Urinary proteomics for early diagnosis in diabetic nephropathy

Application of Proteomics and Machine Learning Methods to Study the Pathogenesis of Diabetic Nephropathy and Screen Urinary Biomarkers

Diabetic nephropathy (DN) has become the main cause of end-stage renal disease worldwide, causing significant health problems. Early diagnosis of the disease is quite inadequate. To screen urine biomarkers of DN and explore its potential mechanism, this study collected urine from 87 patients with type 2 diabetes mellitus (which will be classified into normal albuminuria, microalbuminuria, and macroalbuminuria groups) and 38 healthy subjects. Twelve individuals from each group were then randomly selected as the screening cohort for proteomics analysis and the rest as the validation cohort. The results showed that humoral immune response, complement activation, complement and coagulation cascades, renin-angiotensin system, and cell adhesion molecules were closely related to the progression of DN. Five overlapping proteins (KLK1, CSPG4, PLAU, SERPINA3, and ALB) were identified as potential biomarkers by machine learning methods. Among them, KLK1 and CSPG4 were positively correlated with the urinary albumin to creatinine ratio (UACR), and SERPINA3 was negatively correlated with the UACR, which were validated by enzyme-linked immunosorbent assay (ELISA). This study provides new insights into disease mechanisms and biomarkers for early diagnosis of DN.

The Urinary Glycopeptide Profile Differentiates Early Cardiorenal Risk in Subjects Not Meeting Criteria for Chronic Kidney Disease

Early diagnosis and treatment of chronic kidney disease (CKD) is a worldwide challenge. Subjects with albumin-to-creatinine ratio (ACR) ≥ 30 mg/g and preserved renal function are considered to be at no cardiorenal risk in clinical practice, but prospective clinical studies evidence increased risk, even at the high-normal (HN) ACR range (10-30 mg/g), supporting the need to identify other molecular indicators for early assessment of patients at higher risk. Following our previous studies, here we aim to stratify the normoalbuminuria range according to cardiorenal risk and identify the glycoproteins and N-glycosylation sites associated with kidney damage in subclinical CKD. Glycoproteins were analyzed in urine from hypertensive patients within the HN ACR range compared to control group (C; ACR < 10 mg/g) by mass spectrometry. A different cohort was analyzed for confirmation (ELISA) and sex perspective was evaluated. Patients' follow-up for 8 years since basal urine collection revealed higher renal function decline and ACR progression for HN patients. Differential N-glycopeptides and their N -glycosylation sites were also identified, together with their pathogenicity. N-glycosylation may condition pathological protein deregulation, and a panel of 62 glycoproteins evidenced alteration in normoalbuminuric subjects within the HN range. Haptoglobin-related protein, haptoglobin, afamin, transferrin, and immunoglobulin heavy constant gamma 1 (IGHG1) and 2 (IGHG2) showed increased levels in HN patients, pointing to disturbed iron metabolism and tubular reabsorption and supporting the tubule as a target of interest in the early progression of CKD. When analyzed separately, haptoglobin, afamin, transferrin, and IGHG2 remained significant in HN, in both women and men. At the peptide level, 172 N-glycopeptides showed differential abundance in HN patients, and 26 showed high pathogenicity, 10 of them belonging to glycoproteins that do not show variation between HN and C groups. This study highlights the value of glycosylation in subjects not meeting KDIGO criteria for CKD. The identified N-glycopeptides and glycosylation sites showed novel targets, for both the early assessment of individual cardiorenal risk and for intervention aimed at anticipating CKD progression.

Investigating and Annotating the Human Peptidome Profile from Urine under Normal Physiological Conditions

Examining the composition of the typical urinary peptidome and identifying the enzymes responsible for its formation holds significant importance, as it mirrors the normal physiological state of the human body. Any deviation from this normal profile could serve as an indicator of pathological processes occurring in vivo. Consequently, this study focuses on characterizing the normal urinary peptidome and investigating the various catalytic enzymes that are involved in generating these native peptides in urine. Our findings reveal that 1503 endogenous peptides, corresponding to 436 precursor proteins, were consistently identified robustly in at least 10 samples out of a total of 19 samples. Notably, the liver and kidneys exhibited the highest number of tissue-enriched or enhanced genes in the analyzed urinary peptidome. Furthermore, among the catalytic types, CTSD (cathepsin D) and MMP2 (matrix metalloproteinase-2) emerged as the most prominent peptidases in the aspartic and metallopeptidases categories, respectively. A comparison of our dataset with two of the most comprehensive urine peptidome datasets to date indicates a consistent relative abundance of core endogenous peptides for different proteins across all three datasets. These findings can serve as a foundational reference for the discovery of biomarkers in various human diseases.

A candidate panel of eight urinary proteins shows potential of early diagnosis and risk assessment for diabetic kidney disease in type 1 diabetes

Diabetic kidney disease (DKD) poses a significant health challenge for individuals with diabetes. At its initial stages, DKD often presents asymptomatically, and the standard for non-invasive diagnosis, the albumin-creatinine ratio (ACR), employs discrete categorizations (normal, microalbuminuria, macroalbuminuria) with limitations in sensitivity and specificity across diverse population cohorts. Single biomarker reliance further restricts the predictive value in clinical settings. Given the escalating prevalence of diabetes, our study uses proteomic technologies to identify novel urinary proteins as supplementary DKD biomarkers. A total of 158 T1D subjects provided urine samples, with 28 (15 DKD; 13 non-DKD) used in the discovery stage and 131 (45 DKD; 40 pDKD; 46 non-DKD) used in the confirmation. We identified eight proteins (A1BG, AMBP, AZGP1, BTD, RBP4, ORM2, GM2A, and PGCP), all of which demonstrated excellent area-under-the-curve (AUC) values (0.959 to 0.995) in distinguishing DKD from non-DKD. Furthermore, this multi-marker panel successfully segregated the most ambiguous group (microalbuminuria) into three distinct clusters, with 80% of subjects aligning either as DKD or non-DKD. The remaining 20% exhibited continued uncertainty. Overall, the use of these candidate urinary proteins allowed for the better classification of DKD and offered potential for significant improvements in the early identification of DKD in T1D populations.

Urinary biomarkers in kidney disease

BACKGROUND

Chronic kidney disease (CKD) affects many people worldwide and early diagnosis is essential for successful treatment and improved outcome. Unfortunately, current methods are insufficient especially for early disease detection. However, advances in the analytical methods for urinary biomarkers may provide a unique opportunity for diagnosis and management of CKD. This review explores evolving technology and highlights the importance of early marker detection in these patients.

APPROACH

A search strategy was set up using the terms CKD, biomarkers, and urine. The search included 53 studies comprising 37 biomarkers. The value of these biomarkers for CKD are based on their ability to diagnose CKD, monitor progression, assess mortality and nephrotoxicity.

RESULTS

KIM-1 was the best marker for diagnosis as it increased with the development of incident CKD. DKK3 increased in patients with declining eGFR, whereas UMOD decreased in those with declining kidney function. Unfortunately, none fulfilled all criteria to adequately assess mortality and nephrotoxicity.

CONCLUSION

New developments in the field of urinalysis using smart toilets may open several possibilities for urinary biomarkers. This review explored which biomarkers could be used for CKD disease detection and management.

Gestational Age-Related Urinary Peptidome Changes in Preterm and Term Born Infants

INTRODUCTION

Preterm infants are at risk for a variety of somatic and neurological disorders. In recent years, biofluid proteomics has emerged as a potential diagnostic tool for biomarker analysis. The aim of this study was to determine gestational age (GA)-related patterns of the urinary peptidome in preterm infants for researching potential novel prognostic biomarkers.

METHODS

We performed urinary peptidomics in longitudinal samples of 24 preterm (mean GA weeks 28 + 1 [24+1-31 + 6]) and 27 term born controls (mean GA weeks 39 + 2 [37+0-41 + 1]) using capillary electrophoresis combined with mass spectrometry (CE-MS). Peptides were sequenced using CE-MS/MS or LC-MS/MS analysis and were deposited, matched, and annotated in a Microsoft SQL database for statistical analysis. We compared their abundance in urine of preterm and term born infants and performed a validation analysis as well as correlations to GA and clinical risk scores.

RESULTS

Our results confirmed significant differences in the abundance of peptides and the hypothesis of age-dependent urinary peptidome changes in preterm and term infants. In preterm infants, SLC38A10 (solute carrier family 38 member 10) is one of the most abundant peptides. Combined urinary peptides correlated with clinical risk scores (p < 0.05).

CONCLUSION

This is the first study reporting GA-related urinary peptidome changes of preterm infants detected by CE-MS and a modulation of the peptidome with GA. Further research is required to locate peptidome clusters correlated with specific clinical complications and long-term outcome. This may identify preterm infants at higher risk for adverse outcome who would benefit from early intervention.

Kidney Disease and Proteomics: A Recent Overview of a Useful Tool for Improving Early Diagnosis

Kidney disease is a critical and potentially life-threatening degenerative condition that poses a significant global public health challenge due to its elevated rates of morbidity and mortality. It manifests primarily in two distinct clinical forms: acute kidney injury (AKI) and chronic kidney disease (CKD). The development of these conditions hinges on a multitude of factors, including the etiological agents and the presence of coexisting medical conditions. Despite disparities in their underlying pathogenic mechanisms, both AKI and CKD can progress to end-stage kidney disease (ESKD). This advanced stage is characterized by organ failure and its associated complications, greatly increasing the risk of mortality. There is an urgent need to delve into the pathogenic mechanisms underlying these diseases and to identify novel biomarkers that can facilitate earlier diagnosis. Such early detection is crucial for enhancing the efficacy of therapy and impeding disease progression. In this context, proteomic approaches have emerged as invaluable tools for uncovering potential new markers of different pathological conditions, including kidney diseases. In this chapter, we overview the recent discoveries achieved through diverse proteomic techniques aimed at identifying novel molecules that may play a pivotal role in kidney diseases such as diabetic kidney disease (DKD), IgA nephropathy (IgAN), CKD of unknown origin (CKDu), autosomal dominant polycystic kidney disease (ADPKD), lupus nephritis (LN), hypertensive nephropathy (HN), and COVID-19-associated acute kidney injury (COVID-AKI).

A set of urinary peptides can predict early renal damage in primary hypertension

OBJECTIVES

Renal diseases caused by primary hypertension (HTN) are often asymptomatic without sensitive markers for early diagnosis and prediction, easily progressing to severe and irreversible renal damage in patients with clinical manifestations. This study explored whether a set of urinary peptides could serve as a potential biomarker for early prediction of renal damage in HTN.

METHODS

Urinary peptides level of healthy individuals, HTN + normoalbuminuric and HTN + albuminuria patients were compared, and 22 baseline data including sex, age, renal function, hypertensive fundus lesions were collected. Patients diagnosed with HTN, albuminuria, and normal renal function were followed up. According to the follow-up results, the cut-off value of a set of urinary peptides in predicting hypertensive renal injury was calculated and analyzed in the high-risk and low-risk groups of HTN patients for its performance in detecting early hypertensive renal injury.

RESULTS

Among a sum of 319 participants, average urinary peptides level was significantly higher in patients with HTN than in normal individuals. A total of 147 HTN patients with normal albuminuria were followed up for a mean of 3.8 years. Thirty-five patients showed urinary albumin-to-creatinine ratio (uACR) at least 30 mg/g for three consecutive times. The receiver-operating characteristic (ROC) curve showed that the urinary peptides cut-off value for evaluating new-onset proteinuria in patients with HTN was 0.097. Based on this cut-off value, 39 and 108 patients were included in the high-risk and low-risk groups, respectively. Specifically, compared with patients in the low-risk group, those in the high-risk group showed significantly longer duration of HTN, higher proportions of hypertensive fundus lesions and at least 30 mg/g uACR, and higher levels of homocysteine (Hcy), cystatin C (CysC), beta-2 microglobulin (β2-MG), and uACR. 76.9% of high-risk patients had significantly higher new-onset proteinuria than the low-risk group. Correlation analysis demonstrated a positive correlation between urinary peptides and UACR ( r  = 0.494, P  < 0.001). The incidence of new-onset albuminuria was significantly higher in the high-risk group than in the low-risk group, as shown by Cox regression analysis. The areas under the curve of urinary peptides, Hcy, β2-MG and CysC were 0.925, 0.753, 0.796 and 0.769, respectively.

CONCLUSION

A set of urinary peptides is a predictor of new-onset proteinuria in patients with HTN, therefore, it can be used for diagnosing patients with early renal injury in patients with HTN, contributing to early prevention and treatment of hypertensive nephropathy.

Insulin and the kidneys: a contemporary view on the molecular basis

Insulin is a hormone that is composed of 51 amino acids and structurally organized as a hexamer comprising three heterodimers. Insulin is the central hormone involved in the control of glucose and lipid metabolism, aiding in processes such as body homeostasis and cell growth. Insulin is synthesized as a large preprohormone and has a leader sequence or signal peptide that appears to be responsible for transport to the endoplasmic reticulum membranes. The interaction of insulin with the kidneys is a dynamic and multicenter process, as it acts in multiple sites throughout the nephron. Insulin acts on a range of tissues, from the glomerulus to the renal tubule, by modulating different functions such as glomerular filtration, gluconeogenesis, natriuresis, glucose uptake, regulation of ion transport, and the prevention of apoptosis. On the other hand, there is sufficient evidence showing the insulin receptor's involvement in renal functions and its responsibility for the regulation of glucose homeostasis, which enables us to understand its contribution to the insulin resistance phenomenon and its association with the progression of diabetic kidney disease.

A classifier based on 273 urinary peptides predicts early renal damage in primary hypertension

OBJECTIVES

Renal diseases caused by primary hypertension (HTN) are often asymptomatic without sensitive markers for early diagnosis and prediction, easily progressing to severe and irreversible renal damage in patients with clinical manifestations. This study explored whether a classifier developed based on 273 urinary peptides (CKD273) could serve as a potential biomarker for early prediction of renal damage in HTN.

METHODS

Urinary CKD273 level of healthy individuals, HTN + normoalbuminuric and HTN + albuminuria patients were compared, and 22 baseline data including sex, age, renal function, and hypertensive fundus lesions were collected. Patients diagnosed with HTN, albuminuria, and normal renal function were followed up. According to the follow-up results, the cut-off value of CKD273 in predicting hypertensive renal injury was calculated and analyzed in the high-risk and low-risk groups of HTN patients for its performance in detecting early hypertensive renal injury.

RESULTS

Among a sum of 319 participants, average urinary CKD273 level was significantly higher in patients with HTN than in normal individuals. A total of 147 HTN patients with normal albuminuria were followed up for a mean of 3.8 years. Thirty-five patients showed urinary albumin-to-creatinine ratio (uACR) at least 30 mg/g for three consecutive times. The receiver-operating characteristic (ROC) curve showed that the urinary CKD273 cut-off value for evaluating new-onset proteinuria in patients with HTN was 0.097. Based on this cut-off value, 39 and 108 patients were included in the high-risk and low-risk groups, respectively. Specifically, compared with patients in the low-risk group, those in the high-risk group showed significantly longer duration of HTN, higher proportions of hypertensive fundus lesions and at least 30 mg/g uACR, and higher levels of homocysteine (Hcy), cystatin C (CysC), beta-2 microglobulin (β2-MG), and uACR. 76.9% of high-risk patients had significantly higher new-onset proteinuria than the low-risk group. Correlation analysis demonstrated a positive correlation between urinary CKD273 and UACR ( r  = 0.494, P  = 0.000). The incidence of new-onset albuminuria was significantly higher in the high-risk group than in the low-risk group, as shown by Cox regression analysis. The areas under the curve of CKD273, Hcy, β2-MG, and CysC were 0.925, 0.753, 0.796, and 0.769, respectively.

CONCLUSION

Urinary CKD273 is a predictor of new-onset proteinuria in patients with HTN, therefore, it can be used for diagnosing patients with early renal injury in patients with HTN, contributing to early prevention and treatment of hypertensive nephropathy.

Recent Advances in Urinary Peptide and Proteomic Biomarkers in Chronic Kidney Disease: A Systematic Review

Biomarker development, improvement, and clinical implementation in the context of kidney disease have been a central focus of biomedical research for decades. To this point, only serum creatinine and urinary albumin excretion are well-accepted biomarkers in kidney disease. With their known blind spot in the early stages of kidney impairment and their diagnostic limitations, there is a need for better and more specific biomarkers. With the rise in large-scale analyses of the thousands of peptides in serum or urine samples using mass spectrometry techniques, hopes for biomarker development are high. Advances in proteomic research have led to the discovery of an increasing amount of potential proteomic biomarkers and the identification of candidate biomarkers for clinical implementation in the context of kidney disease management. In this review that strictly follows the PRISMA guidelines, we focus on urinary peptide and especially peptidomic biomarkers emerging from recent research and underline the role of those with the highest potential for clinical implementation. The Web of Science database (all databases) was searched on 17 October 2022, using the search terms "marker *" OR biomarker * AND "renal disease" OR "kidney disease" AND "proteome *" OR "peptid *" AND "urin *". English, full-text, original articles on humans published within the last 5 years were included, which had been cited at least five times per year. Studies based on animal models, renal transplant studies, metabolite studies, studies on miRNA, and studies on exosomal vesicles were excluded, focusing on urinary peptide biomarkers. The described search led to the identification of 3668 articles and the application of inclusion and exclusion criteria, as well as abstract and consecutive full-text analyses of three independent authors to reach a final number of 62 studies for this manuscript. The 62 manuscripts encompassed eight established single peptide biomarkers and several proteomic classifiers, including CKD273 and IgAN237. This review provides a summary of the recent evidence on single peptide urinary biomarkers in CKD, while emphasizing the increasing role of proteomic biomarker research with new research on established and new proteomic biomarkers. Lessons learned from the last 5 years in this review might encourage future studies, hopefully resulting in the routine clinical applicability of new biomarkers.

Use of Computation Ecosystems to Analyze the Kidney-Heart Crosstalk

The identification of mediators for physiologic processes, correlation of molecular processes, or even pathophysiological processes within a single organ such as the kidney or heart has been extensively studied to answer specific research questions using organ-centered approaches in the past 50 years. However, it has become evident that these approaches do not adequately complement each other and display a distorted single-disease progression, lacking holistic multilevel/multidimensional correlations. Holistic approaches have become increasingly significant in understanding and uncovering high dimensional interactions and molecular overlaps between different organ systems in the pathophysiology of multimorbid and systemic diseases like cardiorenal syndrome because of pathological heart-kidney crosstalk. Holistic approaches to unraveling multimorbid diseases are based on the integration, merging, and correlation of extensive, heterogeneous, and multidimensional data from different data sources, both -omics and nonomics databases. These approaches aimed at generating viable and translatable disease models using mathematical, statistical, and computational tools, thereby creating first computational ecosystems. As part of these computational ecosystems, systems medicine solutions focus on the analysis of -omics data in single-organ diseases. However, the data-scientific requirements to address the complexity of multimodality and multimorbidity reach far beyond what is currently available and require multiphased and cross-sectional approaches. These approaches break down complexity into small and comprehensible challenges. Such holistic computational ecosystems encompass data, methods, processes, and interdisciplinary knowledge to manage the complexity of multiorgan crosstalk. Therefore, this review summarizes the current knowledge of kidney-heart crosstalk, along with methods and opportunities that arise from the novel application of computational ecosystems providing a holistic analysis on the example of kidney-heart crosstalk.

The Growing Challenge of Chronic Kidney Disease: An Overview of Current Knowledge

Chronic kidney disease (CKD) is becoming one of the world's most prevalent noncommunicable chronic diseases. The World Health Organization projects CKD to become the 5th most common chronic disease in 2040. Causes of CKD are multifactorial and diverse, but early-stage symptoms are often few and silent. Progression rates are highly variable, but patients encounter both an increased risk for end-stage kidney disease (ESKD) as well as increased cardiovascular risk. End-stage kidney disease incidence is generally low, but every single case carries a significant burden of illness and healthcare costs, making prevention by early intervention both desirable and worthwhile. This review focuses on the prevalence, diagnosis, and causes of CKD. In addition, we discuss the developments in the general treatment of CKD, with particular attention to what can be initiated in general practice. With the addition of recent landmark findings and the expansion of the indication for using sodium-glucose cotransporter 2 inhibitors, there are now new effective treatments to add to standard therapy. This will also be relevant for primary care physicians as many patients with CKD have their family physician as their primary health care professional handling kidney function preservation. In the future, more precise and less invasive diagnostic methods may not only improve the determination of the underlying cause of CKD but may also carry information regarding which treatment to use (i.e. personalized medicine). This could lead to a reduced number of preventive treatments per individual, while at the same time improving the prognosis. This review summarizes ongoing efforts in this area.

Molecular Pathways of Diabetic Kidney Disease Inferred from Proteomics

Diabetic kidney disease (DKD) affects an estimated 20-40% of type 2 diabetes patients and is among the most prevalent microvascular complications in this patient population, contributing to high morbidity and mortality rates. Currently, changes in albuminuria status are thought to be a primary indicator of the onset or progression of DKD, yet progressive nephropathy and renal impairment can occur in certain diabetic individuals who exhibit normal urinary albumin levels, emphasizing the lack of sensitivity and specificity associated with the use of albuminuria as a biomarker for detecting diabetic kidney disease and predicting DKD risk. According to the study, a non-invasive method for early detection or prediction of DKD may involve combining proteomic analytical techniques such second generation sequencing, mass spectrometry, two-dimensional gel electrophoresis, and other advanced system biology algorithms. Another category of proteins of relevance may now be provided by renal tissue biomarkers. The establishment of reliable proteomic biomarkers of DKD represents a novel approach to improving the diagnosis, prognostic evaluation, and treatment of affected patients. In the present review, a series of protein biomarkers that have been characterized to date are discussed, offering a theoretical foundation for future efforts to aid patients suffering from this debilitating microvascular complication.

Early renal structural changes and potential biomarkers in diabetic nephropathy

Diabetic nephropathy is one of the most serious microvascular complications of diabetes mellitus, with increasing prevalence and mortality. Currently, renal function is assessed clinically using albumin excretion rate and glomerular filtration rate. But before the appearance of micro-albumin, the glomerular structure has been severely damaged. Glomerular filtration rate based on serum creatinine is a certain underestimate of renal status. Early diagnosis of diabetic nephropathy has an important role in improving kidney function and delaying disease progression with drugs. There is an urgent need for biomarkers that can characterize the structural changes associated with the kidney. In this review, we focus on the early glomerular and tubular structural alterations, with a detailed description of the glomerular injury markers SMAD1 and Podocalyxin, and the tubular injury markers NGAL, Netrin-1, and L-FABP in the context of diabetic nephropathy. We have summarized the currently studied protein markers and performed bioprocess analysis. Also, a brief review of proteomic and scRNA-seq method in the search of diabetic nephropathy.

Dapagliflozin Improves the Urinary Proteomic Kidney-Risk Classifier CKD273 in Type 2 Diabetes with Albuminuria: A Randomized Clinical Trial

OBJECTIVE

To evaluate the effect of the sodium-glucose cotransporter 2 inhibitor dapagliflozin on the kidney-risk urinary proteomic classifier (CKD273) in persons with type 2 diabetes (T2D) and albuminuria.

RESEARCH DESIGN AND METHODS

In a double-blind, randomized, controlled, crossover trial, we assigned participants with T2D and urinary albumin to creatinine ratio (UACR) ≥30 mg/g to receive dapagliflozin or matching placebo added to guideline-recommended treatment (ClinicalTrial.gov identifier NCT02914691). Treatment periods lasted 12 weeks, when crossover to the opposing treatment occurred. The primary outcome was change in CKD273 score. Secondary outcomes included regression from high-risk to low-risk CKD273 pattern using the prespecified cutoff score of 0.154. The primary outcome was assessed using paired t test between end-to-end CKD273 scores after dapagliflozin and placebo treatment. The McNemar test was used to assess regression in risk category.

RESULTS

A total of 40 participants were randomized and 32 completed the trial with intact proteomic measurements. Twenty-eight (88%) were men, the baseline mean (SD) age was 63.0 (8.3) years, mean (SD) diabetes duration was 15.4 (4.5) years, mean HbA1c was 73 (14) mmol/mol (8.8% [1.3%]), and median (interquartile range) UACR was 154 (94, 329) mg/g. Dapagliflozin significantly lowered CKD273 score compared with placebo (-0.221; 95% CI -0.356, -0.087; P = 0.002). Fourteen participants exhibited a high-risk pattern after dapagliflozin treatment compared with 24 after participants placebo (P = 0.021).

CONCLUSIONS

Dapagliflozin added to renin-angiotensin system inhibition reduced the urinary proteomic classifier CKD273 in persons with T2D and albuminuria, paving the way for the further investigation of CKD273 as a modifiable kidney risk factor.

Microbiome and metabolome analysis to clarify the interaction between the urine microbiota and serum metabolites in Chinese patients with immunoglobulin A nephropathy

Background

The bacterial and metabolic networks in immunoglobin A nephropathy (IgAN), the most common type of primary chronic glomerulonephritis worldwide, have not been extensively studied. To help develop better methods for the diagnosis, treatment, and prognosis of IgAN, we characterized the alterations of the urinary microbiome and serum metabolome in patients with IgAN.

Methods

We analyzed serum and urine samples from Chinese patients with IgAN and healthy controls (HCs) using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and 16S ribosomal RNA gene sequencing.

Results

Patients with IgAN had a higher relative abundance of Actinomyces and a lower relative abundance of Lactobacillus. The elements of metabolism have been affected, including free amino acids, polyunsaturated fatty acids, and oligopeptides. We also identified the 9 metabolites that might be the core metabolites, including guanidinoacetic acid, apo-[3-methylcrotonoyl-CoA:carbon-dioxide ligase (ADP-forming)], and diethanolamine, which linked the metabolic networks between the urinary tract (UT) and blood. Other core metabolites, such as homocitrulline, apo-[3-methylcrotonoyl-CoA:carbon-dioxide ligase (ADP-forming)], butyrylcarnitine, formiminoglutamic acid (FIGLU), diethanolamine, and prolylhydroxyproline, were positively correlated with urinary mili-total protein (MTP). Conversely, Lactobacillus was negatively correlated with MTP.

Conclusions

We verified the connection between the disruption of the microbiota and serum metabolites, along with the clinical parameters, in patients with IgAN, which may help provide a tool for IgAN interventions.

Non-albuminuric Diabetic Kidney Disease Phenotype: Beyond Albuminuria

Diabetic kidney disease (DKD) is the leading cause of chronic and end-stage kidney disease worldwide. Its pathogenic mechanism is complex, and it can affect the entire structures of the kidneys such as the glomerulus, tubules and interstitium. Currently, the urinary albumin excretion rate and the estimated glomerular filtration rate are widely accepted as diagnostic criteria. However, some studies have reported a different or non-classical clinical course of DKD, with some patients showing declined kidney function with normal levels of albuminuria, known as the 'non-albuminuric DKD' phenotype. The pathogenesis of this phenotype remains unclear, but some clinical and pathological features have been postulated. This review explores the evidence regarding this topic.

Novel biomarkers for diabetic kidney disease

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

Pursuing Diabetic Nephropathy through Aqueous Humor Proteomics Analysis

In order to determine the possible aqueous humor (AH) proteins involved in diabetic nephropathy (DN) progression, we performed gel electrophoresis-liquid chromatography-tandem mass spectrometry protein profiling of AH samples from 5 patients with proliferative diabetic retinopathy (PDR) combined DN and 5 patients with PDR. Function enrichment analyses were carried out after the identification of differentially expressed proteins (DEPs). Protein-protein interaction networks were then built and the Search Tool for the Retrieval of Interacting Genes database and CytoNCA plugin in Cytoscape were utilized for module analysis. Ingenuity Pathway Analysis (IPA) was used to analyze disease and biological function, Tox function enrichment and upstream regulatory molecules/networks. Fifty-four DEPs were finally confirmed, whose enriched functions and pathways covered cell adhesion, extracellular exosome, complement activation, complement and coagulation cascades, etc. Nine hub genes were identified, including NCAM1, PLG, APOH, C3, PSAP, RBP4, CDH2, NUCB1, and GNS. IPA showed that C3 and PLG are involved in renal and urological system abnormalities. Conclusively, DEPs and hub proteins confirmed in this exploratory AH proteomic analysis may help us gain a deeper understanding of the molecular mechanisms involved in DN progression, providing novel candidate biomarkers for the early detection for diagnosis of DN.

Microtubule associated protein 4 phosphorylation-induced epithelial-to-mesenchymal transition of podocyte leads to proteinuria in diabetic nephropathy

BACKGROUND

Diabetic nephropathy (DN) involves various structural and functional changes because of chronic glycemic assault and kidney failure. Proteinuria is an early clinical manifestation of DN, but the associated pathogenesis remains elusive. This study aimed to investigate the role of microtubule associated protein 4 (MAP4) phosphorylation (p-MAP4) in proteinuria in DN and its possible mechanisms.

METHODS

In this study, the urine samples of diabetic patients and kidney tissues of streptozotocin (STZ)-induced diabetic mice were obtained to detect changes of p-MAP4. A murine model of hyperphosphorylated MAP4 was established to examine the effect of MAP4 phosphorylation in DN. Podocyte was applied to explore changes of kidney phenotypes and potential mechanisms with multiple methods.

RESULTS

Our results demonstrated elevated content of p-MAP4 in diabetic patients' urine samples, and increased kidney p-MAP4 in streptozocin (STZ)-induced diabetic mice. Moreover, p-MAP4 triggered proteinuria with aging in mice, and induced epithelial-to-mesenchymal transition (EMT) and apoptosis in podocytes. Additionally, p-MAP4 mice were much more susceptible to STZ treatment and showed robust DN pathology as compared to wild-type mice. In vitro study revealed high glucose (HG) triggered elevation of p-MAP4, rearrangement of microtubules and F-actin filaments with enhanced cell permeability, accompanied with dedifferentiation and apoptosis of podocytes. These effects were significantly reinforced by MAP4 hyperphosphorylation, and were rectified by MAP4 dephosphorylation. Notably, pretreatment of p38/MAPK inhibitor SB203580 reinstated all HG-induced pathological alterations.

CONCLUSIONS

The findings indicated a novel role for p-MAP4 in causing proteinuria in DN. Our results indicated the therapeutic potential of MAP4 in protecting against proteinuria and related diseases. Video Abstract.

No evidence of differential impact of sunflower and rapeseed oil on biomarkers of coronary artery disease or chronic kidney disease in healthy adults with overweight and obesity: result from a randomised control trial

Purpose

The perceived benefits and risks associated with seed oil intake remain controversial, with a limited number of studies investigating the impact of intake on a range of compounds used as cardiometabolic markers. This study aimed to explore the proteomic and cardiometabolic effects of commonly consumed seed oils in the UK, with different fatty acid profiles.

Methods

In a parallel randomised control design, healthy adults (n = 84), aged 25–72 with overweight or obesity were randomised to one of three groups: control (habitual diet, CON); 20 mL rapeseed oil per day (RO), or 20 mL sunflower oil per day (SO). Blood, spot urine and anthropometric measures were obtained at 0, 6 and 12 weeks. Proteomic biomarkers analysis was conducted for coronary arterial disease (CAD) and chronic kidney disease (CKD) using capillary electrophoresis coupled to mass spectrometry (CE-MS). Blood lipids, fasting blood glucose, glycative/oxidative stress and inflammatory markers were also analysed.

Results

No differences in change between time points were observed between groups for CAD or CKD peptide fingerprint scores. No change was detected within groups for CAD or CKD scores. No detectable differences were observed between groups at week 6 or 12 for the secondary outcomes, except median 8-isoprostane, ~ 50% higher in the SO group after 12-weeks compared to RO and CON groups (p = 0.03).

Conclusion

The replacement of habitual fat with either RO or SO for 12 weeks does not lead to an improvement or worsening in cardiovascular health markers in people with overweight or obesity.

Trial registration

Trial registration clinicaltrials.gov NCT04867629, retrospectively registered 30/04/2021.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00394-022-02810-5.

One-third of patients with lupus nephritis classified as complete responders continue to accrue progressive renal damage despite resolution of proteinuria

OBJECTIVE

Treatment response in lupus nephritis (LN) is defined based on proteinuria, yet protocol kidney biopsy studies have shown that patients with lupus can have active nephritis in the absence of proteinuria. Using estimated glomerular filtration rate (eGFR) trajectories, we characterised early chronic kidney disease in LN and examined whether certain patients continue to accrue renal damage despite proteinuric response.

METHODS

We conducted a single-centre study of patients diagnosed with their first episode of biopsy-proven class III, IV, and/or V LN (n=37). For each patient, eGFR trajectory was graphed over 5 years following renal biopsy. Participants were divided into those with progressive eGFR loss (eGFR slope <-5 mL/min/1.73 m2/year) versus those with stable eGFR. Participant demographics, renal biopsy features and response status at 1 year (urine protein to creatinine ratio <500 mg/g) were compared between eGFR trajectory groups.

RESULTS

Overall, 30% (n=11) of participants accrued progressive eGFR loss despite standard of care therapy over the first 5 years following renal biopsy. There were no significant differences in baseline renal biopsy features, medication regimens or comorbidities between eGFR trajectory groups. Resolution of proteinuria at 1 year did not differentiate between groups: 6 of 18 (33%) of complete responders continued to accrue renal damage compared with 5 of 17 (29%) of non-responders. Response status could not be assigned for two participants in the stable eGFR group due to missing clinical information at 1 year.

CONCLUSIONS

We identified an understudied category of patients with LN who accrue progressive renal damage despite apparent response to standard of care therapy. Better definitions and biomarkers of response are needed to improve renal outcomes and trial design.

Pathophysiologic Mechanisms and Potential Biomarkers in Diabetic Kidney Disease

Although diabetic kidney disease (DKD) remains the leading cause of end-stage kidney disease eventually requiring chronic kidney replacement therapy, the prevalence of DKD has failed to decline over the past 30 years. In order to reduce disease prevalence, extensive research has been ongoing to improve prediction of DKD onset and progression. Although the most commonly used markers of DKD are albuminuria and estimated glomerular filtration rate, their limitations have encouraged researchers to search for novel biomarkers that could improve risk stratification. Considering that DKD is a complex disease process that involves several pathophysiologic mechanisms such as hyperglycemia induced inflammation, oxidative stress, tubular damage, eventually leading to kidney damage and fibrosis, many novel biomarkers that capture one specific mechanism of the disease have been developed. Moreover, the increasing use of high-throughput omic approaches to analyze biological samples that include proteomics, metabolomics, and transcriptomics has emerged as a strong tool in biomarker discovery. This review will first describe recent advances in the understanding of the pathophysiology of DKD, and second, describe the current clinical biomarkers for DKD, as well as the current status of multiple potential novel biomarkers with respect to protein biomarkers, proteomics, metabolomics, and transcriptomics.

Stratification of diabetic kidney diseases via data-independent acquisition proteomics-based analysis of human kidney tissue specimens

AIM

The aims of this study were to analyze the proteomic differences in renal tissues from patients with diabetes mellitus (DM) and diabetic kidney disease (DKD) and to select sensitive biomarkers for early identification of DKD progression.

METHODS

Pressure cycling technology-pulse data-independent acquisition mass spectrometry was employed to investigate protein alterations in 36 formalin-fixed paraffin-embedded specimens. Then, bioinformatics analysis was performed to identify important signaling pathways and key molecules. Finally, the target proteins were validated in 60 blood and 30 urine samples.

RESULTS

A total of 52 up- and 311 down-regulated differential proteins were identified as differing among the advanced DKD samples, early DKD samples, and DM controls (adjusted p<0.05). These differentially expressed proteins were mainly involved in ion transport, apoptosis regulation, and the inflammatory response. UniProt database analysis showed that these proteins were mostly enriched in signaling pathways related to metabolism, apoptosis, and inflammation. NBR1 was significantly up-regulated in both early and advanced DKD, with fold changes (FCs) of 175 and 184, respectively (both p<0.01). In addition, VPS37A and ATG4B were significantly down-regulated with DKD progression, with FCs of 0.140 and 0.088, respectively, in advanced DKD and 0.533 and 0.192, respectively, in early DKD compared with the DM control group (both p<0.01). Bioinformatics analysis showed that NBR1, VPS37A, and ATG4B are closely related to autophagy. We also found that serum levels of the three proteins and urine levels of NBR1 decreased with disease progression. Moreover, there was a significant difference in serum VPS37A and ATG4B levels between patients with early and advanced DKD (both p<0.05). The immunohistochemistry assaay exhibited that the three proteins were expressed in renal tubular cells, and NBR1 was also expressed in the cystic wall of renal glomeruli.

CONCLUSION

The increase in NBR1 expression and the decrease in ATG4B and VPS37 expression in renal tissue are closely related to inhibition of the autophagy pathway, which may contribute to DKD development or progression. These three proteins may serve as sensitive serum biomarkers for early identification of DKD progression.

Comparison of Nonalbuminuric and Albuminuric Diabetic Kidney Disease Among Patients With Type 2 Diabetes: A Systematic Review and Meta-Analysis

BACKGROUND

Diabetic kidney disease (DKD) is one of most common complications of diabetes. Recently, the classical phenotype of DKD, which is characterized by albuminuria preceding renal insufficiency, has been challenged since a subset of diabetic patients with renal insufficiency but without albuminuria has been increasingly reported. However, the available evidence is inconsistent. Thus, the present systematic review will assess and summarize the available data regarding nonalbuminuric diabetic kidney disease (NADKD).

METHODS

PubMed, Embase, and Cochrane were searched for clinical trials related to NADKD. The results were limited to full-text articles published in English, without restrictions on the publication time. The quality of clinical trials was appraised, and the data were extracted. Meta-analysis was conducted using a random-effects model. Descriptive analysis was performed if the data were insufficient.

RESULTS

A final total of 31 articles were included in this review. The meta-analysis of 18 studies showed that compared with albuminuric DKD, patients with NADKD were older (MD = 1.04 years old, 95% CI [0.52, 1.57], p < 0.05); were more often women (Male RR = 0.74, 95% CI [0.68, 0.81], p < 0.05); had shorter diabetes duration (MD = -2.9 years, 95% CI [-3.63, -2.18], p < 0.05), lower HbA1c levels (MD = -0.34%, 95% CI [-0.42, -0.25], p < 0.05), and lower blood pressure (systolic blood pressure MD = -6.21 mmHg, 95% CI [-9.41, -3.0], p < 0.05; diastolic blood pressure MD = -1.27 mmHg, 95% CI [-2.15, 4.0], p < 0.05); less frequently experienced diabetic retinopathy (RR = 0.58, 95% CI [0.51, 0.67], p < 0.05); and less frequently used renin-angiotensin-aldosterone system (RAAS) inhibitors. The underlying pathology of NADKD might be different from that of the classic phenotype of DKD, which is associated with more advanced tubulointerstitial and vascular lesions but mild typical glomerular lesions. The annual estimated glomerular filtration rate decline tended to be lower in patients with NADKD than in those with albuminuric DKD. The risk for cardiovascular disease, end-stage renal disease, and all-cause death was lower for patients with NADKD than patients with albuminuric DKD.

CONCLUSIONS

The prevalence of NADKD has increased in recent decades, and its characteristics, pathology, and prognosis are different from those of albuminuric DKD; thus, diagnosis and treatment strategies should be different. More attention should be given to this phenotype.

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.

Urinary Protein and Peptide Markers in Chronic Kidney Disease

Chronic kidney disease (CKD) is a non-specific type of kidney disease that causes a gradual decline in kidney function (from months to years). CKD is a significant risk factor for death, cardiovascular disease, and end-stage renal disease. CKDs of different origins may have the same clinical and laboratory manifestations but different progression rates, which requires early diagnosis to determine. This review focuses on protein/peptide biomarkers of the leading causes of CKD: diabetic nephropathy, IgA nephropathy, lupus nephritis, focal segmental glomerulosclerosis, and membranous nephropathy. Mass spectrometry (MS) approaches provided the most information about urinary peptide and protein contents in different nephropathies. New analytical approaches allow urinary proteomic-peptide profiles to be used as early non-invasive diagnostic tools for specific morphological forms of kidney disease and may become a safe alternative to renal biopsy. MS studies of the key pathogenetic mechanisms of renal disease progression may also contribute to developing new approaches for targeted therapy.

Large-Scale Proteomic Assessment of Urinary Extracellular Vesicles Highlights Their Reliability in Reflecting Protein Changes in the Kidney

BACKGROUND

Urinary extracellular vesicles (uEVs) are secreted into urine by cells from the kidneys and urinary tract. Although changes in uEV proteins are used for quantitative assessment of protein levels in the kidney or biomarker discovery, whether they faithfully reflect (patho)physiologic changes in the kidney is a matter of debate.

METHODS

Mass spectrometry was used to compare in an unbiased manner the correlations between protein levels in uEVs and kidney tissue from the same animal. Studies were performed on rats fed a normal or high K⁺ diet.

RESULTS

Absolute quantification determined a positive correlation (Pearson R=0.46 or 0.45, control or high K⁺ respectively, P<0.0001) between the approximately 1000 proteins identified in uEVs and corresponding kidney tissue. Transmembrane proteins had greater positive correlations relative to cytoplasmic proteins. Proteins with high correlations (R>0.9), included exosome markers Tsg101 and Alix. Relative quantification highlighted a monotonic relationship between altered transporter/channel abundances in uEVs and the kidney after dietary K⁺ manipulation. Analysis of genetic mouse models also revealed correlations between uEVs and kidney.

CONCLUSION

This large-scale unbiased analysis identifies uEV proteins that track the abundance of the parent proteins in the kidney. The data form a novel resource for the kidney community and support the reliability of using uEV protein changes to monitor specific physiologic responses and disease mechanisms.

Urinary peptidome and diabetic retinopathy in the DIRECT-Protect 1 and 2 trials

BACKGROUND

Given the association of diabetic retinopathy (DR) and kidney disease, we investigated the urinary peptidome to presence and deterioration of DR in a post hoc analysis of trials investigating the effect of candesartan on progression of DR in type 1 and type 2 diabetes, respectively.

METHODS

Baseline urinary peptidomic analysis was performed on a random selection of 783 and 792 subjects in two randomized controlled trials, DIRECT-Protect 1 and 2, respectively. End points were two-step (RET2) and three-step (RET3) change in Early Treatment of Diabetic Retinopathy Study protocol (ETDRS) defined level. Peptide levels were correlated to baseline EDTRS level in a discovery set of 2/3 of the participants from DIRECT-Protect 1. The identified peptides were then validated cross-sectionally in the remaining 1/3 from DIRECT-Protect 1. Thereafter, peptides identified in the discovery set were assessed in the entire DIRECT-Protect 1 and 2 cohorts and significant peptides were tested longitudinally.

RESULTS

Follow-up ranged 4.0-4.7 years. 24 peptides were associated with baseline DR in the discovery set. COL3A1 (seq: NTG~) and COL4A1 (seq: DGA~) were associated with baseline DR in the validation set (Rho: -.223, p < 0.001 and Rho: -.141, p = 0.024). Neither was significantly associated with end points. Assessing the 24 identified peptides in the entire cohorts, several collagen peptides were associated with baseline DR and end points; however, there was no overlap across diabetes types.

CONCLUSIONS

We identified several urinary peptides (mainly collagen) associated with the presence of DR, however they could not be conclusively associated with worsening of DR.

Urine S-Adenosylmethionine are Related to Degree of Renal Insufficiency in Patients with Chronic Kidney Disease

OBJECTIVE

To determine whether urine S-adenosylmethionine (SAM) might be an indicator of chronic kidney disease (CKD).

METHODS

We investigated urine levels of SAM and related metabolites (S-adenosylhomocysteine and homocysteine cysteine) in 62 patients (average age, 65.9 years) with CKD (stages II-V).

RESULTS

Patients with stages III-V CKD stages have significantly decreased urine levels and SAM/S-adenosylhomocysteine ratio and also cysteine/homocysteine ratio in blood plasma (P <.05), compared with patients with stage II CKD. Urine SAM levels allowed us to distinguish patients with mildly decreased kidney function from those with moderate to severe renal impairment (AUC, 0.791; sensitivity, 85%; specificity, 78.6%).

CONCLUSIONS

Our study results demonstrate that urine SAM is a potent biomarker for monitoring renal function decline at early CKD stages. Urine SAM testing confers an additional advantage to healthcare professionals in that it is noninvasive.

Urinary small extracellular vesicles derived CCL21 mRNA as biomarker linked with pathogenesis for diabetic nephropathy

Background

Diabetic nephropathy (DN) is a leading cause of renal failure, whereas the effective and early diagnostic biomarkers are still lacking.

Methods

Fourteen cytokines and chemokines mRNA were detected in urinary extracellular vesicles (EVs) from the screening cohort including 4 healthy controls (HC), 4 diabetes mellitus (DM) and 4 biopsy-proven DN patients, and was validated in another 16 HC and 15 DM and 28 DN patients. Correlation analysis was performed between the candidate biomarkers and clinic parameters as well as kidney histological changes. The findings were also confirmed in DN rat model with single injection of STZ.

Results

The number of small EVs secreted in urine was increased in DN patients compared to DM patients and healthy controls, with expression of AQP1 (a marker of proximal tubules) and AQP2 (a marker of distal/collecting tubules). Small EVs derived CCL21 mRNA increased significantly in DN patients and correlated with level of proteinuria and eGFR. Interestingly, elevated CCL21 mRNA from urine small EVs was observed in DN patients with normal renal function and could discriminate early DN patients from DM more efficiently compared to eGFR and proteinuria. CCL21 also showed an accurate diagnostic ability in distinguishing incipient from overt DN. Histologically, CCL21 mRNA expression increased progressively with the deterioration of tubulointerstitial inflammation and showed the highest level in nodular sclerosis group (class III) in DN patients. Remarkable infiltration of CD3 positive T cells including both CD4 and CD8 positive T cell population were observed in DN patients with high-CCL21 expression. Besides, accumulation of CD3 positive T cells correlated with level of urinary small EVs derived CCL21 and co-localized with CCL21 in the tubulointerstitium in DN patients. Finally, the correlation of CCL21 expression in renal cortex and urinary small EVs was confirmed in STZ-induced DN rat model.

Conclusions

Urinary small EVs derived CCL21 mRNA may serve as early biomarker for identifying DN linked with pathogenesis. CCL21 mRNA mediated T cell infiltration may constitute the key mechanism of chronic inflammation in DN.

Proteomic Biomarkers in the Cardiorenal Syndrome: Toward Deciphering Molecular Pathophysiology

Cardiorenal syndrome (CRS) is defined by coexisting heart and renal dysfunctions. Malfunction of 1 organ may cause dysfunction of the other with variable causative disease that defines the type of CRS (1-5). Numerous studies showed that the prevalence of cardiovascular disease is increased in patients with chronic kidney disease (CKD). Similarly, CKD affects a large proportion of patients with heart failure. This overlap between primary heart or primary kidney disease blurs cause-effect inferences of the initiator/target organ. The classical subdivision of CRS in 5 categories does not provide pathophysiological suggestions for targeted intervention. It seems timely to revisit the value of CRS biomarkers in a pathophysiology-centered approach. We systematically reviewed the literature in CRS, which revealed 53 clinical studies describing the use of 44 biomarkers and 4 proteomic panels. All biomarkers are involved in at least one of the CRS comorbidities. Among the pathways affected, inflammation, aberrant glucose metabolism, neurohormonal activation, and oxidative stress are well described. There is growing evidence that fibrosis may be the "cornerstone" that unifies most of the pathways leading to CRS. Formation of excess fibrous connective tissue antedates CRS in many cases. This review highlights that biomarkers reflecting fibrosis may be of substantial clinical value in the early detection, prognostication, and guiding treatment of CRS. Biomarkers detecting changes in collagen turnover in the extracellular matrix of heart and kidney appear able to depict subclinical changes in the fibrotic remodeling of tissues and constitute a promising approach toward personalized intervention in CRS.

Novel biomarkers of diabetic kidney disease: current status and potential clinical application

Diabetic kidney disease (DKD) is a leading cause of end-stage renal disease (ESRD). Although both albuminuria and glomerular filtration rate (GFR) are well-established diagnostic/prognostic biomarkers of DKD, they have important limitations. There is, thus, increasing quest to find novel biomarkers to identify the disease in an early stage and to improve risk stratification. In this review, we will outline the major pitfalls of currently available markers, describe promising novel biomarkers, and discuss their potential clinical relevance. In particular, we will focus on the importance of recent advancements in multi-omic technologies in the discovery of new DKD biomarkers. In addition, we will provide an update on new emerging approaches to explore renal function and structure, using functional tests and imaging.

Kidney Biopsy in Type 2 Diabetic Patients: Critical Reflections on Present Indications and Diagnostic Alternatives

Roughly 3% of patients worldwide with a new diagnosis of type 2 diabetes mellitus (T2DM) already have an overt nephropathy at diagnosis and about 20-30% of the remaining ones develop a complication of this kind later in life. The early identification of kidney disease in diabetic patients is important as it slows its progression, which is important not only because this reduces the need for renal replacement therapy, but also because it decreases the high rate of mortality and morbidity associated with a reduction in kidney function. The increasing prevalence of type 2 diabetes and the consequent greater probability of finding different types of kidney diseases in diabetic patients frequently gives rise to overlapping diagnoses, a definition encompassing the differential diagnosis between diabetic and non-diabetic kidney disease. The issue is made more complex by the acknowledgement of the increasing frequency of presentations of what is termed "diabetic kidney disease" without relevant proteinuria, in particular in T2DM patients. Distinguishing between diabetes related and non-diabetes related forms of kidney disease in diabetic patients is not only a semantic question, as different diseases require different clinical management. However, while the urologic and macrovascular complications of diabetes, as well as overlapping parenchymal damage, can be diagnosed by means of imaging studies, often only a kidney biopsy will make a differential diagnosis possible. In fact, the coexistence of typical diabetic lesions, such as nodular glomerulopathy or glomerulosclerosis, with different glomerular, vascular and tubulo-interstitial alterations has been extensively described, and an analysis of the dominant histological pattern can contribute to determining what therapeutic approach should be adopted. However, due to the high frequency of kidney diseases, and to the fact that T2DM patients are often affected by multiple comorbidities, a kidney biopsy is not generally performed in T2DM patients. What follows is a review aiming to discuss the diagnostic work-up, on the base of clinical, laboratory and imaging criteria, and evaluate the present indications and alternatives to renal biopsy.

Clinical significance of serum homocysteine as a biomarker for early diagnosis of diabetic nephropathy in type 2 diabetes mellitus patients

Objective

The aim of this study was to investigate the clinical significance of serum homocysteine (Hcy) as a biomarker for early diagnosis of diabetic nephropathy (DN) in type 2 diabetes mellitus (T2DM) patients.

Methods

Fifty-five T2DM patients with DN and 51 T2DM patients without DN were prospectively recruited from January 2016 to May 2020 in our hospital. The serum Hcy was tested by electrochemiluminescence assay in DN and T2DM groups and compared. The diagnostic efficacy of serum Hcy as a biomarker for early diagnosis of DN was evaluated by calculating the diagnostic sensitivity, specificity and area under the ROC curve (AUC).

Results

The serum levels of Hcy were 15.49 ± 5.40 and 9.23 ± 3.15 μmol/L for DN and T2DM patients, respectively, with statistical difference (t = 7.21, P < 0.001). In the DN group, the serum Hcy levels for patients with hyperfiltration, intermittent proteinuria, microalbuminuria, macroalbuminuria and uremic were 10.99 ± 2.57, 13.90 ± 2.86, 15.38 ± 4.77, 18.98 ± 4.36 and 23.31 ± 5.22 μmol/L, respectively, which indicated that serum Hcy levels in DN were higher than those of T2DM patients and correlated with patient’s renal damage. Using the serum Hcy level as the reference, the diagnostic sensitivity, specificity and AUC were 84.31 (71.41–92.98)%, 74.55 (61.00–85.33)% and 0.85 (0.78–0.92)%, respectively, with the cutoff value of 12.08 between DN and T2DM. The serum Hcy also had relatively good differential diagnostic efficacy between different DN stages with high sensitivity, specificity and AUC.

Conclusion

Serum Hcy was obviously elevated in DN compared to T2MD and correlated with the renal damage severity, which can be applied as a potential serological marker for early diagnosis of DN.

Integrative Biology of Diabetic Retinal Disease: Lessons from Diabetic Kidney Disease

Diabetic retinal disease (DRD) remains the most common cause of vision loss in adults of working age. Progress on the development of new therapies for DRD has been limited by the complexity of the human eye, which constrains the utility of traditional research techniques, including animal and tissue culture models-a problem shared by those in the field of kidney disease research. By contrast, significant progress in the study of diabetic kidney disease (DKD) has resulted from the successful employment of systems biology approaches. Systems biology is widely used to comprehensively understand complex human diseases through the unbiased integration of genetic, environmental, and phenotypic aspects of the disease with the functional and structural manifestations of the disease. The application of a systems biology approach to DRD may help to clarify the molecular basis of the disease and its progression. Acquiring this type of information might enable the development of personalized treatment approaches, with the goal of discovering new therapies targeted to an individual's specific DRD pathophysiology and phenotype. Furthermore, recent efforts have revealed shared and distinct pathways and molecular targets of DRD and DKD, highlighting the complex pathophysiology of these diseases and raising the possibility of therapeutics beneficial to both organs. The objective of this review is to survey the current understanding of DRD pathophysiology and to demonstrate the investigative approaches currently applied to DKD that could promote a more thorough understanding of the structure, function, and progression of DRD.

Linking Kidney and Cardiovascular Complications in Diabetes-Impact on Prognostication and Treatment: The 2019 Edwin Bierman Award Lecture

In diabetes, increasing albuminuria and decreasing glomerular filtration rate are hallmarks of chronic kidney disease in diabetes and increase the risk of atherosclerotic cardiovascular events and mortality as well as the risk for end-stage kidney disease. For two decades, standard of care has been controlling risk factors, such as glucose, blood pressure, lipids, and lifestyle factors, and specifically use of agents blocking the renin-angiotensin system. This has improved outcome, but a large unmet need has been obvious. After many failed attempts to advance the therapeutic options, the past few years have provided several new promising treatment options such as sodium-glucose cotransporter 2 inhibitors, endothelin receptor antagonists, glucagon-like peptide 1 agonists, and nonsteroidal mineralocorticoid receptor antagonists. The benefits and side effects of these agents demonstrate the link between kidney and heart; some have beneficial effects on both, whereas for other potentially renoprotective agents, development of heart failure has been a limiting factor. They work on different pathways such as hemodynamic, metabolic, inflammatory, and fibrotic targets. We propose that treatment may be personalized if biomarkers or physiological investigations assessing activity in these pathways are applied. This could potentially pave the way for precision medicine, where treatment is optimized for maximal benefit and minimal adverse outcomes. At least it may help prioritizing agents for an individual subject.

Genomics, Proteomics and Metabolomics Approaches for Predicting Diabetic Nephropathy in Type 2 Diabetes Mellitus Patients

BACKGROUND

There is a continuous rise in the prevalence of type 2 diabetes mellitus (T2DM) worldwide and most patients are unaware of the presence of this chronic disease at the early stages. T2DM is associated with complications related to long-term damage and failure of multiple organ systems caused by vascular changes associated with glycated end products, oxidative stress, mild inflammation, and neovascularization. Among the most frequent complications of T2DM observed in about 20-40% of T2DM patients is diabetes nephropathy (DN).

METHODS

A literature search was made in view of highlighting the novel applications of genomics, proteomics and metabolomics, as the new prospective strategy for predicting DN in T2DM patients.

RESULTS

The complexity of DN requires a comprehensive and unbiased approach to investigate the main causes of disease and identify the most important mechanisms underlying its development. With the help of evolving throughput technology, rapidly evolving information can now be applied to clinical practice.

DISCUSSION

DN is also the leading cause of end-stage renal disease and comorbidity independent of T2DM. In terms of the comorbidity level, DN has many phenotypes; therefore, timely diagnosis is required to prevent these complications. Currently, urine albumin-to-creatinine ratio and estimated glomerular filtration rate (eGFR) are gold standards for assessing glomerular damage and changes in renal function. However, GFR estimation based on creatinine is limited to hyperfiltration status; therefore, this makes albuminuria and eGFR indicators less reliable for early-stage diagnosis of DN.

CONCLUSION

The combination of genomics, proteomics, and metabolomics assays as suitable biological systems can provide new and deeper insights into the pathogenesis of diabetes, as well as discover prospects for developing suitable and targeted interventions.

Discovery, validation and sequencing of urinary peptides for diagnosis of liver fibrosis-A multicentre study

Background

Liver fibrosis is a consequence of chronic inflammation and is associated with protein changes within the hepatocytes structure. In this study, we aimed to investigate if this is reflected by the urinary proteome and can be explored to diagnose liver fibrosis in patients with chronic liver disease.

Methods

In a multicentre combined cross-sectional and prospective diagnostic test validation study, 129 patients with varying degrees of liver fibrosis and 223 controls without liver fibrosis were recruited. Additionally, 41 patients with no liver, but kidney fibrosis were included to evaluate interference with expressions of kidney fibrosis. Urinary low molecular weight proteome was analysed by capillary electrophoresis coupled to mass spectrometry (CE-MS) and a support vector machine marker model was established by integration of peptide markers for liver fibrosis.

Findings

CE-MS enabled identification of 50 urinary peptides associated with liver fibrosis. When combined into a classifier, LivFib-50, it separated patients with liver fibrosis (N = 31) from non-liver disease controls (N = 123) in cross-sectional diagnostic phase II evaluation with an area under the curve (AUC) of 0.94 (95% confidence intervals (CI): 0.89–0.97, p<0.0001). When adjusted for age, LivFib-50 demonstrated an AUC of 0.94 (95% CI: 0.89–0.97, p<0.0001) in chronic liver disease patients with (N = 19) or without (N = 17) liver fibrosis progression. In this prospective diagnostic phase III validation set, age-adjusted LivFib-50 showed 84.2% sensitivity (95% CI: 60.4–96.6) and 82.4% specificity (95% CI: 56.6–96.2) for detection of liver fibrosis. The sequence-identified peptides are mainly fragments of collagen chains, uromodulin and Na/K-transporting ATPase subunit γ. We also identified ten putative proteolytic cleavage sites, eight were specific for matrix metallopeptidases and two for cathepsins.

Interpretation

In liver fibrosis, urinary peptides profiling offers potential diagnostic markers and leads to discovery of proteolytic sites that could be targets for developing anti-fibrotic therapy.

Biomarkers in Progressive Chronic Kidney Disease. Still a Long Way to Go

The traditional chronic kidney disease (CKD) biomarkers (eGFR based on serum creatinine, sex and age and albuminuria) cannot predict a patient's individual risk for developing progressive CKD. For this reason, it is necessary to identify novel CKD biomarkers that will be able to predict which patients are prone to develop progressive disease and discriminate between disease processes in different parts of the nephron (glomeruli or tubules). A good biomarker should change before or simultaneously with lesion development and its changes should correlate strongly with lesion development. Also, there should be a close relationship between severity of injury and amount of detectable biomarker and its levels should decrease with diminishing injury. Among the large number of molecules under investigation, we have reviewed the most promising ones: NGAL and KIM-1, MCP-1, MMP-9, clusterin, MMP-9, TIMP-1, Procollagen I alpha 1 and suPAR. All these, have been studied as biomarkers for prediction of CKD progression in cohorts of patients with chronic kidney disease of different stages and various aetiologies (proteinuric and non-proteinuric, glomerulonephritides, diabetic, hypertensive and polycystic kidney disease). There is evidence that these molecules could be useful as biomarkers for progressive chronic kidney disease, however, the available data are not enough to draw final conclusions. Further studies with large cohorts and long follow-up are required to identify appropriate biomarkers, that will be able to accurately and reliably define the risk for progressive chronic kidney disease.

Assessment of urinary NGAL for differential diagnosis and progression of diabetic kidney disease

OBJECTIVE

Chronic kidney disease (CKD) related to diabetes has become more common than glomerulonephritis in recent years. Given the inefficient and difficult identification of diabetic kidney disease (DKD) from non-diabetic kidney disease (NDKD) as well as a result of emerging evidence supporting a role for tubular involvement in DKD, we aimed to investigate the utility of urinary neutrophil gelatinase-associated lipocalin (uNGAL) in the differential diagnosis and predictive value of DKD from NDKD.

METHODS

Data for 100 type 2 diabetic patients with CKD at our center from June 2016 to August 2019 were reviewed. All the patients were categorized into 2 groups by the renal biopsy results: DKD and NDKD. Urinary NGAL levels were normalized by urinary creatinine and calculated as uNGAL/creatinine ratios (uNCR). The independent factors of the occurrence of DKD and the diagnostic implications of uNCR were explored by logistic regression and receiver-operating characteristic (ROC) curve analysis. In addition, we analyzed the relationship between uNCR and proteinuria in patients with DKD by Pearson test and linear regression. Kaplan-Meier survival analysis was performed to assess the prospective association of uNCR with the renal outcome.

RESULTS

Significantly higher levels of uNCR were observed in patients with DKD when compared to those with NDKD (28.65 ng/mg vs 27.47 ng/mg, p< .001). uNCR was identified as an independent risk factor for the occurrence of DKD in diabetic patients with CKD (odds ratio [OR] = 1.020; 95%CI = [1.001-1.399], p = .042). The optimal cutoff value of uNCR for predicting DKD was 60.685 ng/mg with high specificity (90.5%) but relatively low sensitivity (55.7%). In Pearson test, uNCR was positively correlated with proteinuria, serum creatine, blood urea nitrogen, duration of diabetes, interstitial inflammation score and global sclerosis, whereas it was inversely correlated with eGFR, hemoglobin, serum albumin and 25-hydroxy vitamin D. Furthermore, in a fully adjusted model including eGFR, serum albumin and total cholesterol, the group with uNCR>60.685 ng/mg was associated with 7.595 times higher likelihood of nephrotic-range proteinuria compared to the group with uNCR≤60.685 ng/mg. In the Kaplan-Meier survival analysis, the event-free survival probability in patients with uNCR>60.685 ng/mg was significantly lower than those with uNCR≤60.685 ng/mg (p = .048).

CONCLUSIONS

uNCR might serve as a potential tool for identifying cases in which there was a high clinical suspicion of DKD and that in whom confirmatory biopsy could be considered, and the best predictive cutoff value of normalized uNCR for DKD diagnosis was 60.685 ng/mg. Type 2 diabetic patients with increased level of uNCR had higher risk to nephrotic-range proteinuria and worse renal outcome.

Reckoning the Dearth of Bioinformatics in the Arena of Diabetic Nephropathy (DN)—Need to Improvise

Diabetic nephropathy (DN) is a recent rising concern amongst diabetics and diabetologist. Characterized by abnormal renal function and ending in total loss of kidney function, this is becoming a lurking danger for the ever increasing population of diabetics. This review touches upon the intensity of this complication and briefly reviews the role of bioinformatics in the area of diabetes. The advances made in the area of DN using proteomic approaches are presented. Compared to the enumerable inputs observed through the use of bioinformatics resources in the area of proteomics and even diabetes, the existing scenario of skeletal application of bioinformatics advances to DN is highlighted and the reasons behind this discussed. As this review highlights, almost none of the well-established tools that have brought breakthroughs in proteomic research have been applied into DN. Laborious, voluminous, cost expensive and time-consuming methodologies and advances in diagnostics and biomarker discovery promised through beckoning bioinformatics mechanistic approaches to improvise DN research and achieve breakthroughs. This review is expected to sensitize the researchers to fill in this gap, exploiting the available inputs from bioinformatics resources.

Urinary peptidomic biomarkers of renal function in heart transplant recipients

Background

Chronic kidney disease (CKD) is common in patients after heart transplantation (HTx). We assessed whether in HTx recipients the proteomic urinary classifier CKD273 or sequenced urinary peptides revealing the parental proteins correlated with the estimated glomerular filtration rate (eGFR).

Methods

In 368 HTx patients, we measured the urinary peptidome and analysed CKD273 and 48 urinary peptides with a detectable signal in >95% of participants. After 9.1 months (median), eGFR and the urinary biomarkers were reassessed.

Results

In multivariable Bonferroni-corrected analyses of the baseline data, a 1-SD increase in CKD273 was associated with a 11.4 [95% confidence interval (CI) 7.25–15.5] mL/min/1.73 m² lower eGFR and an odds ratio of 2.63 (1.56–4.46) for having eGFR <60 mL/min/1.73 m². While relating eGFR category at follow-up to baseline urinary biomarkers, CKD273 had higher (P = 0.007) area under the curve (0.75; 95% CI 0.70–0.80) than 24-h proteinuria (0.64; 95% CI 0.58–0.69), but additional adjustment for baseline eGFR removed significance of both biomarkers. In partial least squares analysis, the strongest correlates of the multivariable-adjusted baseline eGFR were fragments of collagen I (positive) and the mucin-1 subunit α (inverse). Associations between the changes in eGFR and the urinary markers were inverse for CKD273 and mucin-1 and positive for urinary collagen I.

Conclusions

With the exception of baseline eGFR, CKD273 was more closer associated with imminent renal dysfunction than 24-h proteinuria. Fragments of collagen I and mucin-1—respectively, positively and inversely associated with eGFR and change in eGFR—are single-peptide markers associated with renal dysfunction.

Early detection of diabetic kidney disease by urinary proteomics and subsequent intervention with spironolactone to delay progression (PRIORITY): a prospective observational study and embedded randomised placebo-controlled trial

BACKGROUND

Microalbuminuria is an early sign of kidney disease in people with diabetes and indicates increased risk of cardiovascular disease. We tested whether a urinary proteomic risk classifier (CKD273) score was associated with development of microalbuminuria and whether progression to microalbuminuria could be prevented with the mineralocorticoid receptor antagonist spironolactone.

METHODS

In this multicentre, prospective, observational study with embedded randomised controlled trial (PRIORITY), we recruited people with type 2 diabetes, normal urinary albumin excretion, and preserved renal function from 15 specialist centres in ten European countries. All participants (observational cohort) were tested with the CKD273 classifier and classified as high risk (CKD273 classifier score >0·154) or low risk (≤0·154). Participants who were classified as high risk were entered into a randomised controlled trial and randomly assigned (1:1), by use of an interactive web-response system, to receive spironolactone 25 mg once daily or matched placebo (trial cohort). The primary endpoint was development of confirmed microalbuminuria in all individuals with available data (observational cohort). Secondary endpoints included reduction in incidence of microalbuminuria with spironolactone (trial cohort, intention-to-treat population) and association between CKD273 risk score and measures of impaired renal function based on estimated glomerular filtration rate (eGFR; observational cohort). Adverse events (particularly gynaecomastia and hyperkalaemia) and serious adverse events were recorded for the intention-to-treat population (trial cohort). This study is registered with the EU Clinical Trials Register (EudraCT 20120-004523-4) and ClinicalTrials.gov (NCT02040441) and is completed.

FINDINGS

Between March 25, 2014, and Sept 30, 2018, we enrolled and followed-up 1775 participants (observational cohort), 1559 (88%) of 1775 participants had a low-risk urinary proteomic pattern and 216 (12%) had a high-risk pattern, of whom 209 were included in the trial cohort and assigned to spironolactone (n=102) or placebo (n=107). The overall median follow-up time was 2·51 years (IQR 2·0-3·0). Progression to microalbuminuria was seen in 61 (28%) of 216 high-risk participants and 139 (9%) of 1559 low-risk participants (hazard ratio [HR] 2·48, 95% CI 1·80-3·42; p<0·0001, after adjustment for baseline variables of age, sex, HbA_1c, systolic blood pressure, retinopathy, urine albumin-to-creatinine ratio [UACR], and eGFR). Development of impaired renal function (eGFR <60 mL/min per 1·73 m²) was seen in 48 (26%) of 184 high-risk participants and 119 (8%) of 1423 low-risk participants (HR 3·50; 95% CI 2·50-4·90, after adjustment for baseline variables). A 30% decrease in eGFR from baseline (post-hoc endpoint) was seen in 42 (19%) of 216 high-risk participants and 62 (4%) of 1559 low-risk participants (HR 5·15, 95% CI 3·41-7·76; p<0·0001, after adjustment for basline eGFR and UACR). In the intention-to-treat trial cohort, development of microalbuminuria was seen in 35 (33%) of 107 in the placebo group and 26 (25%) of 102 in the spironolactone group (HR 0·81, 95% CI 0·49-1·34; p=0·41). In the safety analysis (intention-to-treat trial cohort), events of plasma potassium concentrations of more than 5·5 mmol/L were seen in 13 (13%) of 102 participants in the spironolactone group and four (4%) of 107 participants in the placebo group, and gynaecomastia was seen in three (3%) participants in the spironolactone group and none in the placebo group. One patient died in the placebo group due to a cardiac event (considered possibly related to study drug) and one patient died in the spironolactone group due to cancer, deemed unrelated to study drug.

INTERPRETATION

In people with type 2 diabetes and normoalbuminuria, a high-risk score from the urinary proteomic classifier CKD273 was associated with an increased risk of progression to microalbuminuria over a median of 2·5 years, independent of clinical characteristics. However, spironolactone did not prevent progression to microalbuminuria in high-risk patients.

FUNDING

European Union Seventh Framework Programme.

A meta-analysis of serum Hcy in diagnosis of diabetic nephropathy

Objective This meta-analysis aims to investigate the diagnostic performance of serum homocysteine (Hcy) as a biomarker for diabetic nephropathy (DN).

Methods Clinical publications relevant to serum Hcy level and DN were systematic searched in the electronic databases of; Pubmed, Cochrane Library, Embase, Web of science, CNKI and CBM. The diagnostic data from each included original study was extracted and pooled by the effect size of diagnostic sensitivity, specificity, positive likely hood ratio (+LR), negative likely hood ratio (-LR), diagnostic odds ratio (DOR) and area under the symmetric ROC curve (AUC).

Results 18 publications relevant to serum Hcy and DN were included in the meta-analysis. The I2 test demonstrated significant statistical heterogeneity across the 18 studies for the effect size of diagnostic. The pooled diagnostic sensitivity, specificity, +LR, -L, DOR, AUC were 0.76 (95%CI: 0.74-0.78), 0.84 (95%CI:0.82-0.86), 5.05 (95%CI:3.52-7.24), 0.27 (95%CI:0.19-0.39), 21.68 (95% CI:11.15to 42.14) and 0.90 respectively in the random effect model.

Conclusion Based on the present publications, serum Hcy is a promising serological marker for DN diagnosis.