Sensitization to peanut, egg or pets is associated with skin barrier dysfunction in children with atopic dermatitis.
Animals
Calgranulin A
/ metabolism
Calgranulin B
/ metabolism
Cats
Child, Preschool
Dermatitis, Atopic
/ immunology
Dogs
Egg Hypersensitivity
/ immunology
Female
Filaggrin Proteins
/ metabolism
Humans
Infant
Machine Learning
Male
Peanut Hypersensitivity
/ immunology
Pets
/ immunology
Skin
/ metabolism
Skin Tests
Water Loss, Insensible
allergens and epitopes
atopic dermatitis
pediatrics
Journal
Clinical and experimental allergy : journal of the British Society for Allergy and Clinical Immunology
ISSN: 1365-2222
Titre abrégé: Clin Exp Allergy
Pays: England
ID NLM: 8906443
Informations de publication
Date de publication:
05 2021
05 2021
Historique:
revised:
21
02
2021
received:
08
10
2020
accepted:
24
02
2021
pubmed:
16
3
2021
medline:
3
2
2022
entrez:
15
3
2021
Statut:
ppublish
Résumé
Children with atopic dermatitis (AD) are often sensitized to food and aeroallergens, but sensitization patterns have not been analysed with biologic measures of disease pathogenicity. We sought to define allergen sensitization grouping(s) using unbiased machine learning and determine their associations with skin filaggrin (FLG) and transepidermal water loss (TEWL) (assesses skin barrier integrity), S100A8 and S100A9 expression (assesses skin inflammation) and AD severity. We studied 400 children with AD in the Mechanisms of Progression from Atopic Dermatitis to Asthma in Children (MPAACH) cohort to identify groupings of food and aeroallergen sensitizations. MPAACH is a paediatric AD cohort, aged 1-2, recruited through hospital/community settings between 2016 and 2018. We analysed these groupings' associations with AD biomarkers: skin FLG, S100A8 and S100A9 expression, total IgE, TEWL and AD severity. An unbiased machine learning approach revealed five allergen clusters. The most common cluster (N = 131), SPT In this largely clinic-based cohort of young children with AD, allergic sensitization to peanut, egg, cat or dog was associated with more severe disease and skin barrier function but not markers of cutaneous inflammation. These data need replicating in a population-based cohort but may have important implications for understanding the interaction between AD and allergic sensitization.
Sections du résumé
BACKGROUND
Children with atopic dermatitis (AD) are often sensitized to food and aeroallergens, but sensitization patterns have not been analysed with biologic measures of disease pathogenicity.
OBJECTIVE
We sought to define allergen sensitization grouping(s) using unbiased machine learning and determine their associations with skin filaggrin (FLG) and transepidermal water loss (TEWL) (assesses skin barrier integrity), S100A8 and S100A9 expression (assesses skin inflammation) and AD severity.
METHODS
We studied 400 children with AD in the Mechanisms of Progression from Atopic Dermatitis to Asthma in Children (MPAACH) cohort to identify groupings of food and aeroallergen sensitizations. MPAACH is a paediatric AD cohort, aged 1-2, recruited through hospital/community settings between 2016 and 2018. We analysed these groupings' associations with AD biomarkers: skin FLG, S100A8 and S100A9 expression, total IgE, TEWL and AD severity.
RESULTS
An unbiased machine learning approach revealed five allergen clusters. The most common cluster (N = 131), SPT
CONCLUSIONS AND CLINICAL RELEVANCE
In this largely clinic-based cohort of young children with AD, allergic sensitization to peanut, egg, cat or dog was associated with more severe disease and skin barrier function but not markers of cutaneous inflammation. These data need replicating in a population-based cohort but may have important implications for understanding the interaction between AD and allergic sensitization.
Identifiants
pubmed: 33721370
doi: 10.1111/cea.13866
pmc: PMC9258184
mid: NIHMS1817389
doi:
Substances chimiques
Calgranulin A
0
Calgranulin B
0
FLG protein, human
0
Filaggrin Proteins
0
S100A8 protein, human
0
S100A9 protein, human
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
666-673Subventions
Organisme : NIAID NIH HHS
ID : U19 AI070235
Pays : United States
Organisme : Eunice Kennedy Shriver National Institute of Child Health and Human Development
ID : 5K12HD28827-27
Informations de copyright
© 2021 John Wiley & Sons Ltd.
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