Biomarkers For Diabetic Kidney Disease Research Articles

Microarray analysis reveals gene and microRNA signatures in diabetic kidney disease.

The current study aimed to identify therapeutic gene and microRNA (miRNA) biomarkers for diabetic kidney disease (DKD). The public expression profile GSE30122 was used. Following data preprocessing, the limma package was used to select differentially-expressed genes (DEGs) in DKD glomeruli samples and tubuli samples and they were compared with corresponding controls. Then overlapping DEGs in glomeruli and tubuli were identified and enriched analysis was performed. In addition, protein-protein interaction (PPI) network analysis as well as sub-network analysis was conducted. miRNAs of the overlapping DEGs were investigated using WebGestal. A total of 139 upregulated and 28 downregulated overlapping DEGs were selected, which were primarily associated with pathways involved in extracellular matrix (ECM)-receptor interactions and cytokine-cytokine receptor interactions. CD44, fibronectin 1, C-C motif chemokine ligand 5 and C-X-C motif chemokine receptor 4 were four primary nodes in the PPI network. miRNA (miR)-17-5p, miR-20a and miR-106a were important and nuclear receptor subfamily 4 group A member 3 (NR4A3), protein tyrosine phosphatase, receptor type O (PTPRO) and Kruppel like factor 9 (KLF9) were all predicted as target genes of the three miRNAs in the integrated miRNA-target network. Several genes were identified in DKD, which may be involved in pathways such as ECM-receptor interaction and cytokine-cytokine receptor interaction. Three miRNAs may also be used as biomarkers for therapy of DKD, including miR-17-5p, miR-20a and miR-106a, with the predicted targets of NR4A3, PTPRO and KLF9.

Urinary glycated uromodulin in diabetic kidney disease.

Advanced glycation end-products (AGEs) form during oxidative stress, which is increased in diabetes mellitus (DM). Uromodulin is a protein with a renal protective effect, and may be subject to glycation. The implications of uromodulin glycation and AGEs in the urine are not understood. Here, immunoprecipitation and liquid chromatography-mass spectrometry identified glycated uromodulin (glcUMOD) in the urine of 62.5% of patients with diabetic kidney disease (DKD), 20.0% of patients with non-diabetic chronic kidney disease (CKD), and no DM patients with normal renal function or healthy control participants; a finding replicated in a larger cohort of 84 patients with CKD in a case-control study (35 with DM, 49 without). Uromodulin forms high molecular weight polymers that associate with microvesicles and exosomes. Differential centrifugation identified uromodulin in the supernatant, microvesicles, and exosomes of the urine of healthy participants, but only in the supernatant of samples from patients with DKD, suggesting that glycation influences uromodulin function. Finally, the diagnostic and prognostic utility of measuring urinary glcUMOD concentration was examined. Urinary glcUMOD concentration was substantially higher in DKD patients than non-diabetic CKD patients. Urinary glcUMOD concentration predicted DKD status, particularly in patients with CKD stages 1-3a aged <65 years and with urine glcUMOD concentration ≥9,000 arbitrary units (AU). Urinary uromodulin is apparently glycated in DKD and forms AGEs, and glcUMOD may serve as a biomarker for DKD.

Reading the tree leaves—how to enrich clinical trials of diabetic kidney disease

Most participants selected for clinical trials of renoprotective drugs do not reach approved endpoints; thus, large trials or prolonged follow-up are needed to achieve adequate statistical power. Yamanouchi etal. used a classification and regression trees analysis to enrich enrollment criterion for patients at the highest risk of reaching these outcomes. Their findings suggest a greater role for newly identified biomarkers of diabetic kidney disease in the selection of participants for clinical trials.

Proteomics for prediction of disease progression and response to therapy in diabetic kidney disease.

The past decade has resulted in multiple new findings of potential proteomic biomarkers of diabetic kidney disease (DKD). Many of these biomarkers reflect an important role in the (patho)physiology and biological processes of DKD. Situations in which proteomics could be applied in clinical practice include the identification of individuals at risk of progressive kidney disease and those who would respond well to treatment, in order to tailor therapy for those at highest risk. However, while many proteomic biomarkers have been discovered, and even found to be predictive, most lack rigorous external validation in sufficiently powered studies with renal endpoints. Moreover, studies assessing short-term changes in the proteome for therapy-monitoring purposes are lacking. Collaborations between academia and industry and enhanced interactions with regulatory agencies are needed to design new, sufficiently powered studies to implement proteomics in clinical practice.

Biomarkers in diabetic kidney disease: good use and pitfalls.

-ses, cystatin C-based formulas showed the best performance, followed closely by the new CKD-EPI creatinine-based equation. Their findings highlight the crave for more precise measures of GFR estimation and waiving of less efficient methods such as Cockcroft-Gault formula. When compared to MDRD equation the new CKD-EPI equation is more accurate and reduces the known effect of MDRD on sub-estimating GFR in normal and near-normal values (2). However, the CKD-EPI equation based on creatinine also requires a race definition, which is always problematic, particularly in highly admixture populations. This formula has not been largely validated outside US, Europe and Australia and this should be done in populations ethnically different from the population in whom the equation was derived and revalidated, such as Brazil. Small Brazilian studies yielded results suggesting that this equation may be applied in our population (3-5), but larger studies are still necessary. On the other hand, cystatin C seems to improve accuracy in comparison to creatinine, but is still not largely avail-able and its cost is still high. These problems could be minimized with a broader use of this marker, but to the present cystatin C use is still very much restricted to the research field.In the other manuscript, Polat and cols. (6) have analyzed several endothelial dys-function biomarkers in 73 patients with diabetes and either normoalbuminuria and microalbuminuria in comparison to healthy controls. The authors showed that al-though differences can be detected among the diabetic and non-diabetic groups, most biomarkers cannot discriminate those with and without albuminuria. Only sVCAM-1 showed a better performance in identifying those with microalbuminuria.Reflections raised by the two papers come in accordance with a very actual discus-sion on diabetic kidney disease. One of the most fearest complications of long-term poor glycemic control, CKD in diabetes still faces old problems regarding two very basic problems: diagnosis and classification. Diagnosis has always been supported by the recognition of long term hyperglycemia, increasing albuminuria occurring along to GFR loss (represented by the hyperfiltration, microalbuminuric and macroalbu-minuric phases), the presence of other microvascular injury, especially diabetic reti-nopathy, and absence of signs of other kidney diseases. However, it has been recently recognized that the classical description of the hyperfiltration, micro- and macroal-buminuric phases is limited, since a significant number of diabetic patients with CKD (and losing GFR over time) may in fact present normoalbuminuria and or micro-

Cystatin C- An Early Diagnostic Biomarker of Diabetic Kidney Disease

Cystatin C- An Early Diagnostic Biomarker of Diabetic Kidney Disease

Recent progress of biomarkers for diabetic kidney disease

Biomarkers can be applied in early diagnosis and classification for the development and progression of diabetic kidney disease (DKD), and thus are very useful in improving patients' prognosis. According to current relevant guidelines, the early screening and staging of DKD is based both on the level of urinary albumin excretion and glomerular filtration rate (GFR). However, the sensitivity and specificity of microalbuminuria recently has been challenged, and high-normal level GFR is difficult to be accurately measured. Therefore, many researchers devote themselves to seek more appropriate biomarkers for DKD. This is a controversial issue with its pros and cons, involving in metabolism, inflammation, oxidation, stress, advanced glycation end products, fibrosis, endothelium function, tubular function, genetic background, podocyte injury, and so on.(Chin J Lab Med, 2015, 38: 583-585) Key words: Diabetic nephropathies; Biological markers

MicroRNAs in Diabetic Kidney Disease

Rapid growth of diabetes and diabetic kidney disease exerts a great burden on society. Owing to the lack of effective treatments for diabetic kidney disease, treatment relies on drugs that either reduces its progression or involve renal replacement therapies, such as dialysis and kidney transplantation. It is urgent to search for biomarkers for early diagnosis and effective therapy. The discovery of microRNAs had lead to a new era of post-transcriptional regulators of gene expression. Studies from cells, experimental animal models and patients under diabetic conditions demonstrate that expression patterns of microRNAs are altered during the progression of diabetic kidney disease. Functional studies indicate that the ability of microRNAs to bind 3′ untranslated region of messenger RNA not only shows their capability to regulate expression of target genes, but also their therapeutic potential to diabetic kidney disease. The presence of microRNAs in plasma, serum, and urine has been shown to be possible biomarkers in diabetic kidney disease. Therefore, identification of the pathogenic role of microRNAs possesses an important clinical impact in terms of prevention and treatment of progression in diabetic kidney disease because it allows us to design novel and specific therapies and diagnostic tools for diabetic kidney disease.

Metabolomics Reveals Signature of Mitochondrial Dysfunction in Diabetic Kidney Disease

Diabetic kidney disease is the leading cause of ESRD, but few biomarkers of diabetic kidney disease are available. This study used gas chromatography-mass spectrometry to quantify 94 urine metabolites in screening and validation cohorts of patients with diabetes mellitus (DM) and CKD(DM+CKD), in patients with DM without CKD (DM-CKD), and in healthy controls. Compared with levels in healthy controls, 13 metabolites were significantly reduced in the DM+CKD cohorts (P≤0.001), and 12 of the 13 remained significant when compared with the DM-CKD cohort. Many of the differentially expressed metabolites were water-soluble organic anions. Notably, organic anion transporter-1 (OAT1) knockout mice expressed a similar pattern of reduced levels of urinary organic acids, and human kidney tissue from patients with diabetic nephropathy demonstrated lower gene expression of OAT1 and OAT3. Analysis of bioinformatics data indicated that 12 of the 13 differentially expressed metabolites are linked to mitochondrial metabolism and suggested global suppression of mitochondrial activity in diabetic kidney disease. Supporting this analysis, human diabetic kidney sections expressed less mitochondrial protein, urine exosomes from patients with diabetes and CKD had less mitochondrial DNA, and kidney tissues from patients with diabetic kidney disease had lower gene expression of PGC1α (a master regulator of mitochondrial biogenesis). We conclude that urine metabolomics is a reliable source for biomarkers of diabetic complications, and our data suggest that renal organic ion transport and mitochondrial function are dysregulated in diabetic kidney disease.

New urinary biomarkers for diabetic kidney disease

Diabetic kidney disease is the leading cause of end-stage renal disease in developed and developing countries. Microalbuminuria is the gold standard for detection and prediction of diabetic kidney disease and cardiovascular risk disease in clinical practice. However, microalbuminuria has several limitations, such as lower sensitive, larger variability. It is urgent to explore higher sensitivity and specificity for earlier detection of diabetic kidney disease and more accurate prediction of the progression to end stage renal disease. We reviewed some new and important urinary biomarkers, such as: transferrin, immunoglobulin G, immunoglobulin M, Cystanic C, podocytes, type IV collagen, 8-oxo-7, 8-dihydro-2'-deoxyguanosine, ceruloplasmin, monocyte chemoattractant protein-1 and so on. We need good quality, long-term, large longitudinal trials to validate published biomarkers and find new biomarkers, considering biomarkers reviewed here are from small cross-sectional studies.

Measuring urinary tubular biomarkers in type 2 diabetes does not add prognostic value beyond established risk factors

Tubulointerstitial disease plays an important role in the pathophysiology of diabetic kidney disease. To determine whether biomarkers of tubular injury could predict renal outcome and mortality in patients with type 2 diabetes, we measured urinary levels of kidney injury molecule-1 (KIM-1) and glycoprotein non-metastatic melanoma B (Gpnmb), both normalized to the urinary creatinine, in 978 individuals from the Edinburgh Type 2 Diabetes Study. At baseline, 238 patients had an estimated glomerular filtration rate (eGFR) below 60 ml/min/1.73 m2 while 147 and 15 patients had microalbuminuria or overt proteinuria, respectively. Both the urine KIM-1 and Gpnmb to creatinine ratios correlated with the urinary albumin to creatinine ratio, the duration of diabetes, and the stringency of glycemic control but not with blood pressure or baseline eGFR. Higher ratios of each marker were associated with a faster decline in kidney function during 4 years of follow-up; however, this was not independent of the urinary albumin to creatinine ratio. Higher KIM-1, but not Gpnmb ratios were associated with an increased risk of mortality, but this association was no longer significant after adjustment for other risk factors, in particular albuminuria. Thus, tubular injury in persons with type 2 diabetes may contribute to the decline in kidney function; however, measuring the urinary concentration of these two tubular biomarkers does not confer additional prognostic information beyond established risk factors.

Biomarkers in diabetic kidney disease

Measures to assess kidney function and injury in the diabetic population are currently either inadequate or manifest late in the progressive phase, leading to extensive irreversible damage. Recent efforts to identify novel biomarkers in the diabetic population have been evolving either to detect early kidney injury or repair that ultimately lead to progression of diabetic kidney disease. Emerging roles of urinary biomarkers have proven beneficial due to the ability to standardize the various markers to creatinine or peptides already present in the urine. The role of neutrophil gelatinase-associated lipoprotein, kidney injury molecule-1 and podocin derivatives have gained enormous significance in the process of early identification of kidney injury in the diabetic population. The recent identification of various novel genomic and proteomic applications in investigations of acute kidney injury and chronic kidney diseases has garnered much attention. This article will discuss the evolution of novel biomarker...

Discovery of early-stage biomarkers for diabetic kidney disease using ms-based metabolomics (FinnDiane study)

Diabetic kidney disease (DKD) is a devastating complication that affects an estimated third of patients with type 1 diabetes mellitus (DM). There is no cure once the disease is diagnosed, but early treatment at a sub-clinical stage can prevent or at least halt the progression. DKD is clinically diagnosed as abnormally high urinary albumin excretion rate (AER). We hypothesize that subtle changes in the urine metabolome precede the clinically significant rise in AER. To test this, 52 type 1 diabetic patients were recruited by the FinnDiane study that had normal AER (normoalbuminuric). After an average of 5.5 years of follow-up half of the subjects (26) progressed from normal AER to microalbuminuria or DKD (macroalbuminuria), the other half remained normoalbuminuric. The objective of this study is to discover urinary biomarkers that differentiate the progressive form of albuminuria from non-progressive form of albuminuria in humans. Metabolite profiles of baseline 24 h urine samples were obtained by gas chromatography–mass spectrometry (GC–MS) and liquid chromatography–mass spectrometry (LC–MS) to detect potential early indicators of pathological changes. Multivariate logistic regression modeling of the metabolomics data resulted in a profile of metabolites that separated those patients that progressed from normoalbuminuric AER to microalbuminuric AER from those patients that maintained normoalbuminuric AER with an accuracy of 75% and a precision of 73%. As this data and samples are from an actual patient population and as such, gathered within a less controlled environment it is striking to see that within this profile a number of metabolites (identified as early indicators) have been associated with DKD already in literature, but also that new candidate biomarkers were found. The discriminating metabolites included acyl-carnitines, acyl-glycines and metabolites related to tryptophan metabolism. We found candidate biomarkers that were univariately significant different. This study demonstrates the potential of multivariate data analysis and metabolomics in the field of diabetic complications, and suggests several metabolic pathways relevant for further biological studies.Electronic supplementary materialThe online version of this article (doi:10.1007/s11306-011-0291-6) contains supplementary material, which is available to authorized users.

Therapeutic Strategies in the Treatment of Diabetic Nephropathy - a Translational Medicine Approach

Type 2 Diabetes (T2D) is an important cause of renal dysfunction and the most common cause of end-stage renal disease (ESRD). Diabetic nephropathy is also associated with an increased risk of vascular disease and patient mortality. Aggressive management of hypertension to reduce microalbuminuria, together with tight glycaemic control are important therapeutic strategies for renal and vascular disease prevention in T2D. The main pathophysiological mechanisms associated with diabetic nephropathy result from activation of the renin-angiotensin-aldosterone system (RAAS), protein kinase C pathway, pro-inflammatory cytokines and various growth factors. Angiotensin II and transforming growth factor-beta (TGF-beta) are two important molecular mediators. The production of advanced glycation end-products (AGEs) and increased oxidative stress further exacerbates renal injury. These molecular changes within the renal tissue result in mesangial expansion, increased extracellular matrix deposition and an alteration in podocyte structure and function. Therapeutic targeting of these molecular pathways is an important area of translational research in diabetes. The elucidation of new genetic associations and proteomic biomarkers of diabetic kidney disease will also assist in the identification and treatment of high-risk patients. This review article will discuss both the molecular and clinical aspects of diabetic nephropathy, providing a bench-to-bedside research perspective to potential new therapeutic strategies.