Identification of urinary protein pattern in type 1 diabetic adolescents with early diabetic nephropathy by a novel combined proteome analysis

Proteomic and bioinformatic discovery of biomarkers for diabetic nephropathy

Diabetes is associated with numerous metabolic and vascular risk factors that contribute to a high rate of micro-vascular and macro-vascular disorders leading to mortality and morbidity from diabetic complications. In this case, the major cause of death in overall diabetic patients results from diabetic nephropathy (DN) or renal failure. The risk factors and mechanisms that correspond to the development of DN are not fully understood and so far, no specific and sufficient diagnostic biomarkers are currently available other than micro- or macroalbuminuria. Therefore, this review describes current and novel protein biomarkers in the context of DN as well as probable proteins biomarkers associated with pathological processes for the early stage of DN via proteomics data together with bioinformatics. In addition, the mechanisms involved in early development of diabetic vascular disorders and complications resulting from glucose induced oxidative stress will also be explored.

Pediatric endocrine and metabolic diseases and proteomics

The principles of Predictive, Preventive and Personalized Medicine (PPPM) dictate the need to recognize individual susceptibility to disease in a timely fashion and to offer targeted preventive interventions and treatments. Proteomics is a state-of-the art technology- driven science aiming at expanding our understanding of the pathophysiologic mechanisms that underlie disease, but also at identifying accurate predictive, diagnostic and therapeutic biomarkers, that will eventually promote the implementation of PPPM. In this review, we summarize the wide spectrum of the applications of Mass Spectrometry-based proteomics in the various fields of Pediatric Endocrinology, including Inborn Errors of Metabolism, type 1 diabetes, Adrenal Disease, Metabolic Syndrome and Thyroid disease, ranging from neonatal screening to early recognition of specific at-risk populations for disease manifestations or complications in adult life and to monitoring of disease progression and response to treatment.

SIGNIFICANCE

Proteomics is a state-of-the art technology- driven science aiming at expanding our understanding of the pathophysiologic mechanisms that underlie disease, but also at identifying accurate predictive, diagnostic and therapeutic biomarkers that will eventually lead to successful, targeted, patient-centric, individualized approach of each patient, as dictated by the principles of Predictive, Preventive and Personalized Medicine. In this review, we summarize the wide spectrum of the applications of Mass Spectrometry-based proteomics in the various fields of Pediatric Endocrinology, including Inborn Errors of Metabolism, type 1 diabetes, Adrenal Disease, Metabolic Syndrome and Thyroid disease, ranging from neonatal screening, accurate diagnosis, early recognition of specific at-risk populations for the prevention of disease manifestation or future complications.

Insights into Diabetic Kidney Disease Using Urinary Proteomics and Bioinformatics

A number of proteomic and peptidomic analyses of urine from diabetic subjects have been published in the quest for a biomarker that predicts progression of nephropathy. Less attention has been paid to the relationships between urinary proteins and the underlying biological processes revealed by the analyses. In this review, we focus on the biological processes identified by studying urinary proteins and protein-protein interactions at each stage of diabetic nephropathy to provide an overview of the events underlying progression of kidney disease reflected in the urine. In uncomplicated diabetes, proteomic/peptidomic analyses indicate that early activation of fibrotic pathways in the kidney occurs before the onset of microalbuminuria. In incipient nephropathy, when albumin excretion rates are abnormal, proteomic/peptidomic analyses suggest that changes in glomerular permselectivity and tubular reabsorption account, at least in part, for the proteins and peptides that appear in the urine. Finally, overt nephropathy is characterized by proteins involved in wound healing, ongoing fibrosis, and inflammation. These findings suggest that there is a spectrum of biological processes in the diabetic kidney and that assessing protein networks may be more informative than individual markers with respect to the stage of disease and the risk of progression.

The progress and potential of proteomic biomarkers for type 1 diabetes in children

INTRODUCTION

Although it is possible to identify the genetic risk for type 1 diabetes (T1D), it is not possible to predict who will develop the disease. New biomarkers are needed that would help understand the mechanisms of disease onset and when to administer targeted therapies and interventions. Areas covered: An overview is presented of international study efforts towards understanding the cause of T1D, including the collection of several extensive temporal sample series that follow the development of T1D in at risk children. The results of the proteomics analysis of these materials are presented, which have included bodily fluids, such as serum or plasma and urine, as well as tissue samples from the pancreas. Expert commentary: Promising recent reports have indicated detection of early proteomic changes in the serum of patients prior to diagnosis, potentially providing new measures for risk assessment. Similarly, there has been evidence that post-translational modification (PTM) may result in the recognition of islet cell proteins as autoantigens; modified proteins could thus be used as targets for immunomodulation to overcome the threat of the autoimmune response.

Urinary Proteomics for Diagnosis and Monitoring of Diabetic Nephropathy

The last decade has seen a surge in publications describing novel biomarkers for early detection of diabetic nephropathy (DN), but as yet none have outperformed albuminuria in well-designed prospective studies. This is partially attributable to our incomplete understanding of the many complex interrelated mechanisms underlying DN development, a heterogeneous process unlikely to be captured by a single biomarker. Proteomics offers the advantage of simultaneously analysing the entire protein content of a biological sample, and the technique has gained attention as a potential tool for a more accurate diagnosis of disease at an earlier stage as well as a means by which to unravel the pathogenesis of complex diseases such as DN using an untargeted approach. This review will discuss the potential of proteomics as both a clinical and research tool, evaluating exploratory work in animal models as well as diagnostic potential in human subjects.

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.

State-of-the-art nanoplatform-integrated MALDI-MS impacting resolutions in urinary proteomics

Urine proteomics has become a subject of interest, since it has led to a number of breakthroughs in disease diagnostics. Urine contains information not only from the kidney and the urinary tract but also from other organs, thus urinary proteome analysis allows for identification of biomarkers for both urogenital and systemic diseases. The following review gives a brief overview of the analytical techniques that have been in practice for urinary proteomics. MALDI-MS technique and its current application status in this area of clinical research have been discussed. The review comments on the challenges facing the conventional MALDI-MS technique and the upgradation of this technique with the introduction of nanotechnology. This review projects nano-based techniques such as nano-MALDI-MS, surface-assisted laser desorption/ionization, and nanostructure-initiator MS as the platforms that have the potential in trafficking MALDI-MS from the lab to the bedside.

Early diabetic nephropathy in type 1 diabetes: new insights

PURPOSE OF REVIEW

Despite improvements in glycemic and blood pressure control in patients with type 1 diabetes, diabetic nephropathy remains the most common cause of chronic kidney disease worldwide. A major challenge in preventing diabetic nephropathy is the inability to identify high-risk patients at an early stage, emphasizing the importance of discovering new therapeutic targets and implementation of clinical trials to reduce diabetic nephropathy risk.

RECENT FINDINGS

Limitations of managing patients with diabetic nephropathy with renin-angiotensin-aldosterone system blockade have been identified in recent clinical trials, including the failure of primary prevention studies in T1D and the demonstration of harm with dual renin-angiotensin-aldosterone system blockade. Fortunately, several new targets, including serum uric acid, insulin sensitivity, vasopressin, and sodium-glucose cotransporter-2 inhibition, are promising in the prevention and treatment of diabetic nephropathy.

SUMMARY

Diabetic nephropathy is characterized by a long clinically silent period without signs or symptoms of disease. There is an urgent need for improved methods of detecting early mediators of renal injury, to ultimately prevent the initiation and progression of diabetic nephropathy. In this review, we will focus on early diabetic nephropathy and summarize potential new therapeutic targets.

Hyperglycemia decreases the expression of ATP synthase β subunit and enolase 2 in glomerular epithelial cells

Glomerular epithelial cells (GECs) are known to play a key role in maintaining the structure and function of the glomerulus. GEC injury induced by hyperglycemia is present in early-stage diabetic nephropathy (DN), which is the most common cause of renal failure. In an attempt to identify target proteins involved in the pathogenesis of GEC injury at early DN, we performed the proteomic analysis using primary cultures of GECs, prepared from the dissected rat glomeruli. The protein expression profiles in the two-dimensional electrophoresis gels were compared between GECs treated for three days with normal glucose (5 mM) and those with high glucose (30 mM) concentrations. These concentrations correspond to blood glucose concentrations under normoglycemia and hyperglycemia, respectively. Proteins with differential expression levels were identified using ESI-Q-TOF tandem mass spectrometry. The primary GECs cultured in hyperglycemic conditions showed cellular hypertrophy and increased production of reactive oxygen species, both of which reflect the GEC injury. Our proteomic analysis identified eight proteins with differential expression profiles, depending on glucose concentrations. Among them, we selected ATP synthase β subunit and enolase 2 that are related to energy metabolism and are down-regulated under hyperglycemia, and confirmed that hyperglycemia decreased the expression levels of ATP synthase β subunit and enolase 2 proteins by western blotting analysis. Hyperglycemia may impair mitochondrial function and alter glycolysis in GECs by down-regulating the expression of ATP synthase β subunit and enolase 2. The present study may provide a better understanding of the pathogenic mechanisms of GEC injury in early DN.

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.

Classical MALDI-MS versus CE-based ESI-MS proteomic profiling in urine for clinical applications

Human urine is an attractive and informative biofluid for medical diagnosis, which has been shown to reflect the (patho)-physiology of not only the urogenital system, but also others such as the cardiovascular system. For this reason, many studies have concentrated on the study of the urine proteome, aiming to find relevant biomarkers that could be applied in a clinical setting. However, this goal can only be achieved after reliable quantitative and qualitative analysis of the urinary proteome. In the last two decades, MS-based platforms have evolved to become indispensable tools for biomarker research. In this review, we will present and compare two of the most clinically relevant analytical platforms that have been used for the study of the urinary proteome, namely CE-based ESI-MS and classical MALDI-MS. These platforms, although not directly comparable, have been extensively used in proteomic profiling and therefore their comparison is fundamentally relevant to this field.

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.

Proteomics and systems biology for understanding diabetic nephropathy

Like many diseases, diabetic nephropathy is defined in a histopathological context and studied using reductionist approaches that attempt to ameliorate structural changes. Novel technologies in mass spectrometry-based proteomics have the ability to provide a deeper understanding of the disease beyond classical histopathology, redefine the characteristics of the disease state, and identify novel approaches to reduce renal failure. The goal is to translate these new definitions into improved patient outcomes through diagnostic, prognostic, and therapeutic tools. Here, we review progress made in studying the proteomics of diabetic nephropathy and provide an introduction to the informatics tools used in the analysis of systems biology data, while pointing out statistical issues for consideration. Novel bioinformatics methods may increase biomarker identification, and other tools, including selective reaction monitoring, may hasten clinical validation.

The renal transcriptome of db/db mice identifies putative urinary biomarker proteins in patients with type 2 diabetes: a pilot study

We sought to identify novel urinary biomarkers of kidney function in type 2 diabetes. We screened the renal transcriptome of db/db and db/m mice for differentially expressed mRNA transcripts that encode secreted proteins with human orthologs. Whether elevated urine levels of the orthologous proteins correlated with diminished glomerular filtration rate was tested in a cross-sectional study of n = 56 patients with type 2 diabetes. We identified 36 putative biomarker genes in db/db kidneys: 31 upregulated and 5 downregulated. Urinary protein levels of six selected candidates (endothelin-1, lipocalin-2, transforming growth factor-β, growth and differentiation factor-15, interleukin-6, and macrophage chemoattractant protein-1) were elevated in type 2 diabetic patients with subnormal glomerular filtration rate (i.e., <90 ml·min(-1)·1.73 m(-2)), independent of microalbuminuria, age, sex, race, and use of angiotensin-converting enzyme inhibitors and angiotensin receptor antagonists. In contrast, urinary levels of fibroblast growth factor were not increased. A composite variable of urine albumin and any of the six candidate markers was associated with subnormal estimated glomerular filtration rate more closely than albumin alone. In addition, urinary endothelin-1, growth and differentiation factor-15, and interleukin-6 were associated with a marker of proximal tubule damage, N-acetyl-β-d-glucosaminidase activity. These results suggest that gene expression profiling in diabetic mouse kidney can complement existing proteomic-based approaches for renal biomarker discovery in humans.

Systems biology of kidney diseases

Kidney diseases manifest in progressive loss of renal function, which ultimately leads to complete kidney failure. The mechanisms underlying the origins and progression of kidney diseases are not fully understood. Multiple factors involved in the pathogenesis of kidney diseases have made the traditional candidate gene approach of limited value toward full understanding of the molecular mechanisms of these diseases. A systems biology approach that integrates computational modeling with large-scale data gathering of the molecular changes could be useful in identifying the multiple interacting genes and their products that drive kidney diseases. Advances in biotechnology now make it possible to gather large data sets to characterize the role of the genome, epigenome, transcriptome, proteome, and metabolome in kidney diseases. When combined with computational analyses, these experimental approaches will provide a comprehensive understanding of the underlying biological processes. Multiscale analysis that connects the molecular interactions and cell biology of different kidney cells to renal physiology and pathology can be utilized to identify modules of biological and clinical importance that are perturbed in disease processes. This integration of experimental approaches and computational modeling is expected to generate new knowledge that can help to identify marker sets to guide the diagnosis, monitor disease progression, and identify new therapeutic targets.

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.

Proteomic analysis of urinary exosomes from patients of early IgA nephropathy and thin basement membrane nephropathy

To identify biomarker candidates associated with early IgA nephropathy (IgAN) and thin basement membrane nephropathy (TBMN), the most common causes presenting isolated hematuria in childhood, a proteomic approach of urinary exosomes from early IgAN and TBMN patients was introduced. The proteomic results from the patients were compared with a normal group to understand the pathophysiological processes associated with these diseases at the protein level. The urinary exosomes, which reflect pathophysiological processes, collected from three groups of young adults (early IgAN, TBMN, and normal) were trypsin-digested using a gel-assisted protocol, and quantified by label-free LC-MS/MS, using an MS(E) mode. A total of 1877 urinary exosome proteins, including cytoplasmic, membrane, and vesicle trafficking proteins, were identified. Among the differentially expressed proteins, four proteins (aminopeptidase N, vasorin precursor, α-1-antitrypsin, and ceruloplasmin) were selected as biomarker candidates to differentiate early IgAN from TBMN. We confirmed the protein levels of the four biomarker candidates by semi-quantitative immunoblot analysis in urinary exosomes independently prepared from other patients, including older adult groups. Further clinical studies are needed to investigate the diagnostic and prognostic value of these urinary markers for early IgAN and TBMN. Taken together, this study showed the possibility of identifying biomarker candidates for human urinary diseases using urinary exosomes and might help to understand the pathophysiology of early IgAN and TBMN at the protein level.

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.

Urinary peptides as a diagnostic tool for renal failure detected by matrix-assisted laser desorption/ionisation mass spectrometry: an evaluation of their clinical significance

The development of new analytical methodologies related to the proteome for the evaluation of renal physiology and pathology is surely of wide interest for physicians, giving them new tools for monitoring complications associated with diabetes, such as end-stage renal disease. In the present study, the clinical significance of the urinary abundance of two peptides, SGSVIDQSRVLNLGPITR (the uromodulin precursor, m/z 1912) and IGPHypGPHypGLMGPP [present in the collagen-α-5(IV) chain precursor, m/z 1219], detected by matrix- assisted laser desorption/ionisation mass spectrometry (MALDI/MS) in microalbuminuric or nephropathic diabetic patients and in non-diabetic nephropathic patients was evaluated. A progressive increase in the abundance of the ion at m/z 1219 and a decrease in the abundance of the ion at m/z 1912 have been found in diabetic microalbuminuric, diabetic-nephropathic and nephropathic patients. Linear correlations are present between serum creatinine values and the abundances of the ions at m/z 1219 (positive correlation, r=0.3645, P<0.0001) and at m/z 1912 (negative correlation, r=-0.3053, P<0.0005). Correlations between the MALDI data and the estimated glomerular filtration rate were also found, while relationships with urinary albumin excretion were found only in sub-sets of patients. Analysis of receiver operating characteristic curves showed a sensitivity up to 96% and a specificity of up to 84% for the two ionic species, or their ratio, for distinguishing diabetic patients with different degrees of nephropathy from healthy subjects, proving that the urinary abundance of the two peptides at m/z 1219 and m/z 1912, determined with MALDI/MS, may be considered as a possible diagnostic tool for the determination of progression toward renal failure, also with the aim of monitoring kidney function, in diabetic patients.

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.

Urinary collagen fragments are significantly altered in diabetes: a link to pathophysiology

Background

The pathogenesis of diabetes mellitus (DM) is variable, comprising different inflammatory and immune responses. Proteome analysis holds the promise of delivering insight into the pathophysiological changes associated with diabetes. Recently, we identified and validated urinary proteomics biomarkers for diabetes. Based on these initial findings, we aimed to further validate urinary proteomics biomarkers specific for diabetes in general, and particularity associated with either type 1 (T1D) or type 2 diabetes (T2D).

Methodology/Principal Findings

Therefore, the low-molecular-weight urinary proteome of 902 subjects from 10 different centers, 315 controls and 587 patients with T1D (n = 299) or T2D (n = 288), was analyzed using capillary-electrophoresis mass-spectrometry. The 261 urinary biomarkers (100 were sequenced) previously discovered in 205 subjects were validated in an additional 697 subjects to distinguish DM subjects (n = 382) from control subjects (n = 315) with 94% (95% CI: 92–95) accuracy in this study. To identify biomarkers that differentiate T1D from T2D, a subset of normoalbuminuric patients with T1D (n = 68) and T2D (n = 42) was employed, enabling identification of 131 biomarker candidates (40 were sequenced) differentially regulated between T1D and T2D. These biomarkers distinguished T1D from T2D in an independent validation set of normoalbuminuric patients (n = 108) with 88% (95% CI: 81–94%) accuracy, and in patients with impaired renal function (n = 369) with 85% (95% CI: 81–88%) accuracy. Specific collagen fragments were associated with diabetes and type of diabetes indicating changes in collagen turnover and extracellular matrix as one hallmark of the molecular pathophysiology of diabetes. Additional biomarkers including inflammatory processes and pro-thrombotic alterations were observed.

Conclusions/Significance

These findings, based on the largest proteomic study performed to date on subjects with DM, validate the previously described biomarkers for DM, and pinpoint differences in the urinary proteome of T1D and T2D, indicating significant differences in extracellular matrix remodeling.

Urinary proteomics--a tool for biomarker discovery

The strong need for the discovery of novel disease markers together with the development of high-throughput techniques that provide highly sensitive analysis of protein content in tissues and bodily fluids, using proteomics, has opened the completely new chapter in biomarker discovery. The detection of biomarkers based on urinary proteome analysis is rapidly advancing and may provide new tools to improve non-invasive diagnostics, prognostics, and therapy enhancement. As a tool for biomarker discovery, urinary proteomics is especially fruitful in the area of early diagnostics and differentiation of renal damage, and it possesses enormous potential for improving and expanding non-invasive cancer diagnostics. An abundance of urinary proteins could provide a wide variety of biomarkers for the diagnosis and follow-up of many systemic diseases as well. This article reviews the utility of urinary proteomics for biomarker discovery from the perspective of clinical application. Despite huge potential and prompt development of urinary proteomics, many challenges are still in front of us. Research effort and financial investment have to be oriented on providing strategies for exceeding current methodological and technical obstacles in a way to ensure the successful validation and implementation of newly discovered urinary biomarkers. The result is expected to be the development of new non-invasive tests and procedures able to guarantee higher efficiency of patient care and provide needed personalized medical approach.

Advances in urinary proteome analysis and biomarker discovery in pediatric renal disease

Recent progress in proteomic analysis and strategies for the identification of clinically useful biomarkers in biofluids has led to the identification of urine as an excellent non-invasive reservoir for biomarkers of disease. Urinary biomarkers have been identified and validated on independent cohorts in different high-incidence adult renal diseases, including diabetic nephropathy, chronic kidney disease and immunoglobulin A-nephropathy, but also in extrarenal disease, such as coronary artery disease. Unfortunately, this type of research is underrepresented in the pediatric population. Here, we present the rare studies in the pediatric population that identified potential clinically useful urinary biomarkers in ureteropelvic junction (UPJ) obstruction and renal Fanconi syndrome. These studies, although limited in number, clearly show the potential of urinary proteomics, especially in the pediatric population. It is anticipated that the advances made in the adult population, the lessons learned on the use of appropriate statistics and the inclusion of independent blinded validation cohorts in these types of studies will rapidly lead to clinical useful urinary biomarkers for other pediatric (renal) disease in a population where non-invasive analysis is particularly appreciated.

The natural progression of kidney injury in young type 1 diabetic patients

Diabetes is the most common cause of end-stage renal disease in industrialized countries. This article describes the structural changes in early diabetic nephropathy and the relationship with renal functional parameters, blood pressure, and albumin excretion. The detrimental influence of sustained hyperglycemia and/or glycemic fluctuations on renal structural change has been well documented. Tight glycemic control is paramount to preventing the development, and even the regression, of renal lesions. As much of the renal injury from diabetes occurs in clinical silence before symptoms or laboratory findings of renal injury are evident, finding early markers of risk is imperative so that nephropathy can be prevented. Currently, the only clinical surrogate marker of diabetic renal injury available is microalbuminuria. However, given the reports of regression of microalbuminuria back to normoalbuminuria, the reliability of this tool as an indicator of risk has been questioned. The need for alternative, noninvasive surrogate markers is described in this report.

A further investigation on a MALDI-based method for evaluation of markers of renal damage

The validity of the urinary protein profile to characterize the pathological states of diabetic, nephropathic and diabetic-nephropathic patients was considered on the basis of previously obtained results by MALDI/MS, showing a different abundance ratio of the collagen alpha1 and alpha5 chain precursor fragments at m/z 1219 and 2049 and of the uromodulin precursor fragment at m/z 1912 observed in healthy subjects and patients; a larger number of subjects was examined and the obtained results were statistically evaluated. The p values related to the observed differences indicate that they are statistically significant when comparing all patients versus healthy controls, diabetic with normo or microalbuminuria versus nephropathic with advanced renal disease patients and diabetic with normo or microalbuminuria versus diabetic with advanced nephropathy patients. The scatter plot matrix gives evidence of the strict inverse relationship between the abundances of ions at m/z 1912 and 1219, the correlation coefficient being particularly high (r = 0.921, p < 0.001). The relationship between the true positive rate (sensitivity) and false positive rate (1-specificity) for every possible cutoff value in abundance of the considered ionic species was investigated through the receiver-operating characteristic (ROC) curve. The obtained data indicate that a good differentiation of nephropathic patients with advanced renal disease and diabetic patients with advanced nephropathy versus healthy subjects can be easily obtained by this approach.

Urinary Proteome Analysis using Capillary Electrophoresis Coupled to Mass Spectrometry: A Powerful Tool in Clinical Diagnosis, Prognosis and Therapy Evaluation

Proteome analysis has emerged as a powerful tool to decipher (patho) physiological processes, resulting in the establishment of the field of clinical proteomics. One of the main goals is to discover biomarkers for diseases from tissues and body fluids. Due to the enormous complexity of the proteome, a separation step is required for mass spectrometry (MS)-based proteome analysis. In this review, the advantages and limitations of protein separation by two-dimensional gel electrophoresis, liquid chromatography, surface-enhanced laser desorption/ionization and capillary electrophoresis (CE) for proteomic analysis are described, focusing on CE-MS. CE-MS enables separation and detection of the small molecular weight proteome in biological fluids with high reproducibility and accuracy in one single processing step and in a short time. As sensitive and specific single biomarkers generally may not exist, a strategy to overcome this diagnostic void is shifting from single analyte detection to simultaneous analysis of multiple analytes that together form a disease-specific pattern. Such approaches, however, are accompanied with additional challenges, which we will outline in this review. Besides the choice of adequate technological platforms, a high level of standardization of proteomic measurements and data processing is also necessary to establish proteomic profiling. In this regard, demands concerning study design, choice of specimens, sample preparation, proteomic data mining, and clinical evaluation should be considered before performing a proteomic study.

Should urine pH be adjusted prior to gel-based proteome analysis?

The urine has become one of the most widely used clinical samples for biomarker discovery. The pH of human urine may vary largely from 4.5 to 8.0. Previously, it was questionable whether the urine pH would affect proteome analysis and whether the urine pH needed to be adjusted prior to proteome analysis remained unclear. We therefore performed a systematic analysis of the effect of urine pH on proteome profile. Midstream second morning and random afternoon urine samples were collected from 5 males and 5 females who were healthy and had no recent medication. After removal of cells and debris by low-speed centrifugation, pH levels of individual samples were measured and urinary proteins were isolated by 75% ethanol precipitation. Equally loaded 100 microg of proteins from individual samples were resolved in 2-DE (linear pH 3-10) and visualized with SYPRO Ruby fluorescence stain. There was no significant correlation between difference in the morning versus afternoon urine pH (DeltapH) and %match of protein spots derived from morning versus afternoon urine samples in individual samples (Pearson's r = 0.074; p = 0.839). In parallel, all individual samples with equal volume were pooled. The pH of the pooled urine was adjusted to 4-10 and urinary proteome profiles were analyzed as for individual samples. ANOVA with Tukey's posthoc multiple comparisons showed no significant differences in total number of detected spots and %match among various pH levels. Our data suggest that the urine pH has no significant effects on urinary proteome profile and thus needs no adjustment prior to gel-based proteome analysis.

Capillary electrophoresis-mass spectrometry as a powerful tool in biomarker discovery and clinical diagnosis: an update of recent developments

Proteome analysis has emerged as a powerful technology to decipher biological processes. One of the main goals is to discover biomarkers for diseases from tissues and body fluids. However, the complexity and wide dynamic range of protein expression present an enormous challenge to separation technologies and mass spectrometry (MS). In this review, we examine the limitations of proteomics, and aim towards the definition of the current key prerequisites. We focus on capillary electrophoresis coupled to mass spectrometry (CE-MS), because this technique continues to show great promise. We discuss CE-MS from an application point of view, and evaluate its merits and vices for biomarker discovery and clinical applications. Finally, we present several examples on the use of CE-MS to determine urinary biomarkers and implications for disease diagnosis, prognosis, and therapy evaluation.

The non-invasive biopsy--will urinary proteomics make the renal tissue biopsy redundant?

Proteomics is a rapidly advancing technique which gives functional insight into gene expression in living organisms. Urine is an ideal medium for study as it is readily available, easily obtained and less complex than other bodily fluids. Considerable progress has been made over the last 5 years in the study of urinary proteomics as a diagnostic tool for renal disease. Advantages over the traditional renal biopsy include accessibility, safety, the possibility of serial sampling and the potential for non-invasive prognostic and diagnostic monitoring of disease and an individual's response to treatment. Urinary proteomics is now moving from a discovery phase in small studies to a validation phase in much larger numbers of patients with renal disease. Whilst there are still some limitations in methodology, which are assessed in this review, the possibility of urinary proteomics replacing the invasive tissue biopsy for diagnosis of renal disease is becoming an increasingly realistic option.

Different expression of fibrinopeptide A and related fragments in serum of type 1 diabetic patients with nephropathy

Type 1 diabetes (insulin-dependent diabetes mellitus, IDDM) is an autoimmune disease affecting about 0.12% of the world's population. Diabetic nephropathy (DN) is a major long-term complication of both types of diabetes and retains a high human, social and economic cost. Thus, the identification of markers for the early detection of DN represents a relevant target of diabetic research. The present work is a pilot study focused on proteomic analysis of serum of controls (n=9), IDDM patients (n=10) and DN patients (n=4) by the ClinProt profiling technology based on mass spectrometry. This approach allowed to identify a pattern of peptides able to differentiate the studied populations with sensitivity and specificity close to 100%. Variance of the results allowed to estimate the sample size needed to keep the expected False Discovery Rate low. Moreover, three peptides differentially expressed in the serum of patients as compared to controls were identified by LC-ESI MS/MS as the whole fibrinopeptide A peptide and two of its fragments, respectively. The two fragments were under-expressed in diabetic patients, while Fibrinopeptide A was over-expressed, suggesting that anomalous turnover of Fibrinopeptide A could be involved in the pathogenesis of DN.

[Early detection of diabetic nephropathy]

Due to the unfavorable prognosis of advanced stages of diabetic nephropathy (DN), the ideal approach is to identify renal involvement as early as possible. It is recommended to measure urinary albumin excretion (UAE) annually, in random urine samples, in order to detect the stages of DN [microalbuminuria (UAE 17-174 mg/l or 30-300 mg albumin/g of creatinine) and macroalbuminuria (> 174 mg/l or > 300 mg/g)]. However, it has been suggested that UAE levels below the threshold of consensus could already signal the risk for DN progression and increased mortality, indicating the need to revise cutoff values. As a substantial amount of UAE (the immunounreactive fraction), is not detected by conventional methods, HPLC would be more sensitive to identify the presence of damage by measuring total UAE (immunoreactive + immunounreactive). Another recent observation is that diminished glomerular filtration rates (GFR) occurs in the presence of normoalbuminuria. Therefore, besides evaluating UAE, it is recommended to estimate GFR with equations employing creatinine; such as the Modification of Diet in Renal Disease (MDRD) study, available at www.mdrd.com. Owing to the known limitations of creatinine, alternative endogenous markers are being studied, and cystatin-C is a promising marker under investigation. Finally, new strategies that could detect DN even earlier, include biomarkers such as proteomics, defining a profile of urinary protein excretion able to identify the subsequent risk of renal disease.

The human urinary proteome reveals high similarity between kidney aging and chronic kidney disease

Aging induces morphological changes of the kidney and reduces renal function. We analyzed the low molecular weight urinary proteome of 324 healthy individuals from 2-73 years of age to gain insight on human renal aging. We observed age-related modification of secretion of 325 out of over 5000 urinary peptides. The majority of these changes were associated with renal development before and during puberty, while 49 peptides were related to aging in adults. We therefore focussed the remainder of the study on these 49 peptides. The majority of these 49 peptides were also markers of chronic kidney disease, suggesting high similarity between aging and chronic kidney disease. Blinded evaluation of samples from healthy volunteers and diabetic nephropathy patients confirmed both the correlation of biomarkers with aging and with renal disease. Identification of a number of these aging-related peptides led us to hypothesize that reduced proteolytic activity is involved in human renal aging. Finally, among the 324 supposedly healthy individuals, some had urinary aging-related peptide excretion patterns typical of an individual significantly older than their actual age. In conclusion, these aging-related biomarkers may allow noninvasive detection of renal lesions in healthy persons and show high resemblance between human aging and chronic kidney disease. This similarity has to be taken into account when searching for biomarkers of renal disease.

Identification of urinary soluble E-cadherin as a novel biomarker for diabetic nephropathy

BACKGROUND

Currently, early diagnosis of diabetic nephropathy (DN) remains a major challenge. Thus, more investigations into new DN-related biomarkers are needed.

METHODS

We employed urinary proteomic approach of fluorescence-based difference gel electrophoresis (DIGE) and mass spectrometry to identify novel biomarkers in urine samples, which were from type 2 diabetes patients with normoalbuminuria (DM group), microalbuminuria (DN1 group), macroalbuminuria (DN2 group) and control group (n=8 in each group). The identified biomarker was further studied by western blot in urine samples (n=6 in each group) and immunohistochemistry in renal biopsies. Besides, the urinary level of biomarker was detected and analyzed using enzyme-linked immunosorbent assay(ELISA) method (n=40 in each group).

RESULTS

A novel DN-related biomarker, urinary E-cadherin, was identified by proteomic methods, which up-regulated 1.3-fold, 5.2-fold and 8.5-fold in DM, DN1 and DN2 groups compared with control group. Meanwhile, high expression of urinary soluble 80 kDa fragment of E-cadherin (sE-cadherin) was verified in DN groups by western blot. The ELISA data also demonstrated that urinary sE-cadherin-to-creatinine ratio was significantly increased in DN1 and DN2 groups versus DM group or control group (2751.5+/-164 and 5839.6+/-428 vs 721.9+/-93 or 652.7+/-87 microg/g; p<0.001). The sensitivity and specificity of urinary sE-cadherin for diagnosis of DN were calculated as 78.8% (95% CI, 74-83%) and 80% (95% CI, 65-91%). Besides, immunohistochemical stain showed that E-cadherin expression was markedly decreased in renal tubular epithelial cells of patients with DN versus healthy controls.

CONCLUSIONS

Urinary sE-cadherin has a potential clinical diagnostic value for DN and E-cadherin may participate in the pathogenesis of DN.

Proteomic analysis of peritoneal dialysate fluid in patients with dialysis-related peritonitis

The prognosis of uremia patients on continuous ambulatory peritoneal dialysis (CAPD) is related to frequent peritonitis rate. Frequent peritonitis will lead to peritoneum failure, making CAPD unfeasible. We have performed proteomic profiling of peritoneal dialysis effluent samples from a cross-section of CAPD patients with and without peritonitis in order to identify biomarkers of peritonitis. We performed 2D gel electrophoresis and surface-enhanced laser esorption/ionization time of flight mass spectrometry (SELDI-TOF MS) on peritoneal dialysis effluent from 16 subjects with peritonitis. A genetic algorithm search of principal component space revealed a group of a peak distinguishing peritonitis-positive subjects, with mass/charge (m/z) values of 11,117.4. Our analyses identified the peak at m/z 11,117.4 with an accuracy of 95% for classifying peritonitis. Mass spectrometric analysis of peritonitis PDE samples identified the 11,117.4 protein as beta2-microglobulin (B2M). Using an unbiased protein profiling approach, we have validated previously reported findings of B2M as a biomarker associated with CAPD peritonitis. Prospective studies are warranted to establish additional biomarkers that would be predictive of peritoneal dialysis peritonitis. Besides, extending the study to a larger number of patients with subgroup analyses may yield additional information of the peritoneal dialysate proteins in association with dialysis adequacy, residual renal function, nutritional status, and risk of peritoneal infection.

Proteomics studies after hematopoietic stem cell transplantation

Complex biological samples hold significant information on the health status and on development of disease. Approximately 35,000 human genes give rise to more than 1,000,000 functional entities at the protein level. Thus, the proteome provides a much richer source of information than the genome for describing the state of health or disease of humans. The composition body fluids comprise a rich source of information on changes of protein and peptide expression. Here we describe the application of capillary electrophoresis (CE) coupled online to an electrospray-ionization time-of-flight mass spectrometer (ESI-TOF-MS) to analyze human urine for the identification of biomarkers specific for complications after allogeneic hematopoietic stem cell transplantation (HSCT). Sequencing of native proteins/peptides is necessary for the identification of possible new therapeutic targets.

Urine proteomic profiling of uranium nephrotoxicity

Uranium is used in many chemical forms in civilian and military industries and is a known nephrotoxicant. A key issue in monitoring occupational exposure is to be able to evaluate the potential damage to the body, particularly the kidney. In this study we used innovative proteomic techniques to analyse urinary protein modulation associated with acute uranium exposure in rats. Given that the rat urinary proteome has rarely been studied, we first identified 102 different proteins in normal urine, expanding the current proteome data set for this central animal in toxicology. Rats were exposed intravenously to uranyl nitrate at 2.5 and 5 mg/kg and samples were collected 24 h later. Using two complementary proteomic methods, a classic 2-DE approach and semi-quantitative SDS-PAGE-LC-MS/MS, 14 modulated proteins (7 with increased levels and 7 with decreased levels) were identified in urine after uranium exposure. Modulation of three of them was confirmed by western blot. Some of the modulated proteins corresponded to proteins already described in case of nephrotoxicity, and indicated a loss of glomerular permeability (albumin, alpha-1-antiproteinase, serotransferrin). Others revealed tubular damage, such as EGF and vitamin D-binding protein. A third category included proteins never described in urine as being associated with metal stress, such as ceruloplasmin. Urinary proteomics is thus a valuable tool to profile uranium toxicity non-invasively and could be very useful in follow-up in case of accidental exposure to uranium.

Increased urinary excretion of orosomucoid is a risk predictor of diabetic nephropathy

AIM

Identification of the risk predictor of diabetic nephropathy (DN) remains a major challenge currently. Thus, proteomic approaches to identify DN-related biomarker were performed.

METHODS

A comparative proteomic approach of 2-D gel electrophoresis (2-DE) and mass spectrometry to identify biomarkers in urine samples from 12 DN patients (six type 1 and six type 2 diabetic patients) and six healthy controls. Then, the urinary level of identified protein biomarker was detected by immunoturbidimetry assay in urine samples from 90 type 1 and type 2 diabetic patients with normo-, micro- and macroalbuminuria (n = 30 in each group), and 30 healthy controls.

RESULTS

A novel DN-related protein, orosomucoid (alpha1-acid glycoprotein), was identified by proteomic method. Its abundance was highly upregulated (>eightfold) in DN patients. The data of immunoturbidimetry assay showed urinary orosomucoid excretion rate (UOER) was gradually increased in the normo-, micro- and macroalbuminuria group versus control (0.71 +/- 0.41, 1.93 +/- 0.68, 2.88 +/- 0.94 vs 0.39 +/- 0.28 ug/min, P < 0.05). The result indicated that UOER increased in early stage of DN and gradually increased with the development of DN. Also, Pearson's correlation analysis indicated UOER was positively correlated with urinary albumin excretion rate, serum creatinine and C-reactive protein (r = 0.830, 0.787 and 0.360, respectively; P < 0.05). Multivariate logistic regression analysis also showed that increased UOER was an independent risk factor for DN (odds ratio = 3.10, P < 0.0001).

CONCLUSION

Urinary orosomucoid is a DN-related biomarker, which is associated with the development and progression of DN. Furthermore, increased UOER is an independent risk factor of DN.

Adapting mass spectrometry-based platforms for clinical proteomics applications: The capillary electrophoresis coupled mass spectrometry paradigm

Single biomarker detection is common in clinical laboratories due to the currently available method spectrum. For various diseases, however, no specific single biomarker could be identified. A strategy to overcome this diagnostic void is to shift from single analyte detection to multiplexed biomarker profiling. Mass spectrometric methods were employed for biomarker discovery in body fluids. The enormous complexity of biofluidic proteome compartments implies upstream fractionation. For this reason, mass spectrometry (MS) was coupled to two-dimensional gel electrophoresis, liquid chromatography, surface-enhanced laser desorption/ionization, or capillary electrophoresis (CE). Differences in performance and operating characteristics make them differentially suited for routine laboratory applications. Progress in the field of clinical proteomics relies not only on the use of an adequate technological platform, but also on a fast and efficient proteomic workflow including standardized sample preparation, proteomic data processing, statistical validation of biomarker selection, and sample classification. Based on CE-MS analysis, we describe how proteomic technology can be implemented in a clinical laboratory environment. In the last part of this review, we give an overview of CE-MS-based clinical studies and present information on identity and biological significance of the identified peptide biomarkers providing evidence of disease-induced changes in proteolytic processing and posttranslational modification.

Evaluation of urinary biomarkers for coronary artery disease, diabetes, and diabetic kidney disease

BACKGROUND

In this study we sought to validate urinary biomarkers for diabetes and two common complications, coronary artery disease (CAD) and diabetic nephropathy (DN).

METHODS

A CAD score calculated by summing the product of a classification coefficient and signal amplitude of 15 urinary polypeptides was previously developed. Five sequences of biomarkers in the panel were identified as fragments of collagen alpha-1(I) and alpha-1(III). Prospectively collected urine samples available for analysis from 19 out of 20 individuals with CAD (15 with type 1 diabetes [T1D] and four without diabetes) and age-, sex-, and diabetes-matched controls enrolled in the Coronary Artery Calcification in Type 1 Diabetes study were analyzed for the CAD score using capillary electrophoresis and electrospray ionization mass spectrometry. Two panels of biomarkers that were previously defined to distinguish diabetes status were analyzed to determine their relationship to T1D. Three biomarker panels developed to distinguish DN (DNS) and two biomarker panels developed to distinguish renal disease (RDS) were examined to determine their relationship with renal function.

RESULTS

The CAD score was associated with CAD (odds ratio with 95% confidence interval, 2.2 [1.3-5.2]; P = 0.0016) and remained significant when adjusted individually for age, albumin excretion rate (AER), blood pressure, waist circumference, intraabdominal fat, glycosylated hemoglobin, and lipids. DNS and RDS were significantly correlated with AER, cystatin C, and serum creatinine. The biomarker panels for diabetes were both significantly associated with T1D status (P < 0.05 for both).

CONCLUSIONS

We validated a urinary proteome pattern associated with CAD and urinary proteome patterns associated with T1D and DN.