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Obesity is associated with SHBG levels rather than blood lipid profiles in PCOS patients with insulin resistance

BMC Endocrine Disorders volume 24, Article number: 254 (2024) Cite this article

Abstract

Objective

Polycystic ovary syndrome (PCOS) is a prevalent endocrine disorder characterized by hormonal imbalances and insulin resistance (IR). Among the metabolic abnormalities associated with PCOS, obesity is often present concurrently. Nevertheless, the correlation between obesity, sex hormone levels, and blood lipid profiles in PCOS patients with IR remains uncertain.

Methods

This is a cross-sectional study including a total of 206 Chinese women diagnosed with PCOS, enrolled between March 2016 and December 2021. The participants’ anthropometric measurements, such as weight, height, waist circumference, and hip circumference, were recorded. Additionally, fasting blood samples were collected to measure various parameters, including fasting glucose, insulin levels, lipid profiles, and sex hormone levels.

Results

Our findings highlight that obesity exhibited a significant correlation with lower levels of sex hormone binding globulin (SHBG) and elevated levels of free androgen index (FAI), fasting insulin, and HOMA-IR in PCOS patients diagnosed with IR. However, no significant association between obesity and blood lipid profiles was observed within this particular group of women.

Conclusion

This study suggests that among PCOS patients with IR, lower levels of SHBG and higher levels of FAI are associated with obesity. These findings indicate that SHBG and FAI may have the potential to serve as a biomarker for the initial identification and prognosis of IR in PCOS patients.

Trial registration

Retrospectively registered on 25/04/2020 at ClinicalTrials.gov Identifer: NCT04264832.

Peer Review reports

Introduction

Polycystic ovary syndrome (PCOS) is the most prevalent endocrine disorder affecting women, with a prevalence ranging from 5 to 20% in the female population [1]. It is commonly observed in reproductive-age women, with an estimated prevalence of up to 15% [2]. Alongside gynecological manifestations and hyperandrogenism, PCOS is often accompanied by metabolic abnormalities, including obesity, dyslipidemia, hyperinsulinemia, and insulin resistance (IR). Approximately 40–80% of women with PCOS experience IR, even in the absence of obesity, and around 40–50% of women with PCOS are clinically obese [3, 4]. Furthermore, patients with PCOS who have a familial history of diabetes and hypertension often display unfavorable endocrine and metabolic profiles [5]. It is noteworthy that there exists a robust correlation between IR and obesity [6]. While some studies suggest that obesity may worsen the clinical presentation of PCOS [7, 8], the precise role of obesity in the development of PCOS pathogenesis remains unclear.

IR has consistently been identified as a common feature of PCOS, particularly among individuals with obesity [9]. However, it is important to note that the presence of IR is frequently observed in most obese women, leading to conflicting findings in the literature [6]. Some studies indicate a connection between IR and obesity in PCOS patients, while others report no significant correlation [10, 11]. Additionally, obesity has been identified as a potential trigger for IR [12]. Although previous studies suggest a potential association between IR and cholesterol levels in PCOS [13], the nature of this relationship remains uncertain.

The underlying causes of PCOS primarily involve hyperandrogenemia and IR. However, using total testosterone levels as a predictor of infertility in women with PCOS can be misleading, as total testosterone does not fully reflect the biologically active testosterone [14]. Only a small fraction of testosterone circulates freely, while another portion binds to sex hormone binding globulin (SHBG) and serum albumin. Therefore, it is the free testosterone that represents the truly active androgen [15]. Previous research indicates that measuring the SHBG-bound free androgen index (FAI) may serve as a more accurate diagnostic marker for distinguishing hyperandrogenemia in PCOS patients compared to total plasma testosterone and bioavailable testosterone [16].

In this study, we aimed to investigate the association between obesity, lipid profiles, and sex hormone in PCOS patients with IR. Through comprehensive analyses, we may gain a deeper understanding of the intricate interplay between them within our study population.

Methods

Participants

Between March 2016 and December 2021, a total of 206 women diagnosed with PCOS were recruited for this study. Among them, 148 were identified as insulin resistant, while 58 age-matched non-insulin resistant women served as a comparison group. These participants were selected from the clinical department and health center of Peking University Third Hospital in Beijing, China. The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of Peking University Third Hospital.

Inclusion and exclusion criteria

Inclusion criteria: women diagnosed with PCOS according to the Rotterdam criteria 2003 [17] with at least two of the following symptoms; infrequent ovulation or anovulation; hyperandrogenism or clinical manifestations of high blood androgen; ultrasound findings of polycystic ovaries in one or two ovaries, or ≥ 12 follicles measuring 2–9 mm in diameter, and/or ovarian volume ≥ 10 mL. Age between 18 and 40 years.

Exclusion criteria: individuals were excluded from the study if they had other endocrine disorders, such as androgen-secreting tumors, suspected Cushing’s syndrome, non-classic congenital adrenal hyperplasia (17-hydroxyprogesterone < 3 nmol/L), thyroid dysfunction (thyroid stimulating hormone ≥ 4.78 mIU/ml), hyperprolactinemia (fasting prolactin < 26 ng/ml), type I diabetes or poorly controlled type II diabetes, stage 2 hypertension (resting blood pressure ≥ 160/100 mmHg), psychiatric diagnoses, or were using psychiatric medications including antidepressants. Additionally, participants who had received any pharmacological treatment within the past 12 weeks (such as cortisone, antidepressants, antidiabetic medications including insulin and acarbose, hormonal contraceptives, hormonal ovulation induction, or other drugs deemed at the discretion of the investigator) were also excluded from the study.

Anthropometry measurements

All participants underwent a medical examination including measurements of body weight and height. Body weight and height were measured with an ultrasonic scale (SY-300), with a precision of 0.1 kg and 1 cm, respectively. Body mass index (BMI) was calculated as the weight in kilograms divided by the square of height in meters (kg/m2). According to the literature, a BMI value greater than 30 is recognized as indicative of obesity, whereas a BMI lower than this threshold is classified as non-obese [18]. Specifically, a BMI between 25 and 30 is deemed as overweight, and a BMI below 25 is considered as normal weight.

Biochemical analysis

Peripheral blood samples were obtained from all study participants after overnight fasting using a standard venipuncture technique for hormonal and metabolic assessments. Metabolic profiles assessed were fasting plasma glucose (FPG) and fasting insulin (FINS). Homeostasis model assessment of IR (HOMA-IR) was calculated by using the formula: [FINS (µU/mL) × FPG (mmol/L)]/22.5; and homeostasis model assessment of β-cell function (HOMA-β) was calculated by using the formula: [FINS (µU/mL) × 20]/[FPG (mmol/L) − 3.5] [19]. According to the literature, a HOMA-IR value greater than 2.69 is considered indicative of IR, while a value below this threshold is not [20]. Hormonal profiles including SHBG (nmol/L), serum follicle-stimulating hormone (FSH, mIU/mL), luteinizing hormone (LH, mIU/ mL), estrogen (E2, pmol/L), prolactin (PRL, ng/mL), total testosterone (T, nmol/L), and androstenedione (A2, nmol/L), blood lipid profiles including total cholesterol (mmol/L), triglyceride (mmol/L), high-density lipoprotein (HDL, mmol/L), and low-density lipoprotein (LDL, mmol/L) were measured by Siemens Immulite 2000 immunoassay system (Siemens Healthcare Diagnostics, Siemens, Germany). FAI was calculated as the ratio of total testosterone level to SHBG values [21].

Statistical analyses

The normality of continuous variables was assessed using the Kolmogorov-Smirnov test and histograms. Continuous variables are presented as mean ± standard deviation (SD). Two-sided t-tests were used to compare normally distributed variables between the obesity and non-obesity groups, while the Wilcoxon rank sum test was used for non-normally distributed variables. A p-value less than 0.05 is considered statistically significant.

Results

Characteristics of included patients with PCOS

Table 1 shows the characteristics of 206 patients diagnosed with PCOS, comprising 86 individuals who are obese and 120 individuals who are non-obese. Among them, 148 patients are classified as IR, while 58 patients are classified as non-IR. BMI tends to be higher in patients with PCOS who have IR compared to those who do not have IR (30.3 ± 4.2 vs. 27.9 ± 3.0, P < 0.001). Obese patients with PCOS exhibit higher levels of HOMA-IR (6.4 ± 4.9 vs. 3.9 ± 1.9 and 2.5 ± 0.7, P < 0.001) and FINS (24.9 ± 16.8 vs. 16.3 ± 6.6 and 11.3 ± 3.2 mU/L, P < 0.001) compared to non-obese patients. PCOS patients with IR tend to have higher levels of total cholesterol (4.8 ± 0.8 vs. 4.4 ± 0.7 mmol/L, P < 0.01), triglycerides (2.0 ± 1.4 vs. 1.3 ± 0.7 mmol/L, P < 0.001), and LDL (3.2 ± 0.6 vs. 2.9 ± 0.7 mmol/L, P < 0.01), as well as lower levels of HDL (1.1 ± 0.2 vs. 1.3 ± 0.3 mmol/L, P < 0.001).

Table 1 Characteristics of included patients with PCOS
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Association among serum SHBG levels, obesity, and IR in PCOS

We found that obese PCOS patients have lower levels of SHBG compared to overweight and normal weight PCOS patients (19.9 ± 9.4 vs. 26.9 ± 14.7 and 34.6 ± 7.3 nmol/L, P < 0.001, Fig. 1A). Additionally, PCOS patients with IR also have lower levels of SHBG compared to non-IR patients (23.0 ± 14.0 vs. 28.5 ± 9.0 nmol/L, P < 0.001, Fig. 1B). Both obese PCOS patients and PCOS patients with IR tend to have higher FAI (Table 1). In the PCOS population with IR, obese patients have lower levels of SHBG (Fig. 1C). In the non-IR PCOS population, it is noteworthy that, although no statistically significant difference in SHBG levels is observed between obese individuals and those who are overweight, a notable difference emerges when comparing obese patients to those of normal weight (Fig. 1D).

Fig. 1
figure 1

Association between serum levels of SHBG and obesity in PCOS patients with IR. (A) The relationship between obesity and SHBG in PCOS. (B) The relationship between IR and SHBG in PCOS. (C-D) The relationship between obesity and SHBG in PCOS patients with or without IR. ***p < 0.001; ****p < 0.0001; ns, no statistically significant

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Obesity is associated with insulin-related indexes in PCOS accompanied by IR

In PCOS patients with IR, obese individuals have higher levels of FINS and HOMA-IR compared to non-obese individuals. However, in PCOS patients without IR, no such differences were found (Fig. 2A-D). Additionally, no correlation between HOMA-β and body weight is found in both IR and non-IR groups (Fig. 2E-F). In the PCOS population with IR, there were no significant differences observed in total cholesterol, triglycerides, HDL, and LDL levels between obese and non-obese patients (Fig. 3A-D). Similarly, in PCOS patients with IR, the presence or absence of obesity does not affect the levels of E2, LH, PRL, FSH, A2, and T (Fig. 4A-F).

Fig. 2
figure 2

Association between obesity and insulin-related indexes in PCOS patients with IR. (A-B) The relationship between obesity and FINS in PCOS patients with or without IR. (C-D) The relationship between obesity and HOMA-IR in PCOS patients with or without IR. (E-F) The relationship between obesity and HOMA-β in PCOS patients with or without IR. **p < 0.01; ****p < 0.0001; ns, no statistically significant

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Fig. 3
figure 3

Association between obesity and blood lipid profiles in PCOS patients. (A) The relationship between obesity and total cholesterol. (B) The relationship between obesity and triglycerides. (C) The relationship between obesity and HDL. (D) The relationship between obesity and LDL. ns, no statistically significant

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Fig. 4
figure 4

Association between obesity and sex hormonal profiles in PCOS patients. (A) The relationship between obesity and E2 levels. (B) The relationship between obesity and LH levels. (C) The relationship between obesity and PRL levels. (D) The relationship between obesity and FSH levels. (E) The relationship between obesity and A2 levels. (F) The relationship between obesity and T levels. ns, no statistically significant

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BMI is associated with serum levels of SHBG and FAI in PCOS accompanied by IR

In PCOS patients with IR, we conducted linear regression analysis between BMI and SHBG, FAI, FINS, and HOMA-IR. We found that in this population, the levels of SHBG in the blood were negatively correlated with BMI (R2 = 0.1, P < 0.001; Fig. 5A), while FAI, FINS, and HOMA-IR were positively correlated with BMI (R2 = 0.11, P < 0.001; R2 = 0.25, P < 0.001; R2 = 0.24, P < 0.001; respectively; Fig. 5B-D). The results from the Receiver Operating Characteristic (ROC) curve analysis revealed that the area under the ROC curve for SHBG was 0.716, while the area under the ROC curve for FAI was 0.665, indicating that both SHBG and FAI exhibited significant diagnostic potential for identifying patients with PCOS and coexisting IR (Fig. 6).

Fig. 5
figure 5

BMI had a negative correlation with SHBG levels in PCOS patients with IR. (A) The correlation between BMI and SHBG levels. (B) The correlation between BMI and FAI. (C) The correlation between BMI and FINS levels. (D) The correlation between BMI and HOMA-IR

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Fig. 6
figure 6

The ROC curves for SHBG and FAI. (A) The ROC curve for diagnosing PCOS with IR using SHBG. (B) The ROC curve for diagnosing PCOS with IR using FAI

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Discussion

Our study revealed that in patients with PCOS who also had IR, obesity exhibited a correlation with lower levels of SHBG and higher levels of FAI, but did not show a significant association with lipid levels or sex hormone levels. These findings imply that SHBG or FAI could serve as an independent predictor of IR in obese PCOS patients. Therefore, this variable holds the potential to serve as an early diagnostic and prognostic indicator of IR in PCOS patients. These results are consistent with the findings reported by Veltman-Verhulst et al., which further emphasize that low levels of SHBG, rather than lipid profiles, possess predictive significance in metabolic complications, such as gestational diabetes, among patients with PCOS [22].

IR, primarily caused by impaired insulin secretion, is notably more pronounced in obese patients with PCOS, resulting in decreased insulin sensitivity. Our study demonstrated that FINS, and HOMA-IR were significantly higher in the obese subgroup among PCOS patients with IR. These findings align with previous literature reports [16, 19]. IR is considered a central mechanism in both obese and non-obese individuals with PCOS. Previous research has suggested a link between the severity of hyperinsulinemia in PCOS patients and the degree of clinical obesity manifestations [23], although the precise mechanism of IR in the context of obesity and PCOS remains unclear. Furthermore, our results are in line with those reported by Mousa et al., who indicated that, despite the prevalence of dyslipidemia in PCOS, specific lipid markers do not always exhibit a strong correlation with IR when assessed alongside established metabolic risk factors [24]. This reinforces the idea that SHBG may be a more pertinent indicator than traditional lipid markers for assessing metabolic risk in this patient population. Our findings further bolster the perspective that SHBG could serve as a biomarker for metabolic risk, particularly in PCOS patients who also have obesity and IR.

Obesity is the result of an excessive intake of energy, which leads to the accumulation of adipose tissue [25]. In obesity, the visceral adipose tissue releases various factors that contribute to increased IR, such as non-esterified fatty acids, glycerol, hormones, and pro-inflammatory cytokines [26]. Abnormalities in insulin action, dysfunction of insulin receptors, and excessive glucose production in the liver are potential mechanisms underlying obesity [27]. Obesity is a common characteristic observed in individuals with PCOS [28]. The reduced secretion of lipocalin in the adipose tissue of women with PCOS may contribute to abnormal adipose tissue function [29]. Moreover, recent studies have associated obesity with chronic low-grade inflammation, where inflammatory adipocytokines like tumor necrosis factor-α, high-sensitivity C-reactive protein, and interleukin have been implicated in IR observed in PCOS [30]. During the pathogenesis of PCOS, altered expression patterns of various adipokines are observed. Specifically, there is an upregulation of adipokines such as leptin, chemerin, and resistin, whereas adiponectin levels are downregulated [31, 32]. Adiponectin, which plays a crucial role in obesity and IR, exerts its metabolic influence on PCOS by modulating energy balance and related metabolic processes [33]. These alterations collectively contribute to the complex metabolic dysregulation observed in PCOS, amplifying the deleterious effects of obesity and IR.

SHBG, a liver-derived glycoprotein, plays a crucial role in binding and transporting testosterone and estradiol in the bloodstream. Its specific interaction with steroid hormones is essential for regulating their availability. In normal circumstances, only a small fraction of testosterone remains unbound and biologically active, as the majority forms inactive testosterone by binding with SHBG [34]. In patients with PCOS who also have IR and obesity, various factors such as hyperinsulinemia, fatty liver, and reduced estrogen levels hinder the hepatic synthesis of SHBG. Consequently, lower concentrations of SHBG are present in the blood, leading to the release of inactive androgens from their bound state. This results in an increased abundance of free and active androgens, contributing to the characteristic hyperandrogenemia observed in PCOS. Our study aligns with previous research and confirms that low levels of SHBG in the serum serve as a valuable biomarker for identifying IR [35]. Furthermore, these observations hold clinical relevance for PCOS patients, especially those exhibiting early metabolic disorders associated with obesity [36].

Hyperlipidemia, characterized by elevated levels of plasma cholesterol and/or triglycerides, often occurs in obese individuals [37]. In contrast to the findings of studies like Chen et al., which highlight a link between IR and dyslipidemia in PCOS populations [10], our study observed weaker correlations between obesity and related indicators in PCOS patients, such as serum cholesterol. The underlying reasons for this phenomenon are likely to be multifaceted and complex. Although poor diet and exercise habits commonly contribute to obesity, its causes can also be influenced by various factors, including genetics, environment, and endocrine factors [38]. It is worth noting that not all obese individuals will necessarily experience hyperlipidemia, particularly when considering factors such as PCOS and IR [39].

Hyperandrogenism is both a significant clinical manifestation and a key underlying mechanism in patients with PCOS. It is widely recognized that hyperinsulinemia resulting from IR plays a crucial role in the development of hyperandrogenism in PCOS patients [17]. In PCOS patients with IR, there is an upregulation of serine phosphorylation of the insulin receptor, leading to the inhibition of insulin receptor tyrosine kinase activity [40]. This alteration affects the activity of the P450c17 enzyme, leading to excess androgen levels in females with PCOS. Furthermore, hyperinsulinemia stimulates the secretion of LH, further increasing the production of ovarian androgens [41]. It is worth noting that hyperinsulinemia not only stimulates ovarian steroidogenesis but also suppresses SHBG production in the liver, which partially explains the mechanism by which IR leads to a decrease in SHBG levels [42]. This decrease in SHBG levels may be associated with an elevated availability of free androgens in the bloodstream [43]. Despite the well-documented relationship between hyperandrogenism, IR, and reduced SHBG in PCOS, as discussed by Maliqueo et al. [44], our study provides further insight by emphasizing that obesity independently exacerbates SHBG reduction in this population. This observation indicates a synergistic effect of obesity on SHBG levels, especially among those with IR, which may ultimately lead to increased free androgen levels and exacerbate the hyperandrogenic symptoms that are hallmark of PCOS.

Estrogen, as the primary sex hormone in women, plays a crucial role in various aspects of PCOS, and extensive research has been conducted on this topic [45]. Estrogens and their receptors have been found to regulate diverse aspects of glucose and lipid metabolism in women. While the decrease in estrogen levels during menopause is strongly associated with an increase in obesity, the precise role of estrogen in regulating IR and body weight in PCOS patients remains unclear [46]. This study did not find a significant correlation between obesity and estradiol levels in PCOS patients with IR. Various factors, including androgens, insulin, lipid metabolism, and glucose metabolism, may contribute to this outcome. It has been observed that women with PCOS often have lower serum estradiol levels compared to healthy women [47]. This reduction in estradiol levels may be linked to abnormalities in hypothalamic-pituitary function or reduced ovarian secretion capacity [48].

The primary focus of this study is to investigate the relationship between obesity, IR, and SHBG in PCOS. One potential explanation for this relationship is that increased lipogenesis disrupts the expression of the SHBG gene by affecting the levels of hepatic nuclear factor-4α (HNF-4α), which in turn leads to IR [49]. A multicenter longitudinal study provides support for the hypothesis that reduced SHBG synthesis plays a more significant role in IR among women with higher levels of hepatic fat [50]. In a study comparing women with and without PCOS, it was observed that insulin sensitivity decreases with higher body weight, and this decline is independently associated with lower levels of SHBG [51]. However, the causal relationship between obesity and IR has not yet been fully understood. Additionally, IR can result in hyperglycemia, and elevated glucose levels can subsequently reduce the expression of HNF-4α in the liver, thereby decreasing SHBG expression [52]. This may partially explain the findings of our study.

This study has several limitations. Firstly, the observation of the association between SHBG, IR, and obesity in PCOS is mainly based on the data from cross-sectional studies, and the causal relationship between them is not yet clear. Secondly, the sample size of this study is relatively small, and there are several confounding factors present, which may potentially impact the results. Additionally, the severity of IR was not assessed using the gold standard euglycemic hyperinsulinemic clamp technique. Therefore, it is important to exercise caution when interpreting the findings. Furthermore, several insulin-related indicators were not measured, highlighting the need for improvement in future research.

Conclusion

In summary, our study established a strong association between obesity and reduced SHBG levels or increased FAI levels among PCOS patients with IR, thus indicating the potential utility of SHBG or FAI as a biomarker for initial identification and prognosis of IR in obese PCOS patients. These results further confirm the interplay between decreased SHBG levels, increased FAI levels, hyperandrogenism, and metabolic abnormalities commonly observed in PCOS. Understanding the underlying mechanisms of this association may facilitate the development of targeted therapeutic strategies for managing PCOS. Further investigation is warranted to elucidate the intricate interactions among SHBG, hyperandrogenism, and metabolic dysfunction in PCOS.

Data availability

The data supporting these study findings are available upon reasonable request from the corresponding author.

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Acknowledgements

Not applicable.

Funding

This work was supported by the Capital’s Funds for Health Improvement and Research (2022-2-4098), National Natural Science Foundation of China (82174151), Peking University Third Hospital “Key Young Talents” Training Program (BYSYFY2021032), CAMS Innovation Fund for Medical Sciences (2019-I2M-5-001) and the National Key Research and Development Project of China (2022YFC2702500).

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Author notes

  1. Haolin Zhang and Weiyu Qiu contributed equally are considered co-first authors.

Authors and Affiliations

  1. Department of Traditional Chinese Medicine, Peking University Third Hospital, Beijing, China

    Haolin Zhang, Ziting Chen, Yang Yang, Yonghao Lu, Lifei Zhou & Yang Ye

  2. Center for Reproductive Medicine, Department of Obstetrics and Gynaecology, Peking University Third Hospital, Beijing, China

    Haolin Zhang, Ping Zhou, Li Shi, Ming Cheng & Rong Li

  3. The Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, China

    Weiyu Qiu

  4. Research Centre of Clinical Epidemiology, Peking University Third Hospital, Beijing, China

    Hua Zhang

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  1. Haolin Zhang
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Contributions

Conceptualization: Haolin Zhang, Weiyu Qiu, Yang Ye, Rong Li. Methodology: Haolin Zhang, Weiyu Qiu, Yang Ye. Formal analysis: Ping Zhou, Li Shi, Ziting Chen, Yang Yang. Investigation: Yonghao Lu, Lifei Zhou, Hua Zhang, Ming Cheng, Yang Ye. Funding acquisition and Supervision: Haolin Zhang, Rong Li. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Yang Ye or Rong Li.

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This study protocol was reviewed and approved by the Ethics Committee of Peking University Third Hospital (PKU3-IRB-2016-212-02). Written informed consent was obtained from all subjects involved in the study.

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Zhang, H., Qiu, W., Zhou, P. et al. Obesity is associated with SHBG levels rather than blood lipid profiles in PCOS patients with insulin resistance. BMC Endocr Disord 24, 254 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12902-024-01789-w

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Keywords

BMC Endocrine Disorders

ISSN: 1472-6823

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