Gene 581 (2016) 57–65
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Research paper
Association of functional genetic variants of transcription factor Forkhead Box P3 and Nuclear Factor-κB with end-stage renal disease and renal allograft outcome Maneesh Kumar Misra a,b, Aditi Mishra a, Shashi Kant Pandey b, Rakesh Kapoor c, Raj Kumar Sharma d, Suraksha Agrawal a,⁎ a
Department of Medical Genetics, Sanjay Gandhi Post-graduate Institute of Medical Sciences, Raebareli Road, Lucknow 226014 (UP), India Department of Anatomy, Institute of Medical Sciences, Banaras Hindu University, Varanasi 221005 (UP), India c Department of Urology and Renal Transplantation, Sanjay Gandhi Post-graduate Institute of Medical Sciences, Raebareli Road, Lucknow 226014 (UP), India d Department of Nephrology, Sanjay Gandhi Post-graduate Institute of Medical Sciences, Raebareli Road, Lucknow 226014 (UP), India b
a r t i c l e
i n f o
Article history: Received 7 August 2015 Received in revised form 30 December 2015 Accepted 16 January 2016 Available online 19 January 2016 Keywords: FOXP3 NF-kB1 Variants ESRD Renal allograft survival
a b s t r a c t Background: The transcription factor FOXP3 and NF-κB regulates the expression of various genes that play an important role in the regulation of renal inflammation. We investigated the association of FOXP3 (rs2232365, rs3761548, rs5902434 and rs2294021) and NF-κB1 (rs28362491 and rs696) gene variants in susceptibility and prognosis of end stage renal disease (ESRD) and renal allograft outcome. Methods: We genotyped four common polymorphisms of FOXP3 and two-tag SNPs of NF-κB1 genes in 350 ESRD cases and 350 controls. Single marker analysis and SNP–SNP interaction model (one to six way combinations) was used for determination of clinical outcome of ESRD and acute rejection episode (ARE). Results: We observed significantly higher occurrence of mutant genotypes of tag-SNPs of FOXP3 namely; rs2232365 and rs3761548 along with NF-kB1 namely; rs28362491 and rs696 in ESRD and ARE cases, suggested a risk association for ESRD and ARE. Interestingly, multifactor dimension reduction analysis suggested an increased risks of nearly 6-folds for ESRD and 23-folds for ARE cases under the six factors model which consists of tag-SNPs of FOXP3 (rs2232365, rs3761548, rs5902434 and rs2294021) and NF-kB1 (rs28362491 and rs696). Kaplan–Meier survival analysis showed the lowest overall survival for mutant genotypes compared with wild and heterozygous genotypes of rs2232365 and rs3761548 tag SNPs of FOXP3 as well as NF-kB1 tag-SNPs rs28362491 and rs696 in renal allograft recipients. The crude and adjusted hazard ratios in univariate and multivariate Cox regression models showed almost 2-folds to 3-folds risk for overall survival against mutant genotypes of tag-SNPs of FOXP3 (rs2232365 and rs3761548) and NF-kB1 (rs28362491 and rs696) genes. Conclusions: These results suggest that variants of transcription factor FOXP3 and NF-kB1 might be associated with increased risk to the clinical outcome of ESRD and renal allograft survival. © 2016 Elsevier B.V. All rights reserved.
1. Introduction Abbreviations: °C, degree celsius; AP-1, activator protein-1; ARE, acute rejection episode; CCDC22, coiled-coil domain containing 22; EDTA, ethylene diamine tetra acetic acid; ESRD, end stage renal disease; FOXP3, Forkhead Box P3; GATA-3, GATA-binding protein-3; GD, Grave's disease; HWE, Hardy–Weinberg equilibrium; IL-2Rβ, interleukin-2Rβ; LD, linkage disequilibrium; MAF, minor allele frequency; matSpD, matrix spectral decomposition; MDR, multifactor dimensionality reduction; MIM, mammalian inheritance in man; ml, milliliter; NFAT, nuclear factor of activated T lymphocytes; NK, Nuclear Factor-κB; OS, overall survival; PCR, polymerase chain reaction; RFLP, restriction fragment length polymorphism; RM, recurrent miscarriages; SAG, stable allograft; SAM, sterile alpha motif; SLE, systemic lupus erythematosus; SMADs, sterile alpha motif domains; SNP, single nucleotide polymorphism; sp-1, specificity protein-1; STAT-5, signal transducer and activator of transcription5; TCR, T cell receptor; TGFβ, transforming growth factor beta; Treg cell, T regulatory cell; UTR, upstream regions; χ, Chi. ⁎ Corresponding author. E-mail addresses:
[email protected],
[email protected] (S. Agrawal).
http://dx.doi.org/10.1016/j.gene.2016.01.028 0378-1119/© 2016 Elsevier B.V. All rights reserved.
Renal replacement therapy is considered as an efficient treatment for end stage renal disease (ESRD). Irrespective of advancements in the drug regime and development of technology, the mortality rate is significantly higher in ESRD cases (Foley and Collins, 2007). The recipient's alloimmune response is responsible for the renal allograft rejection, comprised of manifested deterioration or complete functional loss of the allograft. Recently, T regulatory (Treg) cells have been described as a specific subpopulation of T cells, which may play a major role in the prevention of transplantation tolerance and autoimmunity (Bluestone and Abbas, 2003). The transcription factor Forkhead box p3 (FOXP3) is considered as an excellent marker for the induction and development of Tregs. These Treg cells help in dampening glomerular and tubule-interstitial inflammation in a number of models
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M.K. Misra et al. / Gene 581 (2016) 57–65
of renal injuries (Wolf et al., 2005; Mahajan et al., 2006). The signaling pathway of nuclear factor of kappa B (NF-κB) gene play a crucial role in the regulation of FOXP3 gene expression during the development of Treg cells (Long et al., 2009). Human FOXP3 gene (Gene ID: 50943, MIM number: 300292) maps on chromosome X and constitute a size of approximately 34.39 kb having of 12 exons and 11 introns. FOXP3 contributes to the conversion of naive T cells to Treg-like cells with suppression activity and also promotes Treg differentiation or function (Sauer et al., 2008). The FOXP3 gene is primarily expressed in Treg cells during normal physiological conditions, and it encodes FOXP3 protein, which regulates the activation of T-cells, down-regulates cytokine production in T-cells and acts as a transcriptional repressor (McHugh et al., 2002; Hori et al., 2003). In vivo or in vitro, indirect/direct ways of alloantigen-specific development of naturally originating Treg cells may ascertain antigen-specific dominant tolerance to allogeneic transplants (Nagahama et al., 2007). Thus, it may be postulated that the reduced numbers and/or functional deficiency of Treg cells may cause the predisposition to renal allograft rejection/ESRD. Human NF-κB1 (Gene ID: 4790, MIM number: 164011) is located on chromosome 4q24 with a nucleotide size of about 115.97 kb consisting of 25 exons and 24 introns. There are five proteins in the mammalian NF-κB family namely; NF-κB1, NF-κB2, RelA, RelB and c-Rel (Nabel and Verma, 1993). NF-κB regulates the differentiation of Treg cells, particularly the T helper 17 (Th17) cells, which play a vital role in the pathogenesis of autoimmunity and inflammation (Dong, 2008). Several studies have demonstrated the cell-intrinsic role of NF-κB in Treg cell generation (Isomura et al., 2009; Long et al., 2009). The histological evidence of NF-κB activation has been shown in human renal disease models like diabetic nephropathy, glomerular disease, and acute kidney injury (Sanz et al., 2010). It has been shown that NF-κB signaling pathway regulates the transcription of multiple proinflammatory molecules such as cytokines, chemokines, allograft antigens, adhesion molecules and reactive oxygen in response to renal injuries (Li and Verma, 2002). Since NF-κB signaling pathway play an important role in the regulation of renal inflammation, the observed variations in NF-κB1 gene content may influence the risk for ESRD and renal allograft rejections. The functional polymorphisms are potential regulatory polymorphisms situated in the noncoding regions of the genes, including promoter or upstream, downstream and intron regions, which may affect gene product (protein) due to the transcriptional alterations (Chorley et al., 2008). The tag-SNPs rs2232365, rs3761548 and rs5902434 of FOXP3 and NF-κB1 namely; rs28362491 are located in the putative DNA binding sites of upstream regions, hence, may play a regulatory role by influencing the FOXP3 (Song et al., 2013; Saxena et al., 2015) and NF-κB1 gene expression (Karban et al., 2004). The 3′ un-translated (downstream) region tag-SNPs namely; rs2294021 and rs696 are associated with post-transcriptional regulation of gene expressions. Recently, it has been shown that mutant allele of 3′UTR of NF-kB1 tag-SNP namely; rs696 significantly decreases NF-κB1A mRNA stability (Song et al., 2011). The genetic polymorphisms of NF-kB1 have been shown to be associated with autoimmune and inflammatory diseases like systemic lupus erythematosus (SLE) (Orozco et al., 2005), rheumatoid arthritis (Orozco et al., 2005), and extensive colitis in inflammatory bowel disease (Szamosi et al., 2009). Recently, FOXP3 gene polymorphisms have been shown to be associated with autoimmune diseases, such as vitiligo (Song et al., 2013), SLE (Lin et al., 2011), Grave's disease (GD) (Bossowski et al., 2014). Furthermore, FOXP3 and NF-kB1 gene polymorphism have not been fully explored in ESRD and renal allograft outcome. The present study has been undertaken to fill this gap. The aim of the present study was to investigate the association of FOXP3 (rs2232365 A/G, rs3761548 C/A, rs5902434 del/ATT and rs2294021 T/C) and NF-κB1 (rs28362491 ATTG1/ATTG2 and rs696 A/G) gene variants in susceptibility and prognosis of ESRD and renal allograft outcome in North Indian population.
2. Material and methods 2.1. Participants A total number of 350 unrelated ESRD patients [male = 277(79.14%), female = 73(20.86%)] were included in the present study. The study was initiated in April—2006. The cases were on regular follow-up from June— 2007 to December—2012 in the Department of Nephrology, a super specialty center at Sanjay Gandhi Post Graduate Institute of Medical Sciences (SGPGIMS), Lucknow. The inclusion criteria for patient selection was creatinine clearance b15 ml/min/1.73 m2 and were recommended for renal transplantation. All the patients selected for the present study were on regular hemodialysis the number of dialysis ranges from 1 to 235. A higher range of hemodialysis was because of the long waiting period after the initial diagnosis of end stage renal disease. Cockcroft Gault method was used for the calculation of creatinine clearance. For each patient, the information was collected for various other factors like age, gender, urinary protein level, blood urea nitrogen, blood pressure, complete lipid profile, sodium, potassium, inorganic phosphate, alkaline phosphate in a well-structured proforma and compared with the control group. The most frequent causes of renal failure were intochronic glomerulonephritis (37%), chronic interstitial nephritis (35%) and hypertensive nephrosclerosis (21%). Renal failure cases with concomitant diseases such as diabetic nephropathy and polycystic kidney disease were excluded from the study. Renal allograft biopsy was performed only in allograft recipient having clinical or laboratory evidence of renal dysfunction such as increased serum creatinine level. Renal allograft biopsy specimens were used for standard histological evaluation, and were considered positive for acute or chronic rejection on the basis of histological and immuno-histochemical features for the interpretation of renal allograft biopsy (Solez et al., 2008). All allograft recipients with acute allograft rejection were biopsy proven within 3 months of post transplantation. Among ESRD patients, 292 patients underwent first live related renal transplantation, 56 (19.17%) patients suffered from acute rejection episode (ARE) while 236 (80.82%) showed no rejection and have stable allograft (SAG). Recipients of more than one renal allograft were excluded from the study. Chronic allograft rejection cases were excluded from this study due to loss to follow-up. Our center is a referral hospital and most of the chronic allograft rejections are not on regular follow up due to financial constraints. The ESRD patients who underwent renal allograft transplantation were considered as post-transplant cases. All renal allograft recipients were treated with triple immunosuppressive therapy as initial immunosuppression that incorporated (i) cyclosporine or tacrolimus, (ii) mycophenolate mofetil or everolimus (iii) and prednisolone. Rabbit antithymocyte globulin or basiliximab (simulect) was given during the postoperative period as induction therapy. Three hundred fifty [(male = 269 (76.86%), female = 81(23.14%)] healthy, age, sex and ethnically matched north Indians from the same geographic area were selected as controls. The ethnicity of both patients and controls is shown in Supplementary Table S1. Controls with risk factors like family history of hypertension, diabetes mellitus, hyperlipidemia and autoimmune diseases were excluded from the study. Selection of control sample was based on the absence of any kidney disease established through serum creatinine level. The mean creatinine level of controls was found to be 0.75 ± 0.37 mg/dl, while that of patients was 7.54 ± 4.3 mg/dl indicating the proper selection of controls. Approximately, 79% of the cases were male; hence care was taken to include more number of male controls in order to rule out gender bias. 2.2. Ethics statement The study protocol was reviewed and approved by an Institutional Ethics Committee (IEC) of the Sanjay Gandhi Post-graduate Institute of Medical Sciences before initiation of the study. Further, the study was carried out in accordance with the ethical standards of the Declaration
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of Helsinki. All participants provided written informed consent before their inclusion in the study. 2.3. Tag-SNPs selection The International HapMap database (http://hapmap.ncbi.nlm.nih. gov/index.html.en) and Ensembl (http://www.ensembl.org/index. html) SNP databases were used to select tag-SNPs in the FOXP3 and NF-kB1 genes. The online Tagger software was used for tagging with the pairwise tagging algorithm r2 ≥ 0.8 and minor allele frequency (MAF) ≥ with a minor allele frequency N 5% available in each database (de Bakker et al., 2005). The choice of this MAF served to strike a balance for the following factors: (i) the available sample size, (ii) the number of SNPs to be genotyped, and (iii) a reasonable power of the study (at least 80%) to detect the risk allele. Further, we included only those functional tag-SNPs for which scientific evidence has been published to illustrate their potential role in inflammatory or autoimmune diseases in FOXP3 (Wu et al., 2012; Song et al., 2013) and NF-kB1 gene region (Borm et al., 2005; Szamosi et al., 2009). Accordingly, six SNPs in regions of FOXP3 (rs2232365 A/G, rs3761548 C/A, rs5902434 del/ATT and rs2294021 T/C) and NF-kB1 (rs28362491 ATTG1/ATTG2 and rs696 A/G) genes with MAF N5% in Asian population were selected for the present study. 2.4. Molecular analysis Five ml of peripheral blood sample was drawn from each subject in ethylene diamine tetra acetic acid (EDTA) coated collection vials and stored at −20 °C until use. Genomic DNA was extracted using genomic DNA extraction kit from Qiagen (Brand GMbH and Co KG, Cat # 51104). The tag-SNPs of FOXP3 (rs3761548 C/A and rs2294021 T/C) and NF-kB1 (rs28362491 ATTG1/ATTG2 and rs696 A/G) genes were genotyped by polymerase chain reaction (PCR) followed by restriction fragment length polymorphism analysis (RFLP) assay using primers and restriction enzyme as described in detail elsewhere (Song et al., 2011; Wu et al., 2012). The detection of genetic variants of rs2232365 A/G, and rs5902434 del/ATT tag-SNPs in FOXP3 gene region was carried out by using PCR with sequence-specific primers as reported earlier (Wu et al., 2012). The details of primer sequences and restriction enzymes used for genotyping FOXP3 and NF-kB1 tag-SNPs are mentioned in Supplementary Table S2. Genotyping was performed without the knowledge of the subject's case or control status. For each assay, control DNA samples with known genotypes (positive control) and non-template (water) as a negative control were included in each typing run to ensure that genotypes were called correctly throughout the study. Two researchers independently read the gel pictures and performed repeated assays if they did not reach at consensus on the tested genotype. To validate the results from PCR-RFLP and for quality control, almost 15% of the samples were randomly selected for regenotyping along with DNA sequencing and the results were checked for concordance. The concordance of the quality control samples was 100%. 2.5. Statistical analysis Statistical power of the study and the sample size estimation was carried out using QUANTO (version 1.2, http://hydra.usc.edu/gxe) under the guidance of a statistician. The power of the study was set at 80% with a significance level of 0.05. On the basis of our calculations using the Power and Sample Size software program, our sample (ESRD n = 350 and control n = 350) was considered adequate to study the selected tag-SNPs of the FOXP3 and NF-κB1 genes. We assessed the Hardy–Weinberg equilibrium (HWE) of the genotype distribution among cases and controls by using χ2 test. Unconditional univariate and multivariate logistic regression analysis were performed to obtain the genotype-specific crude and adjusted odds ratios (ORs) and their 95%
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confidence intervals (CIs). The multivariate adjustment included the age, gender, ethnicity and the number of hemodialysis. The survival analysis was performed using Kaplan–Meier method to calculate the overall survival (OS) time, indicated as median ± standard error of median (SEM) in allograft recipients with different genotypes, and the log rank test was applied to compare rejection curves. Univariate and multivariate Cox proportional hazards regression models were used to estimate the crude and adjusted hazard ratios (HRs) and their 95% CIs. The degree of pair wise linkage disequilibrium (LD) was calculated for each pair of tag-SNPs in both ESRD and control groups using the Haploview program (version 4.2, Broad Institute of Harvard and MIT, Cambridge, MA, USA) (Barrett et al., 2005). D′ was calculated to measure LD. To account for multiple testing, a modified Bonferroni correction was made by estimating the number of independent variables in the correlation matrix as implemented in the program Matrix Spectral Decomposition (matSpD; http://gump.qimr.edu.au/general/daleN/ matSpD/) by using Li and Ji's method (Li and Ji, 2005). The results from Li and Ji's method indicated that the four tag-SNPs in FOXP3 and two tag-SNPs in NF-kB1 gene represented 5.19 independent variables. Therefore, p-values were corrected for 5.19 tests for multiple comparisons: Pc = 1 − (1 − P)k, where k is the number of independent comparisons. The statistical significance was considered only when the pcorr-value was ≤0.05. Statistical analysis was performed by using SPSS version 20.0 for Windows (Statistical Package for Social Sciences, SPSS Inc., USA). Further, we have performed Multifactor Dimensionality Reduction (MDR) analysis (MDR software v3.0.2; available on http://sourceforge. net/projects/mdr/), as a non-parametric test to evaluate the potential SNP–SNP interactions (one to six way combinations). The MDR method has been illustrated in detail elsewhere, (Hahn et al., 2003) and used in this study cohort. 3. Results 3.1. Demographic profile and clinical characteristics of cases and controls The baseline laboratory data and demographic profile of the patients and controls are shown in Supplementary Table S1. As expected serum creatinine levels and protein urea which are the most important renal functions showed significant differences (p b 0.001) between patients and controls. 3.2. Impact of transcription factor FOXP3 and NF-kB1 gene variants on ESRD Distribution of Genotype frequencies of tag-SNPs in FOXP3 (rs2232365, rs3761548, rs5902434 and rs2294021) and NF-kB1 (rs28362491 and rs696) genes are shown in Table 1. FOXP3 and NF-kB1 tag-SNPs under investigations were in HWE in both ESRD cases and controls. The p-values of HWE for the studied tag-SNPs namely; rs2232365, rs3761548, rs5902434, rs2294021, rs28362491 and rs696 were 0.321, 0.075, 0.400, 0.898, 0.095 and 0.135 in ESRD and 0.278, 0.927, 0.455, 0.614, 0.201 and 0.739 among control subjects respectively. Single marker analysis revealed an increased risk of almost 3-folds for FOXP3 tag-SNPs namely; rs2232365 and rs3761548 in univariate and multivariate models among ESRD cases (Table 1). However, FOXP3 tag-SNPs namely; rs5902434 and rs2294021 showed no significant correlation with ESRD (Table 1). Moderate risk ranged from nearly 3folds to 2-folds respectively for tag-SNPs of NF-kB1 namely; rs28362491 and rs696 under both univariate and multivariate models in ESRD cases (Table 1). Multifactor dimension reduction (MDR) analysis is the interaction model, which is used to evaluate the potential SNP ~ SNP interaction model (one to six way combinations). An increased risk of almost 6-fold was observed for ESRD cases in six-factors model constituted by tag-SNPs of FOXP3 rs2232365, rs3761548, rs5902434 and rs2294021
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Table 1 Distribution of transcription factor FOXP3 and NF-κB1 gene variants in ESRD cases and controls. Marker
FOXP3 rs2232365 rs3761548 rs5902434 rs2294021 NF-κB1 rs28362491 rs696
Alleles#
MAF$ (%)
Crudea
Adjustedb
ESRD
Controls
OR (95%CI)c
p-valued
OR (95%CI)c
p-valued
(PHWE)Ψ
A/G C/A del/ATT T/C
41.57% 41.71% 42.14% 42.29%
30.86% 31.00% 38.29% 37.71%
2.94 (1.79–4.83) 2.66(1.66–4.27) 1.47 (0.94–2.30) 1.41 (0.91–2.21)
b0.001⁎ b0.001⁎ 0.087 0.122
3.10 (1.58–6.08) 3.08 (1.67–5.66) 1.15 (0.64–2.08) 1.35 (0.74–2.47)
0.001⁎ b0.001⁎ 0.625 0.319
0.278 0.927 0.455 0.614
ATTG1/ATTG2 A/G
56.14% 49.57%
46.00% 41.57%
2.12 (1.41–3.19) 1.89 (1.24–2.87)
b0.001⁎ 0.003⁎
2.61(1.50–4.53) 1.85 (1.18–2.91)
0.001⁎ 0.007⁎
0.201 0.739
#
Major/minor alleles. Minor allele frequencies. a Un-adjusted. b Adjusted by age, gender, ethnicity and the number of hemodialysis. c Additive model. d After Bonferroni correction (yielding pcorr). Ψ Hardy-Weinberg equilibrium p-value among control subjects. ⁎ Statistically risk associated. $
along with NF-kB1 rs28362491 and rs696 (OR = 5.77, 95% CI = 1.75– 19.02, p = 0.002). The maximum testing accuracy, highest cross validation consistency (10-fold) and greater significance was observed in six tag-SNP model (Table 2A). However, the testing accuracy, cross validation consistency and significance was decreased in one-factor (rs3761548), two-factors (rs28362491 and rs696), three-factors (rs3761548, rs28362491 and rs696) four-factors (rs2232365, rs3761548, rs28362491 and rs696) and five-factors (rs2232365, rs3761548, rs2294021, rs28362491 and rs696) models (Table 2A).
rs3761548, rs5902434 and rs2294021 along with NF-kB1 rs28362491 and rs696 tag-SNPs (OR = 22.89, 95% CI = 10.16–51.57, p = b0.001). The six SNP model has shown maximum testing accuracy, highest cross validation consistency (10-fold) and greater significance (Table 2B). Meanwhile, the testing accuracy, cross validation consistency and significance was decreased in one-factor (rs696), two-factors (rs2232365 and rs696), three-factors (rs2232365, rs5902434 and rs28362491) four-factors (rs2232365, rs3761548, rs5902434 and rs28362491) and five-factors (rs2232365, rs3761548, rs5902434, rs2294021 and rs28362491) models (Table 2B).
3.3. Impact of transcription factor FOXP3 and NF-kB1 gene variants on ARE Distributions of FOXP3 and NF-kB1 tag-SNPs under investigation in ARE and SAG cases are shown in Table 3. An increased risk of almost 3.5 folds and 3.0 folds was observed for FOXP3 tag-SNPs namely; rs2232365 and rs3761548 respectively in univariate and multivariate models among ARE cases (Table 3). No significant association was established for FOXP3 tag-SNPs namely; rs5902434 and rs2294021 with ARE cases (Table 3). Nearly 3-folds and 4-folds increased risk was found for NF-kB1 tag-SNPs namely; rs28362491 and rs696 under univariate and multivariate models among ARE cases (Table 3). Interesting, MDR analysis revealed increased risks of almost 23-folds for ARE cases in six-factors model constructed by FOXP3 rs2232365,
3.4. Kaplan Meier survival analysis The renal allograft recipients included in the present study were followed up to 5 years. Survival analysis was performed for only those tag-SNPs which differed significantly among ARE cases when compared with SAG cases, to calculate the 5-year overall survival in months (median ± SEM). The lowest overall survival was observed for mutant genotypes as compared to heterozygous and wild genotypes of tag-SNPs of FOXP3 namely; rs2232365 (Fig. 1A) and rs3761548 (Fig. 1B) along with NF-kB1 namely; rs28362491 (Fig. 2A) and rs696 (Fig. 2B) in renal transplant cases.
Table 2 Multi Dimensionality Reduction (MDR) models showing association of high-order gene–gene interactions in ESRD and Renal transplant recipients. Number of risk factors
Best interaction model
Testing accuracy
CVC
A. ESRD vs. control 1 2 3 4 5 6
rs3761548 rs28362491, rs696 rs3761548, rs28362491, rs696 rs2232365, rs3761548, rs28362491, rs696 rs2232365, rs3761548, rs2294021, rs28362491, rs696 rs2232365, rs3761548, rs5902434, rs2294021, rs28362491, rs696#
0.5029 0.6986 0.6971 0.7014 0.6886 0.6657
5/10 10/10 10/10 9/10 9/10 10/10
0.002⁎ 0.001⁎ 0.001⁎ 0.001⁎ 0.001⁎ 0.002⁎
B. ARE vs. SAG 1 2 3 4 5 6
rs696 rs2232365, rs696 rs2232365, rs5902434, rs28362491 rs2232365, rs3761548, rs5902434, rs28362491 rs2232365, rs3761548, rs5902434, rs2294021, rs28362491 rs2232365, rs3761548, rs5902434, rs2294021, rs28362491, rs696#
0.5999 0.6076 0.5516 0.5427 0.5466 0.5581
6/10 5/10 4/10 5/10 8/10 10/10
b0.001⁎ b0.001⁎ b0.001⁎ b0.001⁎ b0.001⁎ b0.001⁎
CVC cross validation consistency. ARE: Acute rejection episodes; SAG: Stable allograft. # Best model was selected based on maximum testing accuracy and highest CVC. ⁎ Significant p-values.
p-value
OR(95% CI) 1.60(1.18–2.16) 5.74(2.00–16.45) 5.30(1.91–14.72) 5.88(2.04–16.88) 5.42(1.87–15.70) 5.77(1.75–19.02)
3.46(1.85–6.47) 4.31(2.33–7.97) 5.55(2.95–10.42) 9.91(5.08–19.33) 18.94(8.70–41.22) 22.89(10.16–51.57)
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Table 3 Distribution of transcription factor FOXP3 and NF-κB1 gene variants in ARE and SAG cases. MAF$ (%)
Crudea
Adjustedb
Marker
Alleles#
ARE
SAG
OR (95%CI)c
P-valued
OR (95%CI)c
P-valued
(PHWE)Ψ
FOXP3 rs2232365 rs3761548 rs5902434 rs2294021
A/G C/A del/ATT T/C
47.32% 48.21% 48.21% 41.96%
34.75% 35.59% 40.25% 41.95%
3.40 (1.46–7.89) 3.04 (1.37–6.74) 1.81 (0.79–4.15) 1.10 (0.47–2.52)
0.004⁎ 0.006⁎ 0.158 0.822
3.49 (1.48–8.22) 3.04 (1.36–6.82) 1.68 (0.72–3.93) 1.16 (0.50–2.69)
0.004⁎ 0.007⁎ 0.224 0.730
0.115 0.590 0.309 0.345
NF-κB1 rs28362491 rs696
ATTG1/ATTG2 A/G
66.96% 61.61%
51.06% 43.64%
2.85 (1.23–6.57) 3.74 (1.66–8.39)
0.014⁎ 0.001⁎
2.89 (1.24–6.71) 4.12 (1.80–9.39)
0.014⁎ 0.001⁎
0.691 0.434
ARE: Acute rejection episodes; SAG: Stable allograft; # Major/Minor alleles; $ Minor allele frequencies; a Un-adjusted; b Adjusted by age, gender, ethnicity and the number of hemodialysis; c Additive model; d After Bonferroni correction (yielding pcorr); Ψ Hardy-Weinberg equilibrium p-value among SAG cases; ⁎ Statistically risk associated.
We observed 2-folds to 3-folds higher hazard for overall survival in univariate and multivariate Cox regression models for mutant genotypes of tag-SNPs of FOXP3 rs2232365 and rs3761548 along with NF-kB1 rs28362491 and rs696 (Supplementary Table S3). Stepwise (Backwald method) Cox proportional hazard analysis was used to evaluate the correlation between variables including selected demographic characteristics, clinical features, tag SNPs of FOXP3 (rs2232365 and rs3761548) and NF-kB1 (rs28362491 and rs696) and overall survival. The variables like age and gender of recipients and donors along with recipient genotypes (rs2232365, rs3761548, rs28362491 and rs696), systolic blood pressure (BP), diastolic BP, cholesterol, triglycerides and surgical/medical complications were included in the regression model. The criteria for the selection of variables were with a significance level of p ≤ 0.05 for inclusion and p ≥ 0.10 for elimination from the stepwise Cox proportional hazard model (Supplementary Table S3).
3.5. LD analysis LD analysis was carried out between ESRD cases and controls, which revealed that moderate LD exists between rs2232365, rs3761548, rs5902434 and rs2294021 tag-SNPs. Increased LD values showed stronger pairwise correlation between tag-SNPs demonstrated in Fig. 3. 4. Discussion Regulatory T cells are the master regulators of immune response which acts either through secreted cytokines or cell-to-cell interactions with effector T cells (Trzonkowski et al., 2009). Treg cells have been implicated in dampening glomerular and tubule-interstitial inflammation in a number of models of renal injuries (Wolf et al., 2005; Mahajan et al., 2006). The transcription factor FOXP3 helps in the induction and
Fig. 1. Impact of FOXP3 tag-SNPs namely; rs2232365 and rs3761548 on renal allograft outcome. The lowest overall survival was observed for mutant genotypes as compared to heterozygous and wild genotypes of tag-SNPs of FOXP3 namely; rs2232365 (A/A = 25.08 ± 4.30, A/G = 25.07 ± 2.61, GG = 10.09 ± 7.51, log rank: p = 0.024, χ2 = 7.42; Fig. 1A) and rs3761548 (C/C = 25.28 ± 5.62, C/A = 25.07 ± 1.74, A/A = 12.06 ± 2.83, Log rank: p = 0.001, χ2 = 14.51; Fig. 1B) in renal transplant cases.
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Fig. 2. Impact of NF-κB tag-SNPs namely; rs28362491 and rs696 on renal allograft outcome. The lowest overall survival was observed for mutant genotypes as compared to heterozygous and wild genotypes of NF-kB1 tag-SNPs namely; rs28362491 (ATTG1/ATTG1 = 26.16 ± 4.69, ATTG1/ATTG2 = 25.09 ± 1.99, ATTG2/ATTG2 = 15.20 ± 3.91, Log rank: p = b0.001, χ2 = 17.12; Fig. 2A) and rs696 (A/A = 25.28 ± 3.54, A/G = 25.09 ± 1.66, GG = 11.19 ± 3.89, Log rank: p = b0.001, χ2 = 20.78; Fig. 2B) in renal transplant cases.
development of Treg cells. The NF-κB signaling pathway plays a pivotal role in the regulation of FOXP3 gene expression during the development of Treg cells (Long et al., 2009). Further, it has been demonstrated that NF-κB gene plays a cell-intrinsic role in Treg cell generation (Isomura et al., 2009; Long et al., 2009). Thus, it could be hypothesized that the observed variations in transcription factor FOXP3 and NF-κB gene content may impaired the function of Treg cells which affect the clinical outcome of ESRD and renal transplantation. In the present study, we have
evaluated the impact of FOXP3 (rs2232365, rs3761548, rs5902434 and rs2294021) and NF-κB1 (rs28362491 and rs696) gene variants on ESRD, ARE and renal allograft survival. We observed significantly higher occurrence of mutant genotypes of tag-SNPs of FOXP3 namely; rs2232365 and rs3761548 along with NF-kB1 namely; rs28362491 and rs696 in ESRD and ARE cases, indicating a risk association for ESRD (Table 1) and ARE (Table 3). We have used MDR analysis to evaluate the impact of potential SNP–SNP interaction
Fig. 3. Schematic overview of Human FOXP3 gene and Linkage disequilibrium analysis in ESRD cases and controls. The image was generated using HAPLOVIEW (version 4.2) program using tag-SNPs with minor allele frequencies N2%. The black boxes, white boxes, and horizontal lines have been used to represent coding sequences, non-coding sequences and introns respectively. Exon numbers were shown below the exon boxes. The sizes of exons and introns were labeled above them. The locations of rs5902434 (1), rs3761548 (2), rs2232365 (3), rs2294021 (4) and (GT)n microsatellite polymorphisms have been indicated with arrows. Strong LD (LOD ≥ 2, D′ = 1), moderate LD (LOD ≥ 2, D′ b 1) and No LD (LOD b 2, D ′ b 1). LOD: log of the odds; D′: pairwise correlation between SNPs.
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model constituted by FOXP3 and NF-kB1 genes in ESRD and ARE cases. Interestingly, MDR analysis suggested an increased risks of nearly 6-folds for ESRD and 23-folds for ARE cases under the six factors model. This model consists of tag-SNPs of FOXP3 (rs2232365, rs3761548, rs5902434 and rs2294021) and NF-kB1 (rs28362491 and rs696). The six factors model has maximum testing accuracy, highest cross validation consistency and greater significance for probable prediction of clinical outcome of ESRD and ARE. Kaplan–Meier survival analysis showed the lowest overall survival for mutant genotypes compared with the wild and heterozygous genotypes of rs2232365 and rs3761548 tag SNPs of FOXP3 as well as NF-kB1 tag-SNPs rs28362491 and rs696 in renal allograft recipients. The crude and adjusted HRs in univariate and multivariate Cox regression models showed an increased risk ranges from almost 2-folds to 3-folds for overall survival against mutant genotypes of tag-SNPs of FOXP3 (rs2232365 and rs3761548) and NF-kB1 (rs28362491 and rs696) genes. We observed moderate LD between the coding and non-coding variants of FOXP3 gene as shown in Fig. 3, which may be responsible for the alteration of the gene profile and might be associated with increased risk to ESRD. Previously, it has been suggested that functional variants of the FOXP3 gene may affect the risk of human diseases, probably by altering FOXP3 function and/or its expression (Wu et al., 2012). Our results are consistent with other reports which have shown increased risk for mutant genotype at rs2232365 and rs3761548 tag-SNPs of FOXP3 with human diseases such as idiopathic recurrent miscarriages (RM) (Wu et al., 2012) and autoimmune disease (Song et al., 2013). It has been shown that mutant genotypes of tag-SNPs of NF-kB1 namely; rs28362491 and rs696 are associated with increased risk for endometriosis (Zhou et al., 2010) and extensive colitis in inflammatory bowel disease (Szamosi et al., 2009) respectively, which are in concordance with our findings in ESRD and ARE cases. We have found no significant association of FOXP3 tag-SNPs namely; rs5902434 and rs2294021 with clinical outcome of ESRD and ARE. Similarly, no correlation was reported by earlier studies for rs5902434 and rs2294021 tag-SNPs with susceptibility to vitiligo an autoimmune disease (Song et al., 2013) and idiopathic RM (Wu et al., 2012). To the best of our knowledge this is the first study in ESRD; however, few studies have examined FOXP3 and NF-kB1 gene polymorphism in relation to renal allograft outcome. FOXP3 rs3761548 tag-SNP has been shown to be associated with renal allograft rejection in Chinese Han population (Qiu et al., 2012), similar to our observations in north Indian renal allograft recipients. Earlier, one study has evaluated NF-κB1 gene polymorphisms among Hispanic renal allograft recipients and suggested that NF-κB1 gene variants may determine the incidence of acute allograft rejection or graft survival (Vu et al., 2013), which strengthen our findings presented in this study. The FOXP3 tag-SNPs namely; rs2232365, rs3761548 and rs5902434 are placed at nucleotide position −924, −3279 and −6054 respectively in the first intron (upstream regulatory regions) of FOXP3 gene. The transcription factor (TF) binding search analysis was performed using TRANSFAC software (http://www.biobase-international.com), to ascertain the functional relevance of rs2232365 and rs3761548 SNPs located in the first intron of FOXP3 gene. TF search analysis indicated that the variant of rs2232365 and rs3761548 SNPs is situated in a putative DNA binding site for the transcription factor GATA-binding protein-3 (GATA-3) and specificity protein-1 (sp-1) respectively. It has been suggested that maintenance of pro-(Th1)/anti-inflammatory (Th2) cytokine profile depends on the GATA-3 mRNA expression (Chakir et al., 2003). The balance of Th1/Th2 cytokine profile determines the clinical outcome of ESRD and ARE. Previously, it has been shown that Th1 cytokines are increased while Th2 cytokine levels are decreased which may be associated with increased risk for ESRD (Sester et al., 2000; Ando et al., 2005) and renal allograft rejection (Amirzargar et al., 2005). Recently, an intrinsic mechanism prompting FOXP3expressing Treg cells to Th2 conversion through GATA-3 in vivo analysis have been identified (Wang et al., 2010). It might be anticipated that
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rs2232365 variant may contribute towards ESRD/ARE risk by altering the balance of Th1/Th2 cytokine profile. Interestingly, TF search analysis suggested that rs3761548 SNP is located in the core of “GGGCGG” sequences of putative DNA binding site for the transcription factor specificity protein-1 (sp-1). The transcription factor SP1 consists of a zinc finger protein motif (Kolell and Crawford, 2002). The sp-1 binds directly to DNA through zinc finger protein motif and enhances gene transcription (Kolell and Crawford, 2002). It could be speculated that rs3761548 variant may affect the interaction of sp-1 protein with FOXP3 promoter, and, therefore may be risk associated with the clinical outcome of ESRD/ARE. The probable mechanism behind the observed association of tag-SNPs of NF-kB1 namely; rs28362491 and rs696 seems to be correlated with the expression and activity of NF-kB1, which regulates important cellular events like apoptosis and cell death independent of the NF-κB complex (Yu et al., 2009). Recently, it has been reported that rs28362491 tag-SNP in the promoter region of NF-κB1 has regulatory influence on NF-κB1 gene expression and that the activity of the insertion (ATTG1) allele is twice as high as that of the deletion (ATTG2) allele (Karban et al., 2004). A functional study has proposed that mutant alleles of 3'UTR of NF-kB1 gene significantly decreased NF-κB1A mRNA stability (Song et al., 2011). Thus, it may be speculated that the difference in the expression of NF-kB1 gene due to its promoter and 3′UTR variants may alter the risk for clinical outcome of ESRD and ARE. The signal transducer and activator of transcription-5 (STAT5) binds with upstream regions (5′UTR) of FOXP3 gene suggesting interleukin2Rβ (IL-2Rβ)-dependent STAT5 activation which promotes Treg cell differentiation by regulating expression of FOXP3 (Burchill et al., 2007). Calcium/NFAT (nuclear factor of activated T lymphocytes) pathway is a part of signaling cascade, which has been proposed to be a novel regulator of nephrogenesis (Burn et al., 2011). Calcium/NFAT pathway is vital for the development and regulation of function of Treg cells. The upstream region of FOXP3 gene is highly conserved, which is located at 6.5-kb upstream region of this gene. The upstream region consists of classic TATA and CAAT-box-containing sequence, which is activated in response to T cell receptor (TCR) signaling through binding of NFAT and activator protein-1 (AP-1) (Mantel et al., 2006). The non-coding upstream region of FOXP3 gene have transforming growth factor beta (TGFβ)-sensitive element that contains binding sites for NFAT and Sterile alpha motif (SAM) domains (SMADs) (Tone et al., 2008). It may be anticipated that the gene sequence variation in the upstream region of FOXP3, may be due to the SNPs rs2232365, rs3761548 and rs5902434 located in the upstream region, hence, may influence IL-2Rβ-dependent STAT5 and calcium/NFAT pathways. The deregulation in IL-2Rβ-dependent STAT5 and calcium/NFAT pathways may interfere with the development and regulatory function of Treg cells, hence, may contribute to the clinical outcome of ESRD/ARE. The rs2294021 tag-SNP is positioned within the coiled-coil domain containing 22 (CCDC22) genes, indeed close to the FOXP3 gene in the opposite direction but in an intron that is not overlapping with FOXP3 sequences (http://www.ncbi.nlm.nih.gov/projects/SNP/snp_ref.cgi? rs=2294021). CCDC22 participates in NF-κB activation, which is a master regulator of inflammation (Starokadomskyy et al., 2013). Previously, it has been reported that the deficiency of CCDC22 in human is responsible for blunts activation of pro-inflammatory NF-κB signaling (Starokadomskyy et al., 2013). The conserved regulatory sequences of CCDC22 gene within 3'UTRs and the specific elements binding to them are responsible for the post-transcriptional regulation of gene expression. Therefore, the alteration in CCDC22 gene expression, due to rs2294021 SNP in 3′UTR may influence the inflammatory pathway, which is regulated by NF-κB and may alter the risk for clinical outcome of ESRD and ARE. Since CCDC22 gene is positioned in the complementary strand and in close proximity to FOXP3 gene, which is a master regulator of Treg cells, it is possible that such SNPs may be of relevance to the function of FOXP3. The limitation of our study is that we have not carried out functional analysis for these genetic variants which were significantly correlated at
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genomic levels with susceptibility and prognosis of ESRD and renal allograft outcome. However, we performed in silico analysis to understand the functional relevance of tag-SNPs in promoter region of FOXP3. Correlation of genetic variants with blood levels of FOXP3 and NF-κB proteins in ESRD and renal allograft recipients may be informative. The pharmacologic interventions that alter these concentrations could be examined for their role in risk prediction of ESRD and renal allograft outcome. 5. Conclusions To conclude, our study has found an association of FOXP3 namely; rs2232365 and rs3761548 along with NF-kB1 namely; rs28362491 and rs696 with increased risk to ESRD, acute rejection episodes and renal allograft survival. Present study is a preliminary study, which consists of important observations and needs further studies in an independent cohort to confirm these findings. Although limited by small geographic region and number of subjects, this study has the potential of translational in the clinic and may provide better care for patients harboring these mutant variants. If confirm in subsequent studies, these markers of FOXP3 and NF-kB1 may act as predictive markers for the prognosis of ESRD and renal allograft outcome. Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.gene.2016.01.028. Disclosures The authors declare that there exist no competing financial interests of any kind. Acknowledgments We are thankful to the Department of Biotechnology, Government of India, New-Delhi for providing the financial support through Bioinformatics infrastructure facility (BIF) research grant to carry out this work References Amirzargar, A., Lessanpezeshki, M., Fathi, A., Amirzargar, M., Khosravi, F., Ansaripour, B., Nikbin, B., 2005. TH1/TH2 cytokine analysis in Iranian renal transplant recipients. Transplant. Proc. 37, 2985–2987. Ando, M., Shibuya, A., Yasuda, M., Azuma, N., Tsuchiya, K., Akiba, T., Nitta, K., 2005. Impairment of innate cellular response to in vitro stimuli in patients on continuous ambulatory peritoneal dialysis. Nephrol. Dial. Transplant. 20, 2497–2503. Barrett, J.C., Fry, B., Maller, J., Daly, M.J., 2005. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 21, 263–265. Bluestone, J.A., Abbas, A.K., 2003. Natural versus adaptive regulatory T cells. Nat. Rev. Immunol. 3, 253–257. Borm, M.E., van Bodegraven, A.A., Mulder, C.J., Kraal, G., Bouma, G., 2005. A NFKB1 promoter polymorphism is involved in susceptibility to ulcerative colitis. Int. J. Immunogenet. 32, 401–405. Bossowski, A., Borysewicz-Sanczyk, H., Wawrusiewicz-Kurylonek, N., Zasim, A., Szalecki, M., Wikiera, B., Barg, E., Mysliwiec, M., Kucharska, A., Bossowska, A., Goscik, J., Ziora, K., Gorska, M., Kretowski, A., 2014. Analysis of chosen polymorphisms in FoxP3 gene in children and adolescents with autoimmune thyroid diseases. Autoimmunity. Burchill, M.A., Yang, J., Vogtenhuber, C., Blazar, B.R., Farrar, M.A., 2007. IL-2 receptor beta-dependent STAT5 activation is required for the development of Foxp3 + regulatory T cells. J. Immunol. 178, 280–290. Burn, S.F., Webb, A., Berry, R.L., Davies, J.A., Ferrer-Vaquer, A., Hadjantonakis, A.K., Hastie, N.D., Hohenstein, P., 2011. Calcium/NFAT signalling promotes early nephrogenesis. Dev. Biol. 352, 288–298. Chakir, H., Wang, H., Lefebvre, D.E., Webb, J., Scott, F.W., 2003. T-bet/GATA-3 ratio as a measure of the Th1/Th2 cytokine profile in mixed cell populations: predominant role of GATA-3. J. Immunol. Methods 278, 157–169. Chorley, B.N., Wang, X., Campbell, M.R., Pittman, G.S., Noureddine, M.A., Bell, D.A., 2008. Discovery and verification of functional single nucleotide polymorphisms in regulatory genomic regions: current and developing technologies. Mutat. Res. 659, 147–157. de Bakker, P.I., Yelensky, R., Pe'er, I., Gabriel, S.B., Daly, M.J., Altshuler, D., 2005. Efficiency and power in genetic association studies. Nat. Genet. 37, 1217–1223. Dong, C., 2008. TH17 cells in development: an updated view of their molecular identity and genetic programming. Nat. Rev. Immunol. 8, 337–348. Foley, R.N., Collins, A.J., 2007. End-stage renal disease in the United States: an update from the United States Renal Data System. J. Am. Soc. Nephrol. 18, 2644–2648.
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