Evidence map›Paper›PMID 40041792›Full record

ArticleHealth science reports2025

Exploring the Association Between Human Blood Metabolites and Autism Spectrum Disorder Risk: A Bidirectional Mendelian Randomization Study.

Wenhua Li, Suya Ma, Yunong Tian

Abstract read
In one paragraph

Article in Health science reports, 2025. 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

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2 · The registry

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3 · Its place in the literature

Who cites it

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No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Wenhua LiState Key Laboratory of Component-Based Chinese Medicine, Ministry of Education, Key Laboratory of Pharmacology of Traditional Chinese Medicine Formulae, Institute of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine Tianjin China.ORCID 0000-0003-0257-7252
Suya MaGuang'anmen Hospital, China Academy of Chinese Medicine Sciences Beijing China.
Yunong TianCangZhou Hospital of Integrated Traditional Chinese and Western Medicine in Hebei Province Hebei China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Aims: Autism spectrum disorder (ASD) is a complex neurodevelopmental condition with a poorly understood etiology. Recent studies have suggested that metabolic dysregulation might be linked to the development of ASD; however, causal relationships remain unclear. This study aimed to investigate the causal association between these factors using two-sample Mendelian randomization (TSMR). Methods: We conducted a TSMR analysis to assess the relationship between blood metabolites and ASD using summarized GWAS data. The metabolite dataset from the Canadian Longitudinal Study of Aging included 1091 metabolites and 309 ratios from 7824 European individuals. The ASD data from the Psychiatric Genomics Consortium comprised 18,381 ASD cases and 27,969 controls. Blood metabolites were set as exposures with ASD as the outcome. We primarily used the inverse-variance weighted method, supplemented by MR-Egger, weighted median, simple mode, and weighted mode methods. We also conducted sensitivity analyses to confirm robustness. Replication, confounding, and reserve analyses were performed to verify causation. Additionally, metabolic pathway and network pharmacology analyses were conducted to explore potential mechanisms. Results: We identified 55 known metabolites including 13 metabolite ratios and 10 unknown blood metabolites associated with ASD. Additionally, our analysis identified 13 potential metabolic pathways, among which tryptophan metabolism was the most notable ( Conclusions: Our findings indicate that the dodecenedioate, methionine sulfone, cysteine to alanine ratio and proline to glutamate ratio have an impact on ASD. These results enhance our understanding of the metabolic pathways involved in ASD and could lead to new avenues for intervention and prevention. Further research is needed to explore the mechanisms underlying these associations and confirm these findings in different populations.

Indexed as

autism spectrum disorderblood metabolitesMendelian randomizationnetwork pharmacology

Identifiers

PMID40041792
PMCPMC11875788

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