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. 2024 Jan-Dec;16(1):2418984.
doi: 10.1080/19490976.2024.2418984. Epub 2024 Oct 28.

Fecal microbial marker panel for aiding diagnosis of autism spectrum disorders

Yating Wan  1   2   3 , Oscar W H Wong  3   4 , Hein M Tun  1   5   6 , Qi Su  1   2 , Zhilu Xu  1   2 , Whitney Tang  1 , Suk Ling Ma  3   4 , Sandra Chan  3   4 , Francis K L Chan  1   3   7 , Siew C Ng  1   2   5
Affiliations

Fecal microbial marker panel for aiding diagnosis of autism spectrum disorders

Yating Wan et al. Gut Microbes. 2024 Jan-Dec.

Abstract

Accumulating evidence suggests that gut microbiota alterations influence brain function and could serve as diagnostic biomarkers and therapeutic targets. The potential of using fecal microbiota signatures to aid autism spectrum disorder (ASD) detection is still not fully explored. Here, we assessed the potential of different levels of microbial markers (taxonomy and genome) in distinguishing children with ASD from age and gender-matched typically developing peers (n = 598, ASD vs TD = 273 vs 325). A combined microbial taxa and metagenome-assembled genome (MAG) markers showed a better performance than either microbial taxa or microbial MAGs alone for detecting ASD. A machine-learning model comprising 5 bacterial taxa and 44 microbial MAG markers (2 viral MAGs and 42 bacterial MAGs) achieved an area under the receiving operator curve (AUROC) of 0.886 in the discovery cohort and 0.734 in an independent validation cohort. Furthermore, the identified biomarkers and predicted ASD risk score also significantly correlated with the core symptoms measured by the Social Responsiveness Scale-2 (SRS-2). The microbiome panel showed a superior classification performance in younger children (≤6 years old) with an AUROC of 0.845 than older children (>6 years). The model was broadly applicable to subjects across genders, with or without gastrointestinal tract symptoms (constipation and diarrhea) and with or without psychiatric comorbidities (attention deficit and hyperactivity disorder and anxiety). This study highlights the potential clinical validity of fecal microbiome to aid in ASD diagnosis and will facilitate studies to understand the association of disturbance of human gut microbiota and ASD symptom severity.

Keywords: Autism spectrum disorder; bacteria; diagnosis; microbiome.

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Conflict of interest statement

FKLC is Board Member of CUHK Medical Centre. He is a co-founder, non-executive Board Chairman, non-executive scientific advisor, Honorary Chief Medical Officer and shareholder of GenieBiome Ltd. He receives patent royalties through his affiliated institutions. He has received fees as an advisor and honoraria as a speaker for Eisai Co. Ltd., AstraZeneca, Pfizer Inc., Takeda Pharmaceutical Co., and Takeda (China) Holdings Co. Ltd.

SCN has served as an advisory board member for Pfizer, Ferring, Janssen, and Abbvie and received honoraria as a speaker for Ferring, Tillotts, Menarini, Janssen, Abbvie, and Takeda. SCN has received research grants through her affiliated institutions from Olympus, Ferring, and Abbvie. SCN is a founder member, non-executive director, non-executive scientific advisor, and shareholder of GenieBiome Ltd. SCN receives patent royalties through her affiliated institutions.

QS and ZX are Scientists (Diagnostics) of GenieBiome Ltd. WT is a Consultant (Regulatory Affairs) of GenieBiome Ltd.

YW, QS, WT, FKLC, and SCN are named inventors of patent applications held by the CUHK and MagIC that cover the therapeutic and diagnostic use of microbiome related to ASD.

Figures

Figure 1.
Figure 1.
Comparison of four different models for the detection of autism spectrum disorder (ASD) using gut microbial different levels of taxonomy and microbial MAGs.
Figure 2.
Figure 2.
Fecal microbiome-based model performances in the discovery cohort and validation cohort.
Figure 3.
Figure 3.
The optimal cut-off value of the model in the detection of ASD.
Figure 4.
Figure 4.
The fecal microbiome-based model showed younger age preferences.
Figure 5.
Figure 5.
Heatmap of the correlation between host factors and microbial biomarkers.
See this image and copyright information in PMC

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