The gut microbiome in differential diagnosis of diabetic kidney disease and membranous nephropathy

• Main Authors: Wei Yu, Jin Shang, Ruixue Guo, Fanliang Zhang, Weifeng Zhang, Yiding Zhang, Feng Wu, Hongyan Ren, Chao Liu, Jing Xiao, Zhanzheng Zhao
• Format: Article
• Language: English
• Published: Taylor & Francis Group 2020-01-01
• Series: Renal Failure
• Subjects: gut microbiome; 16s rrna; diabetic kidney disease; membranous nephropathy
• Online Access: http://dx.doi.org/10.1080/0886022X.2020.1837869

Background Diabetic kidney disease (DKD) and membranous nephropathy (MN) are the two major causes of end-stage renal disease (ESRD). Increasing evidence has shown that intestinal dysbiosis is associated with many diseases. The aim of this study was to explore the composition of the gut microbiome in DKD and MN patients. Methods 16S rRNA gene sequencing was performed on 271 fecal samples (DKD = 129 and MN = 142), and taxonomic annotation of microbial composition and function was completed. Results We observed distinct microbial communities between the two groups, with MN samples exhibiting more severe dysbiosis than DKD samples. Relative increases in genera producing short-chain fatty acids (SCFAs) in DKD and a higher proportion of potential pathogens in MN were the main contributors to the microbiome alterations in the two groups. Five-fold cross-validation was performed on a random forest model, and four operational taxonomic unit (OTU)-based microbial markers were selected to distinguish DKD from MN. The results showed 92.42% accuracy in the training set and 94.52% accuracy in the testing set, indicating high potential for these microbiome-based markers in separating MN from DKD. Overexpression of several amino acid metabolic pathways, carbohydrate metabolism and lipid metabolism was found in DKD, while interconversion of pentose/glucoronate and membrane transport in relation to ABC transporters and the phosphotransferase system were increased in MN. Conclusion The composition of the gut microbiome appears to differ considerably between patients with DKD and those with MN. Thus, microbiome-based markers could be used as an alternative tool to distinguish DKD and MN.