Urinary peptidomics and bioinformatics for the detection of diabetic kidney disease

Insights into the molecular underpinning of type 2 diabetes complications

Type 2 diabetes (T2D) complications pose a significant global health challenge. Omics technologies have been employed to investigate these complications and identify the biological pathways involved. In this review, we focus on four major T2D complications: diabetic kidney disease, diabetic retinopathy, diabetic neuropathy, and cardiovascular complications. We discuss advancements in omics research, summarizing findings from genetic, epigenomic, transcriptomic, proteomic, and metabolomic studies across different ancestries and disease-relevant tissues. We stress the importance of integrating multi-omics techniques to elucidate the biological mechanisms underlying T2D complications and advocate for ancestrally diverse studies. Ultimately, these insights will improve risk prediction for T2D complications and inform translation strategies.

Protein Biomarkers of Ultra-Processed Food Consumption and Risk of Coronary Heart Disease, Chronic Kidney Disease, and All-Cause Mortality

BACKGROUND

There is a need to understand the underlying biological mechanisms through which ultra-processed foods negatively affect health. Proteomics offers a valuable tool with which to examine different aspects of ultra-processed foods and their impact on health.

OBJECTIVES

The aim of this study was to identify protein biomarkers of usual ultra-processed food consumption and assess their relation to the incidence of coronary heart disease (CHD), chronic kidney disease (CKD), and all-cause mortality risk.

METHODS

A total of 9361 participants from the Atherosclerosis Risk in Communities visit 3 (1993-1995) were included. Dietary intake was assessed using a 66-item food-frequency questionnaire and the processing levels were categorized on the basis of the Nova classification. Plasma proteins were detected using an aptamer-based proteomic assay. We used multivariable linear regressions to examine the association between ultra-processed food and proteins, and Cox proportional hazard models to identify associations between ultra-processed food-related proteins and health outcomes. Models extensively controlled for sociodemographic characteristics, health behaviors, and clinical factors.

RESULTS

Eight proteins (6 positive, 2 negative) were identified as significantly associated with ultra-processed food consumption. Over a median follow-up of 22 y, there were 1276, 3084, and 5127 cases of CHD, CKD, and death, respectively. Three, 5, and 3 ultra-processed food-related proteins were associated with each outcome, respectively. One protein (β-glucuronidase) was significantly associated with a higher risk of all 3 outcomes, and 3 proteins (receptor-type tyrosine-protein phosphatase U, C-C motif chemokine 25, and twisted gastrulation protein homolog 1) were associated with a higher risk of 2 outcomes.

CONCLUSIONS

We identified a panel of protein biomarkers that were significantly associated with ultra-processed food consumption. These proteins may be considered potential biomarkers for ultra-processed food intake and may elucidate the biological processes through which ultra-processed foods impact health outcomes.

Advancements, Challenges, and clinical implications of integration of metabolomics technologies in diabetic nephropathy

BACKGROUND

Diabetic nephropathy (DN), a severe complication of diabetes, involves a range of renal abnormalities driven by metabolic derangements. Metabolomics, revealing dynamic metabolic shifts in diseases like DN and offering insights into personalized treatment strategies, emerges as a promising tool for improved diagnostics and therapies.

METHODS

We conducted an extensive literature review to examine how metabolomics contributes to the study of DN and the challenges associated with its implementation in clinical practice. We identified and assessed relevant studies that utilized metabolomics methods, including nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) to assess their efficacy in diagnosing DN.

RESULTS

Metabolomics unveils key pathways in DN progression, highlighting glucose metabolism, dyslipidemia, and mitochondrial dysfunction. Biomarkers like glycated albumin and free fatty acids offer insights into DN nuances, guiding potential treatments. Metabolomics detects small-molecule metabolites, revealing disease-specific patterns for personalized care.

CONCLUSION

Metabolomics offers valuable insights into the molecular mechanisms underlying DN progression and holds promise for personalized medicine approaches. Further research in this field is warranted to elucidate additional metabolic pathways and identify novel biomarkers for early detection and targeted therapeutic interventions in DN.

The Strategy for Peptidomic LC-MS/MS Data Analysis: The Case of Urinary Peptidome Study

The study of urinary peptidome is an important area of research, which concerns the characterization of endogenous peptides, as well as the identification of biomarkers for a wide range of socially significant diseases. First of all, this relates to renal and genitourinary pathologies and/or pathologies associated with proteinuria, such as kidney diseases, bladder, prostate and ovarian cancers, diabetic nephropathy, and pre-eclampsia. Unlike proteins, peptides do not require proteolytic hydrolysis, can be analyzed in their native form and can provide certain information about occurring (patho)physiological processes. Mass spectrometry (MS)-based approaches are the most unbiased and sensitive instruments with high multiplexing capacity and provided most of the current information about endogenous urine peptides. However, despite the large number of urine peptidomic studies, there are certain issues related to the insufficient comparability of their results due to the lack of consistent approaches to their interpretation. Also the development of a custom project-specific protein library for endogenous peptides search and identification is another important point that should be noted in the context of high-throughput peptidomic analysis. Here we propose the custom-specific urinary protein database and the grouping of endogenous urinary peptides with overlapping sequences as useful tools, which can facilitate the acquisition and analysis of LC-MS peptidomic data, as well as the comparison of results of different studies, which should facilitate their more efficient further application.

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.

Neurobiochemical, Peptidomic, and Bioinformatic Approaches to Characterize Tauopathy Peptidome Biomarker Candidates in Experimental Mouse Model of Traumatic Brain Injury

Traumatic brain injury (TBI) is a multidimensional damage, and currently, no FDA-approved medicine is available. Multiple pathways in the cell are triggered through a head injury (e.g., calpain and caspase activation), which truncate tau and generate variable fragment sizes (MW 400-45,000 K). In this study, we used an open-head TBI mouse model generated by controlled cortical impact (CCI) and collected ipsilateral (IC) and contralateral (CC) mice htau brain cortices at one (D1) three (D3), and seven (D7) days post-injury. We implemented immunological (antibody-based detection) and peptidomic approaches (nano-reversed-phase liquid chromatography/tandem mass spectrometry) to investigate proteolytic tau peptidome (low molecular weight (LMW) < 10 K)) and pathological phosphorylation sites (high-molecular-weight (HMW); > 10 K) derived from CCI-TBI animal models. Our immunoblotting analysis verified tau hyperphosphorylation, HMW, and HMW breakdown products (HMW-BDP) formation of tau (e.g., pSer₂₀₂, pThr₁₈₁, pThr₂₃₁, pSer₃₉₆, and pSer₄₀₄), following CCI-TBI. Peptidomic data revealed unique sequences of injury-dependent proteolytic peptides generated from human tau protein. Among the N-terminal tau peptides, EIPEGTTAEEAGIGDTPSLEDEAAGHVTQA (a.a. 96-125) and AQPHTEIPEGTTAEEAGIGDTPSLEDEAAGHVTQARM (a.a. 91-127). Examples of tau C-terminal peptides identified include NVSSTGSIDMVDSPQLATLADEVSASLAKQGL (a.a. 410-441) and QLATLADEVSASLAKQGL (a.a. 424-441). Our peptidomic bioinformatic tools showed the association of proteases, such as CAPN1, CAPN2, and CTSL; CASP1, MMP7, and MMP9; and ELANE, GZMA, and MEP1A, in CCI-TBI tau peptidome. In clinical trials for novel TBI treatments, it might be useful to monitor a subset of tau peptidome as targets for biomarker utility and use them for a "theranostic" approach.

Mechanisms Linking COPD to Type 1 and 2 Diabetes Mellitus: Is There a Relationship between Diabetes and COPD?

Chronic obstructive pulmonary disease (COPD) patients frequently suffer from multiple comorbidities, resulting in poor outcomes for these patients. Diabetes is observed at a higher frequency in COPD patients than in the general population. Both type 1 and 2 diabetes mellitus are associated with pulmonary complications, and similar therapeutic strategies are proposed to treat these conditions. Epidemiological studies and disease models have increased our knowledge of these clinical associations. Several recent genome-wide association studies have identified positive genetic correlations between lung function and obesity, possibly due to alterations in genes linked to cell proliferation; embryo, skeletal, and tissue development; and regulation of gene expression. These studies suggest that genetic predisposition, in addition to weight gain, can influence lung function. Cigarette smoke exposure can also influence the differential methylation of CpG sites in genes linked to diabetes and COPD, and smoke-related single nucleotide polymorphisms are associated with resting heart rate and coronary artery disease. Despite the vast literature on clinical disease association, little direct mechanistic evidence is currently available demonstrating that either disease influences the progression of the other, but common pharmacological approaches could slow the progression of these diseases. Here, we review the clinical and scientific literature to discuss whether mechanisms beyond preexisting conditions, lifestyle, and weight gain contribute to the development of COPD associated with diabetes. Specifically, we outline environmental and genetic confounders linked with these diseases.

Fluorescence Imaging Using Enzyme-Activatable Probes for Detecting Diabetic Kidney Disease and Glomerular Diseases

A clear identification of the etiology of glomerular disease is essential in patients with diabetes. Renal biopsy is the gold standard for assessing the underlying nephrotic pathology; however, it has the risk for potential complications. Here, we aimed to investigate the feasibility of urinary fluorescence imaging using an enzyme-activatable probe for differentiating diabetic kidney disease and the other glomerular diseases. Hydroxymethyl rhodamine green (HMRG)-based fluorescent probes targeting gamma-glutamyl transpeptidase (GGT) and dipeptidyl-peptidase (DPP) were used. Urinary fluorescence was compared between groups which were classified by their histopathological diagnoses (diabetic kidney disease, glomerulonephritis, and nephrosclerosis) as obtained by ultrasound-guided renal biopsy. Urinary fluorescence was significantly stronger in patients with diabetic kidney disease compared to those with glomerulonephritis/nephrosclerosis after DPP-HMRG, whereas it was stronger in patients with nephrosclerosis than in patients with glomerulonephritis after GGT-HMRG. Subgroup analyses of the fluorescence performed for patients with diabetes showed consistent results. Urinary fluorescence imaging using enzyme-activatable fluorescence probes thus represents a potential noninvasive assessment technique for kidney diseases in patients with diabetes.

Alpha-1 antitrypsin in autoimmune diseases: Roles and therapeutic prospects

Alpha-1 antitrypsin (A1AT) is a protease inhibitor in the serum. Its primary function is to inhibit the activity of a series of proteases, including proteinase 3, neutrophil elastase, metalloproteases, and cysteine-aspartate proteases. In addition, A1AT also has anti-inflammatory, anti-apoptotic, anti-oxidative stress, anti-viral, and anti-bacterial activities and plays essential roles in the regulation of tissue repair and lymphocyte differentiation and activation. The overactivation of the immune system characterizes the pathogenesis of autoimmune diseases. A1AT treatment shows beneficial effects on patients and animal models with autoimmune diseases such as rheumatoid arthritis and systemic lupus erythematosus. This review summarizes the functions and therapeutic prospects of A1AT in autoimmune diseases.

Application of peptide biomarkers in life analysis based on liquid chromatography-mass spectrometry technology

Biomedicine is developing rapidly in the 21st century. Among them, the qualitative and quantitative analysis of peptide biomarkers is of considerable importance for the diagnosis and therapy of diseases and the quality evaluation of drugs and food. The identification and quantitative analysis of peptides have been going on for decades. Traditionally, immunoassays or biological assays are generally used to quantify peptides in biological matrices. However, the selectivity and sensitivity of these methods cannot meet the requirements of the application. The separation and analysis technique of liquid chromatography-mass spectrometry (LC-MS) supplies a reliable alternative. In contrast to immunoassays, LC-MS methods are capable of providing the analytical prowess necessary to satisfy the demands of peptide biomarker research in the life sciences arena. This review article provides a historical account of the in-roads made by LC-MS technology for the detection of peptide biomarkers in the past 10 years, with the focus on the qualification/quantification developments and their applications.

Peptidomics analysis reveals changes in small urinary peptides in patients with interstitial cystitis/bladder pain syndrome

Interstitial cystitis/bladder pain syndrome (IC/BPS) is a chronic and debilitating pain disorder of the bladder and urinary tract with poorly understood etiology. A definitive diagnosis of IC/BPS can be challenging because many symptoms are shared with other urological disorders. An analysis of urine presents an attractive and non-invasive resource for monitoring and diagnosing IC/BPS. The antiproliferative factor (APF) peptide has been previously identified in the urine of IC/BPS patients and is a proposed biomarker for the disorder. Nevertheless, other small urinary peptides have remained uninvestigated in IC/BPS primarily because protein biomarker discovery efforts employ protocols that remove small endogenous peptides. The purpose of this study is to investigate the profile of endogenous peptides in IC/BPS patient urine, with the goal of identifying putative peptide biomarkers. Here, a non-targeted peptidomics analysis of urine samples collected from IC/BPS patients were compared to urine samples from asymptomatic controls. Our results show a general increase in the abundance of urinary peptides in IC/BPS patients, which is consistent with an increase in inflammation and protease activity characteristic of this disorder. In total, 71 peptides generated from 39 different proteins were found to be significantly altered in IC/BPS. Five urinary peptides with high variable importance in projection (VIP) coefficients were found to reliably differentiate IC/BPS from healthy controls by receiver operating characteristic (ROC) analysis. In parallel, we also developed a targeted multiple reaction monitoring method to quantify the relative abundance of the APF peptide from patient urine samples. Although the APF peptide was found in moderately higher abundance in IC/BPS relative to control urine, our results show that the APF peptide was inconsistently present in urine, suggesting that its utility as a sole biomarker of IC/BPS may be limited. Overall, our results revealed new insights into the profile of urinary peptides in IC/BPS that will aid in future biomarker discovery and validation efforts.

Urinary peptidomics reveals proteases involved in idiopathic membranous nephropathy

BACKGROUND

Idiopathic membranous nephropathy (IMN) is a cause of nephrotic syndrome that is increasing in incidence but has unclear pathogenesis. Urinary peptidomics is a promising technology for elucidating molecular mechanisms underlying diseases. Dysregulation of the proteolytic system is implicated in various diseases. Here, we aimed to conduct urinary peptidomics to identify IMN-related proteases.

RESULTS

Peptide fingerprints indicated differences in naturally produced urinary peptide components among 20 healthy individuals, 22 patients with IMN, and 15 patients with other kidney diseases. In total, 1,080 peptide-matched proteins were identified, 279 proteins differentially expressed in the urine of IMN patients were screened, and 32 proteases were predicted; 55 of the matched proteins were also differentially expressed in the kidney tissues of IMN patients, and these were mainly involved in the regulation of proteasome-, lysosome-, and actin cytoskeleton-related signaling pathways. The 32 predicted proteases showed abnormal expression in the glomeruli of IMN patients based on Gene Expression Omnibus databases. Western blot revealed abnormal expression of calpain, matrix metalloproteinase 14, and cathepsin S in kidney tissues of patients with IMN.

CONCLUSIONS

This work shown the calpain/matrix metalloproteinase/cathepsin axis might be dysregulated in IMN. Our study is the first to systematically explore the role of proteases in IMN by urinary peptidomics, which are expected to facilitate discovery of better biomarkers for IMN.

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.

Urine peptidome analysis in cardiorenal syndrome reflects molecular processes

The cardiorenal syndrome (CRS) is defined as the confluence of heart-kidney dysfunction. This study investigates the molecular differences at the level of the urinary peptidome between CRS patients and controls and their association to disease pathophysiology. The urinary peptidome of CRS patients (n = 353) was matched for age and sex with controls (n = 356) at a 1:1 ratio. Changes in the CRS peptidome versus controls were identified after applying the Mann-Whitney test, followed by correction for multiple testing. Proteasix tool was applied to investigate predicted proteases involved in CRS-associated peptide generation. Overall, 559 differentially excreted urinary peptides were associated with CRS patients. Of these, 193 peptides were specifically found in CRS when comparing with heart failure and chronic kidney disease urinary peptide profiles. Proteasix predicted 18 proteases involved in > 1% of proteolytic cleavage events including multiple forms of MMPs, proprotein convertases, cathepsins and kallikrein 4. Forty-four percent of the cleavage events were produced by 3 proteases including MMP13, MMP9 and MMP2. Pathway enrichment analysis supported that ECM-related pathways, fibrosis and inflammation were represented. Collectively, our study describes the changes in urinary peptides of CRS patients and potential proteases involved in their generation, laying the basis for further validation.

Peptidomics: A Review of Clinical Applications and Methodologies

Improvements in both liquid chromatography (LC) and mass spectrometry (MS) instrumentation have greatly enhanced proteomic and small molecule metabolomic analysis in recent years. Less focus has been on the improved capability to detect and quantify small bioactive peptides, even though the exact sequences of the peptide species produced can have important biological consequences. Endogenous bioactive peptide hormones, for example, are generated by the targeted and regulated cleavage of peptides from their prohormone sequence. This process may include organ specific variants, as proglucagon is converted to glucagon in the pancreas but glucagon-like peptide-1 (GLP-1) in the small intestine, with glucagon raising, whereas GLP-1, as an incretin, lowering blood glucose. Therefore, peptidomics workflows must preserve the structure of the processed peptide products to prevent the misidentification of ambiguous peptide species. The poor in vivo and in vitro stability of peptides in biological matrices is a major factor that needs to be considered when developing methods to study them. The bioinformatic analysis of peptidomics data sets requires the inclusion of specific post-translational modifications, which are critical for the function of many bioactive peptides. This review aims to discuss and contrast the various extraction, analytical, and bioinformatics approaches used for human peptidomics studies in a multitude of matrices.

Urinary proteomics for kidney dysfunction: insights and trends

Introduction: Kidney dysfunction poses a high burden on patients and health care systems. Early detection and accurate prediction of kidney disease progression remains a major challenge. Compared to existing clinical parameters, urinary proteomics has the potential to reveal molecular alterations within the kidney that may alter its function before the onset of clinical symptoms. Thus, urinary proteomics has greater prognostic potential for assessment of kidney dysfunction progression.Areas covered: Advances in urinary proteomics for major causes of kidney dysfunction are discussed. The application of urinary extracellular vesicles for studying kidney dysfunction are discussed. Technological advances in urinary proteomics are discussed. The literature was identified using a database search for titles containing 'proteom*' and 'urin*' and published within the past 5 years. Retrieved literature was manually filtered to retain kidney dysfunctions-related studies.Expert opinion: Despite major advances, diagnosis by urinary proteomics has not been fully applied in any clinical settings. This could be attributed to the complex nature of kidney diseases, in addition to the constraints on study power and feasibility of incorporating mass spectrometry techniques in daily routine analysis. Nevertheless, we are confident that advances in urinary proteomics will soon provide superior insights into kidney disease beyond existing clinical parameters.

Therapeutic Potential of Alpha-1 Antitrypsin in Type 1 and Type 2 Diabetes Mellitus

Alpha-1 antitrypsin (AAT) has established anti-inflammatory and immunomodulatory effects in chronic obstructive pulmonary disease but there is increasing evidence of its role in other inflammatory and immune-mediated conditions, like diabetes mellitus (DM). AAT activity is altered in both developing and established type 1 diabetes mellitus (T1DM) as well in established type 2 DM (T2DM). Augmentation therapy with AAT appears to favorably impact T1DM development in mice models and to affect β-cell function and inflammation in humans with T1DM. The role of AAT in T2DM is less clear, but AAT activity appears to be reduced in T2DM. This article reviews these associations and emerging therapeutic strategies using AAT to treat DM.

Risk Factors for Albuminuria in Normotensive Older Adults with Type 2 Diabetes Mellitus and Normal Renal Function: A Cross-Sectional Study

INTRODUCTION

Diabetes mellitus (DM) is prevalent in developed and developing countries, including China. However, few studies have examined the potential risk factors for albuminuria in normotensive older adults with type 2 DM and normal renal function.

METHODS

We recruited normotensive older adults (≥ 65 years) with type 2 DM and normal renal function from the First Affiliated Hospital of Soochow University from January to December 2019. We stratified participants according to their urine albumin to creatinine ratio (ACR) into the following groups: normal ACR (ACR1), microalbuminuria (ACR2), and macroalbuminuria (ACR3). Demographic characteristics, anthropometric parameters, and metabolic profiles were recorded. Creatinine clearance (Ccr) and homeostasis model assessment-insulin resistance (HOMA-IR) were calculated. Logistic regression was used to examine risk factors for albuminuria.

RESULTS

A total of 250 older adults were enrolled during the study period, including 124, 82, and 44 with normal albuminuria, microalbuminuria, and macroalbuminuria, respectively. We found that an extended duration of DM (odds ratio [OR] 1.085, 95% confidence interval [CI] 1.012-1.164, P = 0.022), elevated systolic blood pressure (OR 1.049, 95%CI 1.018-1.081, P < 0.01), elevated glycated hemoglobin (OR 1.734, 95% CI 1.332-2.258, P < 0.01), low insulin (OR 0.871, 95% CI 0.804-0.944, P < 0.01), and low C-peptide (OR 0.365, 95% CI 0.239-0.588, P < 0.01) were independent risk factors for albuminuria.

CONCLUSION

Elevated blood pressure, low insulin, low C-peptide, and poor glycemic control were significant risk factors for albuminuria. These parameters may serve as early indicators for intervention.

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.

Urinary MMP-9/UCr association with albumin concentration and albumin-creatinine-ratio in Mexican patients with type 2 diabetes mellitus

BACKGROUND

Chronic kidney disease is one of the most common complications of type 2 diabetes mellitus (T2DM), causing an increased risk of cardiovascular morbidity and mortality. Matrix metalloproteinase (MMP) activity has been proposed as useful biomarker for diabetic renal and vascular complications.

METHODS

A cross-sectional study was conducted among T2DM patients who attended a public secondary hospital in Mexico. We performed clinical, biochemical, and microbiological assessments, as well chronic kidney disease diagnosis according to the KDIGO guideline. Urinary MMP-9 was quantified by ELISA and adjusted using urinary creatinine (UCr).

RESULTS

A total of 111 patients were included. Most participants were women (66%). Mean age was 61 ± 10 years and median T2DM duration was estimated at 11 years. Through multivariate analysis, MMP-9/UCr was found to be associated with albumin concentration and albumin to creatinine ratio.

DISCUSSION

Validation of non-invasive biomarkers of chronic kidney disease among T2DM patients is necessary. Here, we demonstrate MMP-9/UCr as a potential biomarker of albumin concentration and albumin to creatinine ratio in Mexican patients with T2DM.