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癫痫伴腹泻婴儿肠道微生物群组成改变及潜在指示生物标志物

Altered intestinal microbiota composition with epilepsy and concomitant diarrhea and potential indicator biomarkers in infants.

作者信息

Liu Tingting, Jia Fengan, Guo Ying, Wang Qi, Zhang Xiaoge, Chang Fan, Xie Yun

机构信息

Department of Pediatrics, Northwest Women's and Children's Hospital, Xi'an, China.

Shaanxi Institute of Microbiology, Xi'an, China.

出版信息

Front Microbiol. 2023 Jan 11;13:1081591. doi: 10.3389/fmicb.2022.1081591. eCollection 2022.

Abstract

INTRODUCTION

The diversity and dysregulation of intestinal microbiota is related to the pathology of epilepsy. Gut microbiota plays an important role in epilepsy, and regulating intestinal microbiota through exogenous intervention can alleviate symptoms. However, there are no studies about the effects of epilepsy-related diarrhea on gut microbiota.

METHODS

The diversity and dysregulation of intestinal microbiota is related to the pathology of epilepsy. Gut microbiota plays an important role in epilepsy, and regulating intestinal microbiota through exogenous intervention can alleviate symptoms. However, there are no studies about the effects of epilepsy-related diarrhea on gut microbiota. To evaluate changes in gut microbiota structure and composition in patients with epilepsy and associated diarrhea, the structure and composition of the fecal microbiota among patients with epilepsy (EP, 13 cases), epilepsy with diarrhea (ED, 13 cases), and probiotic treatments (PT, 13 cases), and healthy controls (CK, seven cases) were investigated and validated by utilizing high-throughput 16S rRNA sequencing.

RESULTS

The results showed that the α-diversity indexes indicated that richness and phylogenetic diversity had no significant differences among groups. However, the variation of β-diversity indicated that the structure and composition of intestinal microbiota were significantly different among the CK, EP, ED, and PT groups (permutational multivariate analysis of variance, -value = 0.001). Normalized stochasticity ratio and β-nearest taxon index indicated that stochastic mechanisms exerted increasing influence on community differences with epilepsy and associated diarrhea. ED microbiome alterations include increased Proteobacteria and decreased Actinobacteria and Firmicutes at the phylum level. was the core microbe in CK, EP, and PT, whereas it decreased significantly in ED. In contrast, was the core microbe in CK and ED, whereas it increased significantly in ED (Tukey's multiple comparisons test, adjusted -value <0.05). The association network in CK has higher complexity and aggregation than in the other groups. The EP network indicated high connectivity density within each community and high sparsity among communities. The bacterial community network of the ED had a more compact local interconnection, which was in contrast to that of PT. The top 7 microbial amplicon sequence variant-based markers that were selected by machine learning to distinguish the groups of epilepsy, probiotic treatments, and healthy infants had stronger discrimination ability. In addition, ASVs_1 () and ASVs_3 () had the most importance in the recognition.

DISCUSSION

Our research finally showed that infants with epilepsy, epilepsy with diarrhea, and probiotic treatments exhibit substantial alterations of intestinal microbiota structure and composition, and specific intestinal strains are altered according to different clinical phenotypes and can therefore be used as potential biomarkers for disease diagnosis.

摘要

引言

肠道微生物群的多样性和失调与癫痫的病理过程有关。肠道微生物群在癫痫中起重要作用,通过外源性干预调节肠道微生物群可缓解症状。然而,尚无关于癫痫相关性腹泻对肠道微生物群影响的研究。

方法

肠道微生物群的多样性和失调与癫痫的病理过程有关。肠道微生物群在癫痫中起重要作用,通过外源性干预调节肠道微生物群可缓解症状。然而,尚无关于癫痫相关性腹泻对肠道微生物群影响的研究。为评估癫痫伴腹泻患者肠道微生物群结构和组成的变化,采用高通量16S rRNA测序技术对癫痫患者(EP,13例)、癫痫伴腹泻患者(ED,13例)、益生菌治疗患者(PT,13例)和健康对照者(CK,7例)的粪便微生物群结构和组成进行了研究和验证。

结果

结果显示,α多样性指数表明各组间丰富度和系统发育多样性无显著差异。然而,β多样性的变化表明,CK、EP、ED和PT组之间肠道微生物群的结构和组成存在显著差异(置换多变量方差分析,P值 = 0.001)。标准化随机比率和β最近分类单元指数表明,随机机制对癫痫及相关腹泻的群落差异影响越来越大。ED微生物群的改变包括门水平上变形菌门增加,放线菌门和厚壁菌门减少。 是CK、EP和PT组的核心微生物,而在ED组中显著减少。相反, 是CK和ED组的核心微生物,而在ED组中显著增加(Tukey多重比较检验,校正P值 <0.05)。CK组的关联网络比其他组具有更高的复杂性和聚集性。EP网络表明每个群落内的连接密度高,群落间的稀疏度高。ED组的细菌群落网络具有更紧密的局部互连,这与PT组相反。通过机器学习选择的用于区分癫痫组、益生菌治疗组和健康婴儿组的前7个基于微生物扩增子序列变异的标记物具有更强的区分能力。此外,ASVs_1( )和ASVs_3( )在识别中最为重要。

讨论

我们的研究最终表明,癫痫婴儿、癫痫伴腹泻婴儿和益生菌治疗婴儿的肠道微生物群结构和组成存在实质性改变,特定的肠道菌株根据不同的临床表型而改变,因此可作为疾病诊断的潜在生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8589/9874329/b6d6f13817e9/fmicb-13-1081591-g001.jpg

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