Division of Digestive Diseases, David Geffen School at UCLA, Los Angeles, CA, 90095, USA.
Oppenheimer Center for Neurobiology of Stress and Resilience, CHS 42-210 MC737818 10833 Le Conte Avenue, Los Angeles, CA, 90095-7378, USA.
Microbiome. 2017 May 1;5(1):49. doi: 10.1186/s40168-017-0260-z.
BACKGROUND: Preclinical and clinical evidence supports the concept of bidirectional brain-gut microbiome interactions. We aimed to determine if subgroups of irritable bowel syndrome (IBS) subjects can be identified based on differences in gut microbial composition, and if there are correlations between gut microbial measures and structural brain signatures in IBS. METHODS: Behavioral measures, stool samples, and structural brain images were collected from 29 adult IBS and 23 healthy control subjects (HCs). 16S ribosomal RNA (rRNA) gene sequencing was used to profile stool microbial communities, and various multivariate analysis approaches were used to quantitate microbial composition, abundance, and diversity. The metagenomic content of samples was inferred from 16S rRNA gene sequence data using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt). T1-weighted brain images were acquired on a Siemens Allegra 3T scanner, and morphological measures were computed for 165 brain regions. RESULTS: Using unweighted Unifrac distances with hierarchical clustering on microbial data, samples were clustered into two IBS subgroups within the IBS population (IBS1 (n = 13) and HC-like IBS (n = 16)) and HCs (n = 23) (AUROC = 0.96, sensitivity 0.95, specificity 0.67). A Random Forest classifier provided further support for the differentiation of IBS1 and HC groups. Microbes belonging to the genera Faecalibacterium, Blautia, and Bacteroides contributed to this subclassification. Clinical features distinguishing the groups included a history of early life trauma and duration of symptoms (greater in IBS1), but not self-reported bowel habits, anxiety, depression, or medication use. Gut microbial composition correlated with structural measures of brain regions including sensory- and salience-related regions, and with a history of early life trauma. CONCLUSIONS: The results confirm previous reports of gut microbiome-based IBS subgroups and identify for the first time brain structural alterations associated with these subgroups. They provide preliminary evidence for the involvement of specific microbes and their predicted metabolites in these correlations.
背景：临床前和临床证据支持双向脑-肠微生物组相互作用的概念。我们旨在确定是否可以根据肠微生物组成的差异来识别肠易激综合征（IBS）患者的亚组，以及 IBS 患者的肠道微生物测量值与大脑结构特征之间是否存在相关性。
方法：从 29 名成人 IBS 和 23 名健康对照（HC）受试者中收集行为测量、粪便样本和结构脑图像。使用 16S 核糖体 RNA（rRNA）基因测序来描绘粪便微生物群落，并用各种多元分析方法来定量微生物组成、丰度和多样性。使用 Phylogenetic Investigation of Communities by Reconstruction of Unobserved States（PICRUSt）从 16S rRNA 基因序列数据推断样品的宏基因组内容。在 Siemens Allegra 3T 扫描仪上采集 T1 加权脑图像，并计算 165 个脑区的形态学测量值。
结果：使用未加权的 Unifrac 距离和微生物数据的层次聚类，将样本在 IBS 人群中聚类为两个 IBS 亚组（IBS1（n=13）和 HC 样 IBS（n=16））和 HC（n=23）（AUROC=0.96，敏感性 0.95，特异性 0.67）。随机森林分类器为 IBS1 和 HC 组的区分提供了进一步的支持。属于 Faecalibacterium、Blautia 和 Bacteroides 属的微生物有助于这种分类。区分这些组的临床特征包括早期生活创伤史和症状持续时间（IBS1 更长），但不包括自我报告的排便习惯、焦虑、抑郁或药物使用。肠道微生物组成与包括感觉和突显相关区域在内的脑区的结构测量值以及早期生活创伤史相关。
结论：结果证实了先前关于基于肠道微生物组的 IBS 亚组的报告，并首次确定了与这些亚组相关的大脑结构改变。它们为特定微生物及其预测代谢物在这些相关性中的参与提供了初步证据。
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