Association of polymorphisms near the FOXC2 gene with the risk of varicose veins in ethnic Russians

Abstract

Objective

To investigate the association of polymorphisms located near the FOXC2 gene with the risk of varicose veins in ethnic Russians.

Methods

Allele, genotype, and haplotype frequencies were determined in the sample of 474 patients with primary varicose veins and in the control group of 478 individuals without a history of chronic venous disease.

Results

Polymorphisms rs7189489, rs4633732, and rs1035550 showed the association with the increased risk of varicose veins, but none of the observed associations remained significant after correction for multiple testing. Haplotype analysis revealed the association of haplotype rs7189489 C–rs4633732 T–rs34221221 C–rs1035550 C–rs34152738 T–rs12711457 G with the increased risk of varicose veins (OR = 2.67, P = 0.01).

Conclusions

Our results provide evidence that the studied polymorphisms do not play a major role in susceptibility to varicose veins development in the Russian population.

Keywords

Varicose veins FOXC2 single nucleotide polymorphism association Russians

Introduction

Varicose veins are one of the clinical manifestations of chronic venous disease and can be described as dilated, palpable, tortuous subcutaneous veins with a diameter more than 3 mm.¹ Prevalence estimates of varicose veins vary from <1 to 73% in females and from <1 to 56% in males that could be due to variations in the use of diagnostic criteria as well as differences in the prevalence of risk factors in the studied groups. Generally, this condition is more common in developed countries than in underdeveloped regions.²

Factors involved in the pathogenesis of varicose veins include vessel wall alterations, impaired extracellular matrix remodelling, elevated venous pressure, valve failure, ineffective function of calf muscle pump, inflammation, and impaired balance between growth factors or cytokines,^1,3 though the priority of these events is still controversial and the precise molecular mechanism underlying the development of varicose veins is still not fully understood. A strong body of evidence indicates a prominent role of heredity in the development of varicose veins.^4–11 A twin cohort study showed a linkage between candidate marker D16S520 on chromosome 16q24 and varicose veins in otherwise healthy, unselected sibling pairs.¹¹ The presence of this marker was also found in nine out of 20 families with affected individuals.¹² D16S520 marker is located in close proximity (80 kb) to the FOXC2 gene, which encodes a forkhead transcription factor involved in the development of the lymphatic and vascular system.^13–18 In humans, mutations in this gene cause lymphedema distichiasis, a rare autosomal dominant primary lymphedema of the limbs, associated with an accessary row of aberrant eyelashes present in 94% of the affected individuals.^19–23 Other possible complications include congenital heart defects, cleft palate, ptosis, scoliosis, ocular anomalies, photophobia, spinal extradural cysts.^21,23–25 Notably, half of affected subjects have varicose veins of early onset,²¹ with almost all of patients showing signs of venous insufficiency.^26,27 Recent study reported a strong association of FOXC2 mutations with primary venous valve failure in both the superficial and deep veins in the lower limb.²⁸ These findings provide strong evidence for FOXC2 involvement in the aetiology of varicose veins and make it a good candidate for genetic association studies. To date, one study has been published on association of polymorphisms in the FOXC2 gene with the risk of varicose veins.²⁹ The study was performed on the Indian population, and three polymorphisms were reported to be associated. Further research is warranted to study whether genetic variants in the FOXC2 gene influence the risk of developing varicose veins in other populations. In our study, we investigated the association of six single nucleotide polymorphisms (SNPs) located in a 30.2 kb region of genome containing the FOXC2 gene with the risk of varicose veins in ethnic Russians.

Methods

Patients

The study was approved by the Ethics Committee of Institute of Chemical Biology and Fundamental Medicine (protocol No. 15, 13 September 2013) and the Ethics Committee of Pirogov Russian National Research Medical University (protocol No.123, 21 January 2013). All the individuals enrolled in this study gave signed informed consent. All clinical investigations were conducted according to the principles expressed in the Declaration of Helsinki.

The case group consisted of 474 patients with primary varicose veins. All the participants underwent clinical examination with a subsequent duplex ultrasound of a venous system of both legs. The clinical severity, aetiology, anatomy, and pathophysiology (CEAP) classification system was used to categorise manifestations of chronic venous disease.³⁰ Patients with C1 CEAP class and individuals with postthrombotic syndrome or congenital varicose veins were excluded from the study. A descriptive characteristic of the case group is presented in Table 1.

Table 1.

Descriptive characteristics of patients with varicose veins.

Variable	Value of the variable
Age, years, median (lower quartile, upper quartile), range	48 (37, 57), 18–74
Body mass index, kg/m², median (lower quartile, upper quartile), range	25.7 (22.86, 29.36), 16.0–42.0
Sex, n ^a (%)
Men	146 (30.8%)
Women	328 (69.2%)
Age of onset, n ^a (%)
Below 20 years	117 (24.7%)
21–30 years	193 (40.7%)
31–40 years	99 (20.9%)
41–50 years	60 (12.7%)
over 50 years	5 (1.1%)
Family history ^b , n ^a (%)
Yes	333 (70.3%)
No	124 (26.2%)
N/A^c	17 (3.6%)
CEAP class, n ^a (%)
C2	141 (29.7%)
C3	237 (50.0%)
C4	80 (16.9%)
C5	9 (2.0%)
C6	7 (1.5%)

Number of patients.

Family history was defined as having one or more affected relatives (mother/father, sister/brother, son/daughter, grandmother/grandfather, uncle/aunt, cousin, niece/nephew).

Data not available.

The control group comprised 478 patients without a history of chronic venous disease (147 (30.8%) men and 331 (69.2%) women, median age 55 years, lower quartile 44 years, upper quartile 62 years, range 19–84 years).

All cases and controls were ethnic Russians.

Genomic DNA was isolated from leucocytes in venous blood by proteinase K digestion followed by phenol/chloroform extraction and ethanol precipitation. DNA samples were stored at −20℃ in a freezer compartment.

Genotyping

We selected six SNPs from the SNP database (dbSNP)³¹ for our analysis that are located across a 30.2 kb genomic region containing the FOXC2 gene (1.7 kb FOXC2 gene sequence, about 14 kb upstream of the gene, and about 14 kb downstream of the gene). Two of the chosen SNPs lie within a distal 5′ region of the FOXC2 gene, one SNP in a promoter region, another one in a 3′ near gene region, and two SNPs in a distal 3′ FOXC2 region near the FOXL1 gene coding sequence (Table 2). We selected these SNPs based on their minor allele frequencies (5% or greater in European populations) and on the basis of suitability of the surrounding sequence for primers and probes design. Moreover, polymorphism rs34221221 was chosen as it was shown to be associated with chronic venous disease in the previous study.²⁹

Table 2.

SNPs analysed in our study.

SNP	Nucleotide substitution	Position on chromosome 16	MAF^a (%)
rs7189489	C/A	86553056 (MTHFSD gene)	14–23
rs4633732	T/G	86557806	16–30
rs34221221	T/C	86566824 (FOXC2 gene; promoter region)	32–46
rs1035550	C/T	86569101 (FOXC2; 3′ near gene)	5–16
rs34152738	T/G	86577785 (FOXL1 gene; promoter region)	15–23
rs12711457	G/A	86583280 (FOXL1; 3′ near gene)	36–47

SNP: single nucleotide polymorphism.

Minor allele frequency in European populations according to dbSNP³¹ and 1000 Genomes (http://www.1000genomes.org/).

Genotyping of polymorphisms rs7189489, rs4633732, and rs34152738 was carried out by real-time PCR allelic discrimination with TaqMan probes. PCR was performed in 20 μl reaction volume containing 20–100 ng of genomic DNA, 65 mM Tris–HCl (рН 8.9), 24 mM ammonium sulphate, 3.5 mM magnesium chloride, 0.05% Tween 20, 0.2 mM dNTP, 0.3 mM primers, 0.1 mM probes (see Appendix 1), and 1.0 U of Taq polymerase. PCR thermal cycling conditions were as follows: denaturation for 3 min at 96°С followed by 48 cycles of 8 s at 96°С and 40 s at 60°С. Amplification procedure was conducted using CFX96 Thermal Cycler (Bio-Rad, USA).

Genotypes of polymorphisms rs34221221, rs1035550, and rs12711457 were determined by PCR followed by melting analysis of dual-labelled probes (method described by El Housni et al.³²). PCR was performed in 20 µl reaction volumes containing 20–100 ng of genomic DNA, 10 mM Tris–HCl (рН 8.9), 55 mM potassium chloride, 2.5 mM magnesium chloride, 0.05% Tween 20, 0.2 mM dNTP, 0.1 mM forward primers, 1 mM reverse primers, 0.1 mM probes (see Appendix 1), and 1.0 U of KlenTaq polymerase. PCR thermal cycling conditions were as follows: denaturation for 3 min at 96°С followed by 55 cycles of 6 s at 96°С, 6 s at 56°С (60°С for rs34221221), and 6 s at 72°С; melting curve 30–70°С, 0.5°С per step. Amplification procedure was conducted using DNA Engine Dyad thermal cycler (Bio-Rad, USA) and melting analysis was performed using CFX96 Thermal Cycler (Bio-Rad, USA).

Primers and probes were designed using sequences obtained from the National Center for Biotechnology Information (http://www.ncbi.nlm.nih.gov/), UGENE software (version 1.14, http://ugene.unipro.ru/), and Oligo Analyzer software (version 1.0.3).

Statistical analysis

To evaluate the effects of the polymorphisms on susceptibility to varicose veins, odds ratio (OR) and 95% CI were calculated by logistic regression analysis adopting co-dominant and additive models of inheritance. All data were adjusted for sex and age. The expected frequencies of genotypes in the control group were tested for accordance with Hardy–Weinberg equilibrium using exact test. Differences were considered statistically significant at P < 0.05. Since overall six SNPs were tested, the significance threshold after implementation of Bonferroni correction for multiple testing was P = 0.008. Statistical analyses were performed using the GenABEL statistical package for the R language (version 3.1.1, http://www.r-project.org; glm function). Haplotype frequencies and the corresponding OR and CI 95% values were calculated using the haplo.stats statistical package for the R language (version 3.1.1; haplo.score and haplo.glm functions). Linkage disequilibrium was analysed based on D′ values calculated using the CubeX program (http://www.oege.org/software/cubex/). To estimate the statistical power of study, genetic power calculator (http://pngu.mgh.harvard.edu/∼purcell/gpc/cc2.html) was used.

Shapiro–Wilk test was used to check whether age and body mass index (BMI) are normally distributed in the analysed groups. Since the distribution was not normal, Mann–Whitney U test was used to evaluate the significance of differences between the groups. P < 0.05 was considered significant. The analysis was performed with STATISTICA 8.0 software.

Results

We determined allele, genotype, and haplotype frequencies in the case and the control groups (Tables 3 and 4, Appendix 2). Genotype distribution in the control group was in Hardy–Weinberg equilibrium for all studied SNPs. In the case group, deviation from Hardy–Weinberg equilibrium was observed only for rs1035550 (P = 0.04).

Table 3.

Allele and genotype frequencies in the case and the control groups. Association of the studied SNPs with the risk of varicose veins.

SNP	Genotype/allele	Case	Control	OR (95% CI), P
rs7189489	CC	325 (70.5%)	309 (65.7%)	Reference
	CA	120 (26.0%)	150 (31.9%)	0.72^a (0.54–0.96), 0.03^d
	AA	16 (3.5%)	11 (2.3%)	1.42^a (0.64–3.14), 0.39
	A	16%	18%	0.85^b (0.67–1.09), 0.20
	HWE^c	0.24	0.17
rs4633732	TT	255 (55.3%)	293 (62.3%)	Reference
	TG	180 (39.0%)	152 (32.3%)	1.40^a (1.06–1.85), 0.02^d
	GG	26 (5.6%)^d	25 (5.3%)^d	1.16^a (0.65–2.09), 0.61
	G	25%	21%	1.24^b (0.99–1.54), 0.06
	HWE^c	0.54	0.41
rs34221221	TT	194 (42.1%)	200 (43.0%)	Reference
	TC	208 (45.1%)	214 (46.0%)	1.00^a (0.82–1.22), 0.76
	CC	59 (12.8%)	51 (11.0%)	1.19^a (0.78–1.82), 0.42
	C	35%	34%	1.08^b (0.88–1.31), 0.46
	HWE^c	0.76	0.61
rs1035550	CC	351 (76.7%)	356 (77.6%)	Reference
	CT	94 (20.5%)	99 (21.6%)	0.94^a (0.68–1.30), 0.72
	TT	13 (2.8%)	4 (0.9%)	3.65^a (1.16–11.4), 0.03^d
	T	13%	12%	1.14^b (0.86–1.51), 0.36
	HWE^c	0.04 ^d	0.49
rs34152738	TT	294 (64.9%)	307 (65.0%)	Reference
	TG	140 (30.9%)	150 (31.8%)	0.95^a (0.71–1.26), 0.71
	GG	19 (4.2%)	15 (3.2%)	1.35^a (0.67–2.74), 0.40
	G	20%	19%	1.03^b (0.81–1.30), 0.84
	HWE^c	0.66	0.65
rs12711457	GG	150 (32.7%)	155 (32.8%)	Reference
	GA	219 (47.8%)	250 (52.9%)	0.93^a (0.69–1.25), 0.62
	AA	90 (19.6%)	68 (14.4%)	1.37^a (0.93–2.03), 0.12
	A	43%	41%	1.13^b (0.93–1.36), 0.22
	HWE^c	0.57	0.05

CI: confidence interval; OR: odds ratio.

Co-dominant model of inheritance.

Additive model of inheritance.

P-value for deviation of genotype distribution from the Hardy–Weinberg equilibrium (exact test).

P-values < 0.05 are in bold.

Table 4.

Association of the studied SNPs with the risk of varicose veins.

SNP	Genotype/allele	Case	Control	OR (95% CI), P
C2 CEAP clinical class
rs4633732	TT	67 (51.1%)	293 (62.3%)	Reference
	TG	51 (38.9%)	152 (32.3%)	1.57^a (1.02–2.44), 0.04^b
	GG	13 (9.9%)^b	25 (5.3%)^b	2.28^a (1.06–4.90), 0.03^b
	G	29%	21%	1.53^c (1.12–2.11), 0.01^b
	HWE^d	0.53	0.41
C4–C6 CEAP clinical classes
rs7189489	CC	60 (65.2%)	309 (65.7%)	Reference
	CA	26 (28.3%)	150 (31.9%)	0.93^a (0.56–1.53), 0.77
	AA	6 (6.5%)	11 (2.3%)	2.85^a (1.01–8.05), 0.049^b
	A	21%	18%	1.20^c (0.80–1.79), 0.37
	HWE^d	0.20	0.17
rs1035550	CC	69 (73.4%)	356 (77.6%)	Reference
	CT	21 (22.3%)	99 (21.6%)	1.10^a (0.64–1.89), 0.73
	TT	4 (4.3%)	4 (0.9%)	5.14^a (1.25–21.2), 0.03^b
	T	15%	12%	1.39^c (0.89–2.18), 0.15
	HWE^d	0.22	0.49
Patients with family history of varicose veins
rs1035550	CC	252 (77.3%)	356 (77.6%)	Reference
	CT	65 (19.9%)	99 (21.6%)	0.90^a (0.63–1.29), 0.57
	TT	9 (2.8%)	4 (0.9%)	3.44^a (1.03–11.5), 0.045^b
	T	13%	12%	1.09^c (0.80–1.49), 0.57
	HWE^d	0.08	0.49

CI: confidence interval; OR: odds ratio.

Co-dominant model of inheritance.

P-values < 0.05 are in bold.

Additive model of inheritance.

P-value for deviation of genotype distribution from the Hardy–Weinberg equilibrium (exact test).

We calculated statistical power of our study. We had 80% statistical power to reveal associations with OR = 1.2 or greater for polymorphisms rs34221221 and rs12711457 and to detect associations with OR = 1.3 or greater for polymorphisms rs7189489, rs4633732, rs1035550, and rs34152738.

Three associations with P < 0.05 were observed in our study: the association of genotype rs7189489 CA with the reduced risk of varicose veins (OR = 0.72, P = 0.03) and the associations of rs4633732 TG and rs1035550 TT genotypes with the increased risk of this pathology (OR = 1.40, P = 0.02 and OR = 3.65, P = 0.03, correspondingly; Table 3). Since the association of heterozygous genotype alone hardly ever has biological sense, we tend to think that these associations are false positive. All the revealed associations turned out to be insignificant after the implementation of Bonferroni correction for multiple testing.

Subgroup analysis was performed for patients having C2, C3, and C4–C6 CEAP clinical classes of chronic venous disease and also for patients with positive/negative family history. The revealed associations are presented in Table 4. Polymorphism rs4633732 showed an association with the increased risk of developing varicose veins in the subgroup of patients with C2 class (TG versus TT: OR = 1.57, P = 0.04; GG versus TT: OR = 2.28, P = 0.03; G versus T: OR = 1.53, P = 0.01). Genotype rs7189489 AA was associated with varicose veins in individuals having C4–C6 classes (OR = 2.85, P = 0.049). Genotype rs1035550 TT showed the association in the subgroup of patients with C4–C6 classes and in the subgroup of individuals having positive family history (OR = 5.14, P = 0.03 and OR = 3.44, P = 0.045, correspondingly). None of the revealed associations remained significant after applying the Bonferroni correction.

We evaluated the linkage disequilibrium between the studied polymorphisms (Figure 1). The majority of neighbouring SNPs were tightly linked with D′ = 0.69–1.00 (except rs4633732 and rs34221221, D′ = 0.25). The frequency of the most common haplotype rs7189489 C–rs4633732 T–rs34221221 T–rs1035550 C–rs34152738 T–rs12711457 G was lower in the case than in the control group (37.0% versus 41.6%, P = 0.049; Appendix 2). To evaluate the effect of this major haplotype, we took the sum total of other haplotypes as reference and calculated OR and 95% CI (0.82 and 0.67–0.999, correspondingly). Other haplotypes had frequencies 0–12%, and most of them were very rare or not seen in our sample (Appendix 2). Haplotype rs7189489 C–rs4633732 T–rs34221221 C–rs1035550 C–rs34152738 T–rs12711457 G was more frequent among patients having varicose veins than in the control group (3.82% versus 1.31%) and was associated with the increased risk of the studied pathology (OR = 2.67, 95% CI 1.14–6.24, P = 0.01).

Figure 1.

Linkage disequilibrium between the studied SNPs in the sample of ethnic Russians.

We investigated the influence of SNPs on BMI in patients with varicose veins (Appendix 3). Only polymorphism rs12711457 was significantly associated with BMI. Carriers of rs12711457 A allele had significantly lower BMI (median 25.33 kg/m², lower quartile 22.53 kg/m², upper quartile 29.05 kg/m²) than individuals having GG genotype (median 26.40 kg/m², lower quartile 23.66 kg/m², upper quartile 30.16 kg/m², P = 0.03). The association became insignificant after the implementation of Bonferroni correction.

Discussion

FOXC2 is a member of the forkhead family of transcription factors, which bind to DNA via a highly conserved variant of the helix-turn-helix motif. Human FOX gene family consists of at least 43 members.³³ The exact mechanism of FOXC2 action remains largely unknown. Animal studies have shown that FOXC2 plays an important role in embryonic development, including the development of cardiovascular and lymphatic systems as well as angiogenesis and lymphangiogenesis in postnatal life. FOXC2 is required for mesenchymal cell interactions, arterial cell specification, lymphatic and blood vessel formation, valve formation, lymph node formation, cardiac outflow tract morphogenesis, etc.^13–18,34 It was demonstrated to regulate the expression of genes encoding Ang2, integrin β3, Delta-like 4, Hey2, CXCR4, and some other proteins important for the control of angiogenesis.^35–37 Data obtained from recent studies suggest that FOXC2 could be involved in the aetiology of varicose veins in humans.^{11,21,26–29} In our study, we tested the hypothesis that SNPs in the genomic region containing FOXC2 could be associated with the risk of developing varicose veins in ethnic Russians. The previously published association study revealed the effect of SNPs in the FOXC2 gene on the risk of chronic venous disease in the group of patients having mostly C4–C6 CEAP clinical classes.²⁹ Another study demonstrated the presence of the genetic locus related to the FOXC2 gene (D16S520) in families with patients having varicose veins, and all affected individuals, including older patients (with disease duration >20 years), had C2 class.¹² In our study the majority of patients had C2 and C3 classes (Table 1). In order to examine whether potential influence of the studied SNPs is disease subtype specific as well as to be able to compare our results with the results of previous studies, we stratified our sample according to CEAP classes and presence/absence of family history and conducted a subgroup analysis.

We determined allele, genotype, and haplotype frequencies of polymorphisms rs7189489, rs4633732, rs34221221, rs1035550, rs34152738, and rs12711457 in patients having varicose veins and in the control group of individuals without a history of chronic venous disease (Tables 3 and 4, Appendix 2). Allele frequencies in ethnic Russians were generally close to those reported in the SNP database for European populations³¹ (Table 2) as well as to allele frequencies previously determined by other research groups (rs34221221 C allele frequency was found to be 35–39% in Scandinavians^38,39 and 35% in the Finnish population⁴⁰).

We did not find strong evidence that the studied polymorphisms have an impact on the risk of varicose veins development in our population. We observed several associations with P < 0.05, but none of them remained statistically significant after the implementation of Bonferroni correction for multiple testing (rs1035550, rs4633732, and rs7189489; Tables 3 and 4). We therefore cannot exclude that our findings are false positive, so the revealed associations should be treated with caution until replicated by independent studies. Nevertheless, we found out that the most common haplotype, containing only major alleles (rs7189489 C–rs4633732 T–rs34221221 T–rs1035550 C–rs34152738 T–rs12711457 G), was less frequent in the case than in the control group (P = 0.049, Appendix 2). Only one of the remaining haplotypes was significantly associated with the increased risk of varicose veins (OR = 2.67, P = 0.01). This haplotype was different from the major haplotype only in the presence of rs34221221 C allele, providing evidence that polymorphism rs34221221 could still be associated with the risk of the studied pathology, but its effect might possibly be masked by joint effects of other polymorphisms. Notably, this polymorphism was shown to be strongly associated with the risk of varicose veins in the Indian population.²⁹ Functional analysis in that study revealed that TT genotype was associated with FOXC2 overexpression. In contrast to our results, the association with the increased risk was observed for rs34221221 T variant. It is worth noting that rs34221221 T is a minor allele in Asians, while it is a major allele in Caucasians (rs34221221 T frequency is 38–40% in the Chinese population,³¹ 29–32% in the Japanese population,^31,41 45% in the Indian population,²⁹ and 54–66% in different European populations including our population).^31,38–40 It is also interesting to note that varicose veins were found to be less common in Asians than in non-Hispanic Whites.⁴² We can speculate that genetic differences between the populations, including differences in gene–gene interaction, could underlie discrepancy in the observed effects. It is possible that Asians could have higher basal level of FOXC2 protein, and excessive FOXC2 amount in individuals with T allele can disrupt the balance and lead to varicose veins formation. On the other hand, if Europeans have low basal FOXC2 level, carriers of rs34221221 C allele may be at risk due to the insufficient amount of this regulatory protein. It would therefore be interesting to examine the influence of this SNP on the risk of varicose veins development in other populations of European and Asian origin.

Furthermore, in our study we failed to replicate the association of rs34221221 with BMI, which was previously revealed in the Finnish population⁴⁰ and Pima Indians.⁴³ Since our sample size was close to those in the above-mentioned studies, this result provides additional evidence that the effect of this SNP could be modulated by ethnic factors.

Finally, the main limitation of our study should be acknowledged. We did not use any sophisticated approaches for SNP selection and investigated only six SNPs in the studied genomic region. Nevertheless, our linkage disequilibrium analysis has shown that the studied SNPs are tightly linked to each other and are therefore likely to cover this region of genome.

Conclusion

We revealed the associations of polymorphisms rs1035550, rs4633732, and rs7189489 with the increased risk of varicose veins in ethnic Russians. Polymorphism rs1035550 showed an association in the whole sample of patients and in the subgroups of patients with C4–C6 CEAP classes and positive family history. Polymorphisms rs4633732 and rs7189489 were associated with the risk of varicose veins only in the subgroups of individuals having C2 and C4–C6 CEAP classes, correspondingly. Since none of the revealed associations reached Bonferroni-corrected significance levels, our findings need further confirmation by independent studies. However, our haplotype analysis indicated that the studied SNPs could mask each other’s effect and suggested an association of polymorphism rs34221221 C with the increased risk of the studied pathology.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by Russian Science Fund (grant number 14-15-00734, “Searching of genes involved in varicose vein disease pathology”).

Ethical approval

Guarantor

ASS.

Contributorship

ASS performed the research and wrote the paper. EAS and MAS extracted DNA from blood. KSS, AIS, MYD, OAS, and EAI provided blood specimens and clinical data. MLF designed primers and probes. ENV, IAZ, AIK, and MLF supervised the research. All authors reviewed and edited the manuscript and approved the final version of the manuscript.

References

Segiet

Brzozowa

Piecuch

. Biomolecular mechanisms in varicose veins development. Ann Vasc Surg 2015; 29: 377–384.

Beebe-Dimmer

Pfeifer

Engle

. The epidemiology of chronic venous insufficiency and varicose veins. Ann Epidemiol 2005; 15: 175–184.

Jacob

. Extracellular matrix remodeling and matrix metalloproteinases in the vascular wall during aging and in pathological conditions. Biomed Pharmacother 2003; 57: 195–202.

Cornu-Thenard

Boivin

Baud

. Importance of the familial factor in varicose disease. Clinical study of 134 families. J Dermatol Surg Oncol 1994; 20: 318–326.

Criqui

Denenberg

Bergan

. Risk factors for chronic venous disease: the San Diego Population Study. J Vasc Surg 2007; 46: 331–337.

Brinsuk

Tank

Luft

. Heritability of venous function in humans. Arterioscler Thromb Vasc Biol 2004; 24: 207–211.

Guo

. Genetic analysis of varicose vein of lower extremities. Zhonghua Yi Xue Yi Chuan Xue Za Zhi 1998; 15: 221–223.

Ahti

Mäkivaara

Luukkaala

. Effect of family history on the incidence of varicose veins: a population-based follow-up study in Finland. Angiology 2009; 60: 487–491.

Fiebig

Krusche

Wolf

. Heritability of chronic venous disease. Hum Genet 2010; 127: 669–674.

10.

Krysa

Jones

van Rij

. Evidence for a genetic role in varicose veins and chronic venous insufficiency. Phlebology 2012; 27: 329–335.

11.

MYM

Andrew

Spector

. Linkage to the FOXC2 region of chromosome 16 for varicose veins in otherwise healthy, unselected sibling pairs. J Med Genet 2005; 42: 235–239.

12.

Serra

Buffone

de Franciscis

. A genetic study of chronic venous insufficiency. Ann Vasc Surg 2012; 26: 636–642.

13.

Petrova

Karpanen

Norrmén

. Defective valves and abnormal mural cell recruitment underlie lymphatic vascular failure in lymphedema distichiasis. Nat Med 2004; 10: 974–981.

14.

Shimoda

Bernas

Witte

. Dysmorphogenesis of lymph nodes in Foxc2 haploinsufficient mice. Histochem Cell Biol 2011; 135: 603–613.

15.

Seo

Fujita

Nakano

. The forkhead transcription factors, Foxc1 and Foxc2, are required for arterial specification and lymphatic sprouting during vascular development. Dev Biol 2006; 294: 458–470.

16.

Kume

. The cooperative roles of Foxc1 and Foxc2 in cardiovascular development. Adv Exp Med Biol 2009; 665: 63–77.

17.

Kume

. Foxc2 transcription factor: a newly described regulator of angiogenesis. Trends Cardiovasc Med 2008; 18: 224–228.

18.

Liu

N-F

. FOXC2 transcription factor: a novel regulator of lymphangiogenesis. Lymphology 2011; 44: 35–41.

19.

Fang

Dagenais

Erickson

. Mutations in FOXC2 (MFH-1), a forkhead family transcription factor, are responsible for the hereditary lymphedema-distichiasis syndrome. Am J Hum Genet 2000; 67: 1382–1388.

20.

Bell

Brice

Child

. Analysis of lymphoedema-distichiasis families for FOXC2 mutations reveals small insertions and deletions throughout the gene. Hum Genet 2001; 108: 546–551.

21.

Brice

Mansour

Bell

. Analysis of the phenotypic abnormalities in lymphoedema-distichiasis syndrome in 74 patients with FOXC2 mutations or linkage to 16q24. J Med Genet 2002; 39: 478–483.

22.

Sutkowska

Gil

Stembalska

. Novel mutation in the FOXC2 gene in three generations of a family with lymphoedema-distichiasis syndrome. Gene 2012; 498: 96–99.

23.

Fabretto

Shardlow

Faletra

. A case of lymphedema-distichiasis syndrome carrying a new de novo frameshift FOXC2 mutation. Ophthalmic Genet 2010; 31: 98–100.

24.

Erickson

Dagenais

Caulder

. Clinical heterogeneity in lymphoedema-distichiasis with FOXC2 truncating mutations. J Med Genet 2001; 38: 761–766.

25.

Bahuau

Houdayer

Tredano

. FOXC2 truncating mutation in distichiasis, lymphedema, and cleft palate. Clin Genet 2002; 62: 470–473.

26.

Rosbotham

Brice

Child

. Distichiasis-lymphoedema: clinical features, venous function and lymphoscintigraphy. Br J Dermatol 2000; 142: 148–152.

27.

Vreeburg

Heitink

Damstra

. Lymphedema-distichiasis syndrome: a distinct type of primary lymphedema caused by mutations in the FOXC2 gene. Int J Dermatol 2008; 47: 52–55.

28.

Mellor

Brice

Stanton

AWB

. Mutations in FOXC2 are strongly associated with primary valve failure in veins of the lower limb. Circulation 2007; 115: 1912–1920.

29.

Surendran

Girijamma

Nair

. Forkhead box C2 promoter variant c.-512C>T is associated with increased susceptibility to chronic venous diseases. PLoS One 2014; 9: e90682–e90682.

30.

Eklöf

Rutherford

Bergan

. Revision of the CEAP classification for chronic venous disorders: consensus statement. J Vasc Surg 2004; 40: 1248–1252.

31.

Sherry

Ward

Kholodov

. dbSNP: the NCBI database of genetic variation. Nucleic Acids Res 2001; 29: 308–311.

32.

El Housni

Heimann

Parma

. Single-nucleotide polymorphism genotyping by melting analysis of dual-labeled probes: examples using factor V Leiden and prothrombin 20210A mutations. Clin Chem 2003; 49: 1669–1672.

33.

Katoh

. Human FOX gene family (Review). Int J Oncol 2004; 25: 1495–1500.

34.

Seo

Kume

. Forkhead transcription factors, Foxc1 and Foxc2, are required for the morphogenesis of the cardiac outflow tract. Dev Biol 2006; 296: 421–436.

35.

Hayashi

Kume

. Foxc transcription factors directly regulate Dll4 and Hey2 expression by interacting with the VEGF-Notch signaling pathways in endothelial cells. PLoS One 2008; 3: e2401–e2401.

36.

Hayashi

Kume

. Foxc2 transcription factor as a regulator of angiogenesis via induction of integrin beta3 expression. Cell Adh Migr 2009; 3: 24–26.

37.

Hayashi

Kume

. Forkhead transcription factors regulate expression of the chemokine receptor CXCR4 in endothelial cells and CXCL12-induced cell migration. Biochem Biophys Res Commun 2008; 367: 584–589.

38.

Shaat

Lernmark

Karlsson

. A variant in the transcription factor 7-like 2 (TCF7L2) gene is associated with an increased risk of gestational diabetes mellitus. Diabetologia 2007; 50: 972–979.

39.

Ridderstråle

Carlsson

Klannemark

. FOXC2 mRNA expression and a 5′ untranslated region polymorphism of the gene are associated with insulin resistance. Diabetes 2002; 51: 3554–3560.

40.

Carlsson

Groop

Ridderstråle

. Role of the FOXC2 -512C>T polymorphism in type 2 diabetes: possible association with the dysmetabolic syndrome. Int J Obes (Lond) 2005; 29: 268–274.

41.

Osawa

Onuma

Murakami

. Systematic search for single nucleotide polymorphisms in the FOXC2 gene: the absence of evidence for the association of three frequent single nucleotide polymorphisms and four common haplotypes with Japanese type 2 diabetes. Diabetes 2003; 52: 562–567.

42.

Criqui

Jamosmos

Fronek

. Chronic venous disease in an ethnically diverse population: the San Diego Population Study. Am J Epidemiol 2003; 158: 448–456.

43.

Kovacs

Lehn-Stefan

Stumvoll

. Genetic variation in the human winged helix/forkhead transcription factor gene FOXC2 in Pima Indians. Diabetes 2003; 52: 1292–1295.