Causal relationship between gut microbiota and diabetic nephropathy: A bidirectional mendelian randomization study

Cell Mol Biol (Noisy-le-grand). 2024 Apr 28;70(4):127-133. doi: 10.14715/cmb/2024.70.4.20.

Abstract

In this study, we summarized the key findings and potential implications of association studies investigating the relationship between gut microbiota composition and risks for Diabetic nephropathy (DN). We used Mendelian randomization (MR) analysis to explore the relationship between gut microbiota and DN using two different publicly available DN databases. The results were also summarized using five mainstream MR analysis methods. We controlled for various possible biases in the results. The results showed that specific bacterial genera were associated with increased or decreased risk of DN. These associations can be attributed to a variety of factors, including metabolites produced by certain bacteria. Most of our findings are consistent with the existing research findings, but there are still some differences with the existing results. In addition, we also pointed out that some microbiota that may be associated with DN but remain unnoticed can bring new research directions. Our work made use of MR, a reliable technique for examining causal correlations using genetic data investigating potential processes, carrying out longitudinal studies, looking into intervention options, and using a multi-omics approach may be future research avenues. Further, our findings also point to a few unexplored possible study paths for DN in the future. These initiatives may improve our reconciliation of the internal relationships between the gut microbiota and DN and pave the way for more precise prevention and treatment methods. However, it is also critical to recognize any potential restrictions, such as those caused by sample size, population variety, and analytical techniques.

MeSH terms

  • Diabetic Nephropathies* / genetics
  • Diabetic Nephropathies* / microbiology
  • Gastrointestinal Microbiome* / genetics
  • Humans
  • Mendelian Randomization Analysis*
  • Risk Factors