Cow’s milk allergy (CMA) is one of the most prevalent and first food allergies to occur in early
childhood. Diagnosis of CMA currently relies on challenge-based tests, which have to be repeated
on a yearly basis to assess possible spontaneous resolution. These tests inherently result in allergic
reactions in patients. As metabolites represent the total contribution of genomic, transcriptomic
and proteomic activities, as well as external factors such as food, they constitute the most
promising candidates for early detection of food allergies. Given the emerging evidence for the
involvement of the gut microbiota in the onset of food allergy and its spontaneous resolution, this
project will embark on state-of-the-art high-resolution mass spectrometry based metabolomics
and metagenomics on patients’ bioluid samples, to decipher microbiome/metabolome
correlations and provide a framework for identifying diagnostic and prognostic biomarkers for
children with CMA. Alterations in the metabolomes of germfree and specific-pathogen free mice
following sensitization to cow’s milk will be compared to similar alterations in CMA patients’
human fecal flora associated mice, to map the origin of the proposed biomarkers. Specific
bacterial groups involved in the allergy cascade or proposed biomarkers, will be manipulated
and/or administered to mice to provide mechanistic information on how the biomarkers are
produced or affect allergic responses as a means to achieve biomarker qualification.