Correlation between chronic low-grade inflammation and glucose and lipid metabolism indicators in polycystic ovary syndrome

Abstract

Objective

The purpose of this study was to explore the correlation between inflammatory indicators and blood lipids and to further provide a theoretical basis for the diagnosis and treatment of clinical polycystic ovary syndrome (PCOS).

Methods

Whole-blood cell counts and hormone and blood lipid levels were measured in 110 patients with PCOS and 126 healthy women. The differences in the above levels and the correlation between inflammation and blood lipid levels in the two groups were determined, and classified according to BMI. Differences in inflammatory indices were also analyzed. The independent risk factors for PCOS were analyzed by binary logistic regression.

Results

The PCOS group had greater BMI and greater body weight than the control group. The inflammatory indicators WBC, neutrophil, lymphocyte, monocyte counts and the NLR were significantly higher than those of the control group. It had higher testosterone (TSTO), triglyceride (TG) and total cholesterol (TC) levels. Correlation analysis showed that leukocyte and neutrophil counts were positively correlated with TSTO and TG levels and negatively correlated with HDL. In the BMI ≥ 24 and BMI < 24 groups, WBC was higher in PCOS patients than in healthy controls. Logistic regression showed that TSTO, TG and FSH were independent risk factors for PCOS.

Conclusion

Inflammatory markers are correlated with blood lipids in PCOS. During the treatment of PCOS, blood lipids and serum inflammatory factors should be monitored.

Keywords:

• PCOS
• inflammation
• glucose metabolism
• lipid metabolism

Introduction

Polycystic ovary syndrome (PCOS) is a heterogeneous endocrine disease that is usually characterized by ovarian enlargement and dysfunction, elevated androgen levels, and insulin resistance [1]. PCOS affects 5%–10% of women of childbearing age [2]. PCOS often manifests as endocrine and metabolic disorders and is the leading cause of anovulatory infertility [3]. PCOS patients often exhibit complications such as obesity and disorders of fat metabolism, which are the pathophysiological basis of insulin resistance [4]. Insulin acts as a co-gonadotropin on the ovary, promoting the secretion of androgens by the adrenal gland and the release of luteinizing hormone (LH). Excessive androgens promote visceral obesity and further lead to insulin resistance and hyperinsulinemia. Increased insulin, leading to the release of androgens, further inhibits follicle-stimulating hormone (FSH) aromatase activity and elevates the production of LH and LH receptors by ovarian granulosa cells, which in turn lead to a decrease in estradiol. The imbalance of androgens and estrogen may abnormally deviate the LH:FSH ratio in ovarian granulosa cells, leading to ovarian dysfunction, which is considered a potential cause of PCOS [5]. The exact pathogenesis of PCOS has not been fully elucidated, but research on the pathogenesis of PCOS and the effects of glucose and lipid metabolism has not been performed [6–8].

Chronic low-grade inflammation is closely related to the development of a variety of metabolic diseases, especially insulin resistance and abnormal glucose and lipid metabolism. Metabolic syndrome is an important feature of PCOS [9]. Therefore, inflammation may be a risk factor for PCOS and inflammatory factors and chemokines maybe the immune mechanisms that trigger the occurrence of PCOS [10]. Previous studies have reported that the levels of interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) in women with PCOS are higher than those in healthy women. The reason may be that hyperandrogenemia stimulates the infiltration of monocytes into the ovary, which leads to chronic inflammation of ovarian tissue and further affects the maturation of ovarian follicles during ovarian development [11, 12]. In patients with PCOS, the keys to PCOS control are weight loss and a low-fat, sugar-free diet. Low-grade chronic inflammation in patients with PCOS is also related to the accumulation of visceral fat and the necrosis of adipocytes after hypoxia [13, 14]. Based on the above theory, we detected routine blood indices and calculated the correlations between blood indicators, blood lipids and sex hormones, to further provide a theoretical basis for the prevention and treatment of clinical PCOS.

Methods

Study population

In this study, 110 patients with PCOS diagnosed by the gynecology department in West China Second University Hospital from January 2022 to April 2023 were analyzed retrospectively, and 126 healthy women were selected as the control group from patients. This study was approved by the Ethics Committee of West China Second University Hospital and followed the principles of the Helsinki Declaration. The diagnosis of PCOS was determined according to the Rotterdam standard criteria [15]. The inclusion criteria were as follows: (1) oligoovulation or anovulation; and (2) clinical manifestations of hyperandrogenemia or hyperandrogenism (such as hirsutism, acne, etc.); (3) Ultrasonography was performed 3–5 days after the menstrual cycle or progesterone withdrawal and showed that both ovaries had ≥ 12 small follicles with a diameter of 2 ∼ 9 mm, ovarian polycystic changes, and/or ovarian enlargement (each side > 10 ml). The exclusion criteria were as follows: (1) not meeting any of the Rotterdam diagnostic criteria; (2) hormonal drugs within three months before treatment; (3) other endocrine or metabolic diseases that cause androgen increases; and (4) previous ovarian surgery, early-onset ovarian insufficiency or other ovarian diseases. The inclusion criteria for the control group were as follows: (1) menstruation rule, and no ovulation dysfunction; (2) normal basic hormone levels; (3) a normal uterine cavity; and (4) and ultrasound revealing that the shape of the ovary was normal.

Laboratory tests

Peripheral venous blood was collected in a vacuum tube on the third day of menstruation and after the patients had fasted for 12 h. Hemogram samples were collected in EDTA anticoagulant tubes, and serum samples were collected in standard gel separation tubes for biochemical detection. All the samples were analyzed within 1 h after collection. The whole-blood cell count (CBC) included the white blood cell count (WBC), platelet count (PLT), neutrophil count, monocyte count and lymphocyte count. The neutrophil-to-lymphocyte ratio (NLR) was calculated as the number of neutrophils divided by the number of lymphocytes, the platelet-to-lymphocyte ratio (PLR) was calculated as the number of platelets divided by the number of lymphocytes, and the monocyte-to-lymphocyte ratio (MLR) was calculated as the number of monocytes divided by the number of lymphocytes. All CBC analyses were performed using a Sysmex hematology analyzer (Sysmex, Hematology Analyzer, Kobe, Japan). Estradiol (E), follicle stimulating hormone (FSH), luteinizing hormone (LH), progesterone (P), testosterone (T), total cholesterol (TC), triglyceride (TG), low-density lipoprotein (LDL) and high-density lipoprotein (HDL) levels were detected by an automatic chemical immunoassay system (Atellica, Siemens, Germany).

Statistical analysis

All the data were analyzed with the statistical software SPSS 22.0 (IBM, Chicago, USA). Normally distributed data are presented as the mean ± standard deviation, and nonnormally distributed data are presented as the median and quartile range (IQR). The differences between the two groups were evaluated by Student’s t test and the Mann–Whitney U test. The Spearman correlation coefficient was calculated to determine the correlations between blood inflammation indicators and blood lipid indicators in patients with PCOS. Multivariate logistic regression analysis was used to predict the risk factors for PCOS. P < 0.05 was considered statistically significant.

Results

1. Comparison of basic data between the PCOS and control groups

   By comparing the basic data of the control group and the PCOS group, we found that there was no significant difference in age between the two groups. The body weight and BMI of the PCOS group were significantly higher than those of the control group (Table 1).

2. Comparison of plasma inflammatory indicators between the PCOS and control groups

   By comparing the blood inflammatory indices between the PCOS group and the control group, we found that the WBC, the absolute number of neutrophils, lymphocytes, and monocytes, and the NLR were greater in the PCOS group (P < 0.05, Table 2). There was no difference in the PLT, PLR or MLR between the two groups (P > 0.05, Table 2).

3. Comparison of serum hormones and blood lipids between the PCOS and control groups

   Compared with those in the control group, the PCOS group had higher LH and TSTO but lower FSH (P < 0.05, Table 3). When we compared their blood lipid levels, TC and TGs levels were significantly higher in the PCOS group (P < 0.05, Table 3).

4. Correlations between plasma inflammatory marker and levels of hormone and blood lipid levels

   WBC was positively correlated with testosterone (r = 0.160, P = 0.014) and TGs (r = 0.252, P < 0.001) and negatively correlated with HDL (r = −0.413, P < 0.001). The absolute number of neutrophils was positively correlated with testosterone (r = 0.165, P = 0.011) and triglycerides (r = 0.221, P = 0.001) but negatively correlated with HDL cholesterol (r = −0.373, P < 0.001).

5. Comparison of plasma inflammatory indicators between the PCOS and control groups with BMI ≥ 24

   Among the people with BMI ≥ 24 were 45 individuals had PCOS and 34 were healthy controls. By comparing the inflammatory indices between the two groups, we found that there were significant differences in the WBC and neutrophil counts between the two groups (P < 0.05, Table 4). Moreover, there were no significant differences in the PLT, lymphocyte count, monocytes, NLR, PLR or MLR.

6. Comparison of plasma inflammatory indicators between the PCOS and control groups with BMI < 24

   Among the people with BMI< 24 were 65 individuals had PCOS and 92 were healthy controls. By comparing the inflammatory indexes between the two groups, we found that there were significant differences in WBC, PLT, neutrophils, lymphocytes and monocytes between the two groups (P < 0.05, Table 5). There were no significant differences in the NLR, PLR or MLR.

7. Prediction of independent risk factors for PCOS

   After adjusting for age, we included indicators with significant differences between the two groups. After binary logistic regression analysis, we found that FSH, TGs and testosterone levels were independent risk factors for PCOS (Table 6).

Table 1. Basic data of the control and PCOS groups.

Variables	PCOS group (n = 110)	Control group (n = 126)	P
Age (years)	28.55 ± 4.65	29.71 ± 4.41	0.742
Weight (kg)	56.89 ± 6.30	54.15±±7.10	0.002
BMI (kg/m^2)	23.64 ± 3.31	21.81 ± 3.38	<0.001

Table 2. Comparison of inflammatory markers between the control and PCOS groups.

Variables	PCOS group (n = 110)	Control group (n = 126)	P
WBC	6.57 ± 1.67	5.65 ± 1.10	<0.001
PLT	261.43 ± 70.31	234.21 ± 61.32	0.213
Neutrophils	3.88 ± 1.23	3.18 ± 0.85	0.000
Lymphocyte	2.12 ± 0.58	1.95 ± 0.41	0.006
Monocyte	0.40 ± 0.13	0.36 ± 0.09	0.001
NLR	1.92 ± 0.72	1.69 ± 0.51	0.003
PLR	127.67 ± 36.55	123.02 ± 32.46	0.286
MLR	0.20 ± 0.06	0.19 ± 0.05	0.123

WBC, white blood cell count; PLT, platelets; NLR, neutrophil-to-lymphocyte ratio; PLR, platelet-to-lymphocyte ratio; MLR, monocyte-to-lymphocyte ratio.

Table 3. Comparison of hormone and blood lipid indicators between the control and PCOS groups.

Variables	PCOS group	Control group	P
E	67.08 (43.14, 75.56)	58.26(39.31, 75.17)	0.094
LH	10.27(5.09, 15.28)	8.06 (3.76, 8.46)	<0.001
FSH	5.95(4.68, 7.02)	6.78 (5.36, 7.78)	0.002
PRL	13.69(7.92, 12.44)	12.31 (5.36, 7.78)	0.169
P	1.16(0.40, 0.73)	1.53 (0.46, 0.67)	0.609
TSTO	33.07(25.16, 40.86)	25.26 (19.99, 29.85)	0.000
TC	4.94 ± 1.11	4.94 ± 0.75	0.030
TG	1.69 ± 1.52	0.98 ± 0.43	<0.001
HDL	1.25 ± 0.33	1.51 ± 0.32	0.646
LDL	2.87 ± 0.84	2.66 ± 0.65	0.166

E, Estradiol; FSH, follicle stimulating hormone; LH, luteinizing hormone; P, progesterone; TSTO, testosterone; TC, total cholesterol; TG, triglyceride; LDL, low-density lipoprotein; HDL, high-density lipoprotein.

Table 4. Comparison of inflammatory markers between the control and PCOS groups with BMI ≥ 24.

Variables	PCOS group (n = 45)	Control group (n = 34)	P
WBC	6.49 ± 1.52	5.78 ± 1.23	0.029
PLT	249.07 ± 67.88	234.06 ± 58.33	0.411
Neutrophils	3.95 ± 1.25	3.37 ± 0.98	0.027
Lymphocyte	2.01 ± 0.56	1.91 ± 0.39	0.359
Monocyte	0.39 ± 0.12	0.37 ± 0.10	0.227
NLR	2.09 ± 0.86	1.81 ± 0.56	0.101
PLR	128.82 ± 39.36	127.12 ± 31.26	0.837
MLR	0.20 ± 0.06	0.19 ± 0.06	0.610

WBC, white blood cell count; PLT, platelets; NLR, neutrophil-to-lymphocyte ratio; PLR, platelet-to-lymphocyte ratio; MLR, monocyte-to-lymphocyte ratio.

Table 5. Comparison of inflammatory markers between the control and PCOS groups with BMI < 24.

Variables	PCOS group (n = 65)	Control group (n = 92)	P
WBC	6.63 ± 1.78	5.61 ± 1.06	<0.001
PLT	269.98 ± 71.21	233.15 ± 62.67	0.001
Neutrophils	3.84 ± 1.24	3.12 ± 0.79	<0.001
Lymphocyte	2.20 ± 0.58	1.96 ± 0.42	0.003
Monocyte	0.41 ± 0.13	0.36 ± 0.09	0.020
NLR	1.79 ± 0.58	1.64 ± 0.48	0.078
PLR	126.87 ± 34.77	121.51 ± 32.93	0.328
MLR	0.19 ± 0.06	0.19 ± 0.05	0.985

WBC, white blood cell count; PLT, platelets; NLR, neutrophil-to-lymphocyte ratio; PLR, platelet-to-lymphocyte ratio; MLR, monocyte-to-lymphocyte ratio.

Table 6. Independent risk factors for PCOS among inflammatory factors, blood lipids and hormones.

Variables	OR	95%CI	P
FSH	1.258	1.039–1.522	0.019
TSTO	0.892	0.853–0.932	<0.001
TG	0.265	0.109–0.643	0.009

FSH, follicle stimulating hormone; TSTO, testosterone; TG, triglyceride.

Discussion

PCOS is a complex endocrine disorder that leads to hyperandrogenemia, insulin resistance and abnormal glucose and lipid metabolism. In recent years, as the incidence of PCOS has increased annually, it has aroused widespread concern [16]. Most of the studies on PCOS have focused on the role of androgens and insulin resistance in the progression of the disease [17]. Insulin can directly or indirectly produce and secrete estrogen by stimulating ovarian epithelial cells. However, hyperandrogenaemia further reduces the clearance of insulin and further stimulates the release of TGs, resulting in abnormal blood lipid metabolism. The imbalances in the above indicators reciprocally promote each other [18, 19]. In our study, the testosterone level in the PCOS group was significantly higher than that in the control group, consistent with previous reports. Hyperandrogenemia in patients with PCOS may activate the expression of reactive oxygen species and cytokines and the NF-γB pathway in the ovary, and further cause an ovarian immune response, resulting in further aggravation of hyperandrogenemia [20]. However, the manifestations of PCOS cannot be separated from disordered metabolic function. Patients with PCOS can exhibit signs of abnormal blood lipid metabolism, such as insulin resistance and elevated levels of serum TC, TGs and LDL cholesterol [4]. In our study, the levels of TC and TGs in the PCOS group were significantly higher than those in the control group. Moreover, the body weight and BMI level in the PCOS group were significantly higher than those in the control group. Thus, the occurrence of PCOS is closely related to long-term hyperlipidemia and hypercholesterolemia. This is consistent with previous studies showing that the level of testosterone is positively correlated with BMI, TC and TGs [21]. In patients with PCOS, the interaction between abnormal lipid metabolism, obesity and hyperandrogenemia results in a vicious cycle, which constitutes the main metabolic characteristic of metabolic disorders and jointly promotes the development of PCOS.

Recent studies have also shown that inflammation may be a potential risk factor for PCOS [22]. Patients with PCOS are usually obese, and obesity is a disease state characterized by chronic inflammation, which is usually characterized by high levels of proinflammatory cytokines, WBCs, neutrophils, markers of oxidative stress and inflammation-related proteins, including interleukin-1β and IL-18, which are overexpressed in patients with PCOS. An increase in inflammatory factor levels is also one of the causes of hyperandrogenemia [23]. We analyzed the inflammatory indicators of obese patients (BMI ≥ 24) and normal-weight patients (BMI < 24). The WBC and neutrophil counts in PCOS patients are significantly increased, which suggests that chronic inflammation is a factor in PCOS that cannot be ignored, regardless of whether the patient is obese. In previous studies, the increase in WBC count in patients with PCOS is related to chronic low-grade inflammation but not to obesity, which further leads to a significant correlation between metabolism and complications [24]. In the diagnosis of chronic and subclinical inflammation, cytokines such as IL-6 and TNF-α are undoubtedly the most sensitive markers of the inflammatory state [25]. Currently, in routine clinical examinations, the measurement of the above inflammatory markers is limited at the technical level and there is no routine detection method [26, 27]. Therefore, identifying diagnostic indicators of PCOS that can be measured routinely during the clinical checkup is valuable. Routine blood examination is a common inflammatory screening method in clinical practice and is beneficial for the determination of PCOS. Notably, it is widely used in the clinic and there is a certain correlation of PCOS [28]. We also found that in patients with PCOS, WBC and neutrophil counts were positively correlated with testosterone, the key indicator of PCOS and TG, the indicator of lipid metabolism, and negatively correlated with HDL. The multiple disorders of hormone-lipid metabolism and leukocyte parameters suggest that low-grade inflammation and metabolic endocrine syndrome play important roles in the pathogenesis of PCOS. An elevated WBC count is a potential predictor of low-grade inflammation in PCOS patients [29]. Therefore, screening for inflammation and metabolism indicators should be strengthened among women of PCOS.

Conclusion

In our study, there were correlations between blood inflammatory indices and blood lipid and hormone levels in patients with PCOS. Inflammatory indices and lipid metabolism may promote the occurrence of PCOS. Our study suggested that attention should also be given to the abnormalities in lipids and inflammatory indices in the process of diagnosing and treatment of PCOS patients. Of course, a larger sample size is needed to provide a more accurate basis for clinical PCOS diagnosis and treatment.

Disclosure statement

The authors declare that they have participated sufficiently in the work and take responsibility for the appropriate portions of the content. The authors declare no conflicts of interest in this work.

Data availability statement

All relevant data are included in the paper. The datasets used and/or analyzed during the current study available from the corresponding author upon reasonable request.

Additional information

Funding

The clinical case screening and data collection were supported by the Sichuan Science and Technology Program (2023YFS0186)