The Association of Exaggerated Folliculer Responses to Clomiphene Citrate With Estrogen and Follicle-stimulating Hormone Receptor Polymorphisms in Women With Polycystic Ovary Syndrome

The Association of Exaggerated Folliculer Responses to Clomiphene Citrate With Estrogen and Follicle-stimulating Hormone Receptor Polymorphisms in Women With Polycystic Ovary Syndrome | 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 The Association of Exaggerated Folliculer Responses to Clomiphene Citrate With Estrogen and Follicle-stimulating Hormone Receptor Polymorphisms in Women With Polycystic Ovary Syndrome Görkem Aktaş, Mete Bertizlioğlu, Setenay Arzu Yılmaz, Ayşe Gül Kebapcılar, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7160268/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective: The aim of this study was to evaluate the associations between an exaggerated follicular response to clomiphene citrate (CC) and estrogen and follicle-stimulating hormone (FSH) receptor polymorphisms. Materials and Methods: A total of 60 patients who were diagnosed with polycystic ovary syndrome (PCOS) and whose first treatment cycle started with 50 mg clomiphene citrate were investigated. Patients were evaluated in three groups: those with >17 mm follicle development (Group 1, n=20), normal responders with one or two >17 mm follicles (Group 2, n=20), and overresponders with three or more >17 mm follicles (Group 3, n=20). The FSHR SNPs rs6165 and rs6166, the ER1 SNPs rs2234693 and rs9340799, and the ER2 SNPs rs1256049 and rs4986938 were genotyped via TaqMan assays. Results: When the three different CC response groups were evaluated, no significant differences in genotype, allotype, or haplotype distributions were observed. Conclusion: A clearer understanding of genetic factors that can predict the response to CC could help prevent ovarian hyperstimulation and multiple pregnancies, thereby safeguarding the health of infertile women. The results of this study showed that FSHR, ER1, and ER2 polymorphisms cannot be used to predict the follicular response to CC treatment. polycystic ovary syndrome clomiphene citrate follicle-stimulating hormone receptor ovarian reserve Figures Figure 1 INTRODUCTION Polycystic ovary syndrome (PCOS) is a clinical condition characterized by oligoanovulation, hyperandrogenism, and polycystic ovarian morphology on ultrasonography, with a prevalence of approximately 10–15% in the general population. Oligo-anovulation leads to oligomenorrhea and infertility. In patients with these conditions, when pregnancy cannot be achieved with lifestyle changes such as diet and exercise, the first-line treatment is ovulation induction via oral agents, such as clomiphene citrate (CC) and letrozole. The CC is a selective estrogen receptor modulator. It has both estrogenic and antiestrogenic properties. While resistance to CC and treatment failure with CC, i.e., the failure to achieve pregnancy despite achieving ovulation, have been extensively studied, the exaggerated response to CC has not been thoroughly examined, and the underlying reasons have not been clearly elucidated. The rate of multiple pregnancies due to clomiphene treatment is 8%. In contrast, ovarian hyperstimulation syndrome (OHSS) is rare, with a rate of approximately 1% ( 1 ). CC treatment in anovulatory patients is aimed at the development of a single dominant follicle. Therefore, treatment usually begins with the lowest dosage form available, which is a 50 mg tablet taken once a day. During CC treatment, an exaggerated follicular response, characterized by the development of three or more follicles, is observed in approximately 14% of patients. This rate is higher in ovulatory patients than in anovulatory patients (17% vs. 6%) ( 2 ). This creates a risk of triplet or quadruplet pregnancies, which are now considered treatment failures, and OHSS. Therefore, identifying which patients will have an exaggerated response to this treatment is crucial. Polymorphism can be defined as the presence of two or more distinct phenotypes within a population. Polymorphisms are distinguished from mutations by their presence as variant alleles at a relatively high frequency within a population. They are mostly observed in the form of single nucleotide polymorphisms (SNPs). SNPs can be silent, but they can also influence susceptibility to diseases or the response to medications. When identified as a reason for differences in drug effects, personalized, patient-friendly protocols such as individual treatment options and dose selection on the basis of the patient’s genotype can be established. For example, because the gonadotropin doses required for controlled ovarian hyperstimulation may vary in the presence of different follicle-stimulating hormone (FSH) receptor isoforms in patients undergoing in vitro fertilization (IVF), the evaluation of FSH receptor (FSHR) polymorphisms has become part of daily practice ( 3 ). The CC binds to estrogen receptors (ERs) because of its structural similarity to estrogen. Unlike estrogen, CC binds to the nuclear ER over a longer period and reduces the concentration of ER. One of the mechanisms of action of a drug is dependent on its activity at the hypothalamic level. A reduction in the hypothalamic ER concentration affects the accurate perception of circulating estrogen levels by the hypothalamus. This diminished estrogen feedback signal increases the amplitude of the gonadotropin hormone-releasing hormone pulse during treatment in patients with anovulatory PCOS, leading to increased FSH levels. Successful treatment, the development of one or two mature follicles, is defined by an increase in estrogen from the growing follicles, which triggers the luteinizing hormone (LH) surge and subsequently leads to ovulation ( 3 – 6 ). Polymorphisms in the ER gene can alter the relationship between CC and the receptor by affecting the sensitivity of the receptor to CC. The relationship between FSHR polymorphisms and the development of multiple follicles and the relationship between the exogenous FSH response and under- or overstimulation are known and clinically used to predict the response to exogenous FSH in daily clinical practice. Although the relationship between the response to exogenous FSH and FSHR polymorphisms has been frequently investigated, very few studies have investigated the relationship between CC and FSHR SNPs ( 3 – 7 ). This study focused on ovulation induction treatment using CC, a selective estrogen receptor modulator/partial estrogen antagonist for achieving monofollicular development and ovulation in anovulatory patients diagnosed with PCOS. The aim of this study was to investigate the presence of ER and FSHR polymorphisms in patients exhibiting an exaggerated follicular response. MATERIALS AND METHODS Patients FSHR and ER SNPs were investigated in a total of 60 patients diagnosed with PCOS who presented to the infertility outpatient clinic of the Selçuk University Faculty of Medicine between 2019 and 2020 and started their first treatment cycles with CC. The study was approved by the Ethics Committee of Selçuk University and was conducted in accordance with the Declaration of Helsinki. Informed consent was obtained from all patients who participated in the study. PCOS was diagnosed when two of the three Rotterdam criteria were satisfied: oligo-ovulation or anovulation, polycystic ovary appearance on ultrasound, and clinical or biochemical hyperandrogenism ( 7 ). Women with signs of virilization; those who were diagnosed with nonclassical congenital adrenal hyperplasia, androgen-secreting tumors, Cushing’s syndrome, hyperprolactinemia or thyroid dysfunction; those aged 35 years; those with a body mass index > 40 kg/m 2 ; and those with chronic illnesses were excluded from the study. Oral CC treatment was initiated on the 5th day of menstruation at once-daily doses of 50 mg and continued for 5 days. TVUS-guided folliculometry was performed from day 12 of the cycle. Patients were evaluated in three groups: patients with no > 18 mm follicle (Group 1, n = 20), normal responders with one or two > 18 mm follicles (Group 2, n = 20), and nonresponders with three or more > 18 mm follicles (Group 3, n = 20). Single-Nucleotide Polymorphism Genotyping Three milliliters of venous blood samples obtained from the patients were stored in EDTA tubes at − 20°C. The SNPs were genotyped via TaqMan assays (Applied Biosystems, Foster City, CA, USA) (Table 1 ). The 12-µL reaction mixture contained 25 ng of genomic DNA, 0.25x stock genotyping assay, and 1x TaqMan genotyping PCR master mix. Amplification and hybridization were performed via the Applied Biosystems StepOnePlus Real-Time PCR System according to the manufacturer’s recommendation. Table 1 Annotations of the analyzed single nucleotide polymorphisms. Gene rs ID HGVS Clinical definition Assay ID* FSHR rs6165 c.919A◊G rs6166 C___2676873_30 rs6166 c.2039A◊G Asn680Ser C___2676874_10 ER1 rs9340799 c.351A◊G XbaI C___3163591_10 rs2234693 c.397T◊C PvuII C___3163590_10 ER2 rs1256049 c.1082G◊A RsaI C___7573265_1 rs4986938 c.1730A◊G AluI C__11462726_10 *TaqMan® SNP Genotyping assay, Applied Biosystems Statistical analysis The SPSS (IBM SPSS Statistics for Windows released in 2017, Version 25.0, IBM Corp., Armonk, NY) statistical package program was used for data analysis. Descriptive statistics are presented as the means, standard deviations, numbers, and percentages for categorical and continuous variables where appropriate. In addition, homogeneity of variances, one of the prerequisites of parametric tests, was checked via Levene’s test. The normality assumption was examined via the Shapiro–Wilk test. Differences between two groups were evaluated via Student’s t test for normally distributed variables and the Mann–Whitney U test for nonnormally distributed variables. One-way analysis of variance and Tukey’s HSD test were used for comparisons of normally distributed variables between three or more groups, whereas the Kruskal–Wallis and Bonferroni–Dunn tests were used for nonnormally distributed variables. Differences in categorical variables were analysed via the chi-square test. Cramér’s V and odds ratio are the effect size values used for the chi-square statistic. The odds ratio value was used when categorical variables were evaluated in two groups. Because categorical variables were evaluated among the three groups in this study, Cramér’s V effect size was used. p < 0.05 was considered statistically RESULTS The genotype distribution of the FSHR rs6166 SNP was analysed in 60 patients included in the study. The SS genotype was found in 26.6%, the NS genotype in 46.6%, and the NN genotype in 26.6% of the patients. Analysis of the genotype distribution for the FSHR rs6165 SNP revealed that the AA genotype was found in 25%, the TA genotype in 50%, and the TT genotype in 25% of the patients. For the ER1 rs2234693 polymorphism, 16.6% of the patients had the CC genotype, 53.3% had the CT genotype, and 30% had the TT genotype. For the rs9340799 polymorphism, 33.3% of the patients had the AA genotype, 50% had the GA genotype, and 16.6% had the GG genotype. The genotype distributions for the ER2 rs4986938 SNP were 18.3% and 81.6% for the GA genotype and GG genotype, respectively. For the rs1256049 SNP, the AA genotype was found in 8.3%, the GA genotype in 53.3%, and the GG genotype in 38.3% of the patients. The genotype distribution of the patients is shown in Fig. 1 . An evaluation of the effects of different genotypes on clinical characteristics revealed that body mass index (BMI) measurements were significantly different according to the Ala307Thr (rs6165) polymorphism (P = 0.039). BMI measurements were lower in the TA genotype than in the AA and TT genotypes. LH levels also significantly differed according to genotype (p = 0.027). LH levels were lower in the TT genotype than in the AA genotype. For the Ser680Asn (rs6166) polymorphism, BMI measurements significantly differed according to genotype (P = 0.043). BMI measurements were lower in the NS genotype than in the SS and NN genotypes. LH levels also significantly differed according to genotype (p = 0.042). LH levels were lower in the NN genotype than in the SS genotype. For the Ala307Thr (rs6165) and Ser680Asn (rs6166) polymorphisms, age, FSH, and estradiol measurements did not significantly differ according to genotype (p > 0.05) (Table 2 ). Table 2 Clinical parameters of the study patients segregated based on the FSHR polymorphisms. FSHR SNP Ala307Thr (rs6165) Ser680Asn (rs6166) Genotypes AA (n = 15) TA (n = 30) TT (n = 15) P ¥ SS (n = 16) NS (n = 28) NN (n = 16) P ¥ Age 27.53 ± 3.07 26.60 ± 3.75 26.67 ± 2.64 0.659 27.63 ± 2.99 26.64 ± 3.79 26.44 ± 2.71 0.547 BMI 26.07 ± 2.28 A 23.70 ± 3.84 B 26.00 ± 3.53 A 0.039 * 26.06 ± 2.21 A 23.64 ± 3.96 B 25.81 ± 3.49 A 0.043 * LH 10.47 ± 5.19 A 7.50 ± 4.75 AB 6.13 ± 2.42 B 0.027 * 10,06 ± 5,27 A 7.75 ± 4.82 AB 6.00 ± 2.39 B 0.042 * FSH 5.87 ± 1.36 6.13 ± 1.17 5.67 ± 0.90 0.427 5,81 ± 1,33 6.18 ± 1.19 5.69 ± 0.87 0.348 Estradiol 45.53 ± 16.19 42.33 ± 9.99 35.60 ± 14.47 0.103 45,00 ± 15,79 42.18 ± 10,13 36.63 ± 14.56 0.186 *P < 0.05; ¥ : One-way analysis of variance (ANOVA [F]), Descriptive statistics are given as mean ± standard deviation. A, B : Different letters or letter combinations in the same row indicate statistically significant difference (P < 0.05). Abbreviations: FSHR, follicle-stimulating hormone receptor; SNP, single nucleotide polymorphism; BMI, body mass index; LH, luteinizing hormone; FSH, follicle-stimulating hormone For the PvuII (397 T > C) (rs2234693) polymorphism, there was a statistically significant difference in the mean age among the genotypes (p = 0.045). The mean age was lower in the TT genotype than in the CC and CT genotypes. BMI measurements also revealed a significant difference according to genotype (p = 0.017). BMI measurements were lower in the CC and CT genotypes than in the TT genotype. FSH measurements also revealed a statistically significant difference according to genotype (p = 0.001). FSH measurements were lower in the CC genotype than in the CT and TT genotypes. For the XbaI (351 A > G) (rs9340799) polymorphism, there was a statistically significant difference in the mean age among the genotypes (p = 0.049). The mean age was lower for the AA genotype than for the GG genotype. LH levels also significantly differed according to genotype (p = 0.002). LH levels were lower in the AA genotype than in the GA and GG genotypes. In the PvuII (397 T > C) (rs2234693) polymorphism, LH and estradiol levels did not significantly differ according to genotype (p > 0.05). In the XbaI (351 A > G) (rs9340799) polymorphism, BMI, FSH, and estradiol measurements did not significantly differ according to genotype (p > 0.05) (Table 3 ). Table 3 Clinical parameters of the study patients segregated based on the ER1 polymorphisms. ER1 SNP PvuII (397 T > C) (rs2234693) XbaI (351 A > G) (rs9340799) Genotypes CC (n = 10) CT (n = 32) TT (n = 18) P ¥ AA (n = 20) GA (n = 30) GG (n = 10) P ¥ Age 28.00 ± 2.49 A 27.38 ± 3.2 27 A 25.28 ± 3.48 B 0.045 * 25.70 ± 3.77 B 26.97 ± 2.97 AB 28.8 ± 2.49 A 0.049 * BMI 23.10 ± 2.47 B 24.38 ± 3.73 B 26.72 ± 3.16 A 0.017 * 25.55 ± 3.79 24.67 ± 3.51 24.1 ± 3.51 0.535 LH 9.70 ± 5.31 8.31 ± 5.26 6.17 ± 1.89 0.116 6.95 ± 4.01 B 7.03 ± 4.19 A 12.4 ± 4.79 A 0.002 ** FSH 7.10 ± 0.88 A 5.84 ± 1.17 B 5.50 ± 0.86 B 0.001 ** 5.75 ± 0.91 5.93 ± 1.31 6.4 ± 1.08 0.352 Estradiol 44.60 ± 6.77 38.72 ± 15.18 44.56 ± 11.42 0,234 45.65 ± 10.67 38.80 ± 14.83 41 ± 11.43 0,199 *P < 0.05; ¥ : One-way analysis of variance (ANOVA [F]), Descriptive statistics are given as mean ± standard deviation. A, B : Different letters or letter combinations in the same row indicate statistically significant difference (P G) (rs4986938) polymorphism, estradiol levels were significantly different among the genotypes (p = 0.014). Oestradiol levels were lower in the GG genotype than in the GA genotype. For the RsaI (1082 G > A) (rs1256049) polymorphism, estradiol levels were significantly different among the genotypes (p = 0.014). Oestradiol levels were lower in the GG genotype than in the AA and GA genotypes. In the AluI (1730 A > G) (rs4986938) and RsaI (1082 G > A) (rs1256049) polymorphisms, age, BMI, LH, and FSH measurements did not significantly differ among the genotypes (p > 0.05) (Table 4 ). Table 4 Clinical parameters of the study patients segregated based on the ER2 polymorphisms. ER2 SNP AluI (1730 A > G) (rs4986938) RsaI (1082 G > A) (rs1256049) Genotypes AA (n = 0) GA (n = 11) GG (n = 49) P ∑ AA (n = 5) GA (n = 32) GG (n = 23) P ¥ Age - 26.91 ± 2.70 26.84 ± 3.45 0.948 27 ± 4.06 27.03 ± 3.33 26.57 ± 3.26 0.948 BMI - 23.18 ± 3.57 25.24 ± 3.51 0.084 22 ± 2.65 25.16 ± 3.66 25.09 ± 3.50 0.084 LH - 8.09 ± 5.39 7.86 ± 4.50 0.881 5.8 ± 1.64 8.66 ± 5.48 7.3 ± 3.54 0.881 FSH - 6.45 ± 1.64 5.84 ± 1.01 0.110 6.4 ± 0.55 5.66 ± 1.10 6.26 ± 1.25 0.110 Estradiol - 50.18 ± 16.22 A 39.49 ± 11.75 B 0.014 * 51.4 ± 2.97 A 44.06 ± 14.44 A 35.65 ± 10.22 B 0.014 * *P < 0.05; ¥ : ANOVA (F); ∑ : Student’s t -test (t). Descriptive statistics are given as mean ± standard deviation. A, B : Different letters or letter combinations in the same row indicate statistically significant difference (P < 0.05) ; Abbreviations: ESR1, estrogene receptor 1; SNP, single nucleotide polymorphism; BMI, body mass index; LH, luteinizing hormone; FSH, follicle-stimulating hormone A comparison of the clinical data of the study groups revealed a statistically significant difference in BMI between the groups (p = 0.001). BMI measurements were lower in Group 2 and Group 3 than in Group 1. The estradiol level was also significantly different between the groups (p = 0.048). Estradiol measurements were lower in Group 2 than in Group 1 (Table 5 ). Table 5 Clinical parameters of the study groups Group 1 (n = 20) Group 2 (n = 20) Group 3 (n = 20) P ¥ Age 26,60 ± 2,23 26,80 ± 4,30 27,15 ± 3,22 0,872 BMI 27,45 ± 2,63 A 23,80 ± 3,37 B 23,35 ± 3,31 B 0,001 ** LH 9,50 ± 4,88 7,35 ± 4,58 6,85 ± 4,18 0,158 FSH 5,95 ± 1,28 6,15 ± 1,04 5,75 ± 1,16 0,558 Estradiol 47,25 ± 15,63 A 37,70 ± 12,39 B 39,40 ± 9,41 AB 0,048 * *P < 0.05; **P < 0.01; ¥ : ANOVA (F). Descriptive statistics are given as mean ± standard deviation. A, B : Different letters or letter combinations in the same row indicate a statistically significant difference (P < 0.05); Abbreviations: BMI, body mass index; LH, luteinizing hormone; FSH, follicle-stimulating hormone Analysis of the genotype, allelotype, and haplotype distributions of polymorphisms in the groups revealed that the AA genotype of the FSHR SNP rs6165 polymorphism did not significantly differ between the groups (p = 0.091). The TA genotype did not significantly differ between the groups (p = 0.061). The TT genotype did not significantly differ between the groups (p = 0.449). The allelotype did not significantly differ between the groups (p = 0.819). The allelotype did not significantly differ between the groups (p = 0.911). For the FSHR SNP rs6166 polymorphisms, the SS genotype did not significantly differ between the groups (p = 0.144). The NS genotype did not significantly differ between the groups (p = 0.066). The NN genotype did not significantly differ between the groups (p = 0.444). The S allele did not significantly differ between the groups (p = 0.819). The N allele did not significantly differ between the groups (p = 0.911). Analysis of the haplotypes for the two SNPs in question revealed that the AASS haplotype did not significantly differ between the groups (p = 0.091). The TANS haplotype did not significantly differ between the groups (p = 0.066). The TTNN haplotype did not significantly differ between the groups (p = 0.449) (Table 6 ). Table 6 Comparison of FSHR polymorphism genotype frequencies between the groups The307Ala (rs6165) Group 1 Group 2 Group 3 P ¥ AA 9 (%60) 3 (%20) 3 (%20) 0,091 TA 4 (%13) 14 (%47) 12 (%40) 0,061 TT 7 (%47) 3 (%20) 5 (%33) 0,449 Allelotype A 22 (%37) 20 (%33) 18 (%30) 0,819 T 18 (%30) 20 (%33) 22 (%37) 0,819 Asn680Ser (rs6166) Group 1 Group 2 Group 3 P ¥ SS 9 (%56) 3 (%19) 4 (%25) 0.144 NS 4 (%14) 14 (%50) 10 (%36) 0.066 NN 7 (%44) 3 (%19) 6 (%38) 0.444 Allelotype S 22 (%37) 20 (%33) 18 (%30) 0.819 N 18 (%30) 20 (%33) 22 (%37) 0.819 Haplotype Group 1 Group 2 Group 3 P ¥ AASS 9 (%45) 3 (%15) 3 (%15) 0.091 TANN 0 (%0) 0 (%0) 1 (%5) - TANS 4 (%20) 14 (%70) 10 (%50) 0.066 TASS 0 (%0) 0 (%0) 1 (%5) - TTNN 7 (%35) 3 (%15) 5 (%25) 0.449 *P < 0.05; **P < 0.01; 1 : Chi-square test (χ 2 ); OR, odds ratio. Descriptive statistics are given as number (percentage) values For the ER1 rs2234693 polymorphism, the CC genotype did not significantly differ between the groups (p = 0.905). The CT genotype did not significantly differ between the groups (p = 0.607). The TT genotype did not significantly differ between the groups (p = 0.311). The C allele did not significantly differ between the groups (p = 0.584). The allelotype did not significantly differ between the groups (p = 0.662). For the ER1 rs9340799 polymorphism, the AA genotype was not significantly different between the groups (p = 0.387). The GA genotype did not significantly differ between the groups (p = 0.670). The GG genotype did not significantly differ between the groups (p = 0.273). The allelotype did not significantly differ between the groups (p = 0.476). The G allele did not significantly differ between the groups (p = 0.353). Analysis of the haplotypes for the two SNPs in question revealed that the CCGA haplotype did not significantly differ between the groups (p = 0.180). The CCGG haplotype was not significantly different between the groups (p = 0.317). The CTGA haplotypes did not significantly differ between the groups (p = 0.961). The TAA haplotype did not significantly differ between the groups (p = 0.646) (Table 7 ). Table 7 Comparison of ER1 polymorphism genotype frequencies between the groups PVuII (rs2234693) Group 1 Group 2 Group 3 P ¥ CC 3 (%30) 4 (%40) 3 (%30) 0.905 CT 8 (%25) 12 (%38) 12 (%38) 0.607 TT 9 (%50) 4 (%22) 5 (%28) 0.311 Allelotype C 14 (%27) 20 (%38) 18 (%35) 0.584 T 26 (%38) 20 (%29) 22 (%32) 0.662 XbaI (rs9340799) Group 1 Group 2 Group 3 P ¥ AA 7 (%35) 4 (%20) 9 (%45) 0.387 GA 8 (%27) 12 (%40) 10 (%33) 0.670 GG 5 (%50) 4 (%40) 1 (%10) 0.273 Allelotype A 22 (%31) 20 (%29) 28 (%40) 0.476 G 18 (%36) 20 (%40) 12 (%24) 0.353 Haplotype Group 1 Group 2 Group 3 P ¥ CC-AA 0 (%0) 0 (%0) 1 (%100) - CC-GA 0 (%0) 4 (%80) 1 (%20) 0,180 CC-GG 3 (%75) 0 (%0) 1 (%25) 0,317 CT-AA 0 (%0) 0 (%0) 3 (%100) - CT-GA 8 (%32) 8 (%32) 9 (%36) 0,961 CT-GG 0 (%0) 4 (%100) 0 (%0) - TT-AA 7 (%44) 4 (%25) 5 (%31) 0,646 TT-GG 2 (%100) 0 (%0) 0 (%0) - *P < 0.05; **P < 0.01; 1 : Chi-square test (χ 2 ). Descriptive statistics are given as number (percentage) values. For the ER2 rs4986938 polymorphism, the AA genotype did not significantly differ between the groups (p = 0.655). The GA genotype did not significantly differ between the groups (p = 0.261). The GG genotype did not significantly differ between the groups (P = 0.104). The allelotype did not significantly differ between the groups (p = 0.168). The G allele did not significantly differ between the groups (p = 0.382). For the ER2 rs1256049 polymorphism, the GA genotype did not significantly differ between the groups (p = 0.178). The GG genotype did not significantly differ between the groups (p = 0.679). The allelotype did not significantly differ between the groups (p = 0.178). The G allele did not significantly differ between the groups (p = 0.840). Analysis of the haplotypes for the two SNPs revealed that the AAGG haplotype did not significantly differ between the groups (p = 0.655). The GAGA haplotype did not significantly differ between the groups (p = 0.414). TheGAGG haplotype did not significantly differ between the groups (p = 0.607). The GGGA haplotype did not significantly differ between the groups (p = 0.180). The GGGG haplotype did not significantly differ between the groups (p = 0.311) (Table 8 ). Table 8 Comparison of ER2 polymorphism genotype frequencies between the groups AluI (rs4986938) Group 1 Group 2 Group 3 P ¥ AA 2 (%40) 0 (%0) 3 (%60) 0.655 GA 15 (%47) 9 (%28) 8 (%25) 0.261 GG 3 (%13) 11 (%48) 9 (%39) 0.104 Allelotype A 19 (%45) 9 (%21) 14 (%33) 0.168 G 21 (%27) 31 (%40) 26 (%33) 0.382 RsaI (rs1256049) Group 1 Group 2 Group 3 P ¥ GA 4 (%36) 6 (%55) 1 (%9) 0.178 GG 16 (%33) 14 (%29) 19 (%39) 0.679 Allelotype A 4 (%36) 6 (%55) 1 (%9) 0.178 G 36 (%33) 34 (%31) 39 (%36) 0.840 Haplotype Group 1 Group 2 Group 3 P ¥ AA-GG 2 (%40) 0 (%0) 3 (%60) 0.655 GA-GA 4 (%67) 2 (%33) 0 (%0) 0.414 GA-GG 11 (%42) 7 (%27) 8 (%31) 0.607 GG-GA 0 (%0) 4 (%80) 1 (%20) 0.180 GG-GG 3 (%17) 7 (%39) 8 (%44) 0.311 *P < 0.05; **P < 0.01; 1 : Chi-square test (χ 2 ). Descriptive statistics are given as number (percentage) values. DISCUSSION The selection of medication for ovulation induction and the adjustment of its dosage are crucial steps in individualizing infertility treatments. Selecting the correct dosage of the medication can help prevent inadequate or exaggerated responses, thereby avoiding issues such as cycle cancellation, which can cost patients time, money, and hope. From a medical perspective, it can reduce wasted efforts that lead to no outcome and help manage complications such as OHSS. CC is one of the most commonly used oral agents for inducing ovulation in infertility associated with PCOS. The CC is a selective estrogen receptor modulator. It has both estrogenic and antiestrogenic properties. The CC acts as a competitive antagonist for 17-beta estradiol in the hypothalamus. Because of the blockade of the estrogen receptor, there are no limitations on the release of GnRH, resulting in increased endogenous FSH release. FSH is crucial in regulating steroidogenesis. It activates folliculogenesis and estrogen synthesis via FSHR (8,9). Owing to this activation, ovulation is achieved in 22% and 52% of patients with daily doses of 50 mg and 100 mg, respectively. Because predicting the lowest effective dose to induce ovulation at the beginning of treatment is challenging, the dose is empirically started at 50 mg/day and increased gradually until ovulation induction is achieved (up to a maximum of 250 mg/day) (1). While the aim is to achieve monofollicular or bifollicular development and ovulation, the rate of an exaggerated response, defined as the development of three or more follicles, with 50 mg/day CC treatment in women with PCOS is reported to be 6% (2). The FSHR gene contains two significant SNPs that alter two amino acids at the Ala307Thr and Asn680Ser positions on chromosome 2 exon 10. Numerous studies have investigated the effects of these SNPs on gynecological diseases and the effects of different FSHR isoforms on functionality (3). An examination of the frequency of FSHR polymorphisms in patients with PCOS revealed that it is controversial whether the distribution of polymorphisms in these women is different from that in normo-ovulatory or non-PCOS anovulatory women. Two meta-analyses on this topic reported conflicting results. In the meta-analysis conducted by Chen et al., FSHR polymorphisms were not associated with an increased risk of PCOS, whereas Qui et al. reported that Ala307Thr variant carriers had a decreased sensitivity for PCOS (12,13). Laven et al. reported the frequencies of Ala307Ala, Ala307Thr, Thr307Thr, Asn680Asn, Asn680Ser, and Ser680Ser as 21%, 58%, 25%, 15%, 46%, and 26%, respectively. The frequencies of the polymorphisms evaluated in the present study are consistent with those of Laven et al., and the differences may be related to ethnic factors (12). There are few studies examining how different FSHR isoforms respond to increased FSH levels with CC use. Valkenburg et al. investigated the impact of FSHR polymorphisms on ovulation induction outcomes in WHO Class 2 anovulatory women. They reported that, compared with other alleles, the Ser680Ser polymorphism resulted in a lower rate of recovery of ovulatory menstrual cycles after ovulation induction treatment with CC. The authors suggested that carriers of the 680Ser allele might have a greater probability of achieving an ongoing pregnancy when subsequently treated with FSH. The association of the FSHR Ser680 allele with higher follicular phase FSH levels and a higher requirement for exogenous FSH during IVF treatments may indicate that the FSHR variant encoded by this allele has a higher threshold for exogenous FSH. Consequently, ovulation induction with CC or exogenous FSH could be influenced by the FSHR genotype (13). In a retrospective study conducted by Overbeek et al., the effects of the Ser680Ser polymorphism on CC resistance in PCOS patients were examined. The study revealed that patients with the Ser/Ser polymorphism were more resistant to clomiphene than to other variants (14). One of the limitations of the present study, which differs from that of Overbeek et al., is that we included anovulatory patients who did not respond to 50 mg/day clomiphene treatment rather than 150 mg/day, which is normally considered clomiphene resistance. However, the fact that the SS polymorphism was the most common variant, with 56% of women who did not respond to 50 mg/day clomiphene, while there was no statistically significant difference between the groups is still remarkable and consistent with the reference study. Factors that can affect the response to CC include age, BMI, the free androgen index, insulin resistance, FSH levels, and the FSHR genotype (14-17). Among these factors, the only factor that is not modifiable is the FSHR polymorphism, and our study is the first to investigate FSHR polymorphisms in patients with an exaggerated response to CC. The results revealed that there was no significant difference in terms of FSHR Ala307Thr (rs6165) and Asn680Ser (rs6166) polymorphism distributions between patients with more than three stages of follicle development, defined as an exaggerated response to CC, and other groups. To date, over 2000 ER polymorphisms have been identified. Meta-analyses investigating the ER1 polymorphisms XbaI (351 A>C) (rs9340799) and PvuII (397 T>C) (rs2234693), which are encoded on chromosome 7, as well as the ER2 polymorphisms RsaI 1082 G>A (rs1256049) and AluI 1730 A>G (rs4986938), which are encoded on chromosome 14, indicate that these variations are not individually associated with PCOS susceptibility (18-20). The CC is structurally similar to estrogen. This allows the CC to bind to the nuclear ER in the reproductive system and hypothalamus. Unlike estrogen, CC binds to these receptors for a longer period of time and consequently decreases ER concentrations (1,2). Considering this mechanism of action of the drug, it can be hypothesized that ER polymorphisms may affect drug–receptor binding and alter drug potency. To the best of our knowledge, no other study has investigated the associations between ER polymorphisms and the response to CC. In the present study, no statistically significant difference was found in favour of any of the polymorphisms investigated between patients who developed an exaggerated response to 50 mg/day CC, those who did not develop a response, and those who developed one or two follicles. PCOS is the most common endocrinological abnormality in women of reproductive age and is one of the most frequent causes of infertility etiology. Therefore, it is important to design more effective and individually tailored treatment algorithms for the patients we frequently encounter and treat in daily clinical practice. With a clearer understanding of genetic factors that can predict the response to CC, ovarian hyperstimulation and multiple pregnancies can be prevented, making safeguarding the health of infertile women easier. The results obtained in the present study showed that FSHR, ER1, and ER2 polymorphisms cannot be used to predict ovarian hyperstimulation in response to CC. Further studies with larger patient groups should be conducted to clarify this situation. Abbreviations PCOS: polycystic ovary syndrome CC: clomiphene citrate OHSS: ovarian hyperstimulation syndrome SNP: single-nucleotide polymorphism IVF: in vitro fertilization FSH: follicle-stimulating hormone FSHR: follicle-stimulating hormone receptor ER: estrogen receptor Declarations Author Contribution G Aktaş: Project development, Data collection, Manuscript writing M Bertizlioğlu: Data collection, Manuscript editing SA Yılmaz: Data analysis, Project development AG Kebapcılar: Data collection, Manuscript editing Ö Seçilmiş: Project development, Manuscript writing Compliance with ethical standards Funding: This study was funded by the Selçuk University Scientific Research Project Unit. Conflicts of interest: In accordance with the ICMJE uniform disclosure form, all the authors declare that they have no conflicts of interest. Animal subjects: All the authors confirmed that this study did not involve animal subjects or tissue. Human subjects: Consent was obtained from or waived by all participants in this study. The Local Ethics Committee of the Selçuk University Faculty of Medicine issued approval 2019/49. Financial relationships: All the authors declare that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All the authors declare that there are no other relationships or activities that could influence the submitted work. References Practice Committee of the American Society for Reproductive Medicine Use of clomiphene citrate in infertile women: a committee opinion. Fertil Steril. 2013 Aug;100(2):341-8. doi: 10.1016/j.fertnstert.2013.05.033. Epub 2013 Jun 27. Coughlan C, Fitzgerald J, Milne P, Wingfield M. Is it safe to prescribe clomiphene citrate without ultrasound monitoring facilities? J Obstet Gynaecol. 2010 May;30(4):393-6. doi: 10.3109/01443611003646280. Meduri G, Bachelot A, Cocca MP, Vasseur C, Rodien P, Kuttenn F, Touraine P, Misrahi M (2008) Molecular pathology of the FSH receptor: New insights into FSH physiology. Mol Cellular Endocrinol 282:130–142. doi:10.1016/j.mce.2007.11.027 Lussiana C, Guani B, Mari C, Restagno G, Massobrio M, Revelli A (2008) Mutations and polymorphisms of the FSH receptor (FSHR) gene. Clinical implications in female fecundity and molecular biology of FSHR protein and gene. Obstet Gynecol Surv 12:785–795. doi: 10.1097/OGX.0b013e31818957eb Laven JSE. Follicle Stimulating Hormone Receptor (FSHR) Polymorphisms and Polycystic Ovary Syndrome (PCOS). Front Endocrinol (Lausanne). 2019 Feb 12;10:23. doi: 10.3389/fendo.2019.00023. Simoni M, Tempfer CB, Destenaves B, Fauser BC. Functional genetic polymorphisms and female reproductive disorders: Part I: Polycystic ovary syndrome and ovarian response. Hum Reprod Update. 2008 Sep-Oct;14(5):459-84. doi: 10.1093/humupd/dmn024. Epub 2008 Jul 4. Paschalidou C, Anagnostou E, Mavrogianni D, Raouasnte R, Klimis N, Drakakis P, Loutradis D. The effects of follicle-stimulating hormone receptor (FSHR) -29 and Ser680Asn polymorphisms in IVF/ICSI. Horm Mol Biol Clin Investig. 2020 Mar 2;41(2). doi: 10.1515/hmbci-2019-0058. The Rotterdam ESHRE/ASRM‐sponsored PCOS consensus workshop group. Revised 2003 consensus on diagnostic criteria and long‐term health risks related to polycystic ovary syndrome (PCOS). Human Reproduction, Volume 19, Issue 1, January 2004, Pages 41–47, https://doi.org/10.1093/humrep/deh098 Lessey BA, Metzger DA, Haney AF, McCarty KS Jr (1989) Immunohistochemical analysis of estrogen and progesterone receptors in endometriosis: comparison with normal endometrium during the menstrual cycle and the effect of medical therapy. Fertil Steril 51:409–415. doi:10.1016/S0015-0282(16)60545-9 Chen DJ, Ding R, Cao JY, Zhai JX, Zhang JX, Ye DQ. Two folliclestimulating hormone receptor polymorphisms and polycystic ovary syndrome risk: a meta-analysis. Eur Obstet Gynecol Reprod Biol. (2014) 182:27–32.doi: 10.1016/j.ejogrb.2014.08.014 Qiu L, Liu J, Hei QM. Association between two polymorphisms of follicle stimulating hormone receptor gene and susceptibility to polycystic ovary syndrome: a meta-analysis. Chin Med Sci J. (2015) 30:44–50. doi: 10.1016/S1001-9294(15)30008-0 Laven JS, Mulders AG, Suryandari DA, Gromoll J, Nieschlag E, Fauser BC, Simoni M. Follicle-stimulating hormone receptor polymorphisms in women with normogonadotropic anovulatory infertility. Fertil Steril. 2003 Oct;80(4):986-92. doi: 10.1016/s0015-0282(03)01115-4. Valkenburg O, van Santbrink EJ, König TE, Themmen AP, Uitterlinden AG, Fauser BC, Lambalk CB, Laven JS. Follicle-stimulating hormone receptor polymorphism affects the outcome of ovulation induction in normogonadotropic (World Health Organization class 2) anovulatory subfertility. Fertil Steril. 2015 Apr;103(4):1081-1088.e3. doi: 10.1016/j.fertnstert.2015.01.002. Overbeek A, Kuijper EA, Hendriks ML, Blankenstein MA, Ketel IJ, Twisk JW, Hompes PG, Homburg R, Lambalk CB. Clomiphene citrate resistance in relation to follicle-stimulating hormone receptor Ser680Ser-polymorphism in polycystic ovary syndrome. Hum Reprod. 2009 Aug;24(8):2007-13. doi: 10.1093/humrep/dep114. Epub 2009 Apr 28. Imani B, Eijkemans MJ, te Velde ER, Habbema JD, Fauser BC. Predictors of patients remaining anovulatory during clomiphene citrate induction of ovulation normogonadotropic oligoamenorrheic infertility. J Clin Endocrinol Meta 1998;83:2361 – 2365. doi: 10.1210/jcem.83.7.4919 Imani B, Eijkemans MJ, de Jong FH, Payne NN, Bouchard P, Giudice LC, Fauser BC. Free androgen index and leptin are the most prominent endocrine predictors of ovarian response during clomiphene citrate induction of ovulation in normogonadotropic oligoamenorrheic infertility. J Clin Endocrinol Metab 2000;85:676 – 682. doi: 10.1210/jcem.85.2.6356 Kurabayashi T, Suzuki M, Fujita K, Murakawa H, Hasegawa I, Tanaka K. Prognostic factors for ovulatory response with clomiphene citrate in polycystic ovary syndrome. Eur J Obstet Gynecol Reprod Biol 2006; 126:201– 205. doi: 10.1016/j.ejogrb.2005.11.005 Motawi TM, El-Rehany MA, Rizk SM, Ramzy MM, El-Roby DM. Genetic Polymorphism of Estrogen Receptor Alpha Gene in Egyptian Women With Type II Diabetes Mellitus. Meta Gene (2015) 6:36–41. doi: 10.1016/j.mgene.2015.08.001 Nectaria X, Leandros L, Ioannis G, Agathocles T. The Importance of Erα and Erβ Gene Polymorphisms in PCOS. Gynecol Endocrinol Off J Int Soc Gynecol Endocrinol (2012) 28(7):505–8. doi: 10.3109/09513590.2011.649811 Zhou S, Wen S, Sheng Y, Yang M, Shen X, Chen Y, Kang D, Xu L. Association of Estrogen Receptor Genes Polymorphisms With Polycystic Ovary Syndrome: A Systematic Review and Meta-Analysis Based on Observational Studies. Front Endocrinol (Lausanne). 2021 Oct 4;12:726184. doi: 10.3389/fendo.2021.726184 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-7160268","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":492939359,"identity":"b0be9416-e5a6-4f52-8c8b-f9f3092ddbd5","order_by":0,"name":"Görkem Aktaş","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAqUlEQVRIiWNgGAWjYDACHhBRwcBgQJqWA2dI1nKwjRQt8j5nzB5/nHdY3py9+QDDj4pthLUYnu0xNzi47bDhzp5jCYw9Z24ToaWfx0wCqIVxw40cA2bGNqK1zDlsT7wWed4eoJaGw4nEazHgOVYmceZYevKGM8cSDhLlF/me5G0SFTXWthuONx988KOCGFsOgKlmMHmAsHqQLQ1gqo4oxaNgFIyCUTBCAQBVtUA3IwRKZgAAAABJRU5ErkJggg==","orcid":"","institution":"Selcuk University Medicine Faculty","correspondingAuthor":true,"prefix":"","firstName":"Görkem","middleName":"","lastName":"Aktaş","suffix":""},{"id":492939360,"identity":"9e45051f-d70d-4016-89f3-d2251e09fa52","order_by":1,"name":"Mete Bertizlioğlu","email":"","orcid":"","institution":"Selcuk University Medicine Faculty","correspondingAuthor":false,"prefix":"","firstName":"Mete","middleName":"","lastName":"Bertizlioğlu","suffix":""},{"id":492939361,"identity":"499e6ca5-9b1f-4686-adb1-e911417058de","order_by":2,"name":"Setenay Arzu Yılmaz","email":"","orcid":"","institution":"Selcuk University Medicine Faculty","correspondingAuthor":false,"prefix":"","firstName":"Setenay","middleName":"Arzu","lastName":"Yılmaz","suffix":""},{"id":492939362,"identity":"867cad7e-2398-4b70-8a26-8e3d30e55a57","order_by":3,"name":"Ayşe Gül Kebapcılar","email":"","orcid":"","institution":"Medova Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ayşe","middleName":"Gül","lastName":"Kebapcılar","suffix":""},{"id":492939363,"identity":"717a14d8-87e3-47ed-9bc2-a58a51a17994","order_by":4,"name":"Özlem Seçilmiş","email":"","orcid":"","institution":"Private Clinic","correspondingAuthor":false,"prefix":"","firstName":"Özlem","middleName":"","lastName":"Seçilmiş","suffix":""}],"badges":[],"createdAt":"2025-07-18 19:23:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7160268/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7160268/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88099805,"identity":"3d2db2f9-dbdf-46d0-a53a-aa533ab7b774","added_by":"auto","created_at":"2025-08-01 11:18:10","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":380450,"visible":true,"origin":"","legend":"\u003cp\u003eThe genotype distribution of the FSHR rs6166 SNP was analysed in 60 patients included in the study. The SS genotype was found in 26.6%, the NS genotype in 46.6%, and the NN genotype in 26.6% of the patients. Analysis of the genotype distribution for the FSHR rs6165 SNP revealed that the AA genotype was found in 25%, the TA genotype in 50%, and the TT genotype in 25% of the patients. For the ER1 rs2234693 polymorphism, 16.6% of the patients had the CC genotype, 53.3% had the CT genotype, and 30% had the TT genotype. For the rs9340799 polymorphism, 33.3% of the patients had the AA genotype, 50% had the GA genotype, and 16.6% had the GG genotype. The genotype distributions for the ER2 rs4986938 SNP were 18.3% and 81.6% for the GA genotype and GG genotype, respectively. For the rs1256049 SNP, the AA genotype was found in 8.3%, the GA genotype in 53.3%, and the GG genotype in 38.3% of the patients.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7160268/v1/3ac2e58456b71a00af636cf4.png"},{"id":90993246,"identity":"88be453c-5e50-4ada-b8e7-9fc2e8d188ae","added_by":"auto","created_at":"2025-09-10 11:53:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1446840,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7160268/v1/fa95c078-1341-4019-a01e-a1a962b5f5e3.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eThe Association of Exaggerated Folliculer Responses to Clomiphene Citrate With Estrogen and Follicle-stimulating Hormone Receptor Polymorphisms in Women With Polycystic Ovary Syndrome\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003ePolycystic ovary syndrome (PCOS) is a clinical condition characterized by oligoanovulation, hyperandrogenism, and polycystic ovarian morphology on ultrasonography, with a prevalence of approximately 10\u0026ndash;15% in the general population. Oligo-anovulation leads to oligomenorrhea and infertility. In patients with these conditions, when pregnancy cannot be achieved with lifestyle changes such as diet and exercise, the first-line treatment is ovulation induction via oral agents, such as clomiphene citrate (CC) and letrozole.\u003c/p\u003e\u003cp\u003eThe CC is a selective estrogen receptor modulator. It has both estrogenic and antiestrogenic properties. While resistance to CC and treatment failure with CC, i.e., the failure to achieve pregnancy despite achieving ovulation, have been extensively studied, the exaggerated response to CC has not been thoroughly examined, and the underlying reasons have not been clearly elucidated. The rate of multiple pregnancies due to clomiphene treatment is 8%. In contrast, ovarian hyperstimulation syndrome (OHSS) is rare, with a rate of approximately 1% (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). CC treatment in anovulatory patients is aimed at the development of a single dominant follicle. Therefore, treatment usually begins with the lowest dosage form available, which is a 50 mg tablet taken once a day. During CC treatment, an exaggerated follicular response, characterized by the development of three or more follicles, is observed in approximately 14% of patients. This rate is higher in ovulatory patients than in anovulatory patients (17% vs. 6%) (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). This creates a risk of triplet or quadruplet pregnancies, which are now considered treatment failures, and OHSS. Therefore, identifying which patients will have an exaggerated response to this treatment is crucial.\u003c/p\u003e\u003cp\u003ePolymorphism can be defined as the presence of two or more distinct phenotypes within a population. Polymorphisms are distinguished from mutations by their presence as variant alleles at a relatively high frequency within a population. They are mostly observed in the form of single nucleotide polymorphisms (SNPs). SNPs can be silent, but they can also influence susceptibility to diseases or the response to medications. When identified as a reason for differences in drug effects, personalized, patient-friendly protocols such as individual treatment options and dose selection on the basis of the patient\u0026rsquo;s genotype can be established. For example, because the gonadotropin doses required for controlled ovarian hyperstimulation may vary in the presence of different follicle-stimulating hormone (FSH) receptor isoforms in patients undergoing in vitro fertilization (IVF), the evaluation of FSH receptor (FSHR) polymorphisms has become part of daily practice (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe CC binds to estrogen receptors (ERs) because of its structural similarity to estrogen. Unlike estrogen, CC binds to the nuclear ER over a longer period and reduces the concentration of ER. One of the mechanisms of action of a drug is dependent on its activity at the hypothalamic level. A reduction in the hypothalamic ER concentration affects the accurate perception of circulating estrogen levels by the hypothalamus. This diminished estrogen feedback signal increases the amplitude of the gonadotropin hormone-releasing hormone pulse during treatment in patients with anovulatory PCOS, leading to increased FSH levels. Successful treatment, the development of one or two mature follicles, is defined by an increase in estrogen from the growing follicles, which triggers the luteinizing hormone (LH) surge and subsequently leads to ovulation (\u003cspan additionalcitationids=\"CR4 CR5\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Polymorphisms in the ER gene can alter the relationship between CC and the receptor by affecting the sensitivity of the receptor to CC.\u003c/p\u003e\u003cp\u003eThe relationship between FSHR polymorphisms and the development of multiple follicles and the relationship between the exogenous FSH response and under- or overstimulation are known and clinically used to predict the response to exogenous FSH in daily clinical practice. Although the relationship between the response to exogenous FSH and FSHR polymorphisms has been frequently investigated, very few studies have investigated the relationship between CC and FSHR SNPs (\u003cspan additionalcitationids=\"CR4 CR5 CR6\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThis study focused on ovulation induction treatment using CC, a selective estrogen receptor modulator/partial estrogen antagonist for achieving monofollicular development and ovulation in anovulatory patients diagnosed with PCOS. The aim of this study was to investigate the presence of ER and FSHR polymorphisms in patients exhibiting an exaggerated follicular response.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cp\u003e\u003cb\u003ePatients\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFSHR and ER SNPs were investigated in a total of 60 patients diagnosed with PCOS who presented to the infertility outpatient clinic of the Sel\u0026ccedil;uk University Faculty of Medicine between 2019 and 2020 and started their first treatment cycles with CC. The study was approved by the Ethics Committee of Sel\u0026ccedil;uk University and was conducted in accordance with the Declaration of Helsinki. Informed consent was obtained from all patients who participated in the study. PCOS was diagnosed when two of the three Rotterdam criteria were satisfied: oligo-ovulation or anovulation, polycystic ovary appearance on ultrasound, and clinical or biochemical hyperandrogenism (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Women with signs of virilization; those who were diagnosed with nonclassical congenital adrenal hyperplasia, androgen-secreting tumors, Cushing\u0026rsquo;s syndrome, hyperprolactinemia or thyroid dysfunction; those aged\u0026thinsp;\u0026lt;\u0026thinsp;21 years or \u0026gt;\u0026thinsp;35 years; those with a body mass index\u0026thinsp;\u0026gt;\u0026thinsp;40 kg/m\u003csup\u003e2\u003c/sup\u003e; and those with chronic illnesses were excluded from the study.\u003c/p\u003e\u003cp\u003eOral CC treatment was initiated on the 5th day of menstruation at once-daily doses of 50 mg and continued for 5 days. TVUS-guided folliculometry was performed from day 12 of the cycle. Patients were evaluated in three groups: patients with no\u0026thinsp;\u0026gt;\u0026thinsp;18 mm follicle (Group 1, n\u0026thinsp;=\u0026thinsp;20), normal responders with one or two\u0026thinsp;\u0026gt;\u0026thinsp;18 mm follicles (Group 2, n\u0026thinsp;=\u0026thinsp;20), and nonresponders with three or more\u0026thinsp;\u0026gt;\u0026thinsp;18 mm follicles (Group 3, n\u0026thinsp;=\u0026thinsp;20).\u003c/p\u003e\u003cp\u003e\u003cb\u003eSingle-Nucleotide Polymorphism Genotyping\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThree milliliters of venous blood samples obtained from the patients were stored in EDTA tubes at \u0026minus;\u0026thinsp;20\u0026deg;C. The SNPs were genotyped via TaqMan assays (Applied Biosystems, Foster City, CA, USA) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The 12-\u0026micro;L reaction mixture contained 25 ng of genomic DNA, 0.25x stock genotyping assay, and 1x TaqMan genotyping PCR master mix. Amplification and hybridization were performed via the Applied Biosystems StepOnePlus Real-Time PCR System according to the manufacturer\u0026rsquo;s recommendation.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAnnotations of the analyzed single nucleotide polymorphisms.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGene\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ers ID\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHGVS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eClinical definition\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAssay ID*\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eFSHR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ers6165\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.919A\u0026loz;G\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ers6166\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eC___2676873_30\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ers6166\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.2039A\u0026loz;G\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAsn680Ser\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eC___2676874_10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eER1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ers9340799\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.351A\u0026loz;G\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eXbaI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eC___3163591_10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ers2234693\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.397T\u0026loz;C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePvuII\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eC___3163590_10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eER2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ers1256049\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.1082G\u0026loz;A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRsaI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eC___7573265_1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ers4986938\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.1730A\u0026loz;G\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAluI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eC__11462726_10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e*TaqMan\u0026reg; SNP Genotyping assay, Applied Biosystems\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eThe SPSS (IBM SPSS Statistics for Windows released in 2017, Version 25.0, IBM Corp., Armonk, NY) statistical package program was used for data analysis. Descriptive statistics are presented as the means, standard deviations, numbers, and percentages for categorical and continuous variables where appropriate. In addition, homogeneity of variances, one of the prerequisites of parametric tests, was checked via Levene\u0026rsquo;s test.\u003c/p\u003e\u003cp\u003eThe normality assumption was examined via the Shapiro\u0026ndash;Wilk test. Differences between two groups were evaluated via Student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e test for normally distributed variables and the Mann\u0026ndash;Whitney \u003cem\u003eU\u003c/em\u003e test for nonnormally distributed variables. One-way analysis of variance and Tukey\u0026rsquo;s HSD test were used for comparisons of normally distributed variables between three or more groups, whereas the Kruskal\u0026ndash;Wallis and Bonferroni\u0026ndash;Dunn tests were used for nonnormally distributed variables.\u003c/p\u003e\u003cp\u003eDifferences in categorical variables were analysed via the chi-square test. Cram\u0026eacute;r\u0026rsquo;s V and odds ratio are the effect size values used for the chi-square statistic. The odds ratio value was used when categorical variables were evaluated in two groups. Because categorical variables were evaluated among the three groups in this study, Cram\u0026eacute;r\u0026rsquo;s V effect size was used. p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eThe genotype distribution of the FSHR rs6166 SNP was analysed in 60 patients included in the study. The SS genotype was found in 26.6%, the NS genotype in 46.6%, and the NN genotype in 26.6% of the patients. Analysis of the genotype distribution for the FSHR rs6165 SNP revealed that the AA genotype was found in 25%, the TA genotype in 50%, and the TT genotype in 25% of the patients. For the ER1 rs2234693 polymorphism, 16.6% of the patients had the CC genotype, 53.3% had the CT genotype, and 30% had the TT genotype. For the rs9340799 polymorphism, 33.3% of the patients had the AA genotype, 50% had the GA genotype, and 16.6% had the GG genotype. The genotype distributions for the ER2 rs4986938 SNP were 18.3% and 81.6% for the GA genotype and GG genotype, respectively. For the rs1256049 SNP, the AA genotype was found in 8.3%, the GA genotype in 53.3%, and the GG genotype in 38.3% of the patients. The genotype distribution of the patients is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAn evaluation of the effects of different genotypes on clinical characteristics revealed that body mass index (BMI) measurements were significantly different according to the Ala307Thr (rs6165) polymorphism (P\u0026thinsp;=\u0026thinsp;0.039). BMI measurements were lower in the TA genotype than in the AA and TT genotypes. LH levels also significantly differed according to genotype (p\u0026thinsp;=\u0026thinsp;0.027). LH levels were lower in the TT genotype than in the AA genotype.\u003c/p\u003e\u003cp\u003eFor the Ser680Asn (rs6166) polymorphism, BMI measurements significantly differed according to genotype (P\u0026thinsp;=\u0026thinsp;0.043). BMI measurements were lower in the NS genotype than in the SS and NN genotypes. LH levels also significantly differed according to genotype (p\u0026thinsp;=\u0026thinsp;0.042). LH levels were lower in the NN genotype than in the SS genotype. For the Ala307Thr (rs6165) and Ser680Asn (rs6166) polymorphisms, age, FSH, and estradiol measurements did not significantly differ according to genotype (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eClinical parameters of the study patients segregated based on the FSHR polymorphisms.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFSHR SNP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u003cp\u003eAla307Thr (rs6165)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e\u003cp\u003eSer680Asn (rs6166)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGenotypes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAA (n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTA (n\u0026thinsp;=\u0026thinsp;30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTT (n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP \u003csup\u003e\u0026yen;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eSS (n\u0026thinsp;=\u0026thinsp;16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNS (n\u0026thinsp;=\u0026thinsp;28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eNN (n\u0026thinsp;=\u0026thinsp;16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eP \u003csup\u003e\u0026yen;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27.53\u0026thinsp;\u0026plusmn;\u0026thinsp;3.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26.60\u0026thinsp;\u0026plusmn;\u0026thinsp;3.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26.67\u0026thinsp;\u0026plusmn;\u0026thinsp;2.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.659\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e27.63\u0026thinsp;\u0026plusmn;\u0026thinsp;2.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e26.64\u0026thinsp;\u0026plusmn;\u0026thinsp;3.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e26.44\u0026thinsp;\u0026plusmn;\u0026thinsp;2.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.547\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26.07\u0026thinsp;\u0026plusmn;\u0026thinsp;2.28 \u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23.70\u0026thinsp;\u0026plusmn;\u0026thinsp;3.84 \u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26.00\u0026thinsp;\u0026plusmn;\u0026thinsp;3.53 \u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.039 *\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e26.06\u0026thinsp;\u0026plusmn;\u0026thinsp;2.21 \u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e23.64\u0026thinsp;\u0026plusmn;\u0026thinsp;3.96 \u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e25.81\u0026thinsp;\u0026plusmn;\u0026thinsp;3.49 \u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.043 *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10.47\u0026thinsp;\u0026plusmn;\u0026thinsp;5.19 \u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.50\u0026thinsp;\u0026plusmn;\u0026thinsp;4.75 \u003csup\u003eAB\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.13\u0026thinsp;\u0026plusmn;\u0026thinsp;2.42 \u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.027 *\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e10,06\u0026thinsp;\u0026plusmn;\u0026thinsp;5,27 \u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e7.75\u0026thinsp;\u0026plusmn;\u0026thinsp;4.82 \u003csup\u003eAB\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e6.00\u0026thinsp;\u0026plusmn;\u0026thinsp;2.39 \u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.042 *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFSH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.87\u0026thinsp;\u0026plusmn;\u0026thinsp;1.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.13\u0026thinsp;\u0026plusmn;\u0026thinsp;1.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.427\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5,81\u0026thinsp;\u0026plusmn;\u0026thinsp;1,33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e6.18\u0026thinsp;\u0026plusmn;\u0026thinsp;1.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e5.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.348\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEstradiol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e45.53\u0026thinsp;\u0026plusmn;\u0026thinsp;16.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e42.33\u0026thinsp;\u0026plusmn;\u0026thinsp;9.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35.60\u0026thinsp;\u0026plusmn;\u0026thinsp;14.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.103\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e45,00\u0026thinsp;\u0026plusmn;\u0026thinsp;15,79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e42.18\u0026thinsp;\u0026plusmn;\u0026thinsp;10,13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e36.63\u0026thinsp;\u0026plusmn;\u0026thinsp;14.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.186\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"9\"\u003e*P\u0026thinsp;\u0026lt;\u0026thinsp;0.05; \u003csup\u003e\u0026yen;\u003c/sup\u003e: One-way analysis of variance (ANOVA [F]), Descriptive statistics are given as \u003cem\u003emean\u003c/em\u003e\u0026thinsp;\u0026plusmn;\u0026thinsp;\u003cem\u003estandard\u003c/em\u003e deviation. \u003cb\u003eA, B\u003c/b\u003e: Different letters or letter combinations in the same row indicate statistically significant difference (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Abbreviations: FSHR, follicle-stimulating hormone receptor; SNP, single nucleotide polymorphism; BMI, body mass index; LH, luteinizing hormone; FSH, follicle-stimulating hormone\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFor the PvuII (397 T\u0026thinsp;\u0026gt;\u0026thinsp;C) (rs2234693) polymorphism, there was a statistically significant difference in the mean age among the genotypes (p\u0026thinsp;=\u0026thinsp;0.045). The mean age was lower in the TT genotype than in the CC and CT genotypes. BMI measurements also revealed a significant difference according to genotype (p\u0026thinsp;=\u0026thinsp;0.017). BMI measurements were lower in the CC and CT genotypes than in the TT genotype. FSH measurements also revealed a statistically significant difference according to genotype (p\u0026thinsp;=\u0026thinsp;0.001). FSH measurements were lower in the CC genotype than in the CT and TT genotypes.\u003c/p\u003e\u003cp\u003eFor the XbaI (351 A\u0026thinsp;\u0026gt;\u0026thinsp;G) (rs9340799) polymorphism, there was a statistically significant difference in the mean age among the genotypes (p\u0026thinsp;=\u0026thinsp;0.049). The mean age was lower for the AA genotype than for the GG genotype. LH levels also significantly differed according to genotype (p\u0026thinsp;=\u0026thinsp;0.002). LH levels were lower in the AA genotype than in the GA and GG genotypes. In the PvuII (397 T\u0026thinsp;\u0026gt;\u0026thinsp;C) (rs2234693) polymorphism, LH and estradiol levels did not significantly differ according to genotype (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). In the XbaI (351 A\u0026thinsp;\u0026gt;\u0026thinsp;G) (rs9340799) polymorphism, BMI, FSH, and estradiol measurements did not significantly differ according to genotype (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eClinical parameters of the study patients segregated based on the ER1 polymorphisms.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eER1 SNP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u003cp\u003ePvuII (397 T\u0026thinsp;\u0026gt;\u0026thinsp;C) (rs2234693)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e\u003cp\u003eXbaI (351 A\u0026thinsp;\u0026gt;\u0026thinsp;G) (rs9340799)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGenotypes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCC (n\u0026thinsp;=\u0026thinsp;10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCT (n\u0026thinsp;=\u0026thinsp;32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTT (n\u0026thinsp;=\u0026thinsp;18)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP \u003csup\u003e\u0026yen;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eAA (n\u0026thinsp;=\u0026thinsp;20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eGA (n\u0026thinsp;=\u0026thinsp;30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eGG (n\u0026thinsp;=\u0026thinsp;10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eP \u003csup\u003e\u0026yen;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28.00\u0026thinsp;\u0026plusmn;\u0026thinsp;2.49 \u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27.38\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2 27 \u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e25.28\u0026thinsp;\u0026plusmn;\u0026thinsp;3.48 \u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.045 *\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e25.70\u0026thinsp;\u0026plusmn;\u0026thinsp;3.77 \u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e26.97\u0026thinsp;\u0026plusmn;\u0026thinsp;2.97 \u003csup\u003eAB\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e28.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.49 \u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.049 *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23.10\u0026thinsp;\u0026plusmn;\u0026thinsp;2.47 \u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24.38\u0026thinsp;\u0026plusmn;\u0026thinsp;3.73 \u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26.72\u0026thinsp;\u0026plusmn;\u0026thinsp;3.16 \u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.017 *\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e25.55\u0026thinsp;\u0026plusmn;\u0026thinsp;3.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e24.67\u0026thinsp;\u0026plusmn;\u0026thinsp;3.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e24.1\u0026thinsp;\u0026plusmn;\u0026thinsp;3.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.535\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.70\u0026thinsp;\u0026plusmn;\u0026thinsp;5.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.31\u0026thinsp;\u0026plusmn;\u0026thinsp;5.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.17\u0026thinsp;\u0026plusmn;\u0026thinsp;1.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.116\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6.95\u0026thinsp;\u0026plusmn;\u0026thinsp;4.01 \u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e7.03\u0026thinsp;\u0026plusmn;\u0026thinsp;4.19 \u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e12.4\u0026thinsp;\u0026plusmn;\u0026thinsp;4.79 \u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.002 **\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFSH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88 \u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.84\u0026thinsp;\u0026plusmn;\u0026thinsp;1.17 \u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86 \u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.001 **\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5.93\u0026thinsp;\u0026plusmn;\u0026thinsp;1.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e6.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.352\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEstradiol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e44.60\u0026thinsp;\u0026plusmn;\u0026thinsp;6.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e38.72\u0026thinsp;\u0026plusmn;\u0026thinsp;15.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e44.56\u0026thinsp;\u0026plusmn;\u0026thinsp;11.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0,234\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e45.65\u0026thinsp;\u0026plusmn;\u0026thinsp;10.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e38.80\u0026thinsp;\u0026plusmn;\u0026thinsp;14.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e41\u0026thinsp;\u0026plusmn;\u0026thinsp;11.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0,199\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"9\"\u003e*P\u0026thinsp;\u0026lt;\u0026thinsp;0.05; \u003csup\u003e\u0026yen;\u003c/sup\u003e: One-way analysis of variance (ANOVA [F]), Descriptive statistics are given as \u003cem\u003emean\u003c/em\u003e\u0026thinsp;\u0026plusmn;\u0026thinsp;\u003cem\u003estandard\u003c/em\u003e deviation. \u003csup\u003eA, B\u003c/sup\u003e: Different letters or letter combinations in the same row indicate statistically significant difference (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Abbreviations: ESR1, estrogene receptor 1; SNP, single nucleotide polymorphism; BMI, body mass index; LH, luteinizing hormone; FSH, follicle-stimulating hormone\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFor the AluI (1730 A\u0026thinsp;\u0026gt;\u0026thinsp;G) (rs4986938) polymorphism, estradiol levels were significantly different among the genotypes (p\u0026thinsp;=\u0026thinsp;0.014). Oestradiol levels were lower in the GG genotype than in the GA genotype.\u003c/p\u003e\u003cp\u003eFor the RsaI (1082 G\u0026thinsp;\u0026gt;\u0026thinsp;A) (rs1256049) polymorphism, estradiol levels were significantly different among the genotypes (p\u0026thinsp;=\u0026thinsp;0.014). Oestradiol levels were lower in the GG genotype than in the AA and GA genotypes. In the AluI (1730 A\u0026thinsp;\u0026gt;\u0026thinsp;G) (rs4986938) and RsaI (1082 G\u0026thinsp;\u0026gt;\u0026thinsp;A) (rs1256049) polymorphisms, age, BMI, LH, and FSH measurements did not significantly differ among the genotypes (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eClinical parameters of the study patients segregated based on the ER2 polymorphisms.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eER2 SNP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u003cp\u003eAluI (1730 A\u0026thinsp;\u0026gt;\u0026thinsp;G) (rs4986938)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e\u003cp\u003eRsaI (1082 G\u0026thinsp;\u0026gt;\u0026thinsp;A) (rs1256049)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGenotypes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAA (n\u0026thinsp;=\u0026thinsp;0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGA (n\u0026thinsp;=\u0026thinsp;11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGG (n\u0026thinsp;=\u0026thinsp;49)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP \u003csup\u003e\u0026sum;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eAA (n\u0026thinsp;=\u0026thinsp;5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eGA (n\u0026thinsp;=\u0026thinsp;32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eGG (n\u0026thinsp;=\u0026thinsp;23)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eP \u003csup\u003e\u0026yen;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26.91\u0026thinsp;\u0026plusmn;\u0026thinsp;2.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26.84\u0026thinsp;\u0026plusmn;\u0026thinsp;3.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.948\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e27\u0026thinsp;\u0026plusmn;\u0026thinsp;4.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e27.03\u0026thinsp;\u0026plusmn;\u0026thinsp;3.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e26.57\u0026thinsp;\u0026plusmn;\u0026thinsp;3.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.948\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23.18\u0026thinsp;\u0026plusmn;\u0026thinsp;3.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e25.24\u0026thinsp;\u0026plusmn;\u0026thinsp;3.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.084\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e22\u0026thinsp;\u0026plusmn;\u0026thinsp;2.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e25.16\u0026thinsp;\u0026plusmn;\u0026thinsp;3.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e25.09\u0026thinsp;\u0026plusmn;\u0026thinsp;3.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.084\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.09\u0026thinsp;\u0026plusmn;\u0026thinsp;5.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.86\u0026thinsp;\u0026plusmn;\u0026thinsp;4.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.881\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e8.66\u0026thinsp;\u0026plusmn;\u0026thinsp;5.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e7.3\u0026thinsp;\u0026plusmn;\u0026thinsp;3.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.881\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFSH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.84\u0026thinsp;\u0026plusmn;\u0026thinsp;1.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.110\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5.66\u0026thinsp;\u0026plusmn;\u0026thinsp;1.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e6.26\u0026thinsp;\u0026plusmn;\u0026thinsp;1.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.110\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEstradiol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50.18\u0026thinsp;\u0026plusmn;\u0026thinsp;16.22 \u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e39.49\u0026thinsp;\u0026plusmn;\u0026thinsp;11.75 \u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.014 *\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e51.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.97 \u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e44.06\u0026thinsp;\u0026plusmn;\u0026thinsp;14.44 \u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e35.65\u0026thinsp;\u0026plusmn;\u0026thinsp;10.22 \u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.014 *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"9\"\u003e*P\u0026thinsp;\u0026lt;\u0026thinsp;0.05; \u003csup\u003e\u0026yen;\u003c/sup\u003e: ANOVA (F); \u003csup\u003e\u0026sum;\u003c/sup\u003e: Student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e-test (t). Descriptive statistics are given as \u003cem\u003emean\u003c/em\u003e\u0026thinsp;\u0026plusmn;\u0026thinsp;\u003cem\u003estandard\u003c/em\u003e deviation. \u003csup\u003e\u003cb\u003eA, B\u003c/b\u003e\u003c/sup\u003e: Different letters or letter combinations in the same row indicate statistically significant difference (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) ; Abbreviations: ESR1, estrogene receptor 1; SNP, single nucleotide polymorphism; BMI, body mass index; LH, luteinizing hormone; FSH, follicle-stimulating hormone\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eA comparison of the clinical data of the study groups revealed a statistically significant difference in BMI between the groups (p\u0026thinsp;=\u0026thinsp;0.001). BMI measurements were lower in Group 2 and Group 3 than in Group 1. The estradiol level was also significantly different between the groups (p\u0026thinsp;=\u0026thinsp;0.048). Estradiol measurements were lower in Group 2 than in Group 1 (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eClinical parameters of the study groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGroup 1 (n\u0026thinsp;=\u0026thinsp;20)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGroup 2 (n\u0026thinsp;=\u0026thinsp;20)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGroup 3 (n\u0026thinsp;=\u0026thinsp;20)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP \u003csup\u003e\u0026yen;\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26,60\u0026thinsp;\u0026plusmn;\u0026thinsp;2,23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26,80\u0026thinsp;\u0026plusmn;\u0026thinsp;4,30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27,15\u0026thinsp;\u0026plusmn;\u0026thinsp;3,22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0,872\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27,45\u0026thinsp;\u0026plusmn;\u0026thinsp;2,63 \u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23,80\u0026thinsp;\u0026plusmn;\u0026thinsp;3,37 \u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23,35\u0026thinsp;\u0026plusmn;\u0026thinsp;3,31 \u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0,001 **\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9,50\u0026thinsp;\u0026plusmn;\u0026thinsp;4,88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7,35\u0026thinsp;\u0026plusmn;\u0026thinsp;4,58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6,85\u0026thinsp;\u0026plusmn;\u0026thinsp;4,18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0,158\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFSH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5,95\u0026thinsp;\u0026plusmn;\u0026thinsp;1,28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6,15\u0026thinsp;\u0026plusmn;\u0026thinsp;1,04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5,75\u0026thinsp;\u0026plusmn;\u0026thinsp;1,16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0,558\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEstradiol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47,25\u0026thinsp;\u0026plusmn;\u0026thinsp;15,63 \u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e37,70\u0026thinsp;\u0026plusmn;\u0026thinsp;12,39 \u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e39,40\u0026thinsp;\u0026plusmn;\u0026thinsp;9,41 \u003csup\u003eAB\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0,048 *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e*P\u0026thinsp;\u0026lt;\u0026thinsp;0.05; **P\u0026thinsp;\u0026lt;\u0026thinsp;0.01; \u003csup\u003e\u0026yen;\u003c/sup\u003e: ANOVA (F). Descriptive statistics are given as \u003cem\u003emean\u003c/em\u003e\u0026thinsp;\u0026plusmn;\u0026thinsp;\u003cem\u003estandard\u003c/em\u003e deviation. \u003cb\u003eA, B\u003c/b\u003e: Different letters or letter combinations in the same row indicate a statistically significant difference (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05); Abbreviations: BMI, body mass index; LH, luteinizing hormone; FSH, follicle-stimulating hormone\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAnalysis of the genotype, allelotype, and haplotype distributions of polymorphisms in the groups revealed that the AA genotype of the FSHR SNP rs6165 polymorphism did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.091). The TA genotype did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.061). The TT genotype did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.449). The allelotype did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.819). The allelotype did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.911).\u003c/p\u003e\u003cp\u003eFor the FSHR SNP rs6166 polymorphisms, the SS genotype did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.144). The NS genotype did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.066). The NN genotype did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.444). The S allele did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.819). The N allele did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.911).\u003c/p\u003e\u003cp\u003eAnalysis of the haplotypes for the two SNPs in question revealed that the AASS haplotype did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.091). The TANS haplotype did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.066). The TTNN haplotype did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.449) (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of FSHR polymorphism genotype frequencies between the groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eThe307Ala (rs6165)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGroup 1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGroup 2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGroup 3\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP \u003csup\u003e\u0026yen;\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9 (%60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (%20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (%20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,091\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4 (%13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14 (%47)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12 (%40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,061\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (%47)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (%20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5 (%33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,449\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAllelotype\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22 (%37)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20 (%33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18 (%30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,819\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18 (%30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20 (%33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22 (%37)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,819\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAsn680Ser (rs6166)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGroup 1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGroup 2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGroup 3\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP \u003csup\u003e\u0026yen;\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9 (%56)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (%19)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (%25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.144\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4 (%14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14 (%50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10 (%36)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.066\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (%44)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (%19)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 (%38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.444\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAllelotype\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22 (%37)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20 (%33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18 (%30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.819\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18 (%30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20 (%33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22 (%37)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.819\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabb\" border=\"1\"\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHaplotype\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGroup 1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGroup 2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGroup 3\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP \u003csup\u003e\u0026yen;\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAASS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9 (%45)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (%15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (%15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.091\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTANN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (%0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (%0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (%5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTANS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4 (%20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14 (%70)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10 (%50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.066\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTASS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (%0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (%0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (%5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTTNN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (%35)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (%15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5 (%25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.449\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e*P\u0026thinsp;\u0026lt;\u0026thinsp;0.05; **P\u0026thinsp;\u0026lt;\u0026thinsp;0.01; \u003csup\u003e1\u003c/sup\u003e: Chi-square test (χ\u003csup\u003e2\u003c/sup\u003e); OR, odds ratio. Descriptive statistics are given as \u003cem\u003enumber (percentage)\u003c/em\u003e values\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFor the ER1 rs2234693 polymorphism, the CC genotype did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.905). The CT genotype did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.607). The TT genotype did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.311). The C allele did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.584). The allelotype did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.662).\u003c/p\u003e\u003cp\u003eFor the ER1 rs9340799 polymorphism, the AA genotype was not significantly different between the groups (p\u0026thinsp;=\u0026thinsp;0.387). The GA genotype did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.670). The GG genotype did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.273). The allelotype did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.476). The G allele did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.353).\u003c/p\u003e\u003cp\u003eAnalysis of the haplotypes for the two SNPs in question revealed that the CCGA haplotype did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.180). The CCGG haplotype was not significantly different between the groups (p\u0026thinsp;=\u0026thinsp;0.317). The CTGA haplotypes did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.961). The TAA haplotype did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.646) (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of ER1 polymorphism genotype frequencies between the groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePVuII (rs2234693)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGroup 1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGroup 2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGroup 3\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP \u003csup\u003e\u0026yen;\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (%30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (%40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (%30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.905\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8 (%25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12 (%38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12 (%38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.607\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9 (%50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (%22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5 (%28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.311\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAllelotype\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14 (%27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20 (%38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18 (%35)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.584\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26 (%38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20 (%29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22 (%32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.662\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabc\" border=\"1\"\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eXbaI (rs9340799)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGroup 1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGroup 2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGroup 3\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP \u003csup\u003e\u0026yen;\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (%35)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (%20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 (%45)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.387\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8 (%27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12 (%40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10 (%33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.670\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (%50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (%40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (%10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.273\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAllelotype\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22 (%31)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20 (%29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28 (%40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.476\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18 (%36)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20 (%40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12 (%24)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.353\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabd\" border=\"1\"\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHaplotype\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGroup 1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGroup 2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGroup 3\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP \u003csup\u003e\u0026yen;\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCC-AA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (%0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (%0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (%100)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCC-GA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (%0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (%80)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (%20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0,180\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCC-GG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (%75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (%0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (%25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0,317\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCT-AA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (%0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (%0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (%100)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCT-GA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8 (%32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8 (%32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 (%36)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0,961\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCT-GG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (%0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (%100)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (%0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTT-AA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (%44)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (%25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5 (%31)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0,646\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTT-GG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (%100)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (%0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (%0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e*P\u0026thinsp;\u0026lt;\u0026thinsp;0.05; **P\u0026thinsp;\u0026lt;\u0026thinsp;0.01; \u003csup\u003e1\u003c/sup\u003e: Chi-square test (χ\u003csup\u003e2\u003c/sup\u003e). Descriptive statistics are given as \u003cem\u003enumber (percentage)\u003c/em\u003e values.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFor the ER2 rs4986938 polymorphism, the AA genotype did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.655). The GA genotype did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.261). The GG genotype did not significantly differ between the groups (P\u0026thinsp;=\u0026thinsp;0.104). The allelotype did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.168). The G allele did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.382).\u003c/p\u003e\u003cp\u003eFor the ER2 rs1256049 polymorphism, the GA genotype did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.178). The GG genotype did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.679). The allelotype did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.178). The G allele did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.840).\u003c/p\u003e\u003cp\u003eAnalysis of the haplotypes for the two SNPs revealed that the AAGG haplotype did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.655). The GAGA haplotype did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.414). TheGAGG haplotype did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.607). The GGGA haplotype did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.180). The GGGG haplotype did not significantly differ between the groups (p\u0026thinsp;=\u0026thinsp;0.311) (Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of ER2 polymorphism genotype frequencies between the groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAluI (rs4986938)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGroup 1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGroup 2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGroup 3\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP \u003csup\u003e\u0026yen;\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (%40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (%0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (%60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.655\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15 (%47)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9 (%28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8 (%25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.261\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (%13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11 (%48)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 (%39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.104\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAllelotype\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19 (%45)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9 (%21)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14 (%33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.168\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21 (%27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e31 (%40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26 (%33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.382\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabe\" border=\"1\"\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRsaI (rs1256049)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGroup 1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGroup 2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGroup 3\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP \u003csup\u003e\u0026yen;\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4 (%36)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6 (%55)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (%9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.178\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16 (%33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14 (%29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19 (%39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.679\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAllelotype\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4 (%36)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6 (%55)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (%9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.178\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e36 (%33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34 (%31)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e39 (%36)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.840\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabf\" border=\"1\"\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHaplotype\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGroup 1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGroup 2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGroup 3\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP \u003csup\u003e\u0026yen;\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAA-GG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (%40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (%0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (%60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.655\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGA-GA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4 (%67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (%33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (%0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.414\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGA-GG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11 (%42)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7 (%27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8 (%31)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.607\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGG-GA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (%0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (%80)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (%20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.180\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGG-GG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (%17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7 (%39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8 (%44)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.311\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e*P\u0026thinsp;\u0026lt;\u0026thinsp;0.05; **P\u0026thinsp;\u0026lt;\u0026thinsp;0.01; \u003csup\u003e1\u003c/sup\u003e: Chi-square test (χ\u003csup\u003e2\u003c/sup\u003e). Descriptive statistics are given as \u003cem\u003enumber (percentage)\u003c/em\u003e values.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe selection of medication for ovulation induction and the adjustment of its dosage are crucial steps in individualizing infertility treatments. Selecting the correct dosage of the medication can help prevent inadequate or exaggerated responses, thereby avoiding issues such as cycle cancellation, which can cost patients time, money, and hope. From a medical perspective, it can reduce wasted efforts that lead to no outcome and help manage complications such as OHSS.\u003c/p\u003e\n\u003cp\u003eCC is one of the most commonly used oral agents for inducing ovulation in infertility associated with PCOS. The CC is a selective estrogen receptor modulator. It has both estrogenic and antiestrogenic properties. The CC acts as a competitive antagonist for 17-beta estradiol in the hypothalamus. Because of the blockade of the estrogen receptor, there are no limitations on the release of GnRH, resulting in increased endogenous FSH release.\u003c/p\u003e\n\u003cp\u003eFSH is crucial in regulating steroidogenesis. It activates folliculogenesis and estrogen synthesis via FSHR (8,9). Owing to this activation, ovulation is achieved in 22% and 52% of patients with daily doses of 50 mg and 100 mg, respectively. Because predicting the lowest effective dose to induce ovulation at the beginning of treatment is challenging, the dose is empirically started at 50 mg/day and increased gradually until ovulation induction is achieved (up to a maximum of 250 mg/day) (1). While the aim is to achieve monofollicular or bifollicular development and ovulation, the rate of an exaggerated response, defined as the development of three or more follicles, with 50 mg/day CC treatment in women with PCOS is reported to be 6% (2).\u003c/p\u003e\n\u003cp\u003eThe FSHR gene contains two significant SNPs that alter two amino acids at the Ala307Thr and Asn680Ser positions on chromosome 2 exon 10. Numerous studies have investigated the effects of these SNPs on gynecological diseases and the effects of different FSHR isoforms on functionality (3).\u003c/p\u003e\n\u003cp\u003eAn examination of the frequency of FSHR polymorphisms in patients with PCOS revealed that it is controversial whether the distribution of polymorphisms in these women is different from that in normo-ovulatory or non-PCOS anovulatory women. Two meta-analyses on this topic reported conflicting results. In the meta-analysis conducted by Chen et al., FSHR polymorphisms were not associated with an increased risk of PCOS, whereas Qui et al. reported that Ala307Thr variant carriers had a decreased sensitivity for PCOS (12,13). Laven et al. reported the frequencies of Ala307Ala, Ala307Thr, Thr307Thr, Asn680Asn, Asn680Ser, and Ser680Ser as 21%, 58%, 25%, 15%, 46%, and 26%, respectively. The frequencies of the polymorphisms evaluated in the present study are consistent with those of Laven et al., and the differences may be related to ethnic factors (12).\u003c/p\u003e\n\u003cp\u003eThere are few studies examining how different FSHR isoforms respond to increased FSH levels with CC use. Valkenburg et al. investigated the impact of FSHR polymorphisms on ovulation induction outcomes in WHO Class 2 anovulatory women. They reported that, compared with other alleles, the Ser680Ser polymorphism resulted in a lower rate of recovery of ovulatory menstrual cycles after ovulation induction treatment with CC. The authors suggested that carriers of the 680Ser allele might have a greater probability of achieving an ongoing pregnancy when subsequently treated with FSH. The association of the FSHR Ser680 allele with higher follicular phase FSH levels and a higher requirement for exogenous FSH during IVF treatments may indicate that the FSHR variant encoded by this allele has a higher threshold for exogenous FSH. Consequently, ovulation induction with CC or exogenous FSH could be influenced by the FSHR genotype (13). In a retrospective study conducted by Overbeek et al., the effects of the Ser680Ser polymorphism on CC resistance in PCOS patients were examined. The study revealed that patients with the Ser/Ser polymorphism were more resistant to clomiphene than to other variants (14). One of the limitations of the present study, which differs from that of Overbeek et al., is that we included anovulatory patients who did not respond to 50 mg/day clomiphene treatment rather than 150 mg/day, which is normally considered clomiphene resistance. However, the fact that the SS polymorphism was the most common variant, with 56% of women who did not respond to 50 mg/day clomiphene, while there was no statistically significant difference between the groups is still remarkable and consistent with the reference study.\u003c/p\u003e\n\u003cp\u003eFactors that can affect the response to CC include age, BMI, the free androgen index, insulin resistance, FSH levels, and the FSHR genotype (14-17). Among these factors, the only factor that is not modifiable is the FSHR polymorphism, and our study is the first to investigate FSHR polymorphisms in patients with an exaggerated response to CC. The results revealed that there was no significant difference in terms of FSHR Ala307Thr (rs6165) and Asn680Ser (rs6166) polymorphism distributions between patients with more than three stages of follicle development, defined as an exaggerated response to CC, and other groups.\u003c/p\u003e\n\u003cp\u003eTo date, over 2000 ER polymorphisms have been identified. Meta-analyses investigating the ER1 polymorphisms XbaI (351 A\u0026gt;C) (rs9340799) and PvuII (397 T\u0026gt;C) (rs2234693), which are encoded on chromosome 7, as well as the ER2 polymorphisms RsaI 1082 G\u0026gt;A (rs1256049) and AluI 1730 A\u0026gt;G (rs4986938), which are encoded on chromosome 14, indicate that these variations are not individually associated with PCOS susceptibility (18-20).\u003c/p\u003e\n\u003cp\u003eThe CC is structurally similar to estrogen. This allows the CC to bind to the nuclear ER in the reproductive system and hypothalamus. Unlike estrogen, CC binds to these receptors for a longer period of time and consequently decreases ER concentrations (1,2). Considering this mechanism of action of the drug, it can be hypothesized that ER polymorphisms may affect drug–receptor binding and alter drug potency. To the best of our knowledge, no other study has investigated the associations between ER polymorphisms and the response to CC. In the present study, no statistically significant difference was found in favour of any of the polymorphisms investigated between patients who developed an exaggerated response to 50 mg/day CC, those who did not develop a response, and those who developed one or two follicles.\u003c/p\u003e\n\u003cp\u003ePCOS is the most common endocrinological abnormality in women of reproductive age and is one of the most frequent causes of infertility etiology. Therefore, it is important to design more effective and individually tailored treatment algorithms for the patients we frequently encounter and treat in daily clinical practice. With a clearer understanding of genetic factors that can predict the response to CC, ovarian hyperstimulation and multiple pregnancies can be prevented, making safeguarding the health of infertile women easier. The results obtained in the present study showed that FSHR, ER1, and ER2 polymorphisms cannot be used to predict ovarian hyperstimulation in response to CC. Further studies with larger patient groups should be conducted to clarify this situation.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003ePCOS: polycystic ovary syndrome\u003c/p\u003e\n\u003cp\u003eCC: clomiphene citrate\u003c/p\u003e\n\u003cp\u003eOHSS: ovarian hyperstimulation syndrome\u003c/p\u003e\n\u003cp\u003eSNP: single-nucleotide polymorphism\u003c/p\u003e\n\u003cp\u003eIVF: in vitro fertilization\u003c/p\u003e\n\u003cp\u003eFSH: follicle-stimulating hormone\u003c/p\u003e\n\u003cp\u003eFSHR: follicle-stimulating hormone receptor\u003c/p\u003e\n\u003cp\u003eER: estrogen receptor\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eG Aktaş: Project development, Data\u0026nbsp;collection, Manuscript writing\u003c/p\u003e\n\u003cp\u003eM Bertizlioğlu: Data collection, Manuscript editing\u003c/p\u003e\n\u003cp\u003eSA Yılmaz: Data analysis, Project development\u003c/p\u003e\n\u003cp\u003eAG Kebapcılar: Data collection, Manuscript editing\u003c/p\u003e\n\u003cp\u003eÖ Seçilmiş: Project development, Manuscript writing\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompliance with\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eethical standards\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFunding: This study was funded by the Selçuk University Scientific Research Project Unit.\u003c/p\u003e\n\u003cp\u003eConflicts of interest: In accordance with the ICMJE uniform disclosure form, all\u0026nbsp;the\u0026nbsp;authors\u0026nbsp;declare that they have no conflicts\u0026nbsp;of interest.\u003c/p\u003e\n\u003cp\u003eAnimal subjects: All\u0026nbsp;the\u0026nbsp;authors confirmed that this study did not involve animal subjects or tissue.\u003c/p\u003e\n\u003cp\u003eHuman subjects: Consent was obtained\u0026nbsp;from\u0026nbsp;or waived by all participants in this study.\u0026nbsp;The Local Ethics Committee of the\u0026nbsp;Selçuk University Faculty of Medicine issued approval 2019/49.\u003c/p\u003e\n\u003cp\u003eFinancial relationships: All\u0026nbsp;the\u0026nbsp;authors\u0026nbsp;declare\u0026nbsp;that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work.\u003c/p\u003e\n\u003cp\u003eOther relationships: All\u0026nbsp;the\u0026nbsp;authors\u0026nbsp;declare\u0026nbsp;that there are no other relationships or activities that could\u0026nbsp;influence\u0026nbsp;the submitted work.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003ePractice Committee of the American Society for Reproductive Medicine Use of clomiphene citrate in infertile women: a committee opinion. Fertil Steril. 2013 Aug;100(2):341-8. doi: 10.1016/j.fertnstert.2013.05.033. Epub 2013 Jun 27.\u003c/li\u003e\n \u003cli\u003eCoughlan C, Fitzgerald J, Milne P, Wingfield M. Is it safe to prescribe clomiphene citrate without ultrasound monitoring facilities? J Obstet Gynaecol. 2010 May;30(4):393-6. doi: 10.3109/01443611003646280.\u003c/li\u003e\n \u003cli\u003eMeduri G, Bachelot A, Cocca MP, Vasseur C, Rodien P, Kuttenn F, Touraine P, Misrahi M (2008) Molecular pathology of the FSH receptor: New insights into FSH physiology. Mol Cellular Endocrinol 282:130\u0026ndash;142. doi:10.1016/j.mce.2007.11.027\u003c/li\u003e\n \u003cli\u003eLussiana C, Guani B, Mari C, Restagno G, Massobrio M, Revelli A (2008) Mutations and polymorphisms of the FSH receptor (FSHR) gene. Clinical implications in female fecundity and molecular biology of FSHR protein and gene. Obstet Gynecol Surv 12:785\u0026ndash;795. doi: 10.1097/OGX.0b013e31818957eb\u003c/li\u003e\n \u003cli\u003eLaven JSE. Follicle Stimulating Hormone Receptor (FSHR) Polymorphisms and Polycystic Ovary Syndrome (PCOS). Front Endocrinol (Lausanne). 2019 Feb 12;10:23. doi: 10.3389/fendo.2019.00023.\u003c/li\u003e\n \u003cli\u003eSimoni M, Tempfer CB, Destenaves B, Fauser BC. Functional genetic polymorphisms and female reproductive disorders: Part I: Polycystic ovary syndrome and ovarian response. Hum Reprod Update. 2008 Sep-Oct;14(5):459-84. doi: 10.1093/humupd/dmn024. Epub 2008 Jul 4.\u003c/li\u003e\n \u003cli\u003ePaschalidou C, Anagnostou E, Mavrogianni D, Raouasnte R, Klimis N, Drakakis P, Loutradis D. The effects of follicle-stimulating hormone receptor (FSHR) -29 and Ser680Asn polymorphisms in IVF/ICSI. Horm Mol Biol Clin Investig. 2020 Mar 2;41(2). doi: 10.1515/hmbci-2019-0058.\u003c/li\u003e\n \u003cli\u003eThe Rotterdam ESHRE/ASRM‐sponsored PCOS consensus workshop group. Revised 2003 consensus on diagnostic criteria and long‐term health risks related to polycystic ovary syndrome (PCOS). Human Reproduction, Volume 19, Issue 1, January 2004, Pages 41\u0026ndash;47, https://doi.org/10.1093/humrep/deh098\u003c/li\u003e\n \u003cli\u003eLessey BA, Metzger DA, Haney AF, McCarty KS Jr (1989) Immunohistochemical analysis of estrogen and progesterone receptors in endometriosis: comparison with normal endometrium during the menstrual cycle and the effect of medical therapy. Fertil Steril 51:409\u0026ndash;415. doi:10.1016/S0015-0282(16)60545-9\u003c/li\u003e\n \u003cli\u003eChen DJ, Ding R, Cao JY, Zhai JX, Zhang JX, Ye DQ. Two folliclestimulating hormone receptor polymorphisms and polycystic ovary syndrome risk: a meta-analysis. Eur Obstet Gynecol Reprod Biol. (2014) 182:27\u0026ndash;32.doi: 10.1016/j.ejogrb.2014.08.014\u003c/li\u003e\n \u003cli\u003eQiu L, Liu J, Hei QM. Association between two polymorphisms of follicle stimulating hormone receptor gene and susceptibility to polycystic ovary syndrome: a meta-analysis. Chin Med Sci J. (2015) 30:44\u0026ndash;50. doi: 10.1016/S1001-9294(15)30008-0\u003c/li\u003e\n \u003cli\u003eLaven JS, Mulders AG, Suryandari DA, Gromoll J, Nieschlag E, Fauser BC, Simoni M. Follicle-stimulating hormone receptor polymorphisms in women with normogonadotropic anovulatory infertility. Fertil Steril. 2003 Oct;80(4):986-92. doi: 10.1016/s0015-0282(03)01115-4.\u003c/li\u003e\n \u003cli\u003eValkenburg O, van Santbrink EJ, K\u0026ouml;nig TE, Themmen AP, Uitterlinden AG, Fauser BC, Lambalk CB, Laven JS. Follicle-stimulating hormone receptor polymorphism affects the outcome of ovulation induction in normogonadotropic (World Health Organization class 2) anovulatory subfertility. Fertil Steril. 2015 Apr;103(4):1081-1088.e3. doi: 10.1016/j.fertnstert.2015.01.002.\u003c/li\u003e\n \u003cli\u003eOverbeek A, Kuijper EA, Hendriks ML, Blankenstein MA, Ketel IJ, Twisk JW, Hompes PG, Homburg R, Lambalk CB. Clomiphene citrate resistance in relation to follicle-stimulating hormone receptor Ser680Ser-polymorphism in polycystic ovary syndrome. Hum Reprod. 2009 Aug;24(8):2007-13. doi: 10.1093/humrep/dep114. Epub 2009 Apr 28.\u003c/li\u003e\n \u003cli\u003eImani B, Eijkemans MJ, te Velde ER, Habbema JD, Fauser BC. Predictors of patients remaining anovulatory during clomiphene citrate induction of ovulation normogonadotropic oligoamenorrheic infertility. J Clin Endocrinol Meta 1998;83:2361 \u0026ndash; 2365. doi: 10.1210/jcem.83.7.4919\u003c/li\u003e\n \u003cli\u003eImani B, Eijkemans MJ, de Jong FH, Payne NN, Bouchard P, Giudice LC, Fauser BC. Free androgen index and leptin are the most prominent endocrine predictors of ovarian response during clomiphene citrate induction of ovulation in normogonadotropic oligoamenorrheic infertility. J Clin Endocrinol Metab 2000;85:676 \u0026ndash; 682. doi: 10.1210/jcem.85.2.6356\u003c/li\u003e\n \u003cli\u003eKurabayashi T, Suzuki M, Fujita K, Murakawa H, Hasegawa I, Tanaka K. Prognostic factors for ovulatory response with clomiphene citrate in polycystic ovary syndrome. Eur J Obstet Gynecol Reprod Biol 2006; 126:201\u0026ndash; 205. doi: 10.1016/j.ejogrb.2005.11.005\u003c/li\u003e\n \u003cli\u003eMotawi TM, El-Rehany MA, Rizk SM, Ramzy MM, El-Roby DM. Genetic Polymorphism of Estrogen Receptor Alpha Gene in Egyptian Women With Type II Diabetes Mellitus. Meta Gene (2015) 6:36\u0026ndash;41. doi: 10.1016/j.mgene.2015.08.001\u003c/li\u003e\n \u003cli\u003eNectaria X, Leandros L, Ioannis G, Agathocles T. The Importance of Er\u0026alpha; and Er\u0026beta; Gene Polymorphisms in PCOS. Gynecol Endocrinol Off J Int Soc Gynecol Endocrinol (2012) 28(7):505\u0026ndash;8. doi: 10.3109/09513590.2011.649811\u003c/li\u003e\n \u003cli\u003eZhou S, Wen S, Sheng Y, Yang M, Shen X, Chen Y, Kang D, Xu L. Association of Estrogen Receptor Genes Polymorphisms With Polycystic Ovary Syndrome: A Systematic Review and Meta-Analysis Based on Observational Studies. Front Endocrinol (Lausanne). 2021 Oct 4;12:726184. doi: 10.3389/fendo.2021.726184\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"polycystic ovary syndrome, clomiphene citrate, follicle-stimulating hormone receptor, ovarian reserve","lastPublishedDoi":"10.21203/rs.3.rs-7160268/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7160268/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective:\u003c/strong\u003e The aim of this study was to evaluate the associations between an exaggerated follicular response to clomiphene citrate (CC) and estrogen and follicle-stimulating hormone (FSH) receptor polymorphisms.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMaterials and Methods:\u003c/strong\u003e A total of 60 patients who were diagnosed with polycystic ovary syndrome (PCOS) and whose first treatment cycle started with 50 mg clomiphene citrate were investigated. Patients were evaluated in three groups: those with \u0026gt;17 mm follicle development (Group 1, n=20), normal responders with one or two \u0026gt;17 mm follicles (Group 2, n=20), and overresponders with three or more \u0026gt;17 mm follicles (Group 3, n=20). The FSHR SNPs rs6165 and rs6166, the ER1 SNPs rs2234693 and rs9340799, and the ER2 SNPs rs1256049 and rs4986938 were genotyped via TaqMan assays.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e When the three different CC response groups were evaluated, no significant differences in genotype, allotype, or haplotype distributions were observed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e A clearer understanding of genetic factors that can predict the response to CC could help prevent ovarian hyperstimulation and multiple pregnancies, thereby safeguarding the health of infertile women. The results of this study showed that FSHR, ER1, and ER2 polymorphisms cannot be used to predict the follicular response to CC treatment.\u003c/p\u003e","manuscriptTitle":"The Association of Exaggerated Folliculer Responses to Clomiphene Citrate With Estrogen and Follicle-stimulating Hormone Receptor Polymorphisms in Women With Polycystic Ovary Syndrome","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-01 11:18:05","doi":"10.21203/rs.3.rs-7160268/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"bcadb01c-4280-4cef-be21-f1a618eb12c9","owner":[],"postedDate":"August 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-10T11:53:36+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-01 11:18:05","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7160268","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7160268","identity":"rs-7160268","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}