmation of multiple endotypes in atopic dermatitis based on serum biomarkers

JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY

卷:147

Article

Bakker, Daphne S.^1,2  Nierkens, Stefan²  Knol, Edward F.^1,2  Giovannone, Barbara²  Delemarre, Eveline M.²  van der Schaft, Jorien¹  van Wijk, Femke²  De Bruin-Weller, Marjolein S.¹  Drylewicz, Julia²  Thijs, Judith L.¹ 

[1] Univ Med Ctr Utrecht, Natl Expertise Ctr Atop Dermatitis, Dept Dermatol & Allergol, Utrecht, Netherlands

[2] Univ Med Ctr Utrecht, Ctr Translat Immunol, Utrecht, Netherlands

关键词: Atopic dermatitis;    endotypes;    clusters;    biomarkers;    prediction;    personalized medicine;    principal components analysis;   

DOI  :  10.1016/j.jaci.2020.04.062

来源: Elsevier

【 摘 要 】

Background: Atopic dermatitis (AD) is a highly heterogeneous disease, both clinically and biologically, whereas patients are still being treated according to a one-size-fits-allapproach. Stratification of patients into biomarker-based endotypes is important for future development of personalized therapies. Objective: Our aim was to confirm previously defined serum biomarker-based patient clusters in a new cohort of patients with AD. Methods: A panel of 143 biomarkers was measured by using Luminex technology in serum samples from 146 patients with severe AD (median Eczema Area and Severity Index = 28.3; interquartile range = 25.2-35.3). Principal components analysis followed by unsupervised k-means cluster analysis of the biomarker data was used to identify patient clusters. A prediction model was built on the basis of a previous cohort to predict the 1 of the 4 previously identified clusters to which the patients of our new cohort would belong. Results: Cluster analysis identified 4 serum biomarker-based clusters, 3 of which (clusters B, C, and D) were comparable to the previously identified clusters. Cluster A (33.6%) could be distinguished from the other clusters as being a skin-homing chemokines/IL-1R1-dominantcluster, whereas cluster B (18.5%) was a T(H)1/T(H)2/T(H)17-dominantcluster, cluster C (18.5%) was a T(H)2/T(H)22/PARC-dominantcluster, and cluster D (29.5%) was a T(H)2/eosinophil-inferiorcluster. Additionally, by using a prediction model based on our previous cohort we accurately assigned the new cohort to the 4 previously identified clusters by including only 10 selected serum biomarkers. Conclusion: We confirmed that AD is heterogeneous at the immunopathologic level and identified 4 distinct biomarker-based clusters, 3 of which were comparable with previously identified clusters. Cluster membership could be predicted with a model including 10 serum biomarkers.

【 授权许可】

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