Research on the role of gut microbiota metabolites in autism by multi-omics and network pharmacology.

Overview

1. Department of Pediatrics, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China
2. The First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China
3. College of Computer Science, Guangdong Polytechnic Normal University, Guangzhou, Guangdong, China
4. Department of Microbiology, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China
5. Department of Emergency, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China

Abstract

Objective: The relationship and underlying mechanisms linking the gut microbiota, metabolites and autism spectrum disorder (ASD) have not been fully elucidated.

Methods: In the present study, network pharmacology was combined with machine learning for a systematic investigation into the possible action mechanisms between metabolites derived from the gut microbiota and their targets in ASD. Subsequently, untargeted metabolomics analysis and 16S rRNA sequencing were utilized for investigating alterations in differential metabolites and the composition of principal gut microbiota between normal and BTBR mice.

Results: The findings demonstrated that five characteristic targets: CXCR3, HCAR2, HTR1A, IL-6 and NFKB1 modulated by the gut microbiota and gut microbiota’s metabolites were significantly associated with ASD. The M-S-M-T network prioritized 21 candidate gut-microbiota-derived metabolites, including phenylacetic acid and coumarin. These candidates were generated from database-based target prediction and should be interpreted separately from the differential metabolites detected in fecal metabolomics. Metabolomic and 16S rRNA sequencing analyses revealed that BTBR mice displayed metabolic dysregulation and disrupted gut microbiota composition compared with normal ones. These findings suggest that phenylalanine metabolism and neuroactive ligand-receptor interaction may be associated with ASD-like behavioral phenotypes in BTBR mice and warrant further experimental validation. The gut microbiota-metabolite-behavior network analysis further uncovered significant associations among the behavioral characteristics of ASD, alterations in gut microbiota composition and markedly altered metabolite profiles.

Conclusion: By integrating network pharmacology, transcriptomic re-analysis, fecal metabolomics and 16S rRNA sequencing, this study identifies candidate microbe-metabolite-target associations related to ASD-like phenotypes. These results provide testable hypotheses for future mechanistic studies of gut-brain communication in ASD.

Reproduced under the paper's license (CC BY), from the paper cited above.

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Data

Datasets cited

• bioproject:PRJNA1496513, at NCBI BioProject; found in “Data availability statement”

Other data links

• ncbi.nlm.nih.gov/geo, NCBI; found in the end of the paper

Data availability statement

The original contributions presented in the study are publicly available. The main data generated or analyzed during this study are included in this manuscript and its additional files and are available from the corresponding author on reasonable request. 16s rRNA sequencing data can be found at: https://www.ncbi.nlm.nih.gov/sra/PRJNA1496513.

Reproduced under the paper's license (CC BY), from the paper cited above.

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Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, pages, dates, 9 authors, 5 keywords, 71 references.

Cite

This paper

Hu, X., Zeng, Y., Li, J., Lin, Q., Liang, Z., Zhang, J., Jiang, M., Gao, S., & Liu, H. (2026). Research on the role of gut microbiota metabolites in autism by multi-omics and network pharmacology. Frontiers in microbiology, 17, 1811435. https://doi.org/10.3389/fmicb.2026.1811435

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