Machine Learning–Based Deep Phenotyping of Atopic Dermatitis

Abstract

IMPORTANCE Atopic dermatitis (AD) is the most common chronic inflammatory skin disease and is driven by a complex pathophysiology underlying highly heterogeneous phenotypes. Current advances in precision medicine emphasize the need for stratification. OBJECTIVE To perform deep phenotyping and identification of severity-associated factors in adolescent and adult patients with AD. DESIGN, SETTING, AND PARTICIPANTS Cross-sectional data from the baseline visit of a prospective longitudinal study investigating the phenotype among inpatients and outpatients with AD from the Department of Dermatology and Allergy of the University Hospital Bonn enrolled between November 2016 and February 2020.MAIN OUTCOMES AND MEASURES Patients were stratified by severity groups using the Eczema Area and Severity Index (EASI). The associations of 130 factors with AD severity were analyzed applying a machine learning-gradient boosting approach with cross-validationbased tuning as well as multinomial logistic regression.RESULTS A total of 367 patients (157 male [42.8%]; mean [SD] age, 39 [17] years; 94% adults) were analyzed. Among the participants, 177 (48.2%) had mild disease (EASI Յ7), 120 (32.7%) had moderate disease (EASI >7 and Յ 21), and 70 (19.1%) had severe disease (EASI >21).

IL‐13, periostin and dipeptidyl‐peptidase‐4 reveal endotype‐phenotype associations in atopic dermatitis

“…99 Levels of eosinophils and tIgE are established biomarkers for allergic inflammation and sensitization in AD. 53 The here found correlations of IL-13 and periostin with AD severity and eosinophils align with previous studies, 37,41,46,47,83 as well as the correlation of IL-13 with tIgE. 37 In our German AD cohort, also periostin correlated with tIgE, consistent with reports for Czech patients with asthma, 100 but not for Japanese AD patients.…”

“…Levels of eosinophils and tIgE are established biomarkers for allergic inflammation and sensitization in AD 53 . The here found correlations of IL‐13 and periostin with AD severity and eosinophils align with previous studies, 37,41,46,47,83 as well as the correlation of IL‐13 with tIgE 37 .…”

“…93,94 AA is a frequent comorbidity of AD. 53,92,95,96 In lesional AA scalps, an upregulation of periostin and IL-13 was demonstrated along with other differentially expressed genes. 91 In the heart, periostin contributes to cardiac development and remodeling in CVD such as heart failure or myocardial infarction.…”

“…We analyzed cross‐sectional baseline data of 420 subjects ≥12 years enrolled in the ProRAD 52,53 study after written informed consent: 373 AD patients fulfilling the Hanifin and Rajka criteria with only topical treatment and 47 non‐atopic controls. Exclusion criteria were systemic treatment of AD ≤30 days and remission.…”

Artificial Intelligence: Exploring the Future of Innovation in Allergy Immunology

“…ML models trained on patient-reported data or serum biomarker measurements have been used to predict future AD severity with SCORAD [ 38 – 40 ]. Researchers have employed ML to identify which clinical and demographic characteristics are most associated with severe AD to better understand which patients are at the highest risk [ 41 ].…”