Current updates on metabolites and its interlinked pathways as biomarkers for diabetic kidney disease: A systematic review

Das, Soumik; Devi Rajeswari, V; Venkatraman, Ganesh; Elumalai, Ramprasad; Dhanasekaran, Sivaraman; Ramanathan, Gnanasambandan

doi:10.1016/j.trsl.2023.11.002

Cited by 5 publications

(2 citation statements)

References 222 publications

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“…Diabetic nephropathy (DN) is a serious complication of diabetes and an important cause of death in patients ( Varghese and Jialal, 2023 ; Das et al., 2024 ). Its clinical manifestations include proteinuria, hypertension, and edema.…”

Section: Gut Microbiota and Dmmentioning

confidence: 99%

Advances in fecal microbiota transplantation for the treatment of diabetes mellitus

Zhang,

Wang,

Liu

et al. 2024

Front. Cell. Infect. Microbiol.

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Diabetes mellitus (DM) refers to a group of chronic diseases with global prevalence, characterized by persistent hyperglycemia resulting from various etiologies. DM can harm various organ systems and lead to acute or chronic complications, which severely endanger human well-being. Traditional treatment mainly involves controlling blood sugar levels through replacement therapy with drugs and insulin; however, some patients still find a satisfactory curative effect difficult to achieve. Extensive research has demonstrated a close correlation between enteric dysbacteriosis and the pathogenesis of various types of DM, paving the way for novel therapeutic approaches targeting the gut microbiota to manage DM. Fecal microbiota transplantation (FMT), a method for re-establishing the intestinal microbiome balance, offers new possibilities for treating diabetes. This article provides a comprehensive review of the correlation between DM and the gut microbiota, as well as the current advancements in FMT treatment for DM, using FMT as an illustrative example. This study aims to offer novel perspectives and establish a theoretical foundation for the clinical diagnosis and management of DM.

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Section: Gut Microbiota and Dmmentioning

confidence: 99%

Advances in fecal microbiota transplantation for the treatment of diabetes mellitus

Zhang,

Wang,

Liu

et al. 2024

Front. Cell. Infect. Microbiol.

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“… 10 , 11 With the development of metabolomics, more and more biomarkers of DKD have been explored. 12 , 13 Lactate, a metabolite associated with glucose metabolism and energy supply under anaerobic conditions, has recently gained attention for its potential role as a biomarker. It is becoming increasingly clear that lactate, previously considered a metabolic waste, is also involved in cell signaling, gene expression, and disease occurrence.…”

Section: Introductionmentioning

confidence: 99%

Development of Serum Lactate Level-Based Nomograms for Predicting Diabetic Kidney Disease in Type 2 Diabetes Mellitus Patients

Jiang,

Ma,

Chen

et al. 2024

DMSO

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Purpose To establish nomograms integrating serum lactate levels and traditional risk factors for predicting diabetic kidney disease (DKD) in type 2 diabetes mellitus (T2DM) patients. Patients and methods A total of 570 T2DM patients and 100 healthy subjects were enrolled. T2DM patients were categorized into normal and high lactate groups. Univariate and multivariate logistic regression analyses were employed to identify independent predictors for DKD. Then, nomograms for predicting DKD were established, and the model performance was evaluated using the area under the receiver operating characteristic curve (AUC), calibration, and decision curve analysis (DCA). Results T2DM patients exhibited higher lactate levels compared to those in healthy subjects. Glucose, platelet, uric acid, creatinine, and hypertension were independent factors for DKD in T2DM patients with normal lactate levels, while diabetes duration, creatinine, total cholesterol, and hypertension were indicators in high lactate levels group ( P <0.05). The AUC values were 0.834 (95% CI, 0.776 to 0.891) and 0.741 (95% CI, 0.688 to 0.795) for nomograms in both normal lactate and high lactate groups, respectively. The calibration curve demonstrated excellent agreement of fit. Furthermore, the DCA revealed that the threshold probability and highest Net Yield were 17–99% and 0.36, and 24–99% and 0.24 for the models in normal lactate and high lactate groups, respectively. Conclusion The serum lactate level-based nomogram models, combined with traditional risk factors, offer an effective tool for predicting DKD probability in T2DM patients. This approach holds promise for early risk assessment and tailored intervention strategies.

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Advancements, Challenges, and clinical implications of integration of metabolomics technologies in diabetic nephropathy

Sharma,

Khokhar,

Panigrahi

et al. 2024

Clinica Chimica Acta

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Current updates on metabolites and its interlinked pathways as biomarkers for diabetic kidney disease: A systematic review

Cited by 5 publications

References 222 publications

Advances in fecal microbiota transplantation for the treatment of diabetes mellitus

Advances in fecal microbiota transplantation for the treatment of diabetes mellitus

Development of Serum Lactate Level-Based Nomograms for Predicting Diabetic Kidney Disease in Type 2 Diabetes Mellitus Patients

Advancements, Challenges, and clinical implications of integration of metabolomics technologies in diabetic nephropathy

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