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

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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Publication Details

Journal
Genes
Published
2026-07-27
DOI
https://doi.org/10.3390/genes17080874
Primary Topic
Autism Spectrum Disorder Research
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Yuanfeng Lan, Dan Zhao, Yu Zhang, Haihong Ye et al.
Genes
Autism Spectrum Disorder Research
article

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

Yuanfeng Lan, Dan Zhao, Yu Zhang, Haihong Ye, Tian Zhao, Yiliang Xu, Q T Yang, Junzhi Guo
article en

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.

GenesVol. 17(8)
Capital Medical University (CN), Gene Therapy Laboratory (FR), Beijing Anzhen Hospital (CN)
National Natural Science Foundation of China, Capital Medical University
Openalex Percentile: Top 7%
Autism Spectrum Disorder Research
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