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

Ren Fail. 2020 Nov;42(1):1100-1110. doi: 10.1080/0886022X.2020.1837869.

Abstract

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.

Keywords: 16S rRNA; Gut microbiome; diabetic kidney disease; membranous nephropathy.

MeSH terms

  • Diabetic Nephropathies / diagnosis
  • Diabetic Nephropathies / microbiology*
  • Diagnosis, Differential
  • Dysbiosis / microbiology
  • Feces / microbiology*
  • Gastrointestinal Microbiome / genetics*
  • Glomerulonephritis, Membranous / diagnosis
  • Glomerulonephritis, Membranous / microbiology*
  • Humans
  • RNA, Ribosomal, 16S / genetics*
  • ROC Curve

Substances

  • RNA, Ribosomal, 16S

Grants and funding

This work was supported by the National Natural Science Foundation of China [Grant Nos. 81873611 and 81700633], the Science and Technology Innovation Team of Henan [Grant No. 17IRTSTHN020], and the Foundation for Leading Personnel of the Central Plains of China [Grant No. 194200510006].