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羊水微生物组特征作为围产结局的预测生物标志物。

Microbiome profile of the amniotic fluid as a predictive biomarker of perinatal outcome.

机构信息

Department of Maternal-Fetal Biology, National Research Institute for Child Health and Development, Tokyo, 157-8535, Japan.

Department of Obstetrics and Gynecology, Faculty of Medicine, Fukuoka University, Fukuoka, 814-0180, Japan.

出版信息

Sci Rep. 2017 Sep 22;7(1):12171. doi: 10.1038/s41598-017-11699-8.

Abstract

Chorioamnionitis (CAM), an inflammation of the foetal membranes due to infection, is associated with preterm birth and poor perinatal prognosis. The present study aimed to determine whether CAM can be diagnosed prior to delivery based on the bacterial composition of the amniotic fluid (AF). AF samples from 79 patients were classified according to placental inflammation: Stage III (n = 32), CAM; Stage II (n = 27), chorionitis; Stage 0-I (n = 20), sub-chorionitis or no neutrophil infiltration; and normal AF in early pregnancy (n = 18). Absolute quantification and sequencing of 16S rDNA showed that in Stage III, the 16S rDNA copy number was significantly higher and the α-diversity index lower than those in the other groups. In principal coordinate analysis, Stage III formed a separate cluster from Stage 0-I, normal AF, and blank. Forty samples were classified as positive for microbiomic CAM (miCAM) defined by the presence of 11 bacterial species that were found to be significantly associated with CAM and some parameters of perinatal prognosis. The diagnostic accuracy for CAM according to miCAM was: sensitivity, approximately 94%, and specificity, 79-87%. Our findings indicate the possibility of predicting CAM prior to delivery based on the AF microbiome profile.

摘要

绒毛膜羊膜炎(CAM)是一种由于感染导致的胎儿膜炎症,与早产和围产期不良预后有关。本研究旨在确定是否可以根据羊水(AF)的细菌组成在分娩前诊断 CAM。根据胎盘炎症将 79 名患者的 AF 样本进行分类:III 期(n=32),CAM;II 期(n=27),绒毛膜炎;0-I 期(n=20),亚绒毛膜炎或无中性粒细胞浸润;和早孕正常 AF(n=18)。16S rDNA 的绝对定量和测序显示,在 III 期,16S rDNA 拷贝数明显高于其他组,α多样性指数较低。在主坐标分析中,III 期与 0-I 期、正常 AF 和空白形成了一个单独的聚类。40 个样本被归类为微生物 CAM(miCAM)阳性,miCAM 定义为存在与 CAM 和一些围产期预后参数显著相关的 11 种细菌。根据 miCAM 诊断 CAM 的准确性为:敏感性约为 94%,特异性为 79-87%。我们的研究结果表明,根据 AF 微生物组图谱在分娩前预测 CAM 的可能性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2023/5610236/25ab7f731997/41598_2017_11699_Fig1_HTML.jpg

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