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

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.

Association of insulin resistance indicators with hepatic steatosis and fibrosis in patients with metabolic syndrome.

BACKGROUND: To investigate the association of four insulin resistance (IR) indicators with hepatic steatosis and fibrosis in patients with metabolic syndrome (MetS), as well as to compare the diagnostic value of these indicators in identifying hepatic steatosis and fibrosis in individuals with MetS. METHODS: This cross-sectional study used the data from the National Health and Nutrition Examination Survey 2017-2018. IR indicators included homeostasis model assessment of IR (HOMA-IR), triglyceride/glucose (TyG) index, triglyceride glucose-waist-to-height ratio (TyG-WHtR), and metabolic score for IR (METS-IR). The main endpoints of this study were hepatic steatosis and hepatic fibrosis. Weighted univariate and multivariate logistic regression models were employed to evaluate the association between four IR indicators and both hepatic steatosis, hepatic fibrosis. The efficacy of various IR indicators in the detection of hepatic steatosis and hepatic fibrosis were assessed using receiver operating characteristics curve (ROC). RESULTS: A total of 876 participants with MetS were enrolled. Among the participants, hepatic steatosis was observed in 587 MetS individuals, while hepatic fibrosis was identified in 151 MetS individuals. In multivariate logistic regression model, HOMA-IR, TyG, TyG-WHtR, and METS-IR were related to the increased odd of hepatic steatosis. Additionally, HOMA-IR, TyG-WHtR, and METS-IR were associated with increased odd of hepatic fibrosis. According to the ROC analysis, the area under the curve (AUC) of the TyG-WHtR (AUC = 0.705, 95%CI: 0.668-0.743) was higher than HOMA-IR (AUC = 0.693, 95%CI: 0.656-0.730), TyG (AUC = 0.627, 95%CI: 0.587-0.666), and METS-IR (AUC = 0.685, 95%CI: 0.648-0.722) for identifying hepatic steatosis of MetS patients. Likewise, TyG-WHtR was also higher than HOMA-IR, TyG, and METS-IR for identifying hepatic fibrosis of MetS patients. CONCLUSION: HOMA-IR, TyG-WHtR, and METS-IR may be associated with the risk of hepatic steatosis and fibrosis among the U.S. adult population with MetS. In addition, TyG-WHtR may have a good predictive value for hepatic steatosis and hepatic fibrosis.