VEGFR2 Gene Polymorphism Correlates with Deep Venous Thrombosis Risk in Chinese Han Population

Abstract

Objective: To investigate the correlations between three vascular endothelial growth factor 2 (VEGFR2) gene polymorphisms, +1192C>T, +1719T>A, and −604T>C, and deep venous thrombosis (DVT) in Chinese Han population. Methods: We conducted a case-control study, between September 2009 and September 2012, in a Chinese Han population with onset of lower extremity DVT. A total of 135 patients were enrolled in the case group and 156 healthy individuals in the control group. Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) was used to detect the genotype and allele frequencies of the VEGFR2 gene polymorphisms +1192C>T, +1719T>A, and −604T>C. Haplotype analyses were conducted with SHEsis program. Logistic regression was used to detect the risk factors of DVT. Outpatient review and telephone follow-up were conducted to analyze the long-term treatment of DVT patients. Results: The allele and genotype frequencies of −604T>C VEGFR2 polymorphism exhibited significant differences between the case and control groups (both p < 0.05). Haplotype analyses showed remarkable differences between the case and control groups in the distribution frequency of TAC and CTT haplotypes in the VEGFR2 gene (both p < 0.05). Logistic regression analysis showed independent correlation between the incidence of DVT and TAC haplotype in the VEGFR2 gene (p < 0.05). In addition, the TAC haplotype may be a risk factor for DVT treatment failure. Conclusion: Our findings suggest that the VEGFR2 gene −604T>C polymorphism and TAC haplotype are associated with DVT, and the TAC haplotype might affect the efficacy of long-term treatment of DVT patients.

Introduction

Deep venous thrombosis (DVT) is common in hospitalized patients due to immobility, especially due to postoperative immobility (Hansch et al., 2011). DVT is clinically characterized by leg pain, pressing pain, swelling, and positive Homan's signs, including resistance to ankle dorsiflexion or involuntary flexion of the knee. The most severe complication of DVT is pulmonary embolism, which may lead to chest pain, dyspnea, and even death (Kronberger, 2010). The incidence of DVT is expected to increase in the next decades due to aging populations worldwide and increasing DVT risk factors (Patterson et al., 2010).

Common treatments of DVT include anticoagulant therapy, with either low-molecular-weight heparin (LMWH) or unfractionated heparin, and oral administration of vitamin K or warfarin. Other therapies such as leg stockings and thrombectomy are also used in the treatment of DVT (Collaboration, 2010; Oguzkurt et al., 2012). The mechanisms involved in DVT, according to Rudolf Virchow, include hypercoagulability, hemodynamic restriction, and veinal endothelial injury (Esmon, 2009), and other environmental factors such as aging, cancer, and pregnancy are also associated with DVT (Yang and Chan, 2013). Previous studies have reported that gene polymorphisms, such as in IL-10, ApoE, and vascular endothelial growth factor 2 (VEGFR2), also play a major role in the development of DVT (Modarai et al., 2008; Patterson et al., 2013; Tang et al., 2014).

VEGF and VEGFRs are members of platelet-derived growth factor superfamily and play critical roles in the regulation of vascular endothelial cell functions, including vasculogenesis and angiogenesis (Jopling et al., 2014; Ou et al., 2014).

VEGFR2 is a type III transmembrane tyrosine kinase receptor, and cellular signaling through VEGFR2 is important in mediating angiogenesis and vascular permeability and remodeling (Lim et al., 2014). The phosphorylation of VEGFR2 is initiated upon VEGF-A binding to the receptor, leading to a cascade of intracellular signaling events that regulate endothelial cell development, angiogenesis, and vasculogenesis (Park et al., 2013). The VEGFR2 signaling pathway is also associated with the pathology of many diseases such as mitochondrial dysfunction, lymphoma, and other cancers (Levitt et al., 1990; Hao and Rockwell, 2013; Akhavan-Sigari et al., 2014; Gumus et al., 2014).

VEGFR2 is suspected to play a role in the formation and resolution of thrombosis, and thus is linked to DVT, and inhibition of VEGFR2 activity has been used as an important evaluation criterion to assess the effectiveness of thrombosis treatments (Zhang et al., 2011; Alias et al., 2014). Therefore, we found that it was necessary to analyze the relationships between DVT and VEGFR2 gene polymorphisms that could potentially regulate the expression and activity of VEGFR2. And it is of the same importance to analyze the relationship between VEGFR2 gene polymorphisms and DVT treatment efficacy. The aim of our study is to investigate the correlations of three VEGFR2 gene polymorphisms, +1192C>T, +1719T>A, and −604T>C, with DVT in a Chinese Han population.

Materials and Methods

Ethic statement

This study was approved by the Ethics Committee of Jining No. 1 People's Hospital. All study participants provided written informed consent and the study conformed to the Declaration of Helsinki (Holt, 2014).

Study subject

Between September 2009 and September 2012, 135 patients (84 males and 51 females; mean age, 47.8 ± 11.3 years; ranges, 21-77 years old) receiving warfarin therapy with an onset of lower extremity DVT were selected for this study at the Jining No. 1 People's Hospital. The diagnosis of DVT was established using color Doppler ultrasonography and confirmed by venography performed during endovascular treatment in all patients.

Inclusion criteria: (1) lower extremity central or mixed thrombosis was formed; (2) the course of disease was less than 1 week; (3) patients have significant swelling limbs with the difference of limb circumference greater than 5 cm; (4) patients have no surgical contraindications.

DVT caused by secondary factors such as lower extremity venous injury, iliac vein compression syndrome, bedridden, and blood disease was excluded; DVT caused by coagulopathy diseases such as hepatocirrhosis, severe renal dysfunction, cerebral hemorrhage, and peptic ulcer was also excluded; and patients receiving drugs reducing the efficacy of warfarin for DVT treatment (aspirin, phenobarbital, etc.) were also excluded. One hundred and fifty-six healthy individuals (88 males and 68 females; mean age, 46.2 ± 10.9 years; ranges, 21-72 years old) were treated as the control group. All the study subjects were Han Chinese and showed no consanguinity.

Warfarin treatment

All the DVT patients in the case group were orally administrated with warfarin sodium tablets (Qilu Pharmaceutical Co., Ltd.) for anticoagulation therapy. Before warfarin therapy, prothrombin time (PT) and international normalized ratio (INR) were measured, and the fecal occult blood test was conducted. In the early therapy of DVT, a combination of 5 mg/day warfarin and LMWH was administrated; PT and INR were measured 3 days after medication. LMWH therapy was stopped, while warfarin treatment continued when INR reached 2.0-3.0 for 24 h. Regular monitoring of INR lasted for a week and was changed to once a week to four times a week according to the patient's condition, and the dose of warfarin was regulated based on the INR monitoring.

During the treatment, 16 patients had bleeding gums, nose bleeding, and subcutaneous bleeding, and warfarin dosage was regulated to stop bleeding. DVT patients in the case group showed no serious bleeding condition. When the patient was discharged from hospital, the INR reached 2.0-3.0 (Tsiattalos and Patel, 2014).

Therapeutic evaluation

Lightspeed 64 slice CT (General Electric Medical Systems) was used to conduct an angiography recheck; iopamidol (370 mg) was used as an enhanced contrast agent with a total amount of 120 mL and was injected into the cubital vein of patients through a high-pressure syringe for one time in a fast speed of 4-4.5 mL/s and with a delay time of 150 s.

Patients were in supine position; the scanning position was located by conventional method and the scanning range was from iliac bone upper edge to ankle joint (one or two patients according to the condition of their diseases), at a tube voltage of 120 kv, with intelligent milliampere control from 100 to 500 mA, collimator of 0.625 mm, reconstruction thickness of 0.625 mm, and layer distance of 0.625 mm.

After the end of reconstruction, a series of thin layer images were transferred to a CTA 4.4 processing workstation to conduct CTA image postprocessing. Volume rendering, maximum intensity projection, multiplanar reformation, and other postprocessing technologies were used to conduct revascularization and combined with original images to conduct analysis. Iliac vein, external iliac vein, femoral vein, popliteal vein, and posterior tibial vein were used as target blood vessels and the location and shape of thrombosis were determined. Two experienced doctors determined the angiographic results based on the extent of development.

According to the results of physical examination and angiography, the efficacy of DVT treatment is classified into four classes. Excellent: clinical symptoms and skin pigmentation disappear, blood flow recovers, collateral vessels disappear, no contrast agent retention, and smooth vessel wall. Good: relieved clinical symptoms, discomfort occurs during prolonged standing or long walking time, most of blood flow recovers, a small amount of collateral vessels still exist, no significant contrast agent retention, and smooth vessel wall. Moderate: relieved clinical symptoms, part of blood flow recovers, a relatively large amount of collateral vessels still exist, mild contrast agents retention, and less smooth vessel wall. Poor: no improvement of clinical symptoms, no blood flow recovery, a lot of collateral vessels, significant contrast agent retention, and unsmooth wall.

Follow-up

DVT patients were administrated with warfarin. Outpatient review and telephone follow-up were conducted to analyze the long-term treatment of DVT patients. PT and INR were monitored once a week, 4-6 weeks after patients were discharged from the hospital. Then, the monitor time was once a month and changed to 6 weeks, a time when the indexes are stable.

The initial time of follow-up was December 2009 and the closing time of the follow-up was December 2012. A telephone follow-up was conducted every 3 months. The follow-up time lasted 3 months to 3 years. During the follow-up time, the therapy of patient was regarded effective if they scored excellent, good, and moderate. The therapy of patient was regarded ineffective if they scored poor or diagnosed with recurrent thrombosis or pulmonary embolism or DVT syndrome. A total of 83 DVT patients received regular monitoring of PT and INR and their follow-up data were obtained.

Single-nucleotide polymorphism detection

Peripheral venous blood samples (10 mL for each) were collected early morning after fasting for 10-12 h. Ethylenediaminetetraacetic acid (EDTA) was added as anticoagulant. All the blood samples were stored at −80°C. Genomic DNA was isolated from peripheral blood using the TIANGEN DNA Blood kit (Tiangen Biotech Co., Ltd.). Ultraviolet spectrophotometry was used to measure DNA purity and content.

Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) was used to detect the single-nucleotide polymorphism (SNP) variants +1192C>T, +1719T>A, and −604T>C in the VEGFR2 gene. PCR primers were designed by Primer Premier 5.0 software and synthesized by Shanghai Sangon Biotech Company. Primer sequence and length are listed in Table 1. PCR mix (15 μL) contained the following: 1.5 μL 10× PCR buffer, 0.3 μL 10 mM dNTPs, 0.25 μL 10 pmol/μL forward and reverse primers, 0.25 μL 5 U/0.25 mL Taq polymerase, and 1 μL templates, adding distilled water to 15 μL. PCR conditions were as follows: 5 min initial denaturation at 94°C, 35 cycles of 30 s denaturation at 94°C, 30 s annealing at 60°C, and 30 s extension at 72°C, followed by 10 min extension at 72°C. The negative controls contained sterile water instead of DNA template.

Table 1.

Primer Sequences of VEGFR2 +1192C>T, +1719T>A, and −604T>C Variants

SNP	Primer sequences
+1192C>T (rs2305948)
Forward	5′-ACCCAAGTTCCTGACTACAA-3′
Downstream	5′-TGTTTACCAAAGCCCAGATT-3′
+1719T>A (rs1870377)
Forward	5′-TCCACACTTCTCCATTCTTCA-3′
Downstream	5′-CTGCTTCCCTCCTGTATCCTG-3′
−604T>C (rs2071559)
Forward	5′-GCTCTTAATCAGAAAACGCACTTG-3′
Downstream	5′-GGCTAGGCAGGTCACTTCAAA-3′

SNP, single-nucleotide polymorphism; VEGFR2, vascular endothelial growth factor 2.

PCR products were digested with FspI (Toyobo) and the restriction digestion reaction mix was as follows: 6 μL PCR product, 1.5 μL 10× enzyme buffer, 4 U FspI, and sterile double-distilled water was added to a total volume of 15 μL, and the reaction was incubated at 37°C water bath for 16 h. The digested PCR products (3 μL) were mixed with 6× agarose gel loading buffer and separated on 3% agarose gel electrophoresis at 100 V for 15 min, and the separated products were stained with ethidium bromide (EB, 1 μg/mL) for 30 min. Specific restriction enzymes HincII, XspI, and AseI (TaKaRa) were used to identify specific sites in the PCR products, and resultant digested PCR products were identified by gel electrophoresis. ABI 370 Genetic Analyzer (ABI Company) was used to compare the resulting restriction fragments and PCR products to identify the genotype.

Statistical analysis

Statistical analysis was performed using SPSS 18.0 software. Hardy-Weinberg equilibrium was used to confirm the sample representation in the population. Measurement data were expressed as mean ± standard deviation and compared using t-test, while count data were represented by percentage or ratio and compared using the chi-square test. Differences in genotype and allele frequencies between the case group and control group were expressed by odds ratio (OR) and 95% confidence interval (95% CI). SHEsis program was used to analyze each haplotype of +1192C>T, +1719T>A, and −604T>C in the case group and control group. Logistic regression analysis was used to calculate the OR and 95% CI of each genotype to represent the relative risk. All p-values were two sided and p < 0.05 was considered statistically significant.

Results

Genotype and allele frequencies distribution of VEGFR2 gene

The genotype and allele frequencies distribution of the VEGFR2 +1192C>T, +1719T>A, and −604T>C variants is listed in Table 2. Genotype and allele frequencies of VEGFR2 +1192C>T and +1719T>A variants showed no statistical differences within the case group and control group (both p > 0.05). Notably, significant difference in the genotype and allele frequencies of VEGFR2 −604T>C was found between the case group and control group (p < 0.05). The C-allele and CC genotype of the −604T>C variants were associated with an increased risk of DVT (C-allele: OR = 1.604, p < 0.05; CC genotype: OR = 2.568, p < 0.05).

Table 2.

Genotype and Allele Frequencies Distribution of VEGFR2 +1192C>T, +1719T>A, and −604T>C Variants in the Case Group and the Control Group

SNP	Case group (n = 135)	Control group (n = 156)	p	OR	95% CI
+1192C>T			0.18
CC	93 (68.9)	116 (74.4)		1 (Ref.)	1 (Ref.)
CT	34 (25.2)	37 (23.7)	0.62	1.146	0.668-1.966
TT	8 (5.9)	3 (1.9)	0.067	3.326	0.858-12.89
CT+TT	42 (31.1)	40 (25.6)	0.301	1.31	0.785-2.185
C allele	220 (81.5)	269 (86.2)		1 (Ref.)	1 (Ref.)
T allele	50 (18.5)	43 (13.8)	0.12	1.422	0.911-2.219
+1719T>A			0.466
TT	73 (54.1)	93 (59.6)		1 (Ref.)	1 (Ref.)
TA	51 (37.8)	55 (35.3)	0.504	1.181	0.724-1.927
AA	11 (8.1)	8 (5.1)	0.248	1.752	0.670-4.580
TA+AA	62 (45.9)	63 (40.4)	0.341	1.254	0.787-1.998
T allele	197 (73.0)	241 (77.2)		1 (Ref.)	1 (Ref.)
A allele	73 (27.0)	71 (22.8)	0.233	1.258	0.863-1.834
−604T>C			0.019
TT	32 (23.7)	58 (37.2)		1 (Ref.)	1 (Ref.)
TC	69 (51.1)	74 (47.4)	0.057	1.69	0.983-2.907
CC	34 (25.2)	24 (15.4)	0.006	2.568	1.304-5.058
TC+CC	103 (76.3)	98 (62.8)	0.013	1.905	1.14-3.181
T allele	133 (49.3)	190 (61.0)		1 (Ref.)	1 (Ref.)
C allele	137 (50.7)	122 (39.2)	0.005	1.604	1.154-2.231

OR, odds ratio; CI, confidence interval; Ref., reference.

Haplotype analysis of the VEGFR2 gene

The haplotypes of VEGFR2 +1192C>T, +1719T>A, and −604T>C variants are shown in Table 3. SHEsis program was used to analyze the haplotypes of VEGFR2 variants. The results showed that there was statistically significant difference in the CTT haplotype and TAC haplotype between the case group and control group (both p < 0.05). The frequency of CTT haplotype was significantly lower in the case group than the control group (p < 0.05), while the frequency of TAC haplotype was remarkably higher in the case group compared to the control group (p < 0.05), suggesting a protective role for the CTT haplotype and a disease-aggravating role for TAC in DVT patients (CTT: OR = 0.584; TAC: OR = 6.933).

Table 3.

Haplotype Analysis of VEGFR2 +1192C>T, +1719T>A and −604T>C Variants in the Case Group and the Control Group

Haplotype
+1192C>T	+1719T>A	−604T>C	Case group (n = 135)	Control group (n = 156)	p	OR	95% CI
C	T	T	39 (28.9)	64 (41.0)	0.031	0.584	0.358-0.954
C	T	C	40 (29.6)	41 (30.4)	0.525	1.181	0.707-1.974
C	A	T	14 (10.4)	19 (12.2)	0.627	0.834	0.401-1.736
C	A	C	15 (11.1)	12 (7.7)	0.316	1.500	0.676-3.328
T	T	T	9 (6.7)	10 (6.4)	0.930	1.043	0.411-2.648
T	T	C	9 (6.7)	6 (3.8)	0.278	1.786	0.619-5.155
T	A	T	3 (2.2)	3 (1.9)	0.858	1.159	0.230-5.843
T	A	C	6 (4.4)	1 (0.1)	0.035	6.933	3.535-13.60

Logistic regression analysis of risk factors for DVT

Patients with DVT or not were used as the dependent variable. The VEGFR2 +1192C>T variants, VEGFR2 +1719T>A variants, and VEGFR2 −604T>C variants and their haplotypes were used as independent variables. Binary logistic regression was performed to analyze the risk factors for DVT. The results showed independent correlation between the TAC haplotype and onset of DVT (p < 0.05) (Table 4).

Table 4.

Logistic Regression Analysis of VEGF2 Gene and Risk Factors for DVT

Independent factors	S.E.	Wald	Sig.	Exp (B)	95% CI
+1192C>T (CC vs. CT+TT)	0.19	0.25	0.62	1.21	0.58-2.53
+1719T>A (TT vs. TA+AA)	0.4	0.57	0.45	0.74	0.34-1.61
−604T>C (TT vs. TC+CC)	0.61	2.41	0.12	2.56	0.78-8.37
Haplotype CTT	0.61	0	0.99	1.01	0.30-3.33
Haplotype TAC	1.11	5.43	0.02	0.08	0.01-0.66

S.E., standard error; Sig., significance; DVT, deep venous thrombosis.

Follow-up analysis for DVT treatment efficacy

A total of 83 DVT patients received regular monitoring of PT and INR and their follow-up data were obtained. There were no significant differences in treatment efficacy in the dominant genotypes of VEGFR2 +1192C>T variants, VEGFR2 +1719T>A variants, and VEGFR2 −604T>C variants (all p > 0.05) (Table 5). In terms of haplotypes, significant differences in treatment efficacy were found in DVT patients with TAC haplotype (p < 0.05), while no such differences were found in other haplotypes, suggesting DVT patients with TAC haplotype had less effective DVT treatment efficacy and a higher probability of DVT recurrence (Table 6).

Table 5.

Different SNP of VEGFR2 Gene and DVT Treatment Efficacy

SNP	Genotype	Effective	Ineffective	p
+1192C>T	CC	48	5	0.663
	CT+TT	28	2
+1719T>C	TT	42	3	0.528
	TA+AA	34	4
−604T>C	TT	18	0	0.146
	TC+CC	58	7

Table 6.

Different Haplotype of VEGFR2 Gene and DVT Treatment Efficacy

Haplotype	Effective	Ineffective	p
CTT	27	1	0.255
CTC	24	2	0.867
CAT	7	2	0.115
CAC	10	0	0.306
TTT	3	1	0.222
TTC	4	0	0.534
TAT	0	0	/
TAC	1	1	0.032

Discussion

In our study, genotype and allele frequencies of VEGFR2 +1192C>T and +1719T>A variants showed no statistical differences within the case group and control group. However, significant differences were found in the genotype and allele frequencies of VEGFR2 −604T>C between the case group and control group, and the result suggested that the C allele and CC genotype of the −604T>C increased the risk of DVT. The previous study showed that −604T>C reduced the activity of VEGFR2 promoter and decreased the VEGF-binding affinity of VEGFR2, leading to a functional defect in optimal activation of the receptor by VEGF (Oh et al., 2011).

To the best of our knowledge, the relationship between these VEGFR2 polymorphisms and DVT has not been previously studied, but the same SNPs were studied in the context of other diseases. Brito et al. (2014) showed a significant association between VEGFR2 −604T/C and +1192G/A SNPs and multiple myeloma, and the GG genotype in the VEGFR2 +1192GG and the TT genotype in the VEGFR2 −604TT conferred an increased risk of multiple myeloma. In addition, the SNPs have also been studied in the context of premature ovarian failure, spontaneous abortion recurrent, and type 2 diabetes mellitus (Rah et al., 2012, 2013; Jang et al., 2013; Kariz and Petrovic, 2014).

The result of haplotype analysis showed that there was a statistically significant difference in the CTT haplotypes and TAC haplotype of VEGFR2 gene between the case group and control group, suggesting the potential protective role of CTT haplotype and a disease-promoting role of TAC haplotype in DVT patients. Oh et al. have also conducted a study on the correlation between VEGFR2 polymorphisms and haplotypes of SNP −604T>C, +1192G>A, and +1719A>T. The result showed that TGT, TAT, and CGT haplotypes of VEGFR2 might confer an increased risk of ischemic stroke (Oh et al., 2011).

In our study, logistic regression analysis to detect the risk factors for DVT showed that the TAC haplotype as an independent risk factor for the onset of DVT. Based on our analysis, we postulate that the TAC haplotype might have multiple influences on the VEGFR2 gene, altering the VEGFR2 expression as well as its affinity to VEGF, leading to defective angiogenesis and vasculogenesis.

Our follow-up results showed that significant differences in treatment efficacy were found in DVT patients with the TAC haplotype, suggesting that DVT patients with the TAC haplotype had a less effective DVT treatment efficacy and higher probability of DVT recurrence. Heparin is often used as the initial treatment for acute DVT because such therapy reduces asymptomatic DVT extension (Heit et al., 2011). Warfarin sodium can be used to prevent and treat DVT, and VKORC1 has been reported to be correlated with warfarin sensitivity (Do et al., 2012). Our result showed no significant relationship between VKORC1 polymorphism at +1192C>T, +1719T>A, and −604T>C variants, but the TAC haplotype might relate with warfarin sensitivity and DVT development.

The limitations of our study should be also mentioned. First, the limited sample size is noted. Only 135 patients and 156 normal people were involved. Second, the retrospective analysis has its shortcomings. The retrospective data were not collected under the supervision of experienced researchers, resulting in an inevitable bias. The age range of included patients was also wide (ranges, 21-77 years old) and might influence the results. The study was performed in a Chinese Han population and the applicability of these results to a wider population of DVT patients remains unknown. Finally, contribution by other genes was not considered in the analysis of the formation of DVT in this study.

In summary, based on our findings, VEGFR2 genetic polymorphism −604T>C is associated with DVT in the Chinese Han population. The TAC haplotype and the CC genotype of VEGFR2 −604T>C variants confer a significant risk for DVT. Thus, our study provides the fundamental genetic data, its link to DVT, and offers a possibility that our results may be used in the development of genetic biomarkers to study the development of DVT.

Footnotes

Acknowledgments

We would like to thank our researchers for their hard work and reviewers for their valuable advice.

Author Disclosure Statement

All authors in our study have no conflicts of interest.

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