Abstract
The aim of the study was to investigate the changes in serum glypican 4 (GPC4) and clusterin (CLU) levels in patients with polycystic ovary syndrome (PCOS) as well as their correlation with sex hormones and metabolic parameters. A total of 40 PCOS patients and 40 age-matched healthy women were selected. Serum GPC4 and CLU levels were compared between the PCOS and control groups, and binary logistic regression was used to analyze the relative risk of PCOS at different tertiles of serum GPC4 and CLU concentrations. Stepwise linear regression was used to identify the factors influencing serum GPC4 and CLU levels in PCOS patients. Serum GPC4 (1.82 ± 0.49 vs 1.30 ± 0.61 ng/mL, P < 0.001) and CLU (468.79 ± 92.85 vs 228.59 ± 82.42 µg/mL, P < 0.001) were significantly higher in PCOS patients than in healthy women after adjustment for body mass index (BMI). In the PCOS group, serum GPC4 was positively correlated with follicle-stimulating hormone, fasting plasma glucose (FPG), fasting insulin (FINS), homeostatic model assessment of insulin resistance (HOMA-IR), triglyceride, and CLU (P < 0.05), whereas serum CLU was positively correlated with BMI, FPG, FINS, and HOMA-IR (P < 0.05). Multiple stepwise linear regression analysis showed that HOMA-IR was independently associated with serum GPC4, and BMI and HOMA-IR were independently associated with CLU (P < 0.05). Serum GPC4 and CLU levels were significantly higher in PCOS patients than in healthy women, suggesting that GPC4 and CLU may be markers associated with insulin resistance in women with PCOS.
Introduction
Polycystic ovary syndrome (PCOS) is the most common endocrine disease in women of childbearing age, with an estimated global prevalence of 4–21% (1). PCOS is a heterogeneous disease that is clinically characterized by oligo-ovulatory or anovulatory cycles, ovarian polycystic changes, and signs of hyperandrogenism, such as hirsutism, acne, and androgenic hair loss. Compared to healthy people, individuals with PCOS are prone to various complications, such as metabolic syndrome, diabetes mellitus (DM), nonalcoholic fatty liver disease (NAFLD), cardiovascular disease, endometrial lesions, and hypertension during pregnancy (2, 3, 4, 5). The etiology of PCOS is unclear at present, though environmental and genetic factors are considered potential causes (6). However, increasing evidence (7) shows that insulin resistance and compensatory hyperinsulinemia play an important role in the pathogenesis of PCOS.
The progression of insulin resistance as well as the regulation of glucose and lipid metabolism have been linked to adipocytokines, which are secreted by adipose tissue (8). Adipocytokines, such as adiponectin and visfatin, as well as serine protease inhibitors, are closely related to the development of insulin resistance and the pathophysiology of PCO (9), while glypican 4 (GPC4) and clusterin (CLU), which are also secreted by adipose tissue, are implicated in insulin resistance.
GPC4 is an adipocytokine belonging to the heparan sulfate proteoglycan family (10). GPC4 is anchored to the outer surface of the cell membrane through glycosylphosphatidylinositol (GPI), which can be cleaved by GPI lipase to release GPC4 from the cell membrane surface into the extracellular environment. Thus, GPC4 functions both on the cell membrane and in the extracellular environment. GPC4 was first discovered in mouse kidney and developing brain tissue in 1995 (11). Subsequent research (12) showed that GPC4 is also expressed in visceral and subcutaneous adipose tissue. GPC4 expression is higher in visceral adipose tissue than in subcutaneous adipose tissue, which may partly explain the association of elevated waist-to-hip ratio (WHR) and body mass index (BMI) with an increased risk of cardiovascular and metabolic diseases. Further, a study (13) has revealed that GPC4 levels are related to BMI and insulin sensitivity in humans, and that GPC4 directly binds to insulin receptors in the liver, skeletal muscle, and adipose tissue to enhance insulin signaling. The inhibition of the insulin-mediated phosphorylation of CCAAT/enhancer-binding protein-β (C/EBPβ) prevents adipocyte differentiation in vitro. Yoo et al. (14) studied the correlation of GPC4 levels with body-fat distribution, insulin resistance, arteriosclerosis, and NAFLD in Asian subjects without DM. The researchers found that serum GPC4 levels were significantly higher in men than in women; were positively correlated with WHR and visceral/subcutaneous fat area ratio in men and women; were significantly correlated with cardiometabolic risk factors, such as insulin resistance and arteriosclerosis, in women; and were an independent influencing factor of NAFLD.
CLU, also known as apolipoprotein J, was first isolated from ram testicular fluid in 1983. CLU is a heterodimeric sulfated glycoprotein with a molecular weight of 75–80 kDa (15). In humans, CLU is synthesized in the liver, kidney, brain, ovary, testis, heart, and adipose tissue. CLU is a stress-activated multifunctional glycoprotein that regulates inflammation and lipid transport, inhibits complement proteins, and delays cell apoptosis (16, 17, 18). The downregulation of CLU expression leads to the increased expression of proinflammatory cytokines and ultimately leads to apoptosis (19). In a mouse model of middle cerebral artery occlusion, CLU levels in the cerebral hemisphere were found to be increased during the early ischemic period, suggesting that CLU plays a central role in ischemic injury (20). CLU is also overexpressed in malignant tumors, such as breast, prostate, and lung cancers; hence, CLU overexpression may serve as a prognostic biomarker for aggressive tumors, and CLU inhibition may be an effective treatment to reduce metastasis risk and increase tumor sensitivity to chemotherapy or radiotherapy (21). Ha et al. (22) studied the association between plasma CLU level and DM in patients with Alzheimer disease; the authors found that individuals with Alzheimer disease and abnormal glucose metabolism (including prediabetes and DM) exhibited higher plasma CLU levels, and that CLU was associated with cognitive impairment. In addition, CLU levels were inversely correlated with cognitive function, glycosylated hemoglobin level, and homeostatic model assessment of insulin resistance (HOMA-IR) index but were positively correlated with fasting C-peptide, suggesting that plasma CLU is a potential marker for predicting metabolic disorders and cognitive disorders. Not only is PCOS a chronic low-grade inflammatory disease, but it is also commonly associated with obesity and hyperlipidemia. Therefore, CLU may play a role in the progression of PCOS.
Since PCOS is a chronic endocrine and metabolic disease that is usually accompanied with insulin resistance and metabolic disorders, we aimed to determine whether GPC4 and CLU are involved in the pathophysiology of PCOS. Therefore, the present study explored the changes in serum GPC4 and CLU levels in PCOS patients and analyzed their correlation with the levels of sex hormones and metabolic parameters to provide a basis for the early screening, diagnosis, and treatment of PCOS.
Materials and methods
Patients
This study was performed from January to September 2021. In total, 40 women aged 18–36 years who had been newly diagnosed with PCOS and had not yet received any medication were enrolled in the PCOS group, and 40 age-matched healthy women with regular menstrual cycles and normal ovaries comprised the control group. The diagnosis of PCOS was established using the Rotterdam consensus criteria (23) in patients who met two of the following three criteria: (i) laboratory detection of hyperandrogenism and/or clinical manifestations of hyperandrogenism, (ii) oligomenorrhea or amenorrhea, and (iii) ultrasound imaging showing polycystic ovary. The exclusion criteria were as follows: liver and kidney disorders, DM, heart failure, acute infection, treatment with hormones or medications for insulin sensitivity within the past 3 months, and disorders that cause hyperandrogenemia or ovulatory dysfunction (such as nonclassical congenital adrenal hyperplasia, Cushing syndrome, androgen-secreting tumors of the ovary or adrenal gland, thyroid disease, hyperprolactinemia, hypogonadism, functional hypothalamic amenorrhea, and premature ovarian insufficiency). All subjects voluntarily participated in the present study and signed informed consent forms. The present study was reviewed and approved by the ethics committee of the Second Affiliated Hospital of Nanchang University.
General information collection
We used a unified questionnaire to inquire about the subjects’ personal history (diet, exercise, menstruation, and history of adverse drug reactions). We recorded the participants’ age and measured their height and weight. We calculated and recorded the BMI by using the following formula: BMI = weight/height² (kg/m²).
Measurements of serum GPC4, CLU, sex hormones, and biochemical parameters
All subjects fasted for at least 8 h prior to blood collection. Venous blood samples were collected in the morning, left standing at room temperature (18–25°C) for 1 h, and centrifuged at 3000 rpm for 10 min. The fasting insulin (FINS) level was measured using a chemiluminescence immunoassay, while the fasting plasma glucose (FPG) level was measured using the glucose oxidase method. The levels of total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) were measured using an automatic biochemical analyzer. For the measurement of sex hormone levels, we collected venous blood samples from the healthy controls on days 3–5 of the menstrual cycle; the samples from the women with PCOS were collected either after they had experienced spontaneous menstrual bleeding or amenorrhea for more than 3 months. Follicle-stimulating hormone (FSH), luteinizing hormone (LH), estradiol (E2), and testosterone (TT) levels were measured using a chemiluminescence immunoassay, and the HOMA-IR index was calculated using the following formula: HOMA-IR index = FPG (mmol/L) × FINS (μU/mL)/22.5.
The serum GPC4 and CLU levels were measured using enzyme-linked immunosorbent double-antibody assay, which was performed with GPC4 detection test kits (SEA998Hu, Cloud-Clone Company, Wuhan, China) and CLU detection test kits (SEB180Hu, Cloud-Clone Company), according to the manufacturers’ instructions. Both kits were validated prior to use, and the results of the validation tests are summarized below. With regard to specificity, the two test kits showed no significant cross reaction with other similar substances. The coefficient of variation (CV) of sample measurements was calculated as follows: CV (%) = s.d./mean × 100. To measure the intrabatch difference, we used reagent kits from the same batch for the quantitative testing of low-, medium-, and high-value fixed-value samples. Each sample was continuously tested 20 times, and the average and s.d. values of samples with different concentrations were calculated separately. The CV of the intrabatch difference was <10%. To analyze the interbatch difference, we selected reagent kits from three different batches for the quantitative determination of low-, medium-, and high-value fixed-value samples. Each sample was tested eight times using the same reagent kit, and the average and s.d. values of samples with different concentrations were calculated. The CV of the interbatch difference was <12%.
Statistical analysis
Statistical analysis was performed using SPSS® v25.0 software. Normally distributed measurement data were expressed as mean ± s.d. (x ± s.d.), and non-normally distributed measurement data were expressed as median and interquartile range (M (Q25 and Q75)). The independent-samples t-test was used for between-group comparisons of normally distributed continuous variables, while the Mann‒Whitney U test was used for variables that did not exhibit normal distribution. Binary logistic regression was used to analyze the relative risk of PCOS with different expression levels of serum GPC4 and CLU. Correlations between two variables were evaluated using Pearson correlation analysis (normal distribution) or Spearman’s correlation analysis (non-normal distribution). The multivariate stepwise linear regression method was used to analyze the factors influencing serum GPC4 and CLU levels in PCOS patients. P < 0.05 was considered statistically significant.
Results
Comparison of clinical parameters, laboratory results, and serum GPC4 and CLU levels between women with PCOS and healthy women
The clinical and laboratory parameters, and serum GPC4 and CLU levels in the study cohort are summarized in Table 1. The distributions of GPC4 and CLU concentrations in women with PCOS and healthy women are shown in Fig. 1A and B. Serum GPC4 and CLU levels were significantly higher in PCOS patients than in healthy women after adjustment for BMI (both P < 0.001).
(A) Comparison of serum GPC4 levels in patients with PCOS and healthy controls. (B) Comparison of serum CLU levels in patients with PCOS and healthy controls. Data are expressed as mean ± s.d. **P < 0.001. CLU, clusterin; GPC4, glypican 4; PCOS, polycystic ovary syndrome.
Citation: Endocrine Connections 13, 3; 10.1530/EC-23-0428
Clinical and laboratory parameters and serum GPC4 and CLU levels in PCOS patients and healthy women.
| Variable | Controls (n = 40) | PCOS (n = 40) | P |
|---|---|---|---|
| Age (years) | 27.5 ± 3.63 | 26.2 ± 4.69 | 0.170 |
| BMI (kg/m2) | 21.40 ± 1.76 | 24.03 ± 3.64 | 0.001a |
| FSH (mIU/mL) | 5.42 ± 1.39 | 5.27 ± 1.70 | 0.672 |
| LH (mIU/mL) | 4.95 (3.88–6.18) | 6.15 (4.38–9.18) | 0.012a |
| LH/FSH | 0.95 (0.72–1.13) | 1.22 (1.01–1.51) | <0.001a |
| E2 (pg/mL) | 51.52 (48.34–55.55) | 45.71 (35.13–62.70) | 0.068 |
| TT (ng/dL) | 25.01 (22.10–27.76) | 38.17 (31.73–51.10) | <0.001a |
| FPG (mmol/L) | 4.84 (4.46–5.08) | 5.73 (5.17–6.44) | <0.001a |
| FINS (μU/mL) | 8.68 (7.37–9.03) | 19.70 (12.97–29.93) | <0.001a |
| HOMA-IR | 1.82 (1.50–2.00) | 4.75 (3.57–8.69) | <0.001a |
| TC (mmol/L) | 3.86 (3.55–4.28) | 4.39 (4.06–5.24) | <0.001a |
| TG (mmol/L) | 0.82 (0.65–1.26) | 1.53 (1.19–2.20) | <0.001a |
| HDL-C (mmol/L) | 1.46 ± 0.27 | 1.17 ± 0.26 | <0.001a |
| LDL-C (mmol/L) | 2.21 (2.06–2.54) | 2.80 (2.52–3.44) | <0.001a |
| GPC4 (ng/mL) | 1.30 ± 0.61 | 1.82 ± 0.49 | <0.001a |
| CLU (μg/mL) | 228.59 ± 82.42 | 468.79 ± 92.85 | <0.001a |
aP < 0.05 was considered significant.
BMI, body mass index; CLU, clusterin; E2, estradiol; FINS, fasting insulin; FPG, fasting plasma glucose; FSH, follicle-stimulating hormone; GPC4, glypican 4; HDL-C, high-density lipoprotein cholesterol; HOMA-IR, homeostatic model assessment of insulin resistance; LDL-C, low-density lipoprotein cholesterol; LH, luteinizing hormone; PCOS, polycystic ovary syndrome; TC, total cholesterol; TG, triglyceride; TT, testosterone.
Comparison of the relative risk of PCOS at different serum GPC4 and CLU levels
All subjects were stratified into three tertiles according to their serum GPC4 level: T1 group (GPC4 < 1.29 ng/mL), T2 group (1.29 ≤ GPC4 < 1.80 ng/mL), and T3 group (GPC4 ≥ 1.80 ng/mL). The risk of PCOS was significantly higher in the T3 and T2 groups than in the T1 group (odds ratio (OR): 12.6, 95% CI: 3.443–46.107, P < 0.001; OR: 4.9, 95% CI: 1.413–16.988, P = 0.012, respectively) but did not differ between the T3 and T2 groups (OR: 2.571, 95% CI: 0.813–8.134, P = 0.108; Fig. 2A).
(A) Comparison of the relative risk of PCOS among women with different serum GPC4 levels. (B) Comparison of the relative risk of PCOS among women with different serum CLU levels. *P < 0.05 and **P < 0.001 compared to the lowest tertile. CLU, clusterin; GPC4, glypican 4; PCOS, polycystic ovary syndrome.
Citation: Endocrine Connections 13, 3; 10.1530/EC-23-0428
The study subjects were also stratified according to their serum CLU levels as follows: Q1 group (CLU < 257.65 µg/mL), Q2 group (257.65 ≤ CLU < 442.27 µg/mL), and Q3 group (CLU ≥ 442.27 µg/mL). The risk of PCOS was significantly higher in the Q3 and Q2 groups than in the Q1 group (OR: 625, 95% CI: 37.005–10556.023, P < 0.001; OR: 25, 95% CI: 2.966–210.717, P = 0.003, respectively). Additionally, the risk of PCOS was significantly higher in the highest tertile of CLU (Q3 group) than in the middle tertile (Q2 group, OR: 25, 95% CI: 2.966–210.717, P = 0.003; Fig. 2B).
Correlation of serum GPC4 and CLU levels with general data and clinical indicators
We next performed a correlation analysis of serum GPC4, serum CLU, and other variables. In the control group, the serum GPC4 level was positively correlated with BMI, E2 and FINS levels, and the HOMA-IR index (P < 0.05), while the serum CLU level was positively correlated with BMI, E2 and FPG levels, and the HOMA-IR index (P < 0.05). In the PCOS group, the serum GPC4 level was positively correlated with the FSH, FPG, FINS, and TG levels as well as the HOMA-IR index (P < 0.05), whereas the serum CLU level was positively correlated with BMI, the FPG and FINS levels, and the HOMA-IR index (P < 0.05; Table 2).
Correlation analysis of serum GPC4 and CLU levels with general data and clinical indicators.
| Variable | GPC4 | CLU | ||||||
|---|---|---|---|---|---|---|---|---|
| Controls | PCOS | Controls | PCOS | |||||
| r | P | r | P | r | P | r | P | |
| Age | −0.024 | 0.885 | −0.241 | 0.134 | −0.158 | 0.329 | 0.075 | 0.648 |
| BMI | 0.616 | <0.001* | 0.304 | 0.056 | 0.474 | 0.002* | 0.552 | <0.001* |
| FSH | 0.092 | 0.572 | 0.338 | 0.033* | 0.296 | 0.064 | 0.261 | 0.104 |
| LH | −0.052 | 0.750 | 0.123 | 0.449 | 0.271 | 0.091 | 0.258 | 0.108 |
| LH/FSH | −0.159 | 0.327 | −0.176 | 0.277 | −0.041 | 0.802 | −0.038 | 0.818 |
| E2 | 0.365 | 0.020* | −0.072 | 0.659 | 0.423 | 0.006* | −0.097 | 0.550 |
| TT | 0.244 | 0.128 | 0.139 | 0.393 | 0.051 | 0.753 | 0.201 | 0.213 |
| FPG | 0.254 | 0.114 | 0.384 | 0.014* | 0.373 | 0.018* | 0.363 | 0.021* |
| FINS | 0.325 | 0.041* | 0.729 | <0.001* | 0.281 | 0.078 | 0.639 | <0.001* |
| HOMA-IR | 0.360 | 0.023* | 0.706 | <0.001* | 0.384 | 0.015* | 0.639 | <0.001* |
| TC | 0.149 | 0.359 | 0.059 | 0.716 | 0.010 | 0.950 | 0.222 | 0.169 |
| TG | 0.106 | 0.514 | 0.372 | 0.018* | 0.165 | 0.310 | 0.211 | 0.191 |
| HDL-C | −0.115 | 0.481 | −0.247 | 0.124 | −0.307 | 0.054 | −0.078 | 0.635 |
| LDL-C | 0.204 | 0.206 | 0.138 | 0.396 | 0.191 | 0.238 | 0.295 | 0.065 |
| CLU | 0.493 | 0.001* | 0.493 | 0.001* | – | – | – | – |
*Indicates statistically significant differences at P < 0.05 or P < 0.001.
BMI, body mass index; CLU, clusterin; E2, estradiol; FINS, fasting insulin; FPG, fasting plasma glucose; FSH, follicle-stimulating hormone; GPC4, glypican 4; HDL-C, high-density lipoprotein cholesterol; HOMA-IR, homeostatic model assessment of insulin resistance; LDL-C, low-density lipoprotein cholesterol; LH, luteinizing hormone; PCOS, polycystic ovary syndrome; TC, total cholesterol; TG, triglyceride; TT, testosterone.
The natural logarithmic conversion of the HOMA-IR index conformed to a normal distribution, and the scatterplot indicated that LnHOMA-IR was significantly and linearly correlated with the serum GPC4 (r = 0.74, P < 0.001) and serum CLU (r = 0.589, P < 0.001) levels in PCOS patients (Fig. 3A and B).
(A) Scatterplot showing the correlation of serum GPC4 level and LnHOMA-IR in PCOS patients. (B) Scatterplot showing the correlation of serum CLU level and LnHOMA-IR in PCOS patients. HOMA-IR# indicates logarithmically converted HOMA-IR. CLU, clusterin; GPC4, glypican 4; HOMA-IR, homeostatic model assessment of insulin resistance; PCOS, polycystic ovary syndrome.
Citation: Endocrine Connections 13, 3; 10.1530/EC-23-0428
Multiple linear regression analysis of serum GPC4, serum CLU, and related factors in patients with PCOS
GPC4 was considered the dependent variable, and significant variables in the correlation analysis were included in the multivariate analysis. Because there exists a functional relationship among FINS, FPG, and HOMA-IR, only HOMA-IR, FSH, and TG were included as independent variables in the multiple stepwise linear regression analysis. The results showed that the HOMA-IR index was independently correlated with the serum GPC4 level in PCOS patients (P < 0.001; Table 3).
Multiple linear regression analysis of serum GPC4 and related factors in PCOS patients.
| Variable | B | s.e. | β | t | P | 95% CI |
|---|---|---|---|---|---|---|
| Constant | 1.367 | 0.093 | – | 14.698 | <0.001* | 1.179–1.556 |
| HOMA-IR | 0.067 | 0.011 | 0.699 | 6.028 | <0.001* | 0.044–0.089 |
*P < 0.05 was considered statistically significant.
GPC4, glypican 4; HOMA-IR, homeostatic model assessment of insulin resistance; PCOS, polycystic ovary syndrome.
In addition, with CLU as the dependent variable, meaningful variables in the correlation analysis were included in another multivariate analysis. Because FINS, FPG, and HOMA-IR are functionally related, only BMI and HOMA-IR were included as the independent variables. Multiple stepwise linear regression analysis showed that the BMI and HOMA-IR index were independently correlated with the serum CLU level in PCOS patients (P < 0.05 and P < 0.001, respectively; Table 4).
Multiple linear regression analysis of serum CLU and related factors in PCOS patients.
| Variable | B | S.E. | β | t | P | 95% CI |
|---|---|---|---|---|---|---|
| Constant | 257.575 | 66.460 | – | 3.876 | <0.001* | 122.788–392.361 |
| HOMA-IR | 7.774 | 2.082 | 0.500 | 3.733 | 0.001* | 3.551–11.998 |
| BMI | 6.873 | 2.948 | 0.312 | 2.331 | 0.025* | 0.893–12.853 |
*P < 0.05 was considered statistically significant.
BMI, body mass index; CLU, clusterin; HOMA-IR, homeostatic model assessment of insulin resistance; PCOS, polycystic ovary syndrome; SE, standard error.
Discussion
This study found that compared to healthy controls, PCOS patients had elevated serum GPC4 levels. GPC4 is an adipokine in the proteoglycan family that directly binds to insulin receptors and acts as an insulin-receptor sensitizer to enhance insulin signaling; GPC4 depletion weakens insulin-receptor phosphorylation and downstream signaling (13). The study subjects were divided into three groups according to the tertiles of serum GPC4 concentration. We found that the risk of PCOS was significantly higher in the two highest GPC4 tertiles (T3 and T2 groups) than that in the lowest GPC4 tertile (T1 group); however, no statistically significant difference in the risk of PCOS was observed between the T2 and T3 groups, indicating that the risk of PCOS development may be related to the serum GPC4 level. Correlation analysis showed that in the control group, serum GPC4 was positively correlated with BMI, E2, FINS, HOMA-IR, and CLU, while in the PCOS group, GPC4 was positively correlated with FSH, FPG, FINS, HOMA-IR, TG, and CLU. Further, linear regression analysis found that HOMA-IR was independently correlated with serum GPC4 level in PCOS patients, indicating that serum GPC4 may be a marker related to insulin resistance in PCOS patients. The results of the present study are consistent with those of previous studies. Jędrzejuk et al. (24) found that the serum GPC4 level is higher in PCOS patients than in healthy controls and is associated with risk factors for cardiovascular disease, such as BMI, waist circumference, WHR, FINS, HOMA-IR, and fat distribution. Similarly, Altinkaya et al. (25) reported that the serum GPC4 level is significantly higher in women with PCOS than in control subjects and is positively correlated with BMI, FPG, HOMA-IR, TG, and TT. The authors also reported that BMI is an independent influencing factor of GPC4. However, in the present study, BMI was not found to be correlated with serum GPC4 levels; this discrepancy may be due to population variability and small sample size.
Currently, the mechanism of action of GPC4 in metabolic regulation is not fully understood. Ussar et al. (13) speculated that the increase in GPC4 levels in pathological conditions may be a new regulatory mechanism through which fat counteracts insulin resistance, and maintaining high levels of serum GPC4 in patients with severe insulin resistance or diabetes may reduce insulin requirements. The authors also proposed that GPC4 may affect adipocyte differentiation and enhance insulin receptor signaling through Wnt signaling. However, few studies have investigated GPC4 in PCOS, and its mechanism of action has not been fully elucidated. More basic and prospective studies are needed to explore the relationship between GPC4 and PCOS in the future.
CLU is involved in a wide range of pathological and physiological processes, including cellular senescence, tumorigenesis, tumor development, complement regulation, sperm maturation, and lipid transport (26). In the present study, the serum CLU level of PCOS patients was significantly higher than that of healthy women. When the study subjects were grouped into tertiles according to the serum concentration of CLU, it was found that the relative risk of PCOS gradually increased with increasing tertiles of CLU concentration. Compared with the Q2 group, the Q3 group exhibited a significantly increased relative risk of PCOS. This indicated that the serum CLU level may be closely related to the relative risk of PCOS, and the higher the CLU level, the greater the relative risk of PCOS occurrence. In the control group, serum CLU was positively correlated with BMI, E2, FPG, HOMA-IR, and GPC4, while in women with PCOS, serum CLU was positively correlated with BMI, FPG, FINS, HOMA-IR, and GPC4. Stepwise linear regression analysis revealed that BMI and HOMA-IR were independently correlated with PCOS. The results of the present study are similar to those reported by Seo et al. (27), who found that serum CLU levels were elevated in 20 women with PCOS and were positively correlated with FINS, free fatty acids, and HOMA-IR, suggesting that CLU is a liver factor that regulates muscle glucose metabolism and insulin sensitivity.
It is currently believed that the mechanism of action of serum CLU in metabolic diseases may be through several pathways. First, CLU may be an anorexia-inducing factor, and the key factor through which the hypothalamus controls energy metabolism. Animal studies (28) have found that the administration of CLU to mice leads to anorexia, weight loss, and the activation of signal transduction-activated transcript-3. Conversely, the suppression of hypothalamic CLU increases food intake and body weight, which may lead to obesity. The mechanism of action may involve an increase in the sensitivity of hypothalamic leptin receptors through CLU binding to low-density lipoprotein receptor-related protein 2 (LRP2), which in turn promotes leptin signaling, resulting in reduced energy intake and increased energy consumption. Second, the gene and protein expressions of CLU in fat cells are upregulated in obese patients, and CLU inhibits insulin signaling after binding to LRP2 receptors in the liver, which promotes hepatic gluconeogenesis through the upregulation of glucokinase (GCK) and pyruvate kinase L/R (PKLR) as well as the downregulation of sterol regulatory element binding transcription factor 1 (SREBF1), thereby reducing apolipoprotein A1 expression and decreasing HDL-C levels, ultimately promoting the occurrence of fatty liver (29). Third, CLU acts as a chemoattractant for the directed migration of macrophages and stimulates the expression and secretion of chemotactic cytokines, such as tumor necrosis factor alpha, which allows CLU to act as a bridge between inflammation and tissue remodeling by recruiting immune cells (30). The present study found a significant independent positive correlation of serum CLU with HOMA-IR and BMI in PCOS patients, suggesting that CLU may play a key role in energy metabolism and insulin resistance. However, few studies have been conducted on CLU and PCOS, and the relationship between serum CLU and PCOS as well as its mechanism of action needs to be further explored.
Serum GPC4 and CLU are important adipocytokines, and the present study found that both are abnormally expressed in PCOS patients and that there is a certain correlation between the two. Both are independently and positively correlated with HOMA-IR. Collectively, these findings suggest that GPC4 and CLU jointly affect insulin sensitivity through different insulin-signaling pathways, indicating that they may be markers of insulin resistance in PCOS patients. The above findings imply that in PCOS patients with increased serum GPC4 and CLU levels, it may be necessary to monitor cardiovascular risk factors, such as glucose and lipid levels.
Our study is a cross-sectional observational study with a small sample size, and cannot ascertain causal relationships between serum GPC4, CLU, and PCOS. Future studies with larger sample sizes are needed. Moreover, in future studies, the relationship between these factors should be investigated by grouping subjects according to the phenotype of PCOS. Three distinct PCOS phenotypes have been identified based on the three main features of PCOS (according to the Rotterdam criteria): the classic phenotype, which is characterized by hyperandrogenism, chronic oligovulation or anovulation, and polycystic ovaries; the ovulatory phenotype characterized by hyperandrogenism and polycystic ovaries, and the normo-androgenic phenotype characterized by oligoanovulation and polycystic ovaries. Additionally, as insulin resistance is one of the pathogenic factors of PCOS, current recommendations for PCOS patients include the use of insulin sensitizers such as metformin and pioglitazone. These drugs can improve hyperinsulinemia, reduce androgen secretion, and promote ovulation, so prospective drug intervention studies can be conducted to compare changes in serum GPC4 and CLU levels after treatment with these medications.
In conclusion, serum GPC4 and CLU levels are significantly higher in PCOS patients than in healthy women. GPC4 and CLU may be markers associated with insulin resistance in women with PCOS.
Declaration of interest
The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the study reported.
Funding
This work was supported by a research grant from the Jiangxi Provincial Natural Science Foundation (20165BCB18019).
Availability of data
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
Ethics statement
The present study was reviewed and approved by the ethics committee of the Second Affiliated Hospital of Nanchang University. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.
Author contribution statement
ZC, QH, CL, XL, and SS researched the data. ZC completed the data analysis and wrote the manuscript. HZ contributed to the writing of the manuscript and discussion. JL directed the project, contributed to the discussion, and reviewed the manuscript.
Acknowledgement
We thank Medjaden Inc. for their assistance in the preparation of the manuscript.
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