Gut Feelings: Linking Gastrointestinal Multi-Omic Profiles with Complex Phenotypes in Pediatric ASD
Objectives: This study represents the largest, most well-controlled exploration of the gut microbiome and metabolome in pediatric ASD. Autistic children, unaffected siblings, and unrelated typically developing controls were compared. Comprehensive clinical data, including behavioral and GI phenotypes, have been analyzed in parallel with microbiome and metabolome results to create novel multi-omic profiles.
Methods: Extensive clinical history was obtained as well as data from several behavioral surveys (Sensory Profile-2, the Repetitive Behavior Scale-Revised, Aberrant Behavior Checklist, Social Responsiveness Scale, and the Child Behavior Checklist) and a two-week diary detailing diet, stooling pattern (Bristol stool ratings and stool frequency), and GI pain. Stool specimens were collected from pediatric subjects with ASD (n=145), unaffected siblings (n=48), and unrelated typically developing children (n=219). The QPGS-Rome III questionnaire was also utilized for the identification of FGIDs across all three groups. Microbiome and mycobiome characterization and global metabolomics were performed. Multiple bioinformatics and biostatistical approaches were utilized to identify individual organisms (both bacterial and fungal) and metabolites of interest.
Results: Differences in both microbial composition and diversity were observed across groups. The greatest shifts in the gut microbiome were associated with GI pain, with distinct differences noted in the ASD group that reported pain. Statistically significant differences (p<0.05) were observed in the relative abundances of several organisms that were previously reported as associated with pediatric ASD. These organisms were also associated with specific behavioral patterns and overall severity as well as with a variety of metabolites, including metabolic pathways associated with glutamate and tryptophan metabolism. Unique microbial profiles were also associated with additional behavioral (i.e. self-injurious behavior) and dietary variables (i.e. processed food consumption).
Conclusions: The microbiome-gut-brain axis is emerging as a key component of ASD phenotypes. Distinct differences exist in the gut microbiome and metabolome of children with ASD compared to their typically developing peers. Within ASD, subgroups can be identified based on complex phenotypes composed of behavioral characteristics, GI symptoms, and microbiome/metabolome profiles, and these multi-omic profiles will aid in identifying less communicative autistic individuals who may be experiencing GI pain as well as assist in the development of meaningful selection criteria for future microbially-mediated therapeutic interventions.
See more of: Biomarkers (molecular, phenotypic, neurophysiological, etc)