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

James T. Morton, Dong Min Jin, Robert H. Mills, Yan Shao, Gibraan Rahman, Daniel McDonald, Qiyun Zhu, Metin Balaban, Yueyu Jiang, Kalen Cantrell, Antonio Gonzalez, Julie Carmel, Linoy Mia Frankiensztajn, Sandra Martin-Brevet, Kirsten Berding, Brittany D. Needham, María Fernanda Zurita, Maude David, Olga V. Averina, Alexey S. KovtunAntonio Noto, Michele Mussap, Mingbang Wang, Daniel N. Frank, Ellen Li, Wenhao Zhou, Vassilios Fanos, Valery N. Danilenko, Dennis P. Wall, Paúl Cárdenas, Manuel E. Baldeón, Sébastien Jacquemont, Omry Koren, Evan Elliott, Ramnik J. Xavier, Sarkis K. Mazmanian, Rob Knight, Jack A. Gilbert, Sharon M. Donovan, Trevor D. Lawley, Bob Carpenter, Richard Bonneau, Gaspar Taroncher-Oldenburg

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11 Citas (Scopus)

Resumen

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.

Idioma originalInglés
Páginas (desde-hasta)1208-1217
Número de páginas10
PublicaciónNature Neuroscience
Volumen26
N.º7
DOI
EstadoPublicada - 26 jun. 2023

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