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

Rationale and design of the Japanese Biomarkers in Nephrotic Syndrome (J-MARINE) study

INTRODUCTION

Disease subtyping and monitoring are essential for the management of nephrotic syndrome (NS). Although various biomarkers for NS have been reported, their clinical efficacy has not been comprehensively validated in adult Japanese patients.

METHODS

The Japanese Biomarkers in Nephrotic Syndrome (J-MARINE) study is a nationwide, multicenter, and prospective cohort study in Japan, enrolling adult (≥18 years) patients with minimal change disease (MCD), focal segmental glomerulosclerosis (FSGS), membranous nephropathy (MN), membranoproliferative glomerulonephritis (MPGN), C3 glomerulopathy (C3G), and lupus nephritis (LN). Baseline clinical information and plasma and urine samples will be collected at the time of immunosuppressive therapy initiation or biopsy. Follow-up data and plasma and urine samples will be collected longitudinally based on the designated protocols. Candidate biomarkers will be measured: CD80, cytotoxic T-lymphocyte antigen 4, and soluble urokinase plasminogen activator receptor for MCD and FSGS; anti-phospholipase A2 receptor and thrombospondin type-1 domain-containing protein 7A antibodies for MN; fragment Ba, C3a, factor I, and properdin for MPGN/C3G; and CD11b, CD16b, and CD163 for LN. Outcomes include complete and partial remission, relapse of proteinuria, a 30% reduction in estimated glomerular filtration rate (eGFR), eGFR decline, and initiation of renal replacement therapy. The diagnostic accuracy and predictive ability for clinical outcomes will be assessed for each biomarker.

RESULTS

From April 2019 to April 2023, 365 patients were enrolled: 145, 21, 138, 10, and 51 cases of MCD, FSGS, MN, MPGN/C3G, and LN, respectively.

CONCLUSION

This study will provide valuable insights into biomarkers for NS and serve as a biorepository for future studies.

Screening candidate diagnostic biomarkers for diabetic kidney disease

BACKGROUND

There are big differences in treatments and prognosis between diabetic kidney disease (DKD) and non-diabetic renal disease (NDRD). However, DKD patients couldn't be diagnosed early due to lack of special biomarkers. Urine is an ideal non-invasive sample for screening DKD biomarkers. This study aims to explore DKD special biomarkers by urinary proteomics.

MATERIALS AND METHODS

According to the result of renal biopsy, 142 type 2 diabetes mellitus (T2DM) patients were divided into 2 groups: DKD (n = 83) and NDRD (n = 59). Ten patients were selected from each group to define urinary protein profiles by label-free quantitative proteomics. The candidate proteins were further verifyied by parallel reaction monitoring (PRM) methods (n = 40). Proteins which perform the same trend both in PRM and proteomics were verified by enzyme-linked immunosorbent assays (ELISA) with expanding the sample size (n = 82). The area under the receiver operating characteristic curve (AUC) was used to evaluate the accuracy of diagnostic biomarkers.

RESULTS

We identified 417 peptides in urinary proteins showing significant difference between DKD and NDRD. PRM verification identified C7, SERPINA4, IGHG1, SEMG2, PGLS, GGT1, CDH2, CDH1 was consistent with the proteomic results and p < 0.05. Three potential biomarkers for DKD, C7, SERPINA4, and gGT1, were verified by ELISA. The combinatied SERPINA4/Ucr and gGT1/Ucr (AUC = 0.758, p = 0.001) displayed higher diagnostic efficiency than C7/Ucr (AUC = 0.632, p = 0.048), SERPINA4/Ucr (AUC = 0.661, p = 0.032), and gGT1/Ucr (AUC = 0.661, p = 0.029) respectively.

CONCLUSIONS

The combined index SERPINA4/Ucr and gGT1/Ucr can be considered as candidate biomarkers for diabetic nephropathy after adjusting by urine creatinine.

Urinary Protein-Biomarkers Reliably Indicate Very Early Kidney Damage in Children With Alport Syndrome Independently of Albuminuria and Inflammation

Introduction

Alport syndrome (AS) is a hereditary type IV collagen disease. It starts shortly after birth, without clinical symptoms, and progresses to end-stage kidney disease early in life. The earlier therapy starts, the more effectively end-stage kidney disease can be delayed. Clearly then, to ensure preemptive therapy, early diagnosis is an essential prerequisite.

Methods

To provide early diagnosis, we searched for protein biomarkers (BMs) by mass spectrometry in dogs with AS stage 0. At this very early stage, we identified 74 candidate BMs. Of these, using commercial enzyme-linked immunosorbent assays (ELISAs), we evaluated 27 in dogs and 28 in children, 50 with AS and 104 healthy controls.

Results

Most BMs from blood appeared as fractions of multiple variants of the same protein, as shown by their chromatographic distribution before mass spectrometry. Blood samples showed only minor differences because ELISAs rarely detect disease-specific variants. However, in urine , several proteins, individually or in combination, were promising indicators of very early and preclinical kidney injury. The BMs with the highest sensitivity and specificity were collagen type XIII, hyaluronan binding protein 2 (HABP2), and complement C4 binding protein (C4BP).

Conclusion

We generated very strong candidate BMs by our approach of first examining preclinical AS in dogs and then validating these BMs in children at early stages of disease. These BMs might serve for screening purposes for AS before the onset of kidney damage and therefore allow preemptive therapy.

A Policy Call to Address Rare Kidney Disease in Health Care Plans

Despite a large number of people globally being affected by rare kidney diseases, research support and health care policy programs usually focus on the management of the broad spectrum of CKD without particular attention to rare causes that would require a targeted approach for proper cure. Hence, specific curative approaches for rare kidney diseases are scarce, and these diseases are not treated optimally, with implications on the patients' health and quality of life, on the cost for the health care system, and society. There is therefore a need for rare kidney diseases and their mechanisms to receive the appropriate scientific, political, and policy attention to develop specific corrective approaches. A wide range of policies are required to address the various challenges that target care for rare kidney diseases, including the need to increase awareness, improve and accelerate diagnosis, support and implement therapeutic advances, and inform the management of the diseases. In this article, we provide specific policy recommendations to address the challenges hindering the provision of targeted care for rare kidney diseases, focusing on awareness and prioritization, diagnosis, management, and therapeutic innovation. In combination, the recommendations provide a holistic approach aiming for all aspects of rare kidney disease care to improve health outcomes, reduce the economic effect, and deliver benefits to society. Greater commitment from all the key stakeholders is now needed, and a central role should be assigned to patients with rare kidney disease to partner in the design and implementation of potential solutions.

Liquid biopsy for non-invasive monitoring of patients with kidney transplants

The current tools for diagnosing and monitoring native kidney diseases as well as allograft rejection in transplant patients are suboptimal. Creatinine and proteinuria are non-specific and poorly sensitive markers of injury. Tissue biopsies are invasive and carry potential complications. In this article, we overview the different techniques of liquid biopsy and discuss their potential to improve patients' kidney health. Several diagnostic, predictive, and prognostic biomarkers have been identified with the ability to detect and monitor the activity of native kidney diseases as well as early and chronic allograft rejection, such as donor-derived cell-free DNA, exosomes, messenger RNA/microsomal RNA, proteomics, and so on. While the results are encouraging, additional research is still needed as no biomarker appears to be perfect for a routine application in clinical practice. Despite promising advancements in biomarkers, the most important issue is the lack of standardized pre-analytical criteria. Large validation studies and uniformed standard operating procedures are required to move the findings from bench to bedside. Establishing consortia such as the Liquid Biopsy Consortium for Kidney Diseases can help expedite the research process, allow large studies to establish standardized procedures, and improve the management and outcomes of kidney diseases and of kidney transplant recipients.

Immune checkpoint inhibitor related nephrotoxicity: Advances in clinicopathologic features, noninvasive approaches, and therapeutic strategy and rechallenge

Immune checkpoint inhibitors (ICIs) are used increasingly to treat more than 17 cancers and have shown promising therapeutic results. However, ICI use can result in a variety of immune-related adverse events (IRAEs) which can occur in any organ, including the kidneys. Acute kidney injury (AKI) is the most common nephrotoxicity, classically related to acute interstitial nephritis. Much more diverse patterns and presentations of ICI-related kidney injury can occur, and have implications for diagnostic and therapeutic management approaches. In this review, we summarize the recently approved ICIs for cancer, the incidence and risk factors for nephrotoxicity, our current understanding of the pathophysiological mechanisms and the key clinicopathological features of ICI-related AKI, and therapeutic strategies. We also explore important knowledge that require further investigation, such as the risks/benefits of ICI rechallenge in patients who recover from an episode of ICI-related AKI, and the application of liquid biopsy and microbiome to identify noninvasive biomarkers to diagnose and predict kidney injury and guide ICI therapy.

Urinary Proteomics in Kidney Transplantation

Although kidney transplantation is the best treatment option for end stage kidney disease, it is still associated with long-term graft failure. One of the greater challenges for transplant professionals is the ability to identify grafts with a high risk of failure before initial decline of eGFR with irreversible graft changes. Transplantation medicine is facing an emerging need for novel disease end point-specific biomarkers, with practical application in preventive screening, early diagnostic, and improved prognostic and therapeutic utility. The aim of our review was to evaluate the clinical application of urinary proteomics in kidney transplant recipients at risk for any type of future graft failure.

Urine proteomics identifies biomarkers for diabetic kidney disease at different stages

BACKGROUND

Type 2 diabetic kidney disease is the most common cause of chronic kidney diseases (CKD) and end-stage renal diseases (ESRD). Although kidney biopsy is considered as the 'gold standard' for diabetic kidney disease (DKD) diagnosis, it is an invasive procedure, and the diagnosis can be influenced by sampling bias and personal judgement. It is desirable to establish a non-invasive procedure that can complement kidney biopsy in diagnosis and tracking the DKD progress.

METHODS

In this cross-sectional study, we collected 252 urine samples, including 134 uncomplicated diabetes, 65 DKD, 40 CKD without diabetes and 13 follow-up diabetic samples, and analyzed the urine proteomes with liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). We built logistic regression models to distinguish uncomplicated diabetes, DKD and other CKDs.

RESULTS

We quantified 559 ± 202 gene products (GPs) (Mean ± SD) on a single sample and 2946 GPs in total. Based on logistic regression models, DKD patients could be differentiated from the uncomplicated diabetic patients with 2 urinary proteins (AUC = 0.928), and the stage 3 (DKD3) and stage 4 (DKD4) DKD patients with 3 urinary proteins (AUC = 0.949). These results were validated in an independent dataset. Finally, a 4-protein classifier identified putative pre-DKD3 patients, who showed DKD3 proteomic features but were not diagnosed by clinical standards. Follow-up studies on 11 patients indicated that 2 putative pre-DKD patients have progressed to DKD3.

CONCLUSIONS

Our study demonstrated the potential for urinary proteomics as a noninvasive method for DKD diagnosis and identifying high-risk patients for progression monitoring.

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.

Mapping of the amniotic fluid proteome of fetuses with congenital anomalies of the kidney and urinary tract identifies plastin 3 as a protein involved in glomerular integrity

Congenital anomalies of the kidney and the urinary tract (CAKUT) are the first cause of chronic kidney disease in childhood. Several genetic and environmental origins are associated with CAKUT, but most pathogenic pathways remain elusive. Considering the amniotic fluid (AF) composition as a proxy for fetal kidney development, we analyzed the AF proteome from non-severe CAKUT (n = 19), severe CAKUT (n = 14), and healthy control (n = 22) fetuses using LC-MS/MS. We identified 471 significant proteins that discriminated the three AF groups with 81% precision. Among them, eight proteins independent of gestational age (CSPG4, LMAN2, ENDOD1, ANGPTL2, PRSS8, NGFR, ROBO4, PLS3) were associated with both the presence and the severity of CAKUT. Among those, five were part of a protein-protein interaction network involving proteins previously identified as being potentially associated with CAKUT. The actin-bundling protein PLS3 (plastin 3) was the only protein displaying a gradually increased AF abundance from control, via non-severe, to severe CAKUT. Immunohistochemistry experiments showed that PLS3 was expressed in the human fetal as well as in both the fetal and the postnatal mouse kidney. In zebrafish embryos, depletion of PLS3 led to a general disruption of embryonic growth including reduced pronephros development. In postnatal Pls3-knockout mice, kidneys were macroscopically normal, but the glomerular ultrastructure showed thickening of the basement membrane and fusion of podocyte foot processes. These structural changes were associated with albuminuria and decreased expression of podocyte markers including Wilms' tumor-1 protein, nephrin, and podocalyxin. In conclusion, we provide the first map of the CAKUT AF proteome that will serve as a reference for future studies. Among the proteins strongly associated with CAKUT, PLS3 did surprisingly not specifically affect nephrogenesis but was found as a new contributor in the maintenance of normal kidney function, at least in part through the control of glomerular integrity. © 2021 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Urinary proteomic analysis to identify a potential protein biomarker panel for the diagnosis of tuberculosis

Tuberculosis (TB) is caused by Mycobacterium tuberculosis and is one of the primary causes of death worldwide. Rapid and accurate diagnosis of TB is one of the most direct means to reduce the incidence of TB. In this study, urinary proteomic profiling of TB patients and non-TB individual controls (HCs) was performed, and differentially expressed urinary proteins between TB and HCs were compared and exclusively expressed proteins in TB patients were selected to establish a clinically useful disease marker panel. In total, these top 11 targeted proteins with 265 peptides were scheduled for multiple reaction monitoring validation analysis by using urine samples from 52 TB patients and 52 HCs. The result demonstrated that a three-protein combination out of the five-protein panel (namely P22352, Q9P121, P15151, Q13291, and Q8NDA2) exhibited sensitivity rate of 82.7% in the diagnosis of TB. Furthermore, the three-protein combination could differentiate TB from the latent tuberculosis (LTB) effectively, which exhibited specificity rate of 92.3% for the diagnosis of TB from the LTB category. Although more numbers of clinical samples are required for further verification, the results provided preliminary evidence that this "three-protein combination" out of the five-protein panel could probably be a novel TB diagnostic biomarker in clinical application.

Understanding glomerular diseases through proteomics

INTRODUCTION

Chronic kidney disease is avery common and complex chronic disease. Uncovering the pathological patterns of CKD on the molecular level of bio-fluids and tissue appears to be both vital and promising for a more favorable outcome. We reviewed recently discovered proteomics biomarkers for CKD to provide new insight into disease pathology.

AREAS COVERED

We review the application of proteome analysis in the context of CKD with various etiologies within the last 5 years. Proteins and peptides associated with CKD as derived from multiple sources (urine, blood and tissue) are reported along with their various biological pathways.

EXPERT OPINION

A systematic and theoretical comprehension of the CKD pathology is essential for its successful management. The underlying complexity of the disease further requires specific conditions for reliable and interpretable results. In this context, clinical proteomics has resulted in first encouraging findings in CKD. A more complete understanding of the biological pathways related to the disease, based on the scope of a holistic proteomic approach, could improve substantially the management of CKD, especially when in conjunction with the current trend of personalized medicine.

Value of Urine Peptides in Assessing Kidney and Cardiovascular Disease

Urinary peptides gained significant attention as potential biomarkers especially in the context of kidney and cardiovascular disease. In this manuscript the recent literature since 2015 on urinary peptide investigation in human kidney and cardiovascular disease is reviewed. The technology most commonly used in this context is capillary electrophoresis coupled mass spectrometry, in part owed to the large database available and the well-defined dataspace. Several studies based on over 1000 subjects are reported in the recent past, especially examining CKD273, a classifier for assessment of chronic kidney disease based on 273 urine peptides. Interestingly, the most abundant urinary peptides are generally collagen fragments, which may have gone undetected for some time as they are typically modified via proline hydroxylation. The data available suggest that urinary peptides specifically depict inflammation and fibrosis, and may serve as a non-invasive tool to assess fibrosis, which appears to be a key driver in kidney and cardiovascular disease. The recent successful completion of the first urinary peptide guided intervention trial, PRIORITY, is expected to further spur clinical application of urinary peptidomics, aiming especially at early detection of chronic diseases, prediction of progression, and prognosis of drug response.

Increased urinary exosomal SYT17 levels in chronic active antibody-mediated rejection after kidney transplantation via the IL-6 amplifier

Chronic active antibody-mediated rejection (CAAMR) is a particular problem in kidney transplantation (KTx), and ~25% of grafts are lost by CAAMR. Further, the pathogenesis remains unclear, and there is no effective cure or marker. We previously found that a hyper NFκB-activating mechanism in non-immune cells, called the IL-6 amplifier, is induced by the co-activation of NFκB and STAT3, and that this activation can develop various chronic inflammatory diseases. Here, we show that synaptotagmin-17 (SYT17) is increased in an exosomal fraction of the urine from CAAMR patients, and that this increase is associated with activation of the IL-6 amplifier. Immunohistochemistry showed that SYT17 protein expression was increased in renal tubule cells of the CAAMR group. While SYT17 protein was not detectable in whole-urine samples by western blotting, urinary exosomal SYT17 levels were significantly elevated in the CAAMR group compared to three other histology groups (normal, interstitial fibrosis and tubular atrophy, and calcineurin inhibitors toxicity) after KTx. On the other hand, current clinical laboratory data could not differentiate the CAAMR group from these groups. These data suggest that urinary exosomal SYT17 is a potential diagnostic marker for CAAMR.

Urinary peptidomics and bioinformatics for the detection of diabetic kidney disease

The aim of this study was to establish a peptidomic profile based on LC-MS/MS and random forest (RF) algorithm to distinguish the urinary peptidomic scenario of type 2 diabetes mellitus (T2DM) patients with different stages of diabetic kidney disease (DKD). Urine from 60 T2DM patients was collected: 22 normal (stage A1), 18 moderately increased (stage A2) and 20 severely increased (stage A3) albuminuria. A total of 1080 naturally occurring peptides were detected, which resulted in the identification of a total of 100 proteins, irrespective of the patients’ renal status. The classification accuracy showed that the most severe DKD (A3) presented a distinct urinary peptidomic pattern. Estimates for peptide importance assessed during RF model training included multiple fragments of collagen and alpha-1 antitrypsin, previously associated to DKD. Proteasix tool predicted 48 proteases potentially involved in the generation of the 60 most important peptides identified in the urine of DM patients, including metallopeptidases, cathepsins, and calpains. Collectively, our study lightened some biomarkers possibly involved in the pathogenic mechanisms of DKD, suggesting that peptidomics is a valuable tool for identifying the molecular mechanisms underpinning the disease and thus novel therapeutic targets.

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.

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.

Larger nephron size, low nephron number, and nephrosclerosis on biopsy as predictors of kidney function after donating a kidney

It is unclear whether structural findings in the kidneys of living kidney donors predict postdonation kidney function. We studied living kidney donors who had a kidney biopsy during donation. Nephron size was measured by glomerular volume, cortex volume per glomerulus, and mean cross-sectional tubular area. Age-specific thresholds were defined for low nephron number (calculated from CT and biopsy measures) and nephrosclerosis (global glomerulosclerosis, interstitial fibrosis/tubular atrophy, and arteriosclerosis). These structural measures were assessed as predictors of postdonation measured GFR, 24-hour urine albumin, and hypertension. Analyses were adjusted for baseline age, gender, body mass index, systolic and diastolic blood pressure, hypertension, measured GFR, urine albumin, living related donor status, and time since donation. Of 2673 donors, 1334 returned for a follow-up visit at a median 4.4 months after donation, with measured GFR <60 mL/min/1.73 m² in 34%, urine albumin >5 mg/24 h in 13%, and hypertension in 5.3%. Larger glomerular volume and interstitial fibrosis/tubular atrophy predicted follow-up measured GFR <60 mL/min/1.73 m² . Larger cortex volume per glomerulus and low nephron number predicted follow-up urine albumin >5 mg/24 h. Arteriosclerosis predicted hypertension. Microstructural findings predict GFR <60 mL/min/1.73 m² , modest increases in urine albumin, and hypertension shortly after kidney donation.

Urinary proteomic biomarkers in oncology: ready for implementation?

Introduction: Biomarkers are expected to improve the management of cancer patients by enabling early detection and prediction of therapeutic response. Proteins reflect a molecular phenotype, have high potential as biomarkers, and also are key targets for intervention. Given the ease of collection and proximity to certain tumors, the urinary proteome is a rich source of biomarkers and several proteins have been already implemented. Areas covered: We examined the literature on urine proteins and proteome analysis in oncology from reports published during the last 5 years to generate an overview on the status of urine protein and peptide biomarkers, with emphasis on their actual clinical value. Expert commentary: A few studies report on biomarkers that are ready to be implemented in patient management, among others in bladder cancer and cholangiocarcinoma. These reports are based on multi-marker approaches. A high number of biomarkers, though, has been described in studies with low statistical power. In fact, several of them have been consistently reported across different studies. The latter should be the focus of attention and be tested in properly designed confirmatory and ultimately, prospective investigations. It is expected that multi-marker classifiers for a specific context-of-use, will be the preferred path toward clinical implementation.

Clinical Proteomics: Closing the Gap from Discovery to Implementation

Clinical proteomics, the application of proteome analysis to serve a clinical purpose, represents a major field in the area of proteome research. Over 1000 manuscripts on this topic are published each year, with numbers continuously increasing. However, the anticipated outcome, the transformation of the reported findings into improvements in patient management, is not immediately evident. In this article, the value and validity of selected clinical proteomics findings are investigated, and it is assessed how far implementation has progressed. A main conclusion from this assessment is that to achieve implementation, well-powered clinical studies are required in the appropriate population, addressing a specific clinical need and with a clear context-of-use. Efforts toward implementation, to be feasible, must be supported by the key players in science: publishers and funders. The authors propose a change on objectives, from additional discovery studies toward studies aiming at validation of the plethora of potential biomarkers that have been described, to demonstrate practical value of clinical proteomics. All elements required, potential biomarkers, technologies, and bio-banked samples are available (based on today's literature), hence a change in focus from discovery toward validation and application is not only urgently necessary, but also possible based on resources available today.

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.

Association of kidney fibrosis with urinary peptides: a path towards non-invasive liquid biopsies?

Chronic kidney disease (CKD) is a prevalent cause of morbidity and mortality worldwide. A hallmark of CKD progression is renal fibrosis characterized by excessive accumulation of extracellular matrix (ECM) proteins. In this study, we aimed to investigate the correlation of the urinary proteome classifier CKD273 and individual urinary peptides with the degree of fibrosis. In total, 42 kidney biopsies and urine samples were examined. The percentage of fibrosis per total tissue area was assessed in Masson trichrome stained kidney tissues. The urinary proteome was analysed by capillary electrophoresis coupled to mass spectrometry. CKD273 displayed a significant and positive correlation with the degree of fibrosis (Rho = 0.430, P = 0.0044), while the routinely used parameters (glomerular filtration rate, urine albumin-to-creatinine ratio and urine protein-to-creatinine ratio) did not (Rho = -0.222; -0.137; -0.070 and P = 0.16; 0.39; 0.66, respectively). We identified seven fibrosis-associated peptides displaying a significant and negative correlation with the degree of fibrosis. All peptides were collagen fragments, suggesting that these may be causally related to the observed accumulation of ECM in the kidneys. CKD273 and specific peptides are significantly associated with kidney fibrosis; such an association could not be detected by other biomarkers for CKD. These non-invasive fibrosis-related biomarkers can potentially be implemented in future trials.

Urinary peptidomics analysis reveals proteases involved in diabetic nephropathy

Mechanisms underlying the onset and progression of nephropathy in diabetic patients are not fully elucidated. Deregulation of proteolytic systems is a known path leading to disease manifestation, therefore we hypothesized that proteases aberrantly expressed in diabetic nephropathy (DN) may be involved in the generation of DN-associated peptides in urine. We compared urinary peptide profiles of DN patients (macroalbuminuric, n = 121) to diabetic patients with no evidence of DN (normoalbuminuric, n = 118). 302 sequenced, differentially expressed peptides (adjusted p-value < 0.05) were analysed with the Proteasix tool predicting proteases potentially involved in their generation. Activity change was estimated based on the change in abundance of the investigated peptides. Predictions were correlated with transcriptomics (Nephroseq) and relevant protein expression data from the literature. This analysis yielded seventeen proteases, including multiple forms of MMPs, cathepsin D and K, kallikrein 4 and proprotein convertases. The activity of MMP-2 and MMP-9, predicted to be decreased in DN, was investigated using zymography in a DN mouse model confirming the predictions. Collectively, this proof-of-concept study links urine peptidomics to molecular changes at the tissue level, building hypotheses for further investigation in DN and providing a workflow with potential applications to other diseases.

Direct Mass Spectrometry Differentiation of Ectopic and Eutopic Endometrium in Patients with Endometriosis

STUDY OBJECTIVE

To introduce a method for the rapid assessment of endometriotic tissues using direct mass spectrometry (MS)-based lipidomics.

DESIGN

A prospective observational cohort study (Canadian Task Force classification II2).

SETTING

Department of Operative Gynecology of the Research Centre for Obstetrics, Gynecology and Perinatology.

PATIENTS

Fifty patients with ovarian cysts and peritoneal endometriosis who underwent laparoscopic surgery between 2014 and 2016.

INTERVENTION

Differences in mass spectrometric profiles of ectopic endometria (endometriosis) and eutopic endometria were analyzed for each patient in combination with morphohistologic evaluation. The lipidomic approach was applied using a direct high-resolution MS method.

MEASUREMENTS AND MAIN RESULTS

Of 148 metabolites, 15 showed significant differences between endometriotic tissue and a healthy endometrium of the same patient, considered as a control in this study. The main lipids prevalent in endometriotic tissues were phosphoethanolamine (PE O-20:0), sphingomyelin (SM 34:1), diglycerides (DG 44:9), phosphatidylcholines (PC 32:1, PC O-36:3, PC 38:7, PC 38:6, PC 40:8, PC 40:7, PC 40:6, PC 40:9, and PC O-42:1), and triglycerides (TG 41:2, TG 49:4, and TG 52:3). Using partial least squares discriminant analysis models, MS showed that the lipidomic profile of endometriotic tissue (peritoneal endometriosis and ovarian endometriomas) was clearly separated from the eutopic endometrium, indicating tissue-type differentiation.

CONCLUSION

Our results suggest that direct MS may play an important role for endometriotic tissue identification. Such an approach has potential usefulness for real-time tissue determination and differentiation during surgical treatment. Lipids of 3 important classes, sphingolipids, phospholipids, and the fatty acids (di- and triglycerides), were identified. Validation is required to determine whether these lipids can be used to discriminate between patients with endometriosis and those with other gynecologic diseases.

Urine peptidomic biomarkers for diagnosis of patients with systematic lupus erythematosus

Background Systematic lupus erythematosus (SLE) is characterized with various complications which can cause serious organ damage in the human body. Despite the significant improvements in disease management of SLE patients, the non-invasive diagnosis is entirely missing. In this study, we used urinary peptidomic biomarkers for early diagnosis of disease onset to improve patient risk stratification, vital for effective drug treatment. Methods Urine samples from patients with SLE, lupus nephritis (LN) and healthy controls (HCs) were analyzed using capillary electrophoresis coupled to mass spectrometry (CE-MS) for state-of-the-art biomarker discovery. Results A biomarker panel made up of 65 urinary peptides was developed that accurately discriminated SLE without renal involvement from HC patients. The performance of the SLE-specific panel was validated in a multicentric independent cohort consisting of patients without SLE but with different renal disease and LN. This resulted in an area under the receiver operating characteristic (ROC) curve (AUC) of 0.80 ( p < 0.0001, 95% confidence interval (CI) 0.65-0.90) corresponding to a sensitivity and a specificity of 83% and 73%, respectively. Based on the end terminal amino acid sequences of the biomarker peptides, an in silico methodology was used to identify the proteases that were up or down-regulated. This identified matrix metalloproteinases (MMPs) as being mainly responsible for the peptides fragmentation. Conclusions A laboratory-based urine test was successfully established for early diagnosis of SLE patients. Our approach determined the activity of several proteases and provided novel molecular information that could potentially influence treatment efficacy.

Diagnostic work-up and specific causes of acute kidney injury

Acute kidney injury (AKI) is common in critically ill patients and associated with grim short- and long-term outcome. Although in the vast majority of cases AKI is multifactorial, with sepsis, shock and nephrotoxicity accounting for most episodes, specific causes of AKI are not uncommon. Despite remaining uncertainties regarding their prevalence in the ICU, prompt recognition of specific aetiologies of AKI is likely to ensure timely management, limit worsening of renal dysfunction, and ultimately limit renal and systemic consequences of AKI. The ability to recognize conditions that may be associated with specific aetiologies and the appropriate use of clinical imaging, biological and immunological tests, along with optimal assessment of the need for renal biopsies, should be part of routine ICU care. In this review, we summarize uncertainties, current knowledge and recent advances regarding specific types of AKI. We describe the most common specific causes as well as rare aetiologies requiring urgent management, and outline available tools that may be used during the diagnostic work-up along with their limitations.

Urinary peptide-based classifier CKD273: towards clinical application in chronic kidney disease

Capillary electrophoresis coupled with mass spectrometry (CE-MS) has been used as a platform for discovery and validation of urinary peptides associated with chronic kidney disease (CKD). CKD affects ∼ 10% of the population, with high associated costs for treatments. A urinary proteome-based classifier (CKD273) has been discovered and validated in cross-sectional and longitudinal studies to assess and predict the progression of CKD. It has been implemented in studies employing cohorts of > 1000 patients. CKD273 is commercially available as an in vitro diagnostic test for early detection of CKD and is currently being used for patient stratification in a multicentre randomized clinical trial (PRIORITY). The validity of the CKD273 classifier has recently been evaluated applying the Oxford Evidence-Based Medicine and Southampton Oxford Retrieval Team guidelines and a letter of support for CKD273 was issued by the US Food and Drug Administration. In this article we review the current evidence published on CKD273 and the challenges associated with implementation. Definition of a possible surrogate early endpoint combined with CKD273 as a biomarker for patient stratification currently appears as the most promising strategy to enable the development of effective drugs to be used at an early time point when intervention can still be effective.

Make Precision Medicine Work for Chronic Kidney Disease

Precision medicine is based on accurate diagnosis and tailored intervention through the use of omics and clinical data together with epidemiology and environmental exposures. Precision medicine should be achieved with minimum adverse events and maximum efficacy in patients with chronic kidney disease (CKD). In this review, the breakthroughs of omics in CKD and the application of systems biology are reviewed. The potential role of transforming growth factor-β1 in the targeted intervention of renal fibrosis is discussed as an example of how to make precision medicine work for CKD.

Biomarkers of systemic lupus erythematosus identified using mass spectrometry-based proteomics: a systematic review

Advances in mass spectrometry technologies have created new opportunities for discovering novel protein biomarkers in systemic lupus erythematosus (SLE). We performed a systematic review of published reports on proteomic biomarkers identified in SLE patients using mass spectrometry‐based proteomics and highlight their potential disease association and clinical utility. Two electronic databases, MEDLINE and EMBASE, were systematically searched up to July 2015. The methodological quality of studies included in the review was performed according to Preferred Reporting Items for Systematic Reviews and Meta‐analyses guidelines. Twenty‐five studies were included in the review, identifying 241 SLE candidate proteomic biomarkers related to various aspects of the disease including disease diagnosis and activity or pinpointing specific organ involvement. Furthermore, 13 of the 25 studies validated their results for a selected number of biomarkers in an independent cohort, resulting in the validation of 28 candidate biomarkers. It is noteworthy that 11 candidate biomarkers were identified in more than one study. A significant number of potential proteomic biomarkers that are related to a number of aspects of SLE have been identified using mass spectrometry proteomic approaches. However, further studies are required to assess the utility of these biomarkers in routine clinical practice.

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.

Implementation of CE-MS-identified proteome-based biomarker panels in drug development and patient management

The recent advancements in clinical proteomics enabled identification of biomarker panels for a large range of diseases. A number of CE-MS-identified biomarker panels were verified and implemented in clinical studies. Despite multiple challenges, accumulating evidence supports the value and the need for proteome-based biomarker panels. In this perspective, we provide an overview of clinical studies indicating the added value of CE-MS biomarker panels over traditional diagnostics and monitoring methods. We outline apparent advantages of applying novel proteomic biomarker panels for disease diagnosis, prognosis, staging, drug development and patient management. Facing the plethora of benefits associated with the use of CE-MS biomarker panels, we envision their implementation into the medical practice in the near future.