Messenger RNA expression of glomerular podocyte markers in the urinary sediment of acquired proteinuric diseases

Messenger RNA expression of glomerular podocyte markers in the urinary sediment of acquired proteinuric diseases

Clinica Chimica Acta 361 (2005) 182 – 190 www.elsevier.com/locate/clinchim Messenger RNA expression of glomerular podocyte markers in the urinary sed...

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Clinica Chimica Acta 361 (2005) 182 – 190 www.elsevier.com/locate/clinchim

Messenger RNA expression of glomerular podocyte markers in the urinary sediment of acquired proteinuric diseases Cheuk-Chun Szeto a,*, Ka-Bik Lai a, Kai-Ming Chow a, Carol Yi-Ki Szeto a, Thomas Wai-Cheong Yip c, Kam-Sang Woo a, Philip Kam-Tao Li a, Fernand Mac-Moune Lai b a

Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong, China b Department of Anatomical and Cellular Pathology, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong, China c Department of Medicine, Yan Chai Hospital, N.T., Hong Kong, China Received 22 March 2005; received in revised form 20 May 2005; accepted 20 May 2005 Available online 5 July 2005

Abstract Background: Podocyte slit diaphragm plays an important role in the control of glomerular permeability. We hypothesize that studying the gene expression profile of podocyte in urinary sediment may provide diagnostic and prognostic information on acquired proteinuric diseases. Methods: We studied 28 patients who required kidney biopsy for acquired proteinuric diseases (diabetic glomerulosclerosis, 9 cases; IgA nephropathy, 10 cases; minimal change disease, 5 cases; membranous nephropathy, 5 cases). We also studied 10 cases of diabetic microalbuminuria and 9 healthy controls. The mRNA expressions of nephrin (NephRNA), podocin (PodRNA) and synaptopodin (SynRNA) in urinary sediment were measured by real time quantitative PCR. After recruitment, all patients were followed for at least 12 months. Results: There were significant differences in the NephRNA and PodRNA in the urinary sediment between diagnosis groups ( p b 0.005). On the other hand, SynRNA was only marginally significant between diagnosis groups ( p b 0.05). Although statistically significant, the degree of proteinuria had only modest correlations with the urinary expression of nephrin. After a median follow up for 23 months, there was a significant correlation between the rate of decline in renal function and NephRNA (r = 0.559, p = 0.001) and PodRNA (r = 0.530, p = 0.002), but not SynRNA (r = 0.054, p = NS). The correlation remained statistically significant after multivariate analysis to adjust for the degree of proteinuria and initial renal function. Conclusions: Urinary mRNA expression of podocyte markers, such as nephrin and podocin, are significantly different between proteinuric disease categories. Further, NephRNA and PodRNA correlated with the rate of decline in renal function.

* Corresponding author. Tel.: +852 2632 3173; fax: +852 2647 5632. E-mail address: [email protected] (C.-C. Szeto). 0009-8981/$ - see front matter D 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.cccn.2005.05.016

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Our results suggest that urinary podocyte gene expression may be a useful non-invasive tool which provides additional information for the management of proteinuric diseases. D 2005 Elsevier B.V. All rights reserved. Keywords: Nephrin; Synaptopodin; Chronic kidney disease

1. Introduction Podocyte, the glomerular epithelial cell, plays a critical part in the architecture and function of normal glomerulus [1]. During the formation of glomerular filtrate, the slit diaphragm that joins podocyte foot processes is the major barrier for macromolecule [2]. The slit diaphragm and its underlying contractile apparatus of podocyte are make up of a number of closely inter-linked proteins (for example, nephrin, podocin, a-actinin-4) [3–5]; hereditary defects of some of those may cause congenital forms of massive proteinuria [1]. For example, mutation of the NPHS1 gene that encodes nephrin, a key component of slit diaphragm, is responsible for the Finnish-type congenital nephrotic syndrome [6]. The role of podocyte slit diaphragm protein in acquired forms of kidney disease has become an active area of research. Recent study showed that the staining pattern of nephrin shifted from a linearlike pattern to a discontinuous coarse granular pattern in a number of rat models of nephrotic syndrome, including puromycin aminonucleoside nephropathy, adriamycin nephropathy and passive Heymann nephropathy [7]. In human, nephrin expression patterns in proteinuric diseases are probably different according to the specific glomerular disease or severity of glomerular damage [8,9]. For example, glomerular levels of nephrin mRNA are significantly decreased in cases of minimal change nephropathy [10]. Renal biopsy specimens from patients with minimal change nephropathy showed redistribution and reduction in concentration of nephrin in the areas with foot process effacement [11–13]. Studies of streptozotocin-induced diabetic rats [14,15], patients with type 1 or type 2 diabetes [16], showed down-regulation of nephrin expression in the diabetic kidney, which was partly reversed with angiotensin-converting enzyme inhibitor [14,15], and it has been postulated that these changes may play a role in the pathogenesis of proteinuria [16]. Reduction of renal expression of nephrin

has been shown to be a specific marker of renal disease in diabetes [17]. Recent study in puromycin aminonucleoside nephrosis model of rat further revealed characteristic reduction of nephrin, podocin and beta-catenin, but increase in h1-integrin protein level [18,19]. Furthermore, nephrin level in proteinuric disease might reflect the severity of the structural glomeruli damage rather than the degree of proteinuria [8,11]. Traditionally, podocyte proteins can only be studied from kidney biopsy specimen. However, kidney biopsy is not without complication, and serial monitoring would be technically difficult. Recently, measurement of messenger RNA (mRNA) expression in urinary sediment by the reverse transcription and real time quantitative polymerase chain reaction assay (RT QPCR) became possible [20–23]. Since recent studies [24–26] showed that cells obtained in the urine of patients with glomerular diseases stained positive for podocyte marker, we hypothesize that studying the gene expression of podocyte in urinary sediment may represent a valuable non-invasive method to study proteinuric kidney diseases.

2. Patients and methods 2.1. Patient selection We recruited 29 unselected patients who required kidney biopsy for proteinuria, with or without clinical nephrotic syndrome. The pathologic diagnoses were diabetic glomerulosclerosis (9 cases), IgA nephropathy (10 cases), minimal change nephropathy (5 cases) and membranous nephropathy (5 cases). We also recruited 10 cases of diabetic microalbuminuria and 9 healthy subjects as controls. For all subjects, a whole-stream early morning urine specimen was collected for gene expression study. We recorded clinical data, including the serum creatinine, urea and albumin levels as measured by conventional methods, as well

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as proteinuria and creatinine clearance as determined by 24-h urine collection. Glomerular filtration rate (GFR) was estimated by a standard equation [27]. 2.2. Messenger RNA from urinary sediment The method of mRNA isolation has been described previously [20]. Briefly, the urine samples were centrifuged at 3500 rpm for 30 min at 4 8C. Urine was discarded and the urinary cell pellet was lysed by RNA lysis buffer (Applied Biosystems). Total RNA was then extracted using ABI Prism 6100 Nucleic Acid Prepstation (Applied Biosystems, Foster City, USA) according to the manufacturer’s suggested protocol. Contaminating chromosomal DNA was digested with Absolute RNA Wash (Applied Biosystems) and removed during the extraction process. 2.3. Real time polymerase chain reaction In the present study, we quantified the urinary mRNA expression of nephrin (NephRNA), podocin (PodRNA) and synaptopodin (SynRNA). For reverse transcription, 2 Al of the total RNA was mixed with 1time TaqMan RT buffer, 5.5 mmol/l MgCl2, 500 Am dNTP, 2.5 Amol/l random hexamer, 0.2 U RNase inhibitor, 0.4 U Multiscribe reverse transcriptase and make up to 20Al with H2O. Reverse transcription was performed at 25 8C for 10 min, 48 8C for 30 min and 95 8C for 5 min. The resulting cDNA were stored in 80 8C until use. The quantification of the relative mRNA abundance was performed using the ABI Prism 7700 Sequence Detector System (Applied Biosystems). In brief, 2 Al of the cDNA was mixed with 200 nmol/l of primers, 200 nmol/l of probe and 1-time TaqMan Universal Master Mix in each reaction. The 18s ribosomal RNA was used as housekeeping gene. We studied the expression of nephrin, podocin and synaptopodin as podocyte markers. Pre-developed assay reagents from Applied Biosystems were used for 18s rRNA. The following sequences of oligonucleotide primers and probes were used [28]: nephrin (NPHS1): sense 5V-CAA CTG GGA GAG ACT GGG AGAA, antisense 5VAAT CTG ACA ACA AGA CGG AGCA, internal probe 5V-TCC ACA ATG CAC TGG TAA GCG CCA; podocin (NPHS2): sense 5V-AAG AGT AAT

TAT ATT CCG ACT GGG ACAT, antisense 5V-TGG TCA CGA TCT CAT GAA AAGG, internal probe 5VTCC TGG AAG AGC CAA AGG CCC TG; synaptopodin: sense 5V-CCC AAG GTG ACC CCG AAT, antisense 5V-CTG CCG CCG CTT CTCA, internal probe 5V-ACT TGC TGG ATC TGG TAC AGA CAG CGG. All samples were performed in triplicate. For the quantification of the target mRNA abundance, differences of threshold cycles between target gene and 18s rRNA were calculated. The relative mRNA abundance in the patient groups was calculated using the 2 DDCt method. 2.4. Clinical follow up After recruitment, all patients were followed for at least 12 months. Clinical management was by individual nephrologist and not affected by the study. Renal function test, including serum creatinine, urea and albumin levels, was assessed at least every 6 months. As mentioned above, estimated GFR was calculated by a standard equation [27]. The rate of GFR decline was calculated by the least-square regression method. 2.5. Statistical analysis Statistical analysis will be performed by SPSS for Windows software ver. 10.0 (SPSS Inc., Chicago, IL). All the results are presented in mean F S.D. unless otherwise specified. As described by Schmid et al. [28], NephRNA and PodRNA were expressed as the ratio to synaptopodin expression. Baseline data were compared by one-way analysis of variance (ANOVA) between groups. Because the distributions of the levels of gene expression were highly skewed, they were compared by Kruskal–Wallis test or Mann– Whitney U test between groups as appropriate. Because the data of gene expression, estimated GFR and proteinuria were highly skewed, they were log-transformed before analysis. Since there were zero values for the data on gene expression ratio, we added one to the ratio before transformation [29]. Correlations between gene expression and clinical parameters (e.g., estimated GFR, degree of proteinuria) were calculated by Pearson’s correlation coefficient. To further confirm the independent effect of urinary podocyte marker expression on renal function decline, backward

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statistically significant because of small number of subjects. In contrast to NephRNA and PodRNA, the difference in SynRNA (relative to the 18s RNA housekeeping gene expression) in the urinary sediment was only marginally significant between diagnosis groups (Kruskal–Wallis test for overall comparison, p b 0.05, Fig. 1C). Post hoc analysis by Mann–Whitney U test did not show significant difference between any two diagnostic groups. There was no significant internal correlation between SynRNA and NephRNA or PodRNA (details not shown).

stepwise multivariate linear regression was used to adjust for the effect of proteinuria and renal function. A P value of b0.05 was considered statistically significant. All probabilities were two-tailed.

3. Results The baseline demographic and clinical data of the patients are summarized in Table 1. One-way ANOVA showed that there were significant differences in age, serum creatinine, proteinuria and estimated GFR between groups. Post hoc analysis showed that patients with diabetic glomerulosclerosis and membranous nephropathy were significantly older than other groups, and patients with diabetic glomerulosclerosis had significantly higher serum creatinine, more proteinuria, and lower estimated GFR than the other groups.

3.2. Podocyte marker expression and baseline renal function Although statistically significant, the degree of proteinuria at baseline had only modest correlations with NephRNA (Pearson’s r = 0.319, p b 0.05). The degree of proteinuria did not correlate with the expression of PodRNA or SynRNA (r = 0.083 and 0.077, respectively). The correlations between proteinuria and gene expression remained similar when cases of minimal change disease were excluded. Baseline estimated GFR did not correlate with NephRNA, PodRNA or SynRNA (Pearson’s r = 0.105, 0.05 and 0.05, respectively).

3.1. Podocyte marker expression and renal diagnosis There were significant differences in NephRNA and PodRNA in the urinary sediment between diagnosis groups (Kruskal–Wallis test, p = 0.005 for both, Fig. 1). Furthermore, there was a strong internal correlation between the NephRNA and PodRNA (Pearson’s r = 0.668, p b 0.001). NephRNA was notably significantly higher in patients with diabetic glomerulosclerosis than those with diabetic microalbuminuria (Mann–Whitney U test, p = 0.05), but there was no difference in NephRNA between patients with diabetic microalbuminuria and normal subjects. NephRNA and PodRNA were marginally higher in patients with membranous nephropathy than minimal change disease, although the differences were not

3.3. Podocyte marker expression and renal function decline The patients were followed for a median of 23 months (range 12–36 months). Twenty-nine patients (74.4%) receive angiotensin-converting enzyme inhibitor or angiotensin-II receptor antagonist as part

Table 1 Demographic and clinical data of the study patients Group

DGS

DMA

MCN

MGN

IgAN

Control

No. of patients Sex (M/F) Age (years)* Renal function Serum creatinine (Amol/l)* Proteinuria (g/day)* Glomerular filtration rate (ml/min/1.73 m2)*

9 6:3 52.1 F 9.2

10 5:5 54.4 F 10.0

5 0:5 39.2 F 15.6

5 1:4 54.1 F15.8

10 3:7 35.8 F 10.9

9 3:6 37.8 F 9.1

277.8 F 162.4 7.1 F 6.7 29.1 F17.9

92.0 F 40.4 0.3 F 0.3 76.7 F 32.9

81.0 F 19.2 4.6 F 1.3 77.9 F 21.8

73.2 F 33.1 3.7 F 2.0 98.6 F 43.1

119.0 F 66.3 1.8 F 1.5 66.3 F 27.4

82.8 F 22.9 – 84.6 F 22.3

DGS, diabetic glomerulosclerosis; DMA, diabetic microalbuminuria; MCN, minimal change nephropathy; MGN, membranous nephropathy; IgAN, IgA nephropathy. * p b 0.001 by one-way ANOVA.

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A

B

p < 0.001 p = 0.008

4

p = 0.001

p = 0.002

4

p = 0.003

Podocin-to-synaptopodin mRNA expression ratio

Nephrin-to-synaptopodin mRNA expression ratio

p = 0.016 3

2

1

0

3

2

1

0 DGS

DMA

MCN

MGN

IgAN

DGS

Control

DMA

MCN

p = 0.034

MGN

IgAN

Control

p = 0.011

p = 0.028

p = 0.028

C

25

Synaptopodin-to-18s RNA mRNA expression ratio

20

15

10

5

0

DGS

DMA

MCN

MGN

IgAN

Control

Fig. 1. Relation between underlying renal diagnosis and the urinary mRNA expression of (A) nephrin, (B) podocin, and (C) synaptopodin. There were significant difference in the expression of all three targets (overall comparison by Kruskal–Wallis test, p b 0.005, p b 0.005 and p b 0.05, respectively). P values shown on the figures represent post hoc comparison by Mann–Whitney U test.

of their treatment. The average rate of decline in estimated GFR was 1.1 F 2.1 ml/min/1.73 m2/ month. There was a significant correlation between the rate of decline in estimated GFR and NephRNA (Pearson’s r = 0.559, p = 0.001) and PodRNA (r = 0.530, p b 0.005, Fig. 2). On the other hand, the rate of decline in estimated GFR did not correlate with SynRNA (r = 0.054, p = NS). With backward stepwise linear regression, there remained significant associa-

tion between NephRNA and rate of GFR decline after adjusting for the degree of proteinuria and initial renal function (standardized beta 0.694, 95% confidence interval 0.663 to 1.498, p b 0.001).

4. Discussion In this study on acquired proteinuric diseases, we found that urinary mRNA expression of certain

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A

B 3.0

3.0

r = 0.559, p = 0.001 loge (rate of GFR decline)

2.5 loge (rate of GFR decline)

187

2.0 1.5 1.0 0.5

r = 0.530, p = 0.002

2.5 2.0 1.5 1.0 0.5 0.0

0.0 0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

0.0

1.8

loge (rate of GFR decline)

3.0

0.4

0.6

0.8

1.0

1.2

1.4

1.6

loge (podocin-to-synaptopodin expression ratio)

loge (nephrin-to-synaptopodin expression ratio)

C

0.2

r = 0.054, p = 0.8

2.5 2.0 1.5 1.0 0.5 0.0 0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

loge (synaptopodin-to-18s RNA expression ratio)

Fig. 2. Relation between the rate of decline of estimated glomerular filtration rate (GFR) and the urinary mRNA expression of (A) nephrin, (B) podocin, and (C) synaptopodin. Because the data of gene expression and estimated GFR are highly skewed, they are log-transformed before plotting. A high value of GFR decline represents more rapid loss of renal function.

podocyte markers, such as nephrin and podocin, is significantly different between proteinuric disease categories. Furthermore, the urinary expression of nephrin and podocin correlated with the rate of decline in renal function even after adjusting for the degree of proteinuria. Our results suggest that urinary podocyte gene expression may be a useful non-invasive tool which provides additional information for the management of proteinuric diseases. Our result is different from the recent report by Schmid et al. [28], who found that the mRNA expression of nephrin and podocin in renal biopsy

specimen did not allow a separation between proteinuric disease categories. It should be noted that we studied mRNA expression in urinary sediment, while Schmid et al. [28] studied the glomerular mRNA expression by microdissection of renal biopsy specimens. It is reasonable to assume that surviving podocytes that stay in the glomeruli are qualitatively different from the ones denuded into the urine [1], explaining the difference in results of the two studies. In fact, we found that nephrin expression in the urinary sediment of patients with biopsy-confirmed diabetic glomerulosclerosis was increased, while Toyoda et al. [30] and Doublier et al. [31] both

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reported that nephrin expression was reduced in the renal biopsy specimens. Taken together, these findings are consistent with the current belief that some pathologic processes induce podocyte detachment from glomeruli, resulting in podocytopenia, which probably contribute to the progression of glomerulosclerosis [1]. We found that the urinary expression of nephrin and podocin was useful for distinguishing diagnostic groups as well as predicting renal function decline, while the expression of synaptopodin gave little diagnostic or prognostic information. It is interesting to note that in the study of Schmid et al. [28], synaptopodin was used as the bhouse-keeping geneQ within the glomerulus to correct for the expression of other podocyte markers. The findings of Schmid et al. [28] and ours are both in line with the hypothesis that podocyte expression of synaptopodin is relatively constant, while the expressions of other markers (for example, nephrin and podocin) are affected by various pathologic processes. From an anatomic point of view, synaptopodin is an actinassociate protein and is present in the cytoplasm of podocyte foot processes [1,32], while nephrin and podocin are critical components of slit diaphragm [1], which is the important determinant of glomerular permeability [33,34]. Recent experiments also show that podocyte expression of slit diaphragm components, for example nephrin, is up-regulated by inflammatory cytokines [35] and angiotensin II [36]. It is important to note that our present study represents only a pilot work in this area. The sample size of each diagnostic category was small, and the median duration of follow up was relatively short. Because of limited statistical power, we were unable to perform an extensive multivariate analysis to exclude potential confounding effects of other prognostic indicators, such as anti-proteinuric therapy and degree of kidney scarring in renal biopsy specimen. We believe a study of larger scale is needed to confirm the diagnostic and prognostic value of this novel investigation tool, especially in other chronic proteinuric kidney diseases. In this series of work, we studied the gene expression rather than the actual protein level of podocyte markers. We believe that measuring specific podocyte markers at protein level (for exam-

ple, by Western blotting) in urine may not be valid because a substantial but variable proportion of proteins, especially low molecular ones, are metabolized by renal tubular cells [37]. Our previous experiment showed that the integrity of RNA isolated from urinary sediment, as determined by gel electrophoresis for the 28S and 18S rRNA bands, was satisfactory for RT-QPCR [38]. Furthermore, gene expression study at mRNA level allows high throughput examination of multiple targets simultaneously [39], with better potential of future clinical application. It is important to note that we could not affirm the cellular compositions of the urinary sediment in the present study. We did not perform immunohistochemistry for the urinary sediment to determine the type and proportion of cells with positive stain of nephrin and podocin. Nevertheless, recent studies showed that podocyte can be isolated and cultured in the urine of patients with renal diseases [24–26]. Urine microscopic examination of our patients showed that the sediments were composed mainly of erythrocytes, mononuclear leukocytes and tubular epithelial cells. Furthermore, it was possible that cells from sources other than the kidney (for example, female genital tract) might also appear in the urine [40]. However, to the best of our knowledge, nephrin, podocin and synaptopodin are not expressed by other cellular components of urinary sediment.

Acknowledgement This study was supported by the Chinese University of Hong Kong (CUHK) Direct Research Grant reference number 2041051. All authors declare no conflict of interest.

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