AUTHOR=Chen Jiaxin , Chi Beibei , Ma Jiaying , Zhang Junmei , Gu Qilu , Xie Huijia , Kong Yu , Yao Shanshan , Liu Jiaming , Sun Jing , Chen Songfang TITLE=Gut microbiota signature as predictors of adverse outcomes after acute ischemic stroke in patients with hyperlipidemia JOURNAL=Frontiers in Cellular and Infection Microbiology VOLUME=12 YEAR=2022 URL=https://www.frontiersin.org/journals/cellular-and-infection-microbiology/articles/10.3389/fcimb.2022.1073113 DOI=10.3389/fcimb.2022.1073113 ISSN=2235-2988 ABSTRACT=Introduction

The alterations of gut microbiota have been associated with multiple diseases. However, the relationship between gut microbiota and adverse outcomes of hyperlipidemic stroke patients remains unclear. Here we determined the gut microbial signature to predict the poor outcome of acute ischemic stroke (AIS) with hyperlipidemia (POAH).

Methods

Fecal samples from hyperlipidemic stroke patients were collected, which further analyzed by 16s rRNA gene sequencing. The diversity, community composition and differential gut microbiota were evaluated. The adverse outcomes were determined by modified Rankin Scale (mRS) scores at 3 months after admission. The diagnostic performance of microbial characteristics in predicting adverse outcomes was assessed by receiver operating characteristic (ROC) curves.

Results

Our results showed that the composition and structure of gut microbiota between POAH patients and good outcome of AIS with hyperlipidemia (GOAH) patients were different. The characteristic gut microbiota of POAH patients was that the relative abundance of Enterococcaceae and Enterococcus were increased, while the relative abundance of Lachnospiraceae, Faecalibacterium, Rothia and Butyricicoccus were decreased. Moreover, the characteristic gut microbiota were correlated with many clinical parameters, such as National Institutes of Health Stroke Scale (NIHSS) score, mean arterial pressure, and history of cerebrovascular disease. Moreover, the ROC models based on the characteristic microbiota or the combination of characteristic microbiota with independent risk factors could distinguish POAH patients and GOAH patients (area under curve is 0.694 and 0.971 respectively).

Conclusions

These findings revealed the microbial characteristics of POAH, which highlighted the predictive capability of characteristic microbiota in POAH patients.