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Keywords:

  • Acute cellular rejection;
  • biomarker;
  • kidney graft function;
  • microRNA;
  • urine

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. Disclosure
  9. References

MicroRNAs (miRNAs) are small ribonucleotides regulating gene expression. Circulating miRNAs are remarkably stable in the blood. We tested whether miRNAs are also detectable in urine and may serve as new predictors of outcome in renal transplant patients with acute rejection. We profiled urinary miRNAs of stable transplant patients and transplant patients with acute rejection. The miR-10a, miR-10b and miR-210 were strongly deregulated in urine of the patients with acute rejection. We confirmed these data in urine of a validation cohort of 62 patients with acute rejection, 19 control transplant patients without rejection and 13 stable transplant patients with urinary tract infection by quantitative RT-PCR. The miR-10b and miR-210 were downregulated and miR-10a upregulated in patients with acute rejection compared to controls. Only miR-210 differed between patients with acute rejection when compared to stable transplant patients with urinary tract infection or transplant patients before/after rejection. Low miR-210 levels were associated with higher decline in GFR 1 year after transplantation. Selected miRNAs are strongly altered in urine of the patients with acute renal allograft rejection. The miR-210 levels identify patients with acute rejection and predict long-term kidney function. Urinary miR-210 may thus serve as a novel biomarker of acute kidney rejection.


Abbreviations: 
ATN

acute tubular necrosis

C. elegans

Caenorhabditis elegans

CMV

cytomegalovirus

f/t

freeze/thaw

GN

glomerulonephritis

HD

hemodialyis

miRNA

microRNA

MMF

mycophenolat mofetil

PD

peritoneal dialysis

qRT-PCR

quantitative real-time polymerase chain reaction

RRT

renal replacement therapy

Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. Disclosure
  9. References

The introduction of potent immunosuppressive drugs in the past three decades was the prerequisite for a dramatic reduction in the incidence of acute rejection in kidney transplant recipients. However, the lack of noninvasive biomarkers of rejection oftentimes precludes an optimization of prompt antirejection therapy. Currently, conventional histological examination of renal allograft biopsies remains the gold standard for diagnosing acute rejection among transplant patients with impaired kidney function. In addition to overt acute rejection, protocol biopsies also allow for early detection of subclinical rejection, which is defined as histological evidence of acute rejection without a significant rise in serum creatinine (1). Repeated measurements of serum creatinine levels represent the principal form of monitoring for acute rejection. Although serum creatinine is the most widely used marker to monitor allograft function, it is not sensitive in detecting kidney injury. In contrast, protocol biopsies are a highly sensitive and specific method of detecting acute rejection but are associated with potentially severe side effects due to their invasive nature.

MicroRNAs (miRNAs) are endogenous, single-stranded molecules consisting of approximately 22 noncoding nucleotides, which lead to the repression of target genes through the posttranscriptional degradation of messenger-RNA (mRNA) and translational inhibition of protein expression (2). Genetic gain and loss of function studies showed a disease-specific role for selected miRNAs (3). Thus, deregulation of miRNAs likely results in a severe disturbance of downstream gene networks and signaling cascades within the cell culminating in disease initiation and/or progression (4). The miRNAs also play a role in kidney diseases (5). Accumulating evidence underlines a critical function for miRNAs in the modulation of innate and adaptive immune responses (6,7). Recent studies demonstrated that miRNAs are also detectable in the circulation and useful as biomarkers for diseases (8). The detection of urinary miRNAs and their usefulness as biomarkers in patients with bladder cancer has recently been described (9). Their diagnostic use as markers of acute renal allograft rejection remains unclear. In this study, we tested the hypothesis that urinary miRNAs of transplant patients with acute allograft rejection are altered and hence, might serve as biomarkers and predictors of long-term allograft function. The miRNAs were measured in urine of 62 patients with acute T-cell mediated rejection, including 19 patients before the rejection episode and after successful antirejection therapy and 19 transplant patients with stable kidney function without the evidence of rejection. Thirteen stable transplant patients with urinary tract infection served as additional disease controls.

Materials and Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. Disclosure
  9. References

Patients and sample collection

The study was confirmed by the Ethical Committee of the Hannover Medical School, Germany, and all the patients received/signed written informed consent. At our transplant center, renal protocol biopsies are regularly performed after 6 weeks, 3 and 6 months of kidney or combined kidney/pancreas transplantation. In addition, midstream spot urine samples are collected immediately before the biopsy and are subsequently frozen at −80°C. Fresh urine samples are routinely analyzed for protein concentration and screened for hematuria and leukocyturia by dipstick analysis and microscopic inspection. Using the files from patients who participated in the protocol biopsy program, available urine samples were divided into two groups: (i) patients with biopsy-proven acute cellular rejection (n = 62) and (ii) transplant patients with stable kidney function and without any evidence of acute rejection as controls (n = 19). Sixty-eight urine samples of 62 patients with acute cellular rejection (six patients had two rejection episodes) and 20 urine samples of 19 control patients were analyzed. In total, acute cellular rejection could be detected in 20 urine samples of patients after 6 weeks, 32 urine samples after 3 months and 16 urine samples after 6 months of kidney transplantation. Thirteen additional samples of stable transplant patients with urinary tract infection served as disease controls. Nineteen urine samples before the rejection episode and after successful antirejection therapy of patients with acute rejection were also analyzed (12 samples before and 7 samples after rejection). Interpretation of biopsies was performed according to the updated Banff 2009 classification (10). Glomerular filtration rate (GFR) was calculated according to the Cockroft and Gault formula.

Sampling and quantification of urinary miRNAs

The RNA was isolated using the MasterPure™ RNA Purification Kit (Epicentre Biotechnologies, Madison, WI, USA) according to the manufacturer's instructions. Fifty microliters of urine were used for RNA isolation. We supplemented the samples with 1 fmol/μL Caenorhabditis elegans miR-39 (cel-miR-39) and normalized urinary miRNAs to this control, as described previously (11). The stability of miRNAs in urine was analyzed in urine samples obtained from three healthy individuals. For this purpose, the samples were subjected to incubation at RT for 4 and 24 h as well as to 4 freeze/thaw (f/t) cycles.

miRNA Transcriptome profile analysis

Pooled total urinary RNA from five patients with acute renal allograft rejection (three patients with clinical IIa, two patients with clinical Ia rejection according to the Banff classification), and five age-matched renal transplant patients with a stable kidney function without the signs of rejection as controls was used for a global miRNA array analysis. Total RNA was processed as described earlier (4). We employed the Human Genome Wide miRNA 384-well quantitative real-time polymerase chain reaction (qRT-PCR) Array (Biocat, Hiedelberg, Germany), according to the manufacturer's instructions to screen for deregulated miRNAs.

Detection and quantification of miRNAs by quantitative PCR

From the initial screen, miR-10a, -10b and -210 were validated by quantitative miRNA stem loop RT-PCR technology (TaqMan MicroRNA Assays, Applied Biosystems, Foster City, CA, USA) in 68 urine samples of patients with acute cellular renal allograft rejection, 20 urine samples of transplant patients without rejection, 13 urine samples of transplant patients with urinary tract infection and 19 urine samples of patients with acute cellular renal allograft rejection before and after the rejection episode. We used highly target-specific stem loop structure and reverse transcription primer, and after reverse transcription used specific TaqMan hybridization probes for miRNA amplification. This allowed for high specificity for only the mature miRNA and formation of a reverse transcription primer/mature miRNA chimera, extending the 5′ end of the miRNA. Values were normalized to spiked-in cel-miR-39.

Study outcomes and statistical analysis

The main objective of the study was to analyze the predictive value of urinary miRNAs concerning long-term outcome of renal transplant patients with acute rejection. The study endpoint was defined as change/loss in GFR, 1 year after transplantation. Continuous variables are expressed as medians with corresponding 25th and 75th percentiles (IQR) and were compared by using the Mann–Whitney rank sum test or the Kruskal–Wallis one-way analysis of variance. Age is displayed as median (min–max). Categorical variables were compared using the χ2-test. Variables were assessed for normal distribution using the Kolmogorov–Smirnov test. Correlations between variables were assessed by the Spearman rank correlation coefficient. All statistical analyses were performed with the SPSS package (SPSS Inc., Chicago, IL, USA) and GraphPad Prism software (GraphPad Prism Software Inc., San Diego, CA, USA). Two-sided values p < 0.05 were considered statistically significant for all statistical procedures used.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. Disclosure
  9. References

Preprocessing storage and stability

To test the preprocessing stability, urine samples of three healthy individuals were stored for up to 24 h at RT. The miR-21 as a highly abundant miRNA was amplified using RNA isolated from these samples. Storage at RT did not produce a discernible loss of miR-21 expression after 4 and 24 h (Figure 1). Moreover, four cycles of freezing (20 h at −70°C) and thawing (4 h at RT) induced no discernible loss of cell-free miR-21 expression (Figure 1). The same stability was observed with urinary miR-126 (data not shown). Thus, urinary miRNAs remain stable over time.

image

Figure 1. Stability experiments concerning miR-21 expression in urine of 3 healthy volunteers. Urine of healthy volunteers was subjected to incubation at RT for 4 and 24 h as well as 4 f/t cycles. Incubation for the indicated time points and repeated f/t induced no discernible loss of miR-21 expression. Data are displayed as mean ± standard deviation (SD).

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Deregulated miRNAs in acute cellular renal allograft rejection

To assess the impact of acute renal allograft rejection on urinary miRNA levels, we conducted a global miRNA expression analysis using pooled RNA, isolated from urine of patients with acute cellular rejection (n = 5), and age-matched control kidney transplant patients without rejection (n = 5). The clinical characteristics of the cohort patients (n = 62) are shown in Table 1. In total, 68 samples of patients with acute rejection (6 patients had two rejection episodes at different time points), 20 samples of stable controls without rejection (1 control patient donated 2 different samples after 6 weeks and 3 months of transplantation), 19 samples of patients before/after rejection (these samples were chosen out of the 68 samples with acute rejection at a different time point after transplantation) and 13 stable transplant patients with urinary tract infection were analyzed. The median age of patients with acute rejection was 51 years (21–72) and 51 years (18–67) in stable control patients. Acute rejections were classified as subclinical (i.e. serum creatinine increase at the time of biopsy by less than 20% compared to previous determinations) in 55 samples of patients, and clinical (i.e. serum creatinine increase at the time of biopsy by more than 20% compared to previous determinations) in 13 samples of patients. The majority of rejections were graded Ia according to the Banff 2009 classification (Table 2). Additional biopsy findings included chronic changes such as tubulointerstitial fibrosis and tubular atrophy, acute tubular necrosis, isometric vacuolization of tubular cells and nephrocalcinosis (Table 2). The incidence of these changes was not statistically different between the two groups except for isometric vacuolization (p = 0.03) and acute tubular necrosis (p = 0.07). One of the biopsies of the control patients had signs of de novo glomerulonephritis (GN), whereas none of the patients had signs of recurring GN (Table 2). In the initial screen, the levels of 21 circulating miRNAs differed more than 10-fold between patients and stable controls (Table 3). We then screened urinary miR-10a, -10b and -210 levels in a validation set of 68 samples of patients with acute cellular rejection and 20 samples of transplant patients without evidence of rejection by using TaqMan qRT-PCR. As shown in Figures 2A–C, the results of the miRNA profile could be confirmed in the entire cohort identifying miR-10b and -210 to be downregulated (p = 0.02 and p < 0.05, respectively) and miR-10a to be upregulated (p < 0.01) in patients with acute rejection compared to controls without rejection. Our study population consisted of 35 females (43%) and 46 males (57%), but miR-10a did not differ between males and females. The miR-210 was higher in females as compared to males (p < 0.0001), whereas miR-10b was elevated in male patients (p = 0.04). The significance concerning sex only remained for miR-210 in the group of patients with rejection (p < 0.0001). There was no correlation between age and miR-10b as well as miR-210 levels, but a trend for a weak negative correlation between miR-10a levels and age (r =−0.2; p = 0.06) had been observed. Similarly, the levels of miR-10a (r = 0.09; p = 0.5), miR-10b (r = 0.05; p = 0.7) and miR-210 (r =−0.07; p = 0.5) did not correlate with GFR at the time of biopsy. However, miR-210 (r =−0.3; p < 0.05) was significantly associated with decline in GFR 6 weeks after transplantation compared to 1 year after transplantation, indicating higher GFR loss in patients with low miR-210 levels (Figure 3). When patients were divided according to the severity of rejection as defined by the Banff classification, the levels of urinary miR-210 declined significantly with the increase in severity (p < 0.01). Moreover, patients with clinical acute cellular rejection differed from age-matched stable control patients in a subanalysis (p = 0.05). As in our kidney transplantation program patients are evaluated at three different time points after kidney transplantation, we also included urine samples of 19 patients before or after acute cellular rejection (12 patients before the occurrence of rejection and 7 patients after successful antirejection therapy). The miR-210 was significantly lower (p < 0.001) in urine samples of patients with acute rejection compared to the patients before rejection (Figures 2D–F). Successful antirejection resulted in a normalization of miR-210 levels comparable with the samples of stable controls (Figures 2D–F). Levels of miR-10b were elevated in patients with acute rejection compared to patients before/after rejection (p = 0.02), whereas levels of miR-10a were not significantly different in urine samples of patients with acute cellular rejection compared to urine samples before/after rejection (p = 0.5). The miR-210 levels were decreased in urine samples of patients with acute rejection, but not in a disease control group of stable kidney transplant patients with urinary tract infection ([median: 7.6 × 10−6; IQR: 3.4 × 10−6–2.1 × 10−5 vs. median: 35.1 × 10−6; IQR: 19.5 × 10−6–65.4 × 10−6]; p < 0.01), whereas levels of miR-10a (median: 1.9 × 10−4; IQR: 8.6 × 10−5–2.2 × 10−4) and miR-10b (median: 9.2 × 10−5; IQR: 5.8 × 10−5–1.3 × 10−4) did not significantly differ from these disease controls (p = 0.6 and 0.3, respectively). The miR-210 did not significantly correlate with leukocyturia (p = 0.1). We calculated receiver–operator characteristics curves to address the diagnostic value of urinary miR-210 in patients with acute cellular rejection. In comparison to stable control transplant patients, a ratio of 7.9 × 10−6 resulted in a specificity of 52% and a sensitivity of 74% in diagnosing acute rejection (area under the curve 0.7 ± 0.07; 95% CI 0.5–0.8; p = 0.04).

Table 1.  Demographic, clinical and laboratory characteristics of patients
 TotalNo rejectionRejectionp-Value
  1. CMV = cytomegalovirus; HD = hemodialyis; MMF = mycophenolat mofetil; n = number of patients; PD = peritoneal dialysis; RRT = renal replacement therapy. Values of circulating miRs represent a ratio between the expression of miRs of interest normalized to spiked-in C. elegans control miRs. Levels of urinary miRNAs are expressed as medians with corresponding 25th and 75th percentiles (IQR).

  2. *p < 0.05.

Number of patients8119620.4
 Male (n;%)46 (57)1036 
 Female (n;%)35 (43)926 
Age (years; min-max)50 (18–73)51 (18–67)51 (21–72)0.5
Primary transplant (n)7216560.5
Additional pancreas-Tx (n)3210.07
Type of allograft (n)
 Deceased7018520.2
 Living11110 
Initial graft function (n)6314490.6
Need for HD post-tx (n)195140.7
HLA mismatch (n)
 Locus A (0/1/2)42/32/712/5/230/27/50.4
 Locus B (0/1/2)34/33/1411/6/223/27/120.2
 Locus DR (0/1/2)26/40/1512/7/014/33/150.002*
Donor CMV status (n; pos/neg)49/327/1242/200.02*
Type of RRT before Tx (HD/PD/preemptive)73/6/218/1/055/5/20.6
Diabetes   0.4
 Type I422 
 Type II514 
Hyperparathyroidism before Tx263230.1
Initial immunosuppression (n)
 Cyclosporin6316470.4
 Tacrolimus153120.7
 MMF4812360.7
 Azathioprine1010.6
 Rapamycine7160.5
 Steroides7618580.9
Preformed antibodies (>1%)4310.01*
miR-10a3.4 × 10−5 (1.5 × 10−5–6.8 × 10−5)6.6 × 10−5 (3.6 × 10−5–9.0 × 10−5)2.6 × 10−6 (1.2 × 10−5–5.7 × 10−5)<0.01*
miR-10b1.2 × 10−4 (4.0 × 10−5–2.7 × 10−4)2.0 × 10−4 (4.7 × 10−5–4.9 × 10−4)1.0 × 10−4 (3.4 × 10−5–2.1 × 10−4)0.02*
miR-2101.2 × 10−5 (3.7 × 10−6–2.7 × 10−5)2.7 × 10−5 (6.2 × 10−6–7.0 × 10−5)7.6 × 10−6 (3.4 × 10−6–2.1 × 10−5)<0.05*
Table 2.  Corresponding biopsy findings according to Banff 2009
 Control urine samples (n = 20)Acute rejection urine samples (n = 68)
ClinicalSubclinicalp-Value
  1. ATN = acute tubular necrosis; GN = glomerulonephritis.

  2. *p < 0.05.

aGrade   <0.001*
 Ia837 
 Ib37 
 IIa210 
 IIb01 
cGrade   0.3
 Mild3217 
 Moderate011 
ATN
 Focal710360.07
Calcineurin inhibitor toxicity (Isometric vacuolization)5140.03*
Tubulointerstitial calcification1160.5
Chronic lesions   0.8
 Focal10724 
 5–10%209 
 10–15%014 
 15–20%011 
De novo GN1000.09
Recurrent GN000
Table 3.  qRT-PCR based screen of urinary microRNAs in patients with acute cellular rejection versus control patients with stable kidney function
MicroRNACt value rejectionCt value controlChange in expression >10-fold
  1. *Represents the microRNA star sequence.

hsa-miR-21036.4626.310.0004
hsa-miR-10b37.629.030.0013
hsa-miR-9*37.0430.410.0049
hsa-miR-146937.2131.880.0120
hsa-miR-153735.4931.080.0227
hsa-miR-323–5p36.6332.550.0286
hsa-miR-126032.4328.580.0335
hsa-miR-128035.6832.110.0407
hsa-miR-147037.8934.50.0461
hsa-miR-42135.7832.680.0563
hsa-miR-92b35.9933.270.0733
hsa-miR-548p34.61320.0791
hsa-miR-63837.8735.330.0830
hsa-miR-135a31.2228.830.0921
hsa-miR-187*37.735.320.0928
hsa-miR-128136.3634.070.0988
hsa-miR-64932.937.6212.7293
hsa-miR-373*37.9542.8714.6221
hsa-miR-61034.240.0327.4756
hsa-miR-41234.7440.6929.8586
hsa-miR-10a29.7735.8332.2243
image

Figure 2. Scatter plots of deregulated microRNAs. Levels of urinary miRNAs are strongly deregulated in renal transplant patients with acute rejection (rejection) versus control transplant patients without rejection (CTL). The miR-10a is upregulated (p < 0.01) (A) whereas miR-10b (B) and -210 (C) are downregulated in patients with acute cellular rejection (p = 0.02 and p < 0.05, respectively). Levels of miR-210 significantly differ between patients with acute cellular rejection as compared to transplant patients before/after rejection (D, p < 0.0001). Similarly, levels of miR-210 are significantly lower in urine samples of patients before rejection (E, p < 0.0001) and after successful antirejection therapy (F, p < 0.001). Bars represent mean values. Y-axis is displayed logarithmically.

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image

Figure 3. Urinary miR-210 predicts long-term outcome of renal transplant patients with acute rejection. Low miR-210 levels (r =−0.3, p < 0.05) are significantly associated with decline in GFR 1 year after transplantation.

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Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. Disclosure
  9. References

Our study is the first clinical evaluation of urinary miRNAs in patients with acute renal allograft rejection. The results are as follows: (1) the detection of miRNAs in urine is feasible; (2) levels of miR-10b and -210 were shown to be decreased and miR-10a to be increased in patients with acute renal allograft rejection; (3) miR-210 predicts decline in GFR 1 year after transplantation and (4) only miR-210 differed between patients with acute cellular rejection and stable transplant patients with urinary tract infection as well as between transplant patients before or after acute renal allograft rejection.

We provide evidence of the successful isolation and measurement of urinary miRNAs in patients with acute renal allograft rejection. Due to the profound regulation of multiple miRNAs and the unknown impact of factors that modulate circulating miRNA levels, we did not normalize levels of circulating miRNAs to a urinary “housekeeping” miRNA, which currently is not available. Instead, we supplemented the urine samples with recombinant cel-miR-39, which can be specifically detected by TaqMan-qRT-PCR, to normalize potential differences in the efficiency of RNA isolation, as shown previously for plasma samples (11). Currently, to our knowledge, stable urinary miRNAs have not been identified so far, thus impeding the possibility to use certain miRNAs as normalizing controls in urine. It is unlikely (dependent upon the disease condition investigated) that a single miRNA in urine might serve as a stable control miRNA. Supplementing urine samples with recombinant C. elegans miRNAs provides for a reliable method of normalizing potential differences in the efficiency of RNA isolation.

In the past few years, research efforts aimed toward the identification of noninvasive markers of acute rejection. In this regard, circulating blood levels of soluble adhesion molecules, cytokines and the urokinase plasminogen activator receptor and lymphocyte expression of perforin, granzyme B and FAS ligand, have been investigated as potential markers of rejection (12). In urine, detection of adhesion molecules and complement C4d (12) and the mRNA expression of granzyme B, perforin and granulysin (12) in urinary cells has been studied in acute rejection. However, detection of none of these markers has been introduced to routine clinical application. The underlying mechanistic basis for deregulated gene expression during an episode of acute rejection remains an area of utmost interest, which has not been completely solved. The miRNAs regulate a large fraction of the genome, including genes involved in adaptive immunity. Anglicheau et al. (13) have shown a set of miRNAs to be highly deregulated in renal biopsy samples and peripheral blood mononuclear cells of patients with acute rejection. We present here the first study on the expression of miRNAs in easily accessible urine, which can be obtained without the complications associated with a kidney biopsy. As opposed to circulating plasma or serum miRNAs, deregulated urinary miRNAs might be a better estimate of local intrarenal changes. Circulating miRNAs, on the contrary, might be released by a variety of tissues, thus reflecting a secondary response to acute renal allograft rejection.

During the molecular reaction to hypoxic stimuli, the enrichment of hypoxia-inducible factor in cells is a crucial inducer of miR-210 (14). In addition, miR-210 hypoxic induction was shown to be dependent on the von Hippel–Lindau tumor suppressor gene in RCC4 renal carcinoma cells (15). It is thus conceivable that levels of urinary miR-210 are decreased in acute rejection due to enrichment within kidney tissue. However, levels of circulating miR-210 were shown to be upregulated in acute ischemic diseases such as myocardial infarction (16) and acute kidney injury (17), suggesting differences in miRNA transport and/or secretion dependent on the disease condition. The miR-10a was shown to regulate the proinflammatory phenotype in athero-susceptible endothelium in vivo and in vitro (18). The miR-10a might, therefore, regulate the invasion of immune cells in the setting of acute cellular rejection. Concerning miR-10b, the results of Anglicheau et al. could be confirmed by showing this specific miRNA to be downregulated in patients with acute rejection (13). Although Anglicheau analyzed the expression of miRNAs in biopsy specimens of renal tissue and in circulating mononuclear cells, we concentrated on the detection of urinary miRNAs. The findings concerning miR-10b might represent a common mechanism of deregulation in this patient cohort.

In our cohort of patients, we identified miR-210 as the only specific urinary biomarker of acute cellular rejection, because levels of this particular miRNA, as opposed to miR-10a and -10b, discriminated between stable control transplant patients and other pathologies (i.e. urinary tract infection) as well as between patients before/after the occurrence of acute rejection. The fact that miR-210 decreases specifically with the development of acute rejection and increases to stable control levels with successful antirejection therapy provides evidence for miR-210 to serve as a novel biomarker of acute rejection with the potential for clinical application as a marker to monitor for rejection and/or susceptibility to antirejection therapy without the potential harms associated with an invasive renal allograft biopsy. Our data suggest that urinary miRNAs might be an interesting readout for therapeutic interventions. Interfering with miRNAs in other organ systems has already been shown to alter pathophysiological processes (3,19,20).

There are certain limitations to our study: importantly, molecular insights into the underlying mechanisms causing a dysregulation of urinary miRNAs in patients with acute rejection could not be provided. Levels of urinary miRNAs and the change of tissue expression or the release of the miRNAs by circulating cells might have been influenced by different parameters. In addition, it has been shown that cellular stressors may affect the expression of the enzyme dicer which is essential for the biogenesis of mature miRNAs (21). Thus, a modulation of the miRNA processing apparatus might also have affected the dysregulation of urinary miRNAs. Experimental studies are warranted to further elucidate the mechanisms, by which the development of acute rejection induces or prevents the release of urinary miRNAs by kidney tissue and/or circulating cells.

In conclusion, this study provides first insights into the levels of urinary miRNAs in kidney transplant patients with acute rejection. An array of urinary miRNAs can be reliably detected in this patient cohort. We identified miR-210 as a reliable marker of acute rejection and predictor of long-term graft function. However, prospective data from larger cohorts to validate our single-center study are warranted.

Acknowledgments

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. Disclosure
  9. References

We acknowledge the support of the Deutsche Forschungsgemeinschaft (DFG LO 1736/1-1 to J.L. and T.T.), a grant of the Integrated Research Center Transplantation by the German Federal Ministry of Education and Research (01EO0802 to T.T.).

Disclosure

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. Disclosure
  9. References

The authors of this manuscript have no conflicts of interest to disclose as described by the American Journal of Transplantation.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. Disclosure
  9. References