A research team from The Chinese University of Hong Kong (CUHK)’s Faculty of Medicine (CU Medicine) has conducted a large cohort study among 1,627 children with and without autism spectrum disorder (ASD) and found alterations in four kingdoms of the gut microbial species including archaea, bacteria, fungi and viruses in children with ASD. Using machine learning, they developed a panel of 31 multikingdom and functional markers that showed high diagnostic performance for ASD and has great potential as a clinical diagnostic tool. The findings were published in Nature Microbiology. In a pilot study, the researchers also showed that modulation of the gut microbiome alleviated symptoms of anxiety in children with ASD, introducing the possibility of a new therapeutic paradigm for the condition.
Multikingdom gut microbial markers facilitate ASD diagnosis
ASD is a neurodevelopmental condition characterised by impairment in social communication, and restrictive and repetitive behaviour. Genetic and environmental factors contribute to the pathogenesis of ASD but emerging evidence suggests that impaired cross-talk between the gut microbiome and central nervous system, dubbed the gut-brain axis, may contribute to the development of ASD. According to the latest estimation from CU Medicine, approximately 2.54% of children in Hong Kong has ASD, and the incidence has been rising in recent years.
The CU Medicine research team performed metagenomic sequencing on faecal samples from 1,627 children with or without ASD, aged one to 13 years old from five independent cohorts. Subjects were recruited from the Child and Adolescent Psychiatric Services of the Department of Psychiatry at Alice Ho Miu Ling Nethersole Hospital of the Hospital Authority’s New Territory East Cluster from 2021 to 2023. The team analysed faecal samples and clinical data including diet, medication and co-morbidities. The researchers identified a panel of novel gut microbiome markers including 14 archaea, 51 bacteria, seven fungi, 18 viruses, 27 microbial genes and 12 metabolic pathways that were altered in children with ASD. Using machine learning approaches, they then developed a novel, non-invasive diagnostic model based on a panel of 31 multikingdom and functional markers that showed a high diagnostic accuracy for ASD.
Dr Su Qi, Research Assistant Professor in the Department of Medicine and Therapeutics at CU Medicine, said, “Bacterial composition has been shown to be altered in ASD but the contribution of other components of the microbiome including the archaea, fungi, viruses, microbial genes or functional pathways remains unexplored. We found that the 31-microbiome panel has a sensitivity of 94% and specificity of 93% for the diagnosis of ASD, and maintained a sensitivity of 91% in children from an independent hospital cohort and a younger community cohort from one to six years old.”
Professor Siew Ng, Croucher Professor in Medical Sciences at CU Medicine, Director of the Microbiota I-Center (MagIC), and New Cornerstone Investigator added, “The diagnosis of ASD is challenging and requires regular developmental assessment in children who show signs of atypical social and language development. Diagnosis is often delayed especially in younger children who may only have mild symptoms and this could lead to delayed intervention. This, to our knowledge, is the first study to demonstrate the robustness and utility of a non-invasive biomarker to diagnose and predict ASD across different ages, gender and settings.”