Edited by: Sara Marchiani, University of Florence, Italy
Reviewed by: Natassia Rodrigo, The University of Sydney, Australia; Themistoklis Tzotzas, St. Luke’s Hospital, Greece
*Correspondence: Qianqian Chen,
†These authors have contributed equally to this work
This article was submitted to Obesity, a section of the journal Frontiers in Endocrinology
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Our study aimed to investigate if serum prolactin (PRL) levels associated with insulin resistance and beta-cell dysfunction in infertile patients with polycystic ovary syndrome (PCOS).
This was a retrospective cross-sectional study performed in the reproductive medicine center of the first affiliated hospital of Wenzhou Medical University. From January 2007 to August 2018, a total of 792 PCOS and 700 non-PCOS infertile women were included. All patients’ prolactin levels were in the normal range. PCOS was diagnosed according to the Rotterdam Criteria. Anthropometric parameters, blood pressure, serum prolactin levels, sex hormones, fasting lipids, fasting plasma glucose (FPG), fasting insulin (FINS) and hepatic biological parameters were measured in all subjects.
Serum prolactin levels in PCOS women were significantly decreased compared with levels in non-PCOS women after adjusting for age and BMI (
Low serum PRL levels within the normal range associates with a higher incidence of insulin resistance and beta-cell dysfunction in infertile women with PCOS.
Prolactin (PRL) is a multifunctional polypeptide that stimulates insulin secretion, beta-cell proliferation and survival (
It is reported that the role of PRL on glucose metabolism and insulin resistance depends on its circulating concentration. In the clinic, PRL improves glucose homeostasis by increasing beta-cell mass under certain conditions such as pregnancy, whereas excessive high PRL levels in serum indicate a high-risk of obesity and dysmetabolism, such as decreased insulin sensitivity, abnormal glucose tolerance or progressive insulin resistance (
Polycystic ovary syndrome (PCOS) is a prevalent endocrine and metabolic condition characterized by the disturbance of reproductive hormones, insulin resistance, abnormal glucose tolerance, hypertension and cardiovascular disease (
Thus, we analyzed the association between serum PRL levels and clinical parameters, such as waist circumference (WC), hip circumference (HC), luteinizing hormone (LH), triglyceride (TG), or the homeostasis model assessment of insulin resistance (HOMA-IR), in infertile PCOS patients by a retrospective cross-sectional study, to explore the status of PRL secretion and association with insulin resistance and beta-cell function.
The study was designed as a retrospective observational study of infertile women (792 with PCOS and 700 with tubal infertility) who were initially treated by IVF-ET and referred to the reproductive center, at the First Affiliated Hospital of Wenzhou Medical University during January 2007 to August 2018. All patients’ prolactin levels were in the normal range. The detection lower limit for PRL was 20 mIU/L and if serum PRL is over 530 mIU/L, it is considered to be hyperprolactinemia (
Patients with hormone therapy in three months, smoking, history of ovarian function damage by radiotherapy or chemotherapy, endometriosis, adenomyosis, thyroid disorders, liver disease, kidney disease, high blood pressure, pituitary microadenoma were excluded. Patients were also excluded if she had unexplained infertility, recurrent miscarriage or previous history of adverse pregnancy, congenital abnormalities such as chromosome aberration, congenital adrenal cortex hyperplasia, Cushing’s syndrome or testosterone-secreting tumors.
Fasting blood samples were collected between 9 to 11 am in the morning at least 2 h after wake-up and 8 h after fasting on day 2–5 of a menstrual cycle. The body height (m) and weight (kg), waist-circumference and hip-circumference were measured by experienced nurses according to standard protocols. Body mass index(BMI) was calculated as body weight in kilograms divided by body height in meters squared. Blood pressure was taken twice in an interval of 2 min after at least 10 min rest using a mercury sphygmomanometer.
The PRL, FSH, LH, T, and E2 levels in blood samples were measured using chemiluminescence assay on UniCel® DxI 800 Immunoassay System (Beckman Coulter, USA) with commercial kits according to manufacturer’s and supplier’s instructions. The FPG, TG, TC, LDL-C, HDL-C and hepatic function were measured by a Cobas 8000 modular analyzer kits, and FINS by a Cobas E602 automatic electrochemical luminescence analyzer according to manufacturer’s instructions.
BMI = Weight (kg)/Height (m2)
Waist-hip ratio = Waist circumference (cm)/Hip circumference (cm)
Waist-height ratio = Waist circumference (cm)/Height (cm)
HOMA-IR = Fasting blood-glucose (FPG, mmol/L) × Fasting insulin (FINS, mIU/L)/22.5
HOMA-β = 20 × Fasting insulin (FINS, mIU/L)/[Fasting blood-glucose (FPG, mmol/L) − 3.5] (%)
The normal range of prolactin levels: 70.81–566.46 mIU/L.
Parameters were not normally distributed and were therefore described using medians and quartiles. The rank sum test was used to compare differences between patients and controls. The correlation among variables was analyzed using the Spearman correlation analysis. Univariate logistic regression and multiple linear regression analysis were applied to reveal the association between prolactin and the index. All statistical analyses were performed using the SPSS version 22. P values < 0.05 were considered statistically significant.
Characteristics of 792 PCOS and 700 non-PCOS women are provided in
Clinical and biochemical data from PCOS and control patients.
Variables | PCOS (n = 792) | non-PCOS (n = 700) |
---|---|---|
Age | 29(27–32.5) | 31(28–35)** |
Systolic pressur (mmHg) | 116(106–126.5) | 109(103–117)** |
Diastolic pressure (mmHg) | 77(68–83) | 72(67–77)** |
BMI (kg/m2) | 23.73(21.48–26.85) | 21.64(19.53–23.88)** |
WC (cm) | 84(77–90.5) | 75(70–81)** |
HC (cm) | 94(90–101) | 90(86–96)* |
Waist–hip ratio | 0.88(0.85–0.91) | 0.83(0.79–0.87)** |
Basal serum PRL (mIU/L) | 235.74(186.85–318.03) | 275.13(213.60–355.84)* |
Basal serum LH (IU/L) | 9.09(6.26–13.44) | 4.65(3.48–5.98)** |
Basal serum FSH (IU/L) | 6.62(5.86–7.81) | 7.82(6.67–9.02)** |
LH/FSH | 1.37(0.89–1.96) | 0.59(0.42–0.77)** |
Basal serum E2 (pmol/L) | 180(113.5–238.5) | 182.5(134.5–238) |
Basal serum T (nmol/L) | 2.15(1.59–2.75) | 1.56(1.25–1.96)** |
FINS (pmol/L) | 82.9(50.35–112.30) | 52.75(37.6–75.6)** |
FPG (mmol/L) | 5.2(4.9–5.5) | 5.1(4.9–5.4) |
HOMA-IR | 2.74(1.75–3.76) | 1.74(1.22–2.55)** |
HOMA- β | 137.49(88.35–216.24) | 93.45(67.08–128.42)** |
TG (mmol/L) | 1.37(0.94–1.98) | 0.93(0.69–1.24)** |
TC (mmol/L) | 4.79(4.20–5.30) | 4.48(3.99–4.98)** |
LDL-C (mmol/L) | 2.74(2.31–3.28) | 2.49(2.10–2.92)** |
HDL-C (mmol/L) | 1.29(1.12–1.46) | 1.40(1.23–1.61)** |
AST (U/L) | 18(16–22.5) | 16(14–19)** |
ALT (U/L) | 21(15–28) | 14(11–20.5)** |
Parameters were not normally distributed and data are presented as quartiles. The rank sum test was used to compare differences between patients and controls.
*P < 0.05 versus controls, **P < 0.001 versus controls.
P < 0.05 versus controls after correcting for age and BMI.
P < 0.001 versus controls after correcting for age and BMI.
Clinical and biochemical data from PCOS according to quartiles of prolactin levels.
Variables | PRL ≤ 186.85 (n = 175) | 186.99–235.74 (n = 170) | 235.77–318.03 (n=232) | PRL>318.03 (n = 215) | P-value |
---|---|---|---|---|---|
Age | 31(28–34) | 28.5(27–31) | 29(27–31) | 27(26–31)** | 0.000 |
Systolic pressure (mmHg) | 121(110–128) | 113(98–124) | 117(106–127) | 115(106–12) | 0.369 |
Diastolic pressure (mmHg) | 78(68–83) | 73(62–84) | 77(70–81) | 78(70.5–83) | 0.841 |
BMI (kg/m2) | 26.13(22.83–27.89) | 23.38(21.63–24.848) | 22.86(20.45–25.81) | 22.58(20.50–24.68) | 0.095 |
WC (cm) | 90(82–95) | 82(74–88) | 80(73–88) | 81(78–86)** | 0.000 |
HC (cm) | 100(92–106) | 92.5(88–100) | 93(88–97) | 93(90–98)* | 0.001 |
Waist–hip ratio | 0.89(0.85–0.92) | 0.86(0.85–0.90) | 0.86(0.81–0.89) | 0.88(0.85–0.92) | 0.110 |
Basal serum PRL (mIU/L) | 137.11(107.06–155.76) | 209.20(195.42–227.58) | 275.91(265.71–287.79) | 396.28(353.25–472.53)** | 0.000 |
Basal serum LH (IU/L) | 9.61(7.08–14.28) | 9.83(6.21–13.94) | 8.57(5.02–11.34) | 9.0(6.07–12.03)* | 0.001 |
Basal serum FSH (IU/L) | 7.0(6.02–8.47) | 6.45(5.30–7.16) | 6.60(5.50–8.06) | 6.58(6.03–7.59) | 0.810 |
LH/FSH | 1.40(1.02–1.94) | 1.55(0.98–2.44) | 1.21(0.76–2.03) | 1.32(0.87–1.77)** | 0.000 |
Basal serum E2 (pmol/L) | 162(108–217) | 202(125–269) | 186(143–252) | 182(111–218.5) | 0.345 |
Basal serum T (nmol/L) | 2.17(1.64–2.67) | 2.17(1.66–2.86) | 2.15(1.72–3.02) | 1.91(1.35–2.69) | 0.074 |
FINS (pmol/L) | 91.6(65.3–138.1) | 87.1(50.9–145.4) | 72(41.3–98) | 81.6(52.3–91.25)* | 0.003 |
FPG (mmol/L) | 5.2(4.9–5.5) | 5.2(4.9–5.6) | 5.1(4.9–5.4) | 5.1(4.9–5.6) | 0.372 |
HOMA-IR | 2.81(1.3–4.19) | 2.39(1.59–3.78) | 2.33(1.25–3.87) | 2.20(1.02–3.34)* | 0.006 |
HOMA-β | 129.77(81.75–219.72) | 112.29(78.08–164.75) | 111.03(67.35–193.47) | 104.48(58.59–163.14)* | 0.001 |
TG (mmol/L) | 1.43(1.09–2.26) | 1.32(0.93–1.88) | 1.03(0.88–2.08) | 1.33(0.88–1.82)* | 0.017 |
TC (mmol/L) | 4.78(4.21–5.29) | 4.79(4.120–5.29) | 4.74(4.06–5.35) | 4.98(4.49–5.33) | 0.827 |
LDL-C (mmol/L) | 2.74(2.37–3.20) | 2.45(2.10–3.26) | 2.73(2.30–3.10) | 2.88(2.45–3.39) | 0.810 |
HDL-C (mmol/L) | 1.23(1.05–1.33) | 1.30(1.14–1.58) | 1.30(1.19–1.46) | 1.31(1.16–1.54)* | 0.005 |
AST (U/L) | 18(15–24) | 18(17–20) | 19(15–20) | 19(15.5–25.5) | 0.256 |
ALT (U/L) | 21(15–30) | 22(15–28) | 17(13–29) | 21 (15–26) | 0.123 |
Parameters were not normally distributed and data are presented as quartiles. The rank sum test was used to compare differences between patients and controls.
*P < 0.05 versus four groups, **P < 0.001 versus four groups.
Bivariate associations between prolactin and hormonal and metabolic variables in patients with PCOS.
Variables | R | P |
---|---|---|
Age | −0.123* | 0.001 |
Systolic pressure (mmHg) | −0.062 | 0.079 |
Diastolic pressure (mmHg) | −0.030 | 0.396 |
BMI (kg/m2) | −0.086* | 0.016 |
WC (cm) | −0.302** | 0.000 |
HC (cm) | −0.313** | 0.000 |
Waist–hip ratio | −0.074 | 0.356 |
Basal serum LH (IU/L) | −0.144** | 0.000 |
Basal serum FSH (IU/L) | 0.000 | 0.999 |
LH/FSH | −0.154** | 0.000 |
Basal serum E2 (pmol/L) | −0.071* | 0.047 |
Basal serum T (nmol/L) | −0.035 | 0.320 |
FINS (pmol/L) | −0.152** | 0.000 |
FPG (mmol/L) | 0.042 | 0.234 |
HOMA-IR | −0.144** | 0.000 |
HOMA-β | −0.165** | 0.000 |
TG (mmol/L) | −0.107* | 0.004 |
TC (mmol/L) | −0.014 | 0.702 |
HDL-C (mmol/L) | 0.084* | 0.025 |
LDL-C (mmol/L) | −0.027 | 0.463 |
AST (U/L) | −0.048 | 0.173 |
ALT (U/L) | −0.077* | 0.030 |
Data shown are Spearman’s rank correlation coefficients, *P < 0.05, **P < 0.001.
Regression analysis on the effect of prolactin upon hormonal and metabolic outcomes in patients with PCOS.
Variables | PRL | Age | BMI | R | R2 | Adjusted R2 |
---|---|---|---|---|---|---|
WC (cm) | −0.001 | 2.349 | 2.537 | 0.217 | 0.047 | 0.029 |
HC (cm) | −0.008 | −0.325* | 1.867** | 0.777 | 0.603 | 0.596 |
Basal serum LH (nmol/L) | −0.009** | −0.168* | −0.311** | 0.261 | 0.068 | 0.065 |
LH/FSH | −0.001** | −0.025* | −0.029** | 0.216 | 0.047 | 0.043 |
E2 (pmol/L) | −0.055* | 1.245 | −1.280 | 0.108 | 0.012 | 0.008 |
FINS (pmol/L) | −0.066* | −1.399 | 7.991** | 0.334 | 0.112 | 0.108 |
HOMA-IR (log10) | −0.102* | −0.033 | 0.293** | 0.210 | 0.044 | 0.041 |
HOMA-β | −0.121* | −2.877 | 11.709** | 0.302 | 0.091 | 0.088 |
TG (mmol/L) | 0.000 | 0.019 | 0.081** | 0.319 | 0.102 | 0.098 |
HDL-C (mmol/L) | 0.733 | −0.007* | −0.031** | 0.413 | 0.170 | 0.167 |
ALT (U/L) | −0.004 | −0.046 | 1.819** | 0.211 | 0.044 | 0.041 |
Multiple regression analyses were performed with metabolic and hormonal outcomes as dependent variables and prolactin, age, and BMI as explanatory variables.
Data are presented as B-values (P-levels): *P < 0.05, **P< 0.001.
Bivariate associations between prolactin and hormonal and metabolic variables in non-PCOS patients.
Variables | R | P |
---|---|---|
Age | −0.171** | 0.000 |
Systolic pressure (mmHg) | −0.025 | 0.505 |
Diastolic pressure (mmHg) | 0.004 | 0.916 |
BMI (kg/m2) | −0.130* | 0.001 |
WC (cm) | −0.099 | 0.059 |
HC (cm) | −0.007 | 0.894 |
Waist–hip ratio | −0.142* | 0.007 |
Basal serum LH (IU/L) | 0.094* | 0.013 |
Basal serum FSH (IU/L) | −0.040 | 0.292 |
LH/FSH | 0.120* | 0.001 |
Basal serum E2 (pmol/L) | 0.040 | 0.294 |
Basal serum T (nmol/L) | 0.076* | 0.046 |
FINS (pmol/L) | 0.018 | 0.018 |
FPG (mmol/L) | −0.012 | 0.752 |
HOMA-IR | 0.012 | 0.755 |
HOMA-β | 0.034 | 0.365 |
TG (mmol/L) | −0.053 | 0.177 |
TC (mmol/L) | −0.017 | 0.676 |
HDL-C (mmol/L) | 0.059 | 0.132 |
LDL-C (mmol/L) | −0.021 | 0.587 |
AST (U/L) | −0.063 | 0.100 |
ALT (U/L) | −0.065 | 0.177 |
Data shown are Spearman’s rank correlation coefficients, *P < 0.05, **P < 0.001.
Regression analysis on the effect of prolactin upon hormonal and metabolic outcomes in patients with non-PCOS.
Variables | PRL | Age | BMI | R | R2 | Adjusted R2 |
---|---|---|---|---|---|---|
Waist–hip ratio | −0.427 | −0.790 | 1.315 | 0.081 | 0.007 | −0.002 |
Basal serum LH (nmol/L) | −0.569 | −4.056** | −4.874** | 0.38 | 0.057 | 0.053 |
LH/FSH | −0.348 | −5.951** | −5.951** | 0.230 | 0.053 | 0.049 |
T (nmol/L) | 1.157 | −3.468* | 1.428 | 0.152 | 0.023 | 0.019 |
FPG (mmol/L) | −0.315 | 1.427 | 4.780** | 0.192 | 0.037 | 0.037 |
FINS (pmol/L) | 1.497 | −1.986 | 12.772** | 0.439 | 0.439 | 0.189 |
HOMA-IR(log10) | 1.319 | −1.483 | 12.514** | 0.430 | 0.185 | 0.182 |
HOMA-β | 0.945 | −2.221* | 9.423** | 0.343 | 0.118 | 0.114 |
Multiple regression analyses were performed with metabolic and hormonal outcomes as dependent variables and prolactin, age, and BMI as explanatory variables.
Data are presented as B-values (P-levels): *P < 0.05, **P< 0.001.
To the best of our knowledge, this is the first study to report the association between serum PRL levels within the normal range and insulin resistance and beta-cell dysfunction in infertile patients with PCOS. In the present study, we observed that serum PRL levels were correlated with insulin sensitivity and beta-cell function in infertile PCOS patients with normal PRL levels, through analysis of the association of PRL levels with WC/HC, glucose metabolism indexes, lipid metabolism indexes and sexual hormonal regulation indexes. Whereas the correlation between PRL levels and insulin sensitivity or beta-celll function was not observed in infertile non-PCOS patients with normal PRL levels. The consequences of PRL levels in PCOS patients showed a significant decline after excluding the influence of age and BMI (
As a clinical diagnostic standard of central obesity, WC reflects the addition of visceral and abdominal fat, which can predict obesity-related health risk and provide a key risk factor for metabolic syndrome (MS) involving the onset of insulin resistance (
Circulating PRL levels exert wide effects upon glucose metabolism. Previous studies showed that high PRL disrupted glucose homeostasis and led to metabolic abnormalities (
In the analysis of reproductive hormones, we found that serum PRL exhibited inverse associations with LH, LH/FSH and E2 levels, but was not directly correlated with either T or FSH levels. Excessive PRL reduces the secretion of FSH and LH
Furthermore, we found the PRL levels were also inversely associated with TG and positively associated with HDL-C. TG, TC and LDL-C were significantly higher in PCOS compared with non-PCOS women after correcting the influence of BMI. Thus, there is significant correlation between metabolic abnormalities and serum PRL. We suspect that lower prolactin levels within the normal range may lead to dyslipidemia. Additionally, the index of ALT and AST was higher in PCOS compared with non-PCOS patients (none exhibited hepatitis or liver dysfunction), after controlling for BMI, and PRL was inversely associated with ALT. Hence, low PRL levels within the normal range may have association with higher prevalence of liver damage in PCOS. A recent clinical study into the role of PRL in the development of non-alcoholic fatty liver disease (NAFLED) suggested that there was a negative association between PRL and the presence of NAFLED. Lower PRL levels were found in patients with severe hepatic steatosis compared with those displaying mild and moderate hepatic steatosis (
With regard to the research methods, some limitations need to be acknowledged. For instance, we cannot draw causality from simple correlations in a retrospective study. Prospective studies are needed to testify their correlation, and future research will allow a more detailed investigation of all parameters such as glucose tolerance testing, insulin releasing test or abdominal ultrasonography. In addition, considering that the secretion of PRL is pulsatile and follows a circadian rhythm with the highest plasma concentration reached during sleep, and the lowest observed in the morning about 2–3 h after waking up (
Our clinical study lend support to the assumption that serum PRL levels within the normal range associates with glucose metabolism changes in infertile women with PCOS, suggesting that PRL may be a sensitive marker to predict insulin resistance and dysfunction of beta-cells. Further studies are warranted to confirm this association.
All relevant data are contained within the article: the original contributions presented in the study are included in the article. Further inquiries can be directed to the corresponding authors.
The studies involving human participants were reviewed and approved by The Ethics Committee of The First Affiliated Hospital of Wenzhou Medical University. The patients/participants provided their written informed consent to participate in this study.
HY contributed to the conception, data analysis, and draft writing. JL was involved in the acquisition of data. ZL was involved in the execution. HL provided suggestions on the study design. XC contributed to the conception and design of study. QC contributed to conception and study design and revised the article. All authors contributed to the article and approved the submitted version.
This work was supported by the National Natural Science Foundation of China (No. 81901551).
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Address all correspondence and requests for reprints: QC, MD, Reproductive Medicine Center, The First Affiliated Hospital of Wenzhou Medical University, No.96 Fuxue Road, Wenzhou 325000, People’s Republic of China; Telephone number: +86-13695885092; Fax number: +86-0577-88069786; Email: chancy1031@163.com.
PRL, Prolactin; PCOS, Polycystic ovary syndrome; FPG, Fasting plasma glucose; FINS, Fasting insulin; HDL-C, High-density lipoprotein cholesterol; LDL-C, Low density lipoprotein-cholesterol; WC, Waist circumference; HC, Hip circumference; LH, Luteinizing hormone; FSH, Follicle stimulating hormone; E2, Estradiol; HOMA-IR, Homeostasis model assessment of insulin resistance; HOMA-β, Homeostasis model assessment of β; TC, Total cholesterol TG, Triglyceride; ALT, Alanine aminotransferase; HPL, Hyperprolactinemia; MS, Metabolic syndrome; T2D, Type 2 diabetes; GnRH, Gonadotrophin-releasing hormone; NAFLED, Non-alcoholic fatty liver disease.