Impact of diabetic nephropathy and angiotensin II receptor blockade on urinary polypeptide patterns

Angiotensin-converting-enzyme inhibitors and angiotensin receptor blockers for preventing the progression of diabetic kidney disease

BACKGROUND

Guidelines suggest that adults with diabetes and kidney disease receive treatment with angiotensin-converting-enzyme inhibitors (ACEi) or angiotensin receptor blockers (ARB). This is an update of a Cochrane review published in 2006.

OBJECTIVES

We compared the efficacy and safety of ACEi and ARB therapy (either as monotherapy or in combination) on cardiovascular and kidney outcomes in adults with diabetes and kidney disease.

SEARCH METHODS

We searched the Cochrane Kidney and Transplants Register of Studies to 17 March 2024 through contact with the Information Specialist using search terms relevant to this review. Studies in the Register are identified through searches of CENTRAL, MEDLINE, and EMBASE, conference proceedings, the International Clinical Trials Registry Platform (ICTRP) Search Portal, and ClinicalTrials.gov.

SELECTION CRITERIA

We included studies evaluating ACEi or ARB alone or in combination, compared to each other, placebo or no treatment in people with diabetes and kidney disease.

DATA COLLECTION AND ANALYSIS

Two authors independently assessed the risk of bias and extracted data. Summary estimates of effect were obtained using a random-effects model, and results were expressed as risk ratios (RR) and their 95% confidence intervals (CI) for dichotomous outcomes and mean difference (MD) or standardised mean difference (SMD) and 95% CI for continuous outcomes. Confidence in the evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach.

MAIN RESULTS

One hundred and nine studies (28,341 randomised participants) were eligible for inclusion. Overall, the risk of bias was high. Compared to placebo or no treatment, ACEi may make little or no difference to all-cause death (24 studies, 7413 participants: RR 0.91, 95% CI 0.73 to 1.15; I2 = 23%; low certainty) and with similar withdrawals from treatment (7 studies, 5306 participants: RR 1.03, 95% CI 0.90 to 1.19; I2 = 0%; low certainty). ACEi may prevent kidney failure (8 studies, 6643 participants: RR 0.61, 95% CI 0.39 to 0.94; I2 = 0%; low certainty). Compared to placebo or no treatment, ARB may make little or no difference to all-cause death (11 studies, 4260 participants: RR 0.99, 95% CI 0.85 to 1.16; I2 = 0%; low certainty). ARB have uncertain effects on withdrawal from treatment (3 studies, 721 participants: RR 0.85, 95% CI 0.58 to 1.26; I2 = 2%; low certainty) and cardiovascular death (6 studies, 878 participants: RR 3.36, 95% CI 0.93 to 12.07; low certainty). ARB may prevent kidney failure (3 studies, 3227 participants: RR 0.82, 95% CI 0.72 to 0.94; I2 = 0%; low certainty), doubling of serum creatinine (SCr) (4 studies, 3280 participants: RR 0.84, 95% CI 0.72 to 0.97; I2 = 32%; low certainty), and the progression from microalbuminuria to macroalbuminuria (5 studies, 815 participants: RR 0.44, 95% CI 0.23 to 0.85; I2 = 74%; low certainty). Compared to ACEi, ARB had uncertain effects on all-cause death (15 studies, 1739 participants: RR 1.13, 95% CI 0.68 to 1.88; I2 = 0%; low certainty), withdrawal from treatment (6 studies, 612 participants: RR 0.91, 95% CI 0.65 to 1.28; I2 = 0%; low certainty), cardiovascular death (13 studies, 1606 participants: RR 1.15, 95% CI 0.45 to 2.98; I2 = 0%; low certainty), kidney failure (3 studies, 837 participants: RR 0.56, 95% CI 0.29 to 1.07; I2 = 0%; low certainty), and doubling of SCr (2 studies, 767 participants: RR 0.88, 95% CI 0.52 to 1.48; I2 = 0%; low certainty). Compared to ACEi plus ARB, ACEi alone has uncertain effects on all-cause death (6 studies, 1166 participants: RR 1.08, 95% CI 0.49 to 2.40; I2 = 20%; low certainty), withdrawal from treatment (2 studies, 172 participants: RR 0.78, 95% CI 0.33 to 1.86; I2 = 0%; low certainty), cardiovascular death (4 studies, 994 participants: RR 3.02, 95% CI 0.61 to 14.85; low certainty), kidney failure (3 studies, 880 participants: RR 1.36, 95% CI 0.79 to 2.32; I2 = 0%; low certainty), and doubling of SCr (2 studies, 813 participants: RR 1.14, 95% CI 0.70 to 1.85; I2 = 0%; low certainty). Compared to ACEi plus ARB, ARB alone has uncertain effects on all-cause death (7 studies, 2607 participants: RR 1.02, 95% CI 0.76 to 1.37; I2 = 0%; low certainty), withdrawn from treatment (3 studies, 1615 participants: RR 0.81, 95% CI 0.53 to 1.24; I2 = 0%; low certainty), cardiovascular death (4 studies, 992 participants: RR 3.03, 95% CI 0.62 to 14.93; low certainty), kidney failure (4 studies, 2321 participants: RR 1.15, 95% CI 0.67 to 1.95; I2 = 29%; low certainty), and doubling of SCr (3 studies, 2252 participants: RR 1.18, 95% CI 0.85 to 1.64; I2 = 0%; low certainty). Comparative effects of different ACEi or ARB and low-dose versus high-dose ARB were rarely evaluated. No study compared different doses of ACEi. Adverse events of ACEi and ARB were rarely reported.

AUTHORS' CONCLUSIONS

ACEi or ARB may make little or no difference to all-cause and cardiovascular death compared to placebo or no treatment in people with diabetes and kidney disease but may prevent kidney failure. ARB may prevent the doubling of SCr and the progression from microalbuminuria to macroalbuminuria compared with a placebo or no treatment. Despite the international guidelines suggesting not combining ACEi and ARB treatment, the effects of ACEi or ARB monotherapy compared to dual therapy have not been adequately assessed. The limited data availability and the low quality of the included studies prevented the assessment of the benefits and harms of ACEi or ARB in people with diabetes and kidney disease. Low and very low certainty evidence indicates that it is possible that further studies might provide different results.

Proteomics and Its Current Application in Biomedical Area: Concise Review

Biomedical researchers tirelessly seek cutting-edge technologies to advance disease diagnosis, drug discovery, and therapeutic interventions, all aimed at enhancing human and animal well-being. Within this realm, proteomics stands out as a pivotal technology, focusing on extensive studies of protein composition, structure, function, and interactions. Proteomics, with its subdivisions of expression, structural, and functional proteomics, plays a crucial role in unraveling the complexities of biological systems. Various sophisticated techniques are employed in proteomics, including polyacrylamide gel electrophoresis, mass spectrometry analysis, NMR spectroscopy, protein microarray, X-ray crystallography, and Edman sequencing. These methods collectively contribute to the comprehensive understanding of proteins and their roles in health and disease. In the biomedical field, proteomics finds widespread application in cancer research and diagnosis, stem cell studies, and the diagnosis and research of both infectious and noninfectious diseases. In addition, it plays a pivotal role in drug discovery and the emerging frontier of personalized medicine. The versatility of proteomics allows researchers to delve into the intricacies of molecular mechanisms, paving the way for innovative therapeutic approaches. As infectious and noninfectious diseases continue to emerge and the field of biomedical research expands, the significance of proteomics becomes increasingly evident. Keeping abreast of the latest developments in proteomics applications becomes paramount for the development of therapeutics, translational research, and study of diverse diseases. This review aims to provide a comprehensive overview of proteomics, offering a concise outline of its current applications in the biomedical domain. By doing so, it seeks to contribute to the understanding and advancement of proteomics, emphasizing its pivotal role in shaping the future of biomedical research and therapeutic interventions.

In-depth urinary and exosome proteome profiling analysis identifies novel biomarkers for diabetic kidney disease

Diabetic kidney disease (DKD) is a major microvascular complication of type 2 diabetes mellitus (T2DM). Monitoring the early diagnostic period and disease progression plays a crucial role in treating DKD. In this study, to comprehensively elucidate the molecular characteristics of urinary proteins and urinary exosome proteins in type 2 DKD, we performed large-scale urinary proteomics (n=144) and urinary exosome proteomics (n=44) analyses on T2DM patients with albuminuria in varying degrees. The dynamics analysis of the urinary and exosome proteomes in our study provides a valuable resource for discovering potential urinary biomarkers in patients with DKD. A series of potential biomarkers, such as SERPINA1 and transferrin (TF), were detected and validated to be used for DKD diagnosis or disease monitoring. The results of our study comprehensively elucidated the changes in the urinary proteome and revealed several potential biomarkers reflecting the progression of DKD, which provide a reference for DKD biomarker screening.

Precision Medicine in Diabetic Kidney Disease: A Narrative Review Framed by Lived Experience

Purpose of review

Diabetic kidney disease (DKD) is a leading cause of chronic kidney disease (CKD) for which many treatments exist that have been shown to prevent CKD progression and kidney failure. However, DKD is a complex and heterogeneous etiology of CKD with a spectrum of phenotypes and disease trajectories. In this narrative review, we discuss precision medicine approaches to DKD, including genomics, metabolomics, proteomics, and their potential role in the management of diabetes mellitus and DKD. A patient and caregivers of patients with lived experience with CKD were involved in this review.

Sources of information

Original research articles were identified from MEDLINE and Google Scholar using the search terms "diabetes," "diabetic kidney disease," "diabetic nephropathy," "chronic kidney disease," "kidney failure," "dialysis," "nephrology," "genomics," "metabolomics," and "proteomics."

Methods

A focused review and critical appraisal of existing literature regarding the precision medicine approaches to the diagnosis, prognosis, and treatment of diabetes and DKD framed by a patient partner's/caregiver's lived experience.

Key findings

Distinguishing diabetic nephropathy from CKD due to other types of DKD and non-DKD is challenging and typically requires a kidney biopsy for a diagnosis. Biomarkers have been identified to assist with the prediction of the onset and progression of DKD, but they have yet to be incorporated and evaluated relative to clinical standard of care CKD and kidney failure risk prediction tools. Genomics has identified multiple causal genetic variants for neonatal diabetes mellitus and monogenic diabetes of the young that can be used for diagnostic purposes and to specify antiglycemic therapy. Genome-wide-associated studies have identified genes implicated in DKD pathophysiology in the setting of type 1 and 2 diabetes but their translational benefits are lagging beyond polygenetic risk scores. Metabolomics and proteomics have been shown to improve diagnostic accuracy in DKD, have been used to identify novel pathways involved in DKD pathogenesis, and can be used to improve the prediction of CKD progression and kidney failure as well as predict response to DKD therapy.

Limitations

There are a limited number of large, high-quality prospective observational studies and no randomized controlled trials that support the use of precision medicine based approaches to improve clinical outcomes in adults with or at risk of diabetes and DKD. It is unclear which patients may benefit from the clinical use of genomics, metabolomics and proteomics along the spectrum of DKD trajectory.

Implications

Additional research is needed to evaluate the role of the use of precision medicine for DKD management, including diagnosis, differentiation of diabetic nephropathy from other etiologies of DKD and CKD, short-term and long-term risk prognostication kidney outcomes, and the prediction of response to and safety of disease-modifying therapies.

Novel biomarkers for diabetic kidney disease

Although diabetic kidney disease (DKD) remains one of the leading causes of reduced lifespan in patients with diabetes mellitus; its prevalence has failed to decline over the past 30 years. To identify those at high risk of developing DKD and disease progression at an early stage, extensive research has been ongoing in the search for prognostic and surrogate endpoint biomarkers for DKD. Although biomarkers are not used routinely in clinical practice or prospective clinical trials, many biomarkers have been developed to improve the early identification and prognostication of patients with DKD. Novel biomarkers that capture one specific mechanism of the DKD disease process have been developed, and studies have evaluated the prognostic value of assay-based biomarkers either in small sets or in combinations involving multiple biomarkers. More recently, several studies have assessed the prognostic value of omics- based biomarkers that include proteomics, metabolomics, and transcriptomics. This review will first describe the biomarkers used in current practice and their limitations, and then summarize the current status of novel biomarkers for DKD with respect to assay- based protein biomarkers, proteomics, metabolomics, and transcriptomics.

OMICS in Chronic Kidney Disease: Focus on Prognosis and Prediction

Chronic kidney disease (CKD) patients are characterized by a high residual risk for cardiovascular (CV) events and CKD progression. This has prompted the implementation of new prognostic and predictive biomarkers with the aim of mitigating this risk. The ‘omics’ techniques, namely genomics, proteomics, metabolomics, and transcriptomics, are excellent candidates to provide a better understanding of pathophysiologic mechanisms of disease in CKD, to improve risk stratification of patients with respect to future cardiovascular events, and to identify CKD patients who are likely to respond to a treatment. Following such a strategy, a reliable risk of future events for a particular patient may be calculated and consequently the patient would also benefit from the best available treatment based on their risk profile. Moreover, a further step forward can be represented by the aggregation of multiple omics information by combining different techniques and/or different biological samples. This has already been shown to yield additional information by revealing with more accuracy the exact individual pathway of disease.

Mechanistic interactions of uromodulin with the thick ascending limb: perspectives in physiology and hypertension

Hypertension is a significant risk factor for cardiovascular disease and mortality worldwide. The kidney is a major regulator of blood pressure and electrolyte homeostasis, with monogenic disorders indicating a link between abnormal ion transport and salt-sensitive hypertension. However, the association between salt and hypertension remains controversial. Thus, there is continued interest in deciphering the molecular mechanisms behind these processes. Uromodulin (UMOD) is the most abundant protein in the normal urine and is primarily synthesized by the thick ascending limb epithelial cells of the kidney. Genome-wide association studies have linked common UMOD variants with kidney function, susceptibility to chronic kidney disease and hypertension independent of renal excretory function. This review will discuss and provide predictions on the role of the UMOD protein in renal ion transport and hypertension based on current observational, biochemical, genetic, pharmacological and clinical evidence.

Aspartic acid supplementation ameliorates symptoms of diabetic kidney disease in mice

Diabetic kidney disease (DKD) is among the most common and serious complications of both type 1 and type 2 diabetes. In this study, we used KK/Ta‐Ins2^Akita (KK‐Akita) mice as a model of DKD and KK/Ta (KK) mice as controls to identify novel factors related to the development/progression of DKD. Capillary electrophoresis coupled with mass spectrometry analysis revealed that circulating Asp (l‐aspartic acid) levels in diabetic KK‐Akita mice tend to be lower than those in control KK mice. Therefore, we evaluated the effect of Asp supplementation to prevent the progression of DKD in KK‐Akita mice. Mice were divided into three groups: (a) untreated KK mice (Control group), (b) untreated KK‐Akita mice (DKD group), and (c) treated (double‐volume Asp diet) KK‐Akita mice (Tx group). Kidney sections were stained with fluorescein isothiocyanate‐labeled lectins, wheat germ agglutinin (WGA), and anti‐endothelial nitric oxide synthase (eNOS) antibody for evaluation of endothelial surface layer (ESL) and NO synthesis. The mesangial area and glomerular size in the DKD group were significantly larger than those in the Control group; however, there was no significant difference in those between the DKD and Tx groups. Albuminuria, the ratio of foot process effacement, and thickness of glomerular basement membrane in the Tx group were significantly lower than those in the DKD group. Furthermore, the expression levels of glomerular WGA and microvascular eNOS in the Tx group improved significantly and approached the level in the Control group. In conclusion, the improvement of albuminuria in the Tx group may be caused by the reduction of oxidative stress in the kidneys, which may lead to the subsequent improvement of glomerular ESL.

Urinary Peptidomic Biomarkers in Kidney Diseases

In order to effectively develop personalized medicine for kidney diseases we urgently need to develop highly accurate biomarkers for use in the clinic, since current biomarkers of kidney damage (changes in serum creatinine and/or urine albumin excretion) apply to a later stage of disease, lack accuracy, and are not connected with molecular pathophysiology. Analysis of urine peptide content (urinary peptidomics) has emerged as one of the most attractive areas in disease biomarker discovery. Urinary peptidome analysis allows the detection of short and long-term physiological or pathological changes occurring within the kidney. Urinary peptidomics has been applied extensively for several years now in renal patients, and may greatly improve kidney disease management by supporting earlier and more accurate detection, prognostic assessment, and prediction of response to treatment. It also promises better understanding of kidney disease pathophysiology, and has been proposed as a “liquid biopsy” to discriminate various types of renal disorders. Furthermore, proteins being the major drug targets, peptidome analysis may allow one to evaluate the effects of therapies at the protein signaling pathway level. We here review the most recent findings on urinary peptidomics in the setting of the most common kidney diseases.

Angiotensin II Signal Transduction: An Update on Mechanisms of Physiology and Pathophysiology

The renin-angiotensin-aldosterone system plays crucial roles in cardiovascular physiology and pathophysiology. However, many of the signaling mechanisms have been unclear. The angiotensin II (ANG II) type 1 receptor (AT₁R) is believed to mediate most functions of ANG II in the system. AT₁R utilizes various signal transduction cascades causing hypertension, cardiovascular remodeling, and end organ damage. Moreover, functional cross-talk between AT₁R signaling pathways and other signaling pathways have been recognized. Accumulating evidence reveals the complexity of ANG II signal transduction in pathophysiology of the vasculature, heart, kidney, and brain, as well as several pathophysiological features, including inflammation, metabolic dysfunction, and aging. In this review, we provide a comprehensive update of the ANG II receptor signaling events and their functional significances for potential translation into therapeutic strategies. AT₁R remains central to the system in mediating physiological and pathophysiological functions of ANG II, and participation of specific signaling pathways becomes much clearer. There are still certain limitations and many controversies, and several noteworthy new concepts require further support. However, it is expected that rigorous translational research of the ANG II signaling pathways including those in large animals and humans will contribute to establishing effective new therapies against various diseases.

Kidney protective effects of baroreflex activation therapy in patients with resistant hypertension

Baroreflex activation therapy (BAT) is approved for the treatment of resistant hypertension. In addition to blood pressure (BP) reduction, pilot studies suggested several organoprotective effects of BAT. Thirty-two patients with resistant hypertension were prospectively treated with BAT. Besides office BP and 24-hour ambulatory BP (ABP) measurements, detection of a urinary proteome-based classifier (CKD273), which has been shown to predict chronic kidney disease (CKD) progression, was carried out at baseline and after 6 months of BAT. Office BP significantly decreased from 170 ± 25/90 ± 18 to 149 ± 29/82 ± 18 mm Hg. Analysis of CKD273 score and eGFR with CKD-EPI equation at baseline revealed strong correlation (r = 0.568, P < 0.001). After 6 months of BAT, there was no significant change in CKD273 score (-0.061 [95% CI: -0.262 to 0.140], P = 0.601). However, by stratification of the data regarding ABP response, there was a statistically significant (P = 0.0113) reduction in the CKD273 score from a mean of 0.161 [95% CI: -0.093 to 0.414] to -0.346 [95% CI: -0.632 to -0.060] after BAT in patients with systolic ABP decrease of ≥5 mm Hg. These data emphasized potential nephroprotective effects of BAT in patients with sufficient BP response.

Noninvasive diagnosis of chronic kidney diseases using urinary proteome analysis

Background

In spite of its invasive nature and risks, kidney biopsy is currently required for precise diagnosis of many chronic kidney diseases (CKDs). Here, we explored the hypothesis that analysis of the urinary proteome can discriminate different types of CKD irrespective of the underlying mechanism of disease.

Methods

We used data from the proteome analyses of 1180 urine samples from patients with different types of CKD, generated by capillary electrophoresis coupled to mass spectrometry. A set of 706 samples served as the discovery cohort, and 474 samples were used for independent validation. For each CKD type, peptide biomarkers were defined using statistical analysis adjusted for multiple testing. Potential biomarkers of statistical significance were combined in support vector machine (SVM)-based classifiers.

Results

For seven different types of CKD, several potential urinary biomarker peptides (ranging from 116 to 619 peptides) were defined and combined into SVM-based classifiers specific for each CKD. These classifiers were validated in an independent cohort and showed good to excellent accuracy for discrimination of one CKD type from the others (area under the receiver operating characteristic curve ranged from 0.77 to 0.95). Sequence analysis of the biomarkers provided further information that may clarify the underlying pathophysiology.

Conclusions

Our data indicate that urinary proteome analysis has the potential to identify various types of CKD defined by pathological assessment of renal biopsies and current clinical practice in general. Moreover, these approaches may provide information to model molecular changes per CKD.

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.

Pro: urine proteomics as a liquid kidney biopsy: no more kidney punctures!

In this article, the benefits of urinary proteomics in comparison with kidney biopsy are discussed. The majority of urinary proteins are generated by the kidney, hence the urinary proteome holds substantial information on the kidney, and assessment of the urinary proteome could be considered a 'liquid biopsy'. The main question is how well the information contained in the urinary proteome can be assessed today, if it is ready to be routinely used, and what are the advantages and possible disadvantages in comparison with current standards. Since chronic kidney disease (CKD) is by far the largest area in nephrology based on the number of patients affected, the focus of this article is on CKD. Substantial progress was made in the last decade in urinary proteomics, and today we have comparable urinary proteome datasets of tens of thousands of subjects available. Clinical proteomics studies in CKD including close to, or even exceeding, 1000 subjects have recently been published, demonstrating a benefit over the current state-of-the-art in diagnosis and especially prognosis. The first large multicentric randomized controlled intervention trial aiming at preventing CKD by employing urinary proteomics-guided intervention has been initiated recently. These data provide ample evidence for the utility and value of urinary proteomics in nephrology. A further consideration is that the purpose of the biopsy, be it 'liquid' or 'solid', is to guide intervention. However, essentially all drug targets are proteins, not microscopic structures. Therefore, obtaining information on the proteome to guide intervention appears to be the most appropriate approach. Presenting more detailed evidence, I argue that urinary proteome analysis can, in most cases, be employed to guide therapeutic intervention, can be repeated multiple times as it is without any direct risk or discomfort and can be considered as a liquid biopsy.

The Origin and Activities of IgA1-Containing Immune Complexes in IgA Nephropathy

IgA nephropathy (IgAN) is the most common primary glomerulonephritis, frequently leading to end-stage renal disease, as there is no disease-specific therapy. IgAN is diagnosed from pathological assessment of a renal biopsy specimen based on predominant or codominant IgA-containing immunodeposits, usually with complement C3 co-deposits and with variable presence of IgG and/or IgM. The IgA in these renal deposits is galactose-deficient IgA1, with less than a full complement of galactose residues on the O-glycans in the hinge region of the heavy chains. Research from the past decade led to the definition of IgAN as an autoimmune disease with a multi-hit pathogenetic process with contributing genetic and environmental components. In this process, circulating galactose-deficient IgA1 (autoantigen) is bound by antiglycan IgG or IgA (autoantibodies) to form immune complexes. Some of these circulating complexes deposit in glomeruli, and thereby activate mesangial cells and induce renal injury through cellular proliferation and overproduction of extracellular matrix components and cytokines/chemokines. Glycosylation pathways associated with production of the autoantigen and the unique characteristics of the corresponding autoantibodies in patients with IgAN have been uncovered. Complement likely plays a significant role in the formation and the nephritogenic activities of these complexes. Complement activation is mediated through the alternative and lectin pathways and probably occurs systemically on IgA1-containing circulating immune complexes as well as locally in glomeruli. Incidence of IgAN varies greatly by geographical location; the disease is rare in central Africa but accounts for up to 40% of native-kidney biopsies in eastern Asia. Some of this variation may be explained by genetically determined influences on the pathogenesis of the disease. Genome-wide association studies to date have identified several loci associated with IgAN. Some of these loci are associated with the increased prevalence of IgAN, whereas others, such as deletion of complement factor H-related genes 1 and 3, are protective against the disease. Understanding the molecular mechanisms and genetic and biochemical factors involved in formation and activities of pathogenic IgA1-containing immune complexes will enable the development of future disease-specific therapies as well as identification of non-invasive disease-specific biomarkers.

Prognostic clinical and molecular biomarkers of renal disease in type 2 diabetes

Diabetic kidney disease occurs in ∼ 25-40% of patients with type 2 diabetes. Given the high risk of progressive renal function loss and end-stage renal disease, early identification of patients with a renal risk is important. Novel biomarkers may aid in improving renal risk stratification. In this review, we first focus on the classical panel of albuminuria and estimated glomerular filtration rate as the primary clinical predictors of renal disease and then move our attention to novel biomarkers, primarily concentrating on assay-based multiple/panel biomarkers, proteomics biomarkers and metabolomics biomarkers. We focus on multiple biomarker panels since the molecular processes of renal disease progression in type 2 diabetes are heterogeneous, rendering it unlikely that a single biomarker significantly adds to clinical risk prediction. A limited number of prospective studies of multiple biomarkers address the predictive performance of novel biomarker panels in addition to the classical panel in type 2 diabetes. However, the prospective studies conducted so far have small sample sizes, are insufficiently powered and lack external validation. Adequately sized validation studies of multiple biomarker panels are thus required. There is also a paucity of studies that assess the effect of treatments on novel biomarker panels and determine whether initial treatment-induced changes in novel biomarkers predict changes in long-term renal outcomes. Such studies can not only improve our healthcare but also our understanding of the mechanisms of actions of existing and novel drugs and may yield biomarkers that can be used to monitor drug response. We conclude that this will be an area to focus research on in the future.

Body fluid peptide and protein signatures in diabetic kidney diseases

Body fluid protein-based biomarkers carry the hope of improving patient management in diabetes by enabling more accurate and earlier detection of diabetic kidney disease (DKD), but also of defining the most suitable therapeutic targets. We present the data on some of the best studied individual protein markers in body fluids and conclude that their potential in clinical application for assessing DKD is moderate. Proteome-based approaches aiming at the identification of panels of body fluid biomarkers might be a valid alternative. We discuss the past (first) clinical proteomics studies in DKD, stressing their drawbacks but also the lessons that could be learned from them, as well as the more recent studies that have a potential for actual clinical implementation. We also highlight relevant issues and current problems associated with clinical proteomics from discovery towards application, and give suggestions for solutions that may help guiding proteomic studies, thereby removing some of the current hurdles for implementation of potentially beneficial results.

Identification of urinary proteins potentially associated with diabetic kidney disease

Diabetic nephropathy (DN) is the most common cause of chronic kidney disease. Although several parameters are used to evaluate renal damage, in many instances, there is no pathological change until damage is already advanced. Mass spectrometry-based proteomics is a novel tool to identify newer diagnostic markers. To identify urinary proteins associated with renal complications in diabetes, we collected urine samples from 10 type 2 diabetes patients each with normoalbuminuria, micro- and macro-albuminuria and compared their urinary proteome with that of 10 healthy individuals. Urinary proteins were concentrated, depleted of albumin and five other abundant plasma proteins and in-gel trypsin digested after prefractionation on sodium dodecyl sulfate polyacrylamide gel electrophoresis. The peptides were analyzed using a nanoflow reverse phase liquid chromatography system coupled to linear trap quadrupole-Orbitrap mass spectrometer. We identified large number of proteins in each group, of which many were exclusively present in individual patient groups. A total of 53 proteins were common in all patients but were absent in the controls. The majority of the proteins were functionally binding, biologically involved in metabolic processes, and showed enrichment of alternative complement and blood coagulation pathways. In addition to identifying reported proteins such as α2-HS-glycoprotein and Vitamin D binding protein, we detected novel proteins such as CD59, extracellular matrix protein 1 (ECM1), factor H, and myoglobin in the urine of macroalbuminuria patients. ECM1 and factor H are known to influence mesangial cell proliferation, and CD59 causes microvascular damage by influencing membrane attack complex deposition, suggestive their biological relevance to DN. Thus, we have developed a proteome database where various proteins exclusively present in the patients may be further investigated for their role as stage-specific markers and possible therapeutic targets.

Differential urinary glycoproteome analysis of type 2 diabetic nephropathy using 2D-LC-MS/MS and iTRAQ quantification

Background

Diabetic nephropathy (DN) is the leading cause of chronic kidney failure and end-stage kidney disease. More accurate and non-invasive test for the diagnosis and monitoring the progression of DN is urgently needed for the better care of such patients.

Methods

In this study we utilized urinary glycoproteome to discover the differential proteins during the course of type 2 DN. The urinary glycoproteins from normal controls, normalbuminuira, microalbuminura, and macroalbuminuria patients were enriched by concanavalin A (ConA) and analyzed by 2DLC/MS/MS and isobaric tags for relative and absolute quantitation quantification.

Results

A total of 478 proteins were identified and 408 were annotated as N-linked glycoproteins. A total of 72, 107 and 123 differential proteins were identified in normalbuminuria, microalbuminuria and macroalbuminuria, respectively. By bioinformatics analysis, in normalbuminruia state, cell proliferation and cell movement were activated, which might reflect the compensatory phase during the disease development. In micro- and macro-albuminuria, cell death and apoptosis was activated, which might reflect the de-compensatory phase. Pathway analysis showed acute phase proteins, the member of high density lipoprotein and low density lipoprotein proteins were changed, indicating the role of the inflammatory response and lipid metabolism abnormality in the pathogenesis of DN. Six selected differential proteins were validated by Western Blot. Alpha-1-antitrypsin (SERPINA1) and Ceruloplasmin are the two markers with excellent area under curve values (0.929 and 1.000 respectively) to distinguish the microalbuminuria and normalbuminuria. For the first time, we found pro-epidermal growth factor and prolactin-inducible protein were decreased in macroalbuminuria stage, which might reflect the inhibition of cell viability and the activation of cell death in kidney.

Conclusions

Above data indicated that urinary glycoproteome could be useful to distinguish the differences in protein profiles in different stages in DN, which will help better individualized care of patients in DN.

Electronic supplementary material

The online version of this article (doi:10.1186/s12967-015-0712-9) contains supplementary material, which is available to authorized users.

Current peptidomics: applications, purification, identification, quantification, and functional analysis

Peptidomics is an emerging field branching from proteomics that targets endogenously produced protein fragments. Endogenous peptides are often functional within the body-and can be both beneficial and detrimental. This review covers the use of peptidomics in understanding digestion, and identifying functional peptides and biomarkers. Various techniques for peptide and glycopeptide extraction, both at analytical and preparative scales, and available options for peptide detection with MS are discussed. Current algorithms for peptide sequence determination, and both analytical and computational techniques for quantification are compared. Techniques for statistical analysis, sequence mapping, enzyme prediction, and peptide function, and structure prediction are explored.

Proteomic biomarkers in kidney disease: issues in development and implementation

Proteomic biomarkers offer the hope of improving the management of patients with kidney diseases by enabling more accurate and earlier detection of renal pathology than is possible with currently available biomarkers, serum creatinine and urinary albumin. In addition, proteomic biomarkers could also be useful to define the most suitable therapeutic targets in a given patient or disease setting. This Review describes the current status of proteomic and protein biomarkers in the context of kidney diseases. The valuable lessons learned from early clinical studies of potential proteomic biomarkers in kidney disease are presented to give context to the newly identified biomarkers, which have potential for actual clinical implementation. This article also includes an overview of protein-based biomarker candidates that are undergoing development for use in nephrology, focusing on those with the greatest potential for clinical implementation. Relevant issues and problems associated with the discovery, validation and clinical application of proteomic biomarkers are discussed, along with suggestions for solutions that might help to guide the design of future proteomic studies. These improvements might remove some of the current obstacles to the utilization of proteomic biomarkers, with potentially beneficial results.

Type 1 diabetes: entering the proteomic era

During the last decade, a major breakthrough in the field of proteomics has been achieved. This review describes available techniques for proteomic analyses, both gel and non-gel based, particularly concentrating on relative quantification techniques. The principle of the different techniques is discussed, highlighting the advantages and drawbacks of recently available visualization methods in gel-based assays. In addition, recent developments for quantitative analysis in non-gel-based approaches are summarized. This review focuses on applications in Type 1 diabetes. These mainly include proteomic studies on pancreatic islets in animal models and in the human situation. Also discussed are mass spectrometry-based studies on T-cells, and studies on the development of diagnostic markers for diabetic nephropathology by capillary electrophoresis coupled to mass spectrometry.

Release from glomerular overload by the addition of low-dose thiazide in patients with angiotensin receptor blocker-resistant hypertension

BACKGROUND/AIMS

This multicenter, prospective, observational study assessed the renoprotective effects of losartan/thiazide combination therapy in terms of lowering the estimated glomerular filtration rate (eGFR).

METHODS

Adult patients with angiotensin receptor blocker (ARB)-resistant essential hypertension (n = 104) were enrolled and switched to combination therapy with losartan (50 mg/day) and hydrochlorothiazide (12.5 mg/day).

RESULTS

eGFR values declined significantly during the first 3 months, and changes in eGFR were assessed according to tertiles of the eGFR decrease ratio at 3 months. Only the high eGFR decrease (1st tertile) group showed significantly greater decreases in baseline eGFR and albumin-to-creatinine ratio (ACR) during the first 3 months. Additionally, the assessment according to tertiles of the baseline eGFR showed a signifcant decrease in eGFR and ACR during the first 3 months in the high baseline eGFR (1st tertile) group, but not in the moderate (2nd tertile) and low baseline eGFR (3rd tertile) groups.

CONCLUSION

The present results revealed that losartan/thiazide combination therapy attenuated glomerular overload, indicating that this therapy may provide glomerular protection in patients with an elevated GFR without causing prolonged damage to renal function.

Use of proteomic methods in the analysis of human body fluids in Alzheimer research

Proteomics is the study of the entire population of proteins and peptides in an organism or a part of it, such as a cell, tissue, or fluids like cerebrospinal fluid, plasma, serum, urine, or saliva. It is widely assumed that changes in the composition of the proteome may reflect disease states and provide clues to its origin, eventually leading to targets for new treatments. The ability to perform large-scale proteomic studies now is based jointly on recent advances in our analytical methods. Separation techniques like CE and 2DE have developed and matured. Detection methods like MS have also improved greatly in the last 5 years. These developments have also driven the fields of bioinformatics, needed to deal with the increased data production and systems biology. All these developing methods offer specific advantages but also come with certain limitations. This review describes the different proteomic methods used in the field, their limitations, and their possible pitfalls. Based on a literature search in PubMed, we identified 112 studies that applied proteomic techniques to identify biomarkers for Alzheimer disease. This review describes the results of these studies on proteome changes in human body fluids of Alzheimer patients reviewing the most important studies. We extracted a list of 366 proteins and peptides that were identified by these studies as potential targets in Alzheimer research.

Proteome-base biomarkers in diabetes mellitus: progress on biofluids' protein profiling using mass spectrometry

The worldwide number of individuals suffering from diabetes mellitus (DM) has been projected to rise from 171 million in 2000 to 366 million in 2030. Identification of specific biomarkers for prediction and monitoring of DM is needed not only for the adequate screening diagnosis but also to assist the design of interventions to prevent or delay progression of this pathology and its attendant complications. Proteomic methods based on MS hold special promise for the identification of novel biomarkers that might form the foundation for new clinical tests, but to date, their contribution has been somehow unfruitful. Indeed, from more than 300 proteins found differently modulated in body fluids from diabetic patients, approximately 50 were validated with other approaches like ELISA or Western blotting and the clinical trials are being initiated to employ biofluids' proteomics (specifically urinary proteomics) in clinical decision. This review provides an overview of MS-based applications in the identification of potential biomarkers for DM, emphasizing the methodological challenges involved.

Mass spectrometry for diabetic nephropathy monitoring: new effective tools for physicians

The main aim of diabetic nephropathy monitoring is to identify molecular markers, that is, to find changes occurring at metabolome and proteome levels indicative of the disease's development. The mass spectrometry methods available today have been successfully applied to this field. This paper provides a short description of the basic aspects of the mass spectrometric methods used for diabetic nephropathy monitoring, reporting and discussing the results obtained using different approaches.

Searching for new biomarkers of renal diseases through proteomics

BACKGROUND

Technological advances have resulted in a renaissance of proteomic studies directed at finding markers of disease progression, diagnosis, or responsiveness to therapy. Renal diseases are ideally suited for such research, given that urine is an easily accessible biofluid and its protein content is derived mainly from the kidney. Current renal prognostic markers have limited value, and renal biopsy remains the sole method for establishing a diagnosis. Mass spectrometry instruments, which can detect thousands of proteins at nanomolar (or even femtomolar) concentrations, may be expected to allow the discovery of improved markers of progression, diagnosis, or treatment responsiveness.

CONTENT

In this review we describe the strengths and limitations of proteomic methods and the drawbacks of existing biomarkers, and provide an overview of opportunities in the field. We also highlight several proteomic studies of biomarkers of renal diseases selected from the plethora of studies performed.

SUMMARY

It is clear that the field of proteomics has not yet fulfilled its promise. However, ongoing efforts to standardize sample collection and preparation, improve study designs, perform multicenter validations, and create joint industry-regulatory bodies offer promise for the recognition of novel molecules that could change clinical nephrology forever.

Urine proteomics in kidney and urogenital diseases: Moving towards clinical applications

To date, multiple biomarker discovery studies in urine have been conducted. Nevertheless, the rate of progression of these biomarkers to qualification and even more clinical application is extremely low. The scope of this article is to provide an overview of main clinically relevant proteomic findings from urine focusing on kidney diseases, bladder and prostate cancers. In addition, approaches for promoting the use of urine in clinical proteomics including potential means to facilitate the validation of existing promising findings (biomarker candidates identified from previous studies) and to increase the chances for success for the identification of new biomarkers are discussed.

Proteomics in chronic kidney disease: The issues clinical nephrologists need an answer for

A growing number of patients are recognised to have chronic kidney disease (CKD). However, only a minority will progress to end-stage renal disease requiring dialysis or transplantation. Currently available diagnostic and staging tools frequently fail to identify those at higher risk of progression or death. Furthermore within specific disease entities there are shortcomings in the prediction of the need for therapeutic interventions or the response to different forms of therapy. Kidney and urine proteomic biomarkers are considered as promising diagnostic tools to predict CKD progression early in diabetic nephropathy, facilitating timely and selective intervention that may reduce the related health-care expenditures. However, independent groups have not validated these findings and the technique is not currently available for routine clinical care. Furthermore, there are gaps in our understanding of predictors of progression or need for therapy in non-diabetic CKD. Presumably, a combination of tissue and urine biomarkers will be more informative than individual markers. This review identifies clinical questions in need of an answer, summarises current information on proteomic biomarkers and CKD, and describes the European Kidney and Urine Proteomics initiative that has been launched to carry out a clinical study aimed at identifying urinary proteomic biomarkers distinguishing between fast and slow progressors among patients with biopsy-proven primary glomerulopathies.

Some views on proteomics in diabetes

Mass spectrometry has been widely used in the field of diabetes. The development of new ionization methods and the effective coupling of mass spectrometry with liquid chromatography have enabled the protein modifications due to glycation processes to be investigated. Matrix assisted laser desorption/ionization mass spectrometry (MALDI/MS) has been used to evaluate the degree of glycation of specific plasma proteins. In contrast, the classic proteomic approach has been used to identify glycation sites and condensed sugar modifications. The same methods have been applied to studies on urinary protein profiles, enabling changes due to the development of long-term, diabetes-induced nephropathy to be identified. Published studies demonstrate that mass spectrometry is an important analytical tool for monitoring diabetes, capable of providing physicians with a new, more complete view of the physiopathological changes occurring as the disease develops.

Study of urinary proteomes in Anderson-Fabry disease

BACKGROUND

Anderson-Fabry disease (AFD) is an X-linked genetic disorder with deficient α-galactosidase A activity. The main aim of this work was to investigate possible differences in urine proteins between healthy controls and AFD patients and to identify abnormal proteins as potential biomarkers of disease.

MATERIAL AND METHODS

We studied 2D electrophoresis images of urine samples collected from AFD patients and healthy subjects. The proteins were separated using isoelectric focusing method followed by SDS-PAGE. The proteins were then visualized by silver staining and characterized by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS).

RESULTS

We found out that the urinary spectra of all the Fabry disease samples included identical proteins with molecular weight around 20-40 kDa. The concentration of some proteins was more than three times higher in the AFD samples, compared to the controls. The abundant proteins were identified by MALDI-TOF MS and included the following: alpha-1-antitrypsin, alpha-1-microglobulin, prostaglandin H2 d-isomerase, complement-c1q tumor necrosis factor-related protein, and Ig kappa chain V-III. Possible glycosylation at Asn51 and Asn78 sites of the prostaglandin H2 d-isomerase was detected.

CONCLUSIONS

AFD urinary proteomics revealed increased secretion of several proteins. We postulate that the observed difference in the amount of prostaglandin H2 d-isomerase and its position on two-dimensional gels might be related to different glycosylation in AFD subjects.

Urinary proteome analysis enables assessment of renoprotective treatment in type 2 diabetic patients with microalbuminuria

Background

Previously the angiotensin II receptor blocker Irbesartan has been demonstrated to reduce the risk for progression from microalbuminuria to macroalbuminuria in type 2 diabetic patients. The purpose of this study was to evaluate the effect of treatment with Irbesartan in type 2 diabetic patients with microalbuminuria on the urinary proteome.

Methods

High-resolution capillary-electrophoresis coupled to mass-spectrometry (CE-MS) was used to profile the low-molecular-weight proteome in urine of a subgroup of patients from a two year randomized irbesartan versus placebo therapy trial, which included hypertensive type 2 diabetic patients with microalbuminuria on ongoing antihypertensive medication (IRMA2-substudy).

Results

We demonstrate that the therapy with 300 mg Irbesartan daily over a period of two years results in significant changes of the urinary proteome. Both, a classifier developed previously that consists of urinary peptides indicative of chronic kidney disease, as well as several individual peptides changed significantly after treatment. These changes were not observed in the placebo-treated individuals. Most prominent are changes of urinary collagen fragments associated with progression of diabetic nephropathy, indicating normalization in urinary peptides.

Conclusion

CE-MS analysis of urine enabled identification of peptides as potential surrogate markers for renoprotection in microalbuminuric type 2 diabetic patients, which show persistent improvement after longterm treatment with Irbesartan. The results suggest that a major benefit of treatment by Irbesartan may be improvement of collagen turnover, reduction of fibrosis. They further suggest that urinary proteome analysis could be utilized to assess potential benefit of therapeutic intervention, providing statistically significant results even on a small population.

Multicentric validation of proteomic biomarkers in urine specific for diabetic nephropathy

Background

Urine proteome analysis is rapidly emerging as a tool for diagnosis and prognosis in disease states. For diagnosis of diabetic nephropathy (DN), urinary proteome analysis was successfully applied in a pilot study. The validity of the previously established proteomic biomarkers with respect to the diagnostic and prognostic potential was assessed on a separate set of patients recruited at three different European centers. In this case-control study of 148 Caucasian patients with diabetes mellitus type 2 and duration ≥5 years, cases of DN were defined as albuminuria >300 mg/d and diabetic retinopathy (n = 66). Controls were matched for gender and diabetes duration (n = 82).

Methodology/Principal Findings

Proteome analysis was performed blinded using high-resolution capillary electrophoresis coupled with mass spectrometry (CE-MS). Data were evaluated employing the previously developed model for DN. Upon unblinding, the model for DN showed 93.8% sensitivity and 91.4% specificity, with an AUC of 0.948 (95% CI 0.898-0.978). Of 65 previously identified peptides, 60 were significantly different between cases and controls of this study. In <10% of cases and controls classification by proteome analysis not entirely resulted in the expected clinical outcome. Analysis of patient's subsequent clinical course revealed later progression to DN in some of the false positive classified DN control patients.

Conclusions

These data provide the first independent confirmation that profiling of the urinary proteome by CE-MS can adequately identify subjects with DN, supporting the generalizability of this approach. The data further establish urinary collagen fragments as biomarkers for diabetes-induced renal damage that may serve as earlier and more specific biomarkers than the currently used urinary albumin.

Urine peptidomics for clinical biomarker discovery

Urine-based proteomic profiling is a novel approach that may result in the discovery of noninvasive biomarkers for diagnosing patients with different diseases, with the aim to ultimately improve clinical outcomes. Given new and emerging analytical technologies and data mining algorithms, the urine peptidome has become a rich resource to uncover naturally occurring peptide biomarkers for both systemic and renal diseases. However, significant analytical hurdles remain in sample collection and storage, experimental design, data analysis, and statistical inference. This study summarizes, focusing on our experiences and perspectives, the progress in addressing these challenges to enable high-throughput urine peptidomics-based biomarker discovery.

Naturally occurring human urinary peptides for use in diagnosis of chronic kidney disease

Because of its availability, ease of collection, and correlation with physiology and pathology, urine is an attractive source for clinical proteomics/peptidomics. However, the lack of comparable data sets from large cohorts has greatly hindered the development of clinical proteomics. Here, we report the establishment of a reproducible, high resolution method for peptidome analysis of naturally occurring human urinary peptides and proteins, ranging from 800 to 17,000 Da, using samples from 3,600 individuals analyzed by capillary electrophoresis coupled to MS. All processed data were deposited in an Structured Query Language (SQL) database. This database currently contains 5,010 relevant unique urinary peptides that serve as a pool of potential classifiers for diagnosis and monitoring of various diseases. As an example, by using this source of information, we were able to define urinary peptide biomarkers for chronic kidney diseases, allowing diagnosis of these diseases with high accuracy. Application of the chronic kidney disease-specific biomarker set to an independent test cohort in the subsequent replication phase resulted in 85.5% sensitivity and 100% specificity. These results indicate the potential usefulness of capillary electrophoresis coupled to MS for clinical applications in the analysis of naturally occurring urinary peptides.

Urinary biomarkers involved in type 2 diabetes: a review

Diabetes mellitus is one of the most challenging health concerns of the 21st century. With at least 30% of the diabetic population remaining undiagnosed, effective and early diagnosis is of critical concern. Development of a diagnostic test, more convenient and reliable than those currently used, would therefore be highly beneficial. Urine as a diagnostic medium allows for non-invasive detection of biomarkers, including some associated with type 2 diabetes and its complications. This review provides a synopsis of those urinary biomarkers that potentially may provide a basis for the development of improved diagnostic tests. Three main pathways for the sourcing of potential makers are identified: kidney damage, oxidative stress and low-grade inflammation including atherosclerosis/vascular damage. This review briefly presents each pathway and some of the most relevant urinary biomarkers that may be used to monitor the development or progression of diabetes and its complications. In particular, biomarkers of renal dysfunction such as transferrin, type IV collagen and N-acetyl-beta-D-glucosaminidase might prove to be more sensitive than urinary albumin, the current gold standard, in the detection of incipient nephropathy and risk assessment of cardiovascular disease. Inflammatory markers including orosomucoid, tumour necrosis factor-alpha, transforming growth factor-beta, vascular endothelial growth factor and monocyte chemoattractant protein-1, as well as oxidative stress markers such as 8-hydroxy-2'deoxyguanosine may also be useful biomarkers for diagnosis or monitoring of diabetic complications, particularly kidney disease. However, the sensitivity of these markers compared with albumin requires further investigation.