Peptiduria: a potential early predictor of diabetic kidney disease

Spatiotemporal organisation of protein processing in the kidney

The kidney regulates plasma protein levels by eliminating them from the circulation. Proteins filtered by glomeruli are endocytosed and degraded in the proximal tubule and defects in this process result in tubular proteinuria, an important clinical biomarker. However, the spatiotemporal organization of renal protein metabolism in vivo was previously unclear. Here, using functional probes and intravital microscopy, we track the fate of filtered proteins in real time in living mice, and map specialized processing to tubular structures with singular value decomposition analysis and three-dimensional electron microscopy. We reveal that degradation of proteins requires sequential, coordinated activity of distinct tubular sub-segments, each adapted to specific tasks. Moreover, we leverage this approach to pinpoint the nature of endo-lysosomal disorders in disease models, and show that compensatory uptake in later regions of the proximal tubule limits urinary protein loss. This means that measurement of proteinuria likely underestimates severity of endocytotic defects in patients.

Polesel et al. visualize plasma protein filtration, uptake and metabolism in the kidneys of living mice in real-time. They reveal coordinated activity of different specialized tubular segments, with major compensatory adaptations occurring in disease states.

Serum Arylsulfatase and Acid Phosphatase Activity in Patients with Metabolic Syndrome as a Result of Oxidative Damage to Lysosomes

BACKGROUND

Metabolic and clinical disorders forming the complex of interrelated abnormalities is known as metabolic syndrome (METs).

OBJECTIVE

Our goal was to assess the dependence of serum arylsulfatase (AS) and acid phosphatase (ACP) activities on anthropometric and biochemical parameters in patients with METs.

METHODS

In 142 patients with METs (IDF criteria), consisting of different components in different sequences (hypertension, diabetes, lipid disorders), and in 65 healthy participants, basic biochemical parameters were determined in laboratory tests. The activity of serum hydrolases was determined using Bessey's (ACP) and Roy's (AS) methods.

RESULTS

The AS activity is correlated with waist-to-hip ratio (WHR) (more strongly in women and in most advanced METs), BMI (in men), and triglycerides (TG) (in women, participants with I degree obesity, and those with three METs components). The ACP activity correlated with the WHR of patients with II degree obesity, TG in those with III degree of obesity, and total cholesterol (TC) in those with four METs components.

CONCLUSION

Increased AS activity in patients with METs compared to lower AS activity in the control group may be due to decreased lysosomal function and related to the amount of adipose tissue. Low activity of ACP in the blood serum of patients with METs compared to high activity of ACP in the control group may indicate exhaustion of the lysosomal apparatus and loss of hydrolytic activity. The increase in TG and TC in groups with an increasing number of METs-defining components may be due to the abnormal lysosomal degradation of these compounds.

Urinary Cyclophilin A and serum Cystatin C as biomarkers for diabetic nephropathy in children with type 1 diabetes

BACKGROUND

Currently, microalbuminuria is the gold standard for detection and prediction of diabetic nephropathy (DN). However, microalbuminuria appears once significant kidney damage has actually occurred.

OBJECTIVES

We investigated the diagnostic role of urinary Cyclophilin-A (uCypA), uCypA/creatinine ratio (uCypA/Cr) and serum Cystatin-C (sCysC) as biomarkers for early detection of DN in children with type 1 diabetes mellitus (T1DM) of short duration (2-5 years) before microalbuminuria emerges.

METHODS

uCypA, uCypA/Cr, and sCysC levels were assessed in three age- and sex-matched groups; microalbuminuric diabetic group (n = 31), normoalbuminuric diabetic group (n = 29), and control group (n = 30). Glomerular filtration rate was estimated (eGFR) based on both serum creatinine (eGFR-Cr) and sCysC (eGFR-CysC).

RESULTS

Significantly higher sCysC and lower eGFR-CysC were detected in both diabetic groups compared to controls and in microalbuminuric compared to normoalbuminuric group. No detected significant difference in eGFR-Cr values across the studied groups. Both uCypA and uCypA/Cr were significantly elevated in microalbuminuric compared to both normoalbuminuric and control groups with no difference between normoalbuminuric and control groups. Prediction of microalbuminuria was conducted using sCysC with area under curve up to 0.980. Combined use of sCysC and uCypA had better diagnostic value than uCypA alone.

CONCLUSION

sCysC is a promising early biomarker for DN in childhood T1DM before albuminuria detection. eGFR-CysC is superior to eGFR-Cr in evaluating renal status in childhood T1DM. uCypA and uCypA/Cr were useful tools in predicting microalbuminuria, although not regarded as diagnostic biomarkers for early-stage DN in T1DM children by the current study.

Differential Urinary Proteome Analysis for Predicting Prognosis in Type 2 Diabetes Patients with and without Renal Dysfunction

Renal dysfunction, a major complication of type 2 diabetes, can be predicted from estimated glomerular filtration rate (eGFR) and protein markers such as albumin concentration. Urinary protein biomarkers may be used to monitor or predict patient status. Urine samples were selected from patients enrolled in the retrospective diabetic kidney disease (DKD) study, including 35 with good and 19 with poor prognosis. After removal of albumin and immunoglobulin, the remaining proteins were reduced, alkylated, digested, and analyzed qualitatively and quantitatively with a nano LC-MS platform. Each protein was identified, and its concentration normalized to that of creatinine. A prognostic model of DKD was formulated based on the adjusted quantities of each protein in the two groups. Of 1296 proteins identified in the 54 urine samples, 66 were differentially abundant in the two groups (area under the curve (AUC): p-value < 0.05), but none showed significantly better performance than albumin. To improve the predictive power by multivariate analysis, five proteins (ACP2, CTSA, GM2A, MUC1, and SPARCL1) were selected as significant by an AUC-based random forest method. The application of two classifiers—support vector machine and random forest—showed that the multivariate model performed better than univariate analysis of mucin-1 (AUC: 0.935 vs. 0.791) and albumin (AUC: 1.0 vs. 0.722). The urinary proteome can reflect kidney function directly and can predict the prognosis of patients with chronic kidney dysfunction. Classification based on five urinary proteins may better predict the prognosis of DKD patients than urinary albumin concentration or eGFR.

Flavonoids interference in common protein assays: Effect of position and degree of hydroxyl substitution

Flavonoids interfere with colorimetric protein assays in a concentration- and structure-dependent manner. Degree (≥3) and position (C₃) of -OH substitution was associated with intensified interference (p < 0.05). Significant overestimation of protein (~3-5 folds) could occur at higher flavonoid concentrations (>5 μM) and is particularly evident at lower protein concentrations (25-250 μg/ml). Since, healthy human urinary protein (<200 μg/ml) and flavonoids urinary excretion (0.5-2 μg/ml) levels fall in this range, overestimation of protein concentration with flavonoids consumption in diet, including natural supplements, remains relevant issue for diagnostic and research labs. Protein precipitation by acetone to remove interfering flavonoid successfully resolves the problem.

The role of serum and urinary biomarkers in the diagnosis of early diabetic nephropathy in patients with type 2 diabetes

Background

Previous studies have shown that a variety of biomarkers are closely related to the occurrence and development of early-stage diabetic nephropathy (DN) in patients. The aim of this study was to evaluate the role of multiple sera and urinary biomarkers in the diagnosis of early-stage DN in patients with type 2 diabetes.

Methods

We enrolled 287 patients with type 2 diabetes, who were classified into normoalbuminuria (n = 144), microalbuminuria (n = 94), or macroalbuminuria (n = 49) groups based on their urine albumin to creatinine ratios (UACR), along with 42 healthy controls. We assessed 13 biomarkers, including transferrin (Tf), immunoglobulin G (IgG), podocalyxin, neutrophil gelatinase-associated lipocalin (NGAL), N-acetyl-beta-glucosaminidase, α-1-microglobulin, 8-hydroxy-deoxyguanosine, tumor necrosis factor-alpha (TNF-α), and interleukin-18 in urine samples, along with cystatin C, total bilirubin, and uric acid in sera samples, to evaluate their diagnostic roles. From the measurements, the blood neutrophil to lymphocyte ratio was also calculated.

Results

Urinary Tf, IgG, NGAL, and TNF-α were significantly related to the UACR. We calculated the area under the receiver operating characteristic curves (area under the curve) and found that urinary IgG (0.894), NGAL (0.875), Tf (0.861), TNF-α (0.763), and the combination of urinary Tf + IgG + TNF-α + NGAL (0.922) showed good diagnostic value for early-stage DN.

Conclusions

Urinary Tf, IgG, NGAL, TNF-α, and the combination of all four biomarkers demonstrated excellent diagnostic value for early-stage DN in patients with type 2 diabetes.