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Microbial Pathogenesis
journal homepage:www.elsevier.com/locate/micpath
Increasing of the interferon- γ gene expression during polyomavirus BK infection in kidney transplant patients
Neda Zareei
a,c, Hamid Reza Miri
b, Mohammad Hossein Karimi
c, Afsoon Afshari
c,d, Bita Geramizadeh
c, Jamshid Roozbeh
d, Ramin Yaghobi
c,∗aDepartment of Biology, Faculty of Sciences, University of Zabol, Zabol, Iran
bDepartment of Laboratory Sciences, Torbat Heydariyeh University of Medical Sciences, Torbat Heydariyeh, Iran
cShiraz Transplant Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
dShiraz Nephrology and Urology Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
A R T I C L E I N F O
Keywords:
Interferon-γ Polyomavirus BK Kidney transplantation Nephropathy
A B S T R A C T
Polyomavirus BK infection is a common complication and a major cause of morbidity after kidney transplan- tation. Surveillance of kidney transplant recipients was threatened by reactivation of polyomavirus BK infection can lead to polyomavirus BK-associated nephropathy (PVN). Antiviral immunoregulatory markers like Gamma interferon (IFN-γ) might also affect the polyomavirus BK pathogenesis for its role in antiviral host defense, graft rejection, and regulative of the adaptive immune responses. After screening polyomavirus BK infection, using Real time PCR (Taq-Man), the possible association between polyomavirus BK infection with IFN-γgene ex- pression was assessed. The mRNA levels of IFN-γwas examined in (n = 23) polyomavirus BK infected and (n = 23) non-infected kidney transplant patients in comparison with healthy controls (n = 23), using an in- house Real time PCR (SYBR Green) assay. The correlation of IFN-γexpression with viral load as well as other variables was also performed. The mRNA expression level of IFN-γwas significantly higher in polyomavirus BK infected patients (fold = 58.47) compared with non-infected ones (fold = 4.62), and healthy controls (p= 0.002). IFN-γexpression was higher in patients with higher viral load (p= 0.001). IFN-γexpression was correlated with viral load (r = 0.7,p< 0.0001). Accordingly, polyomavirus BK infection can induce IFN-γgene over expression in kidney transplant infected patients. The results emphasized on the determinative role of IFN-γ in the pathogenesis of activated polyomavirus BK infection and also its importance in managing the clinical complications after kidney transplantation due to virus reactivation, requiring further investigation.
1. Introduction
Polyomavirus BK, a member of Polyomaviridae family, is a common pathogen, resulting in allograft dysfunction in kidney transplant re- cipients [1]. Polyomavirus nephropathy (PVN) with pathologic changes in renal biopsy samples occurres as a result of polyomavirus BK re- activation in 1–10% of renal transplant recipients in thefirst year post- transplantation [2]. Also, graft loss with return to hemodialysis was reported in 30–80% of cases, if diagnosis was delayed [3]. The patho- genesis of PVN is defined by high-level of polyomavirus BK-DNA in renal-tubular epithelial cells, as a result of high viral replication, leading to cytopathic injury and denudation of the epithelial monolayer in the allograft tubules. Consequently, polyomavirus BK viruses pene- trate into the tissue and bloodstream, causing the infiltration of in- flammatory cells leading to tubular atrophy and interstitial fibrosis.
These effects might lead to up-regulation of creatinine level in serum and also reduction of renal allograft function that can increase the risk of graft loss [4–6]. Approximately, polyomavirus BK viruria and vir- emia are observed in up to 20% and 11–13% of patients in renal transplant recipients, respectively [7].
Interferon gamma (INF-γ), the only member of type II family of interferon, is a pro-inflammatory cytokine that plays a critical role in innate and adaptive immunity against viral infections, graft rejection and autoimmunity [8]. INF-γis released by Th1 and cytotoxic T-cells following the adaptive immune response, and natural killer (NK) cells during the innate immune response [9]. The IFN-γ can potentially promote pro and inflammatory responses in balancing the immune response [10]. Studies on animal models infected with a variety of DNA and RNA viruses, showed that IFNeγis related to various viral defense functions like the inhibition of viral protein synthesis, blocking viral
https://doi.org/10.1016/j.micpath.2019.02.015
Received 4 February 2018; Received in revised form 9 January 2019; Accepted 11 February 2019
∗Corresponding author.
E-mail addresses:[email protected],[email protected](R. Yaghobi).
Available online 13 February 2019
0882-4010/ © 2019 Elsevier Ltd. All rights reserved.
T
replication, and involvement in clearance of viral genomes from host cells [7,11,12]. The IFN-γfunction, as a immunomodulatory cytokine, is more significant in coordinating the immune response by establishing an antiviral state for longer term control [13]. IFN-γis able to inhibit polyomavirus BK gene expression, both at transcription and translation levels. It affects the reduction of viral progeny production level during lytic infection [14]. Evidence showed that IFN-γtreatment led to down regulation of polyomavirus large T antigen (LT Ag) expression [15], it also has antiviral activity against mouse polyomavirus (MPyV)in vitro [12] and also mediates the control of HCV replication [16]. Further- more, it was proposed that IFN-γis associated with T cell-mediated rejection through increase in antigenicity, and it is able to increase the expression of major histocompatibility complex (MHC) class I and II molecules on the cell surface that are increased in allograft rejection [8,17,18]. Studies showed that IFN-γhas high level expression in dif- ferent viral infections [16,19,20] The high serum level and intracellular expression of IFN-γwas reported in renal transplant patients with Cy- tomegalovirus (CMV) infection [19]. Also, the increased expression of IFN-γ genes was also observed in patients with Human im- munodeficiency virus (HIV) infection [16]. Moreover, some studies showed an increasing levels of IFN-γserum in patients with chronic Hepatitis C Virus (HCV) infection [21]. Therefore, the aim of this study was to determine the relationship between IFN-γmRNA expression and polyomavirus BK infection in Kidney transplant patients.
2. Materials and methods
2.1. Patient and control groups
In this case control study, 270 kidney transplant patients admitted to Namazi Hospital, affiliated to Shiraz University of Medical Sciences, Iran, enrolled during 2013–2014. Immunosuppressive regiment was implemented for all patients: 1- cyclosporine: 5 mg/kg as initial therapy following a maintenance dose of 2–2.5 mg/kg; 2- prednisolone:
120 mg/day as initial therapy and 10 mg/day routinely; and 3- myco- phenolate mofetil twice daily.
After being monitored for the presence of polyomavirus BK infection in plasma using Real time PCR (Taq-Man) protocol, two groups of pa- tients were selected: 23 kidney transplant with polyomavirus BK active
infection as polyomavirus BK-infected group and 23 kidney transplant patients were chosen randomly amongst all patients without poly- omavirus BK active infection as polyomavirus BK-non infected group.
Total of 23 normal individuals with no known active infection or other inflammatory diseases were considered as healthy control group.
Polyomavirus BK viremia can be considered as a standard index for PVN diagnosis. Diagnostic cut-offvalues for PVN in plasma samples vary between 1.0 × 103–1.0 × 104 copies/mL of polyomavirus BK genomic DNA. The substantial inter-assay variability occurs for a number of reasons such as differences in genome extraction methods, features of primer and probe design (including effects of polyomavirus BK subtype-associated polymorphisms), PCR amplification conditions, and different choices for reference material [22]. Therefore, in this study, the correlation between plasma viral load more than 5 × 103 copy/ml with great risk factors for PVN was considered [23,24].
Therefore, we divided polyomavirus BK infected patients into two groups of patients with polyomavirus BK DNA load >5×103copy/ml (9 patients), and patients with viral load <5×103 copy/ml (14 pa- tients). We compared IFN-γ gene expression of peripheral blood mononuclear cells (PBMCs) between the groups.
The demographic (age and gender), clinical (underlying disease), and laboratory data (blood type, post-transplant serum creatinine level, total protein, total bilirubin, direct bilirubin, blood urea nitrogen, serum protein, serum Ca, serum Na, serum K, alanine aminotransferase, aspartate aminotransferase, and blood sugar) were collected from pa- tient's documents during sampling, and analyzed to detect any possible correlation between these factors, polyomavirus BK viral load and IFN-γ gene expression. Moreover, to prevent any co-infection of polyomavirus BK with other viruses, such as hepatitis B virus (HBV) and CMV, the presence of these viruses was also examined. In addition, HCV and immunodeficiency virus (HIV) in recipients and donors before trans- plantation were checked in patients' documents. All organ donors were checked for ABO blood group compatibility before the transplantation;
but human leukocyte antigen (HLA) matching test is not routinely done for kidney transplant patients in Shiraz transplant center. All the pro- tocols were approved by the local Ethics Committee of Shiraz University of Medical Sciences. Fig. 1 is a flow chart showing in- formation about number of patients and events in this study.
Fig. 1.Procedureflow chart illustration.
2.2. Polyomavirus BK analysis
EDTA-blood samples were obtained from all kidney transplant pa- tients as well as healthy control group. To monitor the individuals for polyomavirus BK infection, Real time PCR assay was conducted. DNA samples were extracted by Invisorb Spin Virus DNA Blood Mini-kit (Invitek, Germany) according to the manufacturer instruction, using 200μl of each plasma sample [25]. The extracted total DNA con- centration and purity were estimated by measuring the optimal density at 260 and 280 nm, using a NanoDrop spectrophotometer (Thermo- fisher Scientific, USA). The absorbance ratio of 260/280 was greater than 1.8.
The Polyomavirus BK-DNA load was determined for all samples by Real time PCR instrument (ABI, Step One Plus, USA) using BKV Real Time (Taq-Man) PCR kit (Gensig, Primer Design, England) [25,26]. The reaction mixture contained 10μl of Taq-Man Universal PCR Master Mix,1μl BKV primer-probe mixture (Primer Design, England), 3μl of water, and 5μl of extracted DNA. The reaction mixture for positive control of DNA extraction was identical, but 1μl of aβ-actin primer- probe mixture was used as internal control. Real time PCR amplification was initiated at95 C° for 10 min, followed by 50 cycles at 94 C° for 10 min, and60 C° for 1 min. The Standard curves were generated using serial dilutions (Ten-fold) of positive control with the concentration between 101 to 105 copies/μl to quantify the of polyomavirus BK genome concentration.
2.3. Hepatitis B virus analysis
Plasma of EDTA-treated samples were used to determine the pre- sence of HBs Ag in both kidney transplant patient and control groups using third generation ELISA kit (DIAPRO-Italy) according to manu- facturer's instruction.
2.4. Cytomegalovirus analysis
DNA was extracted from the plasma of kidney transplant patients and healthy control group, using Invisorb Spin Virus DNA Blood Mini- kit (Invitek, Germany). DNA viral load of CMV was estimated using quantitative real-time PCR kit (Primer Design Ltd TM, Advanced kit, United Kingdom) according to the manufacturer's instruction [27].
2.5. IFN-γgene expression
2.5.1. RNA isolation and complementary DNA (cDNA) synthesis Total RNA was extracted from buffy coat obtained from each sample using RNX plus solution (Cinna Gen, Iran) according to the manu- facturer instruction. The purity and concentration of total RNA were determined by measuring the optimal density in 260/280 nm. RNA integrity was evaluated by agarose gel (1%) electrophoresis. The cDNA was synthesized from 500 ng of total RNA using Takara kit (Dalian, Japan) according to the manufacturer's instruction.
2.5.2. SYBR-green Real Time PCR
Gene expression was measured using Step One Plus Real Time in- strument (ABI, Step One Plus, USA). To prevent the amplification of genomic DNA, couple of primers was designed for IFN-γ (NM- 000619.2) according to the span of exon3 and exon4 junction. The sequences of the forward and reverse primers were 5′-ACGAGATGAC TTCGAAAAGCTGA-3′ and 5′- TTAGCTGCTGGCGACAGTTCA -3′, re- spectively. To normalize the results of the target gene, they were compared with Glyceraldehyde-3-Phosphate Dehydrogenase (GAPDH) cDNA as an internal standard control. The sequences of the forward and reverse primers of GAPDH were 5′- GGACTCATGACCACAGTCCA -3′
and 5′- CCAGTAGAGGCAGGGATGAT -3′, respectively. Real-time quantitative PCR was carried out using SYBR Premix Ex TaqII kit (Takara, Japan). The reaction mixture was prepared by SYBR Green
Premix (10μl), SYBR Green Dye (0.4μl), 0.8μl for each forward and reverse primers (5pM), water (4μl) and template cDNA (4μl). The re- action mixtures were amplified by one cycle in 95 °C for 5 min, followed by 40 cycles in 95 °C for 30 s and 62 °C for 20 s, and 72 °C for 30 s. A melting-curve analysis was generated in order to verify the specificity of the amplification reaction.
2.6. Statistical analysis
Quantitative variables are shown as mean values ( ± SD) for normal distribution of data and median (range) for non-normal distribution.
The IFN-γmRNA expression rate of change was calculated using Livak (2−ΔΔCt) method [28]. The parametric and nonparametric tests were performed to analysis the normal and non-normal distribution data.
Accordingly, two-sided Spearman correlation analysis was used to de- termine the relation between variables by GraphPad Prism 6.01 (GraphPad Software, Inc., San Diego, CA, USA). Finally, the area under a receiver operating characteristic (ROC) curve for IFN-γ expression level was assessed, and sensitivity and specificity of IFN-γas a potential biomarker for polyomavirus BK viremia was determined using MedCalc Statistical Software version 17.9 (MedCalc Software bvba, Ostend, Belgium).p< 0.05 was considered to be statistically significant.
3. Results
3.1. Clinical details of patients
The Real Time PCR revealed polyomavirus BK DNA was observed in 23 (8.5%) out of 270 kidney transplant patients (termed Polyomavirus BK-infected group). The age range of polyomavirus BK-infected group was 20–68 with median of 51 years. The polyomavirus BK-infected group consisted of 8 (34.78%) females and 15 (65.22%) males. Twenty- three kidney transplant patients including 11 (47.82%) females and 12 (52.18%) males with the age range of 21–68 with the median of 33 years, were allocated in polyomavirus BK-non infected group. The healthy control group age range was 22–55 with median of 27 years. No evidence of polyomavirus BK infection was observed in the healthy control group.
No acute rejection in both infected and non-infected kidney trans- plant patient groups was observed. Also, no infection for CMV and HBV viruses were observed in plasma samples of transplanted and control groups. Laboratory data showed no evidence of HCV and HIV infection amongst recipients and donors before transplantation. The demo- graphic and laboratory data of the 46 kidney transplant patients as well as healthy control group are summarized inTable 1.
3.2. IFN-γgene expression
Statistical analysis ofΔCt (Cycle threshold) value revealed a sig- nificant difference between the gene expression of IFN-γ in poly- omavirus BK infected patients (p= 0.01) and non-infected patients (p= 0.008), in comparison with the control group. Using2−ΔΔCt, our results indicated that IFN-γgene expression in PBMCs of polyomavirus BK-infected and non-infected patients was 58.47 (2.4–1424) and 4.62 (0.5–42.5) times higher than the control group, respectively. Also, our results indicated that IFN-γgene expression had significantly increased in polyomavirus BK-infected patients compared with non-infected ones (p= 0.002) (Fig. 2). Moreover, Polyomavirus BK infected group were divided into two groups (viral load >5 10× 3 (n = 9) vs. viral load <
×
5 103(n = 14)). IFN-γexpression was significantly higher in patients with high viral load compared to low viral load, non-infected and healthy groups (p= 0.001). No significant increase in patients with low viral load (Fig. 2).
Moreover, a Spearman's rank-order correlation was performed to determine the association between polyomavirus BK DNA viral load and IFN-γgene expression in polyomavirus BK-infected group. There
was a positive strong correlation between viral DNA load and IFN-γ mRNA level, which was statistically significant (r = 0.73,p< 0.0001) (Fig. 3).
ROC curve analysis was performed to evaluate the ability of IFN-γ mRNA expression to discriminate the polyomavirus BK infection in kidney transplant infected group from non-infected ones. The AUC was 0.750 (95%CI: 0.601–0.866) (p= 0.0008) (Fig. 4). The optimal cut-off value of IFN-γgene expression to differentiate between polyomavirus BK infected and non-infected groups was > 75.53 with a sensitivity 52.17% (95%CI: 30.59–73.18) and specificity 95.65% (95%CI:
78.05–99.89).
3.3. Association of IFN-γgene expression with diabetes mellitus as underlying disease in kidney transplant patients
Type I (n = 7) and type II (n = 13) diabetes mellitus were the most frequent underlying diseases (15.21% and 30.43%, respectively) in our transplant patients with and without infection in comparison with others (Table 2). IFN-γgene expression was higher in infected diabetic patients comparing to non-infected ones, but it was not significant (Fig. 5).
Table 1
Demographic and Laboratory Information of Polyomavirus BK infected and Polyomavirus BK non-infected Kidney Transplant Patients and Controls.
Polyomavirus BK infected, n = 23 (%) Polyomavirus BK non-infected, n = 23 (%) Healthy control, n = 23 (%) p-value Gender
n, (%)
Female 8
(34.78%)
11 (47.82%)
9 (39.14%)
0.8a
Male 15
(65.22%)
12 (52.18%)
14 (60.86%)
Blood Group n (%) O 10 (43.47%) 10 (43.47%) 12 (52.2%) 0.02a
A 5 (21.73%) 10 (43.47%) 5 (21.7%)
B 7 (30.43%) – 6 (26.1%)
AB 1 (4.34%) 3 (13.04%) –
Statistical tests.
a Chi-square or Fisher exact test.
Fig. 2. A:The mRNA Expression level of IFN-γin polyomavirus BK-infected patients compared with non-infected patients; the median of IFN-γexpression level was significantly increased in polyomavirus BK infected patients compared with non-infected patients. Mann-Whitney-U test was used to statistically analyze data.B:IFN- γgene expression in polyomavirus BK infected group with high viral load (n = 9), low viral load (n = 14), non-infected (n = 23) and healthy (n = 23) groups.
Kruskal-Wallis H test showed median of IFN-γgene expression was significantly higher in polyomavirus BK infected with high viral load (>5 10× 3) than low viral load (<5 10× 3), non-infected group and control group.
Fig. 3.Scatter plot of correlation between IFN-γ gene expression level and polyomavirus BK DNA load. Spearman's rank-order determined the strongest correlation between IFN-γgene expression levels measured by Real time PCR (SYBR Green) and polyomavirus BK DNA load determined by Real time PCR (Taq-Man) (r = 0.73,p< 0.0001).
3.4. Correlation of polyomavirus BK viral DNA load and IFN-γgene expression with variables
The correlation between laboratory and demographic data with viral load as well as IFN-γgene expression were analyzed and presented inTable 3. No significant correlation was observed between viral load and also IFN-γgene expression level with laboratory indices in both
polyomavirus BK infected and non-infected groups (Table 3). Labora- tory data was analyzed in all kidney transplant (polyomavirus BK in- fected and non-infected) patients and no significant differences were found in the median of evaluated indices between two studied patient groups. The association between age with IFN-γgene expression as well as viral DNA load was also assed. The results showed no significant correlation between age and IFN-γgene expression in polyomavirus BK- infected group (r = 0.37, p= 0.07) and in polyomavirus BK non-in- fected ones (r = 0.28, p= 0.18) (Fig. 6). Moreover, no significant correlation between age and viral load (r = 0.36,p= 0.002) was ob- served in polyomavirus BK infected group by Spearman correlation test (Fig. 6).
4. Discussion
Polyomavirus BK infection is known as a major challenge in kidney transplantation and related clinical outcomes, especially PVN and al- lograft rejection [14]. On the other hand, higher expression of IFN-γ might form alloimmune response and enhance MHC molecules pre- sentation on graft cell surface [29]. Polyomavirus BK antigen is pre- sented by different epitopes through donor HLA [19], and high HLA mismatch increases the risk of allograft rejection [30]. Hence, it can be proposed that IFN-γ is a determinative cytokine in controlling poly- omavirus BK replication and related disease progression.
Therefore, in this study, the possible relationships between IFNeγ mRNA expression and polyomavirus BK infection were evaluated.
Based on obtained results, polyomavirus BK was found in 8.5% of kidney transplant patients compared with other studies (Table 4).
The IFN-γexpression was also found significantly higher in PBMCs of polyomavirus BK-infected patients in comparison with non-infected ones (Fig. 2). This establishes the hampering role of IFN-γ against polyomavirus BK progression [14,31]. Although the correlation be- tween mRNA transcription level and protein production are poorly re- ported in polyomavirus infection, it was shown to be a close correlation between IFN-γmRNA expression and protein production levels in other viruses earlier [32]. On the other hand, high levels of urinary IFN-γin kidney transplant patients with polyomavirus BK viruria were detected in comparison with healthy individuals [31]. Therefore, it can be concluded that polyomavirus BK infection could activate immune re- sponse through high IFN-γ production in both mRNA and protein synthesis level, need separate clinical experiment has to be conducted.
Moreover, high IFN-γgene expression was observed in studied pa- tients with high plasma polyomavirus BK DNA load (> 5 × 103copy/
ml) compared with lower loads (< 5 × 103 copy/ml) (Fig. 2). Since increased IFN-γlevels was shown to exacerbate the risk of rejection through up-regulation of MHC complex molecules [29], it could be concluded that patients with higher viral load might have a higher risk for allograft rejection. Interestingly, it was shown that the frequency of polyomavirus BK specific T cell producing IFN-γdecrease during the progression of viremia to PVN [33], suggesting that this is the expres- sion of cytokines, which is responsible for defending against poly- omavirus BK virus rather than the number of T cells.
Finding of the significant correlation between increasing level of the IFN-γgene expression with higher viral DNA loads, suggests that IFN-γ could serve as an enhanced cytokines involved in pathogenesis of polyomavirus BK infection and related allograft rejection. Since IFN-γ dose-dependently controls polyomavirus BK replication by inhibiting polyomavirus BK gene expression at both transcriptional and transla- tional levels [14]. Moreover, the area under roc curve implied that IFN- γmRNA expression level might be a suitable predictive power to dis- tinguish kidney transplant patients with polyomavirus BK infection from non-infected ones (Fig. 4). However, there is no study that had analyzed ROC curve of IFN-γ expression to detect polyomavirus BK infection; hence, further investigation is warranted to indicate a cut-off value for this purpose.
Age-related changes in immune response, immunosenescence, has Fig. 4.ROC curve analysis of IFN-γmRNA level showed a significant relation
between IFN-γexpression with polyomavirus BK infection for discriminate in- fected kidney transplant patients and non-infected ones. Cut-offvalue, sensi- tivity, and specificity of IFN-γexpression were calculated. A cut-offvalue for IFN-γwas 73.01 with sensitivity 52.17% and specificity 95.65%.
Table 2
Distribution frequency of underlying diseases in all kidney transplant patients, Polyomavirus BK infected and Polyomavirus BK non-infected groups.
Underlying diseases Studied groups Polyomavirus BK infected n = 23 (%)
Polyomavirus BK non- infected n = 23 (%)
Hypertension 6 (26.08) 7 (30.43)
Renal stone 3 (13.04) 2 (8.69)
Polycystic kidney disease – 3 (13.04)
Type II diabetes mellitus 9 (39.13) 5 (21.73) Type I diabetes mellitus 4 (17.39) 3 (13.04)
Glomerular disease – 3 (13.04)
Systemic lupus Erythematosus
1 (4.34) –
Fig. 5.Median of IFN-γ gene expression in kidney transplant patient with diabetes mellitus as underlying disease. High expression of IFN-γwas not sig- nificant between the two groups. Mann-Whitney-U test was used for analyses.
several effects on T cell function such as the alternation of cytokine production that might increase the susceptibility of elderly persons for infectious diseases [34] such as polyomavirus BK infection [31,35]. On the other hand, immunosenescence has an important role on quality and outcome of organ transplantation [36]. In this study, we observed a correlation between increasing the age and higher level of IFN-γgene
expression currently with higher viral DNA load, but not significant (Fig. 6). The most frequent polyomavirus BK-specific CD4 T cell and immunoglobulin (IgG) antibodies was observed to be associated with age range between 20 and 30 years old. The older kidney transplant patients might be at higher risk for polyomavirus BK reactivation by reducing immune cellular response [37]. Nerveless, understanding the Table 3
Analysis of the correlations between the expression levels of IFN-γgene and polyomavirus BK DNA load with laboratory indices in all kidney transplant recipients.
Characteristics Polyomavirus BK infected group n = 23
Polyomavirus BK non-infected group n = 23
Median/range IFN-γgene expression Viral load Median/range IFN-γgene expression
Spearman's rho p* Spearman's rho p** Spearman's rho p***
Creatinine 1.8
(0.7–6.8)
−0.1 0.6 0.1 0.4 1.7
0.7–7.1
0.04 0.8
Total Bilirubin 0.5
3.3–0.1
0.2 0.1 0.07 0.7 0.6
0.1–1.5
−0.02 0.9 Direct Bilirubin 0.2
0.1–0.8
0.3 0.1 0.3 0.1 0.2
0.1–0.6
−0.2 0.2 Blood Urea Nitrogen 35
12–70
0.2 0.3 0.1 0.4 30
15–105
−0.02 0.2
Total Protein 5.9
4.6–8.7 −0.1 0.4 0.01 0.9 5.9
6–7.5 −0.1 0.4
Serum Protein 3
1.4–6.1
−0.1 0.5 −0.1 0.3 3.2
1.5–9.9
0.1 0.5
Serum Ca 8.3
4.4–9.2
0.1 0.5 −0.1 0.3 8.4
4–11
0.02 0.5
Serum Na 140
129–200 −0.1 0.3 0.1 0.6 139
81–144
0.1 0.5
p*: Correlation analysis between the IFN-γexpression levels and clinical indices in polyomavirus BK infected group, statistical tests: Spearman's rho.
p**: Correlation analysis between viral load and clinical indices in polyomavirus BK infected group, statistical tests: Spearman's rho.
p***: Correlation analysis between the IFN-γexpression levels and clinical indices in polyomavirus BK non-infected group, statistical tests: Spearman's rho.
Fig. 6.Scatter plot of correlation between age and IFN-γgene expression level as well as viral DNA load; Spearman's rank-order was used to determine the correlation between IFN-γgene expression and age in polyomavirus BK-infected group (r = 0.37,p= 0.07) and in polyomavirus BK non-infected group (r = 0.28,p= 0.18).
Also, correlation between viral load and age was calculated by Spearman's rank-order in Polyomavirus BK-infected group (r = 0.31,p= 0.14).
Table 4
Prevalence of polyomavirus BK in kidney transplant patients in different studies.
References Country (Year) Methods Prevalence (n, %)
Total patients n
Polyomavirus BK-infected group Polyomavirus BK-non infected group
Gender (n, %) Gender (n, %)
Male Female Male Female
[38] Brazil
(2017)
Real time PCR 41 (7.4)
553 30 (73.2) 11
(26.8)
329 (64.3) 183 (35.7)
[35] Germany
(2013)
Real time PCR 48 (13.6)
352 36
(75)
12 (25)
196 (64.5)
108 (35.5)
[47] USA (2013) Real time PCR 69
(19.88)
347 41 (59.5) 28
(40.5)
175 (63)
103 (37)
[44] USA (2014) Real time PCR 71
(28.28)
251 64 (90.0) 7
(10)
94 (52.0) 76
(48)
[48] Switzerland
(2010)
Real time PCR 38 (19)
203 32
(84)
6 (16)
106 (64)
59 (36)
mechanisms and consequences of immunosenescence against poly- omavirus BK infection through cytokine production, especially IFN-γ, might assist immune therapy in elderly polyomavirus BK-infected transplant patients.
Diabetes mellitus is considered as a risk factor for polyomavirus BK infection [38,39]. Reduced T cell counts was determined as the cause of increasing infectious diseases in kidney transplant patients with pre- exciting or post-transplant diabetes mellitus [40]. In spite of diagnosis of the diabetes mellitus (type I and II) in 15.21% transplant patients as an determinative underlying disease, increasing of the IFN-γexpression in these infected patients compared with non-infected ones was not significant (Fig. 5).
Since different pre and post-transplant risk factors including: viral infections (CMV [19], HCV [20], HBV [41], and HIV [42]), rejection episodes [43], and genetic polymorphisms in IFN-γgene might affect cytokine levels [14,19]. Hence, these factors were also analyzed to re- inforce on the determinative role of polyomavirus BK on influencing of IFN-γexpression, independently. Confirmatory signs of other viral in- fections and rejection episodes were not found amongst studied pa- tients. On the other hand, several polymorphisms such as SNP 874 (A/
T) (rs2430561) in IFN-γgene makes some patients more susceptible for viremia progression to PVN [14,44]. In this study, some patients with polyomavirus BK infection also had low level of IFN-γ expression (Fig. 2), suggesting that other factors might influence the cytokine level. Furthermore, some polyomavirus BK non-infected patients showed an increase in IFN-γexpression level (Fig. 2), might relate to different host genetic polymorphisms, need more investigations are called to clarify this suggestion.
The expression level of other biomarkers like chemokine such as C- X-C motif chemokine (CXCL9), CXCL10, and CXCL11 were also eval- uated earlier during polyomavirus infection. Results showed that from studied chemokine, CXCL9 expression increased in renal transplant patients with polyomavirus BK infection compared with non-infected ones and healthy controls [26,45,46].
5. Conclusion
Putting together, based on these results, IFN-γis overexpressed in polyomavirus BK infected kidney transplant patients. Higher viral load is associated with higher IFN-γexpression level among infected pa- tients. IFN-γhas a potential to present as a conforming marker for polyomavirus BK infection. Further understanding of the molecular mechanisms of IFN-γresponse to polyomavirus BK infection could be useful for the development of therapeutic strategies preventing PVN.
Acknowledgment
This study was supported by Department of Biology, Faculty of Sciences, Zabol University, Zabol, Iran and Transplant Research Center of Shiraz University of Medical Sciences, Shiraz, Iran. The authors would like to thank Sara Zareei Department of Medicinal Chemistry, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran for kindly edition of the paper.
Appendix A. Supplementary data
Supplementary data to this article can be found online athttps://
doi.org/10.1016/j.micpath.2019.02.015.
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