The Diagnostic Value of Gut Microbiota Analysis for Post-Stroke Sleep Disorders

Background: Gut microbiota have been associated with many psychiatric disorders. However, the changes in the composition of gut microbiota in patients with post-stroke sleep disorders (PSSDs) remain unclear. Here, we determined the gut microbial signature of PSSD patients. Methods: Fecal samples of...

Full description

Bibliographic Details
Main Authors: Huijia Xie, Jiaxin Chen, Qionglei Chen, Yiting Zhao, Jiaming Liu, Jing Sun, Xuezhen Hu
Format: Article
Language:English
Published: MDPI AG 2023-09-01
Series:Diagnostics
Subjects:
Online Access:https://www.mdpi.com/2075-4418/13/18/2970
Description
Summary:Background: Gut microbiota have been associated with many psychiatric disorders. However, the changes in the composition of gut microbiota in patients with post-stroke sleep disorders (PSSDs) remain unclear. Here, we determined the gut microbial signature of PSSD patients. Methods: Fecal samples of 205 patients with ischemic stroke were collected within 24 h of admission and were further analyzed using 16 s RNA gene sequencing followed by bioinformatic analysis. The diversity, community composition, and differential microbes of gut microbiota were assessed. The outcome of sleep disorders was determined by the Pittsburgh Sleep Quality Index (PSQI) at 3 months after admission. The diagnostic performance of microbial characteristics in predicting PSSDs was assessed by receiver operating characteristic (ROC) curves. Results: Our results showed that the composition and structure of microbiota in patients with PSSDs were different from those without sleep disorders (PSNSDs). Moreover, the linear discriminant analysis effect size (LEfSe) showed significant differences in gut-associated bacteria, such as species of <i>Streptococcus</i>, <i>Granulicatella</i>, <i>Dielma</i>, <i>Blautia</i>, <i>Paeniclostridium,</i> and <i>Sutterella</i>. We further managed to identify the optimal microbiota signature and revealed that the predictive model with eight operational-taxonomic-unit-based biomarkers achieved a high accuracy in PSSD prediction (AUC = 0.768). <i>Blautia</i> and <i>Streptococcus</i> were considered to be the key microbiome signatures for patients with PSSD. Conclusions: These findings indicated that a specific gut microbial signature was an important predictor of PSSDs, which highlighted the potential of microbiota as a promising biomarker for detecting PSSD patients.
ISSN:2075-4418