High Expression of FOXP3 mRNA in Blood and Urine as a Predictive Marker in Kidney Transplantation

Abstract

Background:

Diagnosis of allograft dysfunction by noninvasive biomarker tests is preferable to invasive allograft biopsies and has been extensively considered in recent years. This study aims to evaluate blood and urinary forkhead box P3 (FOXP3) messenger RNA (mRNA) expression in renal transplant recipients in an attempt to determine whether differential diagnosis of graft dysfunction is feasible using mRNA profiles.

Methods:

We analyzed FOXP3 mRNA expression in paired urinary and peripheral blood mononuclear cell (PBMC) samples. A total of 91 kidney transplant recipients enrolled in this study that were classified into 3 groups: biopsy-proven acute rejection (AR; n = 27), chronic allograft nephropathy (n = 19), and well-functioning graft (n = 45). The FOXP3 mRNA expression was quantified by TaqMan probe real-time polymerase chain reaction.

Results:

Acute rejection patients had a higher expression level of transcription factor FOXP3 compared to the chronic nephropathy and control groups. Analysis of receiver operating characteristic curves showed that rejection could be diagnosed with 100% sensitivity and 96% specificity in urine, and 92% sensitivity and 86% specificity in PBMC samples using the optimal FOXP3 mRNA cutoff value. We subdivided the AR group into progressive and nonprogressive patients, which showed a significant difference in FOXP3 mRNA expression. This result confirmed the role of FOXP3 as a diagnostic marker in predicting transplantation outcomes.

Conclusion:

Our results suggested that elevated expression of FOXP3 in blood and urine samples from kidney transplant recipients could be a useful noninvasive biomarker to diagnose graft dysfunction.

Keywords

FOXP3 expression urine blood kidney transplantation

Introduction

Kidney transplantation is the best therapeutic option for end-stage renal failure.¹ Occurrence of acute rejection (AR) remains a major cause of chronic allograft nephropathy (CAN) and graft loss.^2,3 In recent years, the appearance of immunosuppressive therapy has reduced the incidence of AR in transplant recipients; however, long-term immunosuppression affects allograft survival and results in nephrotoxicity.^4
–6 Early diagnosis of AR helps to prevent irreversible damage to the graft. The gold standard diagnostic method to determine episodes of rejection is the needle biopsy. However, needle biopsies identify the injury at relatively late stages and is not a favorably accepted method by patients.⁷ Needle biopsy results often lead to a wide range of discrepancies among pathologist reports.⁸ Therefore, development of a replacement diagnostic assay is of paramount importance. A number of gene expression studies have been conducted to find an accurate noninvasive diagnostic marker that predicts acute and chronic rejection in kidney allograft recipients.^9

–13

T regulatory (Treg; CD4⁺CD25⁺FOXP3⁺) cells are naturally derived from the thymus. These cells are critically important in suppressing alloimmune responses and maintenance of transplantation tolerance.^14,15 The potential role of these Treg cells in organ transplantation and cell therapy is often evaluated by FOXP3, a forkhead-winged helix, which is the master gene required for their suppressive function.¹⁶ This transcription factor binds to DNA via a domain called forkhead box,¹⁷ and its mutation results in autoimmunity in humans (immunodysregulation polyendocrinopathy enteropathy X-linked) and mice (scurfy phenotype).^18

–21 Although FOXP3 is expressed in CD8⁺ and CD4⁺ T cells, it mainly expresses in CD4⁺CD25⁺ T suppressor cells, which consist of 5% to 10% of total T cells.²² Transfection of FOXP3 gene into naive T cells leads to the production of Treg, induction of tolerance, and graft acceptance in organ transplant experimental models that highlights the immunomodulatory role of this gene.²³

Objective

Several human studies have been conducted on forkhead box P3 (FOXP3) messenger RNA (mRNA) expression as a predictive marker for transplantation rejection. However, the discrepancies in results obtained from these clinical studies encouraged us to clarify this ambiguity. In the present study, we investigated whether the FOXP3 mRNA expression level in renal transplant peripheral blood mononuclear cells (PBMCs) and urinary cells could be used as an immunological tool in the prediction of graft outcome.

Materials and Methods

Patients

In this cross-sectional cohort study, we investigated the urine (50 mL) and blood (5 mL) samples collected from 91 sequential, nonrandomized, primary kidney transplant recipients who had undergone either a clinically indicated kidney allograft biopsy or protocol follow-up biopsy at Labbafi Nejad Hospital during October 2013 to September 2015. Eligible recipients had a baseline serum creatinine less than or equal to 2.0 mg/dL with subsequent deterioration of graft function resulting in an allograft biopsy.

According to the 2013 update of the Banff classification criteria, we classified the patients into 2 groups, biopsy-proven AR (n = 27) and CAN with interstitial fibrosis and tubular atrophy (grades II, III; n = 19). A single pathologist performed histological examinations of the biopsy specimens. None of the patients had been diagnosed with infectious diseases at the time of biopsy.

The control group comprised 45 renal transplant patients who had clinically well-functioning grafts (WFGs) with no clinical symptoms of increased serum creatinine or decreased glomerular-filtration rate at least 18 months after transplantation, no registered history of AR episodes and diagnosed viral or bacterial infectious disease within 1 month before enrollment.

All participants received the same immunosuppressant regimen, adjusted conventional triple drug therapy that consisted of cyclosporine A or tacrolimus, mycophenolate mofetil or azathioprine, and methylprednisone as the steroid. None of the patients from either group received antibody induction therapy.

RNA Extraction and Complementary DNA Synthesis

Patients provided peripheral blood (5 mL that contained EDTA as the anticoagulant) and urine (50 mL midstream) samples at the time of renal allograft biopsy. The PBMCs were isolated within an hour by Ficoll-Hypaque density gradient centrifugation (Inno-Train, Frankfort, Germany) according to the manufacturer’s instructions. Urine samples (50 mL) were centrifuged at 10 000 rpm for 30 minutes at 4°C. The supernatant was discarded, after which we added freezing media that consisted of a 9:1 ration of fetal bovine serum (Ambion, Inc., New York, NYC2012, Inc., United States) + dimethyl sulfoxide (Sigma) to the pellet, which was stored at −80°C. The RNA was extracted from PBMCs with the (the MirVanaTM miRNA Isolation Kit (cat n#AM1560, ABI, USA) according to the manufacturer’s instructions. The concentration and quality were determined by spectrophotometry using a NanoDrop device (NanoDrop 2000c, Boston, New York, USA, thermo scientific). The complementary DNA (cDNA) synthesis was performed according to the High-Capacity cDNA Reverse Transcription Kit (4374966; ABI) manufacturer’s instructions.

Real-Time Polymerase Chain Reaction

FOXP3 mRNA (assay ID: Hs01085834_m1) expression level was measured using TaqMan Gene Expression Assay, and 18srRNA (assay ID: Hs01554355_m1) was used as the endogenous control to normalize the data. The quantitative real-time polymerase chain reaction (RT-PCR) was performed in duplicate using an optical 96-well plate Applied Biosystem (Foster city, California, USA) StepOnePlus system. The PCR amplification conditions included 2 minutes initial incubation at 50°C, 10 minutes denaturation at 95°C followed by heating at 95°C for 15 seconds and 60°C for 60 seconds repeated for 40 cycles. Each 20-µL reaction contained 10 µL TaqMan Universal PCR Master Mix, 1 µL TaqMan Gene Expression Assay, and 2 µL cDNA template (minimum 1:15 dilution). TaqMan primers and probes (single tube TaqMan Gene Expression Assay; ABI) for FOXP3 were used according to the manufacturer’s instructions. Relative mRNA expression level was calculated using the comparative threshold cycle method using Applied Biosystem, StepOne Software version 2.1. Analyses of amplified products were performed by the relative quantification method 2^−ΔΔCT.

Statistical Analysis

Results were presented as mean (standard deviation [SD]). The box plots were provided to illustrate the data distribution more appropriately. We used the χ² or Fisher exact tests to compare categorical variables between groups and robust analysis of variance to assess differences among the groups of variables that had normal distribution. The Mann-Whitney test was used for comparison between the 2 non-normally distributed groups (reversible and irreversible) and Tukey post hoc comparison for evaluation of the intragroup differences. Optimal diagnostic cutoff values were searched with receiver operating characteristics curve analysis and calculated according to the Youden Index to choose the optimal cutoff associated with the best specificity. The Pearson correlation coefficient was used to explore the linear correlation between variables. All statistical tests were performed with SPSS version 19 (IMB Corp, Armonk, New York) with 2 tailed with a P value <.05 considered statistically significant.

Results

Tables 1 and 2 summarize patients’ demographics and biochemical data. Patients were grouped by presence of AR, presence of CAN, and WFG. The mean age was 36.2 (12.6) years (AR), 45.5 (9.2) years (CAN), and 41 (12.9) years (WFG; P = .038). The majority of patients were male (63.7%) with an overall mean age of 22 years. A total of 15 (16.48%) patients received deceased donor transplants and 76 (83.51%) received living donor transplants.

Table 1.

Demographic Characteristics of Renal Transplant Patients.^a

Parameters	Acute Rejection Group (n = 27)	Chronic Allograft Nephropathy Group (n = 19)	Well-Functioning Group (n = 45)	P Value
Age (years), mean (SD)	36.2 (12.6)	45.5 (9.2)	41 (12.9)	.038
Male (%)	18 (66.65)	13 (68.4)	25 (55.55)	NS
Time posttransplant (months), mean (SD)	14 (14.5)	14 (17.45)	16 (13.87)
Regraft	1	2	–
Donor source, n (%)
Deceased donor	3 (11.11)	3 (15.7)	9 (20)	.136
Living unrelated	20 (74.07)	12 (63.15)	31 (68.88)	.121
Living related	4 (14.81)	4 (21.05)	5 (11.11)	.805
Cause of ESRD, n (%)
Hypertensive nephropathy	8 (29.6)	3 (15.75)	7 (15.55)
Diabetic nephropathy	3 (11.1)	2 (10.52)	4 (8.9)
Chronic glomerulonephritis	2 (7.4)	4 (21)	12 (26.65)
Others	14 (51.85)	10 (52.6)	22 (48.9)

Abbreviations: PRA, panel reactive antibody; ESRD, end stage renal disease; SD, standard deviation.

^aPRA levels for all recipients in 2 groups were between 0.0% and10.0% before transplantation.

Table 2.

Clinical and Biochemical Data of Acute Rejection, Chronic Allograph Nephropathy, and Well-Functioning Groups.

Parameters	Acute Rejection (n = 27)	Chronic Allograft Nephropathy (n = 19)	Well-Functioning Group (Control) (n = 45)
Parameters	Mean (SD)
Creatinine (mg/dL)	3.04 (2.45)^a	2.53 (1.44)^b	1.21 (0.57)^ab
Glomerular filtration rate (MDRD) (mL/min)	36.2 (20.98)^a	32.73 (13.73)^b	85.83 (21.16)^ab
Blood urea nitrogen	41.04 (23.55)^a	45.36 (21.50)^b	29.97 (10.97)^ab
Uric acid	6.14 (1.8)^a	6.71 (1.75)^b	5.08 (1.44)^ab
Fast blood sugar (mg/dL)	85.96 (26.56)^c	117.21 (59.18)^c	105.42 (37.44)
Aspartate aminotransferase	19.12 (7.44)	19.36 (8.22)	17.57 (4.83)
Alanine aminotransferase	21.16 (13.50)	23.10 (18.86)	20.44 (12.42)
Alkaline phosphatase	183.91 (88)	212.84 (119.19)^b	114.92 (51.36)^b
Calcium (Ca⁺²)	9.28 (0.71)	8.9 (0.73)^b	9.29 (0.35)^b
Sodium (Na⁺¹)	139.29 (4.6)	138.42 (6.10)	140.35 (3.01)
Potassium (K⁺)	6.32 (9.5)	4.44 (0.41)	4.45 (0.34)
Hemoglobin (g/dL)	11.53 (2.19)^a	10.92 (1.74)^b	12.81 (0.66)^ab
Hematocrit	33.62 (6.48)^a	32.91 (4.81)^b	38.92 (2.26)^ab
Leukocytes (×10³/µL)	8.5 (3.7)	14.4 (2.4)	9.9 (1.4)
Erythrocytes (×10⁶/µL)	4.04 (0.73)	4.17 (0.76)	4.3 (0.49)

Abbreviations: AR, acute rejection; CAN, chronic allograph nephropathy; MDRD, modification of diet in renal disease, WFG, well-functioning groups.

^a P < .05 for AR versus WFG.

^b P < .05 for CAN versus WFG.

^c P < .05 for AR versus CAN.

At the time of biopsy, patients in the AR group had a mean creatinine level of 3.04 (2.45), whereas those in the CAN group had a mean level of 2.53 (1.44). The WFG had a mean creatinine level of 1.21 (0.57; P < .01). No statistically significant differences existed in time intervals between the transplantation and biopsy time in the AR and CAN groups.

We observed significantly greater relative FOXP3 mRNA expression (fold change) in AR patients compared to CAN and WFG patients. As seen in Figure 1A, mean FOXP3 expression in PBMC samples was 4.31 (1.09; AR), 2.71 (1.43; CAN), and 1.23 (0.91; WFG; P < .01). In urinary cells, the mean FOXP3 expression was 4.75 (2.04; AR), 1.37 (1.06; CAN), and 1.09 (0.6; WFG; P < .001; Figure 1B).

We subdivided the AR patients into 2 groups based on reduction of serum creatinine levels within 2 weeks after needle biopsies. The nonprogressive group included patients with at least a 15% reversal in their creatinine serum levels during 2 weeks after needle biopsy. Patients in this group showed more effective response to antirejection therapy.

Nonprogressive AR patients had significantly greater relative FOXP3 mRNA expression (fold change) compared to progressive AR patients. In urinary cells, the mean FOXP3 expressions were 2.45 (1.6; progressive) and 5.85 (1.58; nonprogressive) as seen in Figure 2A. In PBMCs, the mean FOXP3 expressions were 2.75 (1.05; progressive) and 6.40 (1.45; nonprogressive) as seen in Figure 2B.

Receiver Operating Characteristics Curve Analysis of mRNA Levels in PBMCs and Urinary Cells

We performed receiver operating characteristics curve analysis for FOXP3 mRNA levels as a predictor of rejection reversal to show the diagnostic value of FOXP3 mRNA in distinguishing progressive from nonprogressive rejection (Figure 3). The fraction of true positive (sensitivity) and false positive (specificity) results for cutoff point of FOXP3 mRNA levels is shown in Table 3. The calculated area under the curve was 0.91 for PBMC FOXP3 mRNA levels (95% confidence interval [CI]: 0.85-0.97; P < .01) and 0.94 for the urine FOXP3 mRNA levels (95% CI: 0.87-1; P < .01). The relative expression level of FOXP3 that gave the maximal sensitivity and specificity for an association with AR rejection in PBMCs was 66.5. At this threshold, the test had a sensitivity of 92% and specificity of 86%. The relative expression level of FOXP3 that gave the maximal sensitivity and specificity for an association with AR rejection in urinary cells was 62.86, with a sensitivity of 100% and 96% specificity (Figure 3; Table 3).

Table 3.

Predictive Properties of FOXP3 in Peripheral Blood Mononuclear Cells and Urine Samples in AR Cases.

Specimen	Sensitivity (%)	Specificity (%)	AUC (95% CI)	P Value
PBMCs	92	86	0.91 (0.85-0.97)	.001
Urine	100	96	0.94 (0.87-1.00)	.001

Abbreviations: AUC, area under curve; CI, confidence interval; PBMC, peripheral blood mononuclear cells.

There were significantly higher mRNA levels (95% CI) in both samples in AR patients compared to CAN and WFG patients. A comparison between CAN and WFG showed no significant difference.

Correlation Between FOXP3 mRNA Levels in Blood, Urine, and Serum Creatinine

The FOXP3 mRNA expression significantly correlated in urinary sediments and PBMCs (r = 0.768; P = .000; Figure 4). An inverse correlation was reported between the levels of FOXP3 mRNA and serum creatinine during an episode of AR in blood (Spearman correlation coefficient r = −.59, P = .01) and urine (r = −.46, P = .01). But correlation between the levels of FOXP3 mRNA and serum creatinine in the CAN (blood: r = .13, P = .58; urine: r = .38, P = .1) or WFG patients (blood: r = .14, P = .35; urine: r = .09, P = .55) was not reported as significant. Furthermore, the mean (standard error) serum creatinine level in the progressive AR (3.01 [0.5] mg per deciliter) did not differ significantly from nonprogressive AR (2.9 [0.4] mg per deciliter, P = .64).

Discussion

Early posttransplant immune monitoring predicts long-term outcomes for kidney allografts but also can be used to identify patients at high risk for AR. This will lead to personalized immunosuppressive therapy, improved long-term graft function, and graft survival. In order to achieve this goal of clinical transplantation, it is necessary to define reliable predictive biomarkers, particularly immune markers that can determine the outcomes of kidney allografts in transplant recipients.

The majority of previous studies on FOXP3 mRNA expression, as a specific transcription factor in Tregs, have been associated with the clinical outcome of transplantation.^24,25 Various studies^26
–28 reported a pivotal role of CD4⁺CD25⁺ T cells (Treg) in solid organ transplantation.

In a cohort study on 57 renal transplant patients, we showed that Treg cells decreased 2 weeks after transplantation. This early reduction could be attributed to high-dose administration of immunosuppressive therapy. After 2 weeks, with reduction in immunosuppressive drugs, we observed a clear increasing trend in Treg levels. This observation indicated that the number of Tregs could be modulated by the immunosuppressive regimen. Additionally, CD4⁺CD25⁺FOXP3⁺ cells recovered within 6 months after transplantation. This recovery might play a critical role in graft stability.²⁹

It is likely that during AR, elevated FOXP3 mRNA in PBMCs and urinary cells result from the development of a graft protective response against the activated alloimmune T cells by recruitment of FOXP3 Treg cells.^30,31 Muthukumar et al reported increased FOXP3 mRNA expression levels in urine cell pellets of AR patients compared with the control group, which confirmed its correlation with the allograft outcome.³² A cohort study on lung transplant recipients (n = 20) demonstrated a higher percentage of bronchoalveolar lavage CD4⁺FOXP3⁺ cells in nonprogressive AR patients compared with progressive group (P < .01).²⁶ In another study on liver transplant recipients, a lower circulating CD4⁺CD25^high FOXP3⁺ T cells was reported in AR compared with the nonrejection group (P < .01).²⁷ Our previous cohort study showed that FOXP3 mRNA levels decreased in patients who underwent acute posttransplantation rejection.³³ In the present study, we observed significantly lower FOXP3 mRNA expression in patients with progressive rejection compared to those with nonprogressive rejection. This finding is in line with the results from the study conducted by Abd Elaziz et al, in which program death-1 and FOXP3 mRNA expression showed a significant increase in the AR patients compared with stable graft recipients. But only FOXP3 was able to show the rejection outcome.³⁴ Possibly, elevated FOXP3 mRNA expression in PBMC and urine samples was not only valuable for prediction of an AR episode but also distinguished progressive from nonprogressive AR episodes.

The FOXP3⁺ Treg cells in CAN patients are recruited toward the transplant graft as a part of the inflammatory allogeneic response.³⁵ Bestard et al demonstrated that FOXP3 gene expression in the renal graft was a proper predictor of graft function.³⁶ Yapici et al and Bunnag et al investigated intragraft FOXP3 expression. They observed an association with interstitial fibrosis tubular atrophy and longer time posttransplant nephropathy, yet the association with therapy response remained unclear.^37,38 Based on our findings, the pattern of FOXP3 gene expression in CAN patients differed from AR patients. This difference probably originated from a reduction of blood Tregs in CAN patients due to their improved homing to their appropriate organ or tissue as well as their selective traffic into the transplant microenvironment.^38,39

Veronese et al reported a negative association between the amount of FOXP3 cells in various groups of renal transplant recipients.⁴⁰ Recent studies demonstrated that the number of FOXP3⁺ cells did not correlate with borderline or AR episodes of graft survival.^31,37,40 In our previous study of chronic allograft dysfunction, we reported a lower frequency of CD4⁺CD25⁺CD127⁻ T cells in CAN compared with the stable graft patients.⁴¹

There are discrepancies in the FOXP3 mRNA levels among different studies. These challenges could stem from the nature of RT-PCR method as a quantitative technique in measuring the gene expression level. Although RT-PCR is an extremely sensitive and high-speed method to measure the mRNA expression level, variation in results of the same measurement may happen due to the sample size, storage, and transportation; inhibitory compounds in the body fluids; liability of RNA; using various real-time enzymes or different classes of oligonucleotides; and interlaboratory variabilities in developing the assay or the statistical methods used for data analysis.^39, ⁴² Therefore, experimental design of confirmative techniques may help improve the validity of RT-PCR. Further studies are necessary to evaluate whether the numbers of FOXP3⁺ Tregs can provide a more accurate result in support of gene expression analysis. In addition, most T cells transiently express FOXP3 mRNA during their early activation stages, and the expression of methylated FOXP3 in activated nonregulatory T cells adds ambiguity to the results of gene expression analysis.⁴³

The findings of this study reveals that the quantitative analysis of FOXP3 mRNA in patients with AR in peripheral blood leukocytes and urine-sediment cells provides a reassuring molecular pattern to predict the transplantation outcome which may be employed as a replacement for surveillance biopsy. In the current study, we faced with time limitation and the limited access to a larger sample size to improve the reliability and power of our evaluations. Since organ transplantation adversely affects the immune system, relying on a single biomarker doesn’t reveal the transplantation outcome. Therefore, a panel of several biomarkers will help evaluate the immune system alterations and administration of personalized medicine. Further evidence would be provided by the means of multicentered studies.

Conclusion

Alterations in FOXP3 mRNA expression significantly correlated with kidney allograft outcome. From the results of the present study data, we suggest that determination and monitoring of FOXP3 mRNA in PBMCs and urine, as noninvasive samples, would be a valuable tool to predict kidney allograft outcome.

Footnotes

Acknowledgments

The authors thank all staff members of the transplantation ward in Labbafi Nejad Hospital for their excellent assistance for providing clinical data and samples from all patients.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by a grant (NO: 24285) from Tehran University of Medical Sciences, Research Deputy, Tehran, Iran.

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