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Wheezing preschool children with early‐onset asthma reveal a specific metabolomic profile
Author(s) -
Carraro Silvia,
Bozzetto Sara,
Giordano Giuseppe,
El Mazloum Dania,
Stocchero Matteo,
Pirillo Paola,
Zanconato Stefania,
Baraldi Eugenio
Publication year - 2018
Publication title -
pediatric allergy and immunology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.269
H-Index - 89
eISSN - 1399-3038
pISSN - 0905-6157
DOI - 10.1111/pai.12879
Subject(s) - asthma , medicine , metabolomics , univariate analysis , multivariate analysis , pediatrics , wheeze , univariate , urine , prospective cohort study , urinary system , multivariate statistics , bioinformatics , statistics , mathematics , biology
Background Many children of preschool age present with recurrent wheezing. Most of them outgrow their symptoms, while some have early‐onset asthma. Aim of this prospective preliminary study was to apply a metabolomic approach to see whether biochemical‐metabolic urinary profiles can have a role in the early identification of the children with asthma. Methods Preschool children with recurrent wheezing were recruited and followed up for 3 years, after which they were classified as cases of transient wheezing or early‐onset asthma. A urine sample was collected at recruitment and analyzed using a metabolomic approach based on UPLC mass spectrometry. Results Among 34 children aged 4.0 ± 1.1 years recruited, at the end of the 3‐year follow‐up, 16 were classified as having transient wheezing and 16 as cases of early‐onset asthma. Through a joint multivariate and univariate statistical analyses, we identified a subset of metabolomic variables that enabled the 2 groups to be clearly distinguished. The model built using the identified variables showed an AUC = 0.99 and an AUC = 0.88 on sevenfold full cross‐validation ( P = .002). Conclusions Metabolomic urinary profile can discriminate preschoolers with recurrent wheezing who will outgrow their symptoms from those who have early‐onset asthma. These results may pave the way to the characterization of early non‐invasive biomarkers capable of predicting asthma development.