Clinical Proteomics in Kidney Disease: From Discovery to Clinical Application

Proteome analysis has been applied in multiple studies in the context of chronic kidney disease, aiming at improving our knowledge on the molecular pathophysiology of the disease. The approach is generally based on the hypothesis that proteins are key in maintaining kidney function, and disease is a clinical consequence of a significant change of the protein level. Knowledge on critical proteins and their alteration in disease should in turn enable identification of ideal biomarkers that could guide patient management. In addition, all drugs currently employed target proteins. Hence, proteome analysis also promises to enable identifying the best suited therapeutic target, and, in combination with biomarkers, could be used as the rationale basis for personalized intervention. To assess the current status of proteome analysis in the context of CKD, we present the results of a systematic review, of up-to-date scientific research, and give an outlook on the developments that can be expected in near future. Based on the current literature, proteome analysis has already seen implementation in the management of CKD patients, and it is expected that this approach, also supported by the positive results generated to date, will see advanced high-throughput application.

Systems biology identifies cytosolic PLA2 as a target in vascular calcification treatment

Although cardiovascular disease (CVD) is the leading cause of morbimortality worldwide, promising new drug candidates are lacking. We compared the arterial high-resolution proteome of patients with advanced versus early-stage CVD to predict, from a library of small bioactive molecules, drug candidates able to reverse this disease signature. Of the approximately 4000 identified proteins, 100 proteins were upregulated and 52 were downregulated in advanced-stage CVD. Arachidonyl trifluoromethyl ketone (AACOCF3), a cytosolic phospholipase A2 (cPLA2) inhibitor was predicted as the top drug able to reverse the advanced-stage CVD signature. Vascular cPLA2 expression was increased in patients with advanced-stage CVD. Treatment with AACOCF3 significantly reduced vascular calcification in a cholecalciferol-overload mouse model and inhibited osteoinductive signaling in vivo and in vitro in human aortic smooth muscle cells. In conclusion, using a systems biology approach, we have identified a potentially new compound that prevented typical vascular calcification in CVD in vivo. Apart from the clear effect of this approach in CVD, such strategy should also be able to generate novel drug candidates in other complex diseases.

Proteomics based identification of KDM5 histone demethylases associated with cardiovascular disease

Background

The increased prevalence of cardiovascular disease (CVD) indicates a demand for novel therapeutic approaches. Proteome analysis of vascular tissues from animal models and humans with CVD could lead to the identification of novel druggable targets.

Methods

LC-MS/MS analysis of thoracic aortas from three mouse models of non-diabetic and diabetic (streptozotocin (STZ)-induced) atherosclerosis followed by bioinformatics/pathway analysis was performed. Selected findings were confirmed by proteomics analysis of human vessels from patients with CVD as well as in vitro studies (migration, proliferation, angiogenesis assays) using endothelial (HUVEC) cells.

Findings

Comparative tissue proteomics of low density lipoprotein receptor deficient (Ldlr−/−) and diabetic Ldlr−/− (Ldlr−/−STZ) with wild type (WT) animals led to the identification of 284 differentially expressed proteins in both models. Among them, 177 proteins were also differentially expressed in diabetic apolipoprotein E deficient (ApoE−/−STZ) mice, suggesting expression changes associated with atherosclerosis independent of the model used. These proteins recapitulated the hallmarks of atherosclerosis. Comparison of these findings with differentially expressed proteins in human vessels with CVD enabled shortlisting of six commonly dysregulated proteins. Among them, lysine-specific demethylase 5D (KDM5D) exhibited pronounced overexpression accompanied by a reduction in the protein levels of its substrate, the trimethylated lysine 4 of histone H3 (H3K4me3), in patients with CVD. Functional interference studies applying a KDM5 inhibitor on HUVEC reduced cell proliferation, migration and tube-forming ability in vitro.

Interpretation

This high-throughput proteomics strategy identified KDM5 histone demethylases being potentially involved in CVD, possibly by affecting H3K4 methylation.

Fund

[SysVasc, HEALTH-2013 603288], [ERA-CVD PROACT: ANR-17-ECVD-0006, 01KL1805], [FRM, DEQ20170336759].

Plasma proteomic analysis reveals altered protein abundances in cardiovascular disease

BACKGROUND

Cardiovascular disease (CVD) describes the pathological conditions of the heart and blood vessels. Despite the large number of studies on CVD and its etiology, its key modulators remain largely unknown. To this end, we performed a comprehensive proteomic analysis of blood plasma, with the scope to identify disease-associated changes after placing them in the context of existing knowledge, and generate a well characterized dataset for further use in CVD multi-omics integrative analysis.

METHODS

LC-MS/MS was employed to analyze plasma from 32 subjects (19 cases of various CVD phenotypes and 13 controls) in two steps: discovery (13 cases and 8 controls) and test (6 cases and 5 controls) set analysis. Following label-free quantification, the detected proteins were correlated to existing plasma proteomics datasets (plasma proteome database; PPD) and functionally annotated (Cytoscape, Ingenuity Pathway Analysis). Differential expression was defined based on identification confidence (≥ 2 peptides per protein), statistical significance (Mann-Whitney p value ≤ 0.05) and a minimum of twofold change.

RESULTS

Peptides detected in at least 50% of samples per group were considered, resulting in a total of 3796 identified proteins (838 proteins based on ≥ 2 peptides). Pathway annotation confirmed the functional relevance of the findings (representation of complement cascade, fibrin clot formation, platelet degranulation, etc.). Correlation of the relative abundance of the proteins identified in the discovery set with their reported concentrations in the PPD was significant, confirming the validity of the quantification method. The discovery set analysis revealed 100 differentially expressed proteins between cases and controls, 39 of which were verified (≥ twofold change) in the test set. These included proteins already studied in the context of CVD (such as apolipoprotein B, alpha-2-macroglobulin), as well as novel findings (such as low density lipoprotein receptor related protein 2 [LRP2], protein SZT2) for which a mechanism of action is suggested.

CONCLUSIONS

This proteomic study provides a comprehensive dataset to be used for integrative and functional studies in the field. The observed protein changes reflect known CVD-related processes (e.g. lipid uptake, inflammation) but also novel hypotheses for further investigation including a potential pleiotropic role of LPR2 but also links of SZT2 to CVD.

Proteomics for Biomarker Identification and Clinical Application in Kidney Disease

Treatment effectiveness for kidney disease is limited by lack of accuracy, sensitivity, specificity of diagnostic, prognostic, and therapeutic biomarkers. The gold standard test renal biopsy along with serum creatinine and proteinuria is often necessary to establish a diagnosis, particularly in glomerular disease. Proteomics has become a powerful tool for novel biomarker discovery in kidney disease. Novel proteomics offer earlier and more accurate diagnosis of renal pathology than possible with traditional biomarkers such as serum creatinine and urine protein. In addition, proteomic biomarkers could also be useful to choose the most suitable therapeutic targets. This review focuses on the current status of proteomic biomarkers from animal models (5/6 nephrectomy, unilateral ureteral obstruction, and diabetic nephropathy) and human studies (chronic kidney disease, glomerular diseases, transplantation, dialysis, acute and drug-induced kidney injury) to assess relevant findings and clinical usefulness. Current issues and problems related to the discovery, validation, and clinical application of proteomic biomarkers are discussed. We also describe several proteomic strategies highlighting technologic advancements, specimen selection, data processing and analysis. This review might provide help in future proteomic studies to improve the diagnosis and management of kidney disease.

The Future of "Omics" in Hypertension

Despite decades of research and clinical practice, the pathogenesis of hypertension remains incompletely understood, and blood pressure is often suboptimally controlled. “Omics” technologies allow the description of a large number of molecular features and have the potential to identify new factors that contribute to blood pressure regulation and how they interact. In this review, we focus on the potential of genomics, transcriptomics, proteomics, and metabolomics and explore their roles in unraveling the pathophysiology and diagnosis of hypertension, the prediction of organ damage and treatment response, and monitoring treatment effect. Substantial progress has been made in the area of genomics, in which genome-wide association studies have identified > 50 blood pressure–related, single-nucleotide polymorphisms, and sequencing studies (especially in secondary forms of hypertension) have discovered novel regulatory pathways. In contrast, other omics technologies, despite their ability to provide detailed insights into the physiological state of an organism, have only more recently demonstrated their impact on hypertension research and clinical practice. The majority of current proteomic studies focus on organ damage resulting from hypertension and may have the potential to help us understand the link between blood pressure and organ failure but also serve as biomarkers for early detection of cerebrovascular or coronary disease. Examples include signatures for early detection of left ventricular dysfunction or albuminuria. Metabolomic studies have the potential to integrate environmental and intrinsic factors and are particularly suited to monitor the response to treatment. We discuss examples of omics studies in hypertension and explore the challenges related to these novel technologies.

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.

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.

Integrating proteomics profiling data sets: a network perspective

Understanding disease mechanisms often requires complex and accurate integration of cellular pathways and molecular networks. Systems biology offers the possibility to provide a comprehensive map of the cell's intricate wiring network, which can ultimately lead to decipher the disease phenotype. Here, we describe what biological pathways are, how they function in normal and abnormal cellular systems, limitations faced by databases for integrating data, and highlight how network models are emerging as a powerful integrative framework to understand and interpret the roles of proteins and peptides in diseases.

Clinical proteomics in obstetrics and neonatology

Clinical proteomics has been applied to the identification of biomarkers of obstetric and neonatal disease. We will discuss a number of encouraging studies that have led to potentially valid biomarkers in the context of Down's syndrome, preterm birth, amniotic infections, preeclampsia, intrauterine growth restriction and obstructive uropathies. Obtaining noninvasive biomarkers (e.g., from the maternal circulation, urine or cervicovaginal fluid) may be more feasible for obstetric diseases than for diseases of the fetus, for which invasive methods are required (e.g., amniotic fluid, fetal urine). However, studies providing validated proteomics-identified biomarkers are limited. Efforts should be made to save well-characterized samples of these invasive body fluids so that many valid biomarkers of pregnancy-related diseases will be identified in the coming years using proteomics based analysis upon adoption of 'clinical proteomics guidelines'.

Proteomics in hypertension and other cardiovascular diseases

Hypertension is a major cardiovascular risk factor with a multifactorial pathogenesis, including genetic and environmental factors. In addition to hypothesis-driven strategies, unbiased approaches such as genomics, proteomics, and metabolomics are useful tools to help unravel the pathophysiology of hypertension and associated organ damage. During development of cardiovascular disease the key organs and tissues undergo extensive functional and structural changes that are characterized by alterations in the amount and type of proteins that are expressed. Proteomic approaches study the expression of large numbers of proteins in organs, tissues, cells, and body fluids. A number of different proteomic platforms are available, many of which combine two methods to separate proteins and peptides after an initial digestion step. Identification of these peptides and changes in their expression in parallel with disease processes or medical treatment will help to identify as yet unknown pathophysiological pathways. There is also potential to use proteomic signatures as biomarkers of cardiovascular disease that will contribute to population screening, diagnosis of diseases and their severity, and monitoring of therapeutic interventions.

Urinary proteomics in the assessment of chronic kidney disease

PURPOSE OF REVIEW

Urinary proteomics has emerged as an approach that could deliver relevant clinical information. In this review, we aim at highlighting the recent developments, especially with respect to clinical implementation. We review several of the recent publications reporting on larger cohorts, focusing on those that aim at qualification and/or validation of urinary proteomics biomarkers.

RECENT FINDINGS

Several components of the urinary proteome, especially its low molecular weight fraction (sometimes referred to as the 'peptidome'), have been significantly associated with chronic kidney disease (CKD). Independent studies, encompassing sometimes close to 1000 independent samples, indicate that specific peptides from extracellular matrix (ECM) proteins encompass a major component of the urinary proteome. Highly significant changes in the abundance of some of these peptides are associated with CKD indicating that alterations in ECM, reflected via the urinary proteome, may represent an early stage in CKD pathology. These peptides may serve as specific early biomarkers, and interference with pathological ECM accumulation may be a valuable new therapeutic approach in CKD.

SUMMARY

Urinary proteomic biomarkers have emerged as clinically relevant variables. First studies involving several hundred individuals indicate a potential added benefit of urinary proteomic biomarkers. First large clinical trials are being initiated to employ urinary proteomics in clinical decision making.

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.

Biomarkers to improve the benefit/risk balance for approved therapeutics: a US FDA perspective on personalized medicine

This article highlights a current US FDA perspective concerning the use of biomarker-based diagnostics for personalized medicine. Specifically, current biomarkers that have application for improving the benefit/risk profile of already approved drugs are discussed. The success of biomarkers for use in personalized medicine depends on many factors, including proper evaluation of the usefulness of the biomarker for assessing the event of interest, and the safety and effectiveness of the diagnostic device used to measure the biomarker, which includes appropriate analytical and clinical validation. These points along with the many regulatory concerns regarding co-labeling of drugs and devices and future aspects, such as co-development, will be discussed in this regulatory science focus.

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.