Vol.1, No.3, 87-96 (2011)
doi:10.4236/oji.2011.13011
C
opyright © 2011 SciRes. Openly accessible at http://www.scirp.org/journal/oji/
Open Journal of Immunology
Urine immune profiling by measurement of multiple
cytokine/chemokine mRNA levels in renal allograft
dysfunction
Rubina Naqvi1*, Salma Batool Jafri2, Zahabia Imani2, Mohammad Mubarak3, Rana Muzaffar2
1Department of Nephrology, Sindh Institute of Urology and Transplantation (SIUT), Karachi, Pakistan; *Corresponding Author:
rubinanaqvi@gmail.com
2Department of Molecular Biology, Sindh Institute of Urology and Transplantation (SIUT), Karachi, Pakistan;
3Department of Pathology, Sindh Institute of Urology and Transplantation (SIUT), Karachi, Pakistan.
Received 3 August 2011; revised 18 October 2011; accepted 10 November 2011.
ABSTRACT
Background: An accurate diagnosis of cause of
acute renal graft dysfunction is crucial for the
optimal management of transplant recipients.
Currently available test s are either insensi tive or
nonspecific, or are invasive, such as allograft
biopsy. During last decade, attempts have been
made in search of non invasive markers for the
evaluation of cause of graft dysfunction. We
studied a set of genes expressed on cytotoxic T
Lymphocytes and those related to functioning
of regulatory or helper T cells. Methods: We
obtained 108 urine samples from 108 renal al-
lograft recipients at the time of graft biopsy
done for the evaluation of cause of graft dys-
function. RNA was extracted from urinary cells
and messenger RNA (mRNA) encoding perforin,
granzyme B (GB), FoxP3, CD3, CXCR3, TGF-
,
CTLA4, PI-9, IL-10, TNF
, T-bet and 18SrRNA
measured with the use of quantitative real time
polymerase chain reaction (RT-PCR). The levels
of expression of genes were correlated with the
biop sy findings and the results comp ared among
different groups. Renal allograft biopsies at this
institution are performed when there is unex-
plained rise in serum creatinine of >20% from
the baseline value and reported according to
Banff classification. SPSS v10.0 used for analy-
sis.Results: The mRNA copy numbers of GB,
Perforin, FoxP3, CD3, CXCR3, TGF-
, CTL A4,
PI9, IL-10, TNF
, and T-bet were log transformed
and mean (± SD) levels studied. The expression
of all studied genes were compared between
‘nonspecific biopsy findings’ and other specific
diagnoses. GB, Perforin, FoxP3, TGF-
, CD3,
CTLA4 CXCR3 and T-bet were higher in acute
cellular rejection (ACR), whereas, TGF- was
also found higher in infection, and PI-9 in chro-
nic allograft nephropathy (CAN) and borderline
rejection group. Conclusion: Measurement of
mRNA levels for genes like GB, Perforin, FoxP3,
TGF-β, CD3, CTLA4, CXCR3 and T-bet in urine
samples offers a non invasive means of diag-
nosing cause of graft dysfunction.
Keywords: Renal Allograft Dysfunction; Reje ction;
Cytokines; Chemokines
1. INTRODUCTION
Acute graft dysfunction remains a major impediment
in the successful long-term graft and patient survival in
the setting of renal transplantation. Although graft bi-
opsy is still considered the ‘gold standard’ in the diagno-
sis of graft dysfunction, it has its limitations. Associated
risks like procedure related complications could restrict
its routine application in a live related donor transplant
program. Therefore, the development of sensitive and
specific non-invasive diagnostic tools has been a major
area of interest in the field of transplantation [1]. En-
hanced mRNA expression of several cytokine and che-
mokine genes in urinary cells is shown to be associated
with acute graft rejection [2-14]. Reverse transcriptase-
real time PCR (RT-real time PCR) permits detection and
accurate quantitation of high and low abundant mRNA [8].
Expression of cytotoxic T lymphocyte activation markers
including GB, Perforin, integrins such as CD 103, key
chemokine inducible protein of 10kD (IP-10) and its re-
ceptor CXCR3 have been shown to be associated with
allograft rejection [15-17]. PI-9, an endogenous blocker of
GB/Perforin pathway is also implicated in the rejection
pathway.[18] Several studies have also highlighted the role
of specialized subgroup of CD4+, CD25+ T lymphocytes
R. Naqvi et al. / Open Journal of Immunology 1 (2011) 87-96
Copyright © 2011 SciRes. Openly accessible at http://www.scirp.org/journal/oji/
88
(Treg cells) and X-linked forkhead/ winged helix tran-
scription factor, Fox P3 [13,19-21]. IL-10, required for
the generation of, and suppressor function of Tregs, tu-
mor necrosis factor-
(TNF-
), known to play an essen-
tial role in mediating inflammatory process, and profi-
brotic cytokine, TGF-
, are also reported to be involved
in graft dysfunction [13,22-26]. Development of CD4
effector T cells into T helper 1 (TH1) is regulated by
T-bet (T-box expressed in T cells; also known as Tbx-21)
which positively regulates its own expression [27-30].
CTLA4 is an important T cell downregulatory molecule
that is required for induction of peripheral tolerance in a
number of models. It is primarily expressed as an intra-
cellular molecule that cycles to the cell surface where it
can then interact with B7 counter-ligands (CD 80 and
CD 86) on antigen presenting cells [31]. CTLA 4 expres-
sion is up-regulated by T cell activation, which normally
requires signals through both the TCR and the CD 28
co-stimulatory pathways [32]. The availability of sensi-
tive and specific non-invasive tests for diagnosing the
causes of graft dysfunction remains the ultimate need of
transplant physicians, especially in the setting of live
related transplantation. In the present study, we set out to
determine the utility of urinary cytokine/chemokine
mRNA levels as a noninvasive diagnostic tool in our
transplant recipients, where organ source is from live
related donors.
2. MATERIAL AND METHODS
2.1. Study Structure
The study comprised of 108 urine samples from 108
patients who received living related donor kidneys and
underwent renal allograft biopsy for determining the
causes of graft dysfunction (>20% rise in serum create-
nine from base line). Biopsies were reported and graded
according to the Banff 97 classification [33]. All patients
reported as ACR were given pulse steroids as anti rejec-
tion therapy, whereas, antithymocyte globulin (ATG)
was the drug used in cases of vascular rejection and for
steroid resistant ACR. Urine samples were collected just
before the biopsy procedure on the day the biopsy was
performed. The Ethical Review Committee at SIUT ap-
proved the study. Written informed consent was obtained
from all the participants in the study.
2.2. Extraction of Total RNA from Urinary
Cells and CDNA Synthesis
The cell pellets were obtained by centrifugation and
RNA was extracted and reverse transcribed according to
standard protocols. Briefly, urine specimens were cen-
trifuged at 3000 rpm for 30 min at 4˚C and washed with
chilled PBS (pH 7.4). Pellets were re-suspended in RNA
later (QIAGEN, GmbH, Germany), followed by storage
at –80˚C before RNA extraction. Total RNA was ex-
tracted using RNeasy Mini Kit (Qiagen, GmbH, Ger-
many) along with QIAshredder Spin Columns (Qiagen,
GmbH, Germany). RNA was eluted in 60µl RNase-free
water, its concentration and purity determined by OD260/
280 readings. Between 100 ng and 500 ng of RNA was
reverse-transcribed in a final reaction volume of 100 µl
using cDNA reverse transcription reagents (Applied
Biosystems Inc., Foster City, CA, USA). All urinary
samples yielded satisfactory quality and amount of RNA
for PCR amplification.
2.3. “Pre-Amplification” Polymerase Chain
Reaction (Pre-Amp PCR)
Multi-plex Pre-Amp PCRs were performed for 11 cy-
tokine molecules (FoxP3, CD3ε, GB, TGF-β1, IL-10,
PI-9, TNF-α, Perforin, CXCR 3, CTLA 4, T-bet)) and
18S rRNA (housekeeping gene) in 30 µl using 3 µl of
cDNA. The amplified products were stored at –20˚C
until real-time, quantitative PCR was performed. The se-
quences of primers and probes used in this study are
listed in Table 1.
2.4. Quantitative Real-Time PCR
In-house 18S rRNA standards were used to generate a
standard curve for measuring mRNA levels. Briefly, 18S
rRNA was reverse transcribed and amplified. The pres-
ence of a single PCR product was verified on a 3% aga-
rose gel. The amplified product was purified using Wiz-
ard SV Gel and PCR Clean-up kit (Promega Corp.,
Madison, WI, USA), quantified by spectrophotometry,
and copy numbers calculated.
A series of 10-fold dilutions ranging from 2.5 × 106 to
2.55 × 102 copies were used as standards in duplicates
with every run on ABI Prism SDS 7000 (ABI, Foster
City, CA, USA). PCR for each of the 11 cytokine gene
mRNAs and 18S rRNA was carried out in duplicates.
Every real time PCR run had its own 18S rRNA standard
curve to allow relative quantification of the cytokine
gene expressions.
2.5. Statistical Analysis of Data
Urinary cytokine mRNA copy numbers were log-tra-
nsformed before applying the Mann-Whitney test for
non-parametric data using SPSS v10.0 for Windows.
P-values < 0.05 were considered statistically significant.
Receiver-operating-characteristic (ROC) curve analysis
of normalized mRNA levels of all studied genes was
carried out to determine the cutoff points that yielded the
highest sensitivity and specificity in diagnosis of acute
cellular rejection (ACR).
R. Naqvi et al. / Open Journal of Immunology 1 (2011) 87-96
Copyright © 2011 SciRes. http://www.scirp.org/journal/oji/Openly accessible at
8989
Table 1. Primer and probe sequences of target genes [16,18,19].
Gene Accession no. Sequence location
GB BJ04071
Sense 5’-GCGAATCTGACTTACGCCATTATT-3’
Antisense 5’-CAAGAGGGCCTCCAGAGTCC-3’
Probe 5’-CCCACGCACAACTCAATGGTACTGTCG-3’
(534-557)
(638-619)
(559-585)
Perforin M28393
Sense 5’-GGACCAGTACAGCTTCAGCACTG-3’
Antisense 5’-AGTCAGGGTGCAGCGGG-3’
Probe 5’-TGCCGCTTCTACAGTTTCCATGTGGTACAC-3’
(492-514)
(577-561)
(526-555)
FoxP3 NM014009
Sense 5’-GAGAAGCTGAGTGCCATGCA-3’
Antisense 5’-GGAGCCCTTGTCGGATGAT-3’
Probe 5’-TGCCATTTTCCCAGCCAGGTGG-3’
(939-959)
(1025-1007)
(962-984)
CD3 NM000733
Sense 5’AAGAAATGGGTGGTATTACACAGACA-3’
Antisense 5’-TGCCATAGTATTTCAGATCCAGGAT-3’
Probe 5’-CCATCTCTGGAACCACAGTAATATTGACATGCC-3’
(131-156)
(233-209)
(170-202)
PI9 NM004155
Sense 5’-TCAACACCTGGGTCTCAAAAAA-3’
Antisense 5’-CAGCCTGGTTTCTGCATCAA-3’
Probe 5’-AGCTACCCGGCAACAACTCTTCAATTTTACCT-3’
(508-529)
(590-571)
(536-567)
CXCR3 NM00154
Sense 5’-ACCCAGCAGCCAGAGCAC-3’
Antisense 5’-CAACCTCGGCGTCATTTAGC-3’
Probe 5’-CTTGGTGGTCACTCACCTCAAGGACCAT-3’
(41-58)
(117-98)
(69-96)
IL10 XM001409
Sense 5’-AGGCTACGGCGCTGTCAT-3’
Antisense 5’-GGCATTCTTCACCTGCTCCA-3’
Probe 5’-CTTCCCTGTGAAAACAAGAGCAAGGCC-3’
(394-411)
(465-446)
(418-444)
TGF
NM000660
Sense 5’-CCCTGCCCCTACATTTGGAG-3’
Antisense 5’-CCGGGTTATGCTGGTTGTACA-3’
Probe 5’-CACGCAGTACAGCAAGGTCCTGGCC-3’
(1821-1831)
(1884-1864)
(1838-1862)
TNF
XM165823
Sense 5’-CCCAGGCAGTCAGATCATCTTC-3’
Antisense 5’-AGCTGCCCCTCAGCTTGA-3’
Probe 5’-CAAGCCTGTAGCCCATGTTGTAGCAAACC-3’
(302-323)
(386-368)
(339-367)
CTLA4* BC074893
Sense 5’-CGCCATACTACCTGGGCATAG-3’
Antisense 5’-GATCCAGAGGAGGAAGTCAGAATC-3’
Probe 5’-ACCCAGATTTATGTAATTGATCCAGAACCGTGC-3’
(441-461)
(579-556)
(470-502)
Tbet** BC039739
Sense 5’-GCCTACCAGAATGCCGAGATTA-3’
Antisense 5’-TCAAAGTTCTCCCGGAATCCT-3’
Probe 5’-TCAGCTGAAAATTGATAATAACCCCTTTGCCA-3’
(1086-1107)
(1162-1141)
(1109-1140
18SrRNA K03432
Sense 5’-GCCCGAAGCGTTTACTTTGA-3’
Antisense 5’-TCCATTATTCCTAGCTGCGGTATC-3’
Probe 5’-AAAGCAGGCCCGAGCCGCC-3’
(929-948)
(1009-985)
(965-983)
*,**—not published yet, designed with help of Dr. R. Ding while working at Cornell Molecular Lab. Permission granted for use of all primers and probes sequ-
ences from Dr. Suthanthiran
3. RESULTS
The 108 urine samples were collected from 108 pa-
tients at the time of graft dysfunction, defined as 20%
rise in serum creatinine from the baseline value, on the
same day that the graft biopsy was performed. The uri-
nary samples were analyzed for gene expression and
correlated with biopsy findings. The relevant demo-
graphic, clinical and laboratory characteristics of pa-
tients included in the study are summarized in Table 2.
3.1. Cytokine/Chemokine mRNA Levels in
Urinary Cells
The levels of mRNA and 18SrRNA were log trans-
formed for analysis. Since minimum variability (9.8
0.20) was seen for 18S rRNA copy numbers, normaliza-
tion of mRNA levels was not carried out. The levels of
mRNA in ACR (IA,IB), AVR (IIA,IIB,III), borderline
rejection, CAN, and infection diagnoses were compared
with “mild nonspecific” biopsy findings Figure 1 and
Table 3.
AVR: GB, perforin, FoxP3, TGF-
, CTLA4 and CXC
R3 mRNA levels also showed significant increase in
expression, whereas, PI-9, TNF-
, IL-10 and T-bet lev-
els showed no significant increase in copy numbers.
Borderline Rejection: No significant increase in ex-
pression of studied genes was observed in this group.
Chronic allograft nephropathy (CAN): Highly significant
R. Naqvi et al. / Open Journal of Immunology 1 (2011) 87-96
Copyright © 2011 SciRes. Openly accessible at http://www.scirp.org/journal/oji/
90
Table 2. Patient Characteristics in different groups.
ACR (IA, IB)
(n = 40)
Infection
(n = 17)
CAN
(n = 17)
AVR (IIA,
IIB,III) (n = 7)
Border line
Rejection (n = 5)
Normal (Mild nonspe-
cific changes) (n = 22)
Recipient Age in years
(mean SD) 27 ± 8.2 29 ± 8 22 ± 8 23 ± 7 28 ± 8 26 ± 7
Recipient Sex (M:F) 35:5 14:3 13:4 7:0 4:1 22:0
Duration on Dialysis
in months (mean SD) 7.5 ± 15 9.2 ± 22 10.8 ± 14.7 8.7 12.3 6 ± 6.75 6 ± 7.3
Donor Age in years
(mean SD) 34 ± 9.8 36 ± 8 36 ± 7 42 9 41 ± 11 33 ± 9
Donor Sex (M:F) 13:27 8:9 4:13 2:5 2:3 10:12
HLA Match
Identical 2 1 1 1 0 3
1 H 30 13 13 6 3 16
<1 H 8 3 3 0 2 3
Ischaemia Tim e in
min.(mean SD) 141 ± 42 144 ± 33 158 ± 37 126 ± 22 144 ± 33 146 ± 57
Best Creatinine mg/dl
(mean SD) 1.3 ± 0.23 1.3 ± 0.29 0.9 ± 0.34 1.3 ± 0.41 1.3 ± 0.12 1.2 0.23
Maintenance
Immunosuppression
CyA, Aza, Pred 26 12 13 5 3 17
Tac, MMF, Pred 7 3 3 0 1 3
CyA, MMF, Pred 6 2 1 2 1 2
Tac, Aza, Pred 1 0 0 0 0 0
eGFR (mean SD)
At 1 month 45 ± 11 41 ± 9 51 ± 15 44 ± 11 41 ± 11 51 ± 12
At 3 months 47 ± 11 38 ± 13 48 ± 18 37 ± 6 32 ± 8 47 ± 12
At 6 months 46 ± 12 41 ± 11 46 ± 19 39 ± 13 38 ± 11 52 ± 10
Time of biopsy after
Tx in days (mean ± SD) 31 ± 71 37 ± 42 509 ± 708 16 ± 25 45 ± 40 41 ± 33
1H = one haplotype, CyA = cyclosporin, Tac = tacogen, Aza = azathiaprine, MMF = mycophenolate mofetil, Pred = prednisolone, Tx = transplant; eGFR (for
male) {1.23(140-age) xwt(kg)/s.cr}/100, for female {1.04(140-age) xwt(kg)/s.cr}/100.
Table 3. Comparison of mRNA levels in different biopsy groups with those classified as “Normala”.
p-valuesb
GENE ACRc (N = 40) Infection (N = 17) CANd (N = 17) AVRe (N = 7) Borderline (N = 5)
GB 0.000 0.087 0.325 0.001 0.606
Perforin 0.000 0.279 0.240 0.002 0.650
FoxP3 0.000 0.305 0.904 0.070 0.447
TGF-β 0.000 0.039 0.492 0.006 0.928
CD3ε 0.000 0.747 0.600 0.088 0.524
PI9 0.527 0.747 0.002 0.217 0.099
TNFα 0.193 0.457 0.229 0.258 0.377
IL-10 0.056 0.408 0.209 0.258 0.186
CTLA4 0.000 0.255 0.476 0.021 0.976
CXCR3 0.001 0.604 0.677 0.001 0.928
T-bet 0.012 0.834 0.459 0.122 0.928
a22 classified as normal biopsy findings (mild non specific changes); bP-values based on Fishers Exact Sig. [2*(1-tailed Sig.)]; cACR; Acute Cellular Rejection
(IA,IB); dCAN; Chronic Allograft Nephropathy; eAVR; Acute Vascular Rejection (IIA,IIB,III).
R. Naqvi et al. / Open Journal of Immunology 1 (2011) 87-96
Copyright © 2011 SciRes. Openly accessible at http://www.scirp.org/journal/oji/
9191
Box and whiskers plots show the 10th, 25th, 50th (median), 75th, and 90th percentile values for GB, Perforin, FoxP3, TGF-, CD3ε, PI9, TNF, IL-10,
CTLA4,CXCR3 and Tbet in urine samples from 40 ACR, 17 CAN, 17 bacterial infection, 7 AVR, 5 border line rejection and 22 patients with normal biopsy results.
Levels of mRNA for GB, Perforin, FoxP3, TGF-
, CD3ε, CTLA4, CXCR3, and T-bet were higher in ACR than in patients with normal biopsy findings. GB, Perforin,
TGF-
, CTLA4, and CXCR3 mRNA levels were also high in AVR. TGF- expression was also higher in infection, while PI9 levels were higher in CAN. P-values
are based on the Mann-Whitney test, with the log-transformed mRNA levels treated as the dependent variable. Outliers are marked as 0 on plots. Asterisks represent
extremes.ACR: We observed significant hyper expression of GB, perforin, FoxP3, TGF-
, CD3
, IL-10, CTLA4, CXCR3 and T-bet in this group.
Figure 1. Relative expression of mRNA transcripts in urinary cells after transplantation.
R. Naqvi et al. / Open Journal of Immunology 1 (2011) 87-96
Copyright © 2011 SciRes. http://www.scirp.org/journal/oji/
92
expression of PI-9 was observed in this group while sta-
ble mRNA levels were detected for other genes.
TNF-
showed 97.5% sensitivity and 98.6% specificity
at a cut off value of 3.42, though it has a p-value of 0.193
when compared with “mild nonspecific biopsy findings”
group Table 3 and Figure 2.
Infection: This patient group showed significant hyper
expression of TGF-
(P = 0.039) while rest were not
significant. 3.3. Comparison of Treatment Response vs.
No-Response in ACR
3.2. Receiver Operating Characteristic
(ROC) Curve Analysis Within the ACR group we compared those who
showed complete response to anti rejection therapy (26
out of 40) with those who showed no response (8 out of
40), (remaining six patients fell in category of partial
response). Using the Mann-Whitney test, we found in-
significant values for all genes in terms of prediction of
treatment response. (GB p = 0.869, perforin p = 0.796,
FoxP3 p = 0.760, TGF-
p = 0.944, CD3
p = 0.832, PI-9
p = 0.356, TNF-
p = 0.655, IL-10 p = 0.381, CTLA4 p =
0.494, CXCR3 p = 0.832 and T-bet p = 0.464)
The ROC curve shows the fraction of true positive
results (sensitivity) and false positive results (1-specifi-
city) for cut off values of log transformed mRNA copy
numbers. Perforin showed 97.5% sensitivity and 92.8%
1-specificity at a cut off value of 2.87. GB, Foxp3,
TGF-
, CD3
, PI-9, CTLA4, and CXCR3 also showed
sensitivity of 97.5%, but with specificity varying from
87%, 71%, 76.8%, 91.3%, 87%, 68.1%, and 94.2 % re-
spectively.
All these genes except PI-9 exhibited significant in-
crease in gene expression in comparison to “mild non-
specific biopsy findings group” Table 3. The IL-10
showed 95% sensitivity and 79.7% specificity at a cut
off value of 2.76, while a cut off value of 1.07 for T-bet
showed only 60% sensitivity and 36.2 % specificity. The
4. DISCUSSION
The results of present study clearly demonstrate signifi-
cantly increased expression of several cytokines and
chemokine genes in patients with biopsy findings of acute
rejection (AR). Urine samples in patients with ACR
Openly accessible at
R. Naqvi et al. / Open Journal of Immunology 1 (2011) 87-96
Copyright © 2011 SciRes. Openly accessible at http://www.scirp.org/journal/oji/
9393
The fraction of true positive results (sensitivity) and false positive results (1–specificity) for levels of mRNA for GB, Perforin, FoxP3, TGF-
, CD3ε, PI-9,
TNF
, IL-10, CTLA4,CXCR3 and T-bet as markers of ACR are shown. The calculated area under the curve is mentioned on the right corner. A value of 0.5 is
no better than that expected by chance (the null hypothesis), and a value of 1.0 reflects a perfect indicator. P-values are indicated on left upper corner.
Figure 2. Receiver-Operating Characteristic (ROC) Curves of mRNA Levels in Acute Cellular Rejection (ACR).
displayed strong expression of GB, Perforin, TGF-
,
FoxP3, CXCR3, CD3, T-bet and CTLA4. Cy- totoxic
T Lymphocytes (CTLs) protein activation re- ported
previously showed significant hyper-expression of GB
and perforin in the setting of AR [9]. Another study
which investigated association between enhanced uri-
nary gene expression and early AR, reported high uri-
nary CD3 and CTL granule associated molecule, granu-
lysin. Effector cytokines and cytotoxic molecules (IL-2,
IFN γ, IL-10, TNF-
, TGF-
, RANTES, GB, per- forin
and CCR1) were only marginally increased but were still
found within the upper range of 95% confi- dence inter-
val. Although researchers were able to predict AR with
many fold enhancement of CD3 and granulysin mRNA
expression, which was later proved on biopsy, yet serial
mRNA amplification for gene expression analysis was
found to be expensive and time consum- ing [11]. An-
other study also reported hyperexpression of GB, per-
forin and Fas-Ligand in biopsy samples as well as in
peripheral blood leukocytes, though in the later samples,
there was no statistically significant difference [10]. We
have not analyzed the genes in biopsy samples or pe-
ripheral blood as our aim was to investigate non invasive
markers for detecting the cause of graft dys- function.
FoxP3 gene expression is recognized as a predictive
marker of AR. Muthu et al. reported high levels of
FoxP3 mRNA in urinary cells as an independent predic-
tor of reversal of AR, but the authorswere uncertain
about the mechanisms of immunosuppression by Tregs,
cytokines signaling and inhibition of transcription of
genes central to effector functions in explanation of AR
response [19]. The hyper-expression of FoxP3 has also
been reported at the intra graft level in AR by using im-
munohistochemical method [21,34]. Mansour et al. re-
ported intra graft FoxP3 mRNA levels as predictor of
improved outcome in cases of borderline changes [36].
Elevated levels of FoxP3 in renal biopsy was also de-
tected by Bunnag et al., but no association of mRNA
levels with treatment response was seen [37]. In the pre-
sent study we also found high levels of FoxP3 mRNA in
ACR and AVR, but not in borderline rejection. We have
also not found any significant difference in AR groups
Note 1. Diagonal segments are pro-
duced by ties.
Note 2. Larger values of the test result
variable(s) indicate stronger evidence
for a positive actual state (ACR).
R. Naqvi et al. / Open Journal of Immunology 1 (2011) 87-96
Copyright © 2011 SciRes. Openly accessible at http://www.scirp.org/journal/oji/
94
who completely responded to anti rejection therapy,
versus those who had shown no response (p = 0.760).
This variation in results could possibly be explained by
the fact that FoxP3 binds promoters of over 700 genes
and has both activating and inhibitory activity [38].
Chemokines are members of a large family of chemo-
tactic cytokines, which play an important role in leuko-
cyte recirculation. CXCR3, which is a marker for T
helper cells type-1 is associated with inflammatory pro-
cess, its hyper-expression in renal allograft tissue has
been reported in AR [16,17]. We have also seen hy-
per-expression of CXCR3 in cases of acute cellular or
vascular rejection, whereas its hyper expression in cases
of infection or CAN was insignificant (Table 3).
Considering role of CTLs in AR, PI-9 expression was
also studied in setting of AR. As PI-9 can protect CTL
from its self induced destruction and potentially en-
hances the strength of CTL, its correlation with AR and
with subsequent graft function was studied. It was found
that levels of PI-9 mRNA were higher in urinary cells
from patients with AR compared with those without
AR.[18] We found its levels slightly higher in cases of
borderline rejection (p = 0.099), not significantly high in
ACR (p = 0.527), but significantly high in cases of CAN
(p = 0.002). To the best of our knowledge this is first
such observation in patients with CAN, with an impor-
tant implication, and needs to be further evaluated.
The generation of alloantigen specific CD25+ regula-
tory T cells was first studied in mice model by Kingsley
et al. [14]. They demonstrated that blockade of both
CTLA4 and IL-10 pathways abrogated the immune
regulation of alloresponses mediated by CD25+CD4+ T
cells. Regulation of TGF-
during T cell activation has
been described to be effected with IL-10 [23,35]. De-
pending on the presence or absence of IL-10, which
up-regulates TGF-
expression, the primed T cells can
either further differentiate into effector Th1 or Th2 cells
or be negatively regulated by IL-10 and TGF-
[23].
One isoform of TGF-, TGF-1 not only enhances ex-
pression of integrins and decreases matrix degrading
proteases, it also has immunosuppressive effect by I hi-
biting lymphocyte activation, and plays pro-inflamma-
tory role in tissues. As a result of its various effects in
different cell types it has been reported to be markedly
upregulated in renal tissues from the graft in cases of AR,
CAN and ATN (p < 0.001) and increased in borderline
changes (p < 0.01), recurrence of glomerulonephritis and
cyclosporin toxicity (p < 0.05) [24]. This group did not
report any correlation between intragraft TGF-
1 ex-
pression during AR and short term outcome of a rejec-
tion episode. We have not studied its expression in ATN,
recurrent glomerulonephritis or cyclosporin toxicity but
demonstrated marked hyper expression in urine samples
of patients with AR and bacterial urinary tract infection.
(Ta b l e 3). This observation further helps in understand-
ing the complex role of this gene in immune regulation
of both normal and autoimmune states [39]. CTLA 4
expression is also up-regulated by T cell activation [32].
We have observed hyper-expression of CTLA 4 in cases
of acute cellular as well as vascular rejections, whereas
its expression was not significantly high in cases of bor-
derline rejection, infection or CAN.
In response to different pathogen-derived antigens,
CD4 T lymphocytes become either T helper 1 (TH1) or T
helper 2 (TH2) cells depending on the type of pathogen.
TH1 development is guided by its own transcription fac-
tor, T-bet, which positively regulates its own expression
[28,29]. Earlier studies have demonstrated the hyper-
expression of T-bet in the setting of AR [40]. The present
study has also demonstrated significantly higher mRNA
copy number of T-bet in AR cases, but its specificity is
low (36.2%) leaving its usefulness as non-invasive marker
in dispute.
In summary, we have shown in this study that urinary
cytokine/chemokine expression profile is a valuable
technique in the accurate identification of the major
causes of renal allograft dysfunction. Such non-invasive
tests are highly desirable in a live related renal transplant
program.
5. ACKNOWLEDGEMENTS
This work was initiated with inspiration of Dr. Suthanthiran’s work,
and after getting working experience of first author in his lab. We all
are indebted to Dr. Suthanthiran’s team, especially Dr. T.Muthukumar
for providing continuous help with suggestions during the study, and
Dr.R.Ding for helping in designing primers and probes for CTLA4 and
T-bet.
REFERENCES
[1] Akhtar, F., Rana, T.A., Kazi, J., Zafar, N., Hashmi, A.,
Bhatti, S., et al. (1998) Correlation between Biopsies and
Noninvasive Assessment of Acute Graft Dysfunction.
Transplantation Proceeding, 30, 3069.
doi:10.1016/S0041-1345(98)00933-6
[2] Gwinner, W. (2007) Renal transplant rejection markers.
World Journal of Urology, 25, 445-455.
doi:10.1007/s00345-007-0211-6
[3] Mannon, R.B. and Kirk, A.D. (2006) Beyond histology:
Novel tools to diagnose allograft dysfunction. Clinical
Journal of the American Society of Nephrology, 1, 358-
366.
[4] Yannaraki, M., Rebibou, J.M., Ducloux, D., Saas, P.,
Duperrier, A., Felix, S., et al. (2006) Urinary cytotoxic
molecular markers for a noninvasive diagnosis in acute
renal transplant rejection. Transplant International, 19,
759-768. doi:10.1111/j.1432-2277.2006.00351.x
[5] Strom, T.B. (2005) Rejection—more than the eye can see.
R. Naqvi et al. / Open Journal of Immunology 1 (2011) 87-96
Copyright © 2011 SciRes. Openly accessible at http://www.scirp.org/journal/oji/
9595
New England Journal of Medicine, 353, 2394-2396.
doi:10.1056/NEJMe058257
[6] Anglicheau, D. and Suthanthiran, M. (2008) Noninvasive
prediction of organ graft rejection and outcome using
gene expression patterns. Transplantation, 86, 192-199.
doi:10.1097/TP.0b013e31817eef7b
[7] Hu, H. and Knechtle, S.J. (2006) Elevation of multiple
cytokines/chemokines in urine of human renal transplant
recipients with acute and chronic injuries: Potential usage
for diagnosis and monitoring. Transplantation Review,
20, 165-171. doi:10.1016/j.trre.2006.07.003
[8] Suthanthiran M. (1998) Human renal allograft rejection:
molecular characterization. Nephrology Dialysis Trans-
plantation, 13, 21-24. doi:10.1093/ndt/13.suppl_1.21
[9] Li, B., Hartono, C., Ding, R., Sharma, V.K., Ramaswamy,
R., Qian, B., et al. (2001) Noninvasive diagnosis of re-
nal-allograft rejection by measurement of messenger
RNA for perforin and granzyme B in urine. New England
Journal of Medicine, 344, 947-954.
doi:10.1056/NEJM200103293441301
[10] Graziotto, R., Del Prette, D., Rigotti, P., Anglani, F.,
Baldan, N., Furian, L., et al. (2006) Perforin, granzyme B,
and fas ligand for molecular diagnosis of acute renal al-
lograft rejection: Analyses on serial biopsies suggest
methodological issues. Transplantation, 81, 1125-1132.
doi:10.1097/01.tp.0000208573.16839.67
[11] Kotsch, K., Mashreghi, M.F., Bold, G., Tretow, P., Beyer,
J., Matz, M., et al. (2004) Enhanced granulysin mRNA
expression in urinary sediment in early and delayed acute
renal allograft rejection. Transplantation, 77, 1866-1875.
doi:10.1097/01.TP.0000131157.19937.3F
[12] Matz, M., Beyer, J., Wunsch, D., Mashreghi, M.F., Seiler,
M., Pratschke, J., et al. (2006) Early post-transplant uri-
nary IP-10 expression after kidney transplantation is pre-
dictive of short- and long-term graft function. Kidney In-
ternational, 69, 1683-1690. doi:10.1038/sj.ki.5000343
[13] Kim, S.H., Oh, E.J., Ghee, J.Y., Song, H.K., Han, D.H.,
Yoon, H.E., et al. (2009) Clinical significance of moni-
toring circulating CD4+CD25+ regulatory T cells in kid-
ney transplantation during the early posttransplant period.
Journal of Korean Medical Science, 24, S135-142.
doi:10.3346/jkms.2009.24.S1.S135
[14] Kingsley, C.I., Karim, M., Bushell, A.R., Wood, K.J.
(2002) CD25+CD4+ regulatory T cells prevent graft re-
jection: CTLA-4- and IL-10-dependent immunoregula-
tion of alloresponses. Journal of Immunology, 168, 1080-
1086.
[15] Ding, R., Li, B., Muthukumar, T., Dadhania, D.,
Medeiros, M., Hartono, C., et al. (2003) CD103 mRNA
levels in urinary cells predict acute rejection of renal al-
lografts. Transplantation, 75, 1307-1312.
doi:10.1097/01.TP.0000064210.92444.B5
[16] Tatapudi, R.R., Muthukumar, T., Dadhania, D., Ding, R.,
Li, B., Sharma, V.K., et al. (2004) Noninvasive detection
of renal allograft inflammation by measurements of
mRNA for IP-10 and CXCR3 in urine. Kidney Interna-
tional, 65, 2390-2397.
doi:10.1111/j.1523-1755.2004.00663.x
[17] Hoffmann, U., Segerer, S., Rümmele, P., Krüger, B.,
Pietrzyk, M., Hofstädter, F., et al. (2006) Expression of the
chemokine receptor CXCR3 in human renal allografts—a
prospective study. Nephrology Dialysis Transplantation,
21, 1373- 1381. doi:10.1093/ndt/gfk075
[18] Muthukumar, T., Ding, R., Dadhania, D., Medeiros, M.,
Li, B., Sharma, V.K., et al. (2003) Serine proteinase in-
hibitor-9, an endogenous blocker of granzyme B/perforin
lytic pathway, is hyperexpressed during acute rejection of
renal allografts. Transplantation, 75, 1565-1570.
doi:10.1097/01.TP.0000058230.91518.2F
[19] Muthukumar, T., Dadhania, D., Ding, R., Snopkowski, C.,
Naqvi, R., Lee, J.B., et al. (2005) Messenger RNA for
FOXP3 in the urine of renal-allograft recipients. New
England Journal of Medicine, 353, 2342-2351.
doi:10.1056/NEJMoa051907
[20] Wang, S., Jiang, J., Guan, Q., Lan, Z., Wang, H,, Nguan,
C.Y.C, et al. (2008) Reduction of Foxp3-expressing
regulatory T cell infilterates during the progression of
renal allograft rejection in a mouse model. Transplant
Immunology, 19, 93-102. doi:10.1016/j.trim.2008.03.004
[21] Veronese, F., Rotman, S., Smith, R.N., Pelle, T.D., Farrell,
M.L., Kawai, T., et al. (2007) Pathological and clinical
correlates of FOXP3+ cells in renal allograft during acute
rejection. American Journal of Transplantation, 7, 914-
922. doi:10.1111/j.1600-6143.2006.01704.x
[22] Navarro, J.F., Mora, C. and Muros, M. (2006) Urinary tu-
mor necrosis factor-
excretion independently corre-
lates with clinical markers of glomerular and tubulointer-
stitial injury in type 2 diabetic patients. Nephrology Di-
alysis Transplantation, 21, 3428-3434.
doi:10.1093/ndt/gfl469
[23] Cottrez, F. and Groux, H. (2001) Regulation of TGF-beta
response during T cell activation is modulated by IL-10.
Journal of Immunology, 167, 773-778.
[24] Pribylova-Hribova, P., Kotch, K., Lodererova, A., Vik icky,
O., Vitko, S., Volk, H.D., et al. (2006) TGF-
1 mRNA up-
regulation influences chronic renal allograft dysfunction.
Kidney International, 69, 1872-1879.
doi:10.1038/sj.ki.5000328
[25] Ibrahim, S., Saadi, G. and Al-Ansary, M. (2007) Estima-
tion of serum and urinary profibrotic cytokines in renal
allograft recipients. The Internet Journal of Nephrology,
4.
[26] Helantera, I., Teppo, A.M. and Koskinen, P. (2006) In-
creased urinary excretion of transforming growth factor
1 in renal transplant recipients during cytomegalovirus
infection. Transplant Immunology, 15, 217-221.
doi:10.1016/j.trim.2005.11.001
[27] Pearce, E.L., Mullen, A.C., Martins, G.A., Krawczvk,
C.M., Hutchins, A.S., Zediak, V.P., et al. (2003) Control
of effector CD8+ T cell function by the transcription
factor Eomesodermin, Science, 302 , 1041-1043.
doi:10.1126/science.1090148
[28] Szabo, S.J., Kim, S.T., Costa, G.L., Zhang, X., Fathman,
C.G. and Glimcher, L.H. (2000) A Novel Transcription
Factor, T-bet, detects Th1 Lineage Commitment, Cell,
100, 655-659. doi:10.1016/S0092-8674(00)80702-3
[29] Mullen, A.C., Hutchins, A.S., High, F.A., Lee, H.W.,
Sykes, K.J., Chodosh, L.A., et al. (2002) Hlx is induced
by and genetically interacts with T-bet to promote herita-
ble T(H)1 gene induction. Nature Immunology, 3, 652-
658.
[30] Callard, R.E. (2007) Decision making by the immune
response. Immunology & Cell Biology, 85, 300-305.
doi:10.1038/sj.icb.7100060
R. Naqvi et al. / Open Journal of Immunology 1 (2011) 87-96
Copyright © 2011 SciRes. http://www.scirp.org/journal/oji/Openly accessible at
96
[31] Linsley, P., Bradshaw, J., Greene, J., et al. (1996) Intra-
cellular trafficking of CTLA-4 and focal localization to-
wards sites of TCR engagement. Immunity, 4, 535-543.
doi:10.1016/S1074-7613(00)80480-X
[32] Finn, P.W., He, H., Wang, Y., Wang, Z., Guan, G., List-
man, J., et al. (1997) Synergistic induction of CTLA-4
expression by costimulation with TCR plus CD28 signals
mediated by increased transcription and messenger ribo-
nucleic acid stability. Journal of Immunology, 158, 4074-
4081.
[33] Racusen, L.C., Solez, K., Colvin, R.B., et al. (1999)
Banff 97 working classification of renal allograft pathol-
ogy. Kid International, 55, 713-723.
doi:10.1046/j.1523-1755.1999.00299.x
[34] Martin, L., Funes de la Vega, M., Bocrie, O., Harzallah,
A., Justrabo, E., Rifle, G., et al. (2007) Detection of
Foxp3+ cells on biopsies of kidney transplants with early
acute rejection. Transplantation Proceedings, 39, 2586-
2588. doi:10.1016/j.transproceed.2007.08.037
[35] Zeller, J.C., Panoskaltsis-Mortari, A., Murphy, W.J., Ru-
scetti, F.W., Narula, S., Roncarolo, M.G., et al. (1999)
Induction of CD4+ T cell alloantigen-specific hypore-
sponsiveness by IL-10 and TGF-β. Journal of Immunol-
ogy, 163, 3684.
[36] Mansour, H., Homs, S., Desvaux, D., Badoul, C., Dahan,
K., Matignon, M., et al. (2008) Intragraft levels of Foxp3
mRNA predict progression in renal transplants with bor-
derline change. Journal of the American Society of Ne-
phrology, 19, 2277-2281. doi:10.1681/ASN.2008030254
[37] Bunnag, S., Allanach, K., Jhangri, G.S., Sis, B., Einecke,
G., Mengel, M., et al. (2008) Foxp3 expression in human
kidney transplant biopsies is associated with rejection
and time post transplant but not with favorable outcome.
American Journal of Transplantation, 8, 1423-11433.
doi:10.1111/j.1600-6143.2008.02268.x
[38] Zheng, Y., Josefowicz, S.Z., Kas, A., Chu, T.T., Gavin,
M.A. and Rudensky, A.Y. (2007) Genome wide analysis
of Foxp3 target genes in developing and mature regula-
tory T cells. Nature, 445, 936-940.
doi:10.1038/nature05563
[39] Letterio, J.J. and Roberts, A.B. (1998) Regulation of Im-
mune response by TGFβ. Annual Review of Immunology,
16, 137. doi:10.1146/annurev.immunol.16.1.137
[40] Naqvi, R., Muthukumar, T., Dhadania, D., Ding, R.,
Snopkowski, C., Li, B. et al. (2005) The Yin and Yang of
Allograft rejection: overexpression of T-bet as well as
CTLA 4 during acute rejection of human renal allografts.
Journal of the American Society of Nephrology, 34A.