Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Jan;147(1):189-198.
doi: 10.1016/j.jaci.2020.04.062. Epub 2020 Jun 8.

Confirmation of multiple endotypes in atopic dermatitis based on serum biomarkers

Daphne S Bakker  1 , Stefan Nierkens  2 , Edward F Knol  3 , Barbara Giovannone  2 , Eveline M Delemarre  2 , Jorien van der Schaft  4 , Femke van Wijk  2 , Marjolein S de Bruin-Weller  4 , Julia Drylewicz  2 , Judith L Thijs  4
Affiliations
Free article

Confirmation of multiple endotypes in atopic dermatitis based on serum biomarkers

Daphne S Bakker et al. J Allergy Clin Immunol. 2021 Jan.
Free article

Abstract

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-all" approach. 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-dominant" cluster, whereas cluster B (18.5%) was a "TH1/TH2/TH17-dominant" cluster, cluster C (18.5%) was a "TH2/TH22/PARC-dominant" cluster, and cluster D (29.5%) was a "TH2/eosinophil-inferior" cluster. 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.

Keywords: Atopic dermatitis; biomarkers; clusters; endotypes; personalized medicine; prediction; principal components analysis.

PubMed Disclaimer

Publication types

LinkOut - more resources