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Metabolomic analysis of maternal mid-gestation plasma and cord blood in autism spectrum disorders

Molecular Psychiatry volume 28, pages 2355–2369 (2023)Cite this article

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Abstract

The discovery of prenatal and neonatal molecular biomarkers has the potential to yield insights into autism spectrum disorder (ASD) and facilitate early diagnosis. We characterized metabolomic profiles in ASD using plasma samples collected in the Norwegian Autism Birth Cohort from mothers at weeks 17–21 gestation (maternal mid-gestation, MMG, n = 408) and from children on the day of birth (cord blood, CB, n = 418). We analyzed associations using sex-stratified adjusted logistic regression models with Bayesian analyses. Chemical enrichment analyses (ChemRICH) were performed to determine altered chemical clusters. We also employed machine learning algorithms to assess the utility of metabolomics as ASD biomarkers. We identified ASD associations with a variety of chemical compounds including arachidonic acid, glutamate, and glutamine, and metabolite clusters including hydroxy eicospentaenoic acids, phosphatidylcholines, and ceramides in MMG and CB plasma that are consistent with inflammation, disruption of membrane integrity, and impaired neurotransmission and neurotoxicity. Girls with ASD have disruption of ether/non-ether phospholipid balance in the MMG plasma that is similar to that found in other neurodevelopmental disorders. ASD boys in the CB analyses had the highest number of dysregulated chemical clusters. Machine learning classifiers distinguished ASD cases from controls with area under the receiver operating characteristic (AUROC) values ranging from 0.710 to 0.853. Predictive performance was better in CB analyses than in MMG. These findings may provide new insights into the sex-specific differences in ASD and have implications for discovery of biomarkers that may enable early detection and intervention.

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Fig. 1: Chemical enrichment analyses reveals sex-specific altered chemical clusters in autism spectrum disorders (ASD).
Fig. 2: Autism spectrum disorders (ASD) predictive modeling.
Fig. 3: Venn diagram illustrating ASD-associated chemical compounds and clusters in MMG and CB plasma that are consistent with inflammation, disruption of membrane integrity, and impaired neurotransmission and neurotoxicity.

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Acknowledgements

This paper is dedicated to the memory of Bohyun Lee and Pål Suren-two brilliant young investigators who contributed to the design, execution and analyses presented here. We thank Aaron Cheng, Ziqi Zhou, Yan Wang, and Yuenling Cheng for data preparation and management, James Ng for sample preparation and handling. We are grateful to the participants in the MoBa and ABC studies. This work was funded by National Institutes of Health grants NS047537 and NS086122, the Jane Botsford Johnson foundation, the Norwegian Ministry of Health and Care Services, the Norwegian Ministry of Education and Research, and Research Council of Norway grants 189457, 190694, and 196452. The funding agencies did not participate in study design, data collection and interpretation, or the decision to submit the work for publication.

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  1. These authors contributed equally: Xiaoyu Che, Ayan Roy.

Authors and Affiliations

  1. Center for Infection and Immunity, Mailman School of Public Health, Columbia University, New York, NY, USA

    Xiaoyu Che, Ayan Roy & W. Ian Lipkin

  2. Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA

    Xiaoyu Che & Keming Zhang

  3. Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA

    Michaeline Bresnahan, Ezra Susser & W. Ian Lipkin

  4. New York State Psychiatric Institute, New York, NY, USA

    Michaeline Bresnahan & Ezra Susser

  5. Norwegian Institute of Public Health, Oslo, Norway

    Siri Mjaaland, Ted Reichborn-Kjennerud, Per Magnus & Camilla Stoltenberg

  6. Institute of Clinical Medicine, University of Oslo, Oslo, Norway

    Ted Reichborn-Kjennerud

  7. Department of Global Public Health, University of Bergen, Bergen, Norway

    Camilla Stoltenberg

  8. Department of Public Health Sciences, College of Medicine, Penn State University, State College, PA, 16801, USA

    Yimeng Shang

  9. UC Davis Genome Center—Metabolomics, University of California, Davis, CA, USA

    Oliver Fiehn

  10. Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA

    W. Ian Lipkin

  11. Department of Pathology and Cell Biology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA

    W. Ian Lipkin

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  1. Xiaoyu Che
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Contributions

CS, ES, MB, PM, and WIL developed the experimental design. OF directed metabolomics assays. XC directed statistical analyses and data interpretations. AR, WIL, and XC wrote the manuscript. AR, CS, ES, KZ, MB, OF, PM, SM, TR-K, WIL, XC, and YS contributed to the data analyses, edited, and approved the manuscript.

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Correspondence to W. Ian Lipkin.

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Che, X., Roy, A., Bresnahan, M. et al. Metabolomic analysis of maternal mid-gestation plasma and cord blood in autism spectrum disorders. Mol Psychiatry 28, 2355–2369 (2023). https://doi.org/10.1038/s41380-023-02051-w

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