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Significance Contact dermatitis is an inflammatory skin disorder that arises from direct skin contact with irritants or allergens. Representing over 90% of occupational skin disorders, it has a considerable socioeconomic impact, and patients suffering from contact dermatitis can develop a notable physical handicap. Current diagnostic regimes rely on allergy testing, exposure specification, and follow-up visits. However, distinguishing the clinical phenotype of irritant and allergic contact dermatitis, which is important for appropriate therapeutic strategies, remains challenging. This study identifies and validates biomarkers to distinguish allergic and irritant contact dermatitis in human skin, to be used for the development of novel diagnostic methods and to guide clinical diagnosis.

Machine-learning–driven biomarker discovery for the discrimination between allergic and irritant contact dermatitis