Fecal Microbiome and Food Allergy in Pediatric Atopic Dermatitis: A Cross-Sectional Pilot Study.

International archives of allergy and immunology. 2018;175(1-2):77-84

Plain language summary

Atopic diseases, such as atopic dermatitis (AD), asthma and rhinitis, are on the increase worldwide. Exposure to microbes may be important in the development of an atopic disease. Specifically, reduced early-life exposure is thought to be a contributing factor because microbial colonisation of the intestines during infancy plays a crucial role in the maturation of the immune system. AD, also called eczema, is an inflammatory skin disease often seen in small children. Food allergies are common in children with AD, the most common allergens being eggs, cow’s milk, peanuts, soy and wheat. This cross-sectional observational pilot study with 82 young children with a diagnosis of AD set out to identify distinct microbial patterns in the children’s faecal microbiomes associated with a clinical diagnosis of food allergy. Stool and blood samples were collected for a microbiome analysis and IgE antibody measurement, respectively. 20 children had a confirmed food allergy (most commonly to cow’s milk and peanuts), while almost half of the children without a diagnosed food allergy were sensitised to common food allergens after a food challenge. The study identified a faecal microbial signature in children with AD that differentiates between the presence and absence of food allergy. Children with AD and food allergy had more Escherichia coli and Bifidobacterium pseudocatenulatum species and less Bifidobacterium breve, Faecalibacterium prausnitzii and Akkermansia muciniphila species than children without food allergy. The authors concluded that the study supports a hypothesis that the intestinal microbiome differs in children with AD, depending on whether they have a food allergy or not. They call for future studies to confirm these findings.

Abstract

BACKGROUND Exposure to microbes may be important in the development of atopic disease. Atopic diseases have been associated with specific characteristics of the intestinal microbiome. The link between intestinal microbiota and food allergy has rarely been studied, and the gold standard for diagnosing food allergy (double-blind placebo-controlled food challenge [DBPCFC]) has seldom been used. We aimed to distinguish fecal microbial signatures for food allergy in children with atopic dermatitis (AD). METHODS Pediatric patients with AD, with and without food allergy, were included in this cross-sectional observational pilot study. AD was diagnosed according to the UK Working Party criteria. Food allergy was defined as a positive DBPCFC or a convincing clinical history, in combination with sensitization to the relevant food allergen. Fecal samples were analyzed using 16S rRNA microbial analysis. Microbial signature species, discriminating between the presence and absence food allergy, were selected by elastic net regression. RESULTS Eighty-two children with AD (39 girls) with a median age of 2.5 years, and 20 of whom were diagnosed with food allergy, provided fecal samples. Food allergy to peanut and cow's milk was the most common. Six bacterial species from the fecal microbiome were identified, that, when combined, distinguished between children with and without food allergy: Bifidobacterium breve, Bifidobacterium pseudocatenulatum, Bifidobacterium adolescentis, Escherichia coli, Faecalibacterium prausnitzii, and Akkermansia muciniphila (AUC 0.83, sensitivity 0.77, specificity 0.80). CONCLUSIONS In this pilot study, we identified a microbial signature in children with AD that discriminates between the absence and presence of food allergy. Future studies are needed to confirm our findings.

Lifestyle medicine

Patient Centred Factors : Mediators/Microbiome
Environmental Inputs : Diet ; Microorganisms
Personal Lifestyle Factors : Nutrition ; Environment
Functional Laboratory Testing : Blood ; Stool

Methodological quality

Allocation concealment : Not applicable
Publication Type : Journal Article ; Observational Study

Metadata