Detection of Metabolite Biomarkers for the Early Diagnosis and Prognosis of Cow's Milk Allergy in Children

In this study, fecal and urine samples will be collected from children diagnosed with : * IgE mediated cow's milk allergy, * suspected of a cow's milk allergy, but with negative diagnosis * IgE mediated food allergy other than cow's milk * healthy brothers and sisters of the first three groups A subset of patients with IgE-mediated cow's milk allergy will be asked to provide a urine and fecal sample yearly for prognostic purposes. The samples will be analyzed using a technique called metabolomics to identify biomarker candidates with diagnostic and/or prognostic potential. Additionally, microbiome analysis will be performed to map the microbiome of all groups.

In this study urine and fecal samples will be collected from children until the age of 4 years old. The metabolome and microbiome of children with IgE mediated cow's milk allergy (1) (CMA) will be compared to that of children in three control groups: (2) children suspected of IgE mediated CMA, but with negative diagnosis, (3) children with an IgE mediated food allergy other than cow's milk and (4) healthy brothers and sisters of the first 3 groups. Children will be divided into these four groups based on the current diagnostic tests, including IgE measurements (skin prick tests and IgE measurements in venous blood samples), clinical history of the patients and their response to elimination diets. Samples will be collected shortly after diagnosis. In a second phase of this study several patients will be followed up for several years (3 - 4 years), for which yearly a urine and fecal sample will be collected. Children included in this part will be younger than 1 year at the moment of their first sample donation, and diagnosed with IgE mediated CMA. This longitudinal follow-up is based on the microbial difference at the age between 3 to 6 months between children that will have a persistent allergy and the ones that will grow out of their allergy. These differences are anticipated to be translated in to the metabolomes of these children. The samples will be collected at home and have to be frozen immediately after sample collection, after which they will be picked up by the researchers. The samples will be analyzed using a technique called metabolomics, using UHPLC-HRMS (Ultra-High Performance Liquid Chromatography coupled to High-Resolution Mass Spectrometry). After analysis the metabolic profiles of the different groups will be compared to each other using multivariate statistical analysis. This methodology will be applied to find biomarker candidates with good sensitivity and specificity for future CMA diagnosis or prognosis. Additionally, the identified biomarkers could provide more insights into the mechanisms behind the disease, which can aid in future therapy. Microbiome analysis will be performed using qPCR and 16S rRNA sequencing.