Novel biomarkers of diabetic kidney disease: current status and potential clinical application

Identification of mitochondria-related genes as diagnostic biomarkers for diabetic nephropathy and their correlation with immune infiltration: New insights from bioinformatics analysis

BACKGROUND

Diabetic nephropathy (DN) is a common and severe microvascular complication of diabetes. Mitochondrial dysfunction and immune inflammation are important factors in the pathogenesis of DN. However, the specific mechanisms and their intricate interactions in DN remain unclear. Besides, there are no effective specific predictive or diagnostic biomarkers for DN so far. Therefore, this study aims to elucidate the role of mitochondrial-related genes and their possibility as predictive or diagnostic biomarkers, as well as their crosstalk with immune infiltration in the progression of DN.

METHODS

Based on the GEO database and limma R package, the differentially expressed genes (DEGs) of DN were identified. Mitochondrial-related DEGs (MitoDEGs) were then obtained by intersecting these DEGs with mitochondria-related genes from the MitoCarta 3.0 database. Subsequently, the candidate hub genes were further screened by gene co-expression network analysis (WGCNA), and verified mRNA levels of these genes by real-time quantitative PCR (qRT-PCR) in high-glucose-treated human proximal tubular (HK-2) cells. The verified hub genes were utilized to construct a combined diagnostic model for DN, with its diagnostic efficacy assessed across the GSE30122 and GSE96804 datasets. Additionally, the immune infiltration pattern in DN was assessed with the CIBERSORT algorithm, and the Nephroseq v5 database was used to analyze the correlation between hub genes and clinical features of DN.

RESULTS

Seven mitochondria-related candidate hub genes were screened from 56 MitoDEGs. Subsequently, the expression levels of six of them, namely EFHD1, CASP3, AASS, MPC1, NT5DC2, and BCL2A1, exhibited significant inter-group differences in the HK-2 cell model. The diagnostic model based on the six genes demonstrated good diagnostic efficacy in both training and validation sets. Furthermore, correlation analysis indicated that EFHD1 and AASS, downregulated in DN, are positively correlated with eGFR and negatively with serum creatinine. Conversely, CASP3, NT5DC2, and BCL2A1, upregulated in DN, show opposite correlations. In addition, spearman analysis revealed that the six hub genes were significantly associated with the infiltration of immune cells, including M1 and M2 macrophages, mast cells, resting NK cells, gamma delta T cells, and follicular helper T cells.

CONCLUSION

This study elucidated the characteristics of mitochondria-related genes and their correlation with immune cell infiltration in DN, providing new insights for exploring the pathogenesis of DN and facilitating the identification of new potential biomarkers and therapeutic targets.

Association of major candidate protein biomarkers and long-term diabetic kidney disease progression among Asians with young-onset type 2 diabetes mellitus

AIMS

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.

Preclinical Detection of Early Glomerular Injury in Children with Kidney Diseases-Independently of Usual Markers of Kidney Impairment and Inflammation

Glomerular kidney diseases typically begin insidiously and can progress to end stage kidney failure. Early onset of therapy can slow down disease progression. Early diagnosis is required to ensure such timely therapy. The goal of our study was to evaluate protein biomarkers (BMs) for common nephropathies that have been described for children with Alport syndrome. Nineteen candidate BMs were determined by commercial ELISA in children with congenital anomalies of the kidneys and urogenital tract, inflammatory kidney injury, or diabetes mellitus. It is particularly essential to search for kidney disease BMs in children because they are a crucial target group that likely exhibits early disease stages and in which misleading diseases unrelated to the kidney are rare. Only minor differences in blood between affected individuals and controls were found. However, in urine, several biomarker candidates alone or in combination seemed to be promising indicators of renal injury in early disease stages. The BMs of highest sensitivity and specificity were collagen type XIII, hyaluronan-binding protein 2, and complement C4-binding protein. These proteins are unrelated to inflammation markers or to risk factors for and signs of renal failure. In conclusion, our study evaluated several strong candidates for screening for early stages of kidney diseases and can help to establish early nephroprotective regimens.

Urinary biomarkers in diabetic nephropathy

Diabetic nephropathy (DN), a significant consequence of diabetes, is associated with adverse cardiovascular and renal disease as well as mortality. Although microalbuminuria is considered the best non-invasive marker for DN, better predictive markers are needed of sufficient sensitivity and specificity to detect disease in general and in early disease specifically. Even prior to appearance of microalbuminuria, urinary biomarkers increase in diabetics and can serve as accurate nephropathy biomarkers even in normoalbuminuria. In this review, a number of novel urine biomarkers including those reflecting kidney damage caused by glomerular/podocyte damage, tubular damage, oxidative stress, inflammation, and intrarenal renin-angiotensin system activation are discussed. Our review also includes emerging biomarkers such as urinary microRNAs. These short noncoding miRNAs regulate gene expression and could be utilized to identify potential novel biomarkers in DN development and progression. .

Design of Machine Learning Algorithms and Internal Validation of a Kidney Risk Prediction Model for Type 2 Diabetes Mellitus

Objective

This study aimed to explore specific biochemical indicators and construct a risk prediction model for diabetic kidney disease (DKD) in patients with type 2 diabetes (T2D).

Methods

This study included 234 T2D patients, of whom 166 had DKD, at the First Hospital of Jilin University from January 2021 to July 2022. Clinical characteristics, such as age, gender, and typical hematological parameters, were collected and used for modeling. Five machine learning algorithms [Extreme Gradient Boosting (XGBoost), Gradient Boosting Machine (GBM), Support Vector Machine (SVM), Logistic Regression (LR), and Random Forest (RF)] were used to identify critical clinical and pathological features and to build a risk prediction model for DKD. Additionally, clinical data from 70 patients (nT2D = 20, nDKD = 50) were collected for external validation from the Third Hospital of Jilin University.

Results

The RF algorithm demonstrated the best performance in predicting progression to DKD, identifying five major indicators: estimated glomerular filtration rate (eGFR), glycated albumin (GA), Uric acid, HbA1c, and Zinc (Zn). The prediction model showed sufficient predictive accuracy with area under the curve (AUC) values of 0.960 (95% CI: 0.936-0.984) and 0.9326 (95% CI: 0.8747-0.9885) in the internal validation set and external validation set, respectively. The diagnostic efficacy of the RF model (AUC = 0.960) was significantly higher than each of the five features screened with the highest feature importance in the RF model.

Conclusion

The online DKD risk prediction model constructed using the RF algorithm was selected based on its strong performance in the internal validation.

The predictive value of miR-377 and phospholipase A2 in the early diagnosis of diabetic kidney disease and their relationship with inflammatory factors

OBJECTIVE

The value of novel biomarkers for DKD has received increasing attention, and there is an urgent need for novel biomarkers with sensitivity, specificity and ability to detect kidney damage.miR-377 regulates many basic biological processes, plays a key role in tumor cell proliferation, migration and inflammation, and can also increase the expression of matrix proteins and fibronectin, leading to renal tubulointerstitial inflammation and renal fibrosis. Lipoprotein-associated phospholipase A2, as an inflammatory marker, is involved in the pathological process of microalbuminuria production and renal function decline, and is a predictive factor of microalbuminuria production and renal function decline, and can be used as an indicator to evaluate the progression of DKD.The aim of this study was to investigate the effects of miR-377 and phospholipase A2 on the development of diabetic kidney disease through regulation of inflammatory factors and the mechanism of action.

METHODS

80 diabetic patients were divided into two groups according to urinary albumin-to-creatinine ratio (UACR): diabetic normal proteinuria group (n = 42) and diabetic proteinuria group (n = 38). Forty-three healthy people were selected as the normal control group. The serum levels of TGF-β, IL-6, and IL-18 were measured by ELISA, miR-377 was detected by qPCR, and the serum levels of phospholipase A2 were detected by electrochemiluminescence. Analyze the correlation of study group indicators, ROC curve was used to evaluate the diagnostic efficacy of miR-377 and phospholipase A2 in diabetic kidney disease.

RESULTS

The average levels of serum TGF-β, IL-6, IL-18, miR-377 and phospholipase A2 in diabetic proteinuria group were significantly higher than those in normal control group and diabetic proteinuria normal group(P < 0.05). miR-377, phospholipase A2 were significantly correlated with inflammatory factors such as glomerular filtration rate and TGF-β. miR-377 and phospholipase A2 are independent predictors of diabetic kidney disease. The area under the curve of miR-377 and phospholipase A2 in the normal diabetic proteinuria group and the diabetic proteinuria group were 0.731 and 0.744, respectively.

CONCLUSION

miR-377 and phospholipase A2 have good diagnostic efficiency for the early diagnosis of diabetic kidney disease. They can be used as early biomarkers.miR-377 and phospholipase A2 were positively correlated with inflammatory factors and involved in the occurrence and development of diabetic kidney disease.

Investigating HMGB1 as a potential serum biomarker for early diabetic nephropathy monitoring by quantitative proteomics

Current diagnostic methods for diabetic nephropathy (DN) lack precision, especially in early stages and monitoring progression. This study aims to find potential biomarkers for DN progression and evaluate their accuracy. Using serum samples from healthy controls (NC), diabetic patients (DM), early-medium stage DN (DN-EM), and late-stage DN (DN-L), researchers employed quantitative proteomics and Mfuzz clustering analysis revealed 15 proteins showing increased expression during DN progression, hinting at their biomarker potential. Combining Mfuzz clustering with weighted gene co-expression network analysis (WGCNA) highlighted five candidates (HMGB1, CD44, FBLN1, PTPRG, and ADAMTSL4). HMGB1 emerged as a promising biomarker, closely correlated with renal function changes. Experimental validation supported HMGB1's upregulation under high glucose conditions, reinforcing its potential as an early detection biomarker for DN. This research advances DN understanding and identifies five potential biomarkers, notably HMGB1, as a promising early monitoring target. These findings set the stage for future clinical diagnostic applications in DN.

Explainable Machine Learning-Based Prediction Model for Diabetic Nephropathy

The aim of this study is to analyze the effect of serum metabolites on diabetic nephropathy (DN) and predict the prevalence of DN through a machine learning approach. The dataset consists of 548 patients from April 2018 to April 2019 in the Second Affiliated Hospital of Dalian Medical University (SAHDMU). We select the optimal 38 features through a least absolute shrinkage and selection operator (LASSO) regression model and a 10-fold cross-validation. We compare four machine learning algorithms, including extreme gradient boosting (XGB), random forest, decision tree, and logistic regression, by AUC-ROC curves, decision curves, and calibration curves. We quantify feature importance and interaction effects in the optimal predictive model by Shapley additive explanation (SHAP) method. The XGB model has the best performance to screen for DN with the highest AUC value of 0.966. The XGB model also gains more clinical net benefits than others, and the fitting degree is better. In addition, there are significant interactions between serum metabolites and duration of diabetes. We develop a predictive model by XGB algorithm to screen for DN. C2, C5DC, Tyr, Ser, Met, C24, C4DC, and Cys have great contribution in the model and can possibly be biomarkers for DN.

Should we enlarge the indication for kidney biopsy in patients with diabetes? The pro part

Diabetic nephropathy (DN) and non-diabetic renal diseases (NDRD) represent intricate challenges in diagnosis and treatment within the context of the global diabetes epidemic. As the prevalence of diabetes continues to escalate, effective management of renal complications becomes paramount. Recent advancements in comprehending the multifaceted nature of renal damage, fueled by insights from histopathological investigations, offer unprecedented prospects for refining diagnostic strategies and customizing therapeutic interventions. Renal biopsies have emerged as indispensable tools for unraveling the diverse phenotypes of renal damage in diabetes. The pioneering study by Mazzucco identified three classes of renal damage in type 2 diabetes patients: classical diabetic glomerulosclerosis (DN), vascular and ischemic glomerular changes (NDRD), and other glomerulonephritides in the presence (DN + NDRD, mixed forms) or absence of DN (NDRD). The prevalence of these classes varies widely in published studies, influenced by factors such as ethnicity, geography and selection criteria for renal biopsy. Moreover, the international Renal Pathology Society consensus classification system has stratified the classical diabetic nephropathy into progressive categories of renal impairment, a breakthrough that aids in prognostication. Histopathological scrutiny, particularly the intricate correlation between glomerular and tubulointerstitial lesions, contributes profoundly to enhancing our grasp of the phenotype's heterogeneity. This amplified comprehension holds the potential to steer personalized treatment strategies. Cutting-edge interventions, encompassing sodium-glucose cotransporter 2 inhibitors, mineralocorticoid receptor antagonists and anti-endothelin receptor agents, are broadening the arsenal against renal injury in diabetes. When combined with the profound insights garnered from histopathological, omics, imaging and clinical data, these therapeutic avenues promise a transformative shift towards precision-driven care paradigms. Collaborative efforts uniting researchers, clinicians and patients are indispensable for propelling our knowledge of diabetic renal damage and ameliorating patient outcomes. The fusion of histopathological, omics and imaging findings into clinical decision-making harbors the potential to customize interventions and optimize care for individuals grappling with diabetes-associated renal complications. Furthermore, groundbreaking initiatives like the iBeat Study within the BEAt-DKD (Biomarker Enterprise to Attack Diabetic Kidney Disease) project (https://www.beat-dkd.eu/), elucidating distinct phenotypes of renal damage within diabetes, underscore the imperative necessity of integrating histopathological data into the broader framework of diabetic renal management.

Serum MicroRNA-191-5p Levels in Vascular Complications of Type 1 Diabetes: The EURODIAB Prospective Complications Study

CONTEXT

MicroRNA-191-5p regulates key cellular processes involved in the pathogenesis of diabetic complications such as angiogenesis, extracellular matrix deposition, and inflammation. However, no data on circulating microRNA-191-5p in the chronic complications of diabetes are available.

OBJECTIVE

To assess whether serum levels of microRNA-191-5p were associated with micro- and macrovascular disease in a large cohort of subjects with type 1 diabetes mellitus (DM1) from the EURODIAB Prospective Complication Study.

DESIGN AND SETTING

Levels of microRNA-191-5p were measured by quantitative PCR in 420 patients with DM1 recruited as part of the cross-sectional analysis of the EURODIAB Prospective Complication Study. Cases (n = 277) were subjects with nephropathy and/or retinopathy and/or cardiovascular disease (CVD). Controls (n = 143) were patients without complications. Logistic regression analysis was performed to evaluate the potential independent association of microRNA-191-5p levels with chronic complications of diabetes.

RESULTS

Levels of microRNA-191-5p were significantly reduced (P < .001) in cases compared with controls even after adjustment for age, sex, and diabetes duration. Logistic regression analysis revealed that microRNA-191-5p was negatively associated with a 58% reduced odds ratio (OR) of chronic diabetes complications, specifically CVD, micro-macroalbuminuria, and retinopathy (OR, 0.42; 95% CI, 0.23-0.77), independent of age, sex, physical activity, educational levels, diabetes duration, glycated hemoglobin, total insulin dose, hypertension, smoking, total cholesterol, albumin excretion rate, estimated glomerular filtration rate, serum vascular cell adhesion molecule-1, and tumor necrosis factor-α. Analyses performed separately for each complication demonstrated a significant independent association with albuminuria (OR, 0.36; 95% CI, (0.18-0.75) and CVD (OR, 0.34; 95% CI, 0.16-0.70).

CONCLUSIONS

In DM1 subjects, microRNA-191-5p is inversely associated with vascular chronic complications of diabetes.

Cardiovascular risk and renal injury profile in subjects with type 2 diabetes and non-albuminuric diabetic kidney disease

BACKGROUND

In the last years, the classical pattern of diabetic kidney disease (DKD) has been partially overcome, because of the uncovering of a new DKD phenotype with significant renal dysfunction without presence of albuminuria: the non-albuminuric DKD (NA-DKD). To date, the cardiovascular risk associated with this phenotype is still debated. We investigated the cardiovascular risk and renal injury profile of NA-DKD subjects in comparison with other DKD phenotypes.

METHODS

Pulse wave velocity (PWV), intima-media thickness, presence of carotid atherosclerotic plaque, renal resistive index (RRI), and a panel of urinary biomarkers of kidney injury were evaluated in 160 subjects with type 2 diabetes, stratified according to estimated glomerular filtration rate (eGFR) and urinary albumin to creatinine ratio (UACR) into four groups: controls (UACR < 30 mg/g and eGFR ≥ 60 mL/min/1.73 m2), A-DKD (Albuminuric-DKD, UACR ≥ 30 mg/g and eGFR ≥ 60 mL/min/1.73 m2), NA-DKD (UACR < 30 mg/g and eGFR < 60 mL/min/1.73 m2), AL-DKD (Albuminuric and Low eGFR-DKD; UACR ≥ 30 mg/g and eGFR < 60 mL/min/1.73 m2).

RESULTS

Subjects with NA-DKD showed a higher PWV (11.83 ± 3.74 m/s vs. 10.24 ± 2.67 m/s, P = 0.045), RRI (0.76 ± 0.11 vs. 0.71 ± 0.09, P = 0.04), and prevalence of carotid atherosclerotic plaque (59% vs. 31%, P = 0.009) compared with controls. These characteristics were similar to those of subjects with AL-DKD, whereas the profile of A-DKD subjects was closer to controls. After multiple regression analyses, we found that RRI, that is in turn influenced by eGFR (β = - 0.01, P = 0.01), was one of the major determinants of PWV (β = 9.4, P = 0.02). Urinary TreFoil Factor 3, a marker of tubular damage, was higher in NA-DKD subjects vs. controls (1533.14 ± 878.31 ng/mL vs. 1253.84 ± 682.17 ng/mL, P = 0.047). Furthermore, after multiple regression analyses, we found that urinary osteopontin was independently associated with PWV (β = 2.6, P = 0.049) and RRI (β = 0.09, P = 0.006).

CONCLUSIONS

Our data showed a worse cardiovascular and renal injury profile in NA-DKD subjects. This finding emphasizes the central role of eGFR in the definition of cardiovascular risk profile of diabetic subjects together with albuminuria.

Progression of diabetic nephropathy and vitamin D serum levels: A pooled analysis of 7722 patients

BACKGROUND AND AIM

Low serum Vitamin D levels have been associated with diabetic nephropathy (DN). Our study aimed to analyse the serum levels of vitamin D in patients suffering from DN and the subsequent changes in serum vitamin D levels as the disease progresses.

METHODS

PubMed, Embase, SCOPUS and Web of Science were searched using keywords such as '25 hydroxyvitamin D' and 'diabetic nephropathy'. We included observational studies that reported the association between the serum 25 hydroxy vitamin D levels and diabetic nephropathy without restriction to age, gender, and location. R Version 4.1.2 was used to perform the meta-analysis. The continuous outcomes were represented as mean difference (MD) and standard deviation (SD) and dichotomous outcomes as risk ratios (RR) with their 95% confidence interval (CI).

RESULTS

Twenty-three studies were included in our analysis with 7722 patients. Our analysis revealed that vitamin D was significantly lower in diabetic patients with nephropathy than those without nephropathy (MD: -4.32, 95% CI: 7.91-0.74, p-value = .0228). On comparing diabetic patients suffering from normoalbuminuria, microalbuminuria, or macroalbuminuria, we found a significant difference in serum vitamin D levels across different groups. Normoalbuminuria versus microalbuminuria showed a MD of -1.69 (95% CI: -2.28 to -1.10, p-value = .0002), while microalbuminuria versus macroalbuminuria showed a MD of (3.75, 95% CI: 1.43-6.06, p-value = .0058), proving that serum vitamin D levels keep declining as the disease progresses. Notwithstanding, we detected an insignificant association between Grade 4 and Grade 5 DN (MD: 2.29, 95% CI: -2.69-7.28, p-value = .1862).

CONCLUSION

Serum Vitamin D levels are lower among DN patients and keep declining as the disease progresses, suggesting its potential benefit as a prognostic marker. However, on reaching the macroalbuminuria stage (Grades 4 and 5), vitamin D is no longer a discriminating factor.

Expression of TNFR1, VEGFA, CD147 and MCT1 as early biomarkers of diabetes complications and the impact of aging on this profile

Hyperglycemia leads to microvascular lesions in various tissues. In diabetic nephropathy-DN, alterations in usual markers reflect an already installed disease. The study of new biomarkers for the early detection of diabetic complications can bring new prevention perspectives. Rats were divided into diabetic adult-DMA-or elderly-DME and control sham adult-CSA-or control sham elderly-CSE. Blood and urine samples were collected for biochemical analysis. Bulbar region, cardiac, hepatic and renal tissues were collected for target gene expression studies. As result, DMA showed decreased TNFR1, MCT1 and CD147 expression in the bulbar region, TNFR1 in the heart, VEGFA and CD147 in the kidney and TNFR1 in blood. Positive correlations were found between TNFR1 and MCT1 in the bulbar region and HbA1c and plasma creatinine, respectively. DME showed positive correlation in the bulbar region between TNFR1 and glycemia, in addition to negative correlations between CD147 in the heart versus glycemia and urea. We concluded that the initial hyperglycemic stimulus already promotes changes in the expression of genes involved in the inflammatory and metabolic pathways, and aging alters this profile. These changes prior to the onset of diseases such as DN, show that they have potential for early biomarkers studies.

Clinical and Translational Imaging and Sensing of Diabetic Microangiopathy: A Narrative Review

Microvascular changes in diabetes affect the function of several critical organs, such as the kidneys, heart, brain, eye, and skin, among others. The possibility of detecting such changes early enough in order to take appropriate actions renders the development of appropriate tools and techniques an imperative need. To this end, several sensing and imaging techniques have been developed or employed in the assessment of microangiopathy in patients with diabetes. Herein, we present such techniques; we provide insights into their principles of operation while discussing the characteristics that make them appropriate for such use. Finally, apart from already established techniques, we present novel ones with great translational potential, such as optoacoustic technologies, which are expected to enter clinical practice in the foreseeable future.

The Bidirectional Link Between Diabetes and Kidney Disease: Mechanisms and Management

The complex and mutually influential connection between diabetes mellitus and chronic kidney disease (CKD) is a significant focal point in the current healthcare landscape. Diabetes, a medical condition characterized by elevated blood glucose levels resulting from impaired insulin action or secretion, has become a significant global epidemic. It poses considerable challenges to healthcare systems and affects millions of individuals worldwide. Concurrently, CKD, characterized by the gradual decline of kidney function, has become a persistent health challenge. This narrative review explores the complex relationship between these two conditions, shedding light on their significant implications for public health, clinical practice, and biomedical research. The correlation between diabetes and kidney disease is not merely coincidental. Diabetes is recognized as a significant risk factor for CKD, as individuals with diabetes are considerably more vulnerable to developing renal complications. Diabetic nephropathy, a distinct type of kidney disease closely associated with diabetes, is a significant factor in developing end-stage renal disease. It is imperative to implement efficient diabetes management strategies to regulate blood sugar levels and prevent potential kidney damage. On the other hand, kidney disease may contribute to the development of diabetes. The kidneys regulate glucose levels by filtering the blood and selectively reabsorbing glucose as necessary. In compromised kidney function, such as CKD, impaired glucose metabolism can give rise to insulin resistance and diabetes. As a result, the management of kidney disease plays a dual role in both preserving renal function and preventing diabetes in individuals who are at risk. The coexistence of diabetes and kidney disease in a patient presents complex clinical challenges. Achieving effective management requires a meticulous balance between glycemic control and preservation of renal function. Failing to maintain this delicate equilibrium can lead to cardiovascular complications and subsequent hospitalizations. This comprehensive narrative review aims to thoroughly examine the pathophysiological mechanisms that connect diabetes and kidney disease. It will provide insights into the clinical manifestations and diagnostic methods, explore various approaches to managing the condition, discuss the crucial role of nutrition, delve into pharmacological interventions, emphasize the importance of patient education and self-care, and shed light on emerging research areas. In addition to impacting individual health outcomes, this reciprocal relationship has significant implications for healthcare systems, socioeconomic landscapes, and public health policy. Comprehending this complex interaction is crucial for making well-informed clinical judgments, improving patient care, and developing a more efficient public health approach to address the interconnected issues of diabetes and kidney disease.

Evaluation of Neutrophil/Lymphocyte Ratio, Low-Density Lipoprotein/Albumin Ratio, and Red Cell Distribution Width/Albumin Ratio in the Estimation of Proteinuria in Uncontrolled Diabetic Patients

Introduction Diabetic nephropathy associated with end-stage renal disease (ESRD) is a significant public health problem due to its high morbidity and mortality. We aimed to improve the estimation of proteinuria in diabetic patients and potentially enhance risk stratification and clinical management strategies with the assessment of the correlation of the neutrophil/lymphocyte ratio (NLR), low-density lipoprotein/albumin ratio (LAR), and red cell distribution width/albumin ratio (RAR) with the proteinuria in the uncontrolled diabetes patient population. Methods This was a retrospective study including 327 patients with uncontrolled diabetes (HbA1c > 10%) seen in an outpatient clinic. The study enrolled patients over 18 years old, excluding those with active infections, malignancies, immunodeficiency, hematological diseases, pregnancy, breastfeeding, or type I diabetes. Patients using specific drugs affecting proteinuria or lipid levels were also excluded. Data from patients were retrospectively obtained, including gender, age, blood parameters, glucose, creatinine, albumin, cholesterol, triglyceride, and HbA1c levels, as well as spot urine protein and creatinine levels. Proteinuria was assessed using a spot urine protein/creatinine ratio (>0.30 indicated proteinuria). Patients were divided into two groups: group 1 (non-proteinuric with uncontrolled diabetes) and group 2 (proteinuric with uncontrolled diabetes). Demographics, laboratory results, and LAR, NLR, and RAR values were compared between the groups with univariate and multivariate analyses. All statistical analyses were performed using IBM SPSS Statistics for Windows software. For the statistical significance level, p<0.05 was accepted as meaningful. Results Among 327 patients with uncontrolled diabetes, 33.03% were proteinuric. Patients with proteinuria were significantly older (median age 65 vs. 61 years) and had higher NLR and RAR values. There were no significant differences observed in terms of LAR values between groups. Serum albumin levels were lower and urea levels were higher in the proteinuric group. A multivariate analysis was done to identify variables for the prediction of proteinuria. NLR and RAR were found to be independent predictors of proteinuria even after adjusting for potential confounders in the multivariate analysis. The model achieved a 71.9% correct classification rate. An NLR cutoff of 1.93 increased the likelihood of proteinuria 1.93-fold, while a RAR cutoff of 3.30 increased the likelihood 1.63-fold. Conclusions We found that the LAR ratio cannot be used to predict proteinuria in patients with HbA1C levels above 10, but the NLR and RAR ratios can guide the clinician regarding proteinuria and potentially enhance risk stratification and clinical management strategies before a detailed workup.

Identification of a New RNA and Protein Integrated Biomarker Panel Associated with Kidney Function Impairment in DKD: Translational Implications

Diabetic kidney disease (DKD) is a complication that strongly increases the risk of end-stage kidney disease and cardiovascular events. The identification of novel, highly sensitive, and specific early biomarkers to identify DKD patients and predict kidney function decline is a pivotal aim of translational medicine. In a previous study, after a high-throughput approach, we identified in 69 diabetic patients 5 serum mitochondrial RNAs (MT-ATP6, MT-ATP8, MT-COX3, MT-ND1, and MT-RNR1) progressively downregulated with increasing eGFR stages. Here, we analyzed the protein serum concentrations of three well-validated biomarkers: TNFRI, TNFRII, and KIM-1. The protein biomarkers were gradually upregulated from G1 to G2 and G3 patients. All protein biomarkers correlated with creatinine, eGFR, and BUN. Performing multilogistic analyses, we found that, with respect to single protein biomarkers, the combination between (I) TNFRI or KIM-1 with each RNA transcript and (II) TNFRII with MT-ATP8, MT-ATP6, MT-COX-3, and MT-ND1 determined an outstanding improvement of the diagnostic performance of G3 versus G2 patient identification, reaching values in most cases above 0.9 or even equal to 1. The improvement of AUC values was also evaluated in normoalbuminuric or microalbuminuric patients considered separately. This study proposes a novel, promising multikind marker panel associated with kidney impairment in DKD.

Early diabetic kidney disease: Focus on the glycocalyx

The incidence of diabetic kidney disease (DKD) is sharply increasing worldwide. Microalbuminuria is the primary clinical marker used to identify DKD, and its initiating step in diabetes is glomerular endothelial cell dysfunction, particularly glycocalyx impairment. The glycocalyx found on the surface of glomerular endothelial cells, is a dynamic hydrated layer structure composed of pro-teoglycans, glycoproteins, and some adsorbed soluble components. It reinforces the negative charge barrier, transduces the shear stress, and mediates the interaction of blood corpuscles and podocytes with endothelial cells. In the high-glucose environment of diabetes, excessive reactive oxygen species and proinflammatory cytokines can damage the endothelial glycocalyx (EG) both directly and indirectly, which induces the production of microalbuminuria. Further research is required to elucidate the role of the podocyte glycocalyx, which may, together with endothelial cells, form a line of defense against albumin filtration. Interestingly, recent research has confirmed that the negative charge barrier function of the glycocalyx found in the glomerular basement membrane and its repulsion effect on albumin is limited. Therefore, to improve the early diagnosis and treatment of DKD, the potential mechanisms of EG degradation must be analyzed and more responsive and controllable targets must be explored. The content of this review will provide insights for future research.

Amino acid analysis as a method of discovering biomarkers for diagnosis of diabetes and its complications

Diabetes mellitus (DM) is a severe chronic diseases with a global prevalence of 9%, leading to poor health and high health care costs, and is a direct cause of millions of deaths each year. The rising epidemic of diabetes and its complications, such as retinal and peripheral nerve disease, is a huge burden globally. A better understanding of the molecular pathways involved in the development and progression of diabetes and its complications can facilitate individualized prevention and treatment. High diabetes mellitus incidence rate is caused mainly by lack of non-invasive and reliable methods for early diagnosis, such as plasma biomarkers. The incidence of diabetes and its complications in the world still grows so it is crucial to develop a new, faster, high specificity and more sensitive diagnostic technologies. With the advancement of analytical techniques, metabolomics can identify and quantify multiple biomarkers simultaneously in a high-throughput manner, and effective biomarkers can greatly improve the efficiency of diabetes and its complications. By providing information on potential metabolic pathways, metabolomics can further define the mechanisms underlying the progression of diabetes and its complications, help identify potential therapeutic targets, and improve the prevention and management of T2D and its complications. The application of amino acid metabolomics in epidemiological studies has identified new biomarkers of diabetes mellitus (DM) and its complications, such as branched-chain amino acids, phenylalanine and arginine metabolites. This study focused on the analysis of metabolic amino acid profiling as a method for identifying biomarkers for the detection and screening of diabetes and its complications. The results presented are all from recent studies, and in all cases analyzed, there were significant changes in the amino acid profile of patients in the experimental group compared to the control group. This study demonstrates the potential of amino acid profiles as a detection method for diabetes and its complications.

Novel Biomarkers of Diabetic Kidney Disease

Diabetic kidney disease (DKD) is a highly prevalent condition worldwide. It represents one of the most common complications arising from diabetes mellitus (DM) and is the leading cause of end-stage kidney disease (ESKD). Its development involves three fundamental components: the hemodynamic, metabolic, and inflammatory axes. Clinically, persistent albuminuria in association with a progressive decline in glomerular filtration rate (GFR) defines this disease. However, as these alterations are not specific to DKD, there is a need to discuss novel biomarkers arising from its pathogenesis which may aid in the diagnosis, follow-up, therapeutic response, and prognosis of the disease.

Therapeutic potential of a novel peripherally restricted CB1R inverse agonist on the progression of diabetic nephropathy

Objective

This study assessed the efficacy of INV-202, a novel peripherally restricted cannabinoid type-1 receptor (CB1R) inverse agonist, in a streptozotocin-induced type-1 diabetes nephropathy mouse model.

Methods

Diabetes was induced in 8-week-old C57BL6/J male mice via intraperitoneal injection of streptozotocin (45 mg/kg/day for 5 days); nondiabetic controls received citrate buffer. Diabetic mice were randomized to 3 groups based on blood glucose, polyuria, and albuminuria, and administered daily oral doses for 28-days of INV-202 at 0.3 or 3 mg/kg or vehicle.

Results

INV-202 did not affect body weight but decreased kidney weight compared with the vehicle group. While polyuria was unaffected by INV-202 treatment, urinary urea (control 30.77 ± 14.93; vehicle 189.81 ± 31.49; INV-202 (0.3 mg/kg) 127.76 ± 20; INV-202 (3 mg/kg) 93.70 ± 24.97 mg/24h) and albumin (control 3.06 ± 0.38; vehicle 850.08 ± 170.50; INV-202 (0.3 mg/kg) 290.65 ± 88.70; INV-202 (3 mg/kg) 111.29 ± 33.47 µg/24h) excretion both decreased compared with vehicle-treated diabetic mice. Compared with the vehicle group, there was a significant improvement in the urinary albumin to creatinine ratio across INV-202 groups. Regardless of the dose, INV-202 significantly reduced angiotensin II excretion in diabetic mice. The treatment also decreased Agtr1a renal expression in a dose-dependent manner. Compared with nondiabetic controls, the glomerular filtration rate was increased in the vehicle group and significantly decreased by INV-202 at 3 mg/kg. While the vehicle group showed a significant loss in the mean number of podocytes per glomerulus, INV-202 treatment limited podocyte loss in a dose-dependent manner. Moreover, in both INV-202 groups, expression of genes coding for podocyte structural proteins nephrin (Nphs1), podocin (Nphs2), and podocalyxin (Pdxl) were restored to levels similar to nondiabetic controls. INV-202 partially limited the proximal tubular epithelial cell (PTEC) hyperplasia and normalized genetic markers for PTEC lesions. INV-202 also reduced expression of genes contributing to oxidative stress (Nox2, Nox4, and P47phox) and inflammation (Tnf). In addition, diabetes-induced renal fibrosis was significantly reduced by INV-202.

Conclusions

INV-202 reduced glomerular injury, preserved podocyte structure and function, reduced injury to PTECs, and ultimately reduced renal fibrosis in a streptozotocin-induced diabetic nephropathy mouse model. These results suggest that INV-202 may represent a new therapeutic option in the treatment of diabetic kidney disease.

Urinary Markers of Tubular Injury and Renal Fibrosis in Patients with Type 2 Diabetes and Different Phenotypes of Chronic Kidney Disease

This study assessed the urinary excretion of markers and mediators of tubular injury and renal fibrosis in patients with type 2 diabetes (T2D) and non-albuminuric and albuminuric patterns of chronic kidney disease (CKD). One hundred and forty patients with long-term T2D and different patterns of CKD and twenty non-diabetic individuals were included. Urinary retinol-binding protein 4 (RBP-4), glutathione-S-transferase α₁ and π (GST-α₁ and GST-π), transforming growth factor β (TGF-β), type I and type IV collagen (Col1 and Col4), bone morphogenic protein 7 (BMP-7), and hepatocyte growth factor (HGF) were assessed by ELISA. Patients with T2D demonstrated increased urinary excretion of RBP-4, GST-π, Col4, BMP-7, and HGF (all p < 0.05 vs. control). The excretion of RBP-4, GST-π, Col1, and Col4 was increased in patients with elevated albumin-to-creatinine ratio (UACR; all p < 0.05 vs. control), while BMP-7 and HGF were increased innormoalbuminuric patients also (p < 0.05). Urinary RBP-4, GST-α₁, Col1, Col4, and HGF correlated positively with UACR; meanwhile, no correlations with glomerular filtration rate were found. The results demonstrate that elevated urinary excretions of the markers of tubular injury (RBP-4, GST-π) and renal fibrosis (Col1, Col4), as well as HGF, an antifibrotic regulator, are associated with the albuminuric pattern of CKD in subjects with T2D.

Differences and Clinical Significance of Serum 25-Hydroxyvitamin D3 and Vasohibin-1 (VASH-1) Levels in Patients with Diabetic Nephropathy and Different Renal Injuries

Objective

We investigate the relationship between the changes of serum 25-hydroxyvitamin D3 (25(OH)D3) and vasohibin-1 (VASH-1) and renal function injury in patients with type 2 diabetic nephropathy.

Methods

In this study, 143 patients with diabetic nephropathy (DN) were selected as DN group, and 80 patients with type 2 diabetes mellitus were selected as T2DM group. The serum 25 (OH) D3, VASH-1, blood glucose index, inflammation index and renal function index were compared between the two groups. According to the urinary microalbumin/creatinine ratio (UACR), the DN group was divided into microalbuminuria group (UACR range≥30.0mg/g and <300.0mg/g) and macroalbuminuria group (UACR≥300.0mg/g) for stratified comparison. The correlation between 25-hydroxyvitamin D3, VASH-1 and inflammation index and renal function index was analyzed by simple linear correlation analysis.

Results

The level of 25 (OH) D3 in DN group was significantly lower than that in T2DM group (P<0.05). The levels of VASH-1, CysC, BUN, Scr, 24h urine protein, serum CRP, TGF-β1, TNF-α and IL-6 in DN group were higher than those in T2DM group (P<0.05). The level of 25 (OH) D3 in DN patients with massive proteinuria was significantly lower than that in DN patients with microalbuminuria. The level of VASH-1 in DN patients with massive proteinuria was higher than that in DN patients with microalbuminuria (P<0.05). There was a negative correlation between 25 (OH) D3 and CysC, BUN, Scr, 24h urine protein, CRP, TGF-β1, TNF-α, IL-6 in patients with DN (P<0.05). VASH-1 was positively correlated with Scr, 24h urinary protein, CRP, TGF-β1, TNF-α and IL-6 in patients with DN (P<0.05).

Conclusion

The level of serum 25 (OH) D3 in DN patients was considerably decreased, and the level of VASH-1 was increased, which was related to the degree of renal function injury and inflammatory response.

Molecular Pathways of Diabetic Kidney Disease Inferred from Proteomics

Diabetic kidney disease (DKD) affects an estimated 20-40% of type 2 diabetes patients and is among the most prevalent microvascular complications in this patient population, contributing to high morbidity and mortality rates. Currently, changes in albuminuria status are thought to be a primary indicator of the onset or progression of DKD, yet progressive nephropathy and renal impairment can occur in certain diabetic individuals who exhibit normal urinary albumin levels, emphasizing the lack of sensitivity and specificity associated with the use of albuminuria as a biomarker for detecting diabetic kidney disease and predicting DKD risk. According to the study, a non-invasive method for early detection or prediction of DKD may involve combining proteomic analytical techniques such second generation sequencing, mass spectrometry, two-dimensional gel electrophoresis, and other advanced system biology algorithms. Another category of proteins of relevance may now be provided by renal tissue biomarkers. The establishment of reliable proteomic biomarkers of DKD represents a novel approach to improving the diagnosis, prognostic evaluation, and treatment of affected patients. In the present review, a series of protein biomarkers that have been characterized to date are discussed, offering a theoretical foundation for future efforts to aid patients suffering from this debilitating microvascular complication.

Aggravated renal fibrosis is positively associated with the activation of HMGB1-TLR2/4 signaling in STZ-induced diabetic mice

Diabetic kidney dysfunction is closely associated with renal fibrosis. Although the suppression of fibrosis is crucial to attenuate kidney damage, the underlying mechanisms remain poorly understood. In this study, renal injury in diabetic mice was induced by the intraperitoneal injection of streptozotocin (100 or 150 mg/kg) for 2 consecutive days. In the model mice, remarkable renal injury was observed, manifested by albuminuria, swelling of kidneys, and histopathological characteristics. The renal fibrosis was obviously displayed with high-intensity staining of fibrin, type IV collagen (Col IV), and fibronectin. The levels of Col IV and transforming growth factor-β1 were significantly increased in diabetic mice kidneys. The aggravated fibrotic process was associated with the overexpression of HMGB1, TLR2/4, and p-NF-κB. Furthermore, a high expression of F4/80 and CD14 indicated that macrophage infiltration was involved in perpetuating inflammation and subsequent fibrosis in the kidneys of diabetic mice. The results demonstrate that the severity of renal fibrosis is positively associated with the activation of HMGB1/TLR2/4 signaling in diabetes.

Metabolomic Signature of Diabetic Kidney Disease in Cerebrospinal Fluid and Plasma of Patients with Type 2 Diabetes Using Liquid Chromatography-Mass Spectrometry

Diabetic kidney disease (DKD) is the major cause of end stage renal disease in patients with type 2 diabetes mellitus (T2DM). The subtle metabolic changes in plasma and cerebrospinal fluid (CSF) might precede the development of DKD by years. In this longitudinal study, CSF and plasma samples were collected from 28 patients with T2DM and 25 controls, during spinal anesthesia for elective surgery in 2017. These samples were analyzed using liquid chromatography-mass spectrometry (LC-MS) in 2017, and the results were correlated with current DKD in 2017, and the development of new-onset DKD, in 2021. Comparing patients with T2DM having new-onset DKD with those without DKD, revealed significantly increased CSF tryptophan and plasma uric acid levels, whereas phosphatidylcholine 36:4 was lower. The altered metabolites in the current DKD cases were uric acid and paraxanthine in the CSF and uric acid, L-acetylcarnitine, bilirubin, and phosphatidylethanolamine 38:4 in the plasma. These metabolic alterations suggest the defective mitochondrial fatty acid oxidation and purine and phospholipid metabolism in patients with DKD. A correlation analysis found CSF uric acid had an independent positive association with the urine albumin-to-creatinine ratio. In conclusion, these identified CSF and plasma biomarkers of DKD in diabetic patients, might be valuable for monitoring the DKD progression.

Mitochondrial RNAs as Potential Biomarkers of Functional Impairment in Diabetic Kidney Disease

Type 2 diabetes and renal damage are strictly linked. The progressive increase in T2D incidence has stimulated the interest in novel biomarkers to improve the diagnostic performance of the commonly utilized markers such as albuminuria and eGFR. Through microarray method, we analyzed the entire transcriptome expressed in 12 serum samples of diabetic patients, six without DKD and six with DKD; the downregulation of the most dysregulated transcripts was validated in a wider cohort of 69 patients by qPCRs. We identified a total of 33 downregulated transcripts. The downregulation of four mitochondrial messenger RNAs (MT-ATP6, MT-ATP8, MT-COX3, MT-ND1) and other two transcripts (seysnoy, skerdo) was validated in patients with eGFR stage G3 versus G2 and G1. The four messenger RNAs correlated with creatinine and eGFR stages, while seysnoy and skerdo were associated with white blood cell values. All transcripts correlated also with Blood Urea Nitrogen. The four mitochondrial messenger RNAs had a high diagnostic performance in G3 versus G2 discrimination, with AUC values above 0.8. The most performant transcript was MT-ATP6, with an AUC of 0.846; sensitivity = 90%, specificity = 76%, p-value = 7.8 × 10⁻⁵. This study led to the identification of a specific molecular signature of DKD, proposing the dosage of RNAs, especially mitochondrial RNAs, as noninvasive biomarkers of diabetes complication.

Serum chromogranin A correlated with albuminuria in diabetic patients and is associated with early diabetic nephropathy

BACKGROUND

The kidney is the main site for the removal of chromogranin A (CgA). Previous studies have found that patients with renal impairment displayed elevated concentrations of CgA in plasma and that CgA concentrations reflect a deterioration of renal function. In this study, we aimed to estimate serum CgA levels and to evaluate the role of serum CgA in the early diagnosis of diabetic nephropathy (DN).

METHODS

A total of 219 patients with type 2 diabetes mellitus (T2DM) were included in this cross-sectional study. These patients were classified into normoalbuminuria (n = 121), microalbuminuria (n = 73), or macroalbuminuria (n = 25) groups based on their urine albumin to creatinine ratios (UACRs). The degree of DN is reflected by UACR. A control group consisted of 45 healthy subjects. The serum CgA levels were measured by ELISA, and other key parameters were assayed.

RESULTS

Serum CgA levels were higher in patients with T2DM than in control subjects, and a statistically significant difference among the studied subgroups regarding CgA was found (P < 0.05). The levels of serum CgA increased gradually with the degree of DN (P < 0.001). Serum CgA levels showed a moderate-intensity positive correlation with UACRs (P < 0.001). A cutoff level of 3.46 ng/ml CgA showed 69.86% sensitivity and 66.12% specificity to detect DN in the early stage.

CONCLUSION

The levels of serum CgA increased gradually with the degree of DN and can be used as a biomarker in the early detection of DN.

MicroRNA 146a is associated with diabetic complications in type 1 diabetic patients from the EURODIAB PCS

Background

MicroRNA-146a-5p (miR-146a-5p) is a key regulator of inflammatory processes. Expression of miR-146a-5p is altered in target organs of diabetic complications and deficiency of miR-146a-5p has been implicated in their pathogenesis. We investigated if serum miR-146a-5p levels were independently associated with micro/macrovascular complications of type 1 diabetes (DM1).

Methods

A nested case–control study from the EURODIAB PCS of 447 DM1 patients was performed. Cases (n = 294) had one or more complications of diabetes, whereas controls (n = 153) did not have any complication. Total RNA was isolated from all subjects and miR-146a-5p levels measured by qPCR. Both the endogenous controls U6 snRNA and the spike (Cel-miR-39) were used to normalize the results. Logistic regression analysis was carried out to investigate the association of miR-146a-5p with diabetes complications.

Results

MiR-146a-5p levels were significantly lower in cases [1.15 (0.32–3.34)] compared to controls [1.74 (0.44–6.74) P = 0.039]. Logistic regression analysis showed that levels of miR-146a-5p in the upper quartile were inversely associated with reduced odds ratio (OR) of all complications (OR 0.34 [95% CI 0.14–0.76]) and particularly with cardiovascular diseases (CVD) (OR 0.31 [95% CI 0.11–0.84]) and diabetic retinopathy (OR 0.40 [95% CI 0.16–0.99]), independently of age, sex, diabetes duration, A1c, hypertension, AER, eGFR, NT-proBNP, and TNF-α.

Conclusions

In this large cohort of DM1 patients, we reported an inverse and independent association of miR-146a-5p with diabetes chronic complications and in particular with CVD and retinopathy, suggesting that miR-146a-5p may be a novel candidate biomarker of DM1 complications.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-03142-4.

Re-thinking diabetic nephropathy: Microalbuminuria is just a piece of the diagnostic puzzle

The decline of the estimated glomerular filtration rate (eGFR) and the presence of albuminuria are the typical hallmarks of kidney disease arising as one of the most frequent diabetic complications over a long period of time, generally known as diabetic nephropathy or diabetes kidney disease (DKD). However, a decline in the renal function may occur in diabetic patients for other reasons unrelated to glycemic control, and this condition is known as non-diabetic kidney disease (NDKD). In this opinion paper we will review these conditions, and we outline the importance of other investigations, such as kidney biopsy and the measurement of novel biomarkers, in order to identify the disease progression early, and to allow a timely intervention. We will also focus on the actual limits of the quantitative measurements of albumin in urine, especially with regards to potential interferences due to the treatment of patients with statins.

Identification of Novel Biomarker for Early Detection of Diabetic Nephropathy

Diabetic nephropathy (DN) is one of the most common complications of diabetes mellitus. After development of DN, patients will progress to end-stage renal disease, which is associated with high morbidity and mortality. Here, we developed early-stage diagnostic biomarkers to detect DN as a strategy for DN intervention. For the DN model, Zucker diabetic fatty rats were used for DN phenotyping. The results revealed that DN rats showed significantly increased blood glucose, blood urea nitrogen (BUN), and serum creatinine levels, accompanied by severe kidney injury, fibrosis and microstructural changes. In addition, DN rats showed significantly increased urinary excretion of kidney injury molecule-1 (KIM-1) and neutrophil gelatinase-associated lipocalin (NGAL). Transcriptome analysis revealed that new DN biomarkers, such as complementary component 4b (C4b), complementary factor D (CFD), C-X-C motif chemokine receptor 6 (CXCR6), and leukemia inhibitory factor (LIF) were identified. Furthermore, they were found in the urine of patients with DN. Since these biomarkers were detected in the urine and kidney of DN rats and urine of diabetic patients, the selected markers could be used as early diagnosis biomarkers for chronic diabetic nephropathy.