Endocrine Traits During Pregnancy in Women with Polycystic Ovary Syndrome - Insights from a Prospective Cohort Study in China

doi:10.21203/rs.3.rs-3748838/v1

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Endocrine Traits During Pregnancy in Women with Polycystic Ovary Syndrome - Insights from a Prospective Cohort Study in China

https://doi.org/10.21203/rs.3.rs-3748838/v1

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Background

Polycystic ovary syndrome (PCOS) poses a significant endocrine-metabolic health concern. During pregnancy, PCOS-related endocrine and metabolic disorders are likely to worsen, leading to adverse maternal and fetal health outcomes. Despite existing studies, there is a lack of prospective research focused on Chinese populations. It is imperative to establish a cohort of Chinese women with PCOS to investigate pregnancy-related endocrine traits, providing valuable insights into maternal and neonatal outcomes specific to this demographic.

Methods

A total of 91 participants (33 PCOS, 58 non-PCOS) were enrolled in this study. Thorough evaluations of endocrine metabolic parameters were conducted at 12–16 weeks, 24–28 weeks, and 32–36 weeks of gestation. Primary outcome: Total testosterone (T), hormone binding protein (SHBG), free androgen index (FAI). Secondary outcome: Fasting insulin (FINS), fasting plasma glucose (FPG), triglyceride (TG), total cholesterol (TC), low-density lipoprotein (LDL) and high-density lipoprotein (HDL). Logistic regression models were employed for group comparisons and confounder control.

Results

PCOS women exhibited higher T and FAI levels compared to non-PCOS women across all gestational windows (All P < 0.001), even after adjusting for factors including pre-pregnancy BMI. PCOS women exhibited elevated FINS levels and homeostasis model assessment-insulin resistance (HOMA-IR) at 12–16 weeks of gestation, as well as higher FINS levels at 32–36 weeks of gestation. Upon adjusting for factors including pre-pregnancy BMI, the initial differences in glucose metabolism dissipated. PCOS women displayed a subtle departure in lipid metabolism, manifesting solely as decreased levels of HDL at 12–16 weeks of gestation (P = 0.046).

Conclusion

This investigation sheds light on the intricate metabolic landscape of PCOS during pregnancy, characterized by persistent testosterone elevation and altered glucose metabolism. Elevated pre-pregnancy BMI played a crucial role in exacerbating altered glucose metabolism, rather than elevated androgens. The findings offer a nuanced insight into the interplay between PCOS, pregnancy, and metabolic dynamics, enriching our understanding of this multifaceted relationship.

polycystic ovary syndrome

prospective cohort

endocrine traits

pregnancy

Polycystic ovary syndrome (PCOS) is one of the most common public health issues and is characterized by ovulatory dysfunction, hyperandrogenism, and polycystic ovarian change (1, 2). In addition to reduced fertility, women with PCOS exhibit metabolic syndrome features, including insulin resistance (IR), obesity, nonalcoholic fatty liver disease, and type II diabetes (3, 4). Human and animal experiments have shown that IR and compensatory hyperinsulinemia can act on the ovary and adrenal gland, promote androgen synthesis and secretion, and change the pulse of luteinizing hormone (LH), leading to follicular development disorder (5–8). The interaction and vicious cycle of the above endocrine and metabolic disorders is probably the pathophysiological basis of PCOS.

During periods when pregnancy is not occurring, the endocrine and metabolic irregularities seen in individuals with PCOS predominantly exhibit deviations in androgen levels, glucose metabolism, and lipid metabolism (3).

During pregnancy, the maternal endocrine system must undergo a sequence of physiological adjustments to accommodate the demands of fetal growth and development. These adaptations, including physiological hyperinsulinemia and hyperlipidemia, as reported in studies(9), inevitably serve to exacerbate the pre-existing metabolic disturbances observed in patients with PCOS.

Women with PCOS face an elevated risk of pregnancy complications, including Gestational Diabetes Mellitus (GDM), Pregnancy-Induced Hypertension (PIH), Pre-eclampsia (PE), miscarriage, and preterm birth (10, 11). Current evidence suggests that the distinctive endocrine and metabolic dysregulation within the maternal profile of PCOS patients significantly contributes to these complications (12). Furthermore, Barker pointed out that the intrauterine environment in the early stage of life would have a long-term influence on adult health, broadly known as the “developmental origins of health and disease” or DOHaD (13). The endocrine and metabolic disorders of PCOS during pregnancy are likely to affect the growth and development of the offspring. Nevertheless, it is important to note that while there are relevant studies, most of them are retrospective. Furthermore, there is a notable scarcity of research specifically conducted on Chinese populations in this context.

Consequently, it is necessary to construct a prospective cohort of Chinese women with PCOS to investigate the endocrine traits during pregnancy in individuals diagnosed with PCOS.

Study design and participants

This study was a single-center prospective cohort study conducted at the West China Second University Hospital of Sichuan University, wherein participants were enlisted between the months of January 2019 through August 2019. The ethical approval for this study was granted by the Ethics Committee of China Clinical Trial Registration Center (ChiECRCT20190022). The study adhered to the principles outlined in the Declaration of Helsinki and followed the guidelines set forth by the STROBE statement. Informed consent was acquired from all individuals taking part in the study.

Due to the relatively small number of pregnant women with PCOS, the inclusion of the non-PCOS group took a 1:2 concurrent control strategy (1PCOS:2 non-PCOS). Women in the first trimester of pregnancy aged 18–40 years were eligible for inclusion. The diagnosis of PCOS was made according to the 2003 Rotterdam criteria.(2) Pregnant women were excluded from the study if they suffered from diabetes, known liver or kidney failure, severe cardiovascular disease or respiratory disease, known malignant tumor, known cognitive impairment or serious mental illness (i.e., severe anxiety, severe depression), known alcohol or drug misuse, or could not be followed up during the prenatal period.

Baseline information

Baseline information including demographics was collected at participant enrollment. Pregnancy follow-up was conducted according to the time of each outpatient obstetric examination from the time the subjects were included to the time of delivery. During the follow-up period from delivery to 12 weeks postpartum, telephone follow-up was conducted every two weeks. The neonatal information of this study was collected at delivery, including macrosomia (newborn birthweight > 4000 g); small for gestational age (SGA), i.e., birth weight below the 10th percentile for sex-specific gestational age; fetal death (after week 20); placental weight; birth weight; birth length; offspring sex; and Apgar score. The ratio of birth weight/placental weight (BW/PW) and neonatal body mass index (pondal index, PI) were calculated as follows: BW/PW = birth weight of newborn (g)/placental weight (g), which was used to judge the adaptability of the placenta to fetal growth needs; PI = 100 * neonatal birth weight (g)/neonatal birth length (cm) ³.

Maternal endocrinal and metabolic markers

The peripheral blood tests were performed at 12–16 weeks, 24–28 weeks, and 32–36 weeks of gestation and included total testosterone (T), sex hormone binding protein (SHBG), fasting insulin (FINS), fasting plasma glucose (FPG), triglyceride (TG), total cholesterol (TC), low-density lipoprotein (LDL) and high-density lipoprotein (HDL). Homeostasis model assessment - insulin resistance (HOMA-IR) and free androgen index (FAI) were calculated: HOMA-IR = fasting blood glucose (mmol/L) * fasting insulin (µIU/mL)/22.5; FAI = total testosterone (ng/ml) * 100/sex hormone aggregate protein (nmol/L)/0.288. Siemens ADVIA Centaur (Siemens Medical Solutions Diagnostics, Tarrytown, NY, USA) was used for the measurement of the above parameters, and the coefficients of variation within and between groups were less than 4% (Table S1).

Sample size calculation

Hyperandrogenism is the most significant endocrine and metabolic characteristic of PCOS. Excessive intrauterine androgen exposure is considered to be related to various adverse health outcomes (14–20). Therefore, we calculated the sample size according to the T level during pregnancy(21). Based on two independent samples t tests (α = 0.025, 1- β = 0.80, 1:2 design), the effective sample size was 24 PCOS:48 non-PCOS.

Statistical analyses

Continuous data are presented as the mean (standard deviation) for normally or approximately normally distributed data and as the median (first quartile, third quartile) for nonnormally distributed data. Categorical data are presented as percentages. Descriptive statistics were analyzed between groups by the independent samples t test and the Mann–Whitney U test (if data were nonnormally distributed). Pearson’s chi-square test was applied for categorical data with Fisher's exact test for expected frequencies < 5. Unconditional logistic regression models were used for group comparison and confounders controlling.

All statistical data were analyzed using the software packages R (http://www.R-project.org, The R Foundation) and Empower (R) (www.empowerstats.com; X&Y Solutions, Inc., Boston, MA). A two-tailed P value < 0.05 was considered statistically significant.

From January 2019 to August 2019, a total of 99 (33 PCOS, 66 non-PCOS) women aged 18–40 with confirmed intrauterine singleton pregnancies (8–10 weeks of gestation) were enrolled at the West China Second University Hospital of Sichuan University following the predetermined sample size outlined in the research protocol. Throughout the follow-up period, eight individuals (0 PCOS, 8 non-PCOS) were lost to follow-up as they transferred to another hospital for labor. Consequently, peripheral blood samples and metabolic parameter assessments during pregnancy were eventually conducted on 33 PCOS patients and 58 non-PCOS individuals.

Baseline characteristics

Baseline characteristics of the study population are presented in Table 1. Pre-pregnancy BMI was significantly different between the groups, with the non-PCOS group having a mean BMI of 20.21 ± 1.97 kg/m2, and the PCOS group having a higher mean BMI of 21.84 ± 3.11 kg/m2 (P = 0.003*). Regarding age distribution, no statistically significant difference was observed between the two groups (P = 0.174). The majority of participants in both groups were aged between 25 and 30 years. In terms of education level, there was no significant difference between groups (P = 0.519). Most participants in both groups had a bachelor's degree. Menstrual disorder and ovulation induction were significantly more prevalent in the PCOS group compared to the non-PCOS group (P < 0.001* for both). IVF utilization did not show a significant difference between the groups (P = 0.664).

Table 1

The baseline characters of the participants
	Control	PCOS	P-value
	(N = 58)	(N = 33)	P-value
Pre-pregnancy BMI, kg/m²	20.21 ± 1.97	21.84 ± 3.11	0.003*
Age, years			0.174
<=25	1 (1.72%)	3 (9.09%)
> 25, <=30	32 (55.17%)	19 (57.58%)
> 30, <=35	24 (41.38%)	9 (27.27%)
> 35	1 (1.72%)	2 (6.06%)
Education Level:			0.519
High School and Below	1 (1.72%)	2 (6.06%)
College Diploma	8 (13.79%)	7 (21.21%)
Bachelor's Degree	39 (67.24%)	19 (57.58%)
Master's Degree and Above	10 (17.24%)	5 (15.15%)
Menstrual disorder	1 (1.72%)	28 (84.85%)	< 0.001*
Ovulation induction	1 (1.72%)	14 (42.42%)	< 0.001*
IVF	3 (5.17%)	3 (9.09%)	0.664
Spontaneous premature delivery	3 (5.17%)	0 (0%)	-
Gestational days, days	274.33 ± 12.68	276.21 ± 5.79	0.423
Weight gain during pregnancy, kg	12.63 ± 3.56	12.07 ± 4.12	0.493
Birth length, cm	49.24 ± 2.19	49.48 ± 1.39	0.916
Birth weight, g	3184.14 ± 486.59	3284.97 ± 372.99	0.306
Neonatal PI, g/cm3	2.65 ± 0.23	2.70 ± 0.18	0.244
Placental weight, g	555.33 ± 68.84	578.88 ± 104.37	0.202
BW/PW	5.76 ± 0.82	5.75 ± 0.75	0.939
Macrosomia	1 (1.72%)	1 (3.03%)	> 0.999
Term low birth weight	2 (3.45%)	1 (3.03%)	> 0.999
Any Apgar score < = 7	0 (0%)	0 (0%)	-
The continuous variables were presented as "mean ± standard deviation" (normally or approximate normal distributed) / "median (quartile)" (non-normally distributed) and analyzed by t-test / non-parametric test. Categorical variables were expressed as "quantity (percentage)", and analyzed by chi-square test / Fisher's exact.
* represents a statistical difference

There were no cases of spontaneous premature delivery in the non-PCOS group, while 28 cases were observed in the PCOS group. Gestational days, weight gain during pregnancy, birth length, birth weight, neonatal PI, placental weight, BW/PW ratio, macrosomia, term low birth weight, and any Apgar score < = 7 did not show significant differences between the two groups.

In summary, the baseline characteristics demonstrate significant differences in pre-pregnancy BMI, menstrual disorder, and ovulation induction between the control and PCOS groups. Other demographic and pregnancy-related variables showed no significant differences, suggesting overall comparability between the groups in these aspects.

Endocrine metabolic information

In androgen-related indicators, at 12–16 weeks of gestation, T in the PCOS group was higher than that in the non-PCOS group (0.89 ± 0.30 vs. 0.59 ± 0.19 ng/ml, P < 0.001). With the increase in gestational weeks, PCOS patients maintained higher T levels than those in the non-PCOS group at 24–28 weeks of gestation (0.95 ± 0.38 vs. 0.69 ± 0.28 ng/ml, P < 0.001) and 32–36 weeks of gestation (1.00 ± 0.40 vs. 0.69 ± 0.30 ng/ml, P < 0.001). Similarly, PCOS women had a higher level of FAI than the non-PCOS group in all three detection windows (12–16 weeks of gestation, P < 0.001; 24–28 weeks of gestation, P = 0.002; 32–36 weeks of gestation, P < 0.001). (Table 2, Fig. 1)

Table 2

The endocrine metabolic information of the participants
	Control	PCOS	P-value
	(N = 58)	(N = 33)	Unadjust ^#0	Adjust 1 ^#1	Adjust 2 ^#2
T_1, ng/mL	0.59 ± 0.19	0.89 ± 0.30	< 0.001*	< 0.001*	< 0.001*
T_2, ng/mL	0.69 ± 0.28	0.95 ± 0.38	< 0.001*	0.001*	0.004*
T_3, ng/mL	0.69 ± 0.30	1.00 ± 0.40	< 0.001*	< 0.001*	< 0.001*
SHBG_1, nmol/L	413.9 ± 113.5	366.9 ± 99.0	0.05	0.056	0.307
SHBG_2, nmol/L	450.0 ± 102.9	434.3 ± 110.5	0.51	0.657	0.823
SHBG_3, nmol/L	502.9 ± 166.8	474.7 ± 133.0	0.418	0.5	0.852
FAI_1	0.53 ± 0.23	0.84 (0.58–1.01)	< 0.001*	< 0.001*	< 0.001*
FAI_2	0.56 ± 0.27	0.82 ± 0.41	< 0.001*	0.002*	0.014*
FAI_3	0.48 (0.32–0.65)	0.68 (0.48–0.90)	< 0.001*	0.024*	0.071
FINS_1, µIU/mL	6.96 ± 2.73	9.25 ± 4.23	0.002*	0.002*	0.075
FINS_2, µIU/mL	8.74 ± 3.45	9.59 ± 4.51	0.314	0.318	0.521
FINS_3, µIU/mL	10.40 ± 4.57	12.99 ± 6.99	0.043*	0.044*	0.239
FPG_1, mmol/L	4.38 ± 0.30	4.46 ± 0.22	0.167	0.155	0.402
FPG_2, mmol/L	4.40 ± 0.32	4.36 ± 0.32	0.532	0.565	0.226
FPG_3, mmol/L	4.82 ± 0.49	4.71 ± 0.59	0.365	0.295	0.128
HOMA-IR_1	1.36 ± 0.56	1.85 ± 0.88	0.002*	0.001*	0.061
HOMA-IR_2	1.72 ± 0.71	1.87 ± 0.94	0.379	0.373	0.433
HOMA-IR_3	2.22 ± 0.94	2.79 ± 1.73	0.052	0.057	0.354
TC_1, mmol/L	4.92 ± 1.10	4.66 ± 0.63	0.205	0.206	0.263
TC_2, mmol/L	5.75 ± 1.08	5.41 ± 0.66	0.103	0.117	0.221
TC_3, mmol/L	6.15 ± 1.16	5.83 ± 1.03	0.198	0.229	0.551
TG_1, mmol/L	1.65 ± 0.83	1.95 ± 0.64	0.076	0.057	0.198
TG_2, mmol/L	2.38 ± 1.37	2.62 ± 0.73	0.36	0.303	0.669
TG_3, mmol/L	3.37 ± 1.33	3.52 ± 0.86	0.592	0.512	0.662
HDL_1, mmol/L	2.05 ± 0.35	1.88 ± 0.43	0.046*	0.036*	0.182
HDL_2, mmol/L	2.27 ± 0.41	2.11 ± 0.46	0.09	0.083	0.266
HDL_3, mmol/L	2.10 ± 0.44	2.02 ± 0.44	0.437	0.45	0.733
LDL_1, mmol/L	2.52 ± 0.94	2.41 ± 0.57	0.555	0.572	0.489
LDL_2, mmol/L	3.15 ± 1.01	2.84 ± 0.67	0.114	0.123	0.225
LDL_3, mmol/L	3.35 ± 1.02	3.35 ± 1.70	0.998	0.931	0.854
a "X"_ 1: tested in 12–16 weeks gestation; “X”_ 2: tested in 24–28 weeks gestation; “X”_ 3: tested in 32–36 weeks of gestation ("X" is the corresponding index: T, Testosterone; SHBG, Sex hormone binding protein; FAI, Free androgen index; FPG, Fasting plasma glucose; FINS, Fasting insulin; HOMA-IR, Homeostasis model assessment of insulin resistance; TG, Triglyceride; TC, Total cholesterol; HDL, High-density lipoprotein; LDL, Low-density lipoprotein)。
Regression analysis was conducted with the control group as the reference group. Continuous variables are presented as "β value (95% confidence interval of the β value) P-value," and categorical variables are presented as "OR value (95% confidence interval of the OR value) P-value." Unadjusted #0: No adjustment for confounding factors; Adjust 1#1: Adjustment for age; Adjust 2#2: Adjustment for age and BMI. * indicates two-tailed P-value less than 0.05

In glucose metabolism indicators, the PCOS group had a higher FINS level at 12–16 weeks of gestation (9.25 ± 4.23 vs. 6.96 ± 2.73 µIU/mL; P = 0.002), a higher HOMA-IR level at 12–16 weeks of gestation (1.85 ± 0.88 vs. 1.36 ± 0.56; P = 0.002), and a higher FINS level at 32–36 weeks of gestation (12.99 ± 6.99 vs. 10.40 ± 4.57 µIU/mL; P = 0.043). In addition, no intergroup differences were detected in other glucose metabolism indicators. (Table 2, Fig. 2)

In lipid metabolism indicators, HDL in the PCOS group was lower than that in the non-PCOS group (1.88 ± 0.43 vs. 2.05 ± 0.35 mmol/L; P = 0.046) at 12–16 weeks of gestation. No intergroup differences were detected in other lipid metabolism indicators. (Table 2, Fig. 2)

Polycystic ovary syndrome (PCOS) is a complex endocrine metabolic disorder with significant phenotypic heterogeneity. In this study, we focused on women from the southwestern China, and established a prospective cohort to observe their endocrine and metabolic indicators during pregnancy. Our findings indicate that the levels of T and FAI in PCOS women remained consistently elevated during pregnancy even independent of pre-pregnancy BMI. The abnormal lipid metabolism of PCOS patients during pregnancy is relatively mild, which only showed the decrease of HDL in the early pregnancy. Women with PCOS had abnormal glucose metabolism in the early and late pregnancy. Higher pre-pregnancy BMI is an important contributor to the abnormal glucose and lipid metabolism, rather than elevated androgens in women with PCOS.

While PCOS has a strong genetic component, the genetic contribution of susceptibility loci identified through GWAS to PCOS only accounts for 10% of its heritability despite being associated with 70% of the genetic risk(22). Excessive in utero androgen exposure is considered a primary factor underlying this phenomenon. In the population of the southwestern region of China targeted by this study, the PCOS group exhibited a sustained elevation in T levels and FAI during pregnancy, which is largely consistent with previous research conducted in various countries and regions (21, 23, 24). After adjusting for confounding factors, including BMI, the differences remained relatively stable, suggesting that PCOS can independently contribute to elevated androgen levels during pregnancy. Enrichment analysis based on comprehensive spectral information revealed an upregulation of steroid hormone biosynthesis metabolism in the PCOS group, aligning with the high androgen status observed during PCOS pregnancies. This further confirms the presence of elevated androgen levels during pregnancy in PCOS patients, likely serving as a potential source of excessive androgen exposure to the developing fetus.

As previously mentioned, maternal insulin sensitivity decreases during pregnancy to accommodate the fetus's glucose requirements. However, due to their inherent IR tendencies, PCOS patients are at a higher risk of glucose metabolism disturbances during pregnancy (9, 25, 26). In our study, fasting insulin levels and the HOMA-IR index in PCOS patients were elevated during weeks 12–16 of pregnancy compared to the control group. As pregnancy progressed, both groups experienced reduced insulin sensitivity, reaching their lowest levels in late pregnancy, which is consistent with physiological changes in glucose metabolism during pregnancy (27). Likely due to strict medical advice (diet control and weight management) provided to PCOS patients during antenatal care, there were no significant differences in glucose metabolism indicators between the two groups in mid-pregnancy. After adjusting for confounding factors, including pre-pregnancy BMI, the differences in glucose metabolism disappeared, indicating that pre-pregnancy BMI is a major risk factor for IR. Prior studies have shown that PCOS patients experience elevated levels of LDL, TC, and TG, accompanied by characteristic lipid distribution with reduced HDL during pregnancy (28). In our study, both groups showed gradual increases in TC, TG, and LDL levels during pregnancy, consistent with the physiological changes in lipid metabolism during pregnancy (27). Between-group comparisons revealed no significant differences except for HDL levels during weeks 12–16 of pregnancy. As previously mentioned, this could be attributed to medical interventions and advice provided during pre-pregnancy and antenatal care.

This study is the first prospective cohort study aimed at the Southwestern Chinese women that comprehensively includes endocrine metabolic indexes during pregnancy. However, it has some limitations. First, the sample size was small, which limited the ability to detect minor differences. Second, women in our cohort were mainly from a tertiary referral hospital, limiting the generalizability of the results.

Ethics Approval and Consent to Participate: The ethical approval for this study was granted by the Ethics Committee of China Clinical Trial Registration Center (ChiECRCT20190022). All participants provided informed consent to participate.

Consent for Publication: All authors have consented to the publication of this manuscript.

Availability of Data and Materials: The data supporting the findings of this study are available from the corresponding author upon reasonable request.

Competing Interests: The authors declare no competing interests.

Funding: This study was funded by the Key R&D Plan of the Sichuan Provincial Department of Science and Technology (Grant No. 2021YFS0028) and the Key R&D Plan of the Sichuan Provincial Department of Science and Technology (Grant No. 2017SZ0136).

Authors' Contributions: Conception and design: Professor Wei Huang and Dr. Qi Cao; Literature search: Professor Huili Zhu and Dr. Jing Tan; Clinical studies: Dr. Qi Cao, Dr. Dong Liu, Dr. Qiuyi Wang, and Dr. Jing Tan; Data acquisition: Dr. Qi Cao, Dr. Xin Huang, Dr. Yujing Li, and Professor Rong Zhou; Statistical analysis: Professor Wei Huang and Dr. Qi Cao; Manuscript and manuscript editing: Dr. Ruiying Wang, Dr. Jing Tan, and Dr. Qi Cao; Manuscript review: All authors.

Acknowledgments: Not applicable.

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No competing interests reported.

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Endocrine Traits During Pregnancy in Women with Polycystic Ovary Syndrome - Insights from a Prospective Cohort Study in China

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Background

Methods

Study design and participants

Baseline information

Maternal endocrinal and metabolic markers

Sample size calculation

Statistical analyses

Results

Baseline characteristics

Endocrine metabolic information

Discussion

Conclusion

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References

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