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Gut Microbiota and Targeted Biomarkers Analysis in Patients With Cognitive Impairment

Gut microbial alteration is closely associated with brain disorders including cognitive impairment (CI). Gut microbes have the potential to predicate the development of diseases. However, the gut microbial markers for CI remain to be elucidated. In this study, the gut microbial alterations were asse...

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Autores principales: Lu, Shourong, Yang, Ying, Xu, Qiao, Wang, Shuqiang, Yu, Jie, Zhang, Bingshan, Wang, Zhuo, Zhang, Yunyun, Lu, Wenwei, Hong, Kan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8891499/
https://www.ncbi.nlm.nih.gov/pubmed/35250836
http://dx.doi.org/10.3389/fneur.2022.834403
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author Lu, Shourong
Yang, Ying
Xu, Qiao
Wang, Shuqiang
Yu, Jie
Zhang, Bingshan
Wang, Zhuo
Zhang, Yunyun
Lu, Wenwei
Hong, Kan
author_facet Lu, Shourong
Yang, Ying
Xu, Qiao
Wang, Shuqiang
Yu, Jie
Zhang, Bingshan
Wang, Zhuo
Zhang, Yunyun
Lu, Wenwei
Hong, Kan
author_sort Lu, Shourong
collection PubMed
description Gut microbial alteration is closely associated with brain disorders including cognitive impairment (CI). Gut microbes have the potential to predicate the development of diseases. However, the gut microbial markers for CI remain to be elucidated. In this study, the gut microbial alterations were assessed using16S rRNA sequencing, and identified the gut microbial markers using a random forest model. The results showed that there were significant gut microbial differences between the control and CI groups based on beta diversity (p < 0.002). Patients with CI had higher abundances of Actinobacteria and Proteobacteria but lower proportions of Bcateroidetes and Firmicutes vs. that in the control group. Patients had 39 special genera and the control subjects had 11 special genera. Furthermore, 11 genera such as Blautia, Roseburia, and Lactococcus and 18 genera such as Lactobacillus, Ruminococcus 2, and Akkermansia were the differential taxa in the control and CI groups, respectively. Gene functions related to nutrient metabolisms were upregulated in patients with CI. This suggested that the huge differences in gut microbes between the two groups and gut microbiota had the potential to predicate the development of CI. Based on machine learning results, 15 genera such as Lactobacillus, Bifidobacterium, and Akkermansia were selected as the optimal marker set to predicate CI with an area under curve (AUC) value of 78.4%. The results revealed the gut microbial markers for CI and provided a potential diagnosis tool to prevent the development of CI in the elderly.
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spelling pubmed-88914992022-03-04 Gut Microbiota and Targeted Biomarkers Analysis in Patients With Cognitive Impairment Lu, Shourong Yang, Ying Xu, Qiao Wang, Shuqiang Yu, Jie Zhang, Bingshan Wang, Zhuo Zhang, Yunyun Lu, Wenwei Hong, Kan Front Neurol Neurology Gut microbial alteration is closely associated with brain disorders including cognitive impairment (CI). Gut microbes have the potential to predicate the development of diseases. However, the gut microbial markers for CI remain to be elucidated. In this study, the gut microbial alterations were assessed using16S rRNA sequencing, and identified the gut microbial markers using a random forest model. The results showed that there were significant gut microbial differences between the control and CI groups based on beta diversity (p < 0.002). Patients with CI had higher abundances of Actinobacteria and Proteobacteria but lower proportions of Bcateroidetes and Firmicutes vs. that in the control group. Patients had 39 special genera and the control subjects had 11 special genera. Furthermore, 11 genera such as Blautia, Roseburia, and Lactococcus and 18 genera such as Lactobacillus, Ruminococcus 2, and Akkermansia were the differential taxa in the control and CI groups, respectively. Gene functions related to nutrient metabolisms were upregulated in patients with CI. This suggested that the huge differences in gut microbes between the two groups and gut microbiota had the potential to predicate the development of CI. Based on machine learning results, 15 genera such as Lactobacillus, Bifidobacterium, and Akkermansia were selected as the optimal marker set to predicate CI with an area under curve (AUC) value of 78.4%. The results revealed the gut microbial markers for CI and provided a potential diagnosis tool to prevent the development of CI in the elderly. Frontiers Media S.A. 2022-02-17 /pmc/articles/PMC8891499/ /pubmed/35250836 http://dx.doi.org/10.3389/fneur.2022.834403 Text en Copyright © 2022 Lu, Yang, Xu, Wang, Yu, Zhang, Wang, Zhang, Lu and Hong. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neurology
Lu, Shourong
Yang, Ying
Xu, Qiao
Wang, Shuqiang
Yu, Jie
Zhang, Bingshan
Wang, Zhuo
Zhang, Yunyun
Lu, Wenwei
Hong, Kan
Gut Microbiota and Targeted Biomarkers Analysis in Patients With Cognitive Impairment
title Gut Microbiota and Targeted Biomarkers Analysis in Patients With Cognitive Impairment
title_full Gut Microbiota and Targeted Biomarkers Analysis in Patients With Cognitive Impairment
title_fullStr Gut Microbiota and Targeted Biomarkers Analysis in Patients With Cognitive Impairment
title_full_unstemmed Gut Microbiota and Targeted Biomarkers Analysis in Patients With Cognitive Impairment
title_short Gut Microbiota and Targeted Biomarkers Analysis in Patients With Cognitive Impairment
title_sort gut microbiota and targeted biomarkers analysis in patients with cognitive impairment
topic Neurology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8891499/
https://www.ncbi.nlm.nih.gov/pubmed/35250836
http://dx.doi.org/10.3389/fneur.2022.834403
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