Ren Zhigang, Fan Yajuan, Li Ang, Shen Quanquan, Wu Jian, Ren Lingyan, Lu Haifeng, Ding Suying, Ren Hongyan, Liu Chao, Liu Wenli, Gao Dan, Wu Zhongwen, Guo Shiyuan, Wu Ge, Liu Zhangsuo, Yu Zujiang, Li Lanjuan
Department of Infectious Diseases The First Affiliated Hospital of Zhengzhou University Zhengzhou 450052 China.
Gene Hospital of Henan Province Precision Medicine Center The First Affiliated Hospital of Zhengzhou University Zhengzhou 450052 China.
Adv Sci (Weinh). 2020 Sep 2;7(20):2001936. doi: 10.1002/advs.202001936. eCollection 2020 Oct.
Gut microbiota make up the largest microecosystem in the human body and are closely related to chronic metabolic diseases. Herein, 520 fecal samples are collected from different regions of China, the gut microbiome in chronic kidney disease (CKD) is characterized, and CKD classifiers based on microbial markers are constructed. Compared with healthy controls (HC, = 210), gut microbial diversity is significantly decreased in CKD ( = 110), and the microbial community is remarkably distinguished from HC. Genera and are enriched, while and are reduced in CKD. Fifty predicted microbial functions including tryptophan and phenylalanine metabolisms increase, while 36 functions including arginine and proline metabolisms decrease in CKD. Notably, five optimal microbial markers are identified using the random forest model. The area under the curve (AUC) reaches 0.9887 in the discovery cohort and 0.9512 in the validation cohort (49 CKD vs 63 HC). Importantly, the AUC reaches 0.8986 in the extra diagnosis cohort from Hangzhou. Moreover, and are increased with CKD progression. Thirteen operational taxonomy units are correlated with six clinical indicators of CKD. In conclusion, this study comprehensively characterizes gut microbiome in non-dialysis CKD and demonstrates the potential of microbial markers as non-invasive diagnostic tools for CKD in different regions of China.
肠道微生物群构成了人体最大的微生态系统,并且与慢性代谢性疾病密切相关。在此,从中国不同地区收集了520份粪便样本,对慢性肾脏病(CKD)中的肠道微生物群进行了表征,并构建了基于微生物标志物的CKD分类器。与健康对照(HC,n = 210)相比,CKD患者(n = 110)的肠道微生物多样性显著降低,并且微生物群落与HC有明显区别。在CKD中,属 和 富集,而 属和 属减少。包括色氨酸和苯丙氨酸代谢在内的50种预测的微生物功能增加,而包括精氨酸和脯氨酸代谢在内的36种功能在CKD中减少。值得注意的是,使用随机森林模型鉴定出了五个最佳微生物标志物。在发现队列中曲线下面积(AUC)达到0.9887,在验证队列中(49例CKD对63例HC)达到0.9512。重要的是,在来自杭州的额外诊断队列中AUC达到0.8986。此外, 和 随着CKD进展而增加。13个操作分类单元与CKD的六个临床指标相关。总之,本研究全面表征了非透析CKD中的肠道微生物群,并证明了微生物标志物作为中国不同地区CKD非侵入性诊断工具的潜力。