Open AccessMachine-learning–driven biomarker discovery for the discrimination between allergic and irritant contact dermatitis
Author(s) -
Vittorio Fortino,
Lukas Wisgrill,
Paulina Werner,
Sari Suomela,
Nina Linder,
Erja Jalonen,
Alina Suomalainen,
Veer Singh Marwah,
Mia Kero,
Maria Pesonen,
Johan Lundin,
Antti Lauerma,
Kristiina AaltoKorte,
Dario Greco,
Harri Alenius,
Nanna Fyhrquist
Publication year - 2020
Publication title -
proceedings of the national academy of sciences of the united states of america
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.011
H-Index - 771
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.2009192117
Subject(s) - irritant contact dermatitis , allergic contact dermatitis , dermatology , medicine , contact dermatitis , allergy , biomarker , atopic dermatitis , immunology , biology , biochemistry
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.