Exploring gut microbiome and nutritional status among children with Autism Spectrum Disorder (MY-ASD Microbiome): A study protocol - Kai Xuan Wong; Seong Ting Chen; Jun Jean Ong; Wan Ying Gan; Nor Azian Abdul Murad; Chun Wie Chong; Nurul Hanis Ramzi (PLoS ONE, 2025)
Background Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterised by persistent deficits in social communication and the presence of restricted, repetitive behaviours or interests. Previous literature has identified a link between the gut and ASD; however, the underlying mechanisms remain unclear. Gut microbiota dysbiosis has been extensively reported in cohort studies of ASD, and specific microbial metabolites or by-products may serve as potential biomarkers for ASD. Additionally, children with ASD often exhibit food refusal, have a limited food repertoire and display a tendency to consume the same foods frequently; thus, these behaviours increase their risk of malnutrition (over-nutrition or under-nutrition) compared to typically developing (TD) healthy children. This study primarily aims to identify oral and gut microbiota among children with ASD and TD healthy children. The secondary aim is to determine the associations between oral and gut microbiota with nutritional status among children with ASD. The findings will enhance understanding of the aetiology of ASD and inform early intervention strategies to mitigate disease severity and early identification of malnutrition in genetically at-risk children. Methods and analysis This observational, age-matched, case-control study is conducted in Malaysia among 40 male children with ASD and age-matched with 40 TD healthy controls aged 4–10 years. The dependent variables include the microbiota profile, identified through metagenomic sequencing analysis of saliva and faecal samples, and autism severity, assessed through validated questionnaires. Independent variables include nutritional status, determined through Subjective Global Nutrition Assessment (SGNA), anthropometry and dietary measurements, gastrointestinal symptoms, eating behaviour, behavioural profile, and sleep quality. Data collection is expected to be completed by June 2026. The study nature may limit causality establishment. Analyses will use chi-square/ANOVA for group comparisons, SparCC for microbiota correlations, and mixed-effects logistic regression to model associations. Conclusion This study advances understanding of ASD-related microbiota, guiding personalised nutrition and precision healthcare in Malaysia.