Received 2024-12-16

Revised 2025-02-01

Accepted 2025-04-21

Introduction

Polycystic ovary syndrome (PCOS) is a prevalent reproductive endocrine disorder, affecting about five to ten percent of women of reproductive age (Goodarzi et al., 2011). PCOS is a clinical diagnosis based on parameters including obesity, oligomenorrhea or amenorrhea, elevated androgen levels, and impaired ovulation (Akhtar et al., 2005; Apridonidze et al., 2005). Additionally, women with PCOS exhibit reduced aromatase activity, and due to the relative decrease in follicle-stimulating hormone (FSH) output, follicular growth is disrupted, leading to excess androgen accumulation and hyperandrogenism (Nelson et al., 1999). Defects in the steroidogenic pathway and cortisol metabolism cause excessive adrenal androgen production, which affects about thirty percent of women (Goodarzi et al., 2015). Thus, hyperandrogenism appears central to the pathophysiology of PCOS, influencing both its metabolic and reproductive components (Chaudhary et al., 2021), given that theca cells are the primary source of androgens in PCOS (Jakubowicz et al., 1997; Nestler et al., 1998).

In theca cells, excessive androgen biosynthesis in PCOS is linked to upregulated expression of the CYP17A1 gene, specifically steroid-17-α-hydroxylase/17,20-lyase (Wickenheisser et al., 2012). CYP17, a member of the cytochrome P450 family 17, plays a critical role in androgen synthesis and encodes enzyme activities such as 17-α-hydroxylase and 17,20-lyase (Jahromi et al., 2016). CYP17 is expressed in thecal cells, adrenal glands, and Leydig cells (Chua et al., 2011).

A single nucleotide polymorphism (SNP) in the CYP17 gene involves the substitution of thymine (T) with cytosine (C) at 34 bp upstream of the transcription start site in the promoter region (Carey et al., 1994). This may create an additional Sp-1 transcription factor binding site, potentially increasing CYP17 expression (Carey et al., 1993) due to functional changes in SNP-mediated gene regulation (Xing et al., 2022).

Both adrenal glands and ovaries produce androgens, the final products of enzymatic reactions converting cholesterol to dehydroepiandrosterone (DHEA) and androstenedione. Rate-limiting enzymes in these tissues regulate sex steroid synthesis (Wawrzkiewicz et al., 2020). Variations in the activity of these enzymes contribute to phenotypic diversity in androgen levels (de Medeiros et al., 2015). Androgen biosynthesis may also be influenced by mutations in steroidogenic pathway genes, such as CYP1A, CYP3, CYP11, CYP17, CYP19, and CYP21 (de Medeiros et al., 2015; Pigny et al., 2019).

Previous genetic association studies suggest that hereditary factors significantly influence PCOS susceptibility, with multiple genetic variants linked to the disorder (Saddick et al., 2020). Candidate gene studies provide insights into differences between patient and control populations (Douma et al., 2019). However, only a few studies have examined the association between CYP17 polymorphisms and PCOS risk (Chen et al., 2010; Cong et al., 2018; Li et al., 2015).

Anti-Müllerian hormone (AMH), produced by granulosa cells of small ovarian follicles, regulates folliculogenesis (Carlsson et al., 2006; Dumont et al., 2015) and inhibits CYP17, modulating steroidogenesis (Teixeira et al., 1999). Conversely, some studies suggest that elevated AMH levels contribute to ovarian dysfunction (Laven et al., 2004). In PCOS, abnormally high AMH impairs FSH-stimulated follicular development, leading to anovulation (Pigny et al., 2007).

Another hallmark of PCOS is increased GnRH pulsatility, causing hypersecretion of luteinizing hormone (LH), particularly in lean women with oligomenorrhea (Pellatt et al., 2011). A high LH/FSH ratio (often 3:1) is common, with LH levels two- to three-fold higher than FSH. This elevated ratio enhances LH responsiveness to GnRH (Hendriks et al., 2008).

Few studies have explored the relationship between PCOS and CYP17A1 polymorphisms (Munawar Lone et al., 2021; Ashraf et al., 2020), and data from Middle Eastern populations, remain scarce, particularly Iraqi women.

As Middle Eastern populations exhibit unique genetic admixtures and may modulate have different penetrance of CYP17A1 variants compared to Europeans (Bao); Despite the well-documented role of CYP17A1, 3β-HSD, and CYP11A in androgen biosynthesis and their association with PCOS, the ethnic-specific genetic landscape of PCOS, particularly in understudied populations like Iraqi women, remains poorly characterized. By integrating genotype-phenotype correlations in a homogeneous ethnic group, our work not only validates the universality of CYP17A1’s role in PCOS but also tries to seek for population-specific risk patterns.

Materials and Methods

Study Design

This was a case-control study aimed at investigating the association between CYP17A1 gene polymorphism and the risk of polycystic ovary syndrome (PCOS) in Iraqi women. The study was conducted from June 2023 to October 2024 at Baghdad Teaching Hospital, Iraq.

Participants

A total of 140 women (66 PCOS patients and 74 healthy controls), aged 14–49 years, were included. PCOS diagnosis followed the Rotterdam criteria (2003).

Exclusion criteria for PCOS patients included hyperandrogenism due to other conditions, such as 21-hydroxylase deficiency, non-classical adrenal hyperplasia, hyperprolactinemia, or androgen-secreting tumors. Healthy controls were selected from the same hospital’s gynecology department, with no history of PCOS, infertility, or menstrual irregularities.

Clinical and Hormonal Assessment

Clinical and demographic data were collected through physical examinations and structured interviews. Hormonal profiles (LH, FSH, and AMH) were assessed using fasting blood samples collected on days 3–5 of the menstrual cycle (or at any time for participants with amenorrhea), after a 12-hour fast.

Luteinizing hormone (LH) and follicle-stimulating hormone (FSH) levels were quantified using the Maglumi chemiluminescent immunoassay (CLIA) kit, with confirmatory measurements performed on the Beckman Coulter Immunoassay System Access 2.

To ensure the reliability and reproducibility of our assays, both intra-assay and inter-assay coefficients of variation were maintained below 10%.

Genetic Analysis

Genomic DNA was isolated from 5 mL of peripheral blood samples using the ReliaPrep™ Blood DNA Miniprep System (A5081). The CYP17A1 rs743572 polymorphism was genotyped using the established PCR-RFLP method (Azziz, 2006).

This method was selected for its enhanced sensitivity in detecting genetic variants, a critical factor in genetic association studies.

PCR Reaction Components

The 25 μL PCR reaction mixture contained: 50 ng of genomic DNA extracted from participant blood samples; 10 μM each of forward (5ʹ-CATTCGCACTCTGGAGTC-3ʹ) and reverse (5ʹ-AGGCTCTTGGGGTACTTG-3ʹ) primers; Nuclease-free water to adjust the final volume; 2× GoTaq® Green Master Mix (M712, Promega, USA), which includes Taq DNA polymerase, dNTPs, and reaction buffer.

The circumstances of the thermal cycling for PCR amplification were as follows: Initial denaturation at 95°C for 3 min to ensure that the DNA template was fully denatured.

This was followed by 30 cycles of amplification, each consisting of: DNA strand separation through denaturation at 94°C for 46 s, 46 s of annealing at 55°C, and a one-minute extension at 72°C. Afterward, the PCR results were loaded into a 2% agarose gel and incubated at 72°C for 5 additional minutes to complete the extension step.

Next, the results were mixed with the restriction enzyme MspA1. The digested products were subsequently separated using a 2% agarose gel, and finally, the two profiles were visualized under ultraviolet light following staining with a suitable DNA dye.

Genotypes were defined according to the sizes of the fragments detected: The TT genotype was detected as two bands, one of 290 base pairs (bp) and the other of 124 bp. In the CC genotype, only one band was observed at 414 bp, since it lacked the restriction enzyme recognition site. Genotypes CT and TT generated three bands (414 bp, 290 bp, 124 bp), indicating heterozygosity.

Using this approach, the genotypic distributions of the CYP17A1 polymorphism (rs743572) in the study population could be accurately assessed, allowing for evaluation of any potential association with the risk of developing PCOS among the Iraqi women included in this research.

Figure-1 shows the CYP17A1 gene location on chromosome 10. Data on the samples were collected until October 2023, after which the genetic predisposition was determined, and the significance of associations between the gene polymorphism and the clinical outcomes of the studied patients were evaluated.

Statistical Analysis

The data analysis in this study was conducted using IBM SPSS Statistics version 22 (Armonk, New York, USA) and GraphPad Prism 10. Independent t-tests and Mann-Whitney U tests were used for comparing continuous variables, with the choice of test depending on the data distribution. Logistic regression models, both adjusted and unadjusted, were utilized to determine odds ratios (OR) and 95% confidence intervals (CI) for the association between CYP17A1 genotypes and the risk of Polycystic Ovary Syndrome (PCOS). Furthermore, the genotypic distributions in both groups were assessed for deviation from Hardy-Weinberg equilibrium to evaluate the validity of the genetic analysis.

Ethical Approval and Consent

All participants provided written informed consent before being enrolled in the study. Ethical approval was obtained from college of Health and Medical Technology /University of Al-Turath (CSEC/1019/0004).

Results

Phenotypic and Anthropometric Features

Significant differences (P<0.01) were observed in multiple parameters between the PCOS and control groups, including body mass index (BMI, kg/m²), anti-Müllerian hormone (AMH), luteinizing hormone (LH), follicle-stimulating hormone (FSH), and the LH/FSH ratio. Detailed results are presented in Table-1.

The analysis revealed statistically significant differences between patients and controls for several variables. Both the t-test and Mann-Whitney U test showed no significant age difference between groups (P=0.155 and P=0.129, respectively), with patients having a mean age of 27.59 years (SD=3.54) compared to 26.77 years (SD=3.01) in controls. However, BMI differed significantly (t-test: P=0.000021; Mann-Whitney U test: P=0.000147), with patients exhibiting a higher mean BMI (25.38 ± 3.07) than controls (23.55 ± 1.38).

LH levels were significantly elevated in patients compared to controls (t-test: P<0.0001; Mann-Whitney U test: P<0.0001), with mean values of 12.61 (SD=2.71) versus 6.80 (SD=3.25), respectively. F

SH levels also differed significantly (t-test: P=0.000346; Mann-Whitney U test: P=0.000017), with patients showing lower mean FSH levels (5.88 ± 3.23) compared to controls (7.57±1.87).

The LH/FSH ratio was significantly higher in patients (t-test: P<0.0001; Mann-Whitney U test: P<0.0001), with a mean of 2.71 (SD=1.3) versus 0.97 (SD=0.57) in controls. AMH levels were also markedly elevated in patients (9.24±1.97) compared to controls (4.03±0.94), with both tests confirming high significance (P<0.0001).

Further statistical analysis confirmed significant differences between patients and controls for key variables. Age did not differ significantly (t-test: P=0.15; Mann-Whitney U test: P=0.13), with mean ages of 27.59 (SD=3.54) and 26.77 (SD=3.01) years, respectively. However, BMI was significantly higher in patients (25.38±3.07 vs. 23.55±1.38; t-test: P=0.000021; Mann-Whitney U test: P=0.000147).

LH levels were substantially higher in patients (12.61±2.71 vs. 6.80±3.25; both tests: P<0.0001), whereas FSH levels were lower (5.88±3.23 vs. 7.57±1.87; t-test: P=0.000346; Mann-Whitney U test: P=0.000017). AMH levels were significantly elevated in patients (9.24±1.97 vs. 4.03±0.94; both tests: P<0.0001).

Genotypic Frequency Distribution

The analysis revealed differences in the distribution of gene polymorphism frequencies between patient and control groups, using the CC polymorphism as the reference. The CC polymorphism was found in 43.9% of patients (29/66) and 62.2% of controls (46/74). This polymorphism served as the baseline reference (OR=1.00), as shown in Table-2.

For the TT vs. CC comparison, the TT polymorphism was present in 19.7% of patients (13/66) and 8.1% of controls (6/74). The unadjusted (crude) OR for TT was 3.44 (95% CI: 1.18–13.31, P=0.04), indicating that patients were 3.44 times more likely to carry the TT polymorphism than controls, a statistically significant association. After adjusting for confounding factors (age and BMI), the adjusted OR increased to 3.97 time (P=0.03), further supporting a significant independent association between the TT polymorphism and patient status.

For the CT vs. CC comparison, the CT polymorphism was observed in 36.4% of patients (24/66) and 29.7% of controls (22/74). The crude OR for CT was 1.73 (95% CI: 0.84–4.19, P=0.19), suggesting a higher but non-significant prevalence of CT in patients compared to controls. After adjustment, the OR remained non-significant (adjusted OR=1.87, P=0.113), reinforcing that while CT polymorphism may be more frequent in patients, the association lacks statistical significance after accounting for age and BMI.

Discussion

PCOS is among the most widespread endocrine disorders in females. Obesity is one of the key predisposing risk factors contributing to PCOS development (Rahimi & Mohammadi, 2019). Our study found a highly significant difference in BMI between patients and controls, supporting this association. A study by Legro (2012) reported that obesity correlates with hypothalamic-pituitary-ovarian dysfunction, promoting PCOS development. Increased obesity leads to elevated androgen production, further stimulating luteinizing hormone (LH) and contributing to hyperandrogenism (Güngör et al., 2023).

Our findings align with previous studies (Glueck & Goldenberg, 2019; Güngör et al., 2023; Al-Lami et al., 2020), which also reported significant BMI differences between PCOS patients and controls. Regarding LH levels, our study observed a highly significant increase in PCOS patients compared to controls, consistent with other research (Güngör et al., 2023; Al-Lami et al., 2020; Munawar et al., 2021). While most PCOS patients exhibit elevated LH levels, some show no significant changes in LH, FSH, or the LH/FSH ratio yet still meet diagnostic criteria. Typically, women with PCOS have higher serum LH concentrations (Ashraf et al., 2020), attributed to episodic LH secretion and increased pulse frequency.

Additionally, elevated LH may result from heightened gonadotropin-releasing hormone (GnRH) secretion or pituitary hypersensitivity to GnRH due to abnormal ovarian feedback (Malini & George, 2018).Our study also revealed a highly significant elevation in anti-Müllerian hormone (AMH) levels in PCOS patients, consistent with prior research (Güngör et al., 2023; Hassan, 2010; Jabr & Al-Hakeim, 2015). The rise in AMH levels in PCOS is linked to increased AMH production per follicular unit and the presence of small antral follicles, making it a potential diagnostic marker for PCOS or polycystic ovarian morphology (PCOM) (Liu et al., 2019).

We assessed the association between different CYP17A1 genotypes (CT and TT) and PCOS risk, using the CC genotype as the reference. Both crude (unadjusted) and adjusted (for age and BMI) odds ratios were analyzed. The TT genotype showed a significant association with PCOS in both analyses, suggesting that individuals with this genotype may have a higher PCOS risk than those with the CC genotype.

This association implies that the TT polymorphism may upregulate CYP17A1 gene expression, leading to excessive androgen production—a hallmark of PCOS-related hyperandrogenism. These findings support previous studies identifying elevated androgen levels as a key factor in PCOS pathogenesis (Goodarzi et al., 2015). The rs743572 polymorphism, located in the CYP17A1 promoter region, introduces an additional Sp-1 transcription factor binding site when T replaces C (Carey et al., 1994).

This may result in enhanced transcription of the CYP17A1 gene, leading to excessive androgen production, a key feature of PCOS. The TT genotype showed the strongest association with PCOS risk, supporting our hypothesis. A meta-analysis of 10 studies (CT vs CC genotypes) reported an odds ratio=2.25 (CI=1.338-3.778; P=0.002), indicating the CT genotype had 2.25-fold higher risk than CC. These findings agree with studies in other populations (Liu et al., 2021; Ashraf et al., 2020).

Our study found a significant association between the TT genotype of rs743572 and PCOS risk, consistent with (Hoyos et al., 2020). Unlike some Asian population studies that reported stronger association with the CT genotype (Li et al., 2015), we found no statistically significant PCOS risk with the CT genotype. This suggests CYP17A1 rs743572 genotyping could help identify high-risk women, particularly TT genotype carriers. Early identification may enable personalized management strategies, including lifestyle interventions or anti-androgen therapies.

Another meta-analysis confirmed the TT genotype's significant association with higher PCOS risk, particularly under dominant and codominant models, supporting our findings (Albedairy et al., 2024).

Studies on Iraqi women also reported higher TT genotype frequency in PCOS patients (Hoyos et al., 2020). Furthermore, genetic studies in North Indian and Iranian populations demonstrated strong links between TT genotype and PCOS, further validating our results (Liu et al., 2021).

BMI is a known risk factor for PCOS. Here, we controlled for BMI to isolate the effect of genotypes on PCOS risk. The adjusted odds ratio for BMI (1.38) confirms it as an independent risk factor, with each unit increase in BMI associated with 1.38-fold higher PCOS risk. After adjusting for BMI and age, the TT genotype remained significantly associated with PCOS, indicating its risk effect is independent of these factors. This further supports the role of genetic susceptibility in PCOS pathogenesis.

While BMI confounds the relationship between genotype and PCOS risk, our analysis accounts for BMI, allowing us to assess the direct association between genotypes and PCOS. Our findings align with existing literature demonstrating strong links between elevated BMI and PCOS prevalence. Notably, studies consistently show that higher BMI exacerbates PCOS-related reproductive and metabolic dysfunction. For instance, cross-sectional studies report that obesity worsens both reproductive abnormalities (e.g., menstrual dysfunction, hyperandrogenism) and metabolic complications (e.g., insulin resistance, dyslipidemia) (Heidarzadehpilehrood et al., 2022; Gill et al., 2023).

Genetic evidence further supports our results. Genome-wide association studies (GWAS) reveal that PCOS-associated genetic variants have stronger effects in individuals with higher BMI (Ma et al., 2021). This highlights the critical interplay between genetic predisposition and obesity in driving PCOS development and severity, consistent with our conclusions.

Age is also considered a risk factor for PCOS. In our analysis, the adjusted odds ratio for age (1.05, P=0.427) suggests a minimal, non-significant contribution to PCOS risk after accounting for genotype and BMI. While age itself shows limited independent impact on PCOS risk in this dataset, adjusting for it helps isolate genotype-specific effects.

The crude (unadjusted) odds ratios reflect the genotype-PCOS relationship without accounting for BMI or age. This unadjusted approach does not control for BMI’s influence on PCOS risk, meaning observed associations may partly reflect BMI differences across genotypes. In contrast, the adjusted analysis isolates the genotype effect by controlling for BMI and age.

For example, the adjusted odds ratio of 2.2 (95% CI: 1.5–3.1) for overweight vs. normal weight individuals (Table-2) indicates that both genotype and BMI contribute to PCOS risk in the studied population.

These methodological considerations align with existing literature. For instance, a study used Mendelian randomization to assess BMI’s causal role in PCOS, emphasizing that BMI-adjusted analyses are essential for accurate genetic risk estimation (Burns et al., 2024).

Similarly, a study on PCOS-endometrial cancer links highlighted how multivariate adjustment (e.g., for age/BMI) clarifies associations amidst statistical uncertainty (Zhao et al., 2020). Such approaches ensure robust genetic risk estimates, reinforcing that adjusted odds ratios and confidence intervals are critical in PCOS research (Lu et al., 2023; Boldis et al., 2024).

Conclusion

This study reveals variations in key anthropometric and hormonal parameters between PCOS patients and controls. Patients with PCOS exhibited higher BMI, higher LH, reduced FSH, and markedly increased AMH levels compared to controls.

Genetic analysis revealed a significant association between the TT genotype and increased PCOS risk, with nearly fourfold higher odds versus the CC genotype. Conversely, the CT genotype showed a non-significant trend toward higher risk, which disappeared after adjustment. These results contribute to growing evidence on PCOS genetics and highlight CYP17A1's potential as a predictive marker.

Acknowledgments

We highly appreciate many members of the Baghdad teaching hospital in medical city

For their helping in the collecting samples.

Conflict of Interest

The authors declare no conflict of interests.

GMJ Copyright© 2025, Galen Medical Journal. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/) Email:gmj@salviapub.com

 Correspondence to: Saleh Ali Alqadoori, Department of Medical Laboratory Techniques, Balad Technical Institute, Middle Technical University, Baghdad, Iraq. Telephone Number: +9647704218786 Email Address: Salehali@mtu.edu.iq

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Table 1. Comparison of Clinical and Hormonal Variables between PCOS Patients and Healthy Controls.

Variable	Patient Mean ± SD	Control Mean ± SD	T-Test P-Value	MannWhitney U P-Value
Age (years)	27.59 ± (3.54)	26.77 ± (3.01)	0.15	0.13
BMI (kg/m2 )	25.38 ± (3.07)	23.55 ± (1.38)	0.01*	0.01*
LH	12.61 ± (2.71)	6.80 ± (3.25)	0.01*	0.01*
FSH	5.88 ± (3.23)	7.57 ± (1.87)	0.01*	0.01*
LH/ FSH	2.71± (1.3)	0.97 ± 0.57	0.01*	0.01*
AMH	9.24 ± (1.97)	4.03 ± (0.94)	0.01*	0.01*

BMI: body mass index; FSH: follicle stimulating hormone; LH: luteinizing hormone. LH/ FSH ratio, AMH: Anti-Müllerian hormone. *The logistic regression test was applied, and “statistical significance was set at P-value <0.05”

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Table 2. Determination of CYP17A1 (rs743572) Association with PCOS Patients and Controls using Different Genetic Models

CYP17A1 (rs743572)	Control	PCOS	Crude Odds Ratio	Adjusted #Odds Ratio	Adjusted Lower 95% CI	Adjusted Upper 95% CI	Crude P-value	Adjusted P-value
CC	46 (62.16%)	29 (43.94%)	1.0	1.0	-	-	-	-
CT	22 (29.73%)	24 (36.36%)	1.73	1.87	0.84	4.19	0.19	0.13
TT	6 (8.11%)	13 (19.70%)	3.44	3.97	1.18	13.31	0.04*	0.03*

# adjusted based on the age and BMI. *The logistic regression test was applied, and statistical significance was set at P-value <0.05

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References

1. Ajmal N, Khan SZ, Shaikh R. Polycystic ovary syndrome (PCOS) and genetic predisposition: A review article. European journal of obstetrics & gynecology and reproductive biology: X. 2019 Jul 1;3:100060.
2. Akhtar MK, Kelly SL, Kaderbhai MA. Cytochrome b5 modulation of 17α hydroxylase and 17–20 lyase (CYP17) activities in steroidogenesis. Journal of Endocrinology. 2005 Nov 1;187(2):267-74.
3. Albedairy I H, Aljawad M F, AL-Shammari J M, Alshareefi A F. The CYP17A1 single-nucleotide polymorphism rs743572 in . Iraqi polycystic ovary syndrome patients. 2024;1:8.
4. Al-Lami HB, Al-Tu'ma FJ, Al-Safi WG. Association between anti-Müllerian hormone and other biomarkers with ovarian function in polycystic ovarian syndrome of Iraqi women. Journal of Contemporary Medical Sciences. 2020 Jul 1;6(4): .
5. Apridonidze T, Essah PA, Iuorno MJ, Nestler JE. Prevalence and characteristics of the metabolic syndrome in women with polycystic ovary syndrome. The Journal of Clinical Endocrinology & Metabolism. 2005 Apr 1;90(4):1929-35.
6. Ashraf S, Rasool SU, Nabi M, Ganie MA, Jabeen F, Rashid F, Amin S. CYP17 gene polymorphic sequence variation is associated with hyperandrogenism in Kashmiri women with polycystic ovarian syndrome. Gynecological Endocrinology. 2021 Mar 4;37(3):230-4.
7. Azziz R. Diagnosis of polycystic ovarian syndrome: the Rotterdam criteria are premature. The Journal of Clinical Endocrinology & Metabolism. 2006 Mar 1;91(3):781-5.
8. Bao X, Ding H, Xu Y, Cui G, He Y, Yu X, Wang DW. Prevalence of common mutations in the CYP17A1 gene in Chinese Han population. Clinica chimica acta. 2011 Jun 11;412(13-14):1240-3.
9. Boldis BV, Grünberger I, Cederström A, Björk J, Nilsson A, Helgertz J. Comorbidities in women with polycystic ovary syndrome: a sibling study. BMC Women's Health. 2024 Apr 5;24(1):221.
10. Burns K, Mullin BH, Moolhuijsen LM, Laisk T, Tyrmi JS, Cui J, Actkins KE, Louwers YV, Estonian Biobank Research Team Metspalu Andres Milani Lili Esko Tõnu Nelis Mari Hudjashov Georgi, Davis LK, Dudbridge F. Body mass index stratified meta-analysis of genome-wide association studies of polycystic ovary syndrome in women of European ancestry. BMC genomics. 2024 Feb 26;25(1):208.
11. Carey AH, Chan KL, Short F, White D, Williamson R, Franks S. Evidence for a single gene effect causing polycystic ovaries and male pattern baldness. Clinical endocrinology. 1993 Jun;38(6):653-8.
12. Carey AH, Waterworth D, Patel K, White D, Little J, Novelli P, Franks S, Williamson R. Polycystic ovaries and premature male pattern baldness are associated with one allele of the steroid metabolism gene CYP17. Human molecular genetics. 1994 Oct 1;3(10):1873-6.
13. Carlsson IB, Scott JE, Visser JA, Ritvos O, Themmen AP, Hovatta O. Anti-Müllerian hormone inhibits initiation of growth of human primordial ovarian follicles in vitro. Human reproduction. 2006 Sep 1;21(9):2223-7.
14. Chaudhary H, Patel J, Jain NK, Joshi R. The role of polymorphism in various potential genes on polycystic ovary syndrome susceptibility and pathogenesis. Journal of ovarian research. 2021 Sep 26;14(1):125.
15. Chua A K, Azziz R, Goodarzi M O. Association study of CYP17 and HSD11B1 in polycystic ovary syndrome utilizing comprehensive gene coverage. MHR: Basic science of reproductive medicine. (2012);18(6): 320-324.
16. Chen Y, Pei J. Factors influencing the association between CYP17 T34C polymorphism and the risk of breast cancer: meta-regression and subgroup analysis. Breast Cancer Research and Treatment. 2010 Jul;122:471-81.
17. Cong L, Fu Q, Gao T. CYP17A1 rs743572 polymorphism might contribute to endometriosis susceptibility: evidences from a case–control study. Medicine. 2018 Jul 1;97(28):e11415.
18. de Medeiros SF, Barbosa JS, Yamamoto MM. Comparison of steroidogenic pathways among normoandrogenic and hyperandrogenic polycystic ovary syndrome patients and normal cycling women. Journal of Obstetrics and Gynaecology Research. 2015 Feb;41(2):254-63.
19. Douma Z, Lautier C, Haydar S, Mahjoub T, Grigorescu F. Portability of GWAS results between ethnic populations: genetic markers for polycystic ovary syndrome (PCOS) in mediterranean area. Acta Endocrinologica (Bucharest). 2019 Jul;15(3):364.
20. Dumont A, Robin G, Catteau-Jonard S, Dewailly D. Role of Anti-Müllerian Hormone in pathophysiology, diagnosis and treatment of Polycystic Ovary Syndrome: a review. Reproductive Biology and Endocrinology. 2015 Dec;13:1-0.
21. Gill L, Coborn JE, Hoovler AR, Sherif K. Polycystic ovary syndrome and obesity: a cross-sectional survey of patients and obstetricians/gynecologists. Journal of Women's Health. 2023 Jun 1;32(6):723-31.
22. Glueck CJ, Goldenberg N. Characteristics of obesity in polycystic ovary syndrome: Etiology, treatment, and genetics. Metabolism. 2019 Mar 1;92:108-20.
23. Goodarzi MO, Carmina E, Azziz R. Dhea, dheas and pcos. The Journal of steroid biochemistry and molecular biology. 2015 Jan 1;145:213-25.
24. Goodarzi MO, Dumesic DA, Chazenbalk G, Azziz R. Polycystic ovary syndrome: etiology, pathogenesis and diagnosis. Nature reviews endocrinology. 2011 Apr;7(4):219-31.
25. Güngör ND, Güngör K, Celik N, Önal M, Madenli AA. Impact of body mass index and vitamin D on serum AMH levels and antral follicle count in PCOS. Eur Rev Med Pharmacol Sci. 2023 Jan 1;27:179-87.
26. Hassan B F. Measuring the concentration of some hormones in patients sera of polycystic ovaries. Baghdad Science Journal. (2010); 7(4): 1384-1388.
27. Heidarzadehpilehrood R, Pirhoushiaran M, Abdollahzadeh R, Binti Osman M, Sakinah M, Nordin N, Abdul Hamid H. A review on CYP11A1, CYP17A1, and CYP19A1 polymorphism studies: candidate susceptibility genes for polycystic ovary syndrome (PCOS) and infertility. Genes. 2022 Feb 5;13(2):302.
28. Hendriks ML, Brouwer J, Hompes PG, Homburg R, Lambalk CB. LH as a diagnostic criterion for polycystic ovary syndrome in patients with WHO II oligo/amenorrhoea. Reproductive biomedicine online. 2008 Jan 1;16(6):765-71.
29. Hoyos LR, Visser JA, McLuskey A, Chazenbalk GD, Grogan TR, Dumesic DA. Loss of anti-Müllerian hormone (AMH) immunoactivity due to a homozygous AMH gene variant rs10417628 in a woman with classical polycystic ovary syndrome (PCOS). Human Reproduction. 2020 Oct;35(10):2294-302.-Jabr, I. M., & Al-Hakeim, H. K. (2015). Relation of Antimullarian Hormone with other Hormones in Women with Polycystic Ovary Syndrome. Al-Kufa University Journal for Biology, 7(1)
30. Jahromi MS, Tehrani FR, Noroozzadeh M, Zarkesh M, Ghasemi A, Zadeh-Vakili A. Elevated expression of steroidogenesis pathway genes; CYP17, GATA6 and StAR in prenatally androgenized rats. Gene. 2016 Nov 15;593(1):167-71.
31. Jakubowicz DJ, Nestler JE. 17α-Hydroxyprogesterone responses to leuprolide and serum androgens in obese women with and without polycystic ovary syndrome after dietary weight loss. The Journal of Clinical Endocrinology & Metabolism. 1997 Feb 1;82(2):556-60.
32. Laven JS, Mulders AG, Visser JA, Themmen AP, De Jong FH, Fauser BC. Anti-Mullerian hormone serum concentrations in normoovulatory and anovulatory women of reproductive age. The Journal of Clinical Endocrinology & Metabolism. 2004 Jan 1;89(1):318-23.
33. Legro R S. Obesity and PCOS: implications for diagnosis and treatment In Seminars in reproductive medicine. Thieme Medical Publishers. 2012;30(6):496-506.
34. Li L, Gu ZP, Bo QM, Wang D, Yang XS, Cai GH. Association of CYP17A1 gene-34T/C polymorphism with polycystic ovary syndrome in Han Chinese population. Gynecological Endocrinology. 2015 Jan 2;31(1):40-3.
35. Liu X, Xu M, Qian M, Yang L. CYP17 T/C (rs74357) gene polymorphism contributes to polycystic ovary syndrome susceptibility: evidence from a meta-analysis. Endocrine Connections. 2021 Dec 1;10(12):R305-16.
36. Liu XY, Yang YJ, Tang CL, Wang K, Chen JJ, Teng XM, Ruan YC, Yang JZ. Elevation of antimüllerian hormone in women with polycystic ovary syndrome undergoing assisted reproduction: effect of insulin. Fertility and sterility. 2019 Jan 1;111(1):157-67.
37. Lu L, Luo J, Deng J, Huang C, Li C. Polycystic ovary syndrome is associated with a higher risk of premalignant and malignant endometrial polyps in premenopausal women: a retrospective study in a tertiary teaching hospital. BMC Women's Health. 2023 Mar 24;23(1):127.
38. Ma R, Zou Y, Wang W, Zheng Q, Feng Y, Dong H, Tan Z, Zeng X, Zhao Y, Deng Y, Wang Y. Obesity management in polycystic ovary syndrome: disparity in knowledge between obstetrician-gynecologists and reproductive endocrinologists in China. BMC Endocrine Disorders. 2021 Dec;21:1-0.
39. Malini NA, George KR. Evaluation of different ranges of LH: FSH ratios in polycystic ovarian syndrome (PCOS)–Clinical based case control study. General and comparative endocrinology. 2018 May 1;260:51-7.-Munawar Lone, N., Babar, S., Sultan, S., Malik, S., Nazeer, K., & Riaz, S. (2021). Association of the CYP17 and CYP19 gene polymorphisms in women with polycystic ovary syndrome from Punjab, Pakistan. Gynecological Endocrinology, 37(5), 456-461.
40. Nelson VL, Legro RS, Strauss III JF, McAllister JM. Augmented androgen production is a stable steroidogenic phenotype of propagated theca cells from polycystic ovaries. Molecular endocrinology. 1999 Jun 1;13(6):946-57.
41. Nestler JE, Jakubowicz DJ, Falcon de Vargas A, Brik C, Quintero N, Medina F. Insulin stimulates testosterone biosynthesis by human thecal cells from women with polycystic ovary syndrome by activating its own receptor and using inositolglycan mediators as the signal transduction system. The Journal of Clinical Endocrinology & Metabolism. 1998 Jun 1;83(6):2001-5.
42. Pellatt L, Rice S, Dilaver N, Heshri A, Galea R, Brincat M, Brown K, Simpson ER, Mason HD. Anti-Müllerian hormone reduces follicle sensitivity to follicle-stimulating hormone in human granulosa cells. Fertility and sterility. 2011 Nov 1;96(5):1246-51.
43. Pigny P, Jonard S, Robert Y, Dewailly D. Serum anti-Mullerian hormone as a surrogate for antral follicle count for definition of the polycystic ovary syndrome. The Journal of Clinical Endocrinology & Metabolism. (2006) ; 91(3): 941-945.
44. Rahimi Z. The CYP17 MSP AI (T-34C) and CYP19A1 (Trp39Arg) variants in polycystic ovary syndrome: A case-control study. International Journal of Reproductive BioMedicine. 2019 May 29;17(3):201.
45. Saddick S Y. Identifying genes associated with the development of human polycystic ovary syndrome. Saudi Journal of Biological Sciences. (2020); 27(5): 1271-1279.
46. Teixeira J, Fynn-Thompson E, Payne AH, Donahoe PK. Mullerian-inhibiting substance regulates androgen synthesis at the transcriptional level. Endocrinology. 1999 Oct 1;140(10):4732-8.
47. Wawrzkiewicz-Jałowiecka A, Kowalczyk K, Trybek P, Jarosz T, Radosz P, Setlak M, Madej P. In search of new therapeutics—molecular aspects of the PCOS pathophysiology: genetics, hormones, metabolism and beyond. International Journal of Molecular Sciences. 2020 Sep 25;21(19):7054.
48. Wickenheisser JK, Biegler JM, Nelson-DeGrave VL, Legro RS, Strauss III JF, McAllister JM. Cholesterol side-chain cleavage gene expression in theca cells: augmented transcriptional regulation and mRNA stability in polycystic ovary syndrome. PloS one. 2012 Nov 14;7(11):e48963.
49. Xing C, Zhao H, Zhang J, He B. The association of CYP17A1, CYP19A1, and SHBG gene polymorphisms in polycystic ovary syndrome susceptibility: a systematic review and meta-analysis. Frontiers in Physiology. 2022 May 9;13:741285.
50. Zhao Y, Xu Y, Wang X, Xu L, Chen J, Gao C, Wu C, Pan D, Zhang Q, Zhou J, Chen R. Body mass index and polycystic ovary syndrome: a 2-sample bidirectional Mendelian randomization study. The Journal of Clinical Endocrinology & Metabolism. 2020 Jun;105(6):1778-84.

CYP17A1 Polymorphism in Iraqi women with PCOS

Alqadoori SA, et al.

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Alqadoori SA, et al.

CYP17A1 Polymorphism in Iraqi women with PCOS

10	GMJ.2024;13:e3746 www.gmj.ir