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Published July 2023 | Published
Journal Article Open

Multi-level analysis of the gut–brain axis shows autism spectrum disorder-associated molecular and microbial profiles


Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by heterogeneous cognitive, behavioral and communication impairments. Disruption of the gut–brain axis (GBA) has been implicated in ASD although with limited reproducibility across studies. In this study, we developed a Bayesian differential ranking algorithm to identify ASD-associated molecular and taxa profiles across 10 cross-sectional microbiome datasets and 15 other datasets, including dietary patterns, metabolomics, cytokine profiles and human brain gene expression profiles. We found a functional architecture along the GBA that correlates with heterogeneity of ASD phenotypes, and it is characterized by ASD-associated amino acid, carbohydrate and lipid profiles predominantly encoded by microbial species in the genera Prevotella, Bifidobacterium, Desulfovibrio and Bacteroides and correlates with brain gene expression changes, restrictive dietary patterns and pro-inflammatory cytokine profiles. The functional architecture revealed in age-matched and sex-matched cohorts is not present in sibling-matched cohorts. We also show a strong association between temporal changes in microbiome composition and ASD phenotypes. In summary, we propose a framework to leverage multi-omic datasets from well-defined cohorts and investigate how the GBA influences ASD.

Additional Information

© The Author(s) 2023. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. J.T.M. was funded by the intramural research program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD). Y.S. and T.D.L. are supported by the Wellcome Trust (WT206194). M.W. is supported by the National Natural Science Foundation of China (program no. 82071733) and Shanghai talent development funding (no. 2020115). E.E. is supported by Israel Science Foundation grant 818/17 and a research grant provided by Teva Pharmaceuticals under their support of the Azrieli Faculty of Medicine. O.K. is supported by the European Research Council (ERC) under the European Union's Horizon 2020 Research and Innovation Program (grant agreement ERC-2020-COG no. 101001355). We would like to thank A. Packer, P. Wang, N. Volfovsky, K. Martin and J. Spiro for their critical review of the manuscript. We would like to thank S. Mirarab for feedback on the construction of the Greengenes2 and Web of Life databases. We would like to thank A. Amir for insights on processing shotgun metagenomics and 16S sequencing data using the GetData software package. We would also like to thank K. Liu, H. Sherman and X.-J. Kong for insightful discussions. These authors contributed equally: James T. Morton, Gaspar Taroncher-Oldenburg. Contributions: J.T.M. and G.T.-O. conceived and designed the study, developed the software package q2-matchmaker, analyzed the data, interpreted the results and wrote the manuscript. R.B. contributed to study design, data analysis and results interpretation. R.H.M. contributed to study design, data analysis and manuscript editing. R.J.X. and S.K.M. contributed to study design. G.R. and B.C. contributed to software development and manuscript editing. D.M., Q.Z., K.C., A.G., M.B. and Y.J. have contributed the Greengenes2 and Web of Life 2 databases. D.-M.J. and Y.S. contributed to data analysis. K.B., B.D.N., M.F.Z., M.D., O.V.A., A.S.K., A.N., M.M., M.W., J.C., S.J., S.M.-B., O.K, E.E., D.N.F., E.L., W.Z., V.F., V.N.D., D.P.W., M.E.B., R.K., J.A.G., S.M.D., T.D.L. J.C. and M.F.Z. provided access to data. All authors contributed to manuscript editing. Data availability. This study is based on previously published 16S, metagenomics, RNA-seq and metabolomics data. (The 16S sequencing data in Martin-Brevet et al. is available under accession number ERP147524. All processed datasets and harmonized metadata are available on Zenodo at 10.5281/zenodo.7877350 as well as on Github at https://github.com/mortonjt/asd_multiomics_analyses. Code availability. Software implementation of our Bayesian age-matched and sex-matched differential ranking algorithm can be found at https://github.com/flatironinstitute/q2-matchmaker. Our group-averaged differential ranking algorithm can be found at https://github.com/mortonjt/q2-differential. Finally, our analysis scripts can be found at https://github.com/mortonjt/asd_multiomics_analyses. We would like to acknowledge Matplotlib, Seaborn, Scipy, Numpy, Xarray, Arviz Scikit-learn, biom-format and Scikit-bio for providing the software foundation that this work was built upon. Competing interests: R.H.M. is Scientific Director at Precidiag, Inc. T.D.L. is a co-founder and Chief Scientific Officer of Microbiotica. S.K.M. is a co-founder and has equity in Axial Therapeutics. R.J.X. is a co-founder of Celsius Therapeutics and Jnana Therapeutics, a member of the Scientific Advisory Board at Nestle and a member of the Board of Directors at Moonlake Immunotherapeutics. R.B. is currently Executive Director of Prescient Design, a Genentech Accelerator. J.T.M. is the founder of Gutz Analytics and a co-founder of Integrated Omics AI. G.T.-O. is a Consultant-in-Residence at the Simons Foundation. The remaining authors declare no competing interests.

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Additional details

November 7, 2023
January 9, 2024