Connections between the human gut microbiome and gestational diabetes mellitus.
Connections between the human gut microbiome and gestational diabetes mellitus.
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人类肠道微生物群与妊娠期糖尿病之间的联系。
DOI：
10.1093/gigascience/gix058
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发表时间：
2017-08-01
期刊：
影响因子：
9.2
通讯作者：
Qiu X
中科院分区：
文献类型：
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作者：
Kuang YS;Lu JH;Li SH;Li JH;Yuan MY;He JR;Chen NN;Xiao WQ;Shen SY;Qiu L;Wu YF;Hu CY;Wu YY;Li WD;Chen QZ;Deng HW;Papasian CJ;Xia HM;Qiu X
人体肠道微生物群可调节代谢健康，影响胰岛素抵抗，可能在妊娠期糖尿病(GDM)的发病机制中发挥重要作用。在这里，我们通过对43名GDM患者和81名健康孕妇在21-29周收集的粪便样本进行全基因组鸟枪法测序，比较了他们的肠道微生物组成，以探索GDM与微生物分类单位和功能基因组成的关系。一项全基因组关联研究确定了154个837个基因，它们聚为129个元基因组连锁群(MLGs)，用于物种描述，两个队列之间的相对丰度差异显著。在妊娠期糖尿病患者中，地塞米松副杆菌、变异克雷伯氏菌等菌株较多，而斯氏甲烷短杆菌、泽泻杆菌、双歧杆菌、真细菌等菌株含量较高。在对照组中含量较高。GDM富集型MLGs与对照富集型MLGs的总丰度之比与血糖水平呈正相关。随机森林模型表明，粪便MLGs具有很好的判别能力，可以预测GDM的状况。我们的研究发现了肠道微生物群和GDM状态之间的新关系，并表明微生物组成的变化可能被用于识别GDM的风险个体。
The human gut microbiome can modulate metabolic health and affect insulin resistance, and it may play an important role in the etiology of gestational diabetes mellitus (GDM). Here, we compared the gut microbial composition of 43 GDM patients and 81 healthy pregnant women via whole-metagenome shotgun sequencing of their fecal samples, collected at 21–29 weeks, to explore associations between GDM and the composition of microbial taxonomic units and functional genes. A metagenome-wide association study identified 154 837 genes, which clustered into 129 metagenome linkage groups (MLGs) for species description, with significant relative abundance differences between the 2 cohorts. Parabacteroides distasonis, Klebsiella variicola, etc., were enriched in GDM patients, whereas Methanobrevibacter smithii, Alistipes spp., Bifidobacterium spp., and Eubacterium spp. were enriched in controls. The ratios of the gross abundances of GDM-enriched MLGs to control-enriched MLGs were positively correlated with blood glucose levels. A random forest model shows that fecal MLGs have excellent discriminatory power to predict GDM status. Our study discovered novel relationships between the gut microbiome and GDM status and suggests that changes in microbial composition may potentially be used to identify individuals at risk for GDM.