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Analysis of intestinal microbial communities of cerebral infarction and ischemia patients based on high throughput sequencing technology and glucose and lipid metabolism

Currently, cerebral infarction (CI) is the leading cause of disability and the second leading cause of mortality in China, seriously affecting patient quality of life. Ischemia (IS) is considered to be the early stage of CI. The present study aims to investigate the variation of intestinal microbial...

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Detalles Bibliográficos
Autores principales: Ji, Wenzhen, Zhu, Yu, Kan, Pengcheng, Cai, Ying, Wang, Zhida, Wu, Zijian, Yang, Ping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5647104/
https://www.ncbi.nlm.nih.gov/pubmed/28849032
http://dx.doi.org/10.3892/mmr.2017.7227
Descripción
Sumario:Currently, cerebral infarction (CI) is the leading cause of disability and the second leading cause of mortality in China, seriously affecting patient quality of life. Ischemia (IS) is considered to be the early stage of CI. The present study aims to investigate the variation of intestinal microbial communities in patients with CI and IS using high throughput sequencing technology, and then analyze the results to identify a novel potential pathogenic mechanism of CI and IS. In total, 8 patients with CI, 2 patients with IS and 10 healthy volunteers as a control were selected. Throughput sequencing technology was used to analyze the character and microbial population of the gut. The abundance of Escherichia, Bacteroides, Megamonas, Parabacteroides, Akkermansia, Prevotella, Faecalibacterium, Dialister, Bifidobacterium and Ruminococcus was the significant difference in the intestinal microbial communities of the CI and IS patients compared with the healthy group. It was also observed that CI and IS were closely associated with internal glucose metabolism. The intestinal gut disturbance of CI patients may be one of the causes inducing CI by glucose metabolism and maybe considered as a potential method to predict the disease.