Skip to main content
Download PDF

Gene polymorphisms of VEGF and KDR are associated with initial fast peritoneal solute transfer rate in peritoneal dialysis

BMC Nephrology volume 23, Article number: 365 (2022) Cite this article

Abstract

Background

Peritoneal dialysis (PD) is an effective and successful renal replacement therapy. The baseline peritoneal solute transfer rate (PSTR) is related to local membrane inflammation and may be partially genetically determined. Herein, we focused on vascular endothelial growth factor (VEGF) and its receptor, kinase insert domain containing receptor (KDR).

Methods

This study recruited 200 PD patients from Renji Hospital in Shanghai, China. We analysed the association between the polymorphisms of VEGF and KDR and the 4-hour dialysate-to-plasma ratio for creatinine (4 h D/P Cr), which was measured between one and three months after initiating PD.

Results

The CC genotype in VEGF rs3025039 and the AA genotype in KDR rs2071559 were both positively associated with a fast baseline PSTR (VEGF rs3025039 CC vs. TT + TC: 0.65 ± 0.12 vs. 0.61 ± 0.11; P = 0.029; KDR rs2071559 AA vs. GA + GG: 0.65 ± 0.12 vs. 0.62 ± 0.12; P = 0.039).

Conclusion

Baseline PSTR was partly determined by VEGF and KDR gene polymorphisms.

Peer Review reports

Background

Peritoneal dialysis (PD) is an effective and important treatment for renal replacement in patients with end-stage renal disease (ESRD). Studies from all regions of the world have shown that faster baseline peritoneal solute transfer rate (PSTR) is related to higher risk for technology failure and death [1,2,3,4].

The characteristics of peritoneal baseline transport depend on the structure and function of the pre-dialysis peritoneum, which is related to race, age, sex, and underlying disease [5]. However, only 5–11% of the total interindividual variability in the PSTR can be explained by these demographic or clinical variables. Local peritoneal membrane inflammation seems to play an important role in this process. Dialysate IL-6 is the marker with the strongest known association with PSTR, whereas systemic inflammation is associated with comorbidity and patient survival [6,7,8]. Evidence from several small single-centre studies shows that some of the between-patient variation may be accounted for by genetic factors related to proinflammatory factors [9, 10].

Neovascularization contributes to both initial fast PSTR and fast PSTR in long -term PD. Although more studies have focused on neovascularization in long-term exposure in PD, several studies have shown higher concentrations of VEGF and KDR in peritoneal tissue in PD patients with initial high/high average transport than in patients with low/low average transport, which means that local expression of VEGF and KDR in peritoneal tissue can affect peritoneal baseline transport by increasing the number of new peritoneal vessels and increasing inflammation status [11, 12].

Vascular endothelial growth factor (VEGF) and its main receptor vascular endothelial growth factor receptor-2 (VEGFR2, or kinase insert domain containing receptor, KDR) are key factors involved in angiogenesis and inflammation [13]. Single-nucleotide polymorphisms (SNPs) mainly refer to polymorphisms of DNA sequences caused by variations in single nucleotides at the genome level, which may affect the function of proteins and lead to disease. SNPs of VEGF and KDR have been reported to be related to many diseases, including tumours, by participating in angiogenesis [14,15,16,17,18,19,20,21].

Therefore, we speculate that SNPs may affect the expression of VEGF and KDR in peritoneal tissue at the gene level, thus causing differences in the baseline PSTR by affecting the number of blood vessels and the inflammatory state.

The aim of this study was to investigate the genetic association between VEGF and KDR gene polymorphisms and the type of baseline PSTR in PD patients and to try to find a reliable genetic locus that can predict initial high peritoneal transport, thereby revealing the characteristics of peritoneal transfer in the early stage.

Methods

Clinical characteristics of the study population

In this study, a total of 200 patients starting PD from January 1, 2004, to January 31, 2014, in the Department of Nephrology, Renji Hospital, Shanghai Jiaotong University, School of Medicine were included.

The inclusion criteria were as follows:

(1) Han Chinese;

(2) PD started within 3 months after catheter implantation;

(3) data available from the first peritoneal equilibration test (PET) between 1 and 3 months of starting PD;

(4) agreed to participate in the study.

Patients who were on long-term haemodialysis or who underwent transplantation before the current PD episode were excluded.

Measurement of peritoneal transfer rate

Classic 2.5% PET was performed between 1 and 3 months after PD initiation in all patients. The primary results were expressed as the 4-hour dialysate-to-plasma ratio for creatinine (4 h D/P Cr).

According to the 4 h D/P Cr, patients were classified into four transport types: high transport status (H, 4 h D/P Cr > 0.8), high average transport status (HA, 4 h D/P Cr 0.65–0.8), low average transport status (LA, 4 h D/P Cr 0.5–0.64), and low transport status (4 h D/P Cr < 0.5). In this study, we divided the patients into two groups: the H/HA transporter group and the L/LA transporter group.

SNP selection

Six SNPs of VEGF and seven SNPs of KDR were obtained from International HapMap Project Databases (Fig. 1; Table 1). The screening conditions and scope were as follows: Han Chinese in Beijing & Southern Han Chinese (CHB&CHS); the gene was amplified by 2000 bp upstream and 1000 bp downstream; minor allele frequency (MAF) > 0.05; r2 > 0.8; there was no linkage disequilibrium between each other. We used the Hardy Weinberg equilibrium (HWE) test for all the alleles in all samples as well as each group. If the P value < = 0.001, we considered the allele was not in conformity with the HWE in this population and would not use it for further analysis.

Fig. 1
figure 1

Gene location of tag-SNPs in VEGF and KDR

Full size image
Table 1 Selected SNPs of VEGF and KDR
Full size table

SNP genotyping

Venous blood was collected at the time of PD initiation. DNA was extracted according to the standard process using Wizard® Genomic DNA Purification Kit. The SNPs of VEGF and VEGFR2 were genotyped by a single-base primer extension assay. The sequences of the primers were shown in Table 2. The genomic DNA flanking the SNP was amplified by standard polymerase chain reaction (PCR) using forward and reverse primer pairs. The PCR machine was MJ Research PT-100, and the ABI PRISM® SNaPshot™ Multiplex Kit was used.

Table 2 Sequences of the primers of PCR
Full size table

Statistical analysis

The data were analysed by SPSS 25 and Prism 9. Categorical data are presented as the frequency (percentage); normally distributed continuous data are presented as the mean ± SD, and nonnormally distributed continuous data are expressed as the median (interquartile space). T tests and one-way ANOVA were used to analyse and compare the normally distributed data, and the Wilcoxon rank sum test was used to analyse and compare the nonnormally distributed data. The composition ratio of counting data was analysed and compared by the chi-square test. P < 0.05 was considered statistically significant.

Results

Clinical characteristics of the PD patients

According to the 4 h D/P Cr of their first PET, 94 patients had high/high average transporters, while 104 had low/low average transporters. The baseline clinical characteristics of the patients were shown in Table 3. H/HA transporters had lower haemoglobin (97.95 ± 21.48 vs. 106.21 ± 20.74, P = 0.006), serum albumin (34.55 (31.10, 38.80) vs. 36.49 (33.88, 40.10)) and ultrafiltration (-41.79 ± 595.13 vs. 227.89 ± 525.81) than L/LA group transporters. However, there were no significant differences in sex, age, BMI, underlying diseases (diabetes, hypertension), CRP, urine, urea clearance index (Kt/V) or normalized protein catabolic rate (nPCR) between the two groups.

Table 3 Clinical characteristics of the 200 PD patients
Full size table

Association between VEGF polymorphisms and PSTR

The frequency and distributions of genotypes in VEGF are shown in Fig. 2a. The allelic distributions were all in conformity with Hardy-Weinberg equilibrium.

As shown in Fig. 2a, there was no significant association between D/P Cr and VEGF polymorphisms in rs10434, rs2010963, rs25648, rs3025053 and rs699947. VEGF SNPs in rs3025039 were significantly associated with PSTR.

In the rs3025039 polymorphism (Fig. 2b), patients with the CC genotype were related to higher D/P Cr (CC vs. TT + TC: 0.65 ± 0.12 vs. 0.61 ± 0.11; P = 0.029).

Fig. 2
figure 2

(a) VEGF polymorphisms and D/P Cr. M: alteration allele; m: reference allele.(b) rs3025239 genotypes and D/P Cr

Full size image

Moreover, we found that CC carriers had an increased H/HA transport status risk compared to TT and TC carriers (OR 0.36; 95% CI 0.19–0.65; P = 0.0007) (Table 4). The T alleles appear to decrease the genetic susceptibility to a lower transport status compared to C alleles.

Table 4 rs3025239 genotype in the H/HA and L/LA groups
Full size table

As shown in Table 5, there were no significant differences in age\BMI\Hb\Alb\CRP\UF\urine between rs3025039 polymorphisms. A total of 21.79% of CC carriers had diabetes, while the rate of TT or TC carriers was 15.57%. Patients with TT/CT had a higher Kt/V than those with the CC genotype.

Table 5 Association between clinical characteristics and rs3025039 genotype
Full size table

Association between KDR polymorphisms and peritoneal transport status

We also examined the association between KDR polymorphisms and the 4 h D/P Cr. The allelic distributions were all in conformity with Hardy-Weinberg equilibrium.

Among the seven selected tagSNPs in the KDR gene, rs2071559 was shown to be associated with the 4 h D/P Cr, while the other six SNPs in rs1870377, rs2305945, rs2305948, rs28517645, rs41483145 and rs683773 had no effect on the 4 h D/P Cr (Fig. 3a).

Patients carrying two minor alleles at rs2071559 (AA genotype) had a significantly higher D/P Cr than those carrying the GG or GA genotype (AA vs. GG + GA: 0.65 ± 0.12 vs. 0.62 ± 0.12; P = 0.036) (Fig. 3b).

Fig. 3
figure 3

(a) KDR polymorphisms and D/P Cr. M: alteration allele; m: reference allele. (b) rs2071559 genotypes and D/P Cr

Full size image

Furthermore, H/HA transport status patients had a remarkably higher frequency of the AA genotype than L/LA transport status patients (OR 0.56; 95% CI 0.31–0.99; P = 0.045) (Table 6). The G allele was shown to be associated with an increased risk of L/LA transport status compared to the A allele.

Table 6 rs2071559 genotype in the H/HA and L/LA groups
Full size table

There were no significant differences between the GG + GA and AA genotypes of rs2071559 in age, BMI, Hb, Alb, CRP, UF or urine volume. A total of 23.46% of AA carriers had diabetes, which was higher than the proportion of GG or GA carriers (14.29%). However, AA carriers had a significantly higher Kt/V than GG and GA carriers (Table 7).

Table 7 Association between clinical characteristics and rs2071559 genotype
Full size table

Discussion

In this study, we analysed the association between baseline PSTR and genetic polymorphisms of two genes (VEGF and KDR) in a Chinese Han population. The results showed that SNPs of rs3025039 in VEGF and SNPs of rs2071559 in KDR were significantly associated with initial 4 h D/P Cr. Genetic factors related to neovascularization are related to the initial PSTR in PD.

Fast initial peritoneal transport status is an independent risk factor for long-term prognosis in patients with PD. Meta-analysis showed that for every 0.1 increase in the dialysate over plasma ratio for creatinine (D/P Cr), the relative risk of death increased by 1.15-fold, which was equivalent to a 21.9% increase in low average transporters, a 45.7% increase in high average transporters and a 77.3% increase in high transport of the patients compared with the low transport patients. For every 0.1 increase in the D/P Cr, the risk of death associated with technology failure increased by 1.18-fold [22].

The pathophysiological mechanism of late acquired high transport induced by long-term peritoneal dialysis is different from that of early inherent high transport [23, 24]. After initiating PD, significant changes occur in the transport characteristics, which may be due to the differences in the structure and function of the peritoneum before dialysis; these differences mainly manifest as microvascular endothelial function and microinflammation of the peritoneum [11, 25]. Genetic factors are involved in determining initial peritoneal status. Previous studies in our centre have shown that the gene polymorphisms of vascular-related TIE2(rs639225) and inflammation-related IL-6(rs13306345) are associated with high initial peritoneal transport [26].

The VEGF gene is located on chromosome 6p21.3, containing and contains 8 exons and 7 introns. It belongs to the VEGF/platelet-derived growth factor gene family, also known as the growth factor cystine superfamily [27]. VEGF is an important regulatory factor in endothelial cell physiology and a major specific growth factor of endothelial cells [28, 29]. VEGF affects the inflammatory environment by acting as a proinflammatory cytokine through its ability to act as a monocyte chemotactic agent [30].

To date, VEGF gene polymorphisms have been confirmed to be associated with a variety of diseases by participating in angiogenesis. The rs3025039 polymorphism was found to be associated with elevated plasma VEGF levels in glioma and many other cancers [14,15,16,17, 29, 31].

The biological function of VEGF is achieved through its receptor, mainly for KDR [13]. The KDR gene is located in chromosomal region 4q11-q12 and contains 26 exons [27]. It is mainly expressed in vascular endothelial cells and lymphatic vessels and is the main receptor in the angiogenesis signalling pathway. The gene polymorphisms of rs2071559 were also reported to be associated with tumour recurrence [20].

The two SNPs rs3025039 of VEGF and rs2071559 of KDR, which were found to be associated with initial higher peritoneal transport status, are located in the 3’UTR and upstream, which belong to the noncoding region. Although this region cannot encode proteins, it is indispensable for the expression of genetic information. The nucleotide sequences can regulate the expression of genetic information to have genetic effects. Genetic variation due to gene polymorphisms in noncoding regions may partially explain the significant association between SNPs of the two tested genes and initial peritoneal high transport risk. ESRD patients with the CC genotype of rs3025039 in VEGF or the AA genotype of rs2071559 in KDR are more likely to have a congenital high transport type that may be associated with a poor outcome. Such patients may require a more comprehensive evaluation before dialysis, and perhaps haemodialysis or early intervention through peritoneal dialysis may improve the outcome.

This study also has some limitations. First, our study was conducted in a single population, so our results may not be applicable to other populations due to genetic variation. Second, our study is a single-centre study with a small sample size. Therefore, in future research, we will include patients from multiple centres, increase the sample size, and try to measure the concentration of VEGF and KDR in the initial peritoneum. Tag-SNPs may not completely cover all the genetic variants, and some existing SNPs of VEGF or KDR were not included. Furthermore, the coreceptor neuropilin-1 (Nrp-1) can enhance the effect of VEGF binding to KDR, which plays an important role in the mesothelial to mesenchymal transition (MMT) in long-term PD and causes peritoneal membrane dysfunction [32]. In future studies, we will further study the SNPs of Nrp-1 and focus on the corresponding pathways of SNPs.

At present, the gene polymorphisms of VEGF and KDR are mainly used in the field of cancer. In this study, we investigated for the first time the genetic association between the initial PD transport status and VEGF/KDR. The CC genotype of rs3025039(VEGF) and AA genotype of rs2071559(KDR) could be predictors of initial high transport status, and allele T of rs3025039 or allele G of rs2071559 were associated with the occurrence of initial lower transport status. These results suggest that VEGF and KDR may be used as genetic markers to identify the initial fast PSTR.

Conclusion

The baseline PSTR was partly determined by VEGF and KDR gene polymorphisms. The CC genotype of rs3025039(VEGF) and AA genotype of rs2071559(KDR) could be predictors of initial high transport status.

Data availability

The datasets during and/or analysed during the current study available from the corresponding author on reasonable request.

Abbreviations

PD:

Peritoneal dialysis

PSTR:

Peritoneal solute transfer rate

VEGF:

Vascular endothelial growth factor

KDR:

Kinase insert domain containing receptor

ESRD:

End-stage renal disease

SNP:

Single nucleotide polymorphism

PET:

Peritoneal equilibration test

4 h D/P Cr:

4-hour dialysate-to-plasma ratio for creatinine

CHB&CHS:

Han Chinese in Beijing & Southern Han Chinese

MAF:

Minor allele frequency

HWE:

Hardy Weinberg equilibrium

PCR:

Polymerase chain reaction

H:

High transport status

HA:

High average transport status

LA:

Low average transport status

L:

Low transport status

BMI:

Body mass index

Hb:

Haemoglobin

Alb:

Serum albumin

CRP:

C reactive protein

UF:

Ultrafiltration

Kt/V:

Urea clearance index

nPCR:

Normalized protein catabolic rate

References

  1. Churchill DN, Thorpe KE, Nolph KD, Keshaviah PR, Oreopoulos DG, Pagé D. Increased peritoneal membrane transport is associated with decreased patient and technique survival for continuous peritoneal dialysis patients. The Canada-USA (CANUSA) Peritoneal Dialysis Study Group. J Am Soc Nephrol. 1998;9:1285–92. https://doi.org/10.1681/ASN.V971285.

    Article  CAS  PubMed  Google Scholar 

  2. Davies SJ, Phillips L, Griffiths AM, Russell LH, Naish PF, Russell GI. Impact of peritoneal membrane function on long-term clinical outcome in peritoneal dialysis patients. Perit Dial Int. 1999;19(Suppl 2):91–4.

    Article  Google Scholar 

  3. Rumpsfeld M, McDonald SP, Johnson DW. Higher peritoneal transport status is associated with higher mortality and technique failure in the Australian and New Zealand peritoneal dialysis patient populations. J Am Soc Nephrol. 2006;17:271–8. https://doi.org/10.1681/ASN.2005050566.

    Article  PubMed  Google Scholar 

  4. Chung SH, Heimbürger O, Lindholm B. Poor outcomes for fast transporters on PD: the rise and fall of a clinical concern. Semin Dial. 2008;21:7–10. https://doi.org/10.1111/j.1525-139X.2007.00327.x.

    Article  PubMed  Google Scholar 

  5. Rumpsfeld M, McDonald SP, Purdie DM, Collins J, Johnson DW. Predictors of baseline peritoneal transport status in Australian and New Zealand peritoneal dialysis patients. Am J Kidney Dis. 2004;43:492–501. https://doi.org/10.1053/j.ajkd.2003.11.010.

    Article  PubMed  Google Scholar 

  6. Lambie M, Chess J, Donovan KL, Kim YL, Do JY, Lee HB, et al. Independent effects of systemic and peritoneal inflammation on peritoneal dialysis survival. J Am Soc Nephrol. 2013;24:2071–80. https://doi.org/10.1681/ASN.2013030314.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Pecoits-Filho R, Carvalho MJ, Stenvinkel P, Lindholm B, Heimbürger O. Systemic and intraperitoneal interleukin-6 system during the first year of peritoneal dialysis. Perit Dial Int. 2006;26:53–63.

    Article  CAS  PubMed  Google Scholar 

  8. Yang X, Zhang H, Hang Y, Yan H, Lin A, Huang J, et al. Intraperitoneal interleukin-6 levels predict peritoneal solute transport rate: a prospective cohort study. Am J Nephrol. 2014;39:459–65. https://doi.org/10.1159/000362622.

    Article  CAS  PubMed  Google Scholar 

  9. Gillerot G, Goffin E, Michel C, Evenepoel P, Biesen WV, Tintillier M, et al. Genetic and clinical factors influence the baseline permeability of the peritoneal membrane. Kidney Int. 2005;67:2477–87. https://doi.org/10.1111/j.1523-1755.2005.00357.x.

    Article  PubMed  Google Scholar 

  10. Hwang YH, Son MJ, Yang J, Kim K, Chung W, Joo KW, et al. Effects of interleukin-6 T15A single nucleotide polymorphism on baseline peritoneal solute transport rate in incident peritoneal dialysis patients. Perit Dial Int. 2009;29:81–8.

    Article  CAS  PubMed  Google Scholar 

  11. Teng L, Chang M, Liu S, Niu M, Zhang Y, Liu X, et al. Peritoneal microvascular endothelial function and the microinflammatory state are associated with baseline peritoneal transport characteristics in uremic patients. Int Urol Nephrol. 2015;47:191–9. https://doi.org/10.1007/s11255-014-0775-1.

    Article  CAS  PubMed  Google Scholar 

  12. Zhang AH, Wang G, Zhang DL, Zhang QD, Liu S, Liao Y, et al. Association between VEGF receptors and baseline peritoneal transport status in new peritoneal dialysis patients. Ren Fail. 2012;34:582–9. https://doi.org/10.1007/s00018-005-5426-3.

    Article  CAS  PubMed  Google Scholar 

  13. Cébe-Suarez S, Zehnder-Fjällman A, Ballmer-Hofer K. The role of VEGF receptors in angiogenesis; complex partnerships. Cell Mol Life Sci. 2006;63:601–15. https://doi.org/10.1016/j.gene.2017.07.027.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Liu B, Wei J, Li M, Jiang J, Zhang H, Yang L, et al. Association of common genetic variants in VEGFA with biliary atresia susceptibility in Northwestern Han Chinese. Gene. 2017;628:87–92. https://doi.org/10.22034/APJCP.2017.18.7.1799.

    Article  CAS  PubMed  Google Scholar 

  15. Naikoo NA, Afroze D, Rasool R, Shah S, Ahangar AG, Bhat IA, et al. SNP and Haplotype Analysis of Vascular Endothelial Growth Factor (VEGF) Gene in Lung Cancer Patients of Kashmir. Asian Pac J Cancer Prev. 2017;18:1799–804. https://doi.org/10.2147/HP.S117967.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Buroker NE, Ning XH, Zhou ZN, Li K, Cen WJ, Wu XF, et al. SNPs, linkage disequilibrium, and chronic mountain sickness in Tibetan Chinese. Hypoxia (Auckl). 2017;5:67–74. https://doi.org/10.1186/s12943-016-0497-3.

    Article  CAS  Google Scholar 

  17. Bekes I, Friedl TW, Köhler T, Möbus V, Janni W, Wöckel A, et al. Does VEGF facilitate local tumor growth and spread into the abdominal cavity by suppressing endothelial cell adhesion, thus increasing vascular peritoneal permeability followed by ascites production in ovarian cancer? Mol Cancer. 2016;15:13. https://doi.org/10.3390/genes9120631.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Furuya TK, Jacob CE, Tomitão MTP, Camacho LCC, Ramos MFKP, Eluf-Neto J, et al. Association between Polymorphisms in Inflammatory Response-Related Genes and the Susceptibility, Progression and Prognosis of the Diffuse Histological Subtype of Gastric Cancer. Genes (Basel). 2018;9:631. https://doi.org/10.1007/s12035-015-9240-0.

    Article  CAS  Google Scholar 

  19. Zhang J, Yang J, Chen Y, Mao Q, Li S, Xiong W, et al. Genetic Variants of VEGF (rs201963 and rs3025039) and KDR (rs7667298, rs2305948, and rs1870377) Are Associated with Glioma Risk in a Han Chinese Population: a Case-Control Study. Mol Neurobiol. 2016;53:2610–8. https://doi.org/10.1111/j.1349-7006.2011.02194.x.

    Article  CAS  PubMed  Google Scholar 

  20. Dong G, Guo X, Fu X, Wan S, Zhou F, Myers RE, et al. Potentially functional genetic variants in KDR gene as prognostic markers in patients with resected colorectal cancer. Cancer Sci. 2012;103:561–8. https://doi.org/10.1093/annonc/mdp452.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Kim DH, Xu W, Kamel-Reid S, Liu X, Jung CW, Kim S, et al. Clinical relevance of vascular endothelial growth factor (VEGFA) and VEGF receptor (VEGFR2) gene polymorphism on the treatment outcome following imatinib therapy. Ann Oncol. 2010;21:1179–88. https://doi.org/10.3109/0886022X.2012.669322.

    Article  CAS  PubMed  Google Scholar 

  22. Brimble KS, Walker M, Margetts PJ, Kundhal KK, Rabbat CG. Meta-analysis: peritoneal membrane transport, mortality, and technique failure in peritoneal dialysis. J Am Soc Nephrol. 2006;17:2591–8. https://doi.org/10.1681/ASN.2006030194.

    Article  PubMed  Google Scholar 

  23. Rodrigues AS, Almeida M, Fonseca I, Martins M, Carvalho MJ, Silva F, et al. Peritoneal fast transport in incident peritoneal dialysis patients is not consistently associated with systemic inflammation. Nephrol Dial Transplant. 2006;21:763–9. https://doi.org/10.1093/ndt/gfi245.

    Article  PubMed  Google Scholar 

  24. Rodrigues R, Martins AS, Korevaar M, Silva JC, Oliveira S, Cabrita JC A, et al. Evaluation of peritoneal transport and membrane status in peritoneal dialysis: focus on incident fast transporters. Am J Nephrol. 2007;27:84–91. https://doi.org/10.1159/000099332.

    Article  CAS  PubMed  Google Scholar 

  25. Gao D, Zhao ZZ, Liang XH, Li Y, Cao Y, Liu ZS. Effect of peritoneal dialysis on expression of vascular endothelial growth factor, basic fibroblast growth factor and endostatin of the peritoneum in peritoneal dialysis patients. Nephrol (Carlton). 2011;16:736–42. https://doi.org/10.1111/j.1440-1797.2011.01502.x.

    Article  CAS  Google Scholar 

  26. Ding L, Shao X, Cao L, Fang W, Yan H, Huang J, et al. Possible role of IL-6 and TIE2 gene polymorphisms in predicting the initial high transport status in patients with peritoneal dialysis: an observational study. BMJ Open. 2016;6:e012967. https://doi.org/10.1136/bmjopen-2016-012967.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Takahashi H, Shibuya M. The vascular endothelial growth factor (VEGF)/VEGF receptor system and its role under physiological and pathological conditions. Clin Sci (Lond). 2005;109:227–41. https://doi.org/10.1042/CS20040370.

    Article  CAS  Google Scholar 

  28. Goligorsky MS. Endothelial cell dysfunction: can’t live with it, how to live without it. Am J Physiol Renal Physiol. 2005;288:F871–80. https://doi.org/10.1152/ajprenal.00333.2004.

    Article  CAS  PubMed  Google Scholar 

  29. Melincovici CS, Boşca AB, Şuşman S, Mărginean M, Mihu C, Istrate M, et al. Vascular endothelial growth factor (VEGF) - key factor in normal and pathological angiogenesis. Rom J Morphol Embryol. 2018;59:455–67.

    PubMed  Google Scholar 

  30. Melder RJ, Koenig GC, Witwer BP, Safabakhsh N, Munn LL, Jain RK. During angiogenesis, vascular endothelial growth factor and basic fibroblast growth factor regulate natural killer cell adhesion to tumor endothelium. Nat Med. 1996;2:992–7. https://doi.org/10.1038/nm0996-992.

    Article  CAS  PubMed  Google Scholar 

  31. Watson CJ, Webb NJ, Bottomley MJ, Brenchley PE. Identification of polymorphisms within the vascular endothelial growth factor (VEGF) gene: correlation with variation in VEGF protein production. Cytokine. 2000;12:1232–5. https://doi.org/10.1006/cyto.2000.0692.

    Article  CAS  PubMed  Google Scholar 

  32. Pérez-Lozano ML, Sandoval P, Rynne-Vidal A, Aguilera A, Jiménez-Heffernan JA, Albar-Vizcaíno P, et al (2013) Functional relevance of the switch of VEGF receptors/co-receptors during peritoneal dialysis-induced mesothelial to mesenchymal transition. PLoS One. 2013;8(4):e60776. https://doi.org/10.1371/journal.pone.0060776.

  33. Clinical T. Registration: www.ClinicalTrials.gov, identifier: NCT04888065.

Download references

Acknowledgements

This work was supported by the Department of Nephrology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University. The authors thank physicians and nurses of the PD centre for technical assistance.

Funding

National Natural Science Foundation of China (82070693, 81770666, 81570604), Shanghai Municipal Health Bureau (201740037), School of Medicine, Shanghai Jiao Tong University (DLY201805). The funders of the study had no role in study design, data collection, data analysis, data interpretation, or writing. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication.

Author information

Authors and Affiliations

  1. Department of Nephrology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China

    Yue Qian, Li Ding, Liou Cao, Zanzhe Yu, Xinghua Shao, Ling Wang, Minfang Zhang, Qin Wang, Xiajing Che, Na Jiang, Hao Yan, Wei Fang, Yan Jin, Jiaying Huang, Aiping Gu & Zhaohui Ni

Authors
  1. Yue Qian
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Li Ding
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Liou Cao
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Zanzhe Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Xinghua Shao
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Ling Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Minfang Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Qin Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Xiajing Che
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Na Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Hao Yan
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Wei Fang
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Yan Jin
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Jiaying Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Aiping Gu
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Zhaohui Ni
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

YQ, LD, ZY and ZN contributed to conception and design. YQ, LD, LC, ZY, XS, LW, MZ, QW, XC, NJ, HY, WF, YJ, JH, AG and ZN contributed to acquisition of data, or analysis and interpretation of data. YQ, LD, LC, ZY, XS, LW, MZ, QW, XC, NJ, HY, WF, YJ, JH, AG and ZN contributed to drafting the manuscript or revising it critically for important intellectual content. All authors reviewed the manuscript.

Corresponding author

Correspondence to Zhaohui Ni.

Ethics declarations

Ethics approval and consent to participate

The study was approved by Shanghai Jiaotong University School of Medicine, Renji Hospital Ethics Committee, NO.2018 − 220. All methods were carried out in accordance with relevant guidelines and regulations.

Informed consent

was obtained from all subjects involved in the present study.

Consent for publication

Consents obtained from study participants were written.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Yue Qian and Li Ding have contributed equally to this work.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Qian, Y., Ding, L., Cao, L. et al. Gene polymorphisms of VEGF and KDR are associated with initial fast peritoneal solute transfer rate in peritoneal dialysis. BMC Nephrol 23, 365 (2022). https://doi.org/10.1186/s12882-022-02975-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12882-022-02975-5

Keywords

BMC Nephrology

ISSN: 1471-2369

Contact us