Evidence map›Paper›PMID 42614415›Full record

ArticleFrontiers in microbiology2026

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

Xiaoyun Hu, Yuning Zeng, Junjie Li, Qiongxi Lin, Zixuan Liang, Jing Zhang, Meirong Jiang, Shuoshuo Gao, Hua Liu

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

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No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Xiaoyun Hu *Department of Pediatrics, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.
Yuning Zeng *The First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.
Junjie LiCollege of Computer Science, Guangdong Polytechnic Normal University, Guangzhou, Guangdong, China.
Qiongxi LinDepartment of Microbiology, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China.
Zixuan LiangThe First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.
Jing ZhangDepartment of Emergency, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.
Meirong JiangDepartment of Pediatrics, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.
Shuoshuo GaoDepartment of Pediatrics, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.
Hua LiuDepartment of Pediatrics, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

16S rRNA sequencingautism spectrum disordergut-brain communicationmetabolomicsnetwork pharmacology

Identifiers

PMID42614415
PMCPMC13481684

What Socratic holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.