In a recent study published in the journal Nature Neuroscience, researchers present a framework to utilize multi-omic data from well-defined groups and assess the contribution of gut-brain axis (GBA) disruptions in the pathogenesis of autism spectrum disorder (ASD).
Study: Multi-level analysis of the gut–brain axis shows autism spectrum disorder-associated molecular and microbial profiles. Image Credit: nobeastsofierce / Shutterstock.com
What causes ASD?
ASDs are neurodevelopmental disorders characterized by behavioral, communication, and cognitive impairments manifesting in the initial years of life. Previous studies have reported GBA disruptions in ASDs but with low reproducibility.
The gut microbiome plays a central role in regulating neuroimmune networks, modifying neural networks, and directly communicating with the brain. The metagenomic and metabolic contributions of the microbiome are crucial for understanding the functional framework of ASD.
About the study
ASD patients were matched with neurotypical children by age and sex to adjust for confounding factors in childhood development, batch effects, and confounding variations. Microbes were ranked based on their fold change, whereas sequencing count data were modeled using negative binomial distributions to minimize sequencing depth and compositionality issues. ASD-related molecular and taxonomic profiles were identified using a Bayesian differential ranking algorithm.
The microbial differential rankings obtained from the matched groups were cross-referenced with 16S ribosomal ribonucleic acid (rRNA) sequencing differentials obtained from the sibling-matched groups and those obtained using shotgun metagenomic sequencing (SMS) from other sex- and age-matched groups. The 16S rRNA differentials of the matched groups were cross-referenced using RNA sequencing and cytokine differentials with the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway for reference.
In addition, 16S rRNA sequencing differentials were calculated from a fecal matter transplantation (FMT) study, including 18 pediatric ASD patients. In addition, a microbiome-diet co-occurrence analysis was performed.
Data from the matched cohort datasets and 15 other omic datasets, including diet patterns, cytokine profiles, human brain gene expression profiles, and metabolomics, were analyzed to contextualize the potential functional roles of gut microbes in ASDs.
To ascertain probable crosstalks between the human brain and gut microbiota physiology, the metabolic potential of microbial metagenomes was compared with the differentially expressed human genome in the brain, two omic levels representing entirely different biological contexts.
Age and sex matching enhanced ASD data analysis. Differential ranking analysis revealed strong ASD-microbiome links.
ASD-related patterns were identified at the three omic levels, including the human transcriptome (RNA sequencing) and the microbiome (SMS and 16S sequencing). However, the metabolome and virome did not show significant signals.
Host cytokine expressions were correlated with microbial abundance. Microbiome metabolism mirrored human brain metabolism in ASDs, whereas microbiome metabolic capacity mirrored dietary patterns in ASDs and ASD microbiomes mirrored behavior improvement after FMT.
A functional architecture along the GBA correlated with the ASD phenotypic heterogeneity. This was characterized by ASD-associated lipid, amino acid, and carbohydrate profiles mainly encoded by Bifidobacterium, Prevotella, Bacteroides, and Desulfovibrio species and correlated with brain gene expression changes, pro-inflammatory cytokine profiles and restrictive diet patterns.
The differential and diet-microbiota co-occurrence analyses showed a reduced intake of carbohydrates and amino acids associated with particular microbes among children with ASDs. Prevotella copri counts were strongly associated with carbohydrate depletion in ASDs.
The dietary and metabolic imbalances, especially concerning glutamate, were elucidated in the serological, urinary, and fecal metabolomes analyzed. The multiple-scale overlapping present along the gut-brain axis indicated the presence of an ASD functioning structure based on metabolic capacity at both the genomic as well as metagenomic levels. However, the functional architecture in the sex- and age-matched groups was absent in the sibling-matched groups.
ASD phenotypes were also strongly associated with temporal gut microbial compositional alterations. In ASDs, interleukin-6 (IL-6) levels were upregulated, whereas Bifidobacterium, Prevotella, and Bacteroides counts were mainly associated with the cytokine differentials.
In total, 138 microbial and 1,772 human metabolic encoding genes inferred from the shotgun metagenomic and RNA sequencing datasets, respectively, were associated with ASD phenotypes. Cross-comparisons of ASD-related microbial enzyme-encoding genes with gut-brain modules (GBMs) showed a 49% overlap, underpinning metabolic crosstalk across omic levels.
Autistic children were less likely to consume foods high in glutamic acid, choline, serine, leucine, histidine, phenylalanine, valine, and tyrosine, all natural compounds involved in neurotransmitter biosynthesis. Over the two-year FMT study period, Prevotella and Desulfovibrio piger species counts were elevated, whereas those of butyrate-producing bacteria such as Anaerobutyricum and Butyricimonas remained constant, thus reflecting a role in gut-brain-axis homeostasis.
The study findings provide a framework for future studies to define the causal relationship between the microbiome and other omic levels and ASD. A clear separation between pediatric ASD patients and unrelated sex- and age-matched controls was observed and validated using different methods, including differential abundance, PERMANOVA, and classification, across several cohorts.
ASD subtypes could not be identified; however, strong associations were observed between the gut microbiome, immunity, diet patterns, and brain expression. Nevertheless, further research, including multi-omic longitudinal interventional studies with comprehensive ASD metadata investigating gut microbiota and genomic variations among households with and without pediatric ASD patients, is needed to advance mechanistic studies with a multidisciplinary and unified approach.
- Morton, J. T., Jin, D. M., Mills, R. H. et al. (2023). Multi-level analysis of the gut–brain axis shows autism spectrum disorder-associated molecular and microbial profiles. Nature Neuroscie. doi:10.1038/s41593-023-01361-0