Unique molecular signatures typify skin inflammation induced by chemical allergens and irritants
Background Skin exposure to chemicals may induce an inflammatory disease known as contact dermatitis (CD). Distinguishing the allergic and irritant forms of CD often proves challenging in the clinic. Methods To characterize the molecular signatures of chemical‐induced skin inflammation, we conducted...
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Veröffentlicht in: | Allergy (Copenhagen) 2021-12, Vol.76 (12), p.3697-3712 |
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Sprache: | eng |
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Zusammenfassung: | Background
Skin exposure to chemicals may induce an inflammatory disease known as contact dermatitis (CD). Distinguishing the allergic and irritant forms of CD often proves challenging in the clinic.
Methods
To characterize the molecular signatures of chemical‐induced skin inflammation, we conducted a comprehensive transcriptomic analysis on the skin lesions of 47 patients with positive patch tests to reference contact allergens and nonallergenic irritants.
Results
A clear segregation was observed between allergen‐ and irritant‐induced gene profiles. Distinct modules pertaining to the epidermal compartment, metabolism, and proliferation were induced by both contact allergens and irritants; whereas only contact allergens prompted strong activation of adaptive immunity, notably of cytotoxic T‐cell responses. Our results also confirmed that: (a) unique pathways characterize allergen‐ and irritant‐induced dermatitis; (b) the intensity of the clinical reaction correlates with the magnitude of immune activation. Finally, using a machine‐learning approach, we identified and validated several minimal combinations of biomarkers to distinguish contact allergy from irritation.
Conclusion
These results highlight the value of molecular profiling of chemical‐induced skin inflammation for improving the diagnosis of allergic versus irritant contact dermatitis.
The core transcriptome of allergen‐ and irritant‐induced reactions consists of cytotoxic T‐cell‐and tissue remodeling‐related transcripts, respectively. The magnitude of gene activation correlates with the intensity of the clinical reactions. Machine‐learning approach identifies several minimal combinations of biomarkers to distinguish allergic versus irritant contact dermatitis. Abbreviations: ACD, allergic contact dermatitis; GPR183, G protein‐coupled receptor 183; ICD, irritant contact dermatitis; IGFL3, insulin growth factor‐like family member 3. |
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ISSN: | 0105-4538 1398-9995 |
DOI: | 10.1111/all.14989 |