BACKGROUND: Gut microbes and their metabolites play crucial roles in the pathogenesis of diabetic kidney disease (DKD). However, which one and how specific gut-derived metabolites affect the progression of DKD remain largely unknown.
OBJECTIVE: This study aimed to investigate the potential roles of indole-3-propionic acid (IPA), a microbial metabolite of tryptophan, in DKD.
METHODS: Metagenomic sequencing was performed to analyze the microbiome structure in DKD. Metabolomics screening and validation were conducted to identify characteristic metabolites associated with DKD. The protective effect of IPA on DKD glomerular endothelial cells (GECs) was assessed through in vitro and in vivo experiments. Further validation via western blot, immunoprecipitation, gene knockout, and site-directed mutation elucidated the mechanism of IPA on mitochondrial injury.
RESULTS: Alterations in gut microbial community structure and dysregulated tryptophan metabolism were evident in DKD mice. Serum IPA levels were significantly reduced in DKD patients and correlated with fasting blood glucose, HbA1c, urine albumin-to-creatinine ratio (UACR), and estimated glomerular filtration rate (eGFR). IPA supplementation ameliorated albuminuria, bolstered the integrity of the glomerular filtration barrier, and mitigated mitochondrial impairments in GECs. Mechanistically, IPA hindered SIRT1 phosphorylation-mediated ubiquitin-proteasome degradation, restoring SIRT1\'s role in promoting PGC-1α deacetylation and nuclear translocation, thereby upregulating genes associated with mitochondrial biosynthesis and antioxidant defense.
CONCLUSIONS: Our findings underscore the potential of the microbial metabolite IPA to attenuate DKD progression, offering novel insights and potential therapeutic strategies for its management.

UNASSIGNED: The oxidative balance score (OBS) is a comprehensive concept that includes 20 oxidative stressors and can be used to assess individual pro-oxidant versus antioxidant exposure, and the aim of the present study was to investigate the association between OBS and the risk of diabetic kidney disease (DKD), low estimated glomerular filtration rate (low-eGFR) and albuminuria in patients with diabetes mellitus (DM).
UNASSIGNED: This cross-sectional study included nationally representative consecutive National Health and Nutrition Examination Survey DM patients aged 18 years and older from 2003-2018. The continuous variable OBS was converted into categorical variables by quartiles, and weighted multiple logistic regression analyses and restricted triple spline models were used to explore the relationships. We also performed subgroup analyses and interaction tests to verify the stability of the results.
UNASSIGNED: A total of 5389 participants were included, representing 23.6 million non-institutionalized US residents. The results from both multivariate logistic regression analysis and restricted cubic spline models indicated that OBS and dietary OBS levels were negatively associated with the risk of DKD, low-eGFR, and albuminuria, without finding a significant correlation between lifestyle OBS and these clinical outcomes. Compared to the lowest OBS quartile group, the prevalence risk of DKD (OR = 0.61, 95% CI: 0.46-0.80), low-eGFR (OR = 0.46, 95% CI: 0.33-0.64) and albuminuria (OR = 0.68, 95% CI: 0.51-0.92) decreased by 39%, 54% and 32%, respectively, in the highest OBS quartile group. The results remained stable in subgroup analyses and no interaction between subgroups was found.
UNASSIGNED: Higher levels of OBS and dietary OBS were associated with a lower risk of DKD, low-eGFR, and albuminuria. These findings provided preliminary evidence for the importance of adhering to an antioxidant-rich diet and lifestyle among individuals with diabetes.

Diabetic kidney disease (DKD) is one of the leading causes of end-stage renal disease worldwide and significantly increases the risk of premature death due to cardiovascular diseases. Elevated urinary albumin levels are an important clinical feature of DKD. Effective control of albuminuria not only delays glomerular filtration rate decline but also markedly reduces cardiovascular disease risk and all-cause mortality. New drugs for treating DKD proteinuria, including sodium-glucose cotransporter two inhibitors, mineralocorticoid receptor antagonists, and endothelin receptor antagonists, have shown significant efficacy. Auxiliary treatment with proprietary Chinese medicine has also yielded promising results; however, it also faces a broader scope for development. The mechanisms by which these drugs treat albuminuria in patients with DKD should be described more thoroughly. The positive effects of combination therapy with two or more drugs in reducing albuminuria and protecting the kidneys warrant further investigation. Therefore, this review explores the pathophysiological mechanism of albuminuria in patients with DKD, the value of clinical diagnosis and prognosis, new progress and mechanisms of treatment, and multidrug therapy in patients who have type 2 diabetic kidney disease, providing a new perspective on the clinical diagnosis and treatment of DKD.

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OBJECTIVE: We aim to determine the association of seven major candidate protein biomarkers and diabetic kidney disease (DKD) progression among Asians with young-onset type 2 diabetes mellitus (T2DM).
METHODS: 824 T2DM patients (onset ≤ 40 years old) were classified as DKD progressors based on yearly estimated glomerular filtration rate (eGFR) decline of >3 ml/min/1.73 m2 or >40 % from baseline. Plasma leucine-rich α-2-glycoprotein 1 (pLRG1), tumor necrosis factor-receptor 1 (pTNF-R1), pigment epithelium-derived factor (pPEDF), urinary α-1-microglobulin (uA1M), kidney injury molecular 1 (uKIM-1), haptoglobin (uHP) and uromodulin (uUMOD) were measured using enzyme-linked immunoassays.
RESULTS: Over 5.7 years of follow-up, 25.2 % of patients were DKD progressors. Elevated levels of pLRG1, pTNF-R1, pPEDF, uA1M, uKIM-1 and uHP were associated with DKD progression. The association between pTNF-R1 levels and DKD progression persisted after adjusting for clinical covariates (OR 1.84, 95 %CI 1.44-2.34, p < 0.001). The effects of pTNF-R1 were partially mediated through hyperglycemia (8 %) and albuminuria (10 %). Inclusion of pTNF-R1 in a clinical variable-based model improved the area under the receiver operating characteristics curve for predicting DKD progression by 0.02, from 0.72 (95 %CI 0.68-0.76) to 0.74 (95 %CI 0.70-0.78), p = 0.099.
CONCLUSIONS: Among seven major candidate proteins, pTNF-R1 partially mediated through hyperglycemia and albuminuria, robustly predicted DKD progression among Asians with young-onset T2DM.

UNASSIGNED: To investigate the effects of Bifidobacterium bifidum tetragonum tablets and Jin Gui Ren Qi Pill on intestinal flora and metabolism in patients with diabetic kidney disease.
UNASSIGNED: In the study conducted at Heping Hospital of Changzhi Medical College from March 2021 to December 2022, 30 cases of patients diagnosed with diabetic nephropathy were meticulously selected as study subjects. Employing a double-blind randomized table method, these patients were randomly allocated into three groups: the control group (n = 10), the Bifidobacterium bifidum tetragonum tablets group (n = 10), and the Jin Gui Ren Qi Pill group (n = 10). The control group received standard western medical treatments for diabetic nephropathy, including serum glucose, blood lipids, blood pressure management, and other conventional therapies. In addition to the standard treatments, the Bifidobacterium bifidum tetragonum tablets group received Bifidobacterium bifidum tetragonum tablets, while the Jin Gui Ren Qi Pill group received Jin Gui Ren Qi Pill. Before and after a 4-week treatment period, various baseline parameters were assessed, including fasting blood glucose, 2-h postprandial blood glucose, triglycerides, serum total cholesterol, serum low-density lipoprotein cholesterol, serum high-density lipoprotein cholesterol, random urine microalbumin/creatinine ratio (ACR), blood creatinine (SCr), and traditional Chinese medicine evidence scores. Stool specimens were collected from all three groups before and after treatment for 16S rDNA high-throughput sequencing, followed by comprehensive analyses including OUT clustering, Alpha diversity, Beta diversity, species composition analysis, LEfSe analysis, and KEGG function prediction. Spearman correlation analysis was employed to explore the relationship between intestinal flora and clinical indicators. Furthermore, fasting peripheral venous blood was collected from patients in the Bifidobacterium tetrapunctate tablets group and the control group before and after intervention to measure the optical density values of tumor necrosis factor-α (TNF-α), interleukin-2 (IL-2), and interleukin-6 (IL-6) using the Beijing Biolite ELISA kit. This study was conducted with the approval of the Ethics Committee of Changzhi Medical College.
UNASSIGNED: 1. The 2hPBG, total cholesterol and LDL levels were observed among patients with diabetic kidney disease (DKD) across all groups: the Jin Gui Ren Qi Pill group, the Bifidobacterium bifidum tetragonum tablets group, and the control group (p < 0.05). 2. The Jin Gui Ren Qi Pill demonstrated superior efficacy in alleviating TCM symptoms and reducing the ACR compared to both the Bifidobacterium bifidum tetragonum tablets group and the control group. Conversely, Bifidobacterium bifidum tetragonum tablets exhibited a more pronounced reduction in TC levels compared to both the Jin Gui Ren Qi Pill and control groups. Notably, Bifidobacterium bifidum tetragonum tablets effectively decreased (IL-2) levels in patients with DKD. 3. Bifidobacterium bifidum tetragonum tablets also demonstrated efficacy in reducing IL-2 levels in DKD patients. 4. Analysis of intestinal microorganism abundance and diversity before and after the intervention, as well as among the three groups, revealed no significant alterations. Similarly, comparisons of ACE, Chao, Simpson, and Shannon indices showed no statistically significant differences (p > 0.05). 5. Qualitative analysis of intestinal microorganisms before and after intervention, as well as among the three groups, indicated no significant differences. Anosim test results also did not reveal qualitative distinctions (Anosim test R = 0.021, p = 0.215). 6. LEfSe analysis unveiled a noteworthy increase in Prevotella_7 abundance within the Jin Gui Ren Qi Pill group post-intervention (p < 0.05). 7. Furthermore, Chinese medicine evidence scores, body mass index, TC, and LDL levels correlated positively with the relative abundance of Tyzzerella_3 bacterial flora. Conversely, age, disease duration, and 2hPBG correlated positively with the relative abundance of Christensenellaceae_R_7 flora, while TC and LDL levels displayed a negative correlation with the relative abundance of Christensenellaceae_R_7 flora.
UNASSIGNED: The combination of Jin Gui Ren Qi Pill with western medical treatment exhibited superior efficacy in ameliorating clinical symptoms and reducing the ACR in patients with DKD compared to western medical treatment alone. Furthermore, this combination therapy led to an increase in the abundance of Prevotella_7 within the intestinal flora of patients, suggesting a potential enhancement in carbohydrate metabolism by the intestinal microbiota. On the other hand, Bifidobacterium bifidum tetragonum tablets bacterial tablets combined with western medical treatment demonstrated enhanced efficacy in reducing TC levels in DKD patients compared to western medical treatment alone. Additionally, this combination therapy effectively reduced the levels of IL-2 in DKD patients, thus mitigating inflammation in these individuals.

In China, the Astragalus membranaceus root is used to treat chronic kidney disease. Astragaloside IV (AS-IV), the primary bioactive compound, exhibits anti-inflammatory and antioxidative properties; however, its renoprotective mechanism in diabetic kidney disease (DKD) remains unclear. The study aimed to investigate the protective effects of AS-IV on DKD revealing the underlying mechanisms. We established an early diabetic rat model by feeding a high-fat diet and administering low-dose streptozotocin. Twelve weeks post-treatment, renal function was evaluated using functional assays, histological analyses, immunohistochemistry, western blotting, and transmission electron microscopy. HK-2 cells exposed to high glucose conditions were used to examine the effect of AS-IV on oxidative stress, iron levels, reactive oxygen species (ROS), and lipid peroxidation. Network pharmacology, proteomics, molecular docking, and molecular dynamics simulation techniques were employed to elucidate the role of AS-IV in DKD. The results revealed that AS-IV effectively enhanced renal function and mitigated disease pathology, oxidative stress, and ferroptosis markers in DKD rats. In HK-2 cells, AS-IV lowered the levels of lipid peroxides, Fe2+, and glutathione, indicating the repair of ferroptosis-related mitochondrial damage. AS-IV reduced mitochondrial ROS while enhancing mitochondrial membrane potential and ATP production, indicating its role in combating mitochondrial dysfunction. Overall, in silico analyses revealed that AS-IV interacts with HMOX1, FTH1, and TFR1 proteins, supporting its efficacy in alleviating renal injury by targeting mitochondrial dysfunction and ferroptosis. AS-IV may play a renoprotective role by regulating mitochondrial dysfunction and inhibiting. HMOX1/FTH1/TFR1-induced ferroptosis. Accordingly, AS-IV could be developed for the clinical treatment of DKD-related renal injury.

The inhibition of the autophagolysosomal pathway mediated by transcription factor EB (TFEB) inactivation in proximal tubular epithelial cells (TECs) is a key mechanism of TEC injury in diabetic kidney disease (DKD). Acetylation is a novel mechanism that regulates TFEB activity. However, there are currently no studies on whether the adjustment of the acetylation level of TFEB can reduce the damage of diabetic TECs. In this study, we investigated the effect of Trichostatin A (TSA), a typical deacetylase inhibitor, on TFEB activity and damage to TECs in both in vivo and in vitro models of DKD. Here, we show that TSA treatment can alleviate the pathological damage of glomeruli and renal tubules and delay the DKD progression in db/db mice, which is associated with the increased expression of TFEB and its downstream genes. In vitro studies further confirmed that TSA treatment can upregulate the acetylation level of TFEB, promote its nuclear translocation, and activate the expression of its downstream genes, thereby reducing the apoptosis level of TECs. TFEB deletion or HDAC6 knockdown in TECs can counteract the activation effect of TSA on autophagolysosomal pathway. We also found that TFEB enhances the transcription of Tfeb through binding to its promoter and promotes its own expression. Our results, thus, provide a novel therapeutic mechanism for DKD that the alleviation of TEC damage by activating the autophagic lysosomal pathway through upregulating TFEB acetylation can, thus, delay DKD progression.

Inflammation and fibrosis play important roles in diabetic kidney disease (DKD). Previous studies have shown that glucagon-like peptide-1 receptor (GLP-1R) agonists had renal protective effects. However, the mechanisms are not clear. The present study explored the effect of liraglutide, a GLP-1R agonist, on the downregulation of glomerular inflammation and fibrosis in DKD by regulating the TLR4/MyD88/NF-kappaB signaling pathway in mesangial cells (MCs). In vitro, rat MCs were cultured in high glucose (HG). We found that liraglutide treatment significantly reduced the HG mediated activation of the TLR4/MYD88/NF-κB signaling pathway, extracellular matrix (ECM)-related proteins and inflammatory factors. A combination of TLR4 inhibitor (TAK242) and liraglutide did not synergistically inhibited inflammatory factors and ECM proteins. Furthermore, in the presence of TLR4 siRNA, liraglutide significantly blunted HG-induced expression of fibronectin protein and inflammatory factors. Importantly, TLR4 selective agonist - LPS or TLR4 overexpression eliminated the improvement effects of liraglutide on the HG-induced response. In vivo, administration of liraglutide for 8 weeks significantly improved the glomerular damage in streptozotocin-induced diabetic mice, and reduced the expression of TLR4/MYD88/NF-κB signaling proteins, ECM protein, and inflammatory factors in renal cortex. TLR4-/- diabetic mice showed significant amelioration in urine protein excretion rate, glomerular pathological damage, inflammation and fibrosis. Liraglutide attenuated glomerular hypertrophy, renal fibrosis and inflammatory response in TLR4-/- diabetic mice. Taken together, our findings suggest that TLR4/MYD88/NF-κB signaling is involved in the regulation of inflammatory response and ECM protein proliferation in DKD. Liraglutide alleviates inflammation and fibrosis by downregulating the TLR4/MYD88/NF-κB signaling pathway in MCs.

Diabetic kidney disease (DKD) is a significant complication of type 2 diabetes, posing a global health risk. Detecting and predicting diabetic kidney disease at an early stage is crucial for timely interventions and improved patient outcomes. Artificial intelligence (AI) has demonstrated promise in healthcare, and several tools have recently been developed that utilize Machine Learning with clinical data to detect and predict DKD. This review aims to explore the current landscape of AI and machine learning applications in DKD, specifically examining existing literature on risk scores and machine learning approaches for predicting DKD development. A literature search was conducted using Medline (PubMed), Google Scholar, and Scopus databases until July 2023. Relevant keywords were used to extract studies that described the role of AI in DKD. The review revealed that AI and machine learning have been successfully used to predict DKD progression, outperforming traditional risk score models. Artificial intelligence-driven research for DKD extends beyond prediction models, offering opportunities for integrating genetic and epigenetic data, advancing understanding of the disease\'s molecular basis, personalizing treatment strategies, and fostering the development of novel drugs. However, challenges remain, including the requirement for large datasets and the lack of standardization in AI-driven tools for DKD. Artificial intelligence and machine learning have the potential to revolutionize the management and care of DKD patients, surpassing the limitations of traditional methods reliant on existing knowledge. Future research should address the challenges associated with AI and machine learning in DKD and focus on developing AI-driven tools for clinical practice.