The following is a summary of “Stratum corneum lipid and cytokine biomarkers at age 2 months predict the future onset of atopic dermatitis,” published in the MAY 2023 issue of Allergy (& Immunology) by Berdyshev, et al.

Atopic dermatitis (AD) is a common skin condition in children that can progress to severe phenotypes or atopic march, significantly impacting their quality of life. Early identification of biomarkers before clinical manifestations is crucial for predicting the onset of AD. For a study, researchers sought to identify early predictors of future AD development in the stratum corneum (SC) of the skin.

Skin tape strips were collected from the forearms of newborns (n = 111) with and without a family history of atopic diseases at the age of 2 months, before any signs of clinical AD. The children were clinically monitored until they reached the age of 2 years to confirm the presence or absence of AD. The collected skin tape strips underwent lipidomic analysis using liquid chromatography electrospray ionization tandem mass spectrometry and cytokine determination using the Meso Scale Discovery U-Plex assay.

Among the risk group (n = 74) and the control group (n = 37), 22 (29.7%) and 5 (13.5%) infants, respectively, developed AD. In the SC of children who developed AD, protein-bound ceramides were found to be decreased (P < .001), while unsaturated sphingomyelin species (P < .0001), “short-chain” nonhydroxy fatty acid sphingosine, and alpha-hydroxy fatty acid sphingosine ceramides were elevated (P < .01 and .05, respectively) compared to healthy children. Levels of thymic stromal lymphopoietin and IL-13 were increased in the SC of children who developed AD (by 74.5% and 78.3%, P = .0022 and P < .0001, respectively). Multivariable logistic regression analysis demonstrated that a combination of family history, type 2 cytokines, and dysregulated lipids had a strong predictive power for AD, with an odds ratio of 54.0 (95% CI, 9.2-317.5).

Noninvasive analysis of skin tape strips at the age of 2 months can effectively identify asymptomatic children at risk of developing AD in the future with a high probability.

Source: jacionline.org/article/S0091-6749(23)00227-0/fulltext