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The link between the gut microbiome and autism spectrum disorder (ASD) is strongly supported and expanded on by a new metagenomics study, published in Nature Microbiology from a Chinese team. Their analysis includes not just bacteria native to the digestive tract, but also fungi, archaea, and viruses too. Their work suggests stool-based biomarkers could diagnose autism sooner and provide new leads for additional research.
The team is from the Microbiota I-Center (MagIC) in Hong Kong and The Chinese University of Hong Kong. The lead author is Qi Su, a researcher at the Chinese University of Hong Kong.
They analyzed gut archaea, bacteria, fungi, viruses and their genes and functions, and presented metagenomic analyses of more than 1,000 children considered neurotypical or with ASD, on which they had extensive phenotype data. These findings were then validated against public fecal metagenome datasets. They also analyzed the impact of 236 host factors on the gut microbiome composition to determine potential confounding host or environmental.
The cause of ASD is unknown, but it is believed to relate to a complex interplay between genetic and environmental factors. In the past decade, the gut microbiome has been shown to play a central role in modulating the gut–brain axis by regulating neuroimmune networks and directly communicating with the brain, and which may contribute to the development of autism.
After analyzing more than 1,600 stool samples from children ages 1–13, these researchers found several distinct biological “markers” in the samples of autistic children. Unique traces of gut bacteria, fungi, viruses and more that could one day be the basis of a diagnostic tool. The researchers used machine learning to identify major biological differences between the stool of autistic children and the other samples.
Studies of associations between the gut microbiome and autism have been carried out for years, but most have focused on the bacterial component of the microbiome. Whether gut archaea, fungi and viruses, or function of the gut microbiome, is so far unclear.
The team performed metagenomic sequencing on fecal samples from 1,627 children (aged 1–13 years) with or without ASD, with extensive phenotype data. Integrated analyses revealed that 14 archaea, 51 bacteria, 7 fungi, 18 viruses, 27 microbial genes and 12 metabolic pathways were altered in children with ASD. Machine learning using single-kingdom panels showed areas under the curve (AUC) of 0.68 to 0.87 in differentiating children with ASD from those that are neurotypical.
A panel of 31 multi kingdom and functional markers showed a superior diagnostic accuracy with an AUC of 0.91, with comparable performance for males and females. Accuracy of the model was predominantly driven by the biosynthesis pathways of ubiquinol-7 or thiamine diphosphate, which were less abundant in children with ASD. Collectively, their findings highlight the potential application of multi-kingdom and functional gut microbiota markers as non-invasive diagnostic tools in ASD.
