Pathophysiologic Mechanisms and Potential Biomarkers in Diabetic Kidney Disease

Association between drinking patterns and diabetic kidney disease in United States adults: a cross-sectional study based on data from NHANES 1999-2016

OBJECTIVE

This cross-sectional study aimed to investigate the association between drinking patterns and prevalence of diabetic kidney disease (DKD) among adults in the United States.

METHODS

Data were analyzed from the NHANES surveys conducted between 1999 and 2016, including 26,473 participants. Drinking patterns were categorized by frequency (weekly, monthly, or yearly) and quantity (light, moderate, or heavy, based on daily consumption). Among participants with diabetes, DKD was defined using the albumin-to-creatinine ratio (ACR ≥30 mg/g) and estimated glomerular filtration rate (eGFR <60 mL/min/1.73 m2). Multivariable logistic regression models were used to evaluate associations, adjusting for potential confounders across the four models. Subgroup analyses were performed to assess the effects of modification by age, sex, race, BMI.

RESULTS

Drinking patterns and DKD were analyzed among 26,473 US adults (mean age, 46.6 years; 53.7% male). After adjusting for multiple confounders, heavy alcohol consumption was associated with a higher risk of DKD than light drinking (OR = 1.23, 95% CI, 1.04-1.46; p = 0.016). Conversely, moderate drinking frequency (3-4 days per week, 2-5 days per month, 3-126 days per year) was associated with a reduced DKD risk (OR = 0.67, 95% CI, 0.49-0.91; OR = 0.75, 95% CI, 0.56-0.99, OR = 0.71, 95% CI, 0.58-0.86, respectively). A nonlinear association was observed between alcohol consumption frequency and DKD in terms of weekly and yearly drinking days.

CONCLUSION

This study highlights the importance of drinking behavior in the management of diabetic kidney disease. Daily alcohol consumption was associated with an increased risk of DKD, whereas moderate alcohol consumption was associated with a reduced risk. These findings suggest that moderate drinking frequency may not exacerbate renal burden in individuals with diabetes and provide new perspectives for clinical interventions.

Implementing novel complete blood count-derived inflammatory indices in the diabetic kidney diseases diagnostic models

Objectives

Hemogram inflammatory markers, including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), red-cell distribution width (RDW), and mean platelet volume (MPV) have been associated with type 2 diabetes mellitus (T2DM) and its complications, namely diabetic kidney diseases (DKD). We aimed to develop and validate logistic regression (LR) and CatBoost diagnostic models and study the role of adding these markers to the models.

Methods

All individuals who were managed in our secondary care center from March 2020 to December 2023 were identified. After excluding the ineligible patients, train-test splitting, and data preprocessing, two baseline LR and CatBoost-based models were developed using demographic, clinical, and laboratory features. The AUC-ROC of the models with biomarkers (NLR, PLR, RDW, and MPV) was compared to the baseline models. We calculated net reclassification improvement (NRI) and integrated discrimination index (IDI).

Results

One thousand and eleven T2DM patients were eligible. The AUC-ROC of both LR (0.738) and CatBoost (0.715) models was comparable. Adding target inflammatory markers did not significantly change the AUC-ROC in both LR and CatBoost models. Adding RDW to the baseline LR model reclassified 41.7% of patients without DKD, in the cost of misclassification of 38.4% of DKD cases. This change was absent in CatBoost models, and other markers did not achieve improved NRI or IDI.

Conclusion

The basic models with demographical and clinical features had acceptable performance. Adding RDW to the basic LR model improved the reclassification of the non-DKD participants. However, adding other hematological indices did not significantly improve the LR and CatBoost models' performance.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-024-01523-2.

Association of normal range of urinary albumin-to-creatinine ratio with all-cause mortality among diabetic adults with preserved kidney function: National Health and Nutrition Examination Survey (NHANES) 2003-2018

AIM

To ascertain the connection between normal-range urinary albumin-to-creatinine ratio (UACR) and all-cause mortality (ACM) among diabetic adults with preserved eGFR.

METHODS

We used data from the 2003-2018 National Health and Nutrition Examination Survey. Nationally representative cross-sectional survey data linked with mortality outcomes from the National Death Index. Restricted cubic spline curves (RCS) and multivariable Cox regression models alongside subgroup analyses were utilised for estimating hazard ratios (HRs) and 95% confidence intervals (Cls) for UACR-ACM interplay, adjusting for demographic, socioeconomic, biochemical, medication and medical history factors. The UACR's predictive accuracy for survival outcomes was determined through receiver operating characteristic analysis.

RESULTS

The RCS regression analysis showcased that there was no significant evidence to support a nonlinear relationship between normal-range UACR and ACM (p = 0.080 for nonlinearity) in participants with diabetes mellitus (DM). In the model 2 adjusted for multiple confounding variables, the HR for ACM was 1.22 (95% CI, 1.06-1.40) per 10 mg/g raise in continuous UACR and 1.50 (95%CI, 1.18-1.91) for the high UACR tertile compared to the low. Kaplan-Meier analysis showed significantly lower survival rates in the medium and high UACR groups (p < 0.001). Subgroup analysis manifested a significant UACR-body mass index (BMI) interaction (p = 0.033 for interaction).

CONCLUSIONS

In DM adults without overt kidney dysfunction, elevated normal-range UACR was independently related to escalated ACM, particularly in those with normal BMI. To conclude, we underscore the significance of early risk assessment in DM patients with normal-range albuminuria, even without overt kidney dysfunction.

Predicting diabetic kidney disease with serum metabolomics and gut microbiota

This study aims to identify biomarkers for reliably predicting diabetic kidney disease (DKD), systematically characterize serum metabolites and gut microbiota in DKD patients, and investigate the correlation between differential serum metabolites and gut microbiota. From September 2021 to January 2023, 90 subjects were recruited: 30 with DKD, 30 with type 2 diabetes mellitus (T2DM), and 30 normal controls (NCs). Serum metabolites, including 180 different metabolites, were analyzed using untargeted metabolomics UPLC-MS/MS, and gut microbiota were assessed via 16S rRNA sequencing. Differential metabolites were identified through univariate (t-test or Mann-Whitney U-test, P < 0.05) and multivariate analyses (OPLS-DA model, VIP > 1, P < 0.05), followed by selection using the least absolute shrinkage and selection operator (LASSO). The selected overlapping serum metabolites, along with DKD-associated differential gut microbiota, were used to develop a logistic regression prediction model for DKD based on six markers. In the DKD group compared to the DM and NC groups, 39 and 60 differential serum metabolites were identified, respectively (VIP > 1, P < 0.01). Among these, 36 serum metabolites, including alpha-Hydroxyisobutyric acid, were significantly elevated in DKD patients compared to those with DM. Of these, 28 metabolites showed a negative correlation with estimated glomerular filtration rate (eGFR), while 29 showed a positive correlation with urine albumin creatinine ratio (UACR). Patients with DKD were further categorized into subgroups (DKD middle and DKD early) based on eGFR (eGFR < 90 ml/min/1.73m2, eGFR ≥ 90 ml/min/1.73m2), revealing 23 differential metabolites. Dysbiosis of the gut microbiota was evident in DKD patients, with lower relative abundances of g_Prevotella and g_Faecalibacterium compared to the DM and NC groups. Subgroup analysis indicated decreased relative abundances of g_Prevotella and g_Faecalibacterium in the DKD middle group, along with a decrease in g_Klebsiella compared to the DKD early group, which correlated positively with DKD patients' eGFR. There were 11 common metabolites among the three groups of differential metabolites. Among these, three serum metabolites-imidazolepropionic acid, adipoylcarnitine, and 1-methylhistidine-were identified as predictive serum metabolic markers. Disease prediction models (logistic regression models) were constructed based on these three metabolites combined with three genera of bacteria. These models demonstrated strong discriminatory power for diagnosing patients with DKD compared to patients with DM (area under the receiver operating characteristic curve (AUROC) = 0.939 and precision-recall curve (AUPR) = 0.940). The models also effectively discriminated between patients with DKD and NCs (0.976, 0.973). This study revealed distinctive serum metabolites and gut microbiota in patients with DKD. It demonstrated the potential utility of three specific serum metabolites and three genera of bacteria in diagnosing patients with DKD and assessing their renal dysfunction.

Loureirin B analogs mitigate oxidative stress and confer renal protection

Diabetic kidney disease (DKD) is a microvascular complication of diabetes with high morbidity and mortality, necessitating effective treatment. In this study, the Loureirin B analogue (LB-A) was utilized to treat DKD in mice. The results demonstrated that LB-A effectively prevent the progression of DKD in mice, significantly lowering fasting blood glucose levels and reducing proteinuria levels. Additionally, there was a significant decrease in oxidase content in the kidneys of mice, accompanied by an increase in antioxidant oxidase content, resulting in a decrease in ROS levels, mitigating oxidative stress state through modulation of Cxcl1. Cell experiments further confirmed that reducing Cxcl1/Cxcr2 axis activation prevented the onset of DKD induced by high glucose exposure and affected the therapeutic effect of LB-A as well. These findings provide evidences to support that LB-A may mitigate oxidative stress by modulating the Cxcl1 signaling pathway, thereby contributing to renal protection in the context of DKD treatment.

Progress and perspectives of metabolic biomarkers in blood sample for diabetic microvascular complications

BACKGROUND

Diabetes mellitus refers to a group of metabolic diseases characterized by chronic hyperglycemia due to multiple etiological factors. As the disease progresses, patients gradually develop microvascular complications, including diabetic nephropathy, diabetic retinopathy, and diabetic neuropathy. However, current clinical methods for detecting these microvascular complications are limitations, thus primary prevention and early diagnosis are of great importance.

AIM OF REVIEW

This review summarizes the known blood biomarkers of diabetic microvascular complications, classified according to type of structure, including amino acid metabolism, lipid metabolism, carnitine metabolism, organic acid metabolism, etc., which can be used for the simultaneous typing of diabetes mellitus based on microvascular complications, and to search for the trend of changes to lay the foundation for early diagnosis and understanding of the pathogenesis of diabetic microvascular complications, including oxidative stress, and mitochondrial dysfunction. Searches for the trend of changes to lay the foundation for early diagnosis and understanding of the pathogenesis of diabetic microvascular complications, including oxidative stress, mitochondrial dysfunction.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Due to the limitations of diagnostic criteria for diabetic microvascular complications, some patients already have the disease for which they are being tested. Metabolomics reflects the physiological state of an organism by analyzing the small molecules metabolites present in a biological tissue that are related to clinical phenotypes, providing a snapshot of the physiological and pathophysiological metabolic processes occurring within that organism at any given time, thus opening the door for the development of diagnostic biomarkers and precise treatment. In clinical metabolomics, blood is considered a specialized type of connective tissue, which allows it to transport substances throughout the body, connecting different systems together. Also, blood components are probably the most frequently used matrix in metabolomics studies. Therefore, metabolomics is used to analyze blood biomarkers that reflect the course of diabetes and explore the pathways involved in the pathophysiology of the three most common diabetic microvascular complications. Finally, in this review, we discuss the current limitations of metabolomic analysis, and the integrative multi-omics data, including genomics, transcriptomics, and proteomics, required for developing specific biomarkers for diabetic microvascular complications.

Association of the stress hyperglycemia ratio for all-cause and cardiovascular mortality in population with cardiovascular-kidney-metabolic syndrome stages 0-4: evidence from a large cohort study

BACKGROUND

The Cardiovascular-kidney-metabolic (CKM) syndrome is a health disorder caused by interactions between cardiovascular disease, kidney disease, and metabolism-related risk factors. The stress hyperglycemia ratio (SHR) has been shown to correlate with the prognosis of participants with diabetes mellitus, heart failure, and myocardial infarction. However, the predictive value of SHR in the CKM syndrome population is unclear and requires further exploration.

METHODS

This study analyzed 19,345 participants from the National Health and Nutrition Examination Survey (1999-2018). CKM syndrome was staged according to the American Heart Association (AHA) guidelines. SHR was calculated using fasting blood glucose (FBG) and glycated hemoglobin type A1c (HbA1c). Participants were grouped into four quartiles based on SHR. The primary and secondary outcomes were all-cause mortality and cardiovascular mortality, respectively. Kaplan-Meier survival curves and Cox proportional hazard regression models were used to evaluate the association between SHR and outcomes. Then, the potential nonlinear relationship was explored using restricted cubic spline (RCS) analysis. We also performed subgroup analyses to assess the effects of different variables.

RESULTS

A total of 2,736 all-cause deaths and 699 cardiovascular deaths were recorded during a median follow-up period of 115 months. Kaplan-Meier analysis revealed that participants in quartile 2 had the lowest risk for both all-cause and cardiovascular mortality (Log Rank P < 0.05). Multivariate Cox regression demonstrated the lowest all-cause mortality in the 2nd quartile (HR = 0.84, 95% CI = 0.73-0.97, P = 0.015) and the highest all-cause mortality in the 4th quartile (HR = 1.19, 95% CI = 1.03-1.37, P = 0.018), compared with the 1st quartile group of SHR. The RCS curve demonstrated a U-shape association of SHR with both all-cause and cardiovascular mortality, with the lowest points of 0.89 and 0.91, respectively.

CONCLUSIONS

SHR is strongly correlated with prognosis in the CKM syndrome population, with high or low SHR increasing the risk of death. This index shows great potential for predicting the risk of death in this population.

A Machine Learning-Based Prediction Model for Diabetic Kidney Disease in Korean Patients with Type 2 Diabetes Mellitus

Background/Objectives: Diabetic kidney disease (DKD) is a major cause of end-stage kidney disease and a leading contributor to morbidity and mortality in patients with type 2 diabetes mellitus (T2DM). However, predictive models for DKD onset in Korean patients with T2DM remain underexplored. This study aimed to develop and validate a machine learning (ML)-based DKD prediction model for this population. Methods: This retrospective study utilized electronic health records from six secondary or tertiary hospitals in Korea. The Jeonbuk National University Hospital cohort was used for model development (ratio training: test data, 8:2), whereas datasets from five other hospitals supported external validation. We employed multiple ML algorithms, including lasso, ridge, and elastic net regression; random forest; XGBoost; support vector machines; and neural networks. The model incorporated demographic variables, comorbidities, medications, and laboratory test results. Results: Among 5120 patients with T2DM, 1361 (26.6%) developed DKD. In the development cohort, XGBoost achieved the highest predictive performance (AUC: 0.8099), followed by random forest and logistic regression models (AUCs: 0.7977-0.8019). External validation confirmed the model's robustness with high AUCs (XGBoost: 0.8113, logistic regression models: 0.8228-0.8271). Key predictive factors included age; baseline estimated glomerular filtration rate; and creatinine, hemoglobin, and hemoglobin A1c levels. Conclusions: Our findings highlight the potential of ML-based approaches in predicting DKD in patients with T2DM. The superior performance of XGBoost and logistic regression models underscores their clinical utility. External validation supports the model's generalizability. This model is a valuable tool for the early DKD risk assessment of Korean patients with T2DM.

Serum metabolic profiling of patients with diabetic kidney disease based on gas chromatography-mass spectrometry

Introduction

Given the increasing incidence rate of diabetic kidney disease (DKD), there is an urgent need for methods to diagnose and treat DKD in clinics.

Methods

Serum samples were collected from 56 DKD patients and 32 healthy controls (HCs) at the First Affiliated Hospital of Ningbo University, and the metabolic profiles were obtained through untargeted metabolomics using gas chromatography mass spectrometry. The data were then analyzed using principal components analysis, orthogonal partial least-squares discriminant analysis, Pearson correlation analysis, and receiver operating characteristic (ROC) curve.

Results

It was found that the serum metabolic profiles of the DKD patients were significantly different from those of the HCs. A total of 68 potential differential metabolites were identified that were involved in arginine biosynthesis, ascorbate and aldarate metabolism, and galactose metabolism, among others; a total of 31 differential metabolites were also identified between early-stage (EDG) and late-stage (LDG) DKD patients. Additionally, 30 significant metabolic differences were observed among the EDG, LDG, and HC groups. Based on Pearson correlation analysis between the abundances of the differential metabolites and clinical markers (estimated glomerular filtration rate, blood urea nitrogen, serum creatinine, and urinary albumin/creatinine ratio) and area under the ROC curve (AUROC) analysis, the AUROC values of myoinositol and gluconic acid were found to be 0.992 and 0.991, respectively, which can be used to distinguish DKD patients from HCs.

Discussion

These results indicate that myoinositol and gluconic acid could possibly be used as biomarkers of DKD.

NR4A1 silencing alleviates high-glucose-stimulated HK-2 cells pyroptosis and fibrosis via hindering NLRP3 activation and PI3K/AKT pathway

BACKGROUND

The pathophysiology of diabetic kidney disease (DKD) is complex. Interfering with the processes of pyroptosis and fibrosis is an effective strategy for slowing DKD progression. Previous studies have revealed that nuclear receptor subfamily 4 group A member 1 (NR4A1) may serve as a novel pathogenic element in DKD; however, the specific mechanism by which it contributes to pyroptosis and fibrosis in DKD is unknown.

AIM

To investigate the role of NR4A1 in renal pyroptosis and fibrosis in DKD and possible molecular mechanisms.

METHODS

Streptozotocin 60 mg/kg was injected intraperitoneally to establish a rat model of DKD. Typically, 45 mmol/L glucose [high glucose (HG)] was used to activate HK-2 cells to mimic the DKD model in vitro. HK-2 cells were transfected with NR4A1 siRNA to silence NR4A1.

RESULTS

NR4A1 was elevated in renal tissues of DKD rats and HG-stimulated HK-2 cells. Concurrently, NOD-like receptor protein 3 (NLRP3) and phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT) pathways were triggered, and pyroptosis and expression of fibrosis-linked elements was increased in vivo and in vitro. These alterations were significantly reversed via NR4A1 silencing.

CONCLUSION

Inhibition of NR4A1 mitigated pyroptosis and fibrosis via suppressing NLRP3 activation and the PI3K/AKT pathway in HG-activated HK-2 cells.

Investigation of the role and mechanism of dapagliflozin in mitigating renal injury in rats afflicted with diabetic kidney disease

The etiology of diabetic kidney disease (DKD) is multifaceted, with hyperglycemia, inflammation, oxidative stress, and fibrosis recognized as key contributors to renal damage in individuals with DKD. Clinical evidence suggests that dapagliflozin not only reduces blood glucose levels but also demonstrates superior efficacy in ameliorating pancreatic islet cell injury while preserving cardiac and renal function. However, the precise underlying mechanism has been poorly elucidated in the current literature. In this study, a DKD rat model was established by administering a single intraperitoneal injection of streptozotocin (STZ) to investigate the renoprotective properties of dapagliflozin and its underlying mechanisms. The findings of this study indicate that dapagliflozin enhanced pancreatic islet cell function, lowered blood glucose levels, and significantly reduced biochemical markers and renal pathological damage in DKD rats. Dapagliflozin also exerted anti-inflammatory, antioxidant, and antifibrotic effects by inhibiting the activation of the p38 MAPK/NF-κB pathway, enhancing the activity of the SIRT1/Akt/GSK-3β/Nrf2/HO-1 signaling pathway, and inhibiting the over-activation of the TGF-β1/Smad2/3 signaling pathway. These effects led to a reduction in renal injury and improved renal function in DKD rats.

Uncovering the mechanism of Huangkui capsule in the treatment of diabetic kidney disease based on network pharmacology and experimental validation

Diabetic kidney disease (DKD) is a main complication of diabetes mellitus. experimental in vitro validation and Network pharmacology were used in this study to explore the potential mechanism of Huangkui capsules (HKC) in treating DKD. First, we used CCK8 to analyze the optimal drug concentration of HKC. Next, we used flow cytometry, ELISA, Scratch test, and immunofluorescence to examine the apoptosis, oxidative stress, inflammatory factors, and fibrotic factors (FN and α-SMA) expression in HK-2 cells. Thereafter, in order to determine the potential molecular mechanisms underlying the therapeutic effect of HKC in DKD. Compounds contained in HKC were explored by UPLC-Q-TOF-MS/MS. SwissTargetPrediction was utilized for predicting potential gene targets of these compounds. OMIM, DisGeNet and GeneCards databases were employed to identify DKD-related genes. Meanwhile, the association of compounds with DKD genes was examined by protein-protein interaction, GO and KEGG analysis. Finally, molecular docking and molecular dynamics simulation were adopted for further validation. The results showed that HKC had 40 active ingredients, 1051 possible gene targets, and 133 DKD-HKC intersection genes. IL6, TNF, GAPDH, AKT1, PPARG, and TP53 were candidate hub genes by which HKC exerted its anti-DKD function based on molecular docking, molecular dynamics simulation and experimental results. To conclude, this study sheds more lights on the possible pharmacological activities of HKC in DKD and a foundation for further clinical application.

Proteomics exploration of metformin hydrochloride for diabetic kidney disease treatment via the butanoate metabolism pathway

Diabetic nephropathy (DKD) is a diabetesrelated kidney injury with an increasing incidence every year. Metformin hydrochloride (MET), a cornerstone treatment for glucose lowering, has been widely reported for the treatment of DKD, but the specific molecular mechanisms and potential therapeutic targets still need to be further explored. We used kidney tissues from db/db mice as samples and used proteomics and bioinformatics to analyse the function, distribution and related pathways of differential proteins in DKD, focusing on the assessment of the binding energies of key proteins in the butyrate pathway and drugs at the molecular level, which showed that the expression profiles of differential proteins in kidney tissues were altered after MET treatment, involving energy metabolism. The key proteins involved in the butanoate metabolism pathway, including AACS, ACSM3, EHHADH and HMGCS2, exhibit binding energies to MET of ＜-5 kcal. It is therefore plausible that MET treatment may affect the butanoate metabolism pathway, potentially ameliorating the progression of DKD by modulating mitochondrial function and inflammatory responses.

N6-methyladenosine in inflammatory diseases: Important actors and regulatory targets

N6-methyladenosine (m6A) is one of the most prevalent epigenetic modifications in eukaryotic cells. It regulates RNA function and stability by modifying RNA methylation through writers, erasers, and readers. As a result, m6A plays a critical role in a wide range of biological processes. Inflammation is a common and fundamental pathological process. Numerous studies have investigated the role of m6A modifications in inflammatory diseases. This review highlights the mechanisms by which m6A contributes to inflammation, focusing on pathogen-induced infectious diseases, autoimmune disorders, allergic conditions, and metabolic disorder-related inflammatory diseases.

Serum advanced glycation end products as a putative biomarker in Type2 DKD patients' prognosis

Aim

Advanced glycation end products (AGEs) are pivotal mediators in diabetic kidney disease (DKD). However, their prognostic utility remains underexplored. This study introduced corrected lgAGEs [novel biomarker derived by adjusting logarithmically transformed AGEs (lgAGEs) levels based on serum albumin (ALB) levels] to enhance the prediction of adverse renal outcomes in patients with type 2 DKD (T2DKD).

Methods

In this prospective cohort study, 196 T2DKD patients were followed up longitudinally. Serum AGEs levels were log-transformed and adjusted for ALB to calculate corrected lgAGEs. Participants were stratified into the high- and low-level groups based on the median corrected lgAGEs. The association between corrected lgAGEs and renal outcomes was assessed using Cox proportional hazards models. Receiver operating characteristic (ROC) curve was utilized to evaluate the predictive performance of corrected lgAGEs alone and in combination with the urinary albumin-to-creatinine ratio (UACR).

Results

High level of corrected lgAGEs was independently associated with adverse renal outcomes [hazard ratio (HR), 3.252; 95% confidence interval (CI), 1.461-7.243; p = 0.003]. Kaplan-Meier analysis demonstrated that patients in the high-level group (12 months) exhibited significantly shorter median survival times compared with those in the low-level group (50 months). ROC analysis showed that UACR alone had an area under the curve (AUC) of 0.782 (95% CI, 0.705-0.858), with 82.8% sensitivity and 61.5% specificity. Corrected lgAGEs achieved an AUC of 0.725 (95% CI, 0.637-0.814), with 69.0% sensitivity and 76.9% specificity. Combining UACR and corrected lgAGEs improved the specificity to 75.6%, with an AUC of 0.764 (95% CI, 0.682-0.847), while maintaining a sensitivity of 70.7%.

Conclusion

Corrected lgAGEs are novel and independent biomarkers for predicting adverse renal outcomes in T2DKD. Combining UACR with corrected lgAGEs could enhance risk stratification by improving the specificity, highlighting its potential application in early identification of high-risk patients. These findings should be validated in broader populations in future research.

Detection of Fast Decliner of Diabetic Kidney Disease Using Chiral Amino Acid Profiling: A Pilot Study

Biomarkers for the prediction of diabetic kidney disease are still unsatisfactory. Although D-amino acids have been shown to reflect kidney conditions, their efficacy in treating diabetic kidney disease (DKD) has not been demonstrated. This study explored the potential role of D-amino acids as progression markers for DKD, an aspect not addressed previously. We performed comprehensive D-amino acid measurements and collected the longitudinal estimated glomerular filtration rate (eGFR) data of 135 patients. We defined fast decliners (FDs) as patients exhibiting >10% decline from baseline eGFR per year and compared the D-amino acid levels of FDs and non-FDs. Then, we verified that D-amino acids could predict FDs independent of creatinine levels. In patients with diabetic kidney disease, D-serine, D-alanine, and D-proline were only detected in the blood, while 15 D-amino acids were detected in the urine. Using supervised orthogonal partial least squares analysis, blood D-serine and urine D-amino acid levels were identified as features characterizing diabetic kidney disease. Baseline blood D-serine levels and ratios did not differ between the FD and non-FD groups; however, short-term changes in blood D-serine levels differed. This study emphasized the significance of D-serine as a prognostic marker for DKD, an aspect not identified in previous research.

Progress in the application of novel inflammatory indicators in chronic kidney disease

Chronic kidney disease has become a public health problem endangering the health of all humans because of its high prevalence, high mortality and high medical burden. The chronic micro-inflammatory state is recognized as a significant component of CKD, playing a key role in disease progression. Intervening in chronic inflammation during the disease course can enhance prognosis. Recent studies have demonstrated that novel inflammatory indices, such as the neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and systemic immune-inflammatory index are closely associated with CKD, meanwhile may serve as prognostic monitors of all-cause death and poor renal prognosis for the disease. This article comprehensively reports on the mechanisms of micro-inflammation in CKD, the relationship between inflammatory indicators and CKD, and their impact on prognosis.

Mechanisms, Biomarkers, and Treatment Approaches for Diabetic Kidney Disease: Current Insights and Future Perspectives

Diabetic Kidney Disease (DKD) is the leading cause of end-stage renal disease (ESRD) worldwide. Among individuals with type 1 diabetes mellitus (T1DM), 30-40% are at risk of developing DKD. This review focuses on the mechanistic processes, available and emerging biomarkers for diagnosing, monitoring, and preventing DKD, as well as treatment options targeted at DKD patients. A literature search was conducted on PubMed and Scopus using specific keywords. Inclusion and exclusion criteria were applied to select the articles used for this review. The literature highlights various mechanisms involved in the progression of DKD to more severe stages. Additionally, several biomarkers have been identified, which aid in diagnosing and monitoring the disease. Furthermore, numerous treatment approaches are being explored to address the underlying causes of DKD. Advanced research is exploring new medications to aid in DKD remission; sodium-glucose cotransport (SGLT2) inhibitors and finerenone, in particular, are gaining attention for their novel renoprotective effects. DKD is a major complication of diabetes, marked by complex and multifactorial mechanisms. Thus, understanding these processes is essential for developing targeted therapies to potentially reverse DKD progression. Biomarkers show promise for early diagnosis and monitoring of disease progression, while current treatment strategies underscore the importance of a multifaceted approach.

Global research hotspots and trends in oxidative stress-related diabetic nephropathy: a bibliometric study

Background

Oxidative stress is widely acknowledged as a key pathogenic mechanism in diabetic nephropathy (DN). In recent years, the role of oxidative stress in DN has garnered increasing attention. However, no bibliometric analysis has yet been conducted on the relationship between oxidative stress and DN. This study aims to systematically analyze the relevant literature, identify trends in research, assess current hotspots, and predict future directions.

Methods

We retrieved literature related to oxidative stress and DN from the Web of Science Core Collection database. We analyzed data on publication volume, countries/regions, institutions, journals, keywords, and other relevant metrics using VOSviewer, the Bibliometrix R package, and CiteSpace.

Results

From 2014 to 2024, a total of 4076 publications related to oxidative stress and DN were published across 755 journals, showing a consistent upward trend each year. China and the United States are the leading contributors in this field and demonstrate close collaborative efforts. The top contributors by country, institution, journal, and author include: China (1919 publications), Jilin University and Central South University (69 publications each), BIOMEDICINE & PHARMACOTHERAPY (117 publications), and Prof. Sun Lin (33 publications). The most frequent keyword is "oxidative stress" (3683 occurrences). In the co-citation analysis, Alicic RZ's 2017 study was the most cited (144 citations). These findings highlight the critical importance of investigating the pathogenesis of DN from the oxidative stress perspective.

Conclusion

This study demonstrates a steady increase in research on oxidative stress in DN since 2014, highlighting its central role in the pathogenesis of DN. Future research should focus on the molecular mechanisms of oxidative stress in DN and explore its therapeutic potential, to provide new strategies for the prevention and treatment of DN.

Targeting programmed cell death in diabetic kidney disease: from molecular mechanisms to pharmacotherapy

Diabetic kidney disease (DKD), one of the most prevalent microvascular complications of diabetes, arises from dysregulated glucose and lipid metabolism induced by hyperglycemia, resulting in the deterioration of renal cells such as podocytes and tubular epithelial cells. Programmed cell death (PCD), comprising apoptosis, autophagy, ferroptosis, pyroptosis, and necroptosis, represents a spectrum of cell demise processes intricately governed by genetic mechanisms in vivo. Under physiological conditions, PCD facilitates the turnover of cellular populations and serves as a protective mechanism to eliminate impaired podocytes or tubular epithelial cells, thereby preserving renal tissue homeostasis amidst hyperglycemic stress. However, existing research predominantly elucidates individual modes of cell death, neglecting the intricate interplay and mutual modulation observed among various forms of PCD. In this comprehensive review, we delineate the diverse regulatory mechanisms governing PCD and elucidate the intricate crosstalk dynamics among distinct PCD pathways. Furthermore, we review recent advancements in understanding the pathogenesis of PCD and explore their implications in DKD. Additionally, we explore the potential of natural products derived primarily from botanical sources as therapeutic agents, highlighting their multifaceted effects on modulating PCD crosstalk, thereby proposing novel strategies for DKD treatment.

Research progress of gut microbiome and diabetic nephropathy

Diabetic nephropathy is an important complication of diabetic microvascular injury, and it is also an important cause of end-stage renal disease. Its high prevalence and disability rate significantly impacts patients' quality of life while imposing substantial social and economic burdens. Gut microbiota affects host metabolism, multiple organ functions, and regulates host health throughout the life cycle. With the rapid development of technology, researchers have found that gut microbiota is closely related to the progression of diabetic kidney disease. This review explores the role of gut microbiome in diabetic nephropathy summarizing proposed mechanisms of progression and focusing on microbial metabolites, intestinal barrier disruption, inflammation, filtration barrier damage and renal fibrosis. This review also examines the mechanism and limitations of current treatments, including drugs, fecal microbiota transplantation, and lifestyle changes, offering new perspectives on prevention and treatment.

Sirt6 overexpression relieves ferroptosis and delays the progression of diabetic nephropathy via Nrf2/GPX4 pathway

OBJECTIVE

Sirt6, reactive oxygen species and ferroptosis may participate in the pathogenesis of Diabetic Nephropathy (DN). Exploring the relationship between Sirt6, oxidative stress, and ferroptosis provides new scientific ideas to DN.

METHODS

Human podocytes were stimulated with 30 mM glucose and 5.5 mM glucose. The mice of db/db group were randomly divided into two groups:12 weeks and 16 weeks. Collect mouse blood and urine specimens and renal cortices for investigations. HE, Masson, PAS and immunohistochemical staining were used to observe pathological changes. Western blot, RT-qPCR and immunofluorescence staining were used to evaluate expression of relevant molecules. CCK8 method was introduced to observe cell viability. The changes of podocyte mitochondrial membrane potential and mitochondrial morphology in each group were determined by JC-1 staining and Mito-Tracker.

RESULTS

The expression level of Sirt6, Nrf2, SLC7A11, HO1, SOD2 and GPX4 were reduced, while ACSL4 was increased in DN. Blood glucose, BUN, Scr, TG, T-CHO and 24h urine protein were upregulated, while ALB was reduced in diabetic group. The treatment of Ferrostatin-1 significantly improved these changes, which proved ferroptosis was involved in the development of DN. Overexpression of Sirt6 might ameliorate the oxidation irritable reaction and ferroptosis. Sirt6 plasmid transfection increased mitochondrial membrane potential and protected morphology and structure of mitochondria. The application of Sirt6 siRNA could aggravated the damage manifestations.

CONCLUSION

High glucose stimulation could decrease the antioxidant capacity and increase formation of ROS and lipid peroxidation. Sirt6 might alleviate HG-induced mitochondrial dysfunction, podocyte injury and ferroptosis through regulating Nrf2/GPX4 pathway.

Angiopoietin-like 4 is a potential biomarker for diabetic kidney disease in type 2 diabetes patients

AIMS/INTRODUCTION

The association between serum angiopoietin-like 4 (ANGPTL4) levels and the severity of diabetic kidney disease (DKD) in patients with type 2 diabetes mellitus remains unclear.

METHODS

A total of 1,115 type 2 diabetes mellitus patients were analyzed in this cross-sectional study. DKD index included DKD stages defined by estimated glomerular filtration rate, the albuminuria grades and DKD risk management grades. Serum levels of ANGPTL4 and other biomarkers were detected. Multivariable-adjusted linear and logistic analyses were used to study the association between ANGPTL4 and DKD. The protein levels of ANGPTL4 were assessed in the kidney. Renal tubular cells were stimulated with glucose to study ANGPTL4 expression.

RESULTS

Compared with the participants in the third or fourth quantile of ANGPTL4, those in the first or second quantile of ANGPTL4 were younger, with lower glycated hemoglobin, triglycerides and urinary albumin creatinine ratio (all P < 0.05). There was a negative nonlinear relationship between ANGPTL4 and estimated glomerular filtration rate in type 2 diabetes mellitus patients. One standard deviation increased serum ANGPTL4 levels, the odds ratio of having DKD was 1.40 (95% confidence interval 1.08-1.80). The mediation analysis showed that triglycerides did not mediate the association between ANGPTL4 and DKD. Furthermore, ANGPTL4 could be the strongest among multiple panels of biomarkers in its association of DKD. Compared with mice at 8 weeks-of-age, db/db mice at 18 weeks-of-age had increased ANGPTL4 expression in glomeruli and tubular segments. In vitro, glucose could stimulate ANGPTL4 expression in tubular cells in a dose-dependent manner.

CONCLUSIONS

ANGPTL4 could be a potential marker and therapeutic target for DKD treatment.

Single-cell RNA sequencing in diabetic kidney disease: a literature review

Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease (ESRD), and its pathogenesis has not been clarified. Current research suggests that DKD involves multiple cell types and extra-renal factors, and it is particularly important to clarify the pathogenesis and identify new therapeutic targets. Single-cell RNA sequencing (scRNA-seq) technology is high-throughput sequencing of the transcriptomes of individual cells at the single-cell level, which is an effective technology for exploring the development of diseases by comparing genetic information, reflecting the differences in genetic information between cells, and identifying different cell subpopulations. Accumulating evidence supports the role of scRNA-seq in revealing the pathogenesis of diabetes and strengthening our understanding of the molecular mechanisms of DKD. We reviewed the scRNA-seq data this time. Then, we analyzed and discussed the applications of scRNA-seq technology in DKD research, including annotation of cell types, identification of novel cell types (or subtypes), identification of intercellular communication, analysis of cell differentiation trajectories, gene expression detection, and analysis of gene regulatory networks, and lastly, we explored the future perspectives of scRNA-seq technology in DKD research.

Identification of circulating microbial DNA and its association with kidney function in patients with diabetic kidney disease

AIM

Recently, substantial studies have been accumulated to indicate the important role of gut microbiota in diabetic kidney disease (DKD). The abnormal change of bacterial-derived products could imply specific injuries or play beneficial or harmful roles in DKD progression. In this study, we examined the presence and contribution of the Klebsiella oxytoca gene in the circulation of patients with DKD.

METHOD

We enrolled a total of 16 healthy participants, 17 patients with DKD, 5 patients with DKD requiring haemodialysis (HD), and 7 patients with CKD without diabetes. Bacterial-derived DNA (16S rDNA and a specific K. oxytoca gene) in the blood was detected using droplet digital PCR, then investigated the relationship with clinical characteristics.

RESULTS

We identified an increase in K. oxytoca genes in the blood of DKD patients. Interestingly, blood K. oxytoca copies and K. oxytoca/ 16S DNA ratio correlated with higher blood creatinine and BUN levels together with lower eGFR in DKD patients. K. oxytoca levels were also associated with higher neutrophil percentage, lower lymphocyte frequency, and increased neutrophil-to-lymphocyte ratio.

CONCLUSION

Collectively, the presence of the K. oxytoca gene in the circulation could serve as a biomarker reflecting reduced renal function in DKD patients.

Association of the dietary inflammatory index with complicated diabetic kidney disease in people with diabetes mellitus: evidence from NHANES 2009-2018

AIMS

Diabetic kidney disease (DKD) significantly impairs quality of life in individuals with diabetes mellitus (DM). The influence of the Dietary Inflammatory Index (DII) on DKD, which is associated with adverse health outcomes, is not well-understood.

METHODS

We analyzed 2712 subjects from the National Health and Nutrition Examination Survey (NHANES) spanning 2011-2018, aiming to elucidate the relationship between DII and DKD.

RESULTS

DKD was diagnosed in 1016 participants (37.46%). Elevated DII levels were significantly associated with an increased DKD risk, as evidenced by multivariate logistic regression (Odds Ratio [OR] = 1.40, 95% Confidence Interval [CI] 1.12-1.75, P < 0.05). Further analysis after adjusting for covariates highlighted a notable non-linear correlation between DII and DKD risk, at DII values below 0.45, the risk of DKD increases with higher DII levels, whereas it stabilizes beyond this point. Subgroup analysis additionally revealed that diabetic men have a significantly higher DKD risk compared to women (P < 0.05).

CONCLUSION

Our study indicates a pronounced link between higher DII scores and increased risk of DKD among DM patients. These findings underscore the paramount importance of dietary management in DM treatment, stressing the need for interventions focused on reducing dietary inflammation to decelerate DKD progression.

Fish oil supplementation in relation to the risk of chronic kidney disease among patients with diabetes

AIM

To investigate the association between fish oil supplementation and subsequent risk of chronic kidney disease (CKD) among patients with diabetes, and further evaluate the mediation effect of typical glycolipid and inflammatory biomarkers.

METHODS

In total, 24 497 patients with diabetes from the UK Biobank were included. Cox proportional hazards regression models were used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) for CKD risk, and the rate advancement period was calculated to quantify and communicate the impact of fish oil upon that risk. In addition, we also used mediation analysis to assess the mediating role of plasma biomarkers.

RESULTS

Overall, 7122 patients reported taking fish oil supplements. During a mean of 11.3 years of follow-up, 3533 CKD cases occurred. In the fully adjusted model, fish oil use was inversely associated with the incidence of CKD (HR 0.90; 95% CI: 0.83, 0.97), which was mediated by serum levels of HbA1c (4.7%), C-reactive protein (CRP) (3.4%) and high-density lipoprotein cholesterol (HDL-C) (2.3%). Participants who took fish oil supplements displayed the same risk of CKD events, but that risk was delayed by approximately 2.79 years compared with non-users of fish oil.

CONCLUSIONS

Our findings advocate the beneficial role of fish oil use in preventing CKD among patients with diabetes, which may be mediated by serum levels of HbA1c, CRP and HDL-C, and support public health policies aiming to promote fish oil supplementation for the prevention of diabetes complications.

Association of Succinate and Adenosine Nucleotide Metabolic Pathways with Diabetic Kidney Disease in Patients with Type 2 Diabetes Mellitus

BACKGRUOUND

Although the prevalence of diabetic kidney disease (DKD) is increasing, reliable biomarkers for its early detection are scarce. This study aimed to evaluate the association of adenosine and succinate levels and their related pathways, including hyaluronic acid (HA) synthesis, with DKD.

METHODS

We examined 235 participants and categorized them into three groups: healthy controls; those with diabetes but without DKD; and those with DKD, which was defined as estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2. We compared the concentrations of urinary adenosine, succinate, and HA and the serum levels of cluster of differentiation 39 (CD39) and CD73, which are involved in adenosine generation, among the groups with DKD or albuminuria. In addition, we performed multiple logistic regression analysis to evaluate the independent association of DKD or albuminuria with the metabolites after adjusting for risk factors. We also showed the association of these metabolites with eGFR measured several years before enrollment. This study was registered with the Clinical Research Information Service (https://cris.nih.go.kr; Registration number: KCT0003573).

RESULTS

Urinary succinate and serum CD39 levels were higher in the DKD group than in the control and non-DKD groups. Correlation analysis consistently linked urinary succinate and serum CD39 concentrations with eGFR, albuminuria, and ΔeGFR, which was calculated retrospectively. However, among the various metabolites studied, only urinary succinate was identified as an independent indicator of DKD and albuminuria.

CONCLUSION

Among several potential metabolites, only urinary succinate was independently associated with DKD. These findings hold promise for clinical application in the management of DKD.

Liraglutide ameliorates inflammation and fibrosis by downregulating the TLR4/MyD88/NF-κB pathway in diabetic kidney disease

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 (LR), a GLP-1R agonist, on the downregulation of glomerular inflammation and fibrosis in DKD by regulating the Toll-like receptor (TLR)4/myeloid differentiation marker 88 (MyD88)/nuclear factor κB (NF-κB) 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 inhibit 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 wk 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.NEW & NOTEWORTHY Liraglutide, a glucagon-like peptide-1 receptor agonist (GLP-1RA), has renoprotective effect in diabetic kidney disease (DKD). In DKD, TLR4/MYD88/NF-κB signaling is involved in the regulation of inflammatory responses and extracellular matrix (ECM) protein proliferation. Liraglutide attenuates renal inflammation and overexpression of ECM proteins by inhibiting TLR4/MYD88/NF-κB signaling pathway. Therefore, we have identified a new mechanism that contributes to the renal protection of GLP-1RA, thus helping to design innovative treatment strategies for diabetic patients with various complications.

Pharmacological effects of bioactive agents in earthworm extract: A comprehensive review

This review compiles information from the literature on the chemical composition, pharmacological effects, and molecular mechanisms of earthworm extract (EE) and suggests possibilities for clinical translation of EE. We also consider future trends and concerns in this domain. We summarize the bioactive components of EE, including G-90, lysenin, lumbrokinase, antimicrobial peptides, earthworm serine protease (ESP), and polyphenols, and detail the antitumor, antithrombotic, antiviral, antibacterial, anti-inflammatory, analgesic, antioxidant, wound-healing, antifibrotic, and hypoglycemic activities and mechanisms of action of EE based on existing in vitro and in vivo studies. We further propose the potential of EE for clinical translation in anticancer and lipid-modifying therapies, and its promise as source of a novel agent for wound healing and resistance to antibiotic tolerance. The earthworm enzyme lumbrokinase embodies highly effective anticoagulant and thrombolytic properties and has the advantage of not causing bleeding phenomena due to hyperfibrinolysis. Its antifibrotic properties can reduce the excessive accumulation of extracellular matrix. The glycolipoprotein extract G-90 can effectively scavenge reactive oxygen groups and protect cellular tissues from oxidative damage. Earthworms have evolved a well-developed defense mechanism to fight against microbial infections, and the bioactive agents in EE have shown good antibacterial, fungal, and viral properties in in vitro and in vivo experiments and can alleviate inflammatory responses caused by infections, effectively reducing pain. Recent studies have also highlighted the role of EE in lowering blood glucose. EE shows high medicinal value and is expected to be a source of many bioactive compounds.

Integrating network pharmacology and experimental validation to decipher the pharmacological mechanism of DXXK in treating diabetic kidney injury

Diabetes mellitus (DM) is a chronic metabolic disease that is highly susceptible to kidney injury. Di'ao XinXueKang capsules (DXXK) is a novel Chinese herbal medicine that has been used in clinical trials for the therapy of DM and kidney disease, but the underlying pharmacological mechanism remains unclear. This study aims to integrate network pharmacology, molecular docking and in vivo experiments to explore the potential mechanisms of DXXK in the treatment of diabetic kidney injury. The chemical constituents of DXXK were extracted from the ETCM and Batman-TCM databases, and then evaluated for their pharmacological activity via the Swiss ADME platform. Multiple disease databases were searched and integrated for DM-related targets. Overlapping targets were then collected to construct a protein-protein interaction (PPI) network. KEGG and GO enrichment analyses were performed based on the Metascape database, and molecular docking was performed using AutoDock Vina software. The main components in DXXK were analyzed by HPLC. The results of network pharmacology and molecular docking were validated in an animal model of DM induced by the combination of a high-fat diet (HFD) and streptozotocin (STZ). We screened and obtained 7 ingredients and identified dioscin, protodioscin, and pseudoprotodioscin as the major components of DXXK by HPLC. A total of 2,216 DM-related pathogenic genes were obtained from DrugBank, GeneCards, OMIM, and DisGeNET databases. KEGG and GO enrichment analyses indicated that the TGF-beta signaling pathway is a critical pathway associated with DM therapy. Molecular docking revealed that the ingredients in DXXK bind to the pivotal targets TGFβ1, Smad2, and Smad3. In diabetic mice, we found that DXXK alleviated diabetic symptoms, lowered blood glucose, improved insulin tolerance, and modulated lipid metabolism. Furthermore, DXXK attenuated renal lesions and fibrosis by downregulating TGFβ1, Smad2, and Smad3. Collectively, our results suggest that DXXK has the potential to regulate glucolipid metabolism in DM, and it may serve as a viable therapeutic option for renoprotection by inhibiting of the TGF-β1/Smad2/3 pathway.

Proteome-wide mendelian randomization identifies novel therapeutic targets for chronic kidney disease

There is an urgent need to pinpoint novel targets for drug discovery in the context of chronic kidney disease (CKD), and the proteome represents a significant pool of potential therapeutic targets. To address this, we performed proteome-wide analyses using Mendelian randomization (MR) and colocalization techniques to uncover potential targets for CKD. We extracted summary-level data from the ARIC study, focusing on 7213 European American (EA) individuals and 4657 plasma proteins. To broaden our analysis, we incorporated genetic association data from Icelandic cohorts, thereby enhancing our investigation into the correlations with chronic kidney disease (CKD), creatinine-based estimated glomerular filtration rate (eGFRcrea), and estimated glomerular filtration rate (eGFR). We utilized genetic association data from the GWAS Catalog, including CKD (765,348, 625,219 European ancestry and 140,129 non-European ancestry), eGFRcrea (1,004,040, European ancestry), and eGFR (567,460, European ancestry). Employing MR analysis, we estimated the associations between proteins and CKD risk. Additionally, we conducted colocalization analysis to evaluate the existence of shared causal variants between the identified proteins and CKD. We detected notable correlations between levels predicted based on genetics of three circulating proteins and CKD, eGFRcrea, and eGFR. Notably, our colocalization analysis provided robust evidence supporting these associations. Specifically, genetically predicted levels of Transcription elongation factor A protein 2 (TCEA2) and Neuregulin-4 (NRG4) exhibited an inverse relationship with CKD risk, while Glucokinase regulatory protein (GCKR) showed an increased risk of CKD. Furthermore, our colocalization analysis also supported the associations of TCEA2, NRG4, and GCKR with the risk of eGFRcrea and eGFR.

Molecular Therapeutics for Diabetic Kidney Disease: An Update

Diabetic kidney disease (DKD) is a common microvascular complication of diabetes mellitus (DM). With the increasing prevalence of DM worldwide, the incidence of DKD remains high. If DKD is not well controlled, it can develop into chronic kidney disease or end-stage renal disease (ESRD), which places considerable economic pressure on society. Traditional therapies, including glycemic control, blood pressure control, blood lipid control, the use of renin-angiotensin system blockers and novel drugs, such as sodium-glucose cotransporter 2 inhibitors, mineralocorticoid receptor inhibitors and glucagon-like peptide-1 receptor agonists, have been used in DKD patients. Although the above treatment strategies can delay the progression of DKD, most DKD patients still ultimately progress to ESRD. Therefore, new and multimodal treatment methods need to be explored. In recent years, researchers have continuously developed new treatment methods and targets to delay the progression of DKD, including miRNA therapy, stem cell therapy, gene therapy, gut microbiota-targeted therapy and lifestyle intervention. These new molecular therapy methods constitute opportunities to better understand and treat DKD. In this review, we summarize the progress of molecular therapeutics for DKD, leading to new treatment strategies.

Association of Serum Tsukushi Levels with Urinary Albumin-Creatinine Ratio in Type 2 Diabetes Patients

Objective

Tsukushi is a newly identified hepatokine. Recent studies have shown that it relates to diabetes, lipid metabolism and fibrosis, but there is currently no investigation about whether Tsukushi is associated with diabetic kidney disease. Therefore, this study aimed to investigate the relationship between Tsukushi and diabetic kidney disease by characterizing Tsukushi levels in healthy subjects and type 2 diabetes with urinary albumin-creatinine ratio.

Methods

Serum Tsukushi level was quantified by enzyme-linked immunosorbent assay in 167 normoalbuminuria, 80 microalbuminuria, and 31 macroalbuminuria patients with type 2 diabetes as compared with 53 healthy subjects. The correlation analysis was used to investigate the relationship between urinary albumin-creatinine ratio or Tsukushi level and other metabolic parameters. Multiple linear regression and logistic regression analysis were used to analyze the independent factors for urinary albumin-creatinine ratio and estimated glomerular filtration rate.

Results

The Tsukushi level in the macroalbuminuria group was significantly higher than that in the normoalbuminuria or the microalbuminuria group. Multiple linear regression showed that the significantly independent factors for UACR included high Tsukushi quartile, systolic blood pressure, creatinine, homeostasis model assessment of insulin resistance, low 2-h post-oral glucose tolerance test c-peptide and female. Logistic regression demonstrated that the odds ratio of Tsukushi for glomerular filtration rate ≤90(mL/min/1.73m2) was 1.636 (95% CI 1.091-2.452, P=0.017).

Conclusion

The circulating Tsukushi increased in type 2 diabetes patients with albuminuria and was associated with urinary albumin-creatinine ratio, implying that Tsukushi may be involved in the pathogenesis of diabetic kidney disease, which deserves future studies.

Serum L C3-II levels in type 2 diabetic patients with impaired renal functions

This study was designed to evaluate serum LC3-II, BCL-2, IL-1β, TGF-β1, and podocin levels in. type 2 diabetes (T2DM) patients with renal dysfunction.

MATERIALS

176 Turkish subjects were enrolled, of whom 26 were healthy, and 150 had T2DM.

PATIENTS

were classified according to albumin urea ratio: 88 patients had macroalbuminuria, 20. patients had microalbuminuria, and 42 had normoalbuminuria. T2DM patients were also. classified into three groups according to proteinuria and eGFR stages.

RESULTS

Increased serum LC3-II levels in patients with T2DM with increased urinary albumin. extraction and impaired renal functions. There was a strong relationship between serum. LC3-II levels and serum BCL-2, IL-1β, TGF-β1, and Podocin levels. The efficiency of LC3- II as a diagnostic biomarker in the differential diagnosis of DM patients with. macroproteinuria from DM patients with normoproteinuria was 75.4%.

CONCLUSIONS

It was thought that increased serum LC3-II levels in T2DM patients with impaired renal. functions may cause renal podocyte damage. In these patients, serum LC3-II levels can be. evaluated as a new biomarker to follow the development of renal damage.

Podocyte Death in Diabetic Kidney Disease: Potential Molecular Mechanisms and Therapeutic Targets

Cell deaths maintain the normal function of tissues and organs. In pathological conditions, the abnormal activation or disruption of cell death often leads to pathophysiological effects. Diabetic kidney disease (DKD), a significant microvascular complication of diabetes, is linked to high mortality and morbidity rates, imposing a substantial burden on global healthcare systems and economies. Loss and detachment of podocytes are key pathological changes in the progression of DKD. This review explores the potential mechanisms of apoptosis, necrosis, autophagy, pyroptosis, ferroptosis, cuproptosis, and podoptosis in podocytes, focusing on how different cell death modes contribute to the progression of DKD. It recognizes the limitations of current research and presents the latest basic and clinical research studies targeting podocyte death pathways in DKD. Lastly, it focuses on the future of targeting podocyte cell death to treat DKD, with the intention of inspiring further research and the development of therapeutic strategies.

Serum biomarkers for predicting microvascular complications of diabetes mellitus

INTRODUCTION

Diabetic microvascular complications such as retinopathy, nephropathy, and neuropathy are primary causes of blindness, terminal renal failure, and neuropathic disorders in type 2 diabetes mellitus patients. Identifying reliable biomarkers promptly is pivotal for early detection and intervention in these severe complications.

AREAS COVERED

This review offers a thorough examination of the latest research concerning serum biomarkers for the prediction and assessment of diabetic microvascular complications. It encompasses biomarkers associated with glycation, oxidative stress, inflammation, endothelial dysfunction, basement membrane thickening, angiogenesis, and thrombosis. The review also highlights the potential of emerging biomarkers, such as microRNAs and long non-coding RNAs.

EXPERT OPINION

Serum biomarkers are emerging as valuable tools for the early assessment and therapeutic guidance of diabetic microvascular complications. The biomarkers identified not only reflect the underlying pathophysiology but also align with the extent of the disease. However, further validation across diverse populations and improvement of the practicality of these biomarkers in routine clinical practice are necessary. Pursuing these objectives is essential to advance early diagnosis, risk assessment, and individualized treatment regimens for those affected by diabetes.

CYSTATIN C-A Monitoring Perspective of Chronic Kidney Disease in Patients with Diabetes

Chronic kidney disease (CKD) is a microvascular complication that frequently affects numerous patients diagnosed with diabetes. For the diagnosis of CKD, the guidelines recommend the identification of the urinary albumin/creatinine ratio and the determination of serum creatinine, based on which the estimated rate of glomerular filtration (eGFR) is calculated. Serum creatinine is routinely measured in clinical practice and reported as creatinine-based estimated glomerular filtration rate (eGFRcr). It has enormous importance in numerous clinical decisions, including the detection and management of CKD, the interpretation of symptoms potentially related to this pathology and the determination of drug dosage. The equations based on cystatin C involve smaller differences between race groups compared to GFR estimates based solely on creatinine. The cystatin C-based estimated glomerular filtration rate (eGFRcys) or its combination with creatinine (eGFRcr-cys) are suggested as confirmatory tests in cases where creatinine is known to be less precise or where a more valid GFR estimate is necessary for medical decisions. Serum creatinine is influenced by numerous factors: age, gender, race, muscle mass, high-protein diet, including protein supplements, and the use of medications that decrease tubular creatinine excretion (H2 blockers, trimethoprim, fenofibrate, ritonavir, and other HIV drugs). The low levels of creatinine stemming from a vegetarian diet, limb amputation, and conditions associated with sarcopenia such as cirrhosis, malnutrition, and malignancies may lead to inaccurately lower eGFRcr values. Therefore, determining the GFR based on serum creatinine is not very precise. This review aims to identify a new perspective in monitoring renal function, considering the disadvantages of determining the GFR based exclusively on serum creatinine.

Efficacy and safety of polyethylene glycol loxenatide in treating mild-to-moderate diabetic kidney disease in type 2 diabetes patients: a randomized, open-label, clinical trial

Objective

This study aimed to evaluate the efficacy and safety of polyethylene glycol loxenatide (PEG-Loxe) compared to those of dapagliflozin in patients with mild-to-moderate diabetic kidney disease (DKD), a prevalent microvascular complication of type 2 diabetes mellitus (T2DM). The study is set against the backdrop of increasing global diabetes incidence and the need for effective DKD management.

Methods

This study constituted a single-center, randomized, open-label, clinical trial. The trial included patients with mild-to-moderate DKD and suboptimal glycemic control. Eligible participants were randomly allocated to one of the two groups for treatment with either PEG-Loxe or dapagliflozin. The primary endpoint was the change in UACR from baseline at 24 weeks.

Results

Overall, 106 patients were randomized and 80 patients completed the study. Following 24 weeks of treatment, the PEG-Loxe group exhibited a mean percent change in baseline UACR of -29.3% (95% confidence interval [CI]: -34.8, -23.7), compared to that of -31.8% in the dapagliflozin group (95% CI: -34.8, -23.7). Both PEG-Loxe and dapagliflozin showed similar efficacy in reducing UACR, with no significant difference between the groups (p = 0.336). The HbA1c levels decreased by -1.30% (95% CI: -1.43, -1.18) in the PEG-Loxe group and by -1.29% (95% CI: -1.42, -1.17) in the dapagliflozin group (p = 0.905). The TG levels decreased by -0.56 mmol/L (95% CI: -0.71, -0.42) in the PEG-Loxe group and -0.33 mmol/L (95% CI: -0.48, -0.19) in the dapagliflozin group (p = 0.023). Differences in TC, HDL-C, LDL-C, SBP, and DBP levels between the groups were not statistically significant (all p > 0.05). Safety profiles were consistent with previous findings, with gastrointestinal adverse events being more common in the PEG-Loxe group.

Conclusions

PEG-Loxe is as effective as dapagliflozin in improving urine protein levels in patients with mild-to-moderate DKD and offers superior benefits in improving lipid profiles. These findings support the use of PEG-Loxe in DKD management, contributing to evidence-based treatment options.

Clinical Trial Registration

www.chictr.org.cn, identifier ChiCTR2300070919.

The triglyceride-glucose index is superior to homeostasis model assessment of insulin resistance in predicting metabolic syndrome in an adult population in the United States

BACKGROUND

Metabolic syndrome (MetS) is a cluster of cardio-metabolic features portending an increased risk for both type 2 diabetes mellitus (T2DM) and premature atherosclerotic cardiovascular disease (ASCVD). Homeostasis model assessment of insulin resistance (HOMA-IR) is a widely used surrogate measure of insulin resistance. The triglyceride-glucose (TyG) index is another validated measure of insulin resistance that predicts both diabetes and cardiovascular disease in low and medium-income countries, but only diabetes in high income countries.

OBJECTIVE

Due to the paucity of data on the TyG index in the US population, we compared the validity of the TyG index and HOMA-IR in predicting MetS.

METHODS

Data from the National Health and Nutrition Examination Survey (NHANES) between 2005 and 2018 on Non-Hispanic White (NHW), Hispanic American (HA), and African American (AA) individuals (n = 5380) aged 20-80 years were used for analysis. Individuals were classified as having MetS based on three or more of its components. HOMA-IR and the TyG index were determined from fasting samples.

RESULTS

Both the TyG index and HOMA-IR were significantly increased in MetS and increased significantly with increasing severity of the syndrome. Also both indices correlated significantly with all 5 features of MetS, hsCRP and non-HDL-C. ROC-AUC analysis for TyG index was significantly greater than that of HOMA-IR in predicting MetS: 0.87 (95 % CI 0.85-0.88) versus 0.82 (95 % CI 0.81-0.83) respectively, p < 0.0001. This was not evident for the small AA subgroup.

CONCLUSION

The TyG index outperformed HOMA-IR in predicting MetS, a proxy for both T2DM and ASCVD, in a general US population and is a valuable biomarker.

Multiomics Analyses Identify AKR1A1 as a Biomarker for Diabetic Kidney Disease

Diabetic kidney disease (DKD) is the leading cause of end-stage kidney disease. Because many genes associate with DKD, multiomics approaches were used to narrow the list of functional genes, gene products, and related pathways providing insights into the pathophysiological mechanisms of DKD. The Kidney Precision Medicine Project human kidney single-cell RNA-sequencing (scRNA-seq) data set and Mendeley Data on human kidney cortex biopsy proteomics were used. The R package Seurat was used to analyze scRNA-seq data and data from a subset of proximal tubule cells. PathfindR was applied for pathway analysis in cell type-specific differentially expressed genes and the R limma package was used to analyze differential protein expression in kidney cortex. A total of 790 differentially expressed genes were identified in proximal tubule cells, including 530 upregulated and 260 downregulated transcripts. Compared with differentially expressed proteins, 24 genes or proteins were in common. An integrated analysis combining protein quantitative trait loci, genome-wide association study hits (namely, estimated glomerular filtration rate), and a plasma metabolomics analysis was performed using baseline metabolites predictive of DKD progression in our longitudinal Diabetes Heart Study samples. The aldo-keto reductase family 1 member A1 gene (AKR1A1) was revealed as a potential molecular hub for DKD cellular dysfunction in several cross-linked pathways featured by deficiency of this enzyme.

ARTICLE HIGHLIGHTS

[Exercise promotes irisin expression to ameliorate renal injury in type 2 diabetic rats]

OBJECTIVE

To investigate the role of irisin in exercise-induced improvement of renal function in type 2 diabetic rats.

METHODS

Forty male SD rats aged 4-6 weeks were randomized into normal control group, type 2 diabetes mellitus model group, diabetic exercise (DE) group and diabetic irisin (DI) group (n=8). The rats in DE group were trained with treadmill running for 8 weeks, and those in DI group were given scheduled irisin injections for 8 weeks. After the treatments, blood biochemical parameters of the rats were examined, and renal histopathology was observed with HE, Masson and PAS staining. Western blotting was used to detect the protein expression levels in the rats'kidneys.

RESULTS

The diabetic rats showed significantly increased levels of fasting insulin, total cholesterol, triglyceride, serum creatinine and blood urea nitrogen with lowered serum irisin level (all P < 0.05). Compared with those in DM group, total cholesterol, triglyceride, serum creatinine and blood urea nitrogen levels were decreased and serum irisin levels were increased in both DE and DI groups (all P < 0.05). The rats in DM group showed obvious structural disorders and collagen fiber deposition in the kidneys, which were significantly improved in DE group and DI group. Both regular exercises and irisin injections significantly ameliorated the reduction of FNDC5, LC3-II/I, Atg7, Beclin-1, p-AMPK, AMPK and SIRT1 protein expressions and lowered of p62 protein expression in the kidneys of the diabetic rats (all P < 0.05).

CONCLUSION

Both exercise and exogenous irisin treatment improve nephropathy in type 2 diabetic rats possibly due to irisin-mediated activation of the AMPK/SIRT1 pathway in the kidneys to promote renal autophagy.

Single-Cell RNA Sequencing Reveals RAC1 Involvement in Macrophages Efferocytosis in Diabetic Kidney Disease

Macrophage-mediated inflammation plays a significant role in the development and progression of diabetic kidney disease (DKD). Studies have suggested that impaired macrophage efferocytosis aggravates the inflammatory response. However, its contribution to DKD progression remains unknown. Using single-cell RNA sequencing (scRNA-seq) data obtained from the GSE131882, GSE195460, GSE151302, GSE195460, and GSE131685 datasets, we successfully clustered 13 cell types. Through analysis of the ligand-receptor network, it was discovered that macrophages interact with other cells. Additionally, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses revealed that macrophages exhibit a heightened presence of phagocytosis signaling. We discovered that RAC1 was closely related to macrophage efferocytosis through a Venn diagram and protein-protein interaction (PPI) analysis, which predicted the correlation with the clinical features of DKD using the NephroseqV5 tool. Furthermore, we verified that RAC1 exhibited decreased expression in macrophages cultured with lipopolysaccharide (LPS) and high glucose. Nevertheless, the overexpression of RAC1 promoted macrophage efferocytosis and inhibited the inflammatory response. In summary, our study focused on examining the presence and importance of efferocytosis-related molecules in DKD macrophages. Through a comprehensive analysis using scRNA-seq, we discovered that RAC1 plays a crucial role as an efferocytosis molecule in DKD. These findings enhance our current knowledge of the molecular mechanisms involved in the development of DKD and aid the exploration of new treatments.

Specific Alternation of Gut Microbiota and the Role of Ruminococcus gnavus in the Development of Diabetic Nephropathy

In this study, we aim to investigate the precise alterations in the gut microbiota during the onset and advancement of diabetic nephropathy (DN) and examine the impact of Ruminococcus gnavus (R. gnavus) on DN. Eight-week-old male KK-Ay mice were administered antibiotic cocktails for a duration of two weeks, followed by oral administration of R. gnavus for an additional eight weeks. Our study revealed significant changes in the gut microbiota during both the initiation and progression of DN. Specifically, we observed a notable increase in the abundance of Clostridia at the class level, higher levels of Lachnospirales and Oscillospirales at the order level, and a marked decrease in Clostridia_UCG-014 in DN group. Additionally, there was a significant increase in the abundance of Lachnospiraceae, Oscillospiraceae, and Ruminococcaceae at the family level. Moreover, oral administration of R. gnavus effectively aggravated kidney pathology in DN mice, accompanied by elevated levels of urea nitrogen (UN), creatinine (Cr), and urine protein. Furthermore, R. gnavus administration resulted in down-regulation of tight junction proteins such as Claudin-1, Occludin, and ZO-1, as well as increased levels of uremic toxins in urine and serum samples. Additionally, our study demonstrated that orally administered R. gnavus up-regulated the expression of inflammatory factors, including nucleotide-binding oligomerization domain-like receptor pyrin domain-containing protein 3 (NLRP3) and Interleukin (IL)-6. These changes indicated the involvement of the gut-kidney axis in DN, and R. gnavus may worsen diabetic nephropathy by affecting uremic toxin levels and promoting inflammation in DN.

Identification and validation of immune and cuproptosis - related genes for diabetic nephropathy by WGCNA and machine learning

Background

As the leading cause of chronic kidney disease, diabetic kidney disease (DKD) is an enormous burden for all healthcare systems around the world. However, its early diagnosis has no effective methods.

Methods

First, gene expression data in GEO database were extracted, and the differential genes of diabetic tubulopathy were obtained. Immune-related genesets were generated by WGCNA and immune cell infiltration analyses. Then, differentially expressed immune-related cuproptosis genes (DEICGs) were derived by the intersection of differential genes and genes related to cuproptosis and immune. To investigate the functions of DEICGs, volcano plots and GO term enrichment analysis was performed. Machine learning and protein-protein interaction (PPI) network analysis helped to finally screen out hub genes. The diagnostic efficacy of them was evaluated by GSEA analysis, receiver operating characteristic (ROC) curve, single-cell RNA sequencing and the Nephroseq website. The expression of hub genes at the animal level by STZ -induced and db/db DKD mouse models was further verified.

Results

Finally, three hub genes, including FSTL1, CX3CR1 and AGR2 that were up-regulated in both the test set GSE30122 and the validation set GSE30529, were screened. The areas under the curve (AUCs) of ROC curves of hub genes were 0.911, 0.935 and 0.922, respectively, and 0.946 when taking as a whole. Correlation analysis showed that the expression level of three hub genes demonstrated their negative relationship with GFR, while those of FSTL1 displayed a positive correlation with the level of serum creatinine. GSEA was enriched in inflammatory and immune-related pathways. Single-nucleus RNA sequencing indicated the main distribution of FSTL1 in podocyte and mesangial cells, the high expression of CX3CR1 in leukocytes and the main localization of AGR2 in the loop of Henle. In mouse models, all three hub genes were increased in both STZ-induced and db/db DKD models.

Conclusion

Machine learning was combined with WGCNA, immune cell infiltration and PPI analyses to identify three hub genes associated with cuproptosis, immunity and diabetic nephropathy, which all have great potential as diagnostic markers for DKD and even predict disease progression.

Abdominal adipose tissue and type 2 diabetic kidney disease: adipose radiology assessment, impact, and mechanisms

Diabetic kidney disease (DKD) is a significant healthcare burden worldwide that substantially increases the risk of kidney failure and cardiovascular events. To reduce the prevalence of DKD, extensive research is being conducted to determine the risk factors and consequently implement early interventions. Patients with type 2 diabetes mellitus (T2DM) are more likely to be obese. Abdominal adiposity is associated with a greater risk of kidney damage than general obesity. Abdominal adipose tissue can be divided into different fat depots according to the location and function, including visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), perirenal adipose tissue (PAT), and renal sinus adipose tissue (RSAT), which can be accurately measured by radiology techniques, such as computed tomography (CT) and magnetic resonance imaging (MRI). Abdominal fat depots may affect the development of DKD through different mechanisms, and radiologic abdominal adipose characteristics may serve as imaging indicators of DKD risk. This review will first describe the CT/MRI-based assessment of abdominal adipose depots and subsequently describe the current studies on abdominal adipose tissue and DKD development, as well as the underlying mechanisms in patients of T2DM with DKD.

Urinary podocyte stress marker as a prognostic indicator for diabetic kidney disease

BACKGROUND

Diabetic kidney diseases (DKD) is a the most common cause of end-stage kidney disease (ESKD) around the world. Previous studies suggest that urinary podocyte stress biomarker, e.g. podocin:nephrin mRNA ratio, is a surrogate marker of podocyte injury in non-diabetic kidney diseases.

METHOD

We studied 118 patients with biopsy-proved DKD and 13 non-diabetic controls. Their urinary mRNA levels of nephrin, podocin, and aquaporin-2 (AQP2) were quantified. Renal events, defined as death, dialysis, or 40% reduction in glomerular filtration rate, were determined at 12 months.

RESULTS

Urinary podocin:nephrin mRNA ratio of DKD was significantly higher than the control group (p = 0.0019), while urinary nephrin:AQP2 or podocin:AQP2 ratios were not different between groups. In DKD, urinary podocin:nephrin mRNA ratio correlated with the severity of tubulointerstitial fibrosis (r = 0.254, p = 0.006). and was associated with the renal event-free survival in 12 months (unadjusted hazard ratio [HR], 1.523; 95% confidence interval [CI] 1.157-2.006; p = 0.003). After adjusting for clinical and pathological factors, urinary podocin:nephrin mRNA ratio have a trend to predict renal event-free survival (adjusted HR, 1.327; 95%CI 0.980-1.797; p = 0.067), but the result did not reach statistical significance.

CONCLUSION

Urinary podocin:nephrin mRNA ratio has a marginal prognostic value in biopsy-proven DKD. Further validation is required for DKD patients without kidney biopsy.

Role of MCP-1 as an inflammatory biomarker in nephropathy

The Monocyte chemoattractant protein-1 (MCP-1), also referred to as chemokine ligand 2 (CCL2), belongs to the extensive chemokine family and serves as a crucial mediator of innate immunity and tissue inflammation. It has a notable impact on inflammatory conditions affecting the kidneys. Upon binding to its receptor, MCP-1 can induce lymphocytes and NK cells' homing, migration, activation, differentiation, and development while promoting monocytes' and macrophages' infiltration, thereby facilitating kidney disease-related inflammation. As a biomarker for kidney disease, MCP-1 has made notable advancements in primary kidney diseases such as crescentic glomerulonephritis, chronic glomerulonephritis, primary glomerulopathy, idiopathic proteinuria glomerulopathy, acute kidney injury; secondary kidney diseases like diabetic nephropathy and lupus nephritis; hereditary kidney diseases including autosomal dominant polycystic kidney disease and sickle cell kidney disease. MCP-1 not only predicts the occurrence, progression, prognosis of the disease but is also closely associated with the severity and stage of nephropathy. When renal tissue is stimulated or experiences significant damage, the expression of MCP-1 increases, demonstrating a direct correlation with the severity of renal injury.

Role of Epigenetic Changes in the Pathophysiology of Diabetic Kidney Disease

Background

Diabetic kidney disease (DKD) is a global health issue. Epigenetic changes play an important role in the pathogenesis of this disease.

Summary

DKD is currently the leading cause of kidney failure worldwide. Although much is known about the pathophysiology of DKD, the research field of epigenetics is relatively new. Several recent studies have demonstrated that diabetes-induced dysregulation of epigenetic mechanisms alters the expression of pathological genes in kidney cells. If these changes persist for a long time, the so-called "metabolic memory" could be established. In this review, we highlight diabetes-induced epigenetic modifications associated with DKD. While there is a substantial amount of literature on epigenetic changes, only a few studies describe the underlying molecular mechanisms. Detailed analyses have shown that epigenetic changes play an important role in known pathological features of DKD, such as podocyte injury, fibrosis, accumulation of extracellular matrix, or oxidative injury, all of which contribute to the pathophysiology of disease. The transforming growth factor-β plays a key role as it is involved in all-mentioned epigenetic types of regulation.

Key Messages

Epigenetic is crucial for the development and progression of DKD, but the detailed molecular mechanisms have to be further analyzed more in detail.

Role of polyphenols in the management of diabetic complications

BACKGROUND

Diabetes Mellitus is an endocrine disorder that will affect, about 693 million adults by 2045 worldwide, (>50% increase from 2017). The conventional treatment of the disease, include the oral hypoglycemic drugs which are given in combination with other drugs and are known to possess various adverse effects like gastrointestinal disturbance, nausea, water retention etc. PURPOSE: Due to the urgent need of combating this disorder without side effects, the alternative and complementary therapies should be explored due to their natural origins and comparable safety. Herbal sources serve as new leads, due to the presence of phytoconstituents with potential therapeutic properties, efficacy and safety. In this review, we tried to summarise the polyphenolic phytoconstituents effective in the treatment of diabetic complications.

METHODS

A systematic literature search was conducted using 4 databases (Google scholar, Pubmed, Scopus, Embase) for the identification of relevant data. Search was performed using various key words such as "diabetes", "polyphenols", "marine sources","anti-diabetic polyphenols". The in vitro studies involving the cell lines used in diabetes and animal models were also considered for inclusion. Additional research papers were identified by reviewing abstracts, scrutinizing reference lists, and reviewing previously published review articles.

RESULTS

Polyphenols, a group of phytoconstituents are known worldwide for their tremendous antioxidant potential. So, various research groups have explored their mechanism and therapeutic value in diabetic complications, to improve the insulin sensitivity and glucose metabolism, in controlling the glycemic conditions.

CONCLUSION

Polyphenols exhibit effective therapeutic potential in managing diabetic complications through their multifaceted mechanism of action. They exhibit antioxidative, anti-inflammatory, and anti-glycemic properties, which collectively contribute to their beneficial effects in mitigating diabetic complications. Thus, the inclusion of polyphenols into the diet, may be cosidered as an approach of managing diabetes on long term basis. In this review, we have tried to identify polyphenols effective in diabetes and summarize their mechanism of action along with their potential, for the treatment of diabetic complications.