Investigation of Vascular Endothelial Growth Factor (VEGF) Polymorphism in Patients With Idiopathic Heavy Menstrual Bleeding

Investigation of Vascular Endothelial Growth Factor (VEGF) Polymorphism in Patients With Idiopathic Heavy Menstrual Bleeding | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Investigation of Vascular Endothelial Growth Factor (VEGF) Polymorphism in Patients With Idiopathic Heavy Menstrual Bleeding İkbal Kaygusuz, Nur Semerci Gündüz This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-459616/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 08 Sep, 2021 Read the published version in Archives of Gynecology and Obstetrics → Version 1 posted 5 You are reading this latest preprint version Abstract Purpose: To investigate whether there is a relationship between the VEGF gene polymorphisms and idiopathic heavy menstrual bleeding (HMB-E). Methods: 65 patients diagnosed with HMB-E according to the FIGO classification system and 65 female healty volunteers were included in the study. Detection of rs699947 (-2578C>A), rs1570360 (-1154G>A), rs2010963 (+405G>C), rs3025039 (+936C>T), rs25648 (c534C>T) polymorphic regions of the VEGF gene was performed by Next Generation DNA Sequencing method. Results: the -2578C>A polymorphic region CC, CA+AA genotypes, and C allele, as well as the -1154G>A polymorphic region AA genotype, and A allele were associated with increased risk of HMB-E (all pC, +936C>T, c534C>T polymorphic regions (all p>0.05). While the -2578/-1154/+405/c534 AGGC haplotype decreased the risk of HMB-E, CAGC haplotype was found to increase the risk of HMB-E. Conclusion : VEGF -2578C>A and -1154G>A polymorphisms were significantly associated with the risk of HMB-E in the Turkish population. Obstetrics & Gynecology Excessive menstrual bleeding polymorphism vascular endothelial growth factor VEGF gene Figures Figure 1 Introduction Heavy menstrual bleeding (HMB) is an important health problem defined as menstruation at regular intervals but with excessive flow and duration. Clinically, it is defined as a blood loss of more than 80 ml per cycle. It is a common gynecological problem among women of reproductive age and accounts for more than 20% of outpatient visits to gynecologists [1]. Although HMB is often associated with uterine pathology (e.g., fibroid, polyp, adenomyosis, carcinoma), abnormal blood clotting or disruption of hormonal regulation, approximately 50% of HMB cases occur in the absence of recognized uterine pathology [2,3], suggesting a defect in the cellular processes and regulatory mechanisms of menstruation . Such idiopathic HMB of endometrial origin (HMB-E) has been estimated to account for 9-14% of gyneco­logical outpatient visits [4,5]. HMB can lead to iron deficiency anemia. Current treatment options often compromise fertility, and may require hysterectomy in patients who do not respond to the treatments [6]. Another problem is increased maternal morbidity and mortality for pregnant women who has HMB-associated anemia. Heavy bleeding can affect daily activities. Need for long-term medication, the side effects of these therapies, and the intolerance can cause psychological and social discomfort. Also for numerous female individuals, problems related to employment have led to the designation of HMB as a public health problem [4]. Disturbance of endometrial angiogenesis is one of several proposed underlying mechanisms that have been suggested to play a role in HMB [4,5]. In the formation of functional and stable micro vessels, covering the luminal surface of endothelial tubes with mesenchymal pericytes is an important step. The pericytes interact tightly and adhere to the endothelial cells with the pores in the basal layer [7]. Pericytes may induce angiogenesis with Vascular Endothelial Growth Factor (VEGF) production which stimulates endothelial cell proliferation and tube formation. Previous studies have shown that The biopsy specimens of women with HMB have revealed that number of capillaries expressing VEGF-A and its receptors (VEGFR-1 and VEGFR-2) were significantly higher in patients with HMB compared to healthy controls [1]. It is known that glandular luminal surfaces of patients with HMB are wider and this finding is highly correlated with overexpression of VEGF-A and VEGFR-1 [8]. It is suggested that the mesenchymal pericytes acting on the basis of angiogenesis may contribute to the vascular fragility. This leads to excessive blood loss due to extensive endothelial cell gaps and abnormal vascular remodeling as a result of inappropriate coverage of the laminal surface of endothelial tubes [8,9]. In the literature, there is no study investigating the VEGF polymorphism in patients with idiopathic HMB-E. The evidence of the presence of VEGF polymorphism in patients with HMB-E may provide new opportunities for future research and treatment options. Thus, patients and doctors will avoid the risks of unnecessary surgeries. We therefore planned to investigate the relationship between VEGF polymorphism and idiopathic HMB-E. Materials And Methods Our study is a cross-sectional study conducted from February 2019 to March 2020. It was approved by the Ankara Yıldırım Beyazıt University Yenimahalle Training and Research Hospital Clinical Research Ethics Committee on the date of 29.01.2019 and with the decision number of 2019/01/01 and complied with the Helsinki Declaration, including current revisions and the Good Clinical Practice guidelines. Power analysis of the study showed that 128 patients were needed to gain 80% power when α error was set at 0.05, β error at 0.05, and effect size at 0.50. A total of 65 patients between the ages of 18-45 who were admitted with the complaint of abnormal uterine bleeding and diagnosed with idiopathic HMB according to the FIGO Classification System [10] and 65 voluntary women with regular menstruation were included in the study. All participants were informed about the study and consent forms were signed. The participants were selected according to the defined inclusion criteria: 18 to 45 years old, having a regular menstrual cycle between 24 - 38 days, not using hormonal or intrauterine contraception for at least three months prior the study, no abnormal ultrasonographic or hysteroscopic findings, not pregnant and not lactating. Women were excluded from the study if they had a uterine pathology (such as polyp, adenomyosis, leiomyoma, malignancy, hyperplasia), had a history of significant medical problems (such as coagulopathies, hypothyroidism, hyperprolactinemia, Polycystic ovary syndrome, endometriosis), smokers, taken any medicines that increases the tendency to bleeding. For patient selection according to these criteria all participants were evaluated based on a complete medical, gynecological and obstetric history and gynecological examination with ultrasound assessment. Additionally, hysteroscopy or dilatation and curettage was performed in the presence of suspicion of endometrial pathology. Menstrual blood loss was evaluated with Pictorial Blood loss Assessment Chart (PBAC) which has a a positive predictive value of 85.9% in diagnosing menorrhagia and with a good correlation to alkaline hematin method [11,12]. Self-evaluated PBAC consists of diagrams representing different soiled pads or tampons each day and pads were scored according to the degree of staining and the size of the clots on it. Women with a PBAC score > 100 were included in the HMB group and healthy, ovulating women with a PBAC score A, in the promoter region), rs1570360 (-1154G>A, in the promoter region) rs2010963 (+405G>C, at 5′UTR), rs3025039 (+936C>T, at 3'UTR), rs25648 (c534C>T, at exon1) and checked in Ensemble, dbSNP database. Peripheral venous blood samples were collected from all subjects and transferred to EDTA tubes. Samples were stored frozen at -20°C until they were studied. Laboratory studies were carried out in the INTERGEN Genetic and Rare Diseases Diagnosis Research and Application Center. DNA extraction and genotyping: DNA extraction was performed from 200 µl peripheral blood with spin column method using HibriGen Blood DNA isolation kit (İstanbul, Turkey). The isolates were measured with Nanodrop 1000 (Thermo Inc.) microvolume spectrophotometer and the study continued with samples containing 10 ng / µl and more. Primer design was made for PCR amplification of all coding region and exon-intron junction regions of VEGFA gene and 4 polymorphisms (rs699947, rs1570360, rs2010963, rs3025039). Primers, amplicon size and usage purposes are shown in table 1. Amplification of the regions was achieved by using the isolated DNA and the designed primers in the PCR reaction. Amplification efficiency was evaluated by visualizing the reaction results with 2% agarose gel electrophoresis . PCR pools were created by combining the PCRs of each sample and then purified by NucleoFast® 96 PCR kit (MACHEREY-NAGEL GmbH). The purified samples were quantitated by a spectrophotometer (Nanodrop N1000, Thermo Inc.). The amount of DNA was determined and diluted to 5 ng / µl. Detection of polymorphisms was performed by NGS (Next Generation DNA Sequencing) method using Miseq device (Illumina Inc. San Diego, CA, USA). Standardized samples were prepared for next generation sequencing using the Nextera XT sample preparation kit (Illumina Inc.). DNA Library preparations were made according to the determined instructions. A sample worksheet file was created to introduce the study to the device. All of the prepared samples were loaded into the sample loading compartment in the Miseq Reagent Kit v2 2x150 (MS-102-2002, Illumina Inc.) cartridge. After all the preparations and controls were made, the Miseq device was started. Approximately 24 hours later, study results were taken and analyzed. Alignment of the obtained readings was done with Miseq Reporter (illumina Inc.) software on human genome hg19 version. Analysis of the aligned bam files was performed using IGV 2.3 (Broad Institute) software. Statistical Analyses Continuous variables were first inspected for normality of statistical distribution graphically and by Shapiro–Wilk test. Data were reported as mean ± standard deviation (SD), median with interquartile ranges (IQRs) or numbers and percentages, as appropriate. The data were analyzed using the Student’s t test, Mann–Whitney test or chi square test to determine the significance of the differences between the groups. The Chi-square test was used to assess the variation in each SNP frequency from Hardy–Weinberg equilibrium (HWE). Logistic regression analysis models were used to calculate the odds ratio (OR) and 95% confidence interval (CI), thereby assessing the effect of genotypes on HMB risk. These analyzes were calculated with IBM SPSS 25 and the epitools package in R 3.6.1 program. The haplotype of VEGF polymorphisms was analyzed by using SHEsis. The linkage disequilibrium of genotype and allele pairs was calculated via the Haploview version 4.2 (Broad Institute, Cambridge, MA, USA).Statistical significance was set at P ≤ 0.05. Results Baseline characteristics The baseline characteristics of the subjects are summarized on Table 2. There were no differences in age, Body Mass Index (BMI), marital status, gravidity, parity, age at menarche, length of menstrual cycle between the analyzed groups. Compared with the control group, as aspected the patients in HMB group presented significant increases in menses duration and PBAC score. Genotype and allele distribution of VEGF polymorphisms The genotype frequency distribution of the selected population were found to be compatible in Hardy-Weinberg equilibrium (p > 0.05), suggesting it represents the population. As shown in Table 3, the risk of having HMB in individuals with the VEGF gene −2578A>C polymorphic region CC genotype was 3.05 times higher, the AC + CC genotype was 2.35 times higher compared with the AA genotype, C allele was 1.75 times higher compared with A allele (CC vs AA, OR = 3.05, 95% CI = 1.11-8.84, p = 0.025; AC + CC vs AA, OR = 2.35, 95% CI = 0.97-6.0, p = 0.051; C vs A, OR = 1.75, 95% CI = 1.07-2.88, p = 0.024). In comparison with the −1154G>A polymorphic region GG genotype, AA genotype is related to 3.49 times higher risk of HMB and in comparison with G allele, A allele is related to 1.74 times higher risk og HMB (AA vs GG, OR=3.49, % 95 CI=0.89-18.10, P = 0.06; A vs G, OR=1.74, % 95 CI =1.01-3.01, P = 0.04). However, the genotype and allele frequency distributions of rs2010963, rs3025039 and rs25648 were not statistically different between groups (all p > 0.05). Haplotype analysis for the association between VEGF gene polymorphisms and HMB risk VEGF gene polymorphisms in linkage disequilibrium analysis including four SNP (-2578C>A, -1154G>A, +405G>C and 534C>T) revealed one SNP block (Figure 1). We detected four main haplotypes with frequencies greater than 0.03. CACC, AGGC, CAGC, AAGT. These haplotypes were analyzed with the online software SHEsis and compared between the HMB and the control group (Table 4). The AGGC haplotype was found to be statistically significantly lower in the HMB group with a percentage of 23.8% than in the control group 38.5% (OR = 0.505, 95% CI = 0.295-1.517, p = 0.012). The CAGC haplotype was statistically significantly higher in the HMB group with 25.4% and 9.2% in the control group (OR = 3.387, 95% CI 0.481-2.116, p = 0.0005). As a result, it was concluded that AGGC haplotype decreased the risk of HMB and CAGC haplotype increased the risk of HMB. Discussion In this study we aimed to investigate the significance of SNPs of the VEGF gene (rs699947 (-2578C>A), rs1570360 (-1154G>A) rs2010963 (+405G>C), rs3025039 (+936C>T), rs25648 (c534C>T) in HMB. We have found increased risk for HMB in patients with CC, AC+CC genotype, and C allele of the -2578C>A polymorphic region and AA genotype and A allele of the -1154G>A polymorphic region (p C, +936C>T, and c534C>T (p > 0.05). In the literature, we have not encountered any studies emphasising on the relationship between SNPs and HMB. Nevertheless, there are several studies investigating the effect of VEGF gene polymorphisms in cardiovascular diseases, essential hypertension, certain cancer types, psoriasis, and endometriosis. Although being a unique study represents strength of our work, it also enabled us to discuss or compare our results with similar papers. Therefore, we compared our findings with articles about endometriosis, which defines a gynecologic disease that endometrial tissue is present outside the uterus. Perini et al. [13] evaluated -2578C>A, −460T>C, −1154G>A, +405G>C, and +936C>T polymorphisms in 182 Brazilian women with endometriosis and reported that variant allele -1154A was had significant relationship with endometriosis. They found AA genotype in 9.3% of patients and 1.9% of controls while the frequency of GA+AA genotype was 44.1% in patients and 30.2% in controls, and frequency of A allele was 26.7% in patient group and 16.0% in controls (p < 0.05). In our study, the AA genotype was found in 56.9% of patients and 38.5% of controls while the frequency of GA+AA genotype was 95.4% for patients and 87.7% for controls and the frequency of A allele was 76.1% in HMB patients and 61.5% in controls (p A polymorphic region and an approximate 6-fold increased risk for AA genotype. Similarly, we have observed an approximate two-fold increased risk for HMB in individuals with GA+AA genotype (p > 0.05), an approximate 3.5 fold increase in AA genotype (p = 0.06), and an approximate two fold increase in case of harbouring A allele (p = 0.04). Although these two studies presents distinct genotype and allele frequencies, individuals having A allele in 1154G>A polymorphic region have been found to have significantly increased risk for the defined diseases. On the other hand, in another study from Northern China on 344 women with endometriosis and 360 healthy controls by Liu et al. [14], AA genotype of the -1154G>A polymorphic region was alleged to decrease the risk of endometriosis. The frequency of AA genotype of the -1154G>A polymorphic region was 1.7% in patients and 5.8% in controls while the frequency of harboring A allele was 16.1% in patients and 22.2% in controls concluding a statistically significant reduction of endometriosis risk in case of A allele of -1154G>A polymorphism. Perini at al. [13] did not report an association between endometriosis and VEGF gene -2578C>A polymorphisms. Similarly, in our study the frequency of CC genotype of -2578C>A polymorphism was 38.5% in patients and 24.6% in controls, and the frequency of AC + CC genotype was 86.2% in patients and 72.3% in controls. Despite being more frequent in patients, the difference was not statistically significant (p = 0.083). As for the C allele, the frequency was 62.3% in patients and 48.5% in controls which established a statistically significant difference (p A polymorphic region and an approximate 2 fold increased risk in AC+CC genotype and C allele. Also, Liu et al. [14] reported frequencies of AA, CA, and CC genotypes and A allele frequency of -2578C>A polymorphic region in patient and control groups respectively; 3.2% - 8.1%; 32.0% - 36.4%, and 64.8% - 55.6%, 19.2% - 26.3% concluding a statistically significant difference in terms of genotype and allele harbouring (p C, +936C>T polymorphic region our results suggest no significant effect on the susceptibility to HMB. It is noteworthy that our results are consistent with Perini’s study [13] and Zhao and colleagues [15] which consist a larger number (958 cases and 959 controls) of Australian women. Similarly Liu et al. [14] found that the + 936C>T polymorphic region does not have a significant relationship with the risk of developing endometriosis. The main reason for these inconsistent results may be the differences between ethnic groups. For example, the Ensembl database shows that the frequency of the VEGF -2578 A allele was 27.2% with the CHB (Han Chinese in Beijing), 34.1% with AMR (American), and 45.5% with CEU (Utah Residents with Northern and Western European Ancestry). In the literature, we found two studies from our country evaluating the effect of VEGF gene +405G>C polymorphism on endometriosis risk with controversial results. Altınkaya et al. [16] evaluated the genotype frequencies of VEGF +405G>C polymorphic regions on 98 endometriosis patients and 94 controls. They detected GC genotype in 58.2% of patients and 10.6% of controls and G allele in 45.4% of patients and 5.3% of controls. They suggested that GC genotype and G allele may be associated with the advanced grade endometriosis risk in the Turkish population. In another study from Turkey, Attar et al. [17.] also proposed that CC genotype of +405G>C polymorphisms may be related to endometriosis whereas G allele has a protective role against endometriosis. The small sample sizes impede with reflecting data of the whole Turkish population and may partially explain the conflicting results. The meta-analyses also yielded conflicting results. In a meta-analysis evaluating 14 eligible studies on a total of 3313 endometriosis patients and 3393 controls, VEGF gene -1154G>A polymorphic region GA genotype and A allele and -2578C>A polymorphic region CC genotype and C allele were found to reduce endometriosis risk whereas +936C>T poymorphic region CT genotype and T allele increased the risk similar to our results on HMB [18]. No effect of the +405G>C polymorphism was reported in line with our findings. On the contrary, Jiang et al. [19] stated that VEGF + 405G>C and + 936C>T SNPs may be associated with the risk of endometriosis in their meta-analysis, in which they investigated 9 studies including 1610 endometriosis patients and 1643 control cases. The most important limitation of the current study is the small sample size which can also be held responsible for the controversial results in other studies in the literature. Besides, the facts that these studies have been performed on distinct ethnic groups and different diseases and having identified various haplotypes may have led to the conflicting results. These diverse results suggest that disease tendency may stem from not solely a single polymorphism but a combined effect of polymorphisms and that haplotype effect may play a more significant role in disease tendency than single polymorphisms. In our study in the examination of the - 2578C>A, -1154G>A, +405G>C and 534C> T polymorphic regions of the VEGF gene we have identified 4 haplotypes: CACC (38.1%), AGGC (31.2%), CAGC (17.3%), AAGT (12.3%). AGGC haplotype was less prevalent in HMB patients (23.8% vs 38.5%) while CAGC haplotype was more frequent in the HMB group (25.4% vs 9.2%). Perini et al. [13] emphasized that CCGG haplotype derived from four polymorphisms (-2578C>A / -460T>C / -1154G>A / + 405G>C) has a protective effect against the development of endometriosis (3% in cases, 6.7% in the control group). Liu et al. [14] stated that the VEGF gene -460C>T -1154G>A, -2578C>A regions included CAA, TAA and TAC haplotypes can significantly reduce the risk of developing endometriosis, and the CAC haplotype can significantly increase the risk of developing endometriosis. The polymorphic regions included in the studies produced different linkage disequilibrium results and different haplotypes were obtained in each study making it difficult to compare study results. Our study on VEGF gene polymorphisms in Turkish women with HMB suggests increased risk for C allele, CC, and AC+CC genotypes of −2578A>C polymorphic region, A allele, AA genotype, and CAGC haplotype of the −1154G>A polymorphic region whereas protective role of the AGGC haplotype. However, further studies with a larger sample size are required to figure out a more certain association. Declarations Author Contribution İ Kaygusuz: Project development, Data collection, Data analysis, Manuscript writing, editing N Semerci Gündüz: Project development, reduction, editing I. Ethical approval: The study was approved by the Ankara Yıldırım Betazıt University Human Ethical Committee II. Funding details (In case of Funding): No funding III. Conflict of interest: The authors declare that they have no conflict of interest. IV. Informed Consent: Signed informed consent was obtained from all patients before starting study. References Mints M, Blomgren B, Falconer C, Fianu-Jonasson A, Palmblad J (2005) Microvascular density, vascular endothelial growth factor A, and its receptors in endometrial blood vessels in patients with menorrhagia. Fertil Steril 84(3):692-700. https://doi.org/10.1016/j.fertnstert.2005.03.065 Elkilani OA, Soliman MA (2017) Angiogenesis mediators in women with idiopathic heavy menstrual bleeding. Int J Gynaecol Obstet 136(3):280-284. https://doi.org/10.1002/ijgo.12068 Biswas Shivhare S, Bulmer JN, Innes BA, Hapangama DK, Lash GE (2018) Endometrial vascular development in heavy menstrual bleeding: altered spatio-temporal expression of endothelial cell markers and extracellular matrix components. Hum Reprod 33(3):399-410. https://doi.org/10.1093/humrep/dex378 Kuzmina N, Palmblad J, Mints M (2011) Predictive factors for the occurrence of idiopathic menorrhagia: evidence for a hereditary trait. Mol Med Rep 4(5):935-939. https://doi.org/10.3892/mmr.2011.514 Andersson E, Zetterberg E, Vedin I, Hultenby K, Palmblad J, Mints M (2015) Low pericyte coverage of endometrial microvessels in heavy menstrual bleeding correlates with the microvessel expression of VEGF-A. Int J Mol Med 35(2):433-438. https://doi.org/10.3892/ijmm.2014.2035 Mansour D, Hofmann A, Gemzell-Danielsson K (2021) A Review of Clinical Guidelines on the Management of Iron Deficiency and Iron-Deficiency Anemia in Women with Heavy Menstrual Bleeding. Adv Ther 38(1):201-225. https://doi.org/10.1007/s12325-020-01564-y Fraser IS, Critchley HO, Munro MG, Broder M, Writing Group for this Menstrual Agreement Process (2007) A process designed to lead to international agreement on terminologies and definitions used to describe abnormalities of menstrual bleeding. Fertil Steril 87(3):466-476. https://doi.org/10.1016/j.fertnstert.2007.01.023 Mints M, Hultenby K, Zetterberg E, Blomgren B, Falconer C, Rogers R, Palmblad J (2007) Wall discontinuities and increased expression of vascular endothelial growth factor-A and vascular endothelial growth factor receptors 1 and 2 in endometrial blood vessels of women with menorrhagia. Fertil Steril 88(3):691-697. https://doi.org/10.1016/j.fertnstert.2006.11.190 Mints M, Blomgren B, Palmblad J (2010) Expression of angiopoietins 1, 2 and their common receptor tie-2 in relation to the size of endothelial lining gaps and expression of VEGF and VEGF receptors in idiopathic menorrhagia. Fertil Steril 94(2):701-707. https://doi.org/10.1016/j.fertnstert.2009.03.042 Munro MG, Critchley HO, Broder MS, Fraser IS, FIGO Working Group on Menstrual Disorders (2011) FIGO classification system (PALM-COEIN) for causes of abnormal uterine bleeding in nongravid women of reproductive age. Int J Gynaecol Obstet 113(1):3-13. https://doi.org/ 1016/j.ijgo.2010.11.011 Higham JM, O’Brien PM, Shaw RW (1990) Assessment of menstrual blood loss using a pictorial chart. Br J Obstet Gynaecol 97:734-739. https://doi.org/10.1111/j.1471-0528.1990.tb16249.x Zakherah MS, Sayed GH, El-Nashar SA, Shaaban MM (2011) Pictorial blood loss assessment chart in the evaluation of heavy menstrual bleeding: diagnostic accuracy compared to alkaline hematin. Gynecol Obstet Invest 71: 281-284. https://doi.org/10.1159/000320336 Perini JA, Cardoso JV, Berardo PT, Vianna-Jorge R, Nasciutti LE, Bellodi-Privato M, Machado DE, Abrão MS (2014) Role of vascular endothelial growth factor polymorphisms (-2578C>A, -460 T>C, -1154G>A, +405G>C and +936C>T) in endometriosis: a case-control study with Brazilians. BMC Womens Health 14:117. https://doi.org/ 1186/1472-6874-14-117 Liu Q, Li Y, Zhao J, Sun DL, Duan YN, Wang N, Zhou RM, Kang S (2009) Association of polymorphisms -1154G/A and -2578C/A in the vascular endothelial growth factor gene with decreased risk of endometriosis in Chinese women. Hum Reprod 24(10):2660-2666. https://doi.org/10.1093/humrep/dep208 Zhao ZZ, Nyholt DR, Thomas S, Treloar SA, Montgomery GW (2008) Polymorphisms in the vascular endothelial growth factor gene and the risk of familial endometriosis. Mol Hum Reprod 14(9):531-538. https://doi.org/10.1093/molehr/gan043 Altinkaya SO, Ugur M, Ceylaner G, Ozat M, Gungor T, Ceylaner S (2011) Vascular endothelial growth factor +405 C/G polymorphism is highly associated with an increased risk of endometriosis in Turkish women. Arch Gynecol Obstet 283(2):267-72. https://doi.org/10.1007/s00404-009-1344-1 Attar R, Agachan B, Kuran SB, Toptas B, Eraltan IY, Attar E, Isbir T (2010) Genetic variants of vascular endothelial growth factor and risk for the development of endometriosis. In Vivo 24(3):297-301. Li YZ, Wang LJ, Li X, Li SL, Wang JL, Wu ZH, Gong L, Zhang XD (2013) Vascular endothelial growth factor gene polymorphisms contribute to the risk of endometriosis: an updated systematic review and meta-analysis of 14 case-control studies. Genet Mol Res 12(2):1035-44. https://doi.org/10.4238/2013.April.2.20 Jiang Y, Tang JY, Wu Y, Zhao TF (2012) Vascular endothelial growth factor gene polymorphisms and the risk of endometriosis: a systematic review. Zhonghua Fu Chan Ke Za Zhi 47(3):179-84. Tables Table 1. Primers, amplicon size and usage purposes Primer Orientation Sequencing Genotyping Amplicon size (bp) Sequence (5'-3') VEGFA_SNP2_F Forward Exon 1 SNP 2 SNP 3 SNP 5 1500 CGGATGGGTAATTTTCAGGCTGTG VEGFA_1R Revers CCTCCCCCTGCACCTAAGACGAC VEGFA_2F Forward Exon 2 - 468 GGGAAGTGTGGGGAAGGTACAGG VEGFA_2R Revers CTTCCCCTTCCTCCCCACAGTTC VEGFA_3F Forward Exon 3 - 433 GAAGCTCCAAAGAGTGGCATTACAG VEGFA_3R Revers ACCATACCTCCCCTGTGCAACTC VEGFA_4-5F Forward Exon 4 Exon 5 - 975 AGGAGTCAGGGTGAAGCCTAGAGAG VEGFA_4-5R Revers CACTAGCCCTAGAGCCATCATCCTG VEGFA_6F Forward Exon 6 - 398 AGAGACCACCTGCCTCCTGACAC VEGFA_6R Revers TCTACCCGTTGGTGCCAATTAGTG VEGFA_7F Forward Exon 7 - 429 CTGTAGCGCTCGGATCCTTCCAG VEGFA_7R Revers ACCAGGCAGGCAGCTAGAAACTGAG VEGFA_8F Forward Exon 8 SNP 4 463 CCTTCCTGTCCTCTCTGCTCTTATGG VEGFA_8R Revers ATCTTCCGGGCTCGGTGATTTAG VEGFA_SNP1_F Forward - SNP 1 250 CTGGAGCGTTTTGGTTAAATTGAGG VEGFA_SNP1_R Revers CCCCATCCCATTCTTGCATATAGG Table 2: Baseline characteristics of study subjects Variables HMB group (n=65) Control group (n=65) t/z c 2 p Age (year) 30.58 ± 7.06 29.08 ± 6.56 t=1.261 0.210 Body Mass Index (kg/m 2 ) 22.35 ± 2.57 22.77 ± 2.65 t=0.923 0.358 Marital status Married 43 (% 66.2) 40 (% 61.5) c 2 =0.300 0.584 Unmarried 22 (% 33.8) 25 (% 38.5) Gravidity 1 (2) 1 (1) Z=-1.361 0.180 Parity 1 (2) 1 (2) Z=-1.185 0.290 Age at menarche (year) 13 (2) 13 (1) Z=-1.311 0.190 Menses duration (days) 7 (2.5) 5 (2) Z=5.339 <0.001* Length of Menstrual cycle (day) 28 (3) 28 (2) Z=0.320 0.749 PBAC score 258 (246) 50 (44) Z=9.937 <0.001 Abbreviations: PBAC, Pictorial Blood Loss Assessment Chart Data are mean ± SD, median (IQR) or numbers (n) and percentages (%) t= Student’s t test, Z=Mann–Whitney U-test, c 2 = Chi-square * p values ≤ 0.05 were considered statistically significant Table 3. Logistic regression analysis of associations between VEGF polymorphisms and risk of HMB AMK-E grup, n = 65 (%) Kontrol grup, n = 65 (%) OR (95% CI) p rs699947 (−2578A>C) AA 9 (13.8) 18 (27.7) Referans AC 31 (47.7) 31 (47.7) 1.97 (0.77-5.29) 0.15 CC 25 (38.5) 16 (24.6) 3.05 (1.11-8.84) 0.03* AC+CC 56 (86.2) 47 (72,3) 2.35 (0.97-6.0) 0.05* A Alel 49 (37.7) 67 (51.5) Referans C Alel 81 (62.3) 63 (48.5) 1.75 (1.07-2.88) 0.02* rs1570360 (−1154G>A) GG 3 (4.6) 10 (15.4) Referans GA 25 (38.5) 30 (46.2) 2.13 (0.53-11.20) 0.26 AA 37 (56.9) 25 (38.5) 3.49 (0.89-18.10) 0.06* GA+AA 62 (95.4) 57(87.7) 2.07 (0.56-10.32) 0.26 G Alel 31 (23.8) 50 (38.4) Referans A Alel 99 (76.1) 80 (61.5) 1.74 (1.01-3.01) 0.04* rs2010963 (+405G>C) CC 9 (13.8) 9 (13.8) Referans CG 30 (46.2) 33 (50.8) 0.91 (0.31-2.66) 0.85 GG 26 (40.0) 23 (35.4) 1.12 (0.37-3.41) 0.82 CG+GG 56 (86.2) 56 (86.2) 0.99 (0.33-2.78) 1.00 C Alel 48 (36.9) 51 (39.2) Referans G Alel 82 (63.1) 79 (60.8) 1.10 (0.66-1.82) 0.70 rs3025039 (+936C>T) CC 49 (75.4) 43 (66.2) Referans CT 15 (23.1) 20 (30.8) 0.66 (0.29-1.45) 0.29 TT 1 (1.5) 2 (3.1) 0.46 (0.01-5.98) 0.49 CT+TT 16 (24.6) 22 (33.9) 0.64 (0.29-1.37) 0.24 C Alel 113 (86.9) 106 (81.5) Referans T Alel 17 (13.1) 24 (18.5) 0.66 (0.33-1.30) 0.23 rs25648 (c.534C>T) CC 49 (75.4) 51 (78.5) Referans CT 16 (24.6) 12 (18.5) 0.72 (0.31-1.68) 0.18 TT 0 2 (3.1) - - CT+TT 16 (24.6) 14 (21.6) 0.84 (0.37-1.90) 0.68 C Alel 114 (87.7) 114 (87.7) Referans T Alel 16 (12.3) 16 (12.3) 1 (0.47-2.12) 1.00 Abbreviations: OR, odds ratio; CI, confidence interval. * p values ≤ 0.05 were considered statistically significant Table 4. Haplotype distributions of VEGF gene polymorphisms rs699947, rs1570360, rs2010963, and rs25648 Haplotype Frequency (%) HMB group, n=65 (%) Control group, n=65 (%) P OR (95% CI) CAAC 38.1 48 (36.9) 51 (39.2) 0,737 0.918 (0.555-1.517) AGGC 31.2 31 (23.8) 50 (38.5) 0,012* 0.505 (0.295-0.864) CAGC 17.3 33 (25.4) 12 (9.2) 0,0005* 3.387 (1.659-6.917) AAGT 12.3 16 (12.3) 16 (12.3) 0.981 1.009 (0.481-2.116) Abbreviations: OR, odds ratio; CI, confidence interval. * p values ≤ 0.05 were considered statistically significant Cite Share Download PDF Status: Published Journal Publication published 08 Sep, 2021 Read the published version in Archives of Gynecology and Obstetrics → Version 1 posted Reviews received at journal 03 May, 2021 Reviewers invited by journal 30 Apr, 2021 Editor invited by journal 28 Apr, 2021 Editor assigned by journal 23 Apr, 2021 First submitted to journal 23 Apr, 2021 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-459616","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":24544342,"identity":"3ddc25f7-01ca-4e69-b82c-94ee6b7a0394","order_by":0,"name":"İkbal Kaygusuz","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7ElEQVRIiWNgGAWjYBACNh4eBoYHQIYEiPeBgSGBOC0JUC2MM4jRwoCshZmHGC18PGcPfkhgsJOTnHb42GPbNrs8fvYGxg8fc/A4jLcvWSKBIdlYWjot3Ti3LblYsucAs+TMbXi08PMYALUcSJwnnWMmndvGnLjhRgIbMy9+LcY/gFrq50nnf5O2bKsnQgtvjxnIlgRp6Rw2aca2w0Ro4TmXZgH0i+HM2Wlmkj3njifO7DnYjNcv8j25h298YLCTl7id/EziR1l1Yj9788EPH/FoAQPGfzAGG5hsIKAeBfwhRfEoGAWjYBSMFAAAAdBKSXR4z9AAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-5635-505X","institution":"Department of Obstetrics and Gynecology, VM Medicalpark Ankara Private Hospital, Yüksek İhtisas University, Ankara, Turkey","correspondingAuthor":true,"prefix":"","firstName":"İkbal","middleName":"","lastName":"Kaygusuz","suffix":""},{"id":24544343,"identity":"8b704df7-97e1-432b-b41e-e7f7ef90baf3","order_by":1,"name":"Nur Semerci Gündüz","email":"","orcid":"","institution":"Department of Medical Genetics, Ankara Yıldırım Beyazıt University, Denizli, Turkey","correspondingAuthor":false,"prefix":"","firstName":"Nur","middleName":"Semerci","lastName":"Gündüz","suffix":""}],"badges":[],"createdAt":"2021-04-24 16:47:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-459616/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-459616/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00404-021-06225-1","type":"published","date":"2021-09-08T16:10:03+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":8832440,"identity":"4fdf939b-703f-4f9b-a99f-b792bf3ed9fc","added_by":"auto","created_at":"2021-05-05 22:12:20","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":30847,"visible":true,"origin":"","legend":"Linkage disequilibrium plot created by Haploview 4.2","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-459616/v1/60f1294d9307f69c3d6adff3.jpg"},{"id":17537119,"identity":"422f279e-2413-4fc3-aa00-60b6676a6c9f","added_by":"auto","created_at":"2022-01-21 16:10:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":347862,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-459616/v1/8fb02c14-9a0e-405b-be4e-a05db2643929.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eInvestigation of Vascular Endothelial Growth Factor (VEGF) Polymorphism in Patients With Idiopathic Heavy Menstrual Bleeding\u003c/p\u003e","fulltext":[{"header":"Introduction ","content":"\u003cp\u003eHeavy menstrual bleeding (HMB) is an important health problem defined as menstruation at regular intervals but with excessive flow and duration. Clinically, it is defined as a blood loss of more than 80 ml per cycle. It is a common gynecological problem among women of reproductive age and accounts for more than 20% of outpatient visits to gynecologists [1]. Although HMB is often associated with uterine pathology (e.g., fibroid, polyp, adenomyosis, carcinoma), abnormal blood clotting or disruption of hormonal regulation, approximately 50% of HMB cases occur in the absence of recognized uterine pathology [2,3], suggesting a defect in the cellular processes and regulatory mechanisms of menstruation\u003cstrong\u003e.\u003c/strong\u003e Such idiopathic HMB of endometrial origin (HMB-E) has been estimated to account for 9-14% of gyneco\u0026shy;logical outpatient visits [4,5].\u003c/p\u003e\n\u003cp\u003eHMB can lead to iron deficiency anemia. Current treatment options often compromise fertility, and may require hysterectomy in patients who do not respond to the treatments [6]. Another problem is increased maternal morbidity and mortality for pregnant women who has HMB-associated anemia. Heavy bleeding can affect daily activities. Need for long-term medication, the side effects of these therapies, and the intolerance can cause psychological and social discomfort. Also for numerous female individuals, problems related to employment have led to the designation of HMB as a public health problem [4].\u003c/p\u003e\n\u003cp\u003eDisturbance of endometrial angiogenesis is one of several proposed underlying mechanisms that have been suggested to play a role in HMB [4,5]. In the formation of functional and stable micro vessels, covering the luminal surface of endothelial tubes with mesenchymal pericytes is an important step. The pericytes interact tightly and adhere to the endothelial cells with the pores in the basal layer [7]. Pericytes may induce angiogenesis with Vascular Endothelial Growth Factor (VEGF) production which stimulates endothelial cell proliferation and tube formation. Previous studies have shown that The biopsy specimens of women with HMB have revealed that number of capillaries expressing VEGF-A and its receptors (VEGFR-1 and VEGFR-2) were significantly higher in patients with HMB compared to healthy controls [1]. It is known that glandular luminal surfaces of patients with HMB are wider and this finding is highly correlated with overexpression of VEGF-A and VEGFR-1 [8]. It is suggested that the mesenchymal pericytes acting on the basis of angiogenesis may contribute to the vascular fragility. This leads to excessive blood loss due to extensive endothelial cell gaps and abnormal vascular remodeling as a result of inappropriate coverage of the laminal surface of endothelial tubes [8,9].\u003c/p\u003e\n\u003cp\u003eIn the literature, there is no study investigating the VEGF polymorphism in patients with idiopathic HMB-E. The evidence of the presence of VEGF polymorphism in patients with HMB-E may provide new opportunities for future research and treatment options. Thus, patients and doctors will avoid the risks of unnecessary surgeries. We therefore planned to investigate the relationship between VEGF polymorphism and idiopathic HMB-E.\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cp\u003eOur study is a cross-sectional study conducted from February 2019 to March 2020. It was approved by the Ankara Yıldırım Beyazıt University Yenimahalle Training and Research Hospital Clinical Research Ethics Committee on the date of 29.01.2019 and with the decision number of 2019/01/01 and complied with the Helsinki Declaration, including current revisions and the Good Clinical Practice guidelines.\u003c/p\u003e\n\u003cp\u003ePower analysis of the study showed that 128 patients were needed to gain 80% power when \u0026alpha; error was set at 0.05, \u0026beta; error at 0.05, and effect size at 0.50.\u003c/p\u003e\n\u003cp\u003eA total of 65 patients between the ages of 18-45 who were admitted with the complaint of abnormal uterine bleeding and diagnosed with idiopathic HMB according to the FIGO Classification System [10]\u0026nbsp; and 65 voluntary women with regular menstruation were included in the study. All participants were informed about the study and consent forms were signed.\u003c/p\u003e\n\u003cp\u003eThe participants were selected according to the defined inclusion criteria: 18 to 45 years old, having a regular menstrual cycle between 24 - 38 days, not using hormonal or intrauterine contraception for at least three months prior the study, no abnormal ultrasonographic or hysteroscopic findings, not pregnant and not lactating.\u003c/p\u003e\n\u003cp\u003eWomen were excluded from the study if they had a uterine pathology (such as polyp, adenomyosis, leiomyoma, malignancy, hyperplasia), had a history of significant medical problems (such as coagulopathies, hypothyroidism, hyperprolactinemia, Polycystic ovary syndrome, endometriosis), smokers, taken any medicines that increases the tendency to bleeding.\u003c/p\u003e\n\u003cp\u003eFor patient selection according to these criteria all participants were evaluated based on a complete medical, gynecological and obstetric history and gynecological examination with ultrasound assessment. Additionally, hysteroscopy or dilatation and curettage was performed in the presence of suspicion of endometrial pathology.\u003c/p\u003e\n\u003cp\u003eMenstrual blood loss was evaluated with Pictorial Blood loss Assessment Chart (PBAC) which has a a positive predictive value of 85.9% in diagnosing menorrhagia and with a good correlation to alkaline hematin method [11,12]. Self-evaluated PBAC consists of diagrams representing different soiled pads or tampons each day and pads were scored according to the degree of staining and the size of the clots on it. Women with a PBAC score \u0026gt; 100 were included in the HMB group and healthy, ovulating women with a PBAC score \u0026lt; 100 were considered in the control group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSingle nucleotide polymorphism (SNP) selection: \u003c/strong\u003eFive highly plausible candidate SNPs in the VEGF gene were selected including rs699947 (-2578C\u0026gt;A, in the promoter region), rs1570360 (-1154G\u0026gt;A, in the promoter region) rs2010963 (+405G\u0026gt;C, at 5\u0026prime;UTR), rs3025039 (+936C\u0026gt;T, at 3'UTR), rs25648 (c534C\u0026gt;T, at exon1) and checked in Ensemble, dbSNP database.\u003c/p\u003e\n\u003cp\u003ePeripheral venous blood samples were collected from all subjects and transferred to EDTA tubes. Samples were stored frozen at -20\u0026deg;C until they were studied.\u003c/p\u003e\n\u003cp\u003eLaboratory studies were carried out in the INTERGEN Genetic and Rare Diseases Diagnosis Research and Application Center.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDNA extraction and genotyping: \u003c/strong\u003eDNA extraction was performed from 200 \u0026micro;l peripheral blood with spin column method using HibriGen Blood DNA isolation kit (İstanbul, Turkey). The isolates were measured with Nanodrop 1000 (Thermo Inc.) microvolume spectrophotometer and the study continued with samples containing 10 ng / \u0026micro;l and more.\u003c/p\u003e\n\u003cp\u003ePrimer design was made for PCR amplification of all coding region and exon-intron junction regions of VEGFA gene and 4 polymorphisms (rs699947, rs1570360, rs2010963, rs3025039). Primers, amplicon size and usage purposes are shown in table 1.\u003c/p\u003e\n\u003cp\u003eAmplification of the regions was achieved by using the isolated DNA and the designed primers in the PCR reaction. Amplification efficiency was evaluated by visualizing the reaction results with 2% agarose gel electrophoresis\u003cstrong\u003e. \u003c/strong\u003ePCR pools were created by combining the PCRs of each sample and then purified by NucleoFast\u0026reg; 96 PCR kit (MACHEREY-NAGEL GmbH). The purified samples were quantitated by a spectrophotometer (Nanodrop N1000, Thermo Inc.). The amount of DNA was determined and diluted to 5 ng / \u0026micro;l.\u003c/p\u003e\n\u003cp\u003eDetection of polymorphisms was performed by NGS (Next Generation DNA Sequencing) method using Miseq device (Illumina Inc. San Diego, CA, USA). Standardized samples were prepared for next generation sequencing using the Nextera XT sample preparation kit (Illumina Inc.). DNA Library preparations were made according to the determined instructions. A sample worksheet file was created to introduce the study to the device. All of the prepared samples were loaded into the sample loading compartment in the Miseq Reagent Kit v2 2x150 (MS-102-2002, Illumina Inc.) cartridge. After all the preparations and controls were made, the Miseq device was started. Approximately 24 hours later, study results were taken and analyzed. Alignment of the obtained readings was done with Miseq Reporter (illumina Inc.) software on human genome hg19 version. Analysis of the aligned bam files was performed using IGV 2.3 (Broad Institute) software.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eContinuous variables were first inspected for normality of statistical distribution graphically and by Shapiro\u0026ndash;Wilk test. Data were reported as mean \u0026plusmn; standard deviation (SD), median with interquartile ranges (IQRs) or numbers and percentages, as appropriate. The data were analyzed using the Student\u0026rsquo;s t test, Mann\u0026ndash;Whitney test or chi square test to determine the significance of the differences between the groups. The Chi-square test was used to assess the variation in each SNP frequency from Hardy\u0026ndash;Weinberg equilibrium (HWE). Logistic regression analysis models were used to calculate the odds ratio (OR) and 95% confidence interval (CI), thereby assessing the effect of genotypes on HMB risk. These analyzes were calculated with IBM SPSS 25 and the epitools package in R 3.6.1 program. The haplotype of VEGF polymorphisms was analyzed by using SHEsis. The linkage disequilibrium of genotype and allele pairs was calculated via the Haploview version 4.2 (Broad Institute, Cambridge, MA, USA).Statistical significance was set at P \u0026le; 0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eBaseline characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe baseline characteristics of the subjects are summarized on Table 2. There were no differences in age, Body Mass Index (BMI), marital status, gravidity, parity, age at menarche, length of menstrual cycle between the analyzed groups. Compared with the control group, as aspected the patients in HMB group presented significant increases in menses duration and PBAC score.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGenotype and allele distribution of VEGF polymorphisms\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe genotype frequency distribution of the selected population were found to be compatible in Hardy-Weinberg equilibrium (p \u0026gt; 0.05), suggesting it represents the population.\u003c/p\u003e\n\u003cp\u003eAs shown in Table 3, the risk of having HMB in individuals with the VEGF gene \u0026minus;2578A\u0026gt;C polymorphic region CC genotype was 3.05 times higher, the AC + CC genotype was 2.35 times higher compared with the AA genotype, C allele was 1.75 times higher compared with A allele (CC vs AA, OR = 3.05, 95% CI = 1.11-8.84, p = 0.025; AC + CC vs AA, OR = 2.35, 95% CI = 0.97-6.0, p = 0.051; C vs A, OR = 1.75, 95% CI = 1.07-2.88, p = 0.024). In comparison with the \u0026minus;1154G\u0026gt;A polymorphic region GG genotype, AA genotype is related to 3.49 times higher risk of HMB and in comparison with G allele, A allele is related to 1.74 times higher risk og HMB (AA vs GG, OR=3.49, % 95 CI=0.89-18.10, P = 0.06; A vs G, OR=1.74, % 95 CI =1.01-3.01, P = 0.04). However, the genotype and allele frequency distributions of rs2010963, rs3025039 and rs25648 were not statistically different between groups\u0026nbsp; (all p \u0026gt; 0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHaplotype analysis for the association between VEGF gene polymorphisms and HMB risk\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eVEGF gene polymorphisms in linkage disequilibrium analysis including four SNP (-2578C\u0026gt;A, -1154G\u0026gt;A, +405G\u0026gt;C and 534C\u0026gt;T) revealed one SNP block (Figure 1).\u003c/p\u003e\n\u003cp\u003eWe detected four main haplotypes with frequencies greater than 0.03. CACC, AGGC, CAGC, AAGT. These haplotypes were analyzed with the online software SHEsis and compared between the HMB and the control group (Table 4). The AGGC haplotype was found to be statistically significantly lower in the HMB group with a percentage of 23.8% than in the control group 38.5% (OR = 0.505, 95% CI = 0.295-1.517, p = 0.012). The CAGC haplotype was statistically significantly higher in the HMB group with 25.4% and 9.2% in the control group (OR = 3.387, 95% CI 0.481-2.116, p = 0.0005). As a result, it was concluded that AGGC haplotype decreased the risk of HMB and CAGC haplotype increased the risk of HMB.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study we aimed to investigate the significance of SNPs of the VEGF gene (rs699947 (-2578C\u0026gt;A), rs1570360 (-1154G\u0026gt;A) rs2010963 (+405G\u0026gt;C), rs3025039 (+936C\u0026gt;T), rs25648 (c534C\u0026gt;T) in HMB. We have found increased risk for HMB in patients with CC, AC+CC genotype, and C allele of the -2578C\u0026gt;A polymorphic region and AA genotype and A allele of the -1154G\u0026gt;A polymorphic region (p \u0026lt; 0.05). However, we have not observed any associations between HMB and other three candidate polymorphisms of +405G\u0026gt;C, +936C\u0026gt;T, and c534C\u0026gt;T (p \u0026gt; 0.05).\u003c/p\u003e\n\u003cp\u003eIn the literature, we have not encountered any studies emphasising on the relationship between SNPs and HMB. Nevertheless, there are several studies investigating the effect of VEGF gene polymorphisms in cardiovascular diseases, essential hypertension, certain cancer types, psoriasis, and endometriosis. Although being a unique study represents strength of our work, it also enabled us to discuss or compare our results with similar papers. Therefore, we compared our findings with articles about endometriosis, which defines a gynecologic disease that endometrial tissue is present outside the uterus.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePerini et al. [13] evaluated -2578C\u0026gt;A, \u0026minus;460T\u0026gt;C, \u0026minus;1154G\u0026gt;A, +405G\u0026gt;C, and +936C\u0026gt;T polymorphisms in 182 Brazilian women with endometriosis and reported that variant allele\u0026nbsp;-1154A\u0026nbsp;was had significant relationship with endometriosis. They found AA genotype in 9.3% of patients and 1.9% of controls while the frequency of GA+AA genotype was 44.1% in patients and 30.2% in controls, and frequency of A allele was 26.7% in patient group and 16.0% in controls (p \u0026lt; 0.05). In our study, the AA genotype was found in 56.9% of patients and 38.5% of controls while the frequency of GA+AA genotype was 95.4% for patients and 87.7% for controls and the frequency of A allele was 76.1% in HMB patients and 61.5% in controls (p \u0026lt; 0.05). Perini et al. [13] reported an approximate two-fold increased risk for endometriosis in individuals with GA+AA genotype of the -1154G\u0026gt;A polymorphic region and an approximate 6-fold increased risk for AA genotype.\u0026nbsp; Similarly, we have observed an approximate two-fold increased risk for HMB in individuals with GA+AA genotype (p \u0026gt; 0.05), an approximate 3.5 fold increase in AA genotype (p = 0.06), and an approximate two fold increase in case of harbouring A allele (p = 0.04). Although these two studies presents distinct genotype and allele frequencies, individuals having A allele in 1154G\u0026gt;A polymorphic region have been found to have significantly increased risk for the defined diseases.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOn the other hand, in another study from Northern China on 344 women with endometriosis and 360 healthy controls by Liu et al. [14], AA genotype of the -1154G\u0026gt;A polymorphic region was alleged to decrease the risk of endometriosis. The frequency of AA genotype of the -1154G\u0026gt;A polymorphic region was 1.7% in patients and 5.8% in controls while the frequency of harboring A allele was 16.1% in patients and 22.2% in controls concluding a statistically significant reduction of endometriosis risk in case of A allele of -1154G\u0026gt;A polymorphism.\u003c/p\u003e\n\u003cp\u003ePerini at al. [13] did not report an association between endometriosis and VEGF gene -2578C\u0026gt;A polymorphisms. Similarly, in our study the frequency of CC genotype of -2578C\u0026gt;A polymorphism was 38.5% in patients and 24.6% in controls, and the frequency of AC + CC genotype was 86.2% in patients and 72.3% in controls. Despite being more frequent in patients, the difference was not statistically significant (p = 0.083). As for the C allele, the frequency was 62.3% in patients and 48.5% in controls which established a statistically significant difference (p \u0026lt; 0.05). Therefore, we have found an approximate 3 fold increased risk for HMB in individuals with CC genotype of the -2578C\u0026gt;A polymorphic region and an approximate 2 fold increased risk in AC+CC genotype and C allele. Also, Liu et al. [14] reported frequencies of AA, CA, and CC genotypes and A allele frequency of -2578C\u0026gt;A polymorphic region in patient and control groups respectively; 3.2% - 8.1%; 32.0% - 36.4%, and 64.8% - 55.6%, 19.2% - 26.3% concluding a statistically significant difference in terms of genotype and allele harbouring (p \u0026lt;0.004, p = 0.002 respectively). Similarly,\u0026nbsp; having C allele has been associated with HMB in our study as in case with endometriosis.\u003c/p\u003e\n\u003cp\u003eWith regards to the +405G\u0026gt;C, +936C\u0026gt;T polymorphic region our results suggest no significant effect on the susceptibility to HMB. It is noteworthy that our results are consistent with Perini\u0026rsquo;s study [13] and Zhao and colleagues [15] which consist a larger number (958 cases and 959 controls) of Australian women. Similarly Liu et al. [14] found that the + 936C\u0026gt;T polymorphic region does not have a significant relationship with the risk of developing endometriosis.\u003c/p\u003e\n\u003cp\u003eThe main reason for these inconsistent results may be the differences between ethnic groups. For example, the Ensembl database shows that the frequency of the VEGF -2578 A allele was 27.2% with the CHB (Han Chinese in Beijing), 34.1% with AMR (American), and 45.5% with CEU (Utah Residents with Northern and Western European Ancestry).\u003c/p\u003e\n\u003cp\u003eIn the literature, we found two studies from our country evaluating the effect of VEGF gene +405G\u0026gt;C polymorphism on endometriosis risk with controversial results. Altınkaya et al. [16] evaluated the genotype frequencies of VEGF +405G\u0026gt;C polymorphic regions on 98 endometriosis patients and 94 controls. They detected GC genotype in 58.2% of patients and 10.6% of controls and G allele in 45.4% of patients and 5.3% of controls. They suggested that GC genotype and G allele may be associated with the advanced grade endometriosis risk in the Turkish population. In another study from Turkey, Attar et al. [17.] also proposed that CC genotype of +405G\u0026gt;C polymorphisms may be related to endometriosis whereas G allele has a protective role against endometriosis. The small sample sizes impede with reflecting data of the whole Turkish population and may partially explain the conflicting results.\u003c/p\u003e\n\u003cp\u003eThe meta-analyses also yielded conflicting results. In a meta-analysis evaluating 14 eligible studies on a total of 3313 endometriosis patients and 3393 controls, VEGF gene -1154G\u0026gt;A polymorphic region GA genotype and A allele and -2578C\u0026gt;A polymorphic region CC genotype and C allele were found to reduce endometriosis risk whereas +936C\u0026gt;T poymorphic region CT genotype and T allele increased the risk similar to our results on HMB [18]. No effect of the +405G\u0026gt;C polymorphism was reported in line with our findings. On the contrary, Jiang et al. [19] stated that VEGF + 405G\u0026gt;C and + 936C\u0026gt;T SNPs may be associated with the risk of endometriosis in their meta-analysis, in which they investigated 9 studies including 1610 endometriosis patients and 1643 control cases.\u003c/p\u003e\n\u003cp\u003eThe most important limitation of the current study is the small sample size which can also be held responsible for the controversial results in other studies in the literature. Besides, the facts that these studies have been performed on distinct ethnic groups and different diseases and having identified various haplotypes may have led to the conflicting results. These diverse results suggest that disease tendency may stem from not solely a single polymorphism but a combined effect of polymorphisms and that haplotype effect may play a more significant role in disease tendency than single polymorphisms.\u003c/p\u003e\n\u003cp\u003eIn our study in the examination of the -\u003cstrong\u003e2578C\u0026gt;A, -1154G\u0026gt;A,\u003c/strong\u003e\u003cstrong\u003e+405G\u0026gt;C\u003c/strong\u003e and 534C\u0026gt; T polymorphic regions of the VEGF gene we have identified 4 haplotypes: CACC (38.1%), AGGC (31.2%), CAGC (17.3%), AAGT (12.3%). AGGC haplotype was less prevalent in HMB patients (23.8% vs 38.5%) while CAGC haplotype was more frequent in the HMB group (25.4% vs 9.2%). Perini et al. [13] emphasized that CCGG haplotype derived from four polymorphisms (-2578C\u0026gt;A / -460T\u0026gt;C / -1154G\u0026gt;A / + 405G\u0026gt;C) has a protective effect against the development of endometriosis (3% in cases, 6.7% in the control group). Liu et al. [14] stated that the VEGF gene -460C\u0026gt;T -1154G\u0026gt;A, -2578C\u0026gt;A regions included CAA, TAA and TAC haplotypes can significantly reduce the risk of developing endometriosis, and the CAC haplotype can significantly increase the risk of developing endometriosis. The polymorphic regions included in the studies produced different linkage disequilibrium results and different haplotypes were obtained in each study making it difficult to compare study results.\u003c/p\u003e\n\u003cp\u003eOur study on VEGF gene polymorphisms in Turkish women with HMB suggests increased risk for C allele, CC, and AC+CC genotypes of \u0026minus;2578A\u0026gt;C polymorphic region, A allele, AA genotype, and CAGC haplotype of the \u0026minus;1154G\u0026gt;A polymorphic region whereas protective role of the AGGC haplotype. However, further studies with a larger sample size are required to figure out a more certain association.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eİ Kaygusuz: Project development, Data collection, \u0026nbsp;Data analysis, Manuscript writing, editing\u003c/p\u003e\n\u003cp\u003eN Semerci G\u0026uuml;nd\u0026uuml;z: Project development, reduction, editing\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eI. Ethical approval:\u003c/strong\u003e The study was approved by the Ankara Yıldırım Betazıt University Human Ethical Committee\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eII. Funding details (In case of Funding):\u003c/strong\u003e No funding\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIII.\u0026nbsp;\u0026nbsp;\u0026nbsp; Conflict of interest:\u003c/strong\u003e The authors declare that they have no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIV. Informed Consent:\u003c/strong\u003e Signed informed consent was obtained from all patients before starting study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMints M, Blomgren B, Falconer C, Fianu-Jonasson A, Palmblad J (2005) Microvascular density, vascular endothelial growth factor A, and its receptors in endometrial blood vessels in patients with menorrhagia. Fertil Steril 84(3):692-700. https://doi.org/10.1016/j.fertnstert.2005.03.065\u003c/li\u003e\n\u003cli\u003eElkilani OA, Soliman MA (2017) Angiogenesis mediators in women with idiopathic heavy menstrual bleeding. Int J Gynaecol Obstet 136(3):280-284. https://doi.org/10.1002/ijgo.12068\u003c/li\u003e\n\u003cli\u003eBiswas Shivhare S, Bulmer JN, Innes BA, Hapangama DK, Lash GE (2018) Endometrial vascular development in heavy menstrual bleeding: altered spatio-temporal expression of endothelial cell markers and extracellular matrix components. Hum Reprod 33(3):399-410. https://doi.org/10.1093/humrep/dex378\u003c/li\u003e\n\u003cli\u003eKuzmina N, Palmblad J, Mints M (2011) Predictive factors for the occurrence of idiopathic menorrhagia: evidence for a hereditary trait. Mol Med Rep 4(5):935-939. https://doi.org/10.3892/mmr.2011.514\u003c/li\u003e\n\u003cli\u003eAndersson E, Zetterberg E, Vedin I, Hultenby K, Palmblad J, Mints M (2015) Low pericyte coverage of endometrial microvessels in heavy menstrual bleeding correlates with the microvessel expression of VEGF-A. Int J Mol Med 35(2):433-438. https://doi.org/10.3892/ijmm.2014.2035\u003c/li\u003e\n\u003cli\u003eMansour D, Hofmann A, Gemzell-Danielsson K (2021) A Review of Clinical Guidelines on the Management of Iron Deficiency and Iron-Deficiency Anemia in Women with Heavy Menstrual Bleeding. Adv Ther 38(1):201-225. https://doi.org/10.1007/s12325-020-01564-y\u003c/li\u003e\n\u003cli\u003eFraser IS, Critchley HO, Munro MG, Broder M, Writing Group for this Menstrual Agreement Process (2007) A process designed to lead to international agreement on terminologies and definitions used to describe abnormalities of menstrual bleeding. Fertil Steril 87(3):466-476. https://doi.org/10.1016/j.fertnstert.2007.01.023\u003c/li\u003e\n\u003cli\u003eMints M, Hultenby K, Zetterberg E, Blomgren B, Falconer C, Rogers R, Palmblad J (2007) Wall discontinuities and increased expression of vascular endothelial growth factor-A and vascular endothelial growth factor receptors 1 and 2 in endometrial blood vessels of women with menorrhagia. Fertil Steril 88(3):691-697. https://doi.org/10.1016/j.fertnstert.2006.11.190\u003c/li\u003e\n\u003cli\u003eMints M, Blomgren B, Palmblad J (2010) Expression of angiopoietins 1, 2 and their common receptor tie-2 in relation to the size of endothelial lining gaps and expression of VEGF and VEGF receptors in idiopathic menorrhagia. Fertil Steril 94(2):701-707. https://doi.org/10.1016/j.fertnstert.2009.03.042\u003c/li\u003e\n\u003cli\u003eMunro MG, Critchley HO, Broder MS, Fraser IS, FIGO Working Group on Menstrual Disorders (2011) FIGO classification system (PALM-COEIN) for causes of abnormal uterine bleeding in nongravid women of reproductive age. Int J Gynaecol Obstet 113(1):3-13. https://doi.org/ 1016/j.ijgo.2010.11.011\u003c/li\u003e\n\u003cli\u003eHigham JM, O\u0026rsquo;Brien PM, Shaw RW (1990) Assessment of menstrual blood loss using a pictorial chart. Br J Obstet Gynaecol 97:734-739. https://doi.org/10.1111/j.1471-0528.1990.tb16249.x\u003c/li\u003e\n\u003cli\u003eZakherah MS, Sayed GH, El-Nashar SA, Shaaban MM (2011) Pictorial blood loss assessment chart in the evaluation of heavy menstrual bleeding: diagnostic accuracy compared to alkaline hematin. Gynecol Obstet Invest 71: 281-284. https://doi.org/10.1159/000320336\u003c/li\u003e\n\u003cli\u003ePerini JA, Cardoso JV, Berardo PT, Vianna-Jorge R, Nasciutti LE, Bellodi-Privato M, Machado DE, Abr\u0026atilde;o MS (2014) Role of vascular endothelial growth factor polymorphisms (-2578C\u0026gt;A, -460 T\u0026gt;C, -1154G\u0026gt;A, +405G\u0026gt;C and +936C\u0026gt;T) in endometriosis: a case-control study with Brazilians. BMC Womens Health 14:117. https://doi.org/ 1186/1472-6874-14-117\u003c/li\u003e\n\u003cli\u003eLiu Q, Li Y, Zhao J, Sun DL, Duan YN, Wang N, Zhou RM, Kang S (2009) Association of polymorphisms -1154G/A and -2578C/A in the vascular endothelial growth factor gene with decreased risk of endometriosis in Chinese women. Hum Reprod 24(10):2660-2666. https://doi.org/10.1093/humrep/dep208\u003c/li\u003e\n\u003cli\u003eZhao ZZ, Nyholt DR, Thomas S, Treloar SA, Montgomery GW (2008) Polymorphisms in the vascular endothelial growth factor gene and the risk of familial endometriosis. Mol Hum Reprod 14(9):531-538. https://doi.org/10.1093/molehr/gan043\u003c/li\u003e\n\u003cli\u003eAltinkaya SO, Ugur M, Ceylaner G, Ozat M, Gungor T, Ceylaner S (2011) Vascular endothelial growth factor +405 C/G polymorphism is highly associated with an increased risk of endometriosis in Turkish women. Arch Gynecol Obstet 283(2):267-72. https://doi.org/10.1007/s00404-009-1344-1\u003c/li\u003e\n\u003cli\u003eAttar R, Agachan B, Kuran SB, Toptas B, Eraltan IY, Attar E, Isbir T (2010) Genetic variants of vascular endothelial growth factor and risk for the development of endometriosis. In Vivo 24(3):297-301.\u003c/li\u003e\n\u003cli\u003eLi YZ, Wang LJ, Li X, Li SL, Wang JL, Wu ZH, Gong L, Zhang XD (2013) Vascular endothelial growth factor gene polymorphisms contribute to the risk of endometriosis: an updated systematic review and meta-analysis of 14 case-control studies. Genet Mol Res 12(2):1035-44. https://doi.org/10.4238/2013.April.2.20\u003c/li\u003e\n\u003cli\u003eJiang Y, Tang JY, Wu Y, Zhao TF (2012) Vascular endothelial growth factor gene polymorphisms and the risk of endometriosis: a systematic review. Zhonghua Fu Chan Ke Za Zhi 47(3):179-84.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Primers, amplicon size and usage purposes\u003c/p\u003e\n\u003ctable border=\"1\" width=\"0\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e\u003cstrong\u003ePrimer\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"69\"\u003e\n\u003cp\u003e\u003cstrong\u003eOrientation\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003e\u003cstrong\u003eSequencing\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"69\"\u003e\n\u003cp\u003e\u003cstrong\u003eGenotyping\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"59\"\u003e\n\u003cp\u003e\u003cstrong\u003eAmplicon size (bp)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"220\"\u003e\n\u003cp\u003e\u003cstrong\u003eSequence (5'-3')\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eVEGFA_SNP2_F\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"69\"\u003e\n\u003cp\u003eForward\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"68\"\u003e\n\u003cp\u003eExon 1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"69\"\u003e\n\u003cp\u003eSNP 2\u003c/p\u003e\n\u003cp\u003eSNP 3\u003c/p\u003e\n\u003cp\u003eSNP 5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"59\"\u003e\n\u003cp\u003e1500\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"220\"\u003e\n\u003cp\u003eCGGATGGGTAATTTTCAGGCTGTG\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eVEGFA_1R\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"69\"\u003e\n\u003cp\u003eRevers\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"220\"\u003e\n\u003cp\u003eCCTCCCCCTGCACCTAAGACGAC\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eVEGFA_2F\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"69\"\u003e\n\u003cp\u003eForward\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"68\"\u003e\n\u003cp\u003eExon 2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"69\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"59\"\u003e\n\u003cp\u003e468\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"220\"\u003e\n\u003cp\u003eGGGAAGTGTGGGGAAGGTACAGG\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eVEGFA_2R\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"69\"\u003e\n\u003cp\u003eRevers\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"220\"\u003e\n\u003cp\u003eCTTCCCCTTCCTCCCCACAGTTC\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eVEGFA_3F\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"69\"\u003e\n\u003cp\u003eForward\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"68\"\u003e\n\u003cp\u003eExon 3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"69\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"59\"\u003e\n\u003cp\u003e433\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"220\"\u003e\n\u003cp\u003eGAAGCTCCAAAGAGTGGCATTACAG\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eVEGFA_3R\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"69\"\u003e\n\u003cp\u003eRevers\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"220\"\u003e\n\u003cp\u003eACCATACCTCCCCTGTGCAACTC\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eVEGFA_4-5F\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"69\"\u003e\n\u003cp\u003eForward\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"68\"\u003e\n\u003cp\u003eExon 4\u003c/p\u003e\n\u003cp\u003eExon 5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"69\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"59\"\u003e\n\u003cp\u003e975\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"220\"\u003e\n\u003cp\u003eAGGAGTCAGGGTGAAGCCTAGAGAG\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eVEGFA_4-5R\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"69\"\u003e\n\u003cp\u003eRevers\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"220\"\u003e\n\u003cp\u003eCACTAGCCCTAGAGCCATCATCCTG\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eVEGFA_6F\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"69\"\u003e\n\u003cp\u003eForward\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"68\"\u003e\n\u003cp\u003eExon 6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"69\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"59\"\u003e\n\u003cp\u003e398\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"220\"\u003e\n\u003cp\u003eAGAGACCACCTGCCTCCTGACAC\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eVEGFA_6R\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"69\"\u003e\n\u003cp\u003eRevers\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"220\"\u003e\n\u003cp\u003eTCTACCCGTTGGTGCCAATTAGTG\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eVEGFA_7F\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"69\"\u003e\n\u003cp\u003eForward\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"68\"\u003e\n\u003cp\u003eExon 7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"69\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"59\"\u003e\n\u003cp\u003e429\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"220\"\u003e\n\u003cp\u003eCTGTAGCGCTCGGATCCTTCCAG\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eVEGFA_7R\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"69\"\u003e\n\u003cp\u003eRevers\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"220\"\u003e\n\u003cp\u003eACCAGGCAGGCAGCTAGAAACTGAG\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eVEGFA_8F\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"69\"\u003e\n\u003cp\u003eForward\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"68\"\u003e\n\u003cp\u003eExon 8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"69\"\u003e\n\u003cp\u003eSNP 4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"59\"\u003e\n\u003cp\u003e463\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"220\"\u003e\n\u003cp\u003eCCTTCCTGTCCTCTCTGCTCTTATGG\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eVEGFA_8R\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"69\"\u003e\n\u003cp\u003eRevers\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"220\"\u003e\n\u003cp\u003eATCTTCCGGGCTCGGTGATTTAG\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eVEGFA_SNP1_F\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"69\"\u003e\n\u003cp\u003eForward\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"68\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"69\"\u003e\n\u003cp\u003eSNP 1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"59\"\u003e\n\u003cp\u003e250\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"220\"\u003e\n\u003cp\u003eCTGGAGCGTTTTGGTTAAATTGAGG\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eVEGFA_SNP1_R\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"69\"\u003e\n\u003cp\u003eRevers\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"220\"\u003e\n\u003cp\u003eCCCCATCCCATTCTTGCATATAGG\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 2: Baseline characteristics of study subjects\u003c/p\u003e\n\u003ctable border=\"1\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"206\"\u003e\n\u003cp\u003eVariables\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003eHMB group (n=65)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003eControl group (n=65)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003et/z c\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003ep\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"206\"\u003e\n\u003cp\u003eAge (year)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e30.58 \u0026plusmn; 7.06\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e29.08 \u0026plusmn; 6.56\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003et=1.261\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e0.210\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"206\"\u003e\n\u003cp\u003e\u003cem\u003eBody Mass Index\u003c/em\u003e (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e22.35 \u0026plusmn; 2.57\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e22.77 \u0026plusmn; 2.65\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003et=0.923\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e0.358\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"206\"\u003e\n\u003cp\u003eMarital status\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"206\"\u003e\n\u003cp\u003eMarried\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e43 (% 66.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e40 (% 61.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"89\"\u003e\n\u003cp\u003ec\u003csup\u003e2 \u003c/sup\u003e=0.300\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"89\"\u003e\n\u003cp\u003e0.584\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"206\"\u003e\n\u003cp\u003eUnmarried\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e22 (% 33.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e25 (% 38.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"206\"\u003e\n\u003cp\u003eGravidity\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e1 (2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e1 (1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003eZ=-1.361\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e0.180\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"206\"\u003e\n\u003cp\u003eParity\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e1 (2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e1 (2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003eZ=-1.185\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e0.290\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"206\"\u003e\n\u003cp\u003eAge at menarche (year)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e13 (2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e13 (1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003eZ=-1.311\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e0.190\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"206\"\u003e\n\u003cp\u003eMenses duration (days)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e7 (2.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e5 (2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003eZ=5.339\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"206\"\u003e\n\u003cp\u003eLength of Menstrual cycle (day)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e28 (3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e28 (2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003eZ=0.320\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e0.749\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"206\"\u003e\n\u003cp\u003ePBAC score\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e258 (246)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e50 (44)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003eZ=9.937\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: PBAC, Pictorial Blood Loss Assessment Chart\u003c/p\u003e\n\u003cp\u003eData are mean \u0026plusmn; SD, median (IQR) or numbers (n) and percentages (%)\u003c/p\u003e\n\u003cp\u003et= Student\u0026rsquo;s t test, Z=Mann\u0026ndash;Whitney U-test, c\u003csup\u003e2 \u003c/sup\u003e= Chi-square\u003c/p\u003e\n\u003cp\u003e* p values \u0026le; 0.05 were considered statistically significant\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. \u003c/strong\u003eLogistic regression analysis of associations between VEGF polymorphisms and risk of HMB\u003c/p\u003e\n\u003ctable border=\"1\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003eAMK-E grup,\u003c/p\u003e\n\u003cp\u003en = 65 (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003eKontrol grup,\u003c/p\u003e\n\u003cp\u003en = 65 (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003eOR (95% CI)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003ep\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"190\"\u003e\n\u003cp\u003ers699947 (\u0026minus;2578A\u0026gt;C)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eAA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e9 (13.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e18 (27.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003eReferans\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eAC\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e31 (47.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e31 (47.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003e1.97 (0.77-5.29)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e0.15\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eCC\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e25 (38.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e16 (24.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003e3.05 (1.11-8.84)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.03*\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eAC+CC\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e56 (86.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e47 (72,3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003e2.35 (0.97-6.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.05*\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eA Alel\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e49 (37.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e67 (51.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003eReferans\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eC Alel\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e81 (62.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e63 (48.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003e1.75 (1.07-2.88)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.02*\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"190\"\u003e\n\u003cp\u003ers1570360\u0026nbsp; (\u0026minus;1154G\u0026gt;A)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eGG\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e3 (4.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e10 (15.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003eReferans\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eGA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e25 (38.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e30 (46.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003e2.13 (0.53-11.20)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e0.26\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eAA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e37 (56.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e25 (38.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003e3.49 (0.89-18.10)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.06*\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eGA+AA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e62 (95.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e57(87.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003e2.07 (0.56-10.32)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e0.26\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eG Alel\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e31 (23.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e50 (38.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003eReferans\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eA Alel\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e99 (76.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e80 (61.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003e1.74 (1.01-3.01)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.04*\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"190\"\u003e\n\u003cp\u003ers2010963 (+405G\u0026gt;C)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eCC\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e9 (13.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e9 (13.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003eReferans\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eCG\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e30 (46.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e33 (50.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003e0.91 (0.31-2.66)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e0.85\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eGG\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e26 (40.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e23 (35.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003e1.12 (0.37-3.41)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e0.82\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eCG+GG\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e56 (86.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e56 (86.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003e0.99 (0.33-2.78)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eC Alel\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e48 (36.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e51 (39.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003eReferans\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eG Alel\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e82 (63.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e79 (60.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003e1.10 (0.66-1.82)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e0.70\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"190\"\u003e\n\u003cp\u003ers3025039 (+936C\u0026gt;T)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eCC\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e49 (75.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e43 (66.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003eReferans\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eCT\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e15 (23.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e20 (30.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003e0.66 (0.29-1.45)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e0.29\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eTT\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e1 (1.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e2 (3.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003e0.46 (0.01-5.98)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e0.49\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eCT+TT\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e16 (24.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e22 (33.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003e0.64 (0.29-1.37)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e0.24\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eC Alel\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e113 (86.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e106 (81.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003eReferans\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eT Alel\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e17 (13.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e24 (18.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003e0.66 (0.33-1.30)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e0.23\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"190\"\u003e\n\u003cp\u003ers25648 (c.534C\u0026gt;T)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eCC\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e49 (75.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e51 (78.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003eReferans\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eCT\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e16 (24.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e12 (18.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003e0.72 (0.31-1.68)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e0.18\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eTT\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e2 (3.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eCT+TT\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e16 (24.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e14 (21.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003e0.84 (0.37-1.90)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e0.68\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eC Alel\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e114 (87.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e114 (87.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003eReferans\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eT Alel\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e16 (12.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e16 (12.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003e1 (0.47-2.12)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Abbreviations: OR, odds ratio; CI, confidence interval.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; * p values \u0026le; 0.05 were considered statistically significant\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 4. Haplotype distributions of VEGF gene polymorphisms rs699947, rs1570360, rs2010963, and rs25648\u003c/p\u003e\n\u003ctable border=\"1\" width=\"0\"\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 48.6562px;\"\u003e\n\u003ctd style=\"height: 48.6562px;\" width=\"78\"\u003e\n\u003cp\u003eHaplotype\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 48.6562px;\" width=\"76\"\u003e\n\u003cp\u003eFrequency (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 48.6562px;\" width=\"100\"\u003e\n\u003cp\u003eHMB group, n=65 (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 48.6562px;\" width=\"100\"\u003e\n\u003cp\u003eControl group, n=65 (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 48.6562px;\" width=\"58\"\u003e\n\u003cp\u003eP\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 48.6562px;\" width=\"122\"\u003e\n\u003cp\u003eOR (95% CI)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"78\"\u003e\n\u003cp\u003eCAAC\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e38.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"100\"\u003e\n\u003cp\u003e48 (36.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"100\"\u003e\n\u003cp\u003e51 (39.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"58\"\u003e\n\u003cp\u003e0,737\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"122\"\u003e0.918 (0.555-1.517)\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"78\"\u003e\n\u003cp\u003eAGGC\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e31.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"100\"\u003e\n\u003cp\u003e31 (23.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"100\"\u003e\n\u003cp\u003e50 (38.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"58\"\u003e\n\u003cp\u003e\u003cstrong\u003e0,012*\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"122\"\u003e\n\u003cp\u003e0.505 (0.295-0.864)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"78\"\u003e\n\u003cp\u003eCAGC\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e17.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"100\"\u003e\n\u003cp\u003e33 (25.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"100\"\u003e\n\u003cp\u003e12 (9.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"58\"\u003e\n\u003cp\u003e\u003cstrong\u003e0,0005*\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"122\"\u003e\n\u003cp\u003e3.387 (1.659-6.917)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"78\"\u003e\n\u003cp\u003eAAGT\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e12.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"100\"\u003e\n\u003cp\u003e16 (12.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"100\"\u003e\n\u003cp\u003e16 (12.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"58\"\u003e\n\u003cp\u003e0.981\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"122\"\u003e\n\u003cp\u003e1.009 (0.481-2.116)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: OR, odds ratio; CI, confidence interval.\u003c/p\u003e\n\u003cp\u003e* p values \u0026le; 0.05 were considered statistically significant\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"archives-of-gynecology-and-obstetrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"arch","sideBox":"Learn more about [Archives of Gynecology and Obstetrics](https://www.springer.com/journal/404)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/arch/default.aspx","title":"Archives of Gynecology and Obstetrics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Excessive menstrual bleeding, polymorphism, vascular endothelial growth factor, VEGF gene","lastPublishedDoi":"10.21203/rs.3.rs-459616/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-459616/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose:\u003c/strong\u003e To investigate whether there is a relationship between the VEGF gene polymorphisms and idiopathic heavy menstrual bleeding (HMB-E).\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e 65 patients diagnosed with HMB-E according to the FIGO classification system and 65 female healty volunteers were included in the study. Detection of rs699947 (-2578C\u0026gt;A), rs1570360 (-1154G\u0026gt;A), rs2010963 (+405G\u0026gt;C), rs3025039 (+936C\u0026gt;T), rs25648 (c534C\u0026gt;T) \u0026nbsp;polymorphic regions of the VEGF gene was performed by Next Generation DNA Sequencing method.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e the -2578C\u0026gt;A polymorphic region CC, CA+AA genotypes, and C allele, as well as the -1154G\u0026gt;A polymorphic region AA genotype, and A allele were associated with increased risk of HMB-E (all p\u0026lt;0.05). However, no statistically significant difference was found between the the patient group and the control group in terms of genotype and allele distributions in the 405G\u0026gt;C, +936C\u0026gt;T, c534C\u0026gt;T polymorphic regions (all p\u0026gt;0.05). While the -2578/-1154/+405/c534 AGGC haplotype decreased the risk of HMB-E, CAGC haplotype was found to increase the risk of HMB-E.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e: VEGF -2578C\u0026gt;A and -1154G\u0026gt;A polymorphisms were significantly associated with the risk of HMB-E in the Turkish population.\u0026nbsp;\u003c/p\u003e","manuscriptTitle":"Investigation of Vascular Endothelial Growth Factor (VEGF) Polymorphism in Patients With Idiopathic Heavy Menstrual Bleeding","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-05-05 22:12:18","doi":"10.21203/rs.3.rs-459616/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2021-05-04T01:44:00+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2021-05-01T00:00:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Archives of Gynecology and Obstetrics","date":"2021-04-29T00:00:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2021-04-24T00:00:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"Archives of Gynecology and Obstetrics","date":"2021-04-23T11:44:14+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"archives-of-gynecology-and-obstetrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"arch","sideBox":"Learn more about [Archives of Gynecology and Obstetrics](https://www.springer.com/journal/404)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/arch/default.aspx","title":"Archives of Gynecology and Obstetrics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"7be67fb4-b809-49b6-b550-29aef491dabb","owner":[],"postedDate":"May 5th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":4105050,"name":"Obstetrics \u0026 Gynecology"}],"tags":[],"updatedAt":"2022-01-21T16:10:03+00:00","versionOfRecord":{"articleIdentity":"rs-459616","link":"https://doi.org/10.1007/s00404-021-06225-1","journal":{"identity":"archives-of-gynecology-and-obstetrics","isVorOnly":false,"title":"Archives of Gynecology and Obstetrics"},"publishedOn":"2021-09-08 16:10:03","publishedOnDateReadable":"September 8th, 2021"},"versionCreatedAt":"2021-05-05 22:12:18","video":"","vorDoi":"10.1007/s00404-021-06225-1","vorDoiUrl":"https://doi.org/10.1007/s00404-021-06225-1","workflowStages":[]},"version":"v1","identity":"rs-459616","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-459616","identity":"rs-459616","version":["v1"]},"buildId":"WvIrzKhiLBfengagbw6Ux","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}