Skin is an essential organ that preserves the integrity of the body and the maintenance of lipid content and composition is essential for proper epidermal barrier function. SHANK-associated RH domain interacting protein-deficient mice spontaneously develop a chronic proliferative dermatitis with similarities to atopic dermatitis in humans. To learn about changes in the epidermal lipid-content in male and female mice during disease progression, we used 18 male and 18 female wild-type mice and 3 groups of littermates mice with dermatitis (6 male and 6 female each) divided according to the stage of disease: non-lesional, established and advanced. A mass-spectrometry strategy for biomarker discovery termed multiple-reaction monitoring-profiling was used to detect and monitor 1030 lipid ions present in the epidermis samples. Univariate analysis was performed to link lipids to disease stage in a sex-dependent or independent manner. An elastic-net regression model was built using the top 10 lipid features to predict disease progression. Individual samples were classified into their corresponding disease stage groups with an accuracy of 0.90 (95% CI:0.86, 0.93). Multiple-reaction monitoring-profiling paired with machine-learning identified predictive biomarkers of dermatitis in mice and may provide the basis for a molecular diagnostic approach to atopic dermatitis.
[doi:10.25345/C5PD30]
[dataset license: CC0 1.0 Universal (CC0 1.0)]
Keywords: lipidomics, sex-dimorphism, dermatitis, SHARPIN, elastic-net
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Harm HogenEsch, Purdue University, United States |
Submitting User: | francojackeline |
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