The gut-brain axis in individuals with alcohol use disorder: An exploratory study of associations among clinical symptoms, brain morphometry, and the gut microbiome.

addiction alcohol use disorder gastrointestinal microbiome gut‐brain axis neuroimaging

Journal

Alcohol, clinical & experimental research
ISSN: 2993-7175
Titre abrégé: Alcohol Clin Exp Res (Hoboken)
Pays: United States
ID NLM: 9918609780906676

Informations de publication

Date de publication:
Jul 2024
Historique:
revised: 10 04 2024
received: 21 11 2023
accepted: 18 04 2024
medline: 10 7 2024
pubmed: 10 7 2024
entrez: 10 7 2024
Statut: ppublish

Résumé

Alcohol use disorder (AUD) is commonly associated with distressing psychological symptoms. Pathologic changes associated with AUD have been described in both the gut microbiome and brain, but the mechanisms underlying gut-brain signaling in individuals with AUD are unknown. This study examined associations among the gut microbiome, brain morphometry, and clinical symptoms in treatment-seeking individuals with AUD. We performed a secondary analysis of data collected during inpatient treatment for AUD in subjects who provided gut microbiome samples and had structural brain magnetic resonance imaging (MRI; n = 16). Shotgun metagenomics sequencing was performed, and the morphometry of brain regions of interest was calculated. Clinical symptom severity was quantified using validated instruments. Gut-brain modules (GBMs) used to infer neuroactive signaling potential from the gut microbiome were generated in addition to microbiome features (e.g., alpha diversity and bacterial taxa abundance). Bivariate correlations were performed between MRI and clinical features, microbiome and clinical features, and MRI and microbiome features. Amygdala volume was significantly associated with alpha diversity and the abundance of several bacteria including taxa classified to Blautia, Ruminococcus, Bacteroides, and Phocaeicola. There were moderate associations between amygdala volume and GBMs, including butyrate synthesis I, glutamate synthesis I, and GABA synthesis I & II, but these relationships were not significant after false discovery rate (FDR) correction. Other bacterial taxa with shared associations to MRI features and clinical symptoms included Escherichia coli and Prevotella copri. We identified gut microbiome features associated with MRI morphometry and AUD-associated symptom severity. Given the small sample size and bivariate associations performed, these results require confirmation in larger samples and controls to provide meaningful clinical inferences. Nevertheless, these results will inform targeted future research on the role of the gut microbiome in gut-brain communication and how signaling may be altered in patients with AUD.

Sections du résumé

BACKGROUND BACKGROUND
Alcohol use disorder (AUD) is commonly associated with distressing psychological symptoms. Pathologic changes associated with AUD have been described in both the gut microbiome and brain, but the mechanisms underlying gut-brain signaling in individuals with AUD are unknown. This study examined associations among the gut microbiome, brain morphometry, and clinical symptoms in treatment-seeking individuals with AUD.
METHODS METHODS
We performed a secondary analysis of data collected during inpatient treatment for AUD in subjects who provided gut microbiome samples and had structural brain magnetic resonance imaging (MRI; n = 16). Shotgun metagenomics sequencing was performed, and the morphometry of brain regions of interest was calculated. Clinical symptom severity was quantified using validated instruments. Gut-brain modules (GBMs) used to infer neuroactive signaling potential from the gut microbiome were generated in addition to microbiome features (e.g., alpha diversity and bacterial taxa abundance). Bivariate correlations were performed between MRI and clinical features, microbiome and clinical features, and MRI and microbiome features.
RESULTS RESULTS
Amygdala volume was significantly associated with alpha diversity and the abundance of several bacteria including taxa classified to Blautia, Ruminococcus, Bacteroides, and Phocaeicola. There were moderate associations between amygdala volume and GBMs, including butyrate synthesis I, glutamate synthesis I, and GABA synthesis I & II, but these relationships were not significant after false discovery rate (FDR) correction. Other bacterial taxa with shared associations to MRI features and clinical symptoms included Escherichia coli and Prevotella copri.
CONCLUSIONS CONCLUSIONS
We identified gut microbiome features associated with MRI morphometry and AUD-associated symptom severity. Given the small sample size and bivariate associations performed, these results require confirmation in larger samples and controls to provide meaningful clinical inferences. Nevertheless, these results will inform targeted future research on the role of the gut microbiome in gut-brain communication and how signaling may be altered in patients with AUD.

Identifiants

pubmed: 38982564
doi: 10.1111/acer.15346
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1261-1277

Subventions

Organisme : NIH Clinical Center
ID : Z99CL999999

Informations de copyright

© 2024 The Author(s). Alcohol, Clinical and Experimental Research published by Wiley Periodicals LLC on behalf of Research Society on Alcohol. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

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Auteurs

Katherine A Maki (KA)

Translational Biobehavioral and Health Disparities Branch, National Institutes of Health, Clinical Center, Bethesda, Maryland, USA.

Gwenyth R Wallen (GR)

Translational Biobehavioral and Health Disparities Branch, National Institutes of Health, Clinical Center, Bethesda, Maryland, USA.

Thomaz F S Bastiaanssen (TFS)

APC Microbiome Ireland and Department of Anatomy & Neuroscience, University College Cork, Cork, Ireland.

Li-Yueh Hsu (LY)

Radiology and Imaging Sciences, National Institutes of Health, Clinical Center, Bethesda, Maryland, USA.

Michael E Valencia (ME)

Translational Biobehavioral and Health Disparities Branch, National Institutes of Health, Clinical Center, Bethesda, Maryland, USA.

Vijay A Ramchandani (VA)

National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, Maryland, USA.

Melanie L Schwandt (ML)

National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, Maryland, USA.

Nancy Diazgranados (N)

National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, Maryland, USA.

John F Cryan (JF)

APC Microbiome Ireland and Department of Anatomy & Neuroscience, University College Cork, Cork, Ireland.

Reza Momenan (R)

Clinical NeuroImaging Research Core, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, Maryland, USA.

Jennifer J Barb (JJ)

Translational Biobehavioral and Health Disparities Branch, National Institutes of Health, Clinical Center, Bethesda, Maryland, USA.

Classifications MeSH