Sibei Tao1, Lingzhi Li1, Ling Li1, Yuan Liu2, Qian Ren1, Min Shi1, Jing Liu1, Jing Jiang1, Huichao Ma1, Zhuo Huang1, Zijing Xia1, Jing Pan1, Tiantian Wei1, Yan Wang1, Peiyun Li1, Tian Lan1, Xi Tang1, Xiaoxi Zeng3, Song Lei4, Huairong Tang2, Liang Ma5,6, Ping Fu7. 1. Kidney Research Laboratory, Division of Nephrology and National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, Chengdu, 610041, China. 2. Chinese Health Service Management Department, West China Hospital of Sichuan University, Chengdu, 610041, China. 3. West China Biomedical Big Data Center, Sichuan University, Chengdu, 610041, China. 4. Department of Pathology, West China Hospital of Sichuan University, Chengdu, 610041, China. 5. Kidney Research Laboratory, Division of Nephrology and National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, Chengdu, 610041, China. liang_m@scu.edu.cn. 6. Department of Nephrology, Chinese PLA General Hospital, Chinese PLA Institute of Nephrology, State Key Laboratory of Kidney Diseases, National Clinical Research Center of Kidney Diseases, Beijing Key Laboratory of Kidney Disease, Beijing, 10000, China. liang_m@scu.edu.cn. 7. Kidney Research Laboratory, Division of Nephrology and National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, Chengdu, 610041, China. fupinghx@163.com.
Abstract
AIMS: Type 2 diabetes mellitus (T2DM) has a rising prevalence and gut microbiota involvement is increasingly recognized. Diabetic nephropathy (DN) is a major complication of T2DM. The aim of the study was to understand the gut-kidney axis by an analysis of gut microbiota composition among biopsy-proven DN, T2DM without kidney disease, and healthy control. METHODS: Fecal samples were collected from 14 DNs, 14 age/gender-matched T2DMs without renal diseases (DM), 14 age and gender-matched healthy controls (HC) and household contacts (HH) of DM group. The microbiota composition was analyzed by 16sRNA microbial profiling approach. RESULTS: Substantial differences were found in the richness of gut microbiota and the variation of bacteria population in DM compared to HC, and DN compared to DM, respectively. DM could be accurately distinguished from age/gender-matched healthy controls by the variable of genus g_Prevotella_9 (AUC = 0.9), and DN patients could be accurately distinguished from age/gender-matched DM by the variables of two genera (g_Escherichia-Shigella and g_Prevotella_9, AUC = 0.86). The microbiota composition of HH group was close to that of HC group, and was different from DM group. Under the same diet, DM could be more accurately detected by the same genus (g_Prevotella_9, AUC = 0.92). CONCLUSION: Gut microbiota composition was explored to be related to the occurrence of biopsy-proven DN from DM. DM could be distinguished from HC by detecting g_Prevotella_9 level in feces, while DN was different from DM by the variables of g_Escherichia-Shigella and g_Prevotella_9, which potentially contributed to the physiopathological diagnosis of DN from DM.
AIMS: Type 2 diabetes mellitus (T2DM) has a rising prevalence and gut microbiota involvement is increasingly recognized. Diabetic nephropathy (DN) is a major complication of T2DM. The aim of the study was to understand the gut-kidney axis by an analysis of gut microbiota composition among biopsy-proven DN, T2DM without kidney disease, and healthy control. METHODS: Fecal samples were collected from 14 DNs, 14 age/gender-matched T2DMs without renal diseases (DM), 14 age and gender-matched healthy controls (HC) and household contacts (HH) of DM group. The microbiota composition was analyzed by 16sRNA microbial profiling approach. RESULTS: Substantial differences were found in the richness of gut microbiota and the variation of bacteria population in DM compared to HC, and DN compared to DM, respectively. DM could be accurately distinguished from age/gender-matched healthy controls by the variable of genus g_Prevotella_9 (AUC = 0.9), and DN patients could be accurately distinguished from age/gender-matched DM by the variables of two genera (g_Escherichia-Shigella and g_Prevotella_9, AUC = 0.86). The microbiota composition of HH group was close to that of HC group, and was different from DM group. Under the same diet, DM could be more accurately detected by the same genus (g_Prevotella_9, AUC = 0.92). CONCLUSION: Gut microbiota composition was explored to be related to the occurrence of biopsy-proven DN from DM. DM could be distinguished from HC by detecting g_Prevotella_9 level in feces, while DN was different from DM by the variables of g_Escherichia-Shigella and g_Prevotella_9, which potentially contributed to the physiopathological diagnosis of DN from DM.
Entities:
Keywords:
Diabetic nephropathy; Gut microbiota; Gut–kidney axis; Type 2 diabetes mellitus
Authors: Nadezda V Andrianova; Vasily A Popkov; Natalia S Klimenko; Alexander V Tyakht; Galina V Baydakova; Olga Y Frolova; Ljubava D Zorova; Irina B Pevzner; Dmitry B Zorov; Egor Y Plotnikov Journal: Metabolites Date: 2020-04-04
Authors: Ruijuan Dong; Ming Bai; Jin Zhao; Di Wang; Xiaoxuan Ning; Shiren Sun Journal: Front Cell Infect Microbiol Date: 2020-10-20 Impact factor: 5.293