2097 The Gut Microbiome in the Food Allergic Host

Thursday, 15 October 2015
Hall D1 Foyer (Floor 3) (Coex Convention Center)

Jamie Kiehm, MD , North Shore Long Island Jewish Health System, Great Neck, NY

Punita Ponda, MD , North Shore Long Island Jewish Health System, Great Neck, NY

Cristina Sison, PhD , North Shore Long Island Jewish Health System, Manhasset, NY

Sherry Farzan, MD , North Shore Long Island Jewish Health System, Great Neck, NY

Jared Weiss , North Shore Long Island Jewish Health System, Manhasset, NY

Claudia Elera , North Shore Long Island Jewish Health System, Manhasset, NY

Catherine Destio , North Shore Long Island Jewish Health System, Manhasset, NY

Annette Lee, PhD , North Shore Long Island Jewish Health System, Manhasset, NY

A) Background: Alterations in the diversity and composition of the human gut microbiota have been associated with a myriad of diseases including inflammatory bowel disease and metabolic syndrome. In our study, we explore the association of the host gut microbiome with food allergy.

B) Methods: 12.5 ng of isolated DNA from fecal samples from 8 children with peanut allergy (peanut specific IgE >15 kUA/L) and 10 healthy, non-atopic controls were amplified using primers specifically for the V3-V4 region of the 16S rRNA gene which is unique to bacteria.   Sequence differences within the V1-V9 variable region were used for bacterial classification.  Once amplified, the amplicons were dual-indexed for multiplex sequencing. Pooled libraries were sequenced on the Illumina MiSeq using 300 cycle paired end reads. Sequence data was processed through the MiSeq Reporter Metagenomics 16S application and the Greengenes 16S ribosomal RNA gene database. Data regarding family history of atopic disease, history of breastfeeding, antibiotic treatment per year, medications, and history of other atopic disease was collected via questionnaires.  The Mann-Whitney U-test was used for comparison of continous variables between the two groups.  The Fisher’s exact test was used to compare proportions between groups.  All analyses were carried out using SAS V9.3. 

C) Results:  The median age of subjects with peanut allergy was 6 years (average peanut specific IgE=75.1 kUA/L), and median age of healthy controls was 4 years.  All of the patients with peanut allergy had a history of other atopic diseases.  The phylogentic differences showed that peanut allergic subjects had an increased proportion of Firmicutes (median=71% vs 59%; p<0.03) and a decreased proportion of Proteobacteria (median=1% vs 3%; p<0.009) when compared to healthy controls. At the class level, Clostridia was more abundant in the peanut allergic subjects (median=69% vs. 57%; p<0.03).  Clostridiales order was significantly more abundant in the peanut allergic subjects (median=69% vs. 56%; p<0.03).  Alcaligenaceae family was found in 6/10 healthy controls and in none of the 8 peanut allergic subjects (60% vs 0%; p<0.013).  16 genera were identified in healthy controls while 12 genera were identified in peanut allergic subjects.  The 12 genera identified in the peanut allergic subjects accounted for 82.76% of the total sequences and were all found in the healthy controls.  The 16 genera found in healthy controls accounted for 79.97% of the total sequences.

D) Conclusions:  Analysis of the human gut microbiome in children with peanut allergy and healthy, non-atopic controls revealed differences in the specific composition and diversity of the microbiota that may contribute to the pathogenesis of food allergy. More studies with a larger sample size are needed to further investigate these associations.