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Lipidomic Profiling of the Epidermis in a Mouse Model of Dermatitis Reveals Sexual Dimorphism and Changes in Lipid Composition before the Onset of Clinical Disease.
Franco, Jackeline; Rajwa, Bartek; Ferreira, Christina R; Sundberg, John P; HogenEsch, Harm.
Afiliação
  • Franco J; Department of Comparative Pathobiology, Purdue University, West Lafayette, IN 47907, USA.
  • Rajwa B; Bindley Bioscience Center, Purdue University, West Lafayette, IN 47907, USA.
  • Ferreira CR; Metabolite Profiling Facility, Bindley Bioscience Center, Purdue University, West Lafayette, IN 47907, USA.
  • Sundberg JP; The Jackson Laboratory, Bar Harbor, ME 04609, USA.
  • HogenEsch H; Department of Comparative Pathobiology, Purdue University, West Lafayette, IN 47907, USA.
Metabolites ; 10(7)2020 Jul 21.
Article em En | MEDLINE | ID: mdl-32708296
ABSTRACT
Atopic dermatitis (AD) is a multifactorial disease associated with alterations in lipid composition and organization in the epidermis. Multiple variants of AD exist with different outcomes in response to therapies. The evaluation of disease progression and response to treatment are observational assessments with poor inter-observer agreement highlighting the need for molecular markers. SHARPIN-deficient mice (Sharpincpdm) spontaneously develop chronic proliferative dermatitis with features similar to AD in humans. To study the changes in the epidermal lipid-content during disease progression, we tested 72 epidermis samples from three groups (5-, 7-, and 10-weeks old) of cpdm mice and their WT littermates. An agnostic mass-spectrometry strategy for biomarker discovery termed multiple-reaction monitoring (MRM)-profiling was used to detect and monitor 1,030 lipid ions present in the epidermis samples. In order to select the most relevant ions, we utilized a two-tiered filter/wrapper feature-selection strategy. Lipid categories were compressed, and an elastic-net classifier was used to rank and identify the most predictive lipid categories for sex, phenotype, and disease stages of cpdm mice. The model accurately classified the samples based on phospholipids, cholesteryl esters, acylcarnitines, and sphingolipids, demonstrating that disease progression cannot be defined by one single lipid or lipid category.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Metabolites Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: CH / SUIZA / SUÍÇA / SWITZERLAND

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Metabolites Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: CH / SUIZA / SUÍÇA / SWITZERLAND