Multi-Omic Analysis of Cerebrospinal Fluid Metabolites in Autism Spectrum Disorder: Biomarker Identification, Metabolic Genetics Insights, and Network Toxicology.

Overview

1. Department of Medical Genetics and Developmental Biology, School of Basic Medical Science, Capital Medical University, Beijing 100069, China; (D.Z.); (J.G.); (Y.Z.); (Y.L.); (T.Z.); (Y.X.)
2. Laboratory for Clinical Medicine, Capital Medical University, Beijing 100069, China
3. Beijing Key Laboratory of Cell and Gene Therapy in Otology, Beijing 100069, China
4. Department of Neurocritical Care, Beijing Anzhen Hospital, Capital Medical University, Beijing 100029, China

Abstract

Background: Although genetic-environmental interactions are established in autism spectrum disorder (ASD), how environmental toxicants confer susceptibility remains unclear. This study aimed to investigate potential relationship between genetically predicted cerebrospinal fluid (CSF), metabolite levels and ASD liability, and to prioritize regulatory genes, key pathways, and candidate environmental toxicants. Methods: Using two ASD GWAS datasets (exploration data: 18,381 ASD cases/27,969 controls; validation data: 18,235 ASD cases/36,741 controls), we applied multi-omics approaches to prioritize ASD-associated CSF metabolites, regulatory SNPs, and genes. Enrichment analysis and protein–protein interaction (PPI) network analysis were performed on these metabolite-related genes to explore the potential mechanisms linking CSF metabolic disturbances to ASD. Finally, candidate environmental neurotoxicants were screened through protein-chemical interaction analysis, with binding relationships assessed via molecular docking prediction. Results: Two-sample Mendelian randomization (MR) analysis prioritized adenine and proline as candidate CSF metabolites with potential risk associations with ASD. Summary-data-based MR (SMR) prioritized 39 brain-specific quantitative trait loci (QTL) involving 35 candidate regulatory genes, including dual-metabolite modulator GRM8. Functional enrichment analyses suggested potential associations with mitochondrial dysfunction, Hippo signaling pathway, and microtubule dynamics impairment, with protein–protein interaction networks highlighting KATNA1/KATNAL2 as hubs. Protein-chemical interaction screening nominated 14 candidate environmental toxicants, including established chemicals (acetaminophen, valproic acid, estradiol) and novel candidates (SB-431542, K 7174, benzo[a]pyrene), with docking affinity assessed computationally. Conclusions: Our study provides suggestive evidence that elevated adenine and proline may be potential risk factors for ASD and suggests possible involvement of the mitochondrial–Hippo–microtubule pathway. We also propose benzo[a]pyrene as a candidate environmental toxicant that may perturb CSF metabolism. However, given the limited statistical significance, these findings require further validation.

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Data Availability Statement

The datasets analyzed during the current study are available from publicly accessible databases as follows: WADRC (ftp://ftp.biostat.wisc.edu/pub/lu_group/Projects/MWAS/, accessed on 1 September 2025), iPSYCH (https://ipsych.dk/fileadmin/ipsych.dk/Downloads/iPSYCH-PGC_ASD_Nov2017.gz, accessed on 1 September 2025), ADuLT (https://www.ebi.ac.uk/gwas/studies/GCST90275138, accessed on 1 September 2025), BrainMeta v2 cis-eQTL summary data (https://yanglab.westlake.edu.cn/data/SMR/BrainMeta_cis_eqtl_summary.tar.gz, accessed on 1 October 2025), BrainMeta v2 cis-sQTL summary data (https://yanglab.westlake.edu.cn/data/SMR/BrainMeta_cis_sqtl_summary.tar.gz, accessed on 1 October 2025), Brain-mMeta mQTL summary data (https://yanglab.westlake.edu.cn/data/SMR/Brain-mMeta.tar.gz, accessed on 1 October 2025). Other datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

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

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Version 2, 28 September 2026

• Funding: added National Natural Science Foundation of China: 31971116, 91854209, 92254301, 31801208; Capital Medical University

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 8 authors, 5 keywords, 8 MeSH terms, 138 references.

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This paper

Zhao, D., Guo, J., Zhang, Y., Lan, Y., Zhao, T., Xu, Y., Yang, Q., & Ye, H. (2026). Multi-Omic Analysis of Cerebrospinal Fluid Metabolites in Autism Spectrum Disorder: Biomarker Identification, Metabolic Genetics Insights, and Network Toxicology. Genes, 17(8), 874. https://doi.org/10.3390/genes17080874

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