Alteration of Gut Microbiota in Patients With Epilepsy and the Potential Index as a Biomarker - Gong, Xue; Liu, Xu; Chen, Chu; Lin, Jingfang; Li, Aiqing; Guo, Kundian; An, Dongmei; Zhou, Dong; Hong, Zhen (Frontiers in Microbiology, 2020)
Objective: To explore the structure and composition of the fecal microbiota of patients with epilepsy. Methods: Differences in the fecal microbiota between patients with epilepsy and healthy controls (HCs) from the same household were investigated and validated by utilizing 16S ribosomal RNA sequencing in two independent cohorts [exploration cohort (N=55 patients and N=46 HCs) and validation cohort (N=13 patients and N=10 HCs)]. Results: The alpha diversity indexes of the specimens from patients with epilepsy were much lower than those from the HCs (p<0.05). The composition and structure of the fecal microbiota differed between patients with different clinical prognoses and between patients and HCs (Adonis: p<0.05). Microbiome alterations in patients with epilepsy included increases in Actinobacteria and Verrucomicrobia and decreases in Proteobacteria at the phylum level and increases in Prevotella_9, Blautia, Bifidobacterium, and others at the genus level [linear discriminant analysis (LDA): 3.5] Patients with drug-resistant epilepsy showed enrichment of bacterial taxa in Actinobacteria, Verrucomicrobia and Nitrospirae and the genera Blautia, Bifidobacterium, Subdoligranulum, Dialister, and Anaerostipes (Kruskal-Wallis test: p<0.05). Gut microbiome-based analysis displayed predictive ability for disease diagnosis, with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.97 (95% CI, 0.84-0.98). Applying the model to our validation cohort resulted in an AUC of 0.96 (95% CI, 0.75-0.97). Notably, the model could distinguish drug-resistant from drug-sensitive epilepsy (AUC=0.85, 95% CI: 0.69-0.94). Conclusion: Patients with epilepsy exhibit substantial alterations of fecal microbiota composition, and specific gut commensal strains are altered depending on different clinical phenotypes and thus could serve as potential biomarkers for disease diagnosis.