Extracellular vesicles, such as microvesicles (diameter of 100–1000 nm) and exosomes (diameter of 30–100 nm), are membrane-enclosed particles released by most cells under normal and pathologic conditions (1–5). Microvesicles are shed directly from the plasma membrane, whereas exosomes are formed by the fusion of intracellular multivesicular bodies (also known as late endosomes) with the plasma membrane, leading to the release of their vesicular contents into the extracellular space. These vesicles can mobilize a large number of biologic factors, including receptors, other proteins, nucleic acids, and lipids, thus shuttling information to other cells (6). The transfer of RNA and miRNA can reprogram recipient cells and modify their phenotype (7).
The hypothesis that extracellular vesicles are present in human urine (8) was confirmed by the proteomic identification of membrane proteins in a pellet isolated by the ultracentrifugation of urine samples (9). Such urinary extracellular vesicles contain cell-specific marker proteins from every segment of the nephron (9,10), and they offer a source of potentially valuable urinary biomarkers (10). The intrinsic characteristics of extracellular vesicles also suggest that they may play an important role in kidney development and kidney disease. Accordingly, extracellular vesicles seem to be involved in the mechanism of cystogenesis in autosomal polycystic kidney disease, a common hereditary kidney disorder with a prevalence of 0.1%–0.25%. Autosomal polycystic kidney disease gives rise to predominantly kidney symptoms, including cysts that progressively disrupt the kidney parenchyma, leading to interstitial fibrosis, cellular infiltration, and the loss of functional nephrons.
The proteomic analysis of urinary exosome-like vesicles (particularly those containing polycystin) revealed approximately 500 autosomal dominant polycystic kidney disease–associated proteins, many with signaling functions (11). Furthermore, the quantitative proteomic analysis of urinary extracellular vesicles from patients affected by a complete spectrum of chronic kidney functional damage highlighted 30 proteins strongly associated with the autosomal dominant polycystic kidney disease phenotype, including periplakin, envoplakin, villin-1, and complement C3 (12).
In contrast to the wealth of information available for autosomal dominant polycystic kidney disease, little is known about the role of extracellular vesicles in the onset of medullary sponge kidney, a sporadic cystic kidney malformation that involves nephrocalcinosis and recurrent kidney stones (13). The detailed analysis of extracellular vesicles could provide insight into the pathogenesis of this rare disease. Despite sporadic genetic associations (14,15) and the dysregulation of a few biologic factors (16–18), the systemic and kidney biologic/cellular network underlying this disease is poorly characterized, and its relationship with other cystic diseases is unclear.
To address this knowledge gap, we carried out a comprehensive comparative proteomic analysis of urinary microvesicles and exosomes to identify differences between medullary sponge kidney and autosomal dominant polycystic kidney disease in terms of the mechanism of cystogenesis and identify putative diagnostic biomarkers that distinguish these diseases. In fact, at the moment, no diagnostic biomarkers are available for both diseases. Although some urinary biomarkers for autosomal dominant polycystic kidney disease (NGAL, M-CSF, and MCP-1) (19) have been proposed, none of them have been used in clinical practice (19). Additionally, most of them are only effective in the advanced stage of the disease. Identification of both diseases at early stages could help clinicians start prevention, diet adjustment, and for selected patients, pharmacologic treatment. Finally, they could potentiate diagnostic accuracy for medullary sponge kidney (this disease is often undiagnosed and confused with other cause of nephrocalcinosis or papillary ductal plugging), minimize patients’ radiation and/or nephrotoxic contrast media exposure from medical imaging (e.g., intravenous urography and CT urography), and reduce underdiagnosis of noncontrast CT scans.
Materials and Methods
The study included 15 adult patients with autosomal dominant polycystic kidney disease and 15 adult patients with medullary sponge kidney matched for age, sex, and geographical origin as well as a cohort of 17 healthy donors matched for age and sex (Table 1, Supplemental Figure 1). The patients were followed up by the Renal Unit at the Department of Medicine, University Hospital of Verona (Verona, Italy), and they were enrolled after providing informed consent. Medullary sponge kidney diagnosis was performed as previously reported (15). The diagnosis of autosomal dominant polycystic kidney disease was dependent on the revised Ravine criteria (20). The study was carried out in accordance with the Declaration of Helsinki and approved by the institutional ethical board of the University Hospital of Verona (Verona, Italy; code 1312CESC) and the Independent Ethics Committee (Comitato Etico Regione Liguria) on October 14, 2014 (study number 408REG2014).
Table 1. -
Baseline characteristics of the study participants
||Medullary Sponge Kidney
||Autosomal Dominant Polycystic Kidney Disease
|eGFR, ml/min per 1.73 m2
|Plasma calcium, mg/dl
|Plasma phosphate, mg/dl
|Plasma sodium, mmol/L
|Plasma potassium, mmol/L
|Proteinuria, g/24 h
|Urine volume, ml/d
|Systolic BP, mm Hg
|Diastolic BP, mm Hg
Values are expressed as mean±SD. P values were determined by ANOVA except for sex, which was determined by Fisher exact test.
aIncluded only in the flow cytometry analysis.
Isolation of Microvesicles and Exosomes
Second morning urine samples were obtained from patients and healthy donors. Extracellular vesicles were isolated by centrifugation. Briefly, aliquots of 16 ml were centrifuged at 16,000×g for 30 minutes at 16°C to remove cells, debris, and organelles, such as mitochondria. To obtain the microvesicle fraction, the supernatant was centrifuged at 22,000×g for 120 minutes at 16°C (21). The microvesicle pellet was rinsed in PBS and centrifuged again at 22,000×g; this rinse/centrifugation cycle was carried out five times in total to obtain a clean microvesicle fraction. The supernatant was then centrifuged at 100,000×g for 120 minutes at 16°C to pellet the exosomes. The pellet was resuspended in 1 ml 0.25 M sucrose, loaded on a 1-ml 30% sucrose cushion, and centrifuged at 100,000×g for 120 minutes at 16°C. The pellet was rinsed in PBS and centrifuged again at 100,000×g for 10 minutes at 4°C, and this rinse/centrifugation cycle was carried out five times in total to obtain a clean exosome fraction. For each assay, we have performed the same purification procedure. Each pellet fraction was stored at −80°C until use. The size and purity of microvesicles and exosomes isolated by ultracentrifugation were confirmed by dynamic light scattering, whereas the antigen profile of exosomes and microvesicles was performed by Western blot as described in Supplemental Material.
The samples were processed by the in-StageTip method with two poly(styrene divinylbenzene) reverse phase sulfonate disks (22). Each pellet was solubilized in 25 μl 2% sodium deoxycholate, 10 mM Tris(2-carboxyethyl)phosphine, 40 mM chloroacetamide, and 100 mM Tris (pH 8.5). Microvesicles or exosomes were lysed, reduced, and alkylated in a single step, and then, they were loaded into the StageTip. The lysates were diluted with 25 mM Tris (pH 8.5) containing 1 μg of trypsin. The samples were acidified with 100 μl 1% (vol/vol) trifluoroacetic acid and washed three times with 0.2% (vol/vol) trifluoroacetic acid. The proteins were eluted in 60 μl 5% (vol/vol) ammonium hydroxide containing 80% (vol/vol) acetonitrile. Detailed descriptions of mass spectrometry instrumentation, data analysis, and biologic validation with homemade ELISA are reported in Supplemental Material.
After normalization using the Normalyzer R-package with the LOESS-G method (23), mass spectrometry data were analyzed by unsupervised hierarchical clustering using multidimensional scaling with k means and Spearman correlation to identify outliers and the dissimilarity between samples. The normalized expression profiles of the proteins were then used to construct the coexpression network using the weighted gene coexpression network analysis package in R (24). Additionally, to identify the hub proteins of modules that maximize the discrimination between the selected clinical traits, we applied a nonparametric Mann–Whitney U test, machine learning methods (such as nonlinear support vector machine learning), and partial least squares discriminant analysis. A complete and detailed description of the data analysis has been reported in Supplemental Material.
Characterization of Exosomes and Microvesicles
The size and purity of microvesicles and exosomes isolated by ultracentrifugation were confirmed by dynamic light scattering, revealing a Gaussian distribution profile with peak means at 1000±65 or 90±5 nm, respectively, the typical sizes for microvesicles or exosomes, respectively (Supplemental Figure 2, A and B). There was no difference in size between the microvesicles and exosomes isolated from patients with medullary sponge kidney and patients with autosomal dominant polycystic kidney disease. Western blot analysis revealed that the exosomes were positive for CD63 and CD81 but not CD45, whereas the microvesicles showed the opposite antigen profile (Supplemental Figure 2C).
Protein Composition of Exosomes and Microvesicles
The protein composition of exosomes and microvesicles from the urine of patients with medullary sponge kidney and patients with autosomal dominant polycystic kidney disease was determined by mass spectrometry. We identified 2950 proteins in total, 1579 (54%) of which were present in all four sample types. Among the medullary sponge kidney samples, only 178 (6%) and 88 (3%) proteins were exclusively found in the exosomes and microvesicles, respectively. Similarly, among the autosomal dominant polycystic kidney disease samples, only 183 (6%) and 98 (3%) proteins were exclusively found in the exosomes and microvesicles, respectively (Figure 1A); >60% of all of the extracellular vesicle proteins that we identified were present in exosomes, and >80% were present in microvesicles.
Furthermore, about 40% of the proteins found in extracellular vesicles were associated with one or both kidney diseases: 95% were found in the medullary sponge kidney samples, and 100% were found in the autosomal dominant polycystic kidney disease samples (Figure 1, B and C). The cellular origins of the proteins in the exosomes were very similar in the medullary sponge kidney and autosomal dominant polycystic kidney disease samples, with 18% of proteins originating from membranes, 32% originating from the cytoplasm, 10% originating from the nucleus, and 39% originating from other organelles (Supplemental Figure 3). Similar results were observed for the microvesicle proteins, with 34% originating from membranes, 26% originating from the cytoplasm, 8% originating from the nucleus, and 32% originating from other organelles.
The significant overlap among the groups of proteins found in each sample was confirmed by constructing a two-dimensional scatter plot of the multidimensional scaling analysis (Supplemental Figure 4). No samples were excluded during the quality check performed by nonhierarchical clustering (Supplemental Figure 5). We used weighted gene coexpression network analysis to identify proteins associated with each type of extracellular vesicle and disease, revealing a total of ten modules comprising proteins with similar expression profiles. To distinguish between modules, we chose an arbitrary color for each module (Figure 2A). The number of proteins included in each module ranged from 44 (gray) to 930 (turquoise). The gray, brown, pink, and blue modules showed closer relationships with the medullary sponge kidney, autosomal dominant polycystic kidney disease, microvesicle, and exosome groups, respectively (Figure 2B).
Next, we applied the Mann–Whitney U test to identify the proteins that best distinguish the type of disease in the microvesicles or exosomes (Figure 3, A and B) and the type of extracellular vesicle in the medullary sponge kidney or autosomal dominant polycystic kidney disease samples (Figure 3, C and D). This revealed a total of 255 discriminatory proteins, 50 that distinguished between medullary sponge kidney and autosomal dominant polycystic kidney disease microvesicles, 90 that distinguished between medullary sponge kidney and autosomal dominant polycystic kidney disease exosomes, 150 that distinguished between exosomes and microvesicles in the autosomal dominant polycystic kidney disease samples, and 62 that distinguished between exosomes and microvesicles in the medullary sponge kidney samples (Supplemental Table 1, Supplemental Figures 6 and 7). Support vector machine learning and partial least squares discriminant analysis were then used to highlight the proteins that maximize the discrimination between different sample types, revealing a core panel of 34 proteins that allowed us to distinguish the four conditions with an accuracy of 100% (Figure 4, A and B). After Z-score analysis, we built a heat map of the corresponding expression profiles (Figure 4A) and prepared a graphical representation for their cluster separation (Figure 4B).
The diversity of expression profiles among the proteins in this core panel indicated their association with different functions, and therefore, GO analysis of functional annotations was used to build a scatter plot of enriched gene signatures on the y axis and –log10P values on the x axis (Supplemental Figure 8). The size of scatters is proportional to the number of proteins associated with each biologic process. After Z-score analysis, we built a heat map showing the expression profiles of the enriched biochemical pathways (Figure 4C). Interestingly, this revealed that proteins involved in cell migration/adhesion were over-represented in the microvesicles of patients with polycystic kidney disease, whereas those involved in the regulation of the epithelial cell differentiation were over-represented in the exosomes of patients with autosomal dominant polycystic kidney disease.
ELISA for CD133 in Exosomes-Validated Proteomics
A homemade ELISA for urinary CD133 was performed in exosomes from all patients and healthy controls to validate proteomic data. We found that CD133 was highly expressed in patients with autosomal dominant polycystic kidney disease compared with patients with medullary sponge kidney and healthy controls (Figure 4D). The medians (interquartile ranges [IQRs]) were 1.04 (IQR, 0.54–1.68), 0.4 (IQR, 0.22–0.76), and 0.28 (IQR, 0.16–0.34) for patients with autosomal dominant polycystic kidney disease, patients with medullary sponge kidney, and healthy controls, respectively, and P values were P<0.001 for Kruskal–Wallis test analysis. Also, ROC analysis revealed that the expression of CD133 in urinary exosomes can discriminate patients with autosomal dominant polycystic kidney disease from healthy subjects and patients with medullary sponge kidney. The areas under the curve, the 95% confidence intervals (95% CIs), and P values of ROC analysis were 0.98 (95% CI, 0.94 to 1) and P<0.001 (patients with autosomal dominant polycystic kidney disease versus healthy controls), 0.82 (95% CI, 0.67 to 0.97) and P=0.003 (patients with autosomal dominant polycystic kidney disease versus patients with medullary sponge kidney), and 0.70 (95% CI, 0.51 to 0.89) and P=0.05 (patients with medullary sponge kidney versus healthy controls) (Figure 4E). The cutoff, sensitivity, specificity, and likelihood ratio are reported in Supplemental Table 2.
Microvesicles and exosomes are known to be involved in the pathogenesis of several chronic kidney disorders, but few studies have focused on their role in kidney cystic diseases (9,11,25,26), and their potential involvement in medullary sponge kidney disease has not been addressed. In this study, we used mass spectrometry to identify the protein content of microvesicles and exosomes to gain insight into medullary sponge kidney–related cystogenesis and its similarities and differences compared with autosomal dominant polycystic kidney disease. By applying a layered statistical analysis approach, we found 34 core proteins that distinguished the microvesicles and exosomes of medullary sponge kidney and autosomal dominant polycystic kidney disease. Interestingly, most of these proteins were assigned to a small number of specific functions, including the regulation of epithelial cell differentiation, kidney development, cell migration, cell adhesion, carbohydrate metabolism, and extracellular matrix organization.
One of the core proteins was prominin 1 (CD133), a pentaspan transmembrane glycoprotein that localizes to membrane protrusions and is often expressed on adult stem/progenitor kidney cells, where it is thought to maintain stem cell properties by suppressing differentiation. The high-level expression of prominin 1 is associated with several types of cancer (27–29). This protein was more abundant in the exosomes of patients with autosomal dominant polycystic kidney disease, reflecting the attempted tissue repair in response to the aberrant rate of proliferation and apoptosis, which would require kidney progenitor cells. The upregulation of other proteins involved in cell migration/adhesion, such as Cadherin 4, or the epithelial cell differentiation, such as CREG1, seems to confirm this hypothesis. Accordingly, the kidney progenitor cells in human kidney papillary loops of Henle can differentiate into both neural-like and epithelial-like lineages as well as producing tubules (30). An abundant population of CD133+ cells was also shown to be present in the cystic wall and kidney tubules of patients with autosomal dominant polycystic kidney disease (31). The role of these cells is not yet clear, but it would be interesting to evaluate more patients with autosomal dominant polycystic kidney disease at different disease stages (from asymptomatic to the late disease stage) and clarify whether CD133+ (and CD24+) cells are associated with a better or worse prognosis.
We also found that the cellular repressor of E1A stimulated genes 1 (CREG1), a factor that interacts with the IGF2 receptor to regulate cell growth, was more abundant in autosomal dominant polycystic kidney disease. This protein may facilitate stem cell differentiation and activity, which was recently shown for the differentiation of embryonic stem cells in cardiomyocytes, improving the integration of stem cell–derived cardiomyocytes into recipient hearts (32). The exosomes sourced from our patients with autosomal dominant polycystic kidney disease not only contained higher levels of the proliferation regulator CREG1 but also, proteins required for matrix remodeling (ITIH5) and the regulation of salt secretion (GUCA2B or MAL). All of these mechanisms are important for cyst formation and enlargement, which in autosomal dominant polycystic kidney disease, involve tubular cell proliferation, abnormalities in the extracellular matrix, and transepithelial fluid secretion directed toward the cyst lumen. Because cysts are anatomically separated from their source tubule (33), the intracystic fluid does not originate from the glomerular filtrate, but rather, it originates from transepithelial fluid secretion (34).
Autosomal dominant polycystic kidney disease is also characterized by the disruption of the planar cell polarity pathway, which is required for oriented cell division and convergent extension to establish and maintain the structure of kidney tubules (35). We found that the FAT Atypical Cadherin 4 protein was more abundant in the exosomes of patients with autosomal dominant polycystic kidney disease. The loss of this protein disrupts oriented cell division and tubule elongation during kidney development, causing tubule dilation (36).
Notably, none of the proteins discussed above were upregulated in medullary sponge kidney, showing a different mechanism of cystogenesis. The specific diagnosis of medullary sponge kidney requires the anatomic feature of papillary precalyceal ectasias, sometimes associated with tiny medullary cysts, and such alterations can be unilateral or even limited to a portion of a single kidney medulla. Unlike autosomal dominant polycystic kidney disease, the tubular dilations and microcysts tend to be stable in terms of size throughout life as if they formed at the same time as the kidneys. Taken together, our data confirmed earlier reports indicating that medullary sponge kidney is an inborn malformation similar to developmental disorders, such as congenital hemihypertrophy and Beckwith–Wiedemann syndrome, and kidney developmental anomalies, such as horse-shoe kidney, unilateral kidney aplasia, and contralateral congenital small kidney (37,38), with the absence of the sequence of events leading to cyst formation. Additionally, our data showing the abundance of proteins involved in cell proliferation and extracellular matrix remodeling in patients with autosomal dominant polycystic kidney disease could in part explain why these patients are predisposed to the development of cancer, particularly kidney carcinoma (39).
In contrast, only a few proteins were highly expressed in medullary sponge kidney, mainly in the microvesicles. One example was SPP1 (osteopontin), a protein implicated in nephrolithiasis, a major clinical condition associated with medullary sponge kidney (13). Osteopontin is intimately involved in the regulation of both physiologic and pathologic mineralization. In normal bone tissue, osteopontin is expressed by osteoclasts and osteoblasts during bone remodeling, and osteoclast-derived osteopontin inhibits the formation of hydroxyapatite during normal mineralization (40). Osteopontin is also involved in kidney stone formation (41). This protein is synthesized in the kidney and secreted into the urine by epithelial cells, including the loop of Henle, distal convoluted tubule, and papillary epithelium (42), inhibiting the nucleation, growth, and aggregation of calcium oxalate crystals (43) and the binding of calcium oxalate crystals to kidney epithelial cells (44). Osteopontin knockout mice are hyperoxaluric, leading to the significant intratubular deposition of calcium oxalate, whereas wild-type mice remove calcium oxalate effectively (45). Therefore, the greater abundance of osteopontin in the microvesicles of our patients with medullary sponge kidney could represent a defense mechanism against microcalcification, and it could, at least partially, explain the bone symptoms often observed in patients with this disease. Accordingly, 58% of patients with medullary sponge kidney have a dual-energy x-ray absorptiometry profile of osteopenia, and 14% have a profile of osteoporosis unrelated to the common causes of bone demineralization, particularly hyperparathyroidism and menopause (46).
Taken together, our results have shown for the first time that the urinary microvesicles and exosomes of patients with autosomal dominant polycystic kidney disease and patients with medullary sponge kidney have distinct proteomic profiles. The urine of patients with autosomal dominant polycystic kidney disease was enriched for proteins involved in cell proliferation and matrix remodeling, probably due to pathologic tissue remodeling prompting cystic development and enlargement. In contrast, the urine of patients with medullary sponge kidney revealed a proteome indicative of a systemic biochemical imbalance that could explain the predisposition of such patients to parenchymal calcium deposition/nephrolithiasis and extrarenal complications, including bone mineralization defects.
Although small sample size and lack of independent replication are major weaknesses of the study and additional research is required for validation, some of the proteins (mainly CD133) that we identified could be suitable in the future as diagnostic biomarkers that could help clinicians to distinguish between patients with medullary sponge kidney and patients with autosomal dominant polycystic kidney disease during the early stages of the disease, avoiding time-consuming and expensive clinical testing.
Dr. Antonini, Dr. Antonucci, Dr. Bartolucci, Dr. Bruschi, Dr. Candiano, Dr. Del Zotto, Dr. Fabris, Dr. Gambaro, Dr. Granata, Dr. Ghiggeri, Dr. Lupo, Dr. Petretto, Dr. Santucci, and Dr. Zaza have nothing to disclose.
This article contains the following supplemental material online at http://cjasn.asnjournals.org/lookup/suppl/doi:10.2215/CJN.12191018/-/DCSupplemental.
Supplemental Material. Methods.
Supplemental Figure 1. Age and eGFR of all study participants included in the study.
Supplemental Figure 2. Characterization of isolated exosomes and microvesicles.
Supplemental Figure 3. Gene Ontology annotation of urinary extracellular vesicle proteins.
Supplemental Figure 4. Multidimensional scaling analysis of extracellular vesicles from the urine of patients with medullary sponge kidney (MSK) and patients with autosomal dominant polycystic kidney disease (ADPKD).
Supplemental Figure 5. Sample clustering and trait indicators.
Supplemental Figure 6. Venn diagram of statistically significant differences in protein abundance in the different types of extracellular vesicles from patients with medullary sponge kidney (MSK) or patients with autosomal dominant polycystic kidney disease (ADPKD).
Supplemental Figure 7. Proteins network interaction.
Supplemental Figure 8. Gene ontology enrichment analysis for core discriminatory proteins in the extracellular vesicles of patients with medullary sponge kidney (MSK) and patients with autosomal dominant polycystic kidney disease (ADPKD).
Supplemental Table 1. List of all significant proteins identified using mass spectrometry.
Supplemental Table 2. ELISA cutoff, sensitivity, specificity, and likelihood ratio.
This study was performed (in part) in the Laboratorio Universitario di Ricerca Medica Research Center, University of Verona.
This study was supported by Fondazione Cariverona call 2016 (Principal Investigator Prof. Tagliaro) and Ministero Della Salute grant GR-2011-02350438.
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