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Abstract
Observational studies have shown that the composition of the human gut microbiome in children diagnosed with Autism Spectrum Disorder (ASD) differs significantly from that of their neurotypical (NT) counterparts. Thus far, reported ASD-specific microbiome signatures have been inconsistent. To uncover reproducible signatures, we compiled 10 publicly available raw amplicon and metagenomic sequencing datasets alongside new data generated from an internal cohort (the largest ASD cohort to date), unified them with standardized pre-processing methods, and conducted a comprehensive meta-analysis of all taxa and variables detected across multiple studies. By screening metadata to test associations between the microbiome and 52 variables in multiple patient subsets and across multiple datasets, we determined that differentially abundant taxa in ASD versus NT children were dependent upon age, sex, and bowel function, thus marking these variables as potential confounders in case–control ASD studies. Several taxa, including the strains Bacteroides stercoris t__190463 and Clostridium M bolteae t__180407, and the species Granulicatella elegans and Massilioclostridium coli, exhibited differential abundance in ASD compared to NT children only after subjects with bowel dysfunction were removed. Adjusting for age, sex and bowel function resulted in adding or removing significantly differentially abundant taxa in ASD-diagnosed individuals, emphasizing the importance of collecting and controlling for these metadata. We have performed the largest (n = 690) and most comprehensive systematic analysis of ASD gut microbiome data to date. Our study demonstrated the importance of accounting for confounding variables when designing statistical comparative analyses of ASD- and NT-associated gut bacterial profiles. Mitigating these confounders identified robust microbial signatures across cohorts, signifying the importance of accounting for these factors in comparative analyses of ASD and NT-associated gut profiles. Such studies will advance the understanding of different patient groups to deliver appropriate therapeutics by identifying microbiome traits germane to the specific ASD phenotype.
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Details
1 Second Genome Inc., Brisbane, USA (GRID:grid.452682.f)
2 Stanford University, Department of Bioengineering, Stanford, USA (GRID:grid.168010.e) (ISNI:0000000419368956)
3 Stanford University, Departments of Pediatrics (Systems Medicine), Stanford, USA (GRID:grid.168010.e) (ISNI:0000000419368956)
4 Second Genome Inc., Brisbane, USA (GRID:grid.452682.f); Labii Inc., South San Francisco, USA (GRID:grid.452682.f)
5 Stanford University, Departments of Pediatrics (Systems Medicine), Stanford, USA (GRID:grid.168010.e) (ISNI:0000000419368956); Stanford University, Department of Biomedical Data Science, Stanford, USA (GRID:grid.168010.e) (ISNI:0000000419368956); Stanford University, Department of Psychiatry and Behavioral Sciences (By Courtesy), Stanford, USA (GRID:grid.168010.e) (ISNI:0000000419368956)
6 Oregon State University, Department of Microbiology, Corvallis, USA (GRID:grid.4391.f) (ISNI:0000 0001 2112 1969); Oregon State University, Department of Pharmaceutical Sciences, Corvallis, USA (GRID:grid.4391.f) (ISNI:0000 0001 2112 1969)