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

TL;DR

This study explores how blood metabolites may influence autism risk using genetic data, identifying key metabolic pathways linked to autism.

Contribution

A bidirectional Mendelian randomization study reveals novel causal associations between specific blood metabolites and autism spectrum disorder.

Findings

55 known and 10 unknown blood metabolites were associated with autism spectrum disorder.

Tryptophan metabolism and other pathways like glucuronosyltransferase activity were highlighted as significant.

Metabolites like dodecenedioate and methionine sulfone showed a notable impact on ASD risk.

Abstract

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).

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.

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 (p = 0.0388). Gene Ontology functional analysis and Kyoto Encyclopedia of Genes and Genomes analysis highlighted crucial pathways, such as cellular glucuronidation, glucuronosyltransferase activity, and bile secretion, and the significance of the apical part of the cell.

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.

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