Associations of urinary epidermal growth factor and monocyte chemotactic protein-1 with kidney involvement in patients with diabetic kidney disease

Simultaneous detection of multiple urinary biomarkers in patients with early-stage diabetic kidney disease using Luminex liquid suspension chip technology

Background

Several urinary biomarkers have good diagnostic value for diabetic kidney disease (DKD); however, the predictive value is limited with the use of single biomarkers. We investigated the clinical value of Luminex liquid suspension chip detection of several urinary biomarkers simultaneously.

Methods

The study included 737 patients: 585 with diabetes mellitus (DM) and 152 with DKD. Propensity score matching (PSM) of demographic and medical characteristics identified a subset of 78 patients (DM = 39, DKD = 39). Two Luminex liquid suspension chips were used to detect 11 urinary biomarkers according to their molecular weight and concentration. The biomarkers, including cystatin C (CysC), nephrin, epidermal growth factor (EGF), kidney injury molecule-1 (KIM-1), retinol-binding protein4 (RBP4), α1-microglobulin (α1-MG), β2-microglobulin (β2-MG), vitamin D binding protein (VDBP), tissue inhibitor of metalloproteinases-1 (TIMP-1), tumor necrosis factor receptor-1 (TNFR-1), and tumor necrosis factor receptor-2 (TNFR-2) were compared in the DM and DKD groups. The diagnostic values of single biomarkers and various biomarker combinations for early diagnosis of DKD were assessed using receiver operating characteristic (ROC) curve analysis.

Results

Urinary levels of VDBP, RBP4, and KIM-1 were markedly higher in the DKD group than in the DM group (p < 0.05), whereas the TIMP-1, TNFR-1, TNFR-2, α1-MG, β2-MG, CysC, nephrin, and EGF levels were not significantly different between the groups. RBP4, KIM-1, TNFR-2, and VDBP reached p < 0.01 in univariate analysis and were entered into the final analysis. VDBP had the highest AUC (0.780, p < 0.01), followed by RBP4 (0.711, p < 0.01), KIM-1 (0.640, p = 0.044), and TNFR-2 (0.615, p = 0.081). However, a combination of these four urinary biomarkers had the highest AUC (0.812), with a sensitivity of 0.742 and a specificity of 0.760.

Conclusions

The urinary levels of VDBP, RBP4, KIM-1, and TNFR-2 can be detected simultaneously using Luminex liquid suspension chip technology. The combination of these biomarkers, which reflect different mechanisms of kidney damage, had the highest diagnostic value for DKD. However, this finding should be explored further to understand the synergistic effects of these biomarkers.

Longitudinal Trajectories of Biomarkers of Kidney Tubular Function in Type 1 Diabetes

Introduction

Tubular biomarkers may shed insight into progression of kidney tubulointerstitial pathology complementary to traditional measures of glomerular function and damage.

Methods

We examined trajectories of tubular biomarkers in the Diabetes Control and Complications Trial and the Epidemiology of Diabetes Interventions and Complications Study (DCCT/EDIC Study) of type 1 diabetes (T1D). Biomarkers were measured in a subset of 220 participants across 7 time points over 26 years. Measurements included the following: kidney injury molecule 1 (KIM-1), soluble tumor necrosis factor 1 (sTNFR1) in serum or plasma, epidermal growth factor (EGF), monocyte chemoattractant protein-1 (MCP1) in timed urine, and a composite tubular secretion score. We described biomarker trajectories and examined how these were affected by intensive glucose-lowering therapy and glycemia.

Results

At baseline, participants had a mean age of 28 years, 45% were women, and 50% were assigned to intensive glucose-lowering therapy. The mean estimated glomerular filtration rate (eGFR) was 125 ml/min per 1.73 m2 and 90% of participants had a urinary albumin excretion rate (AER) <30 mg/24h. Mean changes in biomarkers over time (percent/decade) were: KIM-1: 27.3% (95% confidence interval [CI]: 21.4-33.5), sTNFR1: 16.9% (14.5-19.3), MCP1: 18.4% (8.9-28.8), EGF: -13.5% (-16.7 to -10.1), EGF-MCP1 ratio: -26.9% (-32.2 to -21.3), and tubular secretion score -0.9% (-1.8 to 0.0), versus -12.0% (CI: -12.9 to -11.1) for eGFR and 10.9% (2.5-20.1) for AER. Intensive versus conventional glucose-lowering therapy was associated with slower increase in sTNFR1 (relative difference in change: 0.94 [0.90-0.98]). Higher HbA1c was associated with faster increases in sTNFR1 (relative difference in change: 1.06 per 1% higher HbA1c [1.05-1.08]) and KIM-1 (1.09 [1.05-1.14]).

Conclusion

Among participants with T1D and normal eGFR at baseline, kidney tubular biomarkers changed significantly over long-term follow-up. Hyperglycemia was associated with larger increases in serum or plasma sTNFR1 and KIM-1, when followed-up longitudinally.

Investigating EGF and PAG1 as necroptosis-related biomarkers for diabetic nephropathy: an in silico and in vitro validation study

The current study aims to understand the mechanisms behind regulated cell death (RCD) in diabetic nephropathy and identify related biomarkers through bioinformatics and experimental validation. Datasets of bulk and single-cell RNA sequencing were obtained from public databases and analyzed using gene set variation analysis (GSVA) with gene sets related to RCD, including autophagy, necroptosis, pyroptosis, apoptosis, and ferroptosis. RCD-related gene biomarkers were identified using weighted gene correlation network analysis (WGCNA). The results were verified through experiments with an independent cohort and in vitro experiments. The GSVA revealed higher necroptosis scores in diabetic nephropathy. Three necroptosis-related biomarkers, EGF, PAG1, and ZFP36, were identified and showed strong diagnostic ability for diabetic kidney disease. In vitro experiments showed high levels of necroptotic markers in HK-2 cells treated with high glucose. Bioinformatics and experimental validation have thus identified EGF and PAG1 as necroptosis-related biomarkers for diabetic nephropathy.

Intraindividual variations of urinary biomarkers in hospitalized children with glomerular diseases: a prospective observational study

This study aimed to assess the intraindividual variations of urinary biomarkers in hospitalized children with glomerular diseases. Hospitalized children with glomerular diseases participated in the study. For each patient, an overnight (9:00 p.m.-7:00 a.m.) urine was collected, followed by a 24-h urine (classified into four distinct periods: morning 7:00 a.m.-12:00 p.m., afternoon 12:00 p.m.-4:00 p.m., evening 4:00 p.m.-9:00 p.m., and overnight 9:00 p.m.-7:00 a.m.). The concentrations of protein, albumin, N-acetyl-beta-D-glucosaminidase, and epidermal growth factor (EGF) were measured and normalized by three correction factors (creatinine, osmolality, or specific gravity, respectively). Additionally, the 2nd overnight urine sample was grouped into different aliquots according to centrifugation, additives, storage temperature, or delayed processing. Twenty (14 boys, 6 girls) children were enrolled, with an average age of 11.3 years. Among the three correction factors, creatinine-normalized biomarkers provided the best agreements among different periods over 24 h. There were significant diurnal variations during 24 h in the concentrations of urinary protein, albumin, N-acetyl-beta-D-glucosaminidase, and EGF (p = 0.001, p = 0.003, p = 0.003, and p = 0.003, respectively). Evening urine overestimated 24-h urinary protein and albumin, while overnight urine underestimated 24-h urinary albumin. Urinary EGF showed low variability within a day or between the 2 days (coefficients of variation 10.2% and 10.6%, respectively) and excellent agreements (intraclass correlation coefficients > 0.9) with 24-h urinary concentration. Furthermore, urinary EGF was not affected by centrifugation, additives, storage temperature, or delayed processing of urine samples (all p > 0.05).  Conclusion: Given the diurnal variations of urinary biomarkers, urine samples should be collected during the same time period in clinical practice if possible. The results also extend the evidence for urinary EGF as a relatively stable biomarker applied in the future clinical practice. What is Known: • Urinary biomarkers have been widely used or discussed in making diagnoses and therapy regimens and estimating the prognosis of pediatric glomerular diseases. It remains unclear whether their levels would be affected by the time of sample collection, processing methods, and storage conditions in hospitalized children with glomerular diseases. What is New: • The levels of both commonly used biomarkers and novel biomarkers exhibited diurnal variations in hospitalized children with glomerular diseases. • Our results extend the evidence for urinary EGF as a relatively stable biomarker applied in the future clinical practice.

The Michigan O'Brien Kidney Research Center: transforming translational kidney research through systems biology

Research on kidney diseases is being transformed by the rapid expansion and innovations in omics technologies. The analysis, integration, and interpretation of big data, however, have been an impediment to the growing interest in applying these technologies to understand kidney function and failure. Targeting this urgent need, the University of Michigan O'Brien Kidney Translational Core Center (MKTC) and its Administrative Core established the Applied Systems Biology Core. The Core provides need-based support for the global kidney community centered on enabling incorporation of systems biology approaches by creating web-based, user-friendly analytic and visualization tools, like Nephroseq and Nephrocell, guiding with experimental design, and processing, analysis, and integration of large data sets. The enrichment core supports systems biology education and dissemination through workshops, seminars, and individualized training sessions. Meanwhile, the Pilot and Feasibility Program of the MKTC provides pilot funding to both early-career and established investigators new to the field, to integrate a systems biology approach into their research projects. The relevance and value of the portfolio of training and services offered by MKTC are reflected in the expanding community of young investigators, collaborators, and users accessing resources and engaging in systems biology-based kidney research, thereby motivating MKTC to persevere in its mission to serve the kidney research community by enabling access to state-of-the-art data sets, tools, technologies, expertise, and learning opportunities for transformative basic, translational, and clinical studies that will usher in solutions to improve the lives of people impacted by kidney disease.

Urinary excretion of epidermal growth factor and rapid loss of kidney function

BACKGROUND

Lower urinary excretion of the kidney tubule-specific biomarker epidermal growth factor (uEGF) is associated with increased risk of renal function [glomerular filtration rate (GFR)] loss in diabetes and in patients with established chronic kidney disease (CKD). We investigated whether uEGF is associated with rapid GFR decline or incident CKD in the general population.

METHODS

Subjects without CKD or diabetes were recruited from the general population in Tromso, Norway [Renal Iohexol Clearance Survey (RENIS); N = 1249] and Groningen, the Netherlands [Prevention of REnal and Vascular END-stage disease (PREVEND); N = 4534], with a median follow-up of 5.6 and 7.4 years, respectively. GFR was measured by iohexol clearance in the RENIS and estimated using the CKD Epidemiology Collaboration creatinine-cystatin C equation in the PREVEND study. Rapid GFR decline was defined as an annual GFR loss >3.0 mL/min/1.73 m2 and in sensitivity analyses as subjects with the 10% steepest GFR slope within each cohort.

RESULTS

Lower baseline uEGF excretion was associated with rapid GFR loss in both cohorts {RENIS, odds ratio [OR] per 1 μg/mmol lower uEGF 1.42 [95% confidence interval (CI) 1.06-1.91], P = 0.02; PREVEND, OR 1.29 [95% CI 1.10-1.53], P < 0.01}, adjusted for baseline GFR, albumin:creatinine ratio and conventional CKD risk factors. Similar results were obtained using the outcome of the 10% steepest GFR slope in each cohort. Lower uEGF levels were associated with incident CKD in the combined analysis of both cohorts.

CONCLUSIONS

Lower uEGF levels are associated with increased risk of rapid GFR loss and incident CKD in the general population. This finding, together with previous findings in CKD and high-risk populations, supports that uEGF may serve as a broadly applicable biomarker representing the tubular component of the current glomerulus-centric clinical risk assessment system.

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

Diabetic kidney disease (DKD) is a leading cause of end-stage renal disease (ESRD). Although both albuminuria and glomerular filtration rate (GFR) are well-established diagnostic/prognostic biomarkers of DKD, they have important limitations. There is, thus, increasing quest to find novel biomarkers to identify the disease in an early stage and to improve risk stratification. In this review, we will outline the major pitfalls of currently available markers, describe promising novel biomarkers, and discuss their potential clinical relevance. In particular, we will focus on the importance of recent advancements in multi-omic technologies in the discovery of new DKD biomarkers. In addition, we will provide an update on new emerging approaches to explore renal function and structure, using functional tests and imaging.

Urinary EGF and MCP-1 and risk of CKD after cardiac surgery

BACKGROUND

Assessment of chronic kidney disease (CKD) risk after acute kidney injury (AKI) is based on limited markers primarily reflecting glomerular function. We evaluated markers of cell integrity (EGF) and inflammation (monocyte chemoattractant protein-1, MCP-1) for predicting long-term kidney outcomes after cardiac surgery.

METHODS

We measured EGF and MCP-1 in postoperative urine samples from 865 adults who underwent cardiac surgery at 2 sites in Canada and the United States and assessed EGF and MCP-1’s associations with the composite outcome of CKD incidence or progression. We used single-cell RNA-Seq (scRNA-Seq) of AKI patient biopsies to perform transcriptomic analysis of programs corregulated with the associated genes.

RESULTS

Over a median (IQR) follow-up of 5.8 (4.2–7.1) years, 266 (30.8%) patients developed the composite CKD outcome. Postoperatively, higher levels of urinary EGF were protective and higher levels of MCP-1 were associated with the composite CKD outcome (adjusted HR 0.83, 95% CI 0.73–0.95 and 1.10, 95% CI 1.00–1.21, respectively). Intrarenal scRNA-Seq transcriptomes in patients with AKI-defined cell populations revealed concordant changes in EGF and MCP-1 levels and underlying molecular processes associated with loss of EGF expression and gain of CCL2 (encoding MCP-1) expression.

CONCLUSION

Urinary EGF and MCP-1 were each independently associated with CKD after cardiac surgery. These markers may serve as noninvasive indicators of tubular damage, supported by tissue transcriptomes, and provide an opportunity for novel interventions in cardiac surgery.

TRIAL REGISTRATION

ClinicalTrials.gov NCT00774137.

FUNDING

The NIH funded the TRIBE-AKI Consortium and Kidney Precision Medicine Project. Yale O’Brien Kidney Center, American Heart Association, Patterson Trust Fund, Dr. Adam Linton Chair in Kidney Health Analytics, Canadian Institutes of Health Research, ICES, Ontario Ministry of Health and Long-Term Care, Academic Medical Organization of Southwestern Ontario, Schulich School of Medicine & Dentistry, Western University, Lawson Health Research Institute, Chan Zuckerberg Initiative Human Cell Atlas Kidney Seed Network.

Urinary soluble CD90 predicts renal prognosis in patients with diabetic kidney disease

Background

Diabetic kidney disease (DKD), the major cause of chronic kidney disease, is associated with progressive renal fibrosis. The expression of CD90 correlated with fibrogenesis. However, the association between urinary soluble CD90 and renal disease severity, and whether it predicts outcomes in patients with DKD are still unclear.

Methods

Urinary sCD90 was measured in 285 patients with DKD in a longitudinal cohort. The composite endpoint was defined as end-stage renal disease (ESRD) or 40% reduction of estimated glomerular filtration rate (eGFR). The associations between urinary sCD90/Cr and clinical parameters, as well as renal outcomes were evaluated. Moreover, we detected the intrarenal CD90 expression, and demonstrated the correlation of intrarenal CD90 with clinico-pathological parameters.

Results

The urinary sCD90 level of DKD patients is significantly higher than diabetes patients without kidney injuries and healthy controls. We further showed urinary sCD90/Cr had significantly correlations with eGFR (r=−0.373, P<0.001), uACR (r=0.303, P<0.001), serum creatinine (r=0.344, P<0.001), and the eGFR slope (r=−0.27, P<0.001). Elevated urinary sCD90/Cr was an independent risk factor for the composite endpoint, adjustment for potential confounders in DKD patients (HR 1.20, 95% CI: 1.04–1.38, P=0.015). However, the CD90 expression in the renal tubulointerstitial compartment in DKD patients was significantly lower than healthy controls, and showed significant negative correlations with the interstitial fibrosis and tubular atrophy score (IFTA) (r=−0.3, P=0.047), and urinary sCD90/Cr (r=−0.399, P=0.029).

Conclusions

This study provided evidence that urinary sCD90 could reflect the disease severity and serve as a valuable factor for renal outcome prediction in patients with DKD.

Review: Detection and quantification of proteins in human urine

Extensive medical research showed that patients, with high protein concentration in urine, have various kinds of kidney diseases, referred to as proteinuria. Urinary protein biomarkers are useful for diagnosis of many health conditions - kidney and cardio vascular diseases, cancers, diabetes, infections. This review focuses on the instrumental quantification (electrophoresis, chromatography, immunoassays, mass spectrometry, fluorescence spectroscopy, the infrared spectroscopy, and Raman spectroscopy) of proteins (the most of all albumin) in human urine matrix. Different techniques provide unique information on what constituents of the urine are. Due to complex nature of urine, a separation step by electrophoresis or chromatography are often used for proteomics study of urine. Mass spectrometry is a powerful tool for the discovery and the analysis of biomarkers in urine, however, costs of the analysis are high, especially for quantitative analysis. Immunoassays, which often come with fluorescence detection, are major qualitative and quantitative tools in clinical analysis. While Infrared and Raman spectroscopies do not give extensive information about urine, they could become important tools for the routine clinical diagnostics of kidney problems, due to rapidness and low-cost. Thus, it is important to review all the applicable techniques and methods related to urine analysis. In this review, a brief overview of each technique's principle is introduced. Where applicable, research papers about protein determination in urine are summarized with the main figures of merits, such as the limit of detection, the detectable range, recovery and accuracy, when available.

Panel of novel urine biomarkers for incident microalbuminuria in people with type 2 diabetes mellitus

AIM

The need to identify novel biomarkers for early diagnosis and treatment of diabetic nephropathy is widely recognized. However, only a few studies have investigated the association between biomarkers and the onset of albuminuria. In this study, we aimed to investigate a panel of biomarkers suitable for predicting microalbuminuria.

METHODS

Some 346 Japanese people with type 2 diabetes exhibiting normoalbuminuria were studied. The endpoint was defined as the onset of microalbuminuria. Thirty biomarkers were selected from among urinary biomarkers described in previous studies. A panel of biomarkers was selected using least absolute shrinkage and selection operator (LASSO). The prognostic performance of the developed panel was evaluated.

RESULTS

During a mean follow-up of 6.2 years, 45 people progressed to microalbuminuria. A composite panel of six biomarkers (monocyte chemoattractant protein-1, osteopontin, soluble human tumour necrosis factor receptor-1, tenascin C, vascular endothelial growth factor-A and kidney injury molecule-1) was developed using LASSO. Compared with the basal model comprising estimated GFR and urinary albumin-to-creatinine ratio, addition of these six biomarkers significantly increased the overall C index from 0.773 to 0.824 (P = 0.019). Net reclassification improvement and integrated discrimination improvement were estimated to be 0.412 (P = 0.049) and 0.040 (P = 0.040), respectively. Decision curve analysis also showed that the model with the six novel biomarkers had a better prognostic value for predicting the onset of microalbuminuria. The optimism was moderate or negligible according to measures.

CONCLUSIONS

The panel consisting of six novel urinary biomarkers effectively predicted incident microalbuminuria in people with type 2 diabetes.

Lipid deposition and metaflammation in diabetic kidney disease

A critical link between metabolic disorders and a form of low-grade systemic and chronic inflammation has been recently established and named 'Metaflammation'. Metaflammation has been recognized as a key mediator of both microvascular and macrovascular complications of diabetes and as a significant contributor to the development of diabetic kidney disease (DKD). The goal of this review is to summarize the contribution of diabetes-induced inflammation and the related signaling pathways to diabetic complications, with a particular focus on how innate immunity and lipid metabolism influence each other.

Protective factors as biomarkers and targets for prevention and treatment of diabetic nephropathy: From current human evidence to future possibilities

Although hyperglycemia, high blood pressure and aging increase the risk of developing kidney complications, some diabetes patients exposed to these risk factors do not develop kidney disease, suggesting the presence of endogenous protective factors. There is a growing need to understand these factors determining protection of the kidney in order to improve the design of preventive strategies and to enhance the processes responsible for renoprotection. The aim of this review was to present the existing molecular and epidemiological data on factors showing protective effects in diabetic kidney disease, and to summarize the evidence regarding their potential in the area of future clinical diagnostics, therapeutics and early preventive strategies. These include transcriptomic and proteomic studies regarding the anti-inflammatory, anti-fibrotic and regenerative factors that were associated with slower progression of renal function loss. Another focus is the new evidence regarding the evaluation of alterations in the regulatory epigenome and its involvement in the risk of diabetic kidney disease. Further effort is required to validate and extend these findings, and to define their potential for clinical implementation in the future.

The Association of dp-ucMGP with Cardiovascular Morbidity and Decreased Renal Function in Diabetic Chronic Kidney Disease

We aimed to investigate the possible association of the inactive, dephosphorylated, uncarboxylated matrix Gla protein (dp-ucMGP) with oxidized low-density lipoprotein (ox-LDL) and all-cause/cardiovascular (CV) mortality and renal function in diabetic chronic kidney disease (CKD). Ox-LDL and dp-ucMGP were determined in 66 diabetic CKD patients. All patients were prospectively followed for seven years, or until the occurrence of death, or a composite renal outcome of 30% estimated glomerular filtration rate (eGFR) reduction or progression to end-stage renal disease (ESRD) requiring dialysis occurred. Secondary outcomes were the occurrence of CV events. Kaplan-Meier curves showed that patients with plasma dp-ucMGP levels above the median (≥656 pM) had a significantly higher risk for all study endpoints. After adjustment for several well-known cofounders, multivariate Cox analysis showed that high plasma dp-ucMGP levels were associated with all-cause mortality (Hazard ratio-HR = 2.63, 95% Confidence Interval-CI = 1.17-5.94, p = 0.02), CV mortality (HR = 2.82, 95% CI = 1.07-7.49, p = 0.037) and progression of CKD (HR = 4.02, 95% CI = 1.20-13.46, p = 0.024). Circulating dp-ucMGP is associated with mortality and decreased renal function in diabetic CKD.

Identification of hub genes in diabetic kidney disease via multiple-microarray analysis

Background

Diabetic kidney disease (DKD) is a leading cause of end-stage renal disease; however, the underlying molecular mechanisms remain unclear. Recently, bioinformatics analysis has provided a comprehensive insight toward the molecular mechanisms of DKD. Here, we re-analyzed three mRNA microarray datasets including a single-cell RNA sequencing (scRNA-seq) dataset, with the aim of identifying crucial genes correlated with DKD and contribute to a better understanding of DKD pathogenesis.

Methods

Three datasets including GSE131882, GSE30122, and GSE30529 were utilized to find differentially expressed genes (DEGs). The potential functions of DEGs were analyzed by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. A protein-protein interaction (PPI) network was constructed, and hub genes were selected with the top three molecular complex detection (MCODE) score. A correlation analysis between hub genes and clinical indicators was also performed.

Results

In total, 84 upregulated DEGs and 49 downregulated DEGs were identified. Enriched pathways of the upregulated DEGs included extracellular matrix (ECM) receptor interaction, focal adhesion, human papillomavirus infection, malaria, and cell adhesion molecules. The downregulated DEGs were mainly enriched in ascorbate and aldarate metabolism, arginine and proline metabolism, endocrine- and other factor-regulated calcium reabsorption, mineral absorption and longevity regulating pathway, and multiple species signaling pathway. Seventeen hub genes were identified, and correlation analysis between unexplored hub genes and clinical features of DKD suggested that EGF, KNG1, GADD45B, and CDH2 might have reno-protective roles in DKD. Meanwhile, ATF3, B2M, VCAM1, CLDN4, SPP1, SOX9, JAG1, C3, and CD24 might promote the progression of DKD. Finally, most hub genes were found present in the immune cells of diabetic kidneys, which suggest the important role of inflammation infiltration in DKD pathogenesis.

Conclusions

In this study, we found seventeen hub genes using a scRNA-seq contained multiple-microarray analysis, which enriched the present understanding of molecular mechanisms underlying the pathogenesis of DKD in cells' level and provided candidate targets for diagnosis and treatment of DKD.

Diabetic kidney diseases revisited: A new perspective for a new era

BACKGROUND

Globally, diabetic kidney disease (DKD) is the leading cause of end-stage renal disease. As the most common microvascular complication of diabetes, DKD is a thorny, clinical problem in terms of its diagnosis and management. Intensive glucose control in DKD could slow down but not significantly halt disease progression. Revisiting the tremendous advances that have occurred in the field would enhance recognition of DKD pathogenesis as well as improve our understanding of translational science in DKD in this new era.

SCOPE OF REVIEW

In this review, we summarize advances in the understanding of the local microenvironmental changes in diabetic kidneys and discuss the involvement of genetic and epigenetic factors in the pathogenesis of DKD. We also review DKD prevalence changes and analyze the challenges in optimizing the diagnostic approaches and management strategies for DKD in the clinic. As we enter the era of 'big data', we also explore the possibility of linking systems biology with translational medicine in DKD in the current healthcare system.

MAJOR CONCLUSION

Newer understanding of the structural changes of diabetic kidneys and mechanisms of DKD pathogenesis, as well as emergent research technologies will shed light on new methods of dealing with the existing clinical challenges of DKD.