https://orcid.org/0009-0001-5099-3587
Figures
Abstract
Objective
Abnormal body mass index (BMI) has been associated with pregnancy complications and adverse pregnancy outcomes; however, its clinical significance during early pregnancy remains unclear. This study aimed to investigate the relationships and underlying mechanisms between maternal BMI, reproductive endocrine parameters, and pregnancy outcomes, thereby providing a theoretical basis and clinical guidance for the management of pregnancies in women with abnormal BMI.
Methods
A total of 353 pregnant women were enrolled in this study and categorized into four groups according to BMI: underweight (n = 45), normal weight (n = 229), overweight (n = 57), and obese (n = 22). At 6–8 weeks of gestation, pregnancy-related hormones, glucose and lipid metabolism parameters, and uterine artery blood flow indices were collected and analyzed. Pregnancy outcomes and neonatal birth information were also recorded. In addition, an obese mouse model was established to evaluate maternal weight changes during pregnancy and their effects on uterine and embryonic development. The expression of genes and proteins related to en[docrine metabolism, inflammatory regulation, and angiogenesis was assessed using RT-qPCR and Western blot techniques to further explore the potential mechanisms involved.
Results
During early pregnancy, pregnant women with low BMI exhibited significantly lower estradiol levels (P < 0.05). In contrast, women with high BMI had significantly reduced levels of human chorionic gonadotropin, estradiol, and progesterone, along with markedly elevated glucose and lipid metabolism parameters (P < 0.05). However, BMI had no significant impact on uterine artery blood flow indices, live birth rate, gestational age, or mode of delivery (P > 0.05). High BMI was associated with an increased risk of macrosomia in neonates (P < 0.05). In the animal experiments, obese pregnant mice exhibited significantly greater gestational weight gain compared to controls (P < 0.05), and their offspring showed a predisposition to obesity. RT-qPCR analysis revealed that, relative to the control group, mRNA expression levels of VEGFA, VEGFR-2, CD31, and SIRT1 were significantly decreased in the obese group (P < 0.001), whereas mRNA expression of GLUT1, HIF-1α, TNF-α, IL-6, HMGB1, and TLR4 was significantly upregulated (P < 0.01). Western blot results demonstrated that compared with controls, the obese group showed significantly lower expression levels of GLUT4 and phosphorylated IRS1 (P < 0.0001), while the expression of HIF-1α and TNF-α was significantly increased (P < 0.0001). Additionally, there were no significant differences in the protein expression levels of IRS1, SGK1, and NFκB p65 between the two groups (P > 0.05).
Conclusion
Abnormal BMI affects hormonal profiles and glucose and lipid metabolism during early pregnancy. Although it does not significantly impact fetal survival rates, it markedly increases the risks of cesarean delivery, preterm birth, and abnormal neonatal birth weight. These alterations not only pose challenges for postpartum maternal and neonatal health management but may also exert adverse effects on the long-term health of the offspring. Maternal obesity may impair pregnancy outcomes by inhibiting insulin signaling, enhancing proinflammatory responses, inducing a hypoxic microenvironment in the decidual tissue, and suppressing angiogenesis, thereby disrupting maternal–fetal interface homeostasis.
Citation: Shen W, Niu A, Zhang Q, Deng J, Xu X, Ma X, et al. (2026) Effects of maternal BMI on early pregnancy endocrine–metabolic function and offspring development: Evidence from a retrospective cohort and animal model. PLoS One 21(1): e0333081. https://doi.org/10.1371/journal.pone.0333081
Editor: Bella Stevanny, Sriwijaya University: Universitas Sriwijaya, INDONESIA
Received: January 25, 2025; Accepted: September 9, 2025; Published: January 8, 2026
Copyright: © 2026 Shen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting Information files.
Funding: This research was funded by the Zhejiang Provincial Natural Science Foundation of China (No. ZCLMS25H2709); Medical and Health Research Project of Zhejiang Province (No. 2025KY1152); Medical and Health Research Project of Zhejiang Province (No. 2022RC232); Zhejiang Traditional Medicine and Technology Program of China (No. 2022ZA111); Key Project of Hangzhou Health Science and Technology Program of China (No. ZD20230093); Research Project of Zhejiang Chinese Medical University (No. 2024GJYY53).
Competing interests: The authors have declared that no competing interests exist.
1. Introduction
In recent years, with lifestyle changes and increasing social pressures, the prevalence of abnormal body mass index (BMI) among women of reproductive age has shown a steadily rising trend worldwide [1,2]. Abnormal BMI may impair female reproductive function by disrupting endocrine balance, inducing lipotoxicity, oxidative stress, and inflammatory responses, interfering with gene expression, and even causing structural alterations in the ovaries, thereby increasing the risk of infertility, miscarriage, and failure of assisted reproductive technologies [3–6]. A substantial body of research has demonstrated a significant association between elevated maternal BMI and adverse perinatal outcomes [7,8]. Previous studies have reported that abnormal BMI is not only an independent risk factor for spontaneous miscarriage but also markedly increases the incidence of pregnancy complications such as gestational diabetes mellitus, hypertension, and preterm birth [9–11].
Moreover, early pregnancy represents a critical period for embryonic implantation and the initial development of organ systems. Beginning in the sixth week of gestation, the embryo starts to differentiate and form essential systems, including the circulatory, nervous, and urinary systems. During this stage, the embryo is particularly sensitive to external factors; immune rejection or abnormalities in the maternal internal environment can lead to embryonic developmental disorders, congenital malformations, or miscarriage, resulting in significant psychological distress for the pregnant woman [12,13]. Our previous studies have found that pregnancy-related hormonal parameters measured at the seventh week of gestation possess good predictive value for pregnancy outcomes [14].
Therefore, this study selected 6–8 weeks of gestation as the observation window and, by integrating clinical data and animal experiments, comprehensively analyzed the impact and potential mechanisms of maternal BMI on early pregnancy hormonal levels, glucose and lipid metabolism, uterine artery blood flow parameters, pregnancy outcomes, and neonatal birth characteristics. The aim is to provide scientific evidence and clinical guidance for pregnancy management in women with abnormal BMI.
2. Human study
2.1. Data sources and grouping
This study was approved by the Medical Ethics Committee of Hangzhou Hospital of Traditional Chinese Medicine (Ethics Approval Number: 2024KLL219), and the data were accessed for research purposes from December 31, 2024, to January 10, 2025. The authors have access to identifiable information of individual participants during or after data collection, but we have signed a data confidentiality agreement and will anonymize identifiable information when publishing the data.
The study included women aged 20–40 years in early pregnancy who attended Hangzhou Hospital of Traditional Chinese Medicine from June 1, 2022, to June 1, 2023. Women with a history of chronic diseases, reproductive tract anomalies, multiple pregnancies, ectopic pregnancies, or chromosomal abnormalities were excluded. Ultimately, 353 cases with complete clinical records were collected.
Maternal BMI was calculated based on height and weight measured at admission. According to national standards, participants were classified into four groups: underweight (BMI < 18.5 kg/m2, n = 45), normal weight (18.5 ≤ BMI < 24 kg/m2, n = 229), overweight (24 ≤ BMI < 28 kg/m2, n = 57), and obese (BMI ≥ 28 kg/m2, n = 22) [15].
2.2. Observational indicators
- (i) Clinical parameters assessed at 6–8 weeks of gestation: (a) Pregnancy-related hormones: human chorionic gonadotropin (hCG), estradiol (E2), and progesterone (P4); (b) Glucose and lipid metabolism parameters: triglycerides (TG), total cholesterol (TC), high-density lipoprotein (HDL), and fasting plasma glucose (FPG). According to the criteria of the International Association of Diabetes and Pregnancy Study Groups (IADPSG) and the reference ranges recommended by the hospital, abnormal values were defined as TG ≥ 1.7 mmol/L, TC ≥ 5.2 mmol/L, HDL ≤ 1.0 mmol/L, and FPG ≥ 5.1 mmol/L [16]. (c) Ultrasound parameters of uterine artery blood flow: pulsatility index (PI), resistance index (RI), and the systolic/diastolic ratio (S/D).
- (ii) Pregnancy outcomes: Pregnancy outcome, gestational age at delivery, and mode of delivery. Preterm birth was defined as delivery before 37 weeks of gestation (<260 days), and post-term pregnancy as delivery after 42 weeks of gestation (>293 days) [17].
- (iii) Neonatal birth characteristics: Neonatal birth weight. Low birth weight was defined as neonatal weight < 2500 g, and macrosomia (high birth weight, HBW) as neonatal weight > 4000 g [17].
2.3. Data collection methods
- (i) Serum hormone and glucose-lipid metabolism parameters: Peripheral venous blood samples were collected from pregnant women in the morning after overnight fasting. HCG, E2, and P4 were measured using an automated chemiluminescence immunoassay analyzer (ADVIA Centaur XP). TG, TC, HDL, and FPG values were determined with an automated biochemical analyzer (BECKMAN COULTER AU5842).
- (ii) Uterine artery blood flow parameters: A color Doppler ultrasound diagnostic system (Nuewa R9T) was used, with the probe frequency set at 5–9 MHz, to visualize the color Doppler blood flow signals of the bilateral uterine arteries at the uterine isthmus. Measurements of PI, RI, and S/D were performed and recorded by experienced sonographers at the hospital.
- (iii) Pregnancy outcomes and neonatal information collection: Data on pregnancy outcomes and neonatal birth characteristics were obtained through the hospital’s electronic medical record system and telephone follow-up.
3. Animal study
3.1. Animal sources and housing conditions
All experimental protocols strictly complied with the Guide for the Care and Use of Laboratory Animals published by the U.S. National Institutes of Health and were approved by the Ethics Committee of the Animal Experimental Research Center of Zhejiang Chinese Medical University (Ethics Approval No.: IACUC-20240729–21).
The study used 20 specific pathogen-free (SPF) nulliparous female ICR mice (28 days old, body weight 15 ± 2 g) and 10 male ICR mice of the same age and weight, all provided by Zhejiang Chinese Medical University and purchased from Shanghai Slake Laboratory Animal Co., Ltd. (License No.: SCXK Shanghai 2022−0004). All animals were housed in the SPF-grade animal facility of the Animal Experimental Research Center of Zhejiang Chinese Medical University. Environmental conditions were maintained at 22–24 °C, relative humidity of 55%–65%, and a 12-hour light/dark cycle. Animals had free access to food and water.
3.2. Obesity model induction
Ten female ICR mice were randomly selected as the normal weight group and co-housed with male mice while being fed a standard diet (provided by the Animal Research Center of Zhejiang Chinese Medical University). The remaining ten female mice were fed a high-fat diet to induce obesity. The high-fat diet was purchased from Wuxi Fanbo Biotechnology Co., Ltd. and composed of the following: 10% lard, 10% egg yolk powder, 2% cholesterol, 0.1% bile salts, 6% casein, 1.2% premix, and 3% maltodextrin, with the remaining proportion being the basal feed. A significant increase in body weight compared to the normal diet group was considered indicative of successful obesity model establishment. After modeling, all mice were fed a standard diet.
From day 21 of modeling (corresponding to day 49 of age), daily vaginal smears were performed at 9:00 a.m. to monitor the estrous cycle. At 56 days of age, female mice in estrus were paired for mating at a ratio of two females to one male at 17:00 on the same day. The presence of a vaginal plug was checked at 8:00 a.m. the following day. Females with a vaginal plug were considered successfully mated, individually housed, and designated as pregnancy day 1 (PD1).
3.3. Specimen collection and outcome measures
3.3.1. General indicators.
The general health status of all experimental mice was monitored daily, including coat luster, locomotor activity, behavioral responses, feeding and excretion, and any abnormal secretions. After pregnancy was confirmed, body weight was measured every other day. Mice were also observed for signs of vaginal bleeding or embryo expulsion.
3.3.2. Embryo-related assessments.
From each group, five pregnant mice were randomly selected. Beginning at 21:00 on PD9, food and water were withdrawn. The following morning at 9:00, the mice were anesthetized via intraperitoneal injection of sodium pentobarbital (40 mg/kg), followed by euthanasia through cervical dislocation. The intact uterus, ovaries, and embryos were carefully removed and rinsed with PBS buffer to eliminate adherent tissues. The gross morphology was examined, and the number of implantation sites and resorbed embryos was recorded. Photographic documentation was performed. Portions of the uterine tissue were placed into 2 mL cryovials and stored at −80 °C for subsequent analyses. The remaining tissues were fixed in Eppendorf tubes containing paraformaldehyde for histological examination.
3.3.3. Pregnancy-related assessments.
The remaining five pregnant mice in each group were maintained on a standard diet until spontaneous delivery. The day of parturition was designated as birth day 0 (BD0). Each pup was individually marked and weighed within 12 hours of birth. Thereafter, body weight was measured every three days for 15 consecutive days, with weights recorded to the nearest 0.1 gram.
3.3.4. RNA isolation and RT-qPCR.
Quantitative PCR primers were designed using Primer Premier 6.0 and Beacon Designer 7.8 software and synthesized by Bioengineering (Shanghai) Co., Ltd. The primer sequences are listed in S1 Table. Total RNA was extracted from uterine tissue using the TRIzol® Plus RNA Purification Kit. RNA concentration, purity, and integrity were assessed by UV spectrophotometry (DU-800) and agarose gel electrophoresis. Complementary DNA (cDNA) was synthesized from total RNA using the SuperScript™ III First-Strand Synthesis SuperMix kit. RT-qPCR was performed on a CFX384 Real-Time PCR Detection System (Bio-Rad, USA). Each 20 μL reaction contained 8.0 μL sterile distilled water (SDW), 10.0 μL Power SYBR® Green Master Mix, 0.5 μL each of forward and reverse primers (10 μmol/L), and 1 μL cDNA template. The amplification protocol was as follows: initial denaturation at 95 °C for 1 min, followed by 40 cycles of 95 °C for 15 s and 63 °C for 25 s. All reactions were performed in triplicate. The mRNA expression levels of vascular endothelial growth factor A (VEGFA), vascular endothelial growth factor receptor-2 (VEGFR-2), platelet endothelial cell adhesion molecule-1 (CD31), glucose transporter 1 (GLUT1), hypoxia-inducible factor 1α (HIF-1α), tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), high-mobility group box 1 (HMGB1), sirtuin 1 (SIRT1), and toll-like receptor 4 (TLR4) were quantified. Relative mRNA expression levels were normalized to β-actin and calculated using the 2−ΔΔCt method.
3.3.5. Protein extraction and western blot quantification.
Total protein was extracted using a lysis buffer containing protease inhibitors (Thermo Pierce, Cat# 78510). Protein concentration was determined with a BCA Protein Assay Kit (Beyotime Biotechnology, Cat# P0010) following the manufacturer’s instructions. Aliquots of 60 μg protein were separated by 8–12% SDS-PAGE under constant voltage conditions (stacking gel: 60 V; resolving gel: 80 V). Proteins were then transferred onto methanol-activated PVDF membranes (Millipore, Cat# IPVH00010) using Tris-Glycine transfer buffer containing 5% methanol at 100 V constant voltage for 2 hours at 4 °C. Following transfer, membranes were blocked with T-TBS containing 5% BSA for 1 hour at room temperature. Subsequently, membranes were incubated overnight at 4 °C with primary antibodies diluted in T-TBS containing 3% BSA (S2 Table). After primary antibody incubation, membranes were incubated with a Goat anti-Mouse IgG (H + L) secondary antibody (Thermo Pierce, Cat# 31160 or 31210) at a 1:5000 dilution in T-TBS supplemented with 3% BSA for 1 hour at room temperature. After T-TBS washes, protein signals were detected using SuperSignal West Dura Extended Duration Substrate (Thermo Pierce, Cat# 34075) with X-ray film exposure. Band intensities were quantified by Image J 1.8.0 (NIH, USA) using β-actin and TATA binding protein (TBP) as loading controls, with relative expression calculated as (target density/internal reference density) ×10ⁿ. Data represent mean ± standard deviation from triplicate experiments.
4. Statistical analysis
Statistical analyses were performed using SPSS version 29.0. The distribution of continuous variables was assessed using the Shapiro–Wilk test. Data conforming to a normal distribution were expressed as mean ± standard deviation ( ), and differences between two groups were evaluated using the independent samples t-test. For comparisons among multiple groups, one-way ANOVA was applied when variances were equal. If significant differences were detected, pairwise comparisons were performed using the Bonferroni correction, with adjusted P values reported.
For data that exhibited a severely skewed distribution, values were expressed as median and interquartile range [M (P25, P75)], and group comparisons were conducted using the Kruskal–Wallis test. If significant differences were found, pairwise comparisons were also performed using the Bonferroni method.Categorical variables were presented as proportions, and inter-group differences were analyzed using the chi-square (X2) test or Fisher’s exact test as appropriate. The Bonferroni correction was applied for multiple comparisons. Asterisks were used to indicate statistical significance relative to the normal control group: *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.
5. Results
5.1. Clinical study findings
5.1.1. Comparison of baseline characteristics among pregnant women.
As shown in S3 Table, there were no statistically significant differences among the groups regarding menstrual cycle length, history of miscarriage, number of adverse pregnancies, or mode of conception (P > 0.05), indicating good comparability among the groups. Notably, women in the overweight group were older and had a shorter duration of menstruation, and these differences were statistically significant (P < 0.05).
5.1.2. Abnormal BMI may contribute to lower hCG, E2, and P4 levels during early pregnancy.
As presented in Table 1, compared with the normal-weight group, the overweight group exhibited significantly lower serum hCG levels across all gestational weeks assessed (P < 0.05). Additionally, the other groups showed a similar trend of decreased hCG levels, although these differences did not reach statistical significance (P > 0.05).
5.1.3. Women with high BMI in early pregnancy are prone to glucose and lipid metabolism disorders.
As shown in Table 2, pregnant women with high BMI exhibited significantly elevated TG and TC levels (P < 0.05). Although there was an overall statistical difference in HDL levels, pairwise comparisons between groups did not reveal significant differences (P > 0.05). FPG levels and the prevalence of glucose and lipid metabolism disorders were significantly higher in the obese group compared with the normal-weight group (P < 0.05), and the incidence of these abnormalities demonstrated a positive correlation with BMI.
5.1.4. Impaired uterine microcirculation in women with high BMI at 6–8 weeks of gestation.
As shown in Table 3, during gestational weeks 6–8, the uterine artery blood resistance flow exhibited a positive correlation with BMI classification. The PI showed a significant difference in overall distribution (P < 0.05); however, pairwise comparisons between groups did not reveal statistically significant differences (P > 0.05).
5.1.5. Maternal BMI affects neonatal birth outcomes.
As presented in Table 4, there were no statistically significant differences among groups regarding live birth rate, gestational age at delivery, mode of delivery, incidence of LBW, preterm birth rate, or overall neonatal abnormalities (P > 0.05). Additionally, no cases of post-term pregnancy were observed in any group.
5.2. Results of animal experiments
5.2.1. Comparison of body weight during model induction.
After 21 days of modeling, the body weight of mice in the obesity group was significantly higher compared to the normal group (P < 0.0001) (S1 Fig.a). The overall increase in body weight was also significantly greater (P < 0.0001) (S1 Fig.b), confirming the successful establishment of the obesity model (S1 Fig.c).
Following model induction, vaginal exfoliated cells were collected daily at 9:00 a.m. During estrus, a large number of cornified epithelial cells and a small number of nucleated epithelial cells were observed. Comparison of vaginal smears between the two groups showed that the number of cornified epithelial cells was reduced in the obesity group, suggesting a shortened estrous phase(S1 Fig.d).
5.2.2. Obesity does not affect maternal weight gain, embryo weight, or embryo loss rate.
In early pregnancy, the body weight of obese pregnant mice remained significantly higher than that of normal-weight pregnant mice (P < 0.01) (Fig 1a); however, the magnitude of weight gain showed no statistically significant difference between groups (P > 0.05) (Fig 1b).
(a) Line graph depicting maternal body weight at different gestational ages. Group differences are indicated as **P < 0.01, ***P < 0.001. (b) Box plot showing body weight gain of pregnant mice during PD9. No significant difference was observed between groups (P > 0.05). (c) Representative images of uteri and implantation sites in pregnant mice (upper panel: uterus, embryos, and ovaries; lower panel: uterus and embryos). Scale bar = 5 mm.
There were no significant differences between the obesity and control groups in terms of uterine weight, mean embryo weight, or embryo loss rate (P > 0.05) (Table 5). Total uterine weight was associated with the number of implanted embryos. Obese mice had a lower average number of embryos compared to control group.
In normal-weight mice, the uteri appeared pale red, bead-like in shape, and relatively uniform in size, with occasional minor congestion in the uterine cavity. In contrast, uteri and embryos from obese mice were darker in color, with more pronounced intrauterine congestion and uneven degrees of embryonic development ((Fig 1c).
5.2.3. Offspring of obese pregnant mice exhibit a tendency toward obesity.
The body weight of the offspring born to obese pregnant mice was significantly higher than that of the control group (P < 0.0001) (Fig 2a). Moreover, during development, these offspring showed a markedly greater increase in body weight, demonstrating an apparent trend toward obesity (P < 0.0001) (Fig 2b). The developmental progression of the offspring is illustrated in Fig 2c.
(a) Line graph showing body weight changes of neonatal mice at different postnatal ages. Group differences are indicated as ****P < 0.0001. (b) Box plot depicting total body weight gain during BD15 in neonatal mice. Group differences are indicated as ****P < 0.0001. (c) Representative morphology of neonatal mice at different postnatal ages. Scale bar = 5 mm.
5.2.4. Obesity may induce characteristic endometrial changes of inflammation–hypoxia–metabolic–angiogenic imbalance.
RT-qPCR results showed that, compared with the control group, mRNA expression levels of VEGFA, VEGFR-2, CD31, and SIRT1 were significantly decreased in the obesity group (P < 0.001), while the expression levels of GLUT1, HIF-1α, TNF-α, IL-6, HMGB1, and TLR4 were significantly upregulated (P < 0.01) (Fig 3a).
(a) Relative mRNA expression levels of VEGFA, VEGFR-2, CD31, GLUT1, HIF-1α, TNF-α, IL-6, HMGB1, SIRT1, and TLR4 in uterine tissues analyzed by RT-qPCR (n = 3 per group). Values are presented as mean ± standard deviation. Group differences are indicated as **P < 0.01, ***P < 0.001, and ****P < 0.0001. (b) Representative Western blot bands of GLUT4, IRS1, p-IRS1, SGK1, NF-κB p65, HIF-1α, and TNF-α proteins in uterine tissues (n = 3 per group). (c) Densitometric analysis of relative protein expression levels of GLUT4, IRS1, p-IRS1, SGK1, NF-κB p65, HIF-1α, and TNF-α measured by Western blotting (n = 3 per group). Values are presented as mean ± standard deviation. Group differences are indicated as ****P < 0.0001.
Western blot analysis revealed that, compared with controls, the protein expression levels of GLUT4 and p-IRS1 were markedly decreased in the obesity group (P < 0.0001), whereas HIF-1α and TNF-α protein levels were significantly increased (P < 0.0001). Additionally, there were no significant differences between groups in the expression of IRS1, SGK1, and NFκB p65 proteins (P > 0.05) (Fig 3b and 3c).
6. Analysis and discussion
Abnormal BMI is closely associated with various reproductive complications; however, the underlying links between BMI and pregnancy outcomes remain incompletely understood. This study aimed to investigate the relationships between BMI and multiple clinical indicators in early pregnancy, to analyze their potential impact and mechanisms on pregnancy outcomes and fetal development, and to provide a basis for clinical assessment and pregnancy management in women with abnormal BMI.
During pregnancy, placental cholesterol and maternal lipoprotein-derived cholesterol serve as major precursors for the synthesis of sex hormones [18]. Dysregulation of adipose tissue-derived factors can disrupt glucose and lipid metabolism, trigger chronic low-grade inflammation, and alter the immunological microenvironment at the maternal–fetal interface [19]. Concurrently, disruption of metabolic homeostasis impairs adipocyte function and tissue remodeling capacity, further exacerbating maternal inflammatory responses and oxidative stress [20]. These pathological changes can interfere with the function of the hypothalamic–pituitary–ovarian (HPO) axis, suppress the secretion of gonadotropin-releasing hormone (GnRH), and reduce the responsiveness of granulosa cells to follicle-stimulating hormone (FSH), ultimately leading to decreased levels of E2 and P4 [19,21,22]. These hormonal alterations negatively impact endometrial receptivity and embryo implantation [23,24]. Therefore, the metabolic status of glucose and lipids in early pregnancy may serve as an early warning indicator of metabolic syndrome and adverse pregnancy outcomes [25,26].
In early pregnancy, normal embryonic development depends on a variety of hormones secreted by the corpus luteum and placenta. Among them, hCG promotes corpus luteum growth and estrogen secretion by stimulating the expression of adhesion molecules, improves local uterine blood supply, thereby enhancing endometrial receptivity and facilitating successful embryo implantation [27]. During normal pregnancy, serum hCG levels typically rise significantly starting from gestational week 6 and reach a peak around week 10. Previous studies have demonstrated that hCG levels in early pregnancy are closely associated with pregnancy outcomes [28]. E2, a steroid hormone, is primarily secreted by the corpus luteum under the stimulation of hCG during early pregnancy. Its level serves as an important indicator for evaluating dominant follicle quality and luteal function. E2 plays a critical role in regulating endometrial receptivity, microcirculation at the maternal–fetal interface, and pregnancy-related immune responses [29,30]. Earlier studies have shown that E2 can activate serum- and glucocorticoid-inducible kinase 1 (SGK1), an upstream regulator of the PI3K signaling pathway, effectively inhibiting Toll-like receptor 4 (TLR4)-mediated pro-apoptotic and pro-inflammatory Th1-type immune responses while enhancing anti-inflammatory Th2-type immune responses. This process promotes the differentiation of M2 macrophages, facilitating decidual remodeling and angiogenesis at the maternal–fetal interface during early pregnancy, thereby maintaining an optimal environment for embryo implantation [31,32]. In addition, E2 has been reported to enhance the transcriptional activity of the low-density lipoprotein receptor (LDLR) gene and to augment the function of placental desmolase, thereby accelerating the conversion of cholesterol to pregnenolone and promoting P4 synthesis [33,34]. Further clinical studies have found that starting from gestational week 6, serum E2 levels in women experiencing spontaneous miscarriage are significantly lower compared with those with normal pregnancies [35]. A multicenter study involving 548 singleton pregnancies also confirmed a significant negative correlation between BMI and E2 levels, indicating that for every one-unit increase in BMI, E2 levels decrease on average by 1%–2% [36]. P4 also plays a pivotal role in trophoblast adhesion and proliferation. Working synergistically with E2, P4 participates in regulating uterine microcirculation and enhances immune tolerance at the maternal–fetal interface, thereby maintaining a stable intrauterine environment necessary for embryo implantation and development [37,38]. Insufficient P4 secretion can impair trophoblast invasiveness, increase the risk of maternal immune rejection of the embryo, and ultimately compromise pregnancy maintenance [39].
In terms of endocrine metabolism, GLUT4 is a key transporter regulated by insulin that plays a critical role in cellular energy metabolism by facilitating glucose uptake [40]. IRS1, as a principal mediator of insulin signaling, undergoes tyrosine phosphorylation to activate the phosphoinositide 3-kinase (PI3K)/Akt signaling pathway, thereby promoting GLUT4 translocation to the plasma membrane and enhancing cellular glucose uptake capacity [41,42]. The findings of this study demonstrated that, under obese conditions, the expression levels of GLUT4 and p-IRS1 were significantly downregulated. This is consistent with previous reports indicating that obesity-associated lipid accumulation in the endometrium can suppress IRS1 and GLUT4 expression [43]. Animal experiments by Long et al. also revealed that impaired GLUT4 function leads to restricted glucose uptake by the endometrium during early pregnancy, inducing endometrial dysfunction and reducing embryo implantation rates [40]. Meanwhile, local metabolic disturbances can exacerbate hypoxia in endometrial tissues and induce the upregulation of HIF-1α expression. HIF-1α is a central cellular responder under hypoxic conditions and can enhance the biological effects of VEGF through multiple mechanisms to adapt to a low-oxygen environment [44]. VEGF, a critical downstream target of HIF-1α, promotes endothelial cell migration, proliferation, and angiogenesis [45]. Inactivation of the VEGF gene results in severe vascular developmental defects and is a major cause of early embryonic lethality [46].
Regarding inflammation regulation, HMGB1 is an endogenous danger-associated molecular pattern protein that can be actively or passively released upon cellular damage or necrosis, inducing sterile inflammation and contributing to the dynamic regulation of the inflammatory response and tissue repair [47]. Upon binding to the Toll-like receptor 4 (TLR4), HMGB1 activates the nuclear factor-κB (NF-κB) signaling pathway, increasing the production of pro-inflammatory cytokines such as IL-6 and TNF-α, thereby creating a chronic sterile inflammatory microenvironment [48]. This, in turn, restricts nutrient transport across the placenta, induces decidual cell dysfunction, and disrupts maternal–fetal immune tolerance [49,50]. Yeung et al. reported that under physiological conditions, SIRT1 deacetylates the p65 subunit of NF-κB and suppresses its activity, thereby exerting anti-inflammatory effects [51].
The results of this study showed that underweight pregnant women exhibited slightly lower serum hCG levels compared to those with normal weight, which may be related to delayed embryonic development due to insufficient nutritional intake. Moreover, E2 levels in underweight pregnant women were significantly lower than in other groups, whereas P4 levels were relatively higher, although the latter did not reach statistical significance. Given that low body weight may lead to dysregulation of reproductive endocrine function and adversely affect ovarian activity and luteal hormone secretion [52], we speculate that reduced E2 levels during early pregnancy could be associated with potential ovarian insufficiency in underweight women. Conversely, women with high BMI generally exhibited lower serum levels of hCG, E2, and P4. This may result from the hemodilution effect associated with obesity as well as its negative impact on ovarian and placental function. However, it is noteworthy that during weeks 6–8 of gestation, pregnancy-related hormone levels in obese women were actually higher than those observed in overweight women. This observation contrasts with the findings of Bartha et al., who reported lower progesterone concentrations in obese women between gestational weeks 9–11 [18]. Lassance et al. further demonstrated that maternal obesity during pregnancy can downregulate mitochondrial cholesterol transport protein TSPO, thereby suppressing mitochondrial steroidogenesis and impairing sex hormone synthesis [53]. Nevertheless, whether a threshold difference exists in cholesterol metabolism or steroid production between overweight and obese populations remains unclear and warrants further investigation.
Additionally, our results showed that women with high BMI had significantly elevated levels and rates of abnormal glucose and lipid metabolism during early pregnancy, with a positive correlation observed between BMI and metabolic disturbance. Obesity-related metabolic disorders can substantially affect the activity of the fibrinolytic system, constituting a major risk factor for both arterial and venous thrombosis [54]. During pregnancy, the uterine spiral arteries undergo invasive remodeling mediated by extravillous trophoblasts (EVTs), which, together with the formation of the intervillous space, establish an efficient perfusion network supplying the embryo with essential oxygen and nutrients to meet metabolic demands throughout gestation [55]. Uterine artery blood flow parameters are widely used to assess uteroplacental circulation during early pregnancy and serve as important indicators of placental perfusion status [56]. Perdu et al. proposed that maternal obesity may impair vascular remodeling at the uteroplacental interface by inhibiting natural killer (NK) cell–mediated remodeling of uterine arteries and interfering with normal trophoblast differentiation [57]. Our study further found a positive correlation between maternal BMI and uterine artery blood flow resistance, suggesting that obese pregnant women are more prone to uterine microcirculatory dysfunction. This finding is highly consistent with previous related studies [58]. Therefore, it is recommended that pregnant women with high BMI undergo enhanced assessment and monitoring of uteroplacental microcirculation function early in pregnancy to prevent adverse pregnancy outcomes associated with inadequate uterine perfusion or thrombotic events.
Regarding pregnancy outcomes and neonatal status, our study found that underweight pregnant women were more prone to preterm birth and delivering low birth weight infants. This observation is consistent with conclusions from previous large-scale studies [59]. Such adverse outcomes are likely related to factors including maternal malnutrition, intrauterine growth restriction (IUGR), and cervical insufficiency. In contrast, neonates born to obese mothers typically had higher birth weights, with a significantly increased risk of macrosomia. This, in turn, raises the likelihood of obstetric complications such as difficult labor and intrapartum hemorrhage and represents one of the major contributors to elevated cesarean section rates. Additionally, previous research has demonstrated that maternal obesity can influence offspring body weight and endocrine–metabolic function through genetic and epigenetic mechanisms [21]. Therefore, it is essential to prioritize BMI management during the preconception period by promoting balanced nutrition and appropriate exercise to optimize weight control strategies. For pregnant women with elevated BMI, it is recommended to closely monitor glucose and lipid metabolism and track gestational weight gain. When necessary, dietary interventions emphasizing low glycemic load and reduced fat intake should be implemented to lower the risk of gestational diabetes mellitus, gestational hypertension, and other adverse pregnancy outcomes.
The RT-qPCR and Western blot analyses in this study showed that obesity may significantly increase miscarriage risk by suppressing insulin signaling and angiogenic networks while activating inflammatory and oxidative stress–related pathways, thereby altering the metabolic and immune microenvironment of decidual tissue. Obesity-related systemic low-grade inflammation can upregulate TLR4 expression via fatty acids and endotoxins, which, in turn, promote HMGB1 release (either passively or actively). This process further activates the TLR4/NF-κB signaling cascade, significantly increasing transcription of pro-inflammatory cytokines such as TNF-α and IL-6. Persistently elevated levels of inflammatory mediators not only maintain a chronic inflammatory state but also suppress SIRT1 transcription and activity. The resulting loss of SIRT1-mediated deacetylation of NF-κB amplifies sustained inflammatory activation. Chronic inflammation and oxidative stress stimulate HIF-1α accumulation, reflecting local uterine hypoxic stress. However, unlike the typical adaptive hypoxic response, high-fat diet–induced inflammation and metabolic disturbances impair the functional regulation of angiogenic genes by HIF-1α, leading to downregulation of VEGFA and its receptor VEGFR-1, which suppresses endothelial cell proliferation and neovascularization. The reduced expression of CD31 further indicates compromised remodeling of the uterine vascular network and diminished angiogenic capacity. The observed upregulation of GLUT1 expression, consistent with increased HIF-1α, suggests that glucose transport is enhanced via insulin-independent pathways in response to localized hypoxia. In contrast, the decreased expression of GLUT4 and phosphorylated IRS1 proteins reflects impaired insulin signaling and a shift away from normal insulin-dependent glucose metabolism. While total IRS1 levels remained unchanged, reduced p-IRS1 levels indicate suppressed activation status, highlighting significant insulin resistance within uterine tissue. Notably, SGK1 expression showed no marked difference, suggesting a limited role in mediating insulin resistance in this context.
To our knowledge, this study is the first to systematically analyze the association between early pregnancy clinical indicators and maternal BMI. However, our investigation primarily focused on differences in key indicators across BMI groups, and the underlying mechanistic relationships among these markers warrant further exploration. Additionally, as a retrospective study, there are inherent limitations, such as the inability to obtain more comprehensive metabolic, inflammatory, and immunological data, and the difficulty in fully excluding the effects of concomitant medications or other confounding factors on the results. Therefore, future prospective, multicenter, large-sample mechanistic studies are needed to validate these findings and elucidate their causal relationships.
7. Conclusion
The results of this study demonstrated that during gestational weeks 6–8, underweight pregnant women exhibited relatively lower serum levels of hCG and E2, while P4 levels were comparatively higher. In contrast, women with high BMI showed a general reduction in all three hormonal indicators. Additionally, obese pregnant women presented with elevated uterine artery resistance indices and significant glucose and lipid metabolic disturbances. These findings provide important clinical reference values for interpreting early pregnancy hormonal and metabolic profiles in women with varying BMI categories.
It is noteworthy that the influence of maternal BMI on early embryonic survival appears to be relatively limited, which may help to alleviate concerns among pregnant women with abnormal BMI. However, deviations from a normal BMI remain strongly associated with an elevated risk of adverse pregnancy outcomes in later gestation, including preterm birth, LBW, HBW, and cesarean delivery. Importantly, while obesity may have a genetic basis, epigenetic modifications shaped by lifestyle, nutrition, and environmental exposures can interact with these genetic susceptibilities, potentially influencing endocrine and metabolic health in the offspring.
Moreover, obesity exhibits a certain degree of metabolic and genetic predisposition. Maternal obesity may induce characteristic alterations in endometrial and placental tissues, manifesting as a dysregulated interplay of inflammation, hypoxia, metabolic imbalance, and impaired angiogenesis. Chronic obesity-related inflammation activates the HMGB1/TLR4/NF-κB signaling cascade, while concurrent downregulation of SIRT1 further amplifies pro-inflammatory signaling. Although hypoxic stress results in upregulation of HIF-1α, it fails to effectively induce angiogenesis. Impairment of insulin signaling leads to downregulation of GLUT4 and disrupts glucose utilization. This multidimensional dysregulation not only damages decidual function and adaptive vascular remodeling but may also compromise maternal–fetal immune tolerance and energy homeostasis, thereby constituting an important molecular basis for adverse pregnancy outcomes.
Therefore, it is recommended to strengthen BMI management before and during pregnancy, with close monitoring of glucose–lipid metabolism and inflammatory markers. Rational control of gestational weight gain through nutritional counseling and lifestyle interventions is essential to prevent obesity-related pregnancy complications and improve maternal and neonatal outcomes.
8. Limitations
This study has several limitations that warrant consideration and should be addressed in future research. First, due to its retrospective design, the sample size was constrained by the availability of existing clinical data. In an effort to maximize the sample size, potential confounding variables such as dietary patterns, educational level, and occupation were not controlled, which may have introduced selection bias. Second, the relatively small number of obese pregnant participants may have limited the statistical power and reduced the generalizability of the findings. Third, owing to the retrospective nature of the study, there was a lack of systematic monitoring of body weight dynamics and standardized specimen collection during pregnancy. To address this gap, we employed a mouse model for weight assessment and mechanistic exploration. However, due to species-specific differences between mice and humans, the translational relevance of animal findings may be limited. Therefore, interpretations of the animal data should be made with caution and considered only as preliminary references for understanding the potential mechanisms underlying gestational weight management.
Supporting information
S3 Table. Basic information on pregnant women.
https://doi.org/10.1371/journal.pone.0333081.s004
(DOCX)
S1 Fig. Changes in body weight and vaginal smears during the modeling process in mice.
(a) Line graph showing body weight gain of female mice during the modeling period. **P < 0.01, ****P < 0.0001. (b) Box plot illustrating body weight increase in the two groups after modeling. ****P < 0.0001. (c) Morphological appearance of mice after modeling (left: control group; right: obese group). (d) Vaginal cytology smears obtained during the modeling process. Scale bar = 40 μm.
https://doi.org/10.1371/journal.pone.0333081.s005
(TIF)
References
- 1. Muhammad T, Wan Y, Lv Y, Li H, Naushad W, Chan W-Y, et al. Maternal obesity: A potential disruptor of female fertility and current interventions to reduce associated risks. Obes Rev. 2023;24(10):e13603. pmid:37452501
- 2. Poston L, Caleyachetty R, Cnattingius S, Corvalán C, Uauy R, Herring S, et al. Preconceptional and maternal obesity: epidemiology and health consequences. Lancet Diabetes Endocrinol. 2016;4(12):1025–36. pmid:27743975
- 3. Metwally M, Tuckerman EM, Laird SM, Ledger WL, Li TC. Impact of high body mass index on endometrial morphology and function in the peri-implantation period in women with recurrent miscarriage. Reprod Biomed Online. 2007;14(3):328–34. pmid:17390512
- 4. Mintziori G, Nigdelis MP, Mathew H, Mousiolis A, Goulis DG, Mantzoros CS. The effect of excess body fat on female and male reproduction. Metabolism. 2020;107:154193. pmid:32119876
- 5. Moragianni VA, Jones S-ML, Ryley DA. The effect of body mass index on the outcomes of first assisted reproductive technology cycles. Fertil Steril. 2012;98(1):102–8. pmid:22584023
- 6. Zheng Y, Dong X, Chen B, Dai J, Yang W, Ai J, et al. Body mass index is associated with miscarriage rate and perinatal outcomes in cycles with frozen-thawed single blastocyst transfer: a retrospective cohort study. BMC Pregnancy Childbirth. 2022;22(1):118. pmid:35148705
- 7. Tang J, Zhu X, Chen Y, Huang D, Tiemeier H, Chen R, et al. Association of maternal pre-pregnancy low or increased body mass index with adverse pregnancy outcomes. Sci Rep. 2021;11(1):3831. pmid:33589654
- 8. Zhang CXW, Candia AA, Sferruzzi-Perri AN. Placental inflammation, oxidative stress, and fetal outcomes in maternal obesity. Trends Endocrinol Metab. 2024;35(7):638–47. pmid:38418281
- 9. Chen LL, Lin X, Wang Z. Effects of abnormal changes of sex hormones in early pregnancy on threatened abortion and analysis of risk factors. Matern Child Health Care China. 2022;37(18):3389–93.
- 10. Sun Y, Shen Z, Zhan Y, Wang Y, Ma S, Zhang S, et al. Effects of pre-pregnancy body mass index and gestational weight gain on maternal and infant complications. BMC Pregnancy Childbirth. 2020;20(1):390. pmid:32631269
- 11. Xiong Y, Wang J, Huang S, Liu C, Liu Y, Qi Y, et al. Association between maternal prepregnancy body mass index and pregnancy outcomes following assisted reproductive technology: A systematic review and dose-response meta-analysis. Obes Rev. 2021;22(6):e13219. pmid:33554474
- 12. Howell KR, Powell TL. Effects of maternal obesity on placental function and fetal development. Reproduction. 2017;153(3):R97–108. pmid:27864335
- 13. Weiss JL, Malone FD, Vidaver J, Ball RH, Nyberg DA, Comstock CH, et al. Threatened abortion: A risk factor for poor pregnancy outcome, a population-based screening study. Am J Obstet Gynecol. 2004;190(3):745–50. pmid:15042008
- 14. Lou YY, Fu P, Liu XR, Jiang P, WAng SX, Zhao HL, et al. Relation of Serum Estradiol and Progesterone Levels with Abortive Anticipation in Pregnant Women with Fetal Irritability and Vaginal Bleeding. Chinese J Integr Tradit West Med. 2010;30(11):1153–6.
- 15. Prevention CSO, Section C, Section CNSCN, Section CPMABH, Sports CPMA, Section H. Expert consensus on obesity prevention and treatment in China. Chinese Prevent Med. 2022;23(05):321–39.
- 16. International Association of Diabetes and Pregnancy Study Groups Consensus Panel, Metzger BE, Gabbe SG, Persson B, Buchanan TA, Catalano PA, et al. International association of diabetes and pregnancy study groups recommendations on the diagnosis and classification of hyperglycemia in pregnancy. Diabetes Care. 2010;33(3):676–82. pmid:20190296
- 17.
Organization WH. International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD-10)-WHO Version. 2016.
- 18. Bartha I, Joumady I, Cuerva M, Bartha JL. The effect of maternal obesity and lipid profile on first-trimester serum progesterone levels. Am J Obstet Gynecol MFM. 2023;5(7):100959. pmid:37030509
- 19. Yong W, Wang J, Leng Y, Li L, Wang H. Role of Obesity in Female Reproduction. Int J Med Sci. 2023;20(3):366–75. pmid:36860674
- 20. Kawai T, Autieri MV, Scalia R. Adipose tissue inflammation and metabolic dysfunction in obesity. Am J Physiol Cell Physiol. 2021;320(3):C375–91. pmid:33356944
- 21. Catalano PM, Shankar K. Obesity and pregnancy: mechanisms of short term and long term adverse consequences for mother and child. BMJ. 2017;356:16. pmid:28179267
- 22. Xu P, Huang B-Y, Zhan J-H, Liu M-T, Fu Y, Su Y-Q, et al. Insulin Reduces Reaction of Follicular Granulosa Cells to FSH Stimulation in Women With Obesity-Related Infertility During IVF. J Clin Endocrinol Metab. 2019;104(7):2547–60. pmid:30476103
- 23. Cheng J, Yang S, Ma H, Liang Y, Zhao J. Estradiol (E2) Reduction Adversely Affect the Embryo Quality and Clinical Outcomes of In Vitro Fertilization and Embryo transfer (IVF-ET). J Healthc Eng. 2022;2022:2473876. pmid:35432835
- 24. Luke B, Brown MB, Stern JE, Missmer SA, Fujimoto VY, Leach R, et al. Female obesity adversely affects assisted reproductive technology (ART) pregnancy and live birth rates. Hum Reprod. 2011;26(1):245–52. pmid:21071489
- 25. Zhu S-M, Zhang H-Q, Li C, Zhang C, Yu J-L, Wu Y-T, et al. Maternal lipid profile during early pregnancy and birth weight: A retrospective study. Front Endocrinol (Lausanne). 2022;13:951871. pmid:36187100
- 26. Zhu X-Z, Deng Z-M, Dai F-F, Liu H, Cheng Y-X. The impact of early pregnancy metabolic disorders on pregnancy outcome and the specific mechanism. Eur J Med Res. 2023;28(1):197. pmid:37355665
- 27. Liu NH, Zhou CJ, Chen YX, Zhao JF. The involvement of osteopontin and β3 integrin in implantation and endometrial receptivity in an early mouse pregnancy model. Eur J Obstet Gynecol Reprod Biol. 2013;171(1):195-.
- 28. Wang XM. Value of dynamic monitoring of the levels of estrogen, progesterone, and β-human chorionic gonadotropin of pregnant women with recurrent spontaneous abortion during the first trimester of pregnancy for predicting their spontaneous abortion again. Chinese J Fam Plann. 2022;30(06):1318–22.
- 29. Parisi F, Fenizia C, Introini A, Zavatta A, Scaccabarozzi C, Biasin M, et al. The pathophysiological role of estrogens in the initial stages of pregnancy: molecular mechanisms and clinical implications for pregnancy outcome from the periconceptional period to end of the first trimester. Hum Reprod Update. 2023;29(6):699–720. pmid:37353909
- 30.
Wu YH. Analysis of the predictive value of β-HCG, E2, P for pregnancy outcome and related factors and TCM syndrome elements in threatened abortion. Zhejiang University of Traditional Chinese Medicine; 2022.
- 31. Khatpe AS, Adebayo AK, Herodotou CA, Kumar B, Nakshatri H. Nexus between PI3K/AKT and Estrogen Receptor Signaling in Breast Cancer. Cancers (Basel). 2021;13(3):369. pmid:33498407
- 32. Lou Y, Hu M, Wang Q, Yuan M, Wang N, Le F, et al. Estradiol Suppresses TLR4-triggered Apoptosis of Decidual Stromal Cells and Drives an Anti-inflammatory TH2 Shift by Activating SGK1. Int J Biol Sci. 2017;13(4):434–48. pmid:28529452
- 33. Liang J, Zhang B, Hu Y, Na Z, Li D. Effects of steroid hormones on lipid metabolism in sexual dimorphism: A Mendelian randomization study. Front Endocrinol (Lausanne). 2023;13:1119154. pmid:36726474
- 34. Vondra S, Kunihs V, Eberhart T, Eigner K, Bauer R, Haslinger P, et al. Metabolism of cholesterol and progesterone is differentially regulated in primary trophoblastic subtypes and might be disturbed in recurrent miscarriages. J Lipid Res. 2019;60(11):1922–34. pmid:31530576
- 35. Lou Y, Fu Z, Tian Y, Hu M, Wang Q, Zhou Y, et al. Estrogen-sensitive activation of SGK1 induces M2 macrophages with anti-inflammatory properties and a Th2 response at the maternal-fetal interface. Reprod Biol Endocrinol. 2023;21(1):50. pmid:37226177
- 36. Barrett ES, Mbowe O, Thurston SW, Butts S, Wang C, Nguyen R, et al. Predictors of Steroid Hormone Concentrations in Early Pregnancy: Results from a Multi-Center Cohort. Matern Child Health J. 2019;23(3):397–407. pmid:30659461
- 37. Noyola-Martínez N, Halhali A, Barrera D. Steroid hormones and pregnancy. Gynecol Endocrinol. 2019;35(5):376–84. pmid:30793997
- 38. Pang Y, Thomas P. Progesterone induces relaxation of human umbilical cord vascular smooth muscle cells through mPRα (PAQR7). Mol Cell Endocrinol. 2018;474:20–34. pmid:29428395
- 39. Wahabi HA, Fayed AA, Esmaeil SA, Bahkali KH. Progestogen for treating threatened miscarriage. Cochrane Database Syst Rev. 2018;8(8):CD005943. pmid:30081430
- 40. Long Y, Wang Y-C, Yuan D-Z, Dai X-H, Liao L-C, Zhang X-Q, et al. GLUT4 in Mouse Endometrial Epithelium: Roles in Embryonic Development and Implantation. Front Physiol. 2021;12:674924. pmid:34248664
- 41. Copps KD, White MF. Regulation of insulin sensitivity by serine/threonine phosphorylation of insulin receptor substrate proteins IRS1 and IRS2. Diabetologia. 2012;55(10):2565–82. pmid:22869320
- 42. Czech MP. Insulin action and resistance in obesity and type 2 diabetes. Nat Med. 2017;23(7):804–14. pmid:28697184
- 43. Namvarsigaroudi N, Tahmasebi Fard Z. Endometrial Expression of Insulin Signaling Pathway Genes in Pregnancy Leading to Abortion under 20 Weeks in Infertile Women: A Case-Control Study. Int J Fertil Steril. 2022;16(4):286–91. pmid:36273315
- 44. Kou J, Yuan E, Yan G. Association between HIF-1α, BNIP3, and autophagy in the chorionic villi of missed abortion. J Obstet Gynaecol Res. 2023;49(7):1710–6. pmid:37150840
- 45. Guo X, Yi H, Li TC, Wang Y, Wang H, Chen X. Role of Vascular Endothelial Growth Factor (VEGF) in Human Embryo Implantation: Clinical Implications. Biomolecules. 2021;11(2):253. pmid:33578823
- 46. Apte RS, Chen DS, Ferrara N. VEGF in Signaling and Disease: Beyond Discovery and Development. Cell. 2019;176(6):1248–64. pmid:30849371
- 47. Chen R, Kang R, Tang D. The mechanism of HMGB1 secretion and release. Exp Mol Med. 2022;54(2):91–102. pmid:35217834
- 48. Hu M, Zhang Y, Lu Y, Han J, Guo T, Cui P, et al. Regulatory mechanisms of HMGB1 and its receptors in polycystic ovary syndrome-driven gravid uterine inflammation. FEBS J. 2023;290(7):1874–906. pmid:36380688
- 49. Denizli M, Capitano ML, Kua KL. Maternal obesity and the impact of associated early-life inflammation on long-term health of offspring. Front Cell Infect Microbiol. 2022;12:940937. pmid:36189369
- 50. Xu S, Lu F, Gao J, Yuan Y. Inflammation-mediated metabolic regulation in adipose tissue. Obes Rev. 2024;25(6):e13724. pmid:38408757
- 51. Yu Q, Dong L, Li Y, Liu G. SIRT1 and HIF1α signaling in metabolism and immune responses. Cancer Lett. 2018;418:20–6. pmid:29306019
- 52. Boutari C, Pappas PD, Mintziori G, Nigdelis MP, Athanasiadis L, Goulis DG, et al. The effect of underweight on female and male reproduction. Metabolism. 2020;107:154229. pmid:32289345
- 53. Lassance L, Haghiac M, Minium J, Catalano P, Hauguel-de Mouzon S. Obesity-induced down-regulation of the mitochondrial translocator protein (TSPO) impairs placental steroid production. J Clin Endocrinol Metab. 2015;100(1):E11-8. pmid:25322273
- 54. Borch KH, Nyegaard C, Hansen J-B, Mathiesen EB, Njølstad I, Wilsgaard T, et al. Joint effects of obesity and body height on the risk of venous thromboembolism: the Tromsø Study. Arterioscler Thromb Vasc Biol. 2011;31(6):1439–44. pmid:21527750
- 55. Albrecht ED, Pepe GJ. Regulation of Uterine Spiral Artery Remodeling: a Review. Reprod Sci. 2020;27(10):1932–42. pmid:32548805
- 56. Moore LG, Wesolowski SR, Lorca RA, Murray AJ, Julian CG. Why is human uterine artery blood flow during pregnancy so high?. Am J Physiol Regul Integr Comp Physiol. 2022;323(5):R694–9. pmid:36094446
- 57. Perdu S, Castellana B, Kim Y, Chan K, DeLuca L, Beristain AG. Maternal obesity drives functional alterations in uterine NK cells. JCI Insight. 2016;1(11):e85560. pmid:27699222
- 58. Habets DHJ, Schiffer VMMM, Kraneburg LPA, de Krom FJW, Gürtekin I, van Bree BE, et al. Preconceptional evaluation of women with recurrent pregnancy loss: the additional value of assessing vascular and metabolic status. BMC Pregnancy Childbirth. 2022;22(1):75. pmid:35086506
- 59. Nakanishi K, Saijo Y, Yoshioka E, Sato Y, Kato Y, Nagaya K, et al. Severity of low pre-pregnancy body mass index and perinatal outcomes: the Japan Environment and Children’s Study. BMC Pregnancy Childbirth. 2022;22(1):121. pmid:35148693