Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China.
Department of Obstetrics, Hunan Provincial Maternal and Child Health Hospital, Changsha, China.
Front Cell Infect Microbiol. 2020 Feb 27;10:58. doi: 10.3389/fcimb.2020.00058. eCollection 2020.
Dysbiosis of human gut microbiota is associated with a wide range of metabolic disorders, including gestational diabetes mellitus (GDM). Yet whether gut microbiota dysbiosis participates in the etiology of GDM remains largely unknown. Our study was initiated to determine whether the alternations in gut microbial composition during early pregnancy linked to the later development of GDM, and explore the feasibility of microbial biomarkers for the early prediction of GDM. This nested case-control study was based upon an early pregnancy follow-up cohort (ChiCTR1900020652). Gut microbiota profiles of 98 subjects with GDM and 98 matched healthy controls during the early pregnancy (10-15 weeks) were assessed via 16S rRNA gene amplicon sequencing of V4 region. The data set was randomly split into a discovery set and a validation set, the former was used to analyze the differences between GDM cases and controls in gut microbial composition and functional annotation, and to establish an early identification model of GDM, then the performance of the model was verified by the external validation set. Bioinformatic analyses revealed changes to gut microbial composition with significant differences in relative abundance between the groups. Specifically, , and were enriched in the GDM group, whereas group, etc. remained dominant in the controls. Correlation analysis revealed that GDM-enriched genera and were positively correlated with fasting blood glucose levels, while three control-enriched genera (, and ) were the opposite. Further, GDM functional annotation modules revealed enrichment of modules for sphingolipid metabolism, starch and sucrose metabolism, etc., while lysine biosynthesis and nitrogen metabolism were reduced. Finally, five genera and two clinical indices were included in the linear discriminant analysis model for the prediction of GDM; the areas under receiver operating characteristic curves of the training and validation sets were 0.736 (95% confidence interval: 0.663-0.808) and 0.696 (0.575-0.818), respectively. Gut bacterial dysbiosis in early pregnancy was found to be associated with the later development of GDM, and gut microbiota-targeted biomarkers might be utilized as potential predictors of GDM.
人类肠道微生物群落的失调与广泛的代谢紊乱有关,包括妊娠期糖尿病(GDM)。然而,肠道微生物群落失调是否参与 GDM 的病因尚不清楚。我们的研究旨在确定妊娠早期肠道微生物组成的变化是否与 GDM 的后期发展有关,并探讨微生物生物标志物用于 GDM 早期预测的可行性。这项嵌套病例对照研究基于一项妊娠早期随访队列(ChiCTR1900020652)。通过 16S rRNA 基因扩增子测序 V4 区,评估了 98 例 GDM 患者和 98 例匹配健康对照者在妊娠早期(10-15 周)的肠道微生物群谱。数据集随机分为发现集和验证集,前者用于分析 GDM 病例与对照组肠道微生物组成和功能注释的差异,并建立 GDM 的早期识别模型,然后通过外部验证集验证模型的性能。生物信息学分析显示,肠道微生物组成发生变化,两组间相对丰度存在显著差异。具体而言,在 GDM 组中富集了 、 和 ,而在对照组中仍以 组等为主。相关性分析显示,GDM 富集属 和 与空腹血糖水平呈正相关,而三个对照富集属(、和 )则相反。此外,GDM 功能注释模块显示鞘脂代谢、淀粉和蔗糖代谢等模块的富集,而赖氨酸生物合成和氮代谢减少。最后,线性判别分析模型纳入了 5 个属和 2 个临床指标用于预测 GDM;训练集和验证集的受试者工作特征曲线下面积分别为 0.736(95%置信区间:0.663-0.808)和 0.696(0.575-0.818)。妊娠早期肠道细菌失调与 GDM 的后期发展有关,肠道微生物靶向生物标志物可能作为 GDM 的潜在预测指标。