Gut microbial dysbiosis is associated with occurrence and post-surgical prognosis of unraptured cerebral aneurysm
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BACKGROUND
The microbiota has been reported to play an important role in the occurrence of brain aneurysms (CA). However, no microbiota or metabolite has been used for diagnosis or therapy of CA till now. Therefore, we investigated the shifts of gut microbiota and metabolites in CA patients, and explored the feasibility of using them as biomarkers and therapeutic targets.
METHODS
The microbial DNA was extracted from the stool samples of the CA and healthy volunteer groups. The variable V3-V4 region of the 16S rDNA gene was sequenced on a MiSeq system. R software package was used to analyze the sequence, and the variations in microbial composition was obtained. The correlation analysis of the differential intestinal bacteria, metabolites and blood parameters was explored based on a logistic regression model. A random forest algorithm was used to predict the classification of samples for further exploring the relationship between fecal microbiota and CA.
RESULTS
The α-diversity indexes demonstrated an altered within-sample microbial diversities between patients and healthy people. The subsequent beta diversity results indicated that shift in the between-sample microbial diversities of the intestinal microbiota was associated with the occurrence of cerebral aneurysm. Specifically, the abundance of some gut bacterial genera, such as Blautia and Faecalibacterium, changed significantly after CA. Intestinal metabolite enrichment results highlight the role of carbohydrate metabolic pathways in CA, including sedoheptulose 7-phosphate (S-7-P). The correlation analysis of the differential intestinal bacteria, metabolites and blood parameters indicated that intestinal bacteria and metabolites were related to host blood parameters. Then, the predictive models were employed to test the significance of the combination of differential bacteria, metabolites and blood parameters in CA diagnosis and prognosis. The predictive model built by Faecalibacterium and s7p obtained an area under ROC curve (AUC) of 99.7%, and Faecalibacterium and s-7-p were also associated with some metabolite that have significance in post-surgery prognosis of CA.
Conclusions
The gut microbiota and metabolites profiles of patients with CA were significantly altered. Bacterial genus Faecalibacterium and metabolite s-7-p could serve as potential biomarkers in CA prediction and post-surgery prognosis.
