Association of BAFF/BAFF-R Single Nuclear Polymorphisms with Renal Graft Function in Kidney Transplant Recipients

doi:10.21203/rs.3.rs-1337055/v1

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Association of BAFF/BAFF-R Single Nuclear Polymorphisms with Renal Graft Function in Kidney Transplant Recipients

https://doi.org/10.21203/rs.3.rs-1337055/v1

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The BAFF/BAFF-R signal correlates with antibody-mediated rejection and renal function decline after renal transplantation. We investigated the relationship between BAFF/BAFF-R single nucleotide polymorphisms (SNPs) and renal graft function in kidney transplant recipients. Kidney transplant recipients (310) along with randomly selected healthy control individuals (51) were followed from September 2020 to March 2021 in Third Affiliated Hospital of Soochow University. Anticoagulated peripheral blood and serum were collected from all individuals. Five BAFF/BAFF-R SNPs were genotyped by TaqMan quantitative PCR. According to the estimated glomerular filtration rate (eGFR) cut-off value of 90 mL·min-1·1.73 (m2)-1, the recipients were divided into normal and abnormal eGFR groups. Analysis results revealed that BAFF rs9514828 CT genotype carriers had a significantly higher incidence of abnormal graft kidney function than other genotype carriers (OR = 1.597, 95% CI = 1.012–2.519, P < 0.05) and had no significant correlation with serum soluble BAFF level and positive rate of panel reactive antibodies; There was a strong linkage disequilibrium between the BAFF rs16972194, rs9514828, and rs16972197; Recipients woth haploid GCG had a significantly higher incidence of normal graft function (OR = 0.381, 95% CI = 0.156–0.931, P < 0.05). This present results suggest that BAFF rs9514828 CT genotype may be a risk factor for kidney transplant recipients, resulting in reduced graft function, whereas the GCG haploid may play a protective role in normal graft function.

Single nucleotide polymorphisms (SNPs)

BAFF

BAFF-R

Kidney transplantation

Renal transplantation remains the most viable treatment option for patients with end-stage renal failure. However, the long-term outcomes of renal transplantation remain to be fully elucidated [1]. Several factors are involved in renal allograft function, including the genetic factors of the recipient [2]. Recent studies have made progress in determining the heritable variation associated with common complex diseases by exploring single nucleotide polymorphisms (SNPs) in the genome [3].

The human B-cell-activating factor (BAFF) gene belonging to the tumor necrosis factor family is located on chromosome 13q32–34, it has a length of 2.6 kb, and a specific receptor, namely BAFF-R [4]. The human BAFF-R gene is located on chromosome 22q13.1–13.31 and has a length of 4.5 kb. The BAFF/BAFF-R signal can regulate the survival and activation of B lymphocytes [5], and abnormal signals are closely related to the occurrence and development of several diseases. Additionally, the enhancement of the BAFF signal plays a role in renal transplantation rejection [6].

SNPs in the BAFF and BAFF-R genes have been found to be associated with certain diseases. For instance, BAFF rs16972197 C allele carriers have an increased risk of systemic myasthenia gravis [7], BAFF rs9514828 CT genotype carriers have a decreased risk of chronic lymphocytic leukemia [8], BAFF expression has been found to increase in patients with systemic lupus erythematosus (SLE) with the BAFF rs9514828 T allele [9], an increased frequency of the BAFF rs4000607 AA genotype has been found in Graves’ patients in the UK [10], and BAFF-R rs61756766 GA+AA genotype carriers have an increased risk of multiple sclerosis [11].

Few studies have investigated genomic SNPs in kidney transplant recipients. We selected and analyzed five SNPs, namely BAFF rs16972194, rs9514828, rs16972197, and BAFF-R rs61756766, and rs77874543. The genotype of each SNP was determined and analyzed with respect to the clinical indices of kidney transplant recipients.

This study was approved by the Ethics Committee of Third Affiliated Hospital of Soochow University and informed consent was obtained from the relevant research participants. During the study, followed-up kidney transplant recipients were randomly selected in Jiangsu from September 2020 to March 2021. Basic information such as age, sex, weight, and clinical indices, including routine blood examination, hepatic and renal function, and C-reaction protein, were collected. Peripheral blood was collected (2 ml) from kidney transplant recipients (EDTA anticoagulation), stored at 4 ℃, and analyzed for completion within one week. Additionally, 500 μl of serum was collected and stored at –80 ℃ for future use.

All renal transplant recipients were treated with the combined immunosuppression regimen, more specifically, a combination of tacrolimus/cyclosporine A, mycophenolate/mycophenolate sodium, and glucocorticoids.

Healthy volunteers were routinely selected by medical personnel (excluded individuals were those with abnormal blood, urine, or stool test results, or abnormal cardiopulmonary, kidney, or liver function test results). Anticoagulated peripheral blood and serum were obtained from these healthy volunteers and stored for future use.

The whole genome DNA of each participant was extracted and purified following the extraction kit instructions (TaKaRa, Dalian China). DNA concentration and purity was detected using the NanoDrop 2000 (ThermoScientific, MA, USA). The purified DNA (1.8 < 260/280 ratio < 2.2) was stored at –20 °C for later use.

The five SNPS, namely BAFF rs16972194 (-1283 G>A), rs9514828 (-871 C>T), and rs16972197 (-353 G>C), BAFF-R rs61756766 (475 G>A) and rs77874543 (62 G>C) were tested using specific SNP detection reagents and TaqMan real-time fluorescent quantitative PCR. The PCR reaction system (20 μL) included a 20 ng DNA template, as well as 10 μL 2× Taqman universal PCR master mix (ThermoFisher Scientific) and 1 μL 20× SNP genotyping assay mix (ThermoFisher Scientific). The following reaction parameters were used: denaturation for 15 s at 95 °C, annealing for 90 s at 60 °C, extension for 60 s at 60 °C for a total of 50 cycles. The Taqman^®Genotyper™Software (ThermoFisher Scientific) was used to examine the PCR results and identify each SNP genotype.

Human BAFF PicoKine™ ELISA kits (BOSTER, Wuhan China) were used according to the manufacturer’s instructions to detect the serum concentration of sBAFF.

The Lambda Antigen Tray^TM Mixed kit (One Lamda, CA USA) was used, following the manufacturer’s instructions to screen serum for donor-specific anti-human leukocyte antigen (HLA) antibodies.

All data were analyzed using the SPSS 22.0. The continuous variables were expressed as mean ± standard deviation and analyzed by t-test, whereas the categorical variables were analyzed using the c² test. More specifically, the c² test was used to compare the genotype and allele frequencies between three groups, namely, the recipient, recipient subsets, and the healthy control groups. Statistical significance was set at P < 0.05. SNPstats (http://bioinfo.iconcologia.net/snpstats/start.htm) was used to estimate the Hardy-Weinberg equilibrium, and logistic regression was used to adjust for potential confounders that may have affected the differences between the three groups. Finally, linkage disequilibrium analysis and haploid analysis were performed using Haploview software (version 4.0).

All kidney transplant recipients were Han Chinese from the Jiangsu Province. We enrolled 310 kidney transplant recipients (198 men, 112 women) aged 44.32 ± 19.21 years and 51 healthy control individuals (26 men, 25 women) aged 48.38 ± 12.23 years.

The corrected estimated glomerular filtration rate (eGFR) was calculated using the following formula: eGFR=186 × [Scr]^-1.154 × [age]^-0.203 × [0.742 if female] × 1.233 [12]. The cut-off value was defined as 90 ml·min^-1·1.73 (m²)^-1. All kidney transplant recipients were subsequently divided into two groups, namely the eGFR normal group (140 individuals, eGFR ≥ 90 ml·min^-1·1.73 (m²)^-1) and the eGFR abnormal group (170 individuals, eGFR < 90 ml·min^-1·1.73 (m²)^-1).

Significant differences between the recipient subsets and the control group (Table 1) were found for sex (P < 0.05), but not for age, weight, or postoperative delayed graft function (clinical diagnosis) (P > 0.05).

The Hardy-Weinberg genetic distribution test results revealed that all the kidney transplant recipient genotypes were in accordance with genetic equilibrium (P > 0.05), suggesting that the recipients enrolled in this present study were likely representative of the population (Table 2).

Thereafter, we analyzed the association between BAFF/BAFF-R SNPs genotypes and eGFR using logistic regression analysis after adjusting for sex. The results indicated that recipients with the rs9514828 CT genotype had a significantly higher incidence of abnormal graft function than those with the rs9514828 (CC+TT) genotype in the hybrid model (OR = 1.597, 95% CI = 1.012–2.519, P < 0.05). However, no significance differences were found for the rs16972194 and rs16972197 genotypes in the implicit, dominant, and heterozygous models. The BAFF-R rs61756766 genotype in all recipients comprised the GG mutation, and no statistical differences were observed for the BAFF-R rs7787543 genotype and eGFR under all the genetic models (P > 0.05) (Table 3).

The SNP alleles of the recipient subsets and the control group were also studied, however, significant allele differentiation was not observed (Table 4).

We compared the clinical data of recipients with the BAFF rs9514828CT (CC+TT) genotype and all the other genotypes in the hybrid model. The clinical data included the following parameters: sex, age, duration after kidney transplantation, sBAFF, and positive rate of PRA. No significant differences were found between the genotypes and sBAFF, positive rate of PRA, and other indices for the recipient subsets and control groups (P > 0.05). Additionally, the indices coincided with rs16972194 and rs16972197 carriers. The sBAFF concentration in kidney transplant recipients were notably higher than those in the healthy control individuals, but the difference was not statistically significant (P > 0.05) (Table 5).

The Haploview software (version 4.0) was used for linkage disequilibrium and haplotype analyses. The results revealed that the D’ value was > 0.8 for BAFF rs16972193, rs9514828, and rs16972197, suggesting a strong linkage disequilibrium among the three SNPs (Figure 1). The same analyses showed that three haploids could be formed, namely GCG, GTG, and ACC. Finally, the logistic analysis results revealed a significant difference in the number of kidney transplant recipients with the GCG haploid between the eGFR normal and abnormal groups (P < 0.05), suggesting that kidney transplant recipients with the GCG haploid had a higher eGFR or a significantly lower incidence of abnormal graft function than those with other haploids (Table 6).

With the development of genome-wide association studies, millions of mutations have been discovered, most of which are single nucleotide substitutions [13]. These mutations are also referred to as SNPs. SNPs can occur in any region of the genome which is likely due to various selection pressures that generate single-base mutations in specific regions of the genome, with varying frequencies [14]. There are two types of SNPs, namely synonymous and non-synonymous SNPs. Synonymous SNPs do not alter encoded amino acids, whereas non-synonymous SNPs do alter amino acids and may ultimately influence certain protein properties or functions. Additionally, studies have found that non-synonymous SNPs may also play a regulatory role by interacting with non-coding RNAs [15].

To date, more than 15,000 SNPs of the BAFF gene have been identified, yet fewer than 20 of these SNPs have been intensively studied. In this present study, five BAFF/BAFF-R SNPs were selected, including three BAFF SNPs located in the promoter region and two non-synonymous BAFF-R SNPs. Considering the role of BAFF/BAFF-R signaling in antibody-mediated rejection, the primary purpose of this study was to analyze the correlation between these five SNPs and chronic rejection in kidney transplant recipients. Since the number of pathologically confirmed patients presenting with chronic rejection was limited, we used eGFR as an indicator of graft renal function during the data analyses.

Ultimately, we found that having the BAFF rs9514828 CT genotype may be a risk factor for Han Chinese from the Jiangsu Province, resulting in reduced renal allograft function after kidney transplantation, however, no significant correlation with sBAFF or positive rate of PRA was found. Gottenberg et al. [16] studied 162 French patients with Sjogren’s syndrome and found that patients with the rs9514828 TT genotype had higher levels of sBAFF, which was associated with anti-SSA and anti-SSB antibody levels. Furthermore, Kawasaki et al. [17] studied Japanese patients with SLE and rheumatoid arthritis and found that rs9514828 TT genotype carriers tended to have higher levels of anti-Sm antibodies, and patients with the -871 T allele had significantly higher levels of BAFF mRNA in monocytes. However, several studies related to rs9514828 have not obtained significant results [18,19]. Kompoti et al. [20] found that severely ill patients with the rs61756766 C allele had a lower risk of acquiring sepsis in the ICU, but no association was found between rs61756766 and susceptibility to sepsis in trauma and surgical patients in Greece. In a study of Spanish patients with immunoglobulin A vasculitis, BAFF, APRIL, and BAFF-R SNPs, including BAFF-R rs77874543, were not found to be associated with the pathological mechanisms of the disease [21]. We also examined two non-synonymous BAFF-R SNPs, but did not obtain statistically significant results. We postulate that the different significant genotype results found in these studies may be due to variation in pathological mechanisms or ethnic differences.

The analyses of clinical data for significantly differentiated genotypes in this present study included assessing the association between sBAFF and positive rate of PRA, however, no significant results were obtained.

Currently, only two reports related to BAFF SNPs and kidney transplantation have been published on PubMed. One study assessed Hispanic white kidney transplant recipients and found that BAFF rs12583006 was associated with a higher level of the class II donor specific antibody [22]. The other study investigated BAFF system SNPs (including BAFF, three BAFF receptor SNPs, and APRIL SNPs) in Hispanic white kidney transplant recipients, and found that the APRIL rs3803800 AA genotype may be high risk factor for acute rejection. Compared to GG/GA carriers, recipients with this genotype had a significant acute rejection free time [23]. Interestingly, despite both studies investigating kidney transplant recipients, contrasting results were found. This begs the question: are these different findings related to geographical, or ethnic differences? Ultimately, more data needs to be gathered before drawing such conclusions.

Graft renal function is affected by several factors, and immune rejection caused by alloantigens should be one of the important ones [24], and some evidences suggested that the rate of graft loss caused by antibody-mediated rejection is more than 50% [25]. The successful development of novel immunosuppressants has many benefits for transplant recipients. Belimumab, a specific anti-BAFF monoclonal antibody, has been approved by the US Food and Drug Administration for the treatment of SLE, however, unexpected effects have been observed in some patients [26]. Moreover, belimumab did not meet certain clinical expectations in a phase II trial in kidney transplant recipients [27]. Some studies suggest that differences in belimumab efficacy may be due to individual genetic factors [28]. Ultimately, further research is required to determine whether BAFF SNPs affect the action of BAFF-specific antibody reagents.

Kidney transplant recipients with the GCG haplotype may be prone to abnormal graft function. Indeed, all clinical indices of recipients with the rs16972194 and rs16972197 SNPs were coincident (for all seven kidney transplant recipients). This finding is consistent with the linkage disequilibrium analysis results and our initial hypotheses.

At present, research methods concerning SNPs have seen an increase in quantity and ease of use, resulting in an improved understanding of SNPs. Remarkable strides in SNP research have taken place since the construction of an SNP database [29], completion of protocols for a genome-wide, preponderant SNP network [30], and development of a model to predict tacrolimus levels in pediatric solid organ transplant recipients, by integrating clinical data with genetic factors [31]. The effect of the interaction between different SNPs, and between SNPs and non-coding RNAs (such as miRNA and lncRNA) on the translation, expression, and function of relevant genes forms an important component of SNP research [32,33].

SNPs represent stable genetic alterations in the genome [34]. The present study partially elucidated the correlation between genomic SNPs found in kidney transplant recipients in the Jiangsu Province. We aim to increase the sample size and screen for BAFF SNPs related to chronic rejection, and combine this informaion with the pathological diagnosis. Ultimately, this work will help to establish individual treatment protocols after kidney transplantations to obtain satisfactory long-term outcomes based on genetic variation.

Authors’ contributions (I) HX and XH designed and supervised the project, (II) JC and XH performed the experiments, (III) HX, XH, JC and XR analyzed and interpreted data, (IV) JC and XR collected blood and plasma samples and clinical data, (V) Manuscript writing: all authors, (VI) All authors read and approved the final manuscript.

Funding This work has been funded by the 15^th batch of the “six talent peaks” project in Jiangsu Province, the Science and Technology Project of the Changzhou Health Committee of Jiangsu Province (ZD201761), and the National Natural Science Foundation of China (81272367).

Conflict interests The authors declare that they have no competing interests.

Ethics approval and consent to participate Patient data were anonymized for analysis and the study was approved by the ethical committee of hospital. An explanation of the project was provided to those individuals and participants signed an informed consent form. The informed consent was prepared according to the Declaration of Helsinki principles.

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Table 1. General data of kidney transplant recipients

		eGFR normal group	eGFR abnormal group	Healthy controls	P
Cases（%）		140 (46%)	170 (54%)	51	-
Gender（%）	Male	99 (72%)	99 (58%)	26 (51%)	0.023^*
Gender（%）	Female	41 (28%)	71 (42%)	25 (49%)	0.023^*
Age（y）		45 (45±10)	45（44±10)	45 (45±10)	0.528
Weight（Kg）		61 (61±11)	61 (61±12)	52 (52±13)	0.744
DGF		21（14%）	31（18%）	-	0.448

Note: eGFR: estimated glomerular filtration rate; DGF: delayed graft function. Those kidney transplant recipients are diagnosed as DGF in clinic and treated with dialysis immediately. P < 0.05 is considered to be significant. ^* Differences between male and female of recipients.

Table 2. Hardy-Weinberg Equilibrium test

		Kidney transplant recipients（310 cases）			Healthy controls （51cases）
		N (%)	c²	P	N (%)	c²	P
rs16972194 (-1283G>A)	GG	233 (75%)	0.40	0.87	46 (90%)	4.34	0.11
	GA	70 (23%)			4 (8%)
	AA	7 (2%)			1 (2%)
rs9514828 (-871C>T)	CC	120 (39%)	0.04	0.70	19 (37%)	1.07	0.58
	CT	147 (47%)			27 (53%)
	TT	43 (14%)			5 (10%)
rs16972197 (-353G>C)	GG	233 (75%)	0.40	0.87	46 (90%)	4.34	0.11
	GC	70 (23%)			4 (8%)
	CC	7 (2%)			7 (2%)
rs61756766 (475G>A)	GG	310 (100%)	-	-	50 (98%)	0.005	1
	GA	0			1 (2%)
	AA	0			0
rs77874543 (62G>C)	GG	284 (92%)	3.25	0.26	44 (86%)	1.83	0.4
	GC	24 (7%)			6 (12%)
	CC	2 (1%)			1 (2%)

Note: P < 0.05 is considered to be significant.

Table 3. Correlation analysis of BAFF/BAFF-R SNP genotypes and eGFR value

		eGFR normal group（N %）	eGFR abnormal group (N %)	Healthy controls (N %)	Hybrid model（*XY VS.* XX+YY**）
		eGFR normal group（N %）	eGFR abnormal group (N %)	Healthy controls (N %)	OR（95%CI）	P
rs16972194	GG (YY)	116 (76%)	126（74%）	46（90%）	1.365（0.79-2.358）	0.265
	GA (YX)	31 (21%)	42（25%）	4（8%）
	AA (XX)	5 (3%)	2（1%）	1（2%）
rs9514828	CC (YY)	62 (42%)	58（34%）	19（37%）	1.597（1.012-2.519）	0.044^*
	CT (YX)	69 (45%)	90（53%）	27（53%）
	TT (XX)	21 (14%)	22（13%）	5（10%）
rs16972197	GG (YY)	116 (72%)	126（77%）	46（90%）	1.365（0.79-2.358）	0.265
	GC (YX)	31 (24%)	42（25%）	4（8%）
	CC (XX)	5 (4%)	2（1%）	1（2%）
rs61756766	GG (YY)	140（100%）	170（100%）	50（98%） 1（2%）	-	-
	GC (YX)	0	0
	CC (XX)	0	0
rs77874543	GG (YY)	138（91%）	156（92%）	44（86%）	0.963（0.414-2.237）	0.929
	GC (YX)	13（8.5%）	13（7.6%）	6（12%）
	CC (XX)	1（0.5%）	1（0.4）	1（2%）

Note: eGFR: estimated glomerular filtration rate; OR: odds ratio. P < 0.05 is considered to be significant. ^*Difference between recipients carrying rs9514828 CT and (CT+TT). Y: allele 1. X: allele 2.

Table 4. Alleles comparison of three BAFF SNPs and two BAFF-R SNPs

		eGFR normal group	eGFR abnormal group	Healthy controls	OR	95%CI	χ²	P
rs16972194	G	135（80%））	168（79%）	96（94%）	0.933	0.563~1.547	0.072	0.789
	A	33（20%）	44（21%））	6（6%）	0.933	0.563~1.547	0.072	0.789
rs9514828	C	119（60%）	148（57%）	65（64%）	1.155	0.792~1.682	0.56	0.454
	T	78（40%）	112（43%）	37（36%）	1.155	0.792~1.682	0.56	0.454
rs16972197	G	135（80%）	168（79%）	96（94%）	0.933	0.563~1.547	0.072	0.789
	C	33（20%）	44（21%））	6（6%）	0.933	0.563~1.547	0.072	0.789
rs61756766	G	140（100%）	170（100%）	101（99%）	-		-	-
	A	0	0	1（1%）	-		-	-
rs77874543	G	139（92%）	169（92%）	94（92%）	1.042	0.467~2.326	0.01	0.920
	C	12（18%）	14（8%）	8（8%）	1.042	0.467~2.326	0.01	0.920

Note: eGFR: estimated glomerular filtration rate; OR: odds ratio. P<0.05 is considered to be significant.

Table 5. Comparison analysis of clinical data under hybrid genetic model

SNP	Genotype	Gender（N %）		Age （y）	Duration after KT（Y, min-max, means）	sBAFF (pg/mL）		Positive rate of PRA
SNP	Genotype	Male	Female	Age （y）	Duration after KT（Y, min-max, means）	Recipients	HC	Recipients	HC
rs16972194	GA	48（69%）	22（31%）	47.5±4.4	0.1~8.1， 5.1±3.3	505±392	153±63	80%	9%
rs16972194	GA+AA	150（63%）	90（37%）	44.3±9.9	0.1~22， 4.0±4.1	569±580	259±165	46%	13%
rs9514828	CT	89（61%）	58（39%）	44.2±10.8	0.1~22， 3.9±4.2	620±678	301±195	49%	12%
rs9514828	CC+TT	109（67%）	54（33%）	44.4±10	0.1~22.2， 4.2±4.1	549±586	204±116	40%	8%
rs16972197	GC	48（69%）	22（31%）	47.5±4.4	0.1~8.1， 5.1±3.3	505±392	153±63	80%	9%
rs16972197	GG+CC	150（63%）	90（37%）	44±9.9	0.1~22， 4.0±4.1	586±638	259±165	46%	13%
rs61756766	GA	-	-	-	-	-		-	-
rs61756766	GG+AA	198（64%）	112（36%）	44.3±10.4	0.1~22，4.0±4.2	584±633	248±160	44%	10%
rs77874543	GC	15（63%）	9（37%）	46.3±8	0.3~7.5，2.2±2.1	446±465	221±193	50%	14%
rs77874543	GG+CC	183（64%）	103（36%）	44.1±10.6	0.1~22.2，4.1±4.2	595±644	250±162	44%	7%

Note: SNP: single nuclear polymorphisms; y: year; KT: kidney transplantation; min: minimum duration; max: maximum duration; sBAFF: soluble BAFF; HC: healthy controls; PRA: panel reactive antibody.

Table 6. Haploid analysis of three BAFF SNPs

Haploid	eGFR normal group （N）	eGFR abnormal group （N）	OR	95%CI	P
GCG	38	37	0.381	0.156-0.931	0. 034*
GTG	21	22	0.786	0.371-1.662	0. 528
ACC	5	2	0. 279	0.053-1.473	0. 132

Note: eGFR: estimated glomerular filtration rate; OR: odds ratio; CI: confidence interval.

No competing interests reported.

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Association of BAFF/BAFF-R Single Nuclear Polymorphisms with Renal Graft Function in Kidney Transplant Recipients

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