Multi-level Analysis Sheds Light On Autism-Microbiome Link

A recent study published in Nature Neuroscience initiated at the Simons Foundation's Autism Research Initiative (SFARI) casts new light on the intricate relationship between the microbiome and autism.

The research titled “Multi-level analysis of the gut–brain axis shows autism spectrum disorder-associated molecular and microbial profiles” represents a breakthrough in understanding the link between the microbiome and autism. By reanalysing numerous previously published datasets, this study successfully harmonised disparate data from various studies and identified a microbial signature distinguishing autistic individuals from their neurotypical counterparts.

Initially reported in a press release by the Simons Foundation, the ambitious study brought together 43 experts from diverse fields, including computational biology, engineering, medicine, autism research, and microbiome studies. Their collaboration spanned institutions in North America, South America, Europe, and Asia, underlining the necessity of cross-disciplinary cooperation to gain a more comprehensive understanding of autism.

Autism’s complexity has been a formidable obstacle in identifying specific gut microbes associated with the condition. Autistic individuals display genetic, physiological, and behavioural differences, making pinpointing a one-size-fits-all microbial profile challenging. Furthermore, microbiome studies typically provide relative proportions of specific microbes, necessitating advanced statistical analyses to discern the microbial population changes relevant to autism. Adding to the complexity, most previous studies only offered snapshots of microbial populations in autistic individuals, which can vary significantly over time.

The research team developed an innovative algorithm to reanalyse 25 previously published datasets to address these challenges. These datasets included microbiome data and other ‘omic’ data, like gene expression, immune responses, and dietary information, from both autistic and neurotypical cohorts. The algorithm identified the most suitable pairs of autistic and neurotypical individuals within each dataset based on age and sex, common factors that can confound autism studies. This approach enabled the simultaneous analysis of over 600 autism-control pairs, forming a cohort of more than 1,200 children. This novel computational approach facilitated the identification of microbes with differing abundances between individuals with autism and their neurotypical counterparts.

The analysis revealed autism-specific metabolic pathways linked to specific human gut microbes. These pathways were found in the gut and mirrored in other aspects of autistic individuals, such as their brain-related gene expression profiles and dietary preferences. This fascinating overlap between gut microbes and their metabolic products, associated with autism and those identified in a recent faecal microbiota transplant study led by James Adams and Rosa Krajmalnik-Brown at Arizona State University’s Biodesign Center for Health Through Microbiomes provides additional validation.

This research goes beyond autism, offering a structured approach applicable to other challenging areas of biomedicine. By shedding light on the microbiome’s role in autism, this approach can be extended to various fields, such as depression, Parkinson’s disease, and cancer, where the microbiome’s role remains enigmatic. It provides a structured framework for future studies in these areas, emphasising the need for more comprehensive, longitudinal research to uncover cause-and-effect relationships.