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Association between microbiome and the development of adverse posttraumatic neuropsychiatric sequelae after traumatic stress exposure

Authors :
Abigail L. Zeamer
Marie-Claire Salive
Xinming An
Francesca L. Beaudoin
Stacey L. House
Jennifer S. Stevens
Donglin Zeng
Thomas C. Neylan
Gari D. Clifford
Sarah D. Linnstaedt
Scott L. Rauch
Alan B. Storrow
Christopher Lewandowski
Paul I. Musey
Phyllis L. Hendry
Sophia Sheikh
Christopher W. Jones
Brittany E. Punches
Robert A. Swor
Lauren A. Hudak
Jose L. Pascual
Mark J. Seamon
Erica Harris
Claire Pearson
David A. Peak
Roland C. Merchant
Robert M. Domeier
Niels K. Rathlev
Brian J. O’Neil
Paulina Sergot
Leon D. Sanchez
Steven E. Bruce
Ronald C. Kessler
Karestan C. Koenen
Samuel A. McLean
Vanni Bucci
John P. Haran
Source :
Translational Psychiatry, Vol 13, Iss 1, Pp 1-14 (2023)
Publication Year :
2023
Publisher :
Nature Publishing Group, 2023.

Abstract

Abstract Patients exposed to trauma often experience high rates of adverse post-traumatic neuropsychiatric sequelae (APNS). The biological mechanisms promoting APNS are currently unknown, but the microbiota-gut-brain axis offers an avenue to understanding mechanisms as well as possibilities for intervention. Microbiome composition after trauma exposure has been poorly examined regarding neuropsychiatric outcomes. We aimed to determine whether the gut microbiomes of trauma-exposed emergency department patients who develop APNS have dysfunctional gut microbiome profiles and discover potential associated mechanisms. We performed metagenomic analysis on stool samples (n = 51) from a subset of adults enrolled in the Advancing Understanding of RecOvery afteR traumA (AURORA) study. Two-, eight- and twelve-week post-trauma outcomes for post-traumatic stress disorder (PTSD) (PTSD checklist for DSM-5), normalized depression scores (PROMIS Depression Short Form 8b) and somatic symptom counts were collected. Generalized linear models were created for each outcome using microbial abundances and relevant demographics. Mixed-effect random forest machine learning models were used to identify associations between APNS outcomes and microbial features and encoded metabolic pathways from stool metagenomics. Microbial species, including Flavonifractor plautii, Ruminococcus gnavus and, Bifidobacterium species, which are prevalent commensal gut microbes, were found to be important in predicting worse APNS outcomes from microbial abundance data. Notably, through APNS outcome modeling using microbial metabolic pathways, worse APNS outcomes were highly predicted by decreased L-arginine related pathway genes and increased citrulline and ornithine pathways. Common commensal microbial species are enriched in individuals who develop APNS. More notably, we identified a biological mechanism through which the gut microbiome reduces global arginine bioavailability, a metabolic change that has also been demonstrated in the plasma of patients with PTSD.

Details

Language :
English
ISSN :
21583188
Volume :
13
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Translational Psychiatry
Publication Type :
Academic Journal
Accession number :
edsdoj.fb57c63b495e44c08b1765a3bb2c473b
Document Type :
article
Full Text :
https://doi.org/10.1038/s41398-023-02643-8